Oxford Handbook of Eating Disorders [2 ed.] 9780190620998, 0190620994

Table of contents :
Cover
Half title
Series
The Oxford Handbook of Eating Disorders
Copyright
Short Contents
About The Editors
Contributors
Contents
Introduction
Part One Phenomenology and Epidemiology
1. The Classification of Eating Disorders
2. Research Domain Criteria: The Impact of RDoC on the Conceptualization of Eating Disorders
3. Epidemiology and Course of Eating Disorders
Part Two Approaches to Understanding the Eating Disorders
4. Appetitive Regulation in Anorexia Nervosa and Bulimia Nervosa
5. Genetic Influences on Eating Disorders
6. Psychosocial Risk Factors for Eating Disorders
7. Dieting and the Eating Disorders
8. Mood, Emotions, and Eating Disorders
9. Cultural Influences on Body Image and Eating Disorders
Part Three Assessment and Comorbidities of the Eating Disorders
10. Psychological Assessment of the Eating Disorders
11. Medical Complications of Anorexia Nervosa and Bulimia Nervosa
12. Psychological Comorbidities of Eating Disorders
Part Four Prevention and Treatment
13. Prevention: Current Status and Underlying Theory
14. Cognitive-Behavioral Therapy for Eating Disorders
15. Interpersonal Psychotherapy for the Treatment of Eating Disorders
16. Family Therapy for Eating Disorders
17. Dialectical Behavior Therapy and Emotion-Focused Therapies for Eating Disorders
18. Self-​Help and Stepped Care Treatments for Eating Disorders
19. Pharmacotherapy for Eating Disorders
20. Cognitive Remediation Therapy for Eating Disorders
21. Costs and Cost-​Effectiveness in Eating Disorders
Part Five Emerging Topics
22. Selective Eating: Normative Developmental Phase or Clinical Condition?
23. Emerging Syndromes
24. Eating Disorders and Problematic Eating Behaviors After Bariatric Surgery
25. Virtual Reality: Applications to Eating Disorders
26. Mobile Device Applications for the Assessment and Treatment of Eating Disorders
27. Internet-​Based Interventions for Eating Disorders
Afterword
Index

Citation preview

The Oxford Handbook of Eating Disorders

OX F O R D L I B R A RY O F P S YC H O LO G Y

Area Editors Clinical Psychology David H. Barlow Cognitive Neuroscience Kevin N. Ochsner and Stephen M. Kosslyn Cognitive Psychology Daniel Reisberg Counseling Psychology Elizabeth M. Altmaier and Jo-​Ida C. Hansen Developmental Psychology Philip David Zelazo Health Psychology Howard S. Friedman History of Psychology David B. Baker Methods and Measurement Todd D. Little Neuropsychology Kenneth M. Adams Organizational Psychology Steve W. J. Kozlowski Personality and Social Psychology Kay Deaux and Mark Snyder

OXFORD

LIBRARY

OF

PSYCHOLOGY

The Oxford Handbook of Eating Disorders Second Edition Edited by W. Stewart Agras Athena Robinson

1

1 Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and certain other countries. Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America. © Oxford University Press 2018 First Edition published in 2010 Second Edition published in 2018 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by license, or under terms agreed with the appropriate reproduction rights organization. Inquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above. You must not circulate this work in any other form and you must impose this same condition on any acquirer. Library of Congress Cataloging-​in-​Publication Data Names: Agras, W. Stewart, editor. | Robinson, Athena Hagler, editor. Title: The Oxford handbook of eating disorders / edited by W. Stewart Agras and Athena Robinson. Description: Second edition. | Oxford ; New York : Oxford University Press, [2018] | Series: Oxford library of psychology | Includes bibliographical references and index. Identifiers: LCCN 2017044310 (print) | LCCN 2017044448 (ebook) | ISBN 9780190621018 (updf ) | ISBN 9780190662721 (epub) | ISBN 9780190620998 Subjects: LCSH: Eating disorders. Classification: LCC RC552.E18 (ebook) | LCC RC552.E18 O97 2018 (print) | DDC 616.85/26—dc23 LC record available at https://lccn.loc.gov/2017044310 9 8 7 6 5 4 3 2 1 Printed by Sheridan Books, Inc., United States of America

S H O RT CO N T E N T S

About the Editors  vii Contributors ix Contents xiii Chapters 1–524 Index 525

v

A B O U T T H E   E D I TO R S

W. Stewart Agras W. Stewart Agras, MD, is professor emeritus in the Department of Psychiatry and Behavioral Sciences at Stanford University. He was editor of the Journal of Applied Behavior Analysis and the Annals of Behavioral Medicine and president of the Association for Behavioral and Cognitive Therapies and the Society of Behavioral Medicine. He has been working in the field of eating disorders for the past 30 years, focusing on the treatment of anorexia nervosa, bulimia nervosa, and binge eating disorder, and continues an active research program at Stanford.

Athena Robinson Athena Robinson, PhD, is a clinical associate professor in the Department of Psychiatry and Behavioral Sciences at Stanford University’s School of Medicine. Her core areas of programmatic research include treatment outcome and implementation of evidence based treatments for eating disorders. She is an attending faculty member in Stanford’s Eating Disorders Clinic and Dialectical Behavior Therapy Program, and is the clinic’s liaison with Stanford campus, including Student Health Services and Athletics. She teaches and supervises graduate students and postdoctoral fellows.

vii

CO N T R I B U TO R S

W. Stewart Agras Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA Kelly C. Allison Department of Psychiatry Perelman School of Medicine at the University of Pennsylvania Philadelphia, PA Drew A. Anderson Department of Psychology SUNY at Albany Albany, NY Eileen Anderson-​Fye Department of Bioethics Case Western Reserve University Cleveland, OH Courtney Arena Department of Psychology and Neuroscience Duke University Durham, NC Cara Bohon Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA Cynthia M. Bulik Department of Psychiatry School of Medicine University of North Carolina Chapel Hill, NC Natasha L. Burke Department of Medical and Clinical Psychology Uniformed Services University of Health Sciences Bethesda, MD

Eunice Y. Chen Department of Psychology Temple University Philadelphia, PA Ross Crosby Neuropsychiatric Research Institute Department of Clinical Neuroscience University of North Dakota School of Medicine and Health Sciences Fargo, ND Scott J. Crow Department of Psychiatry University of Minnesota School of Medicine Minneapolis, MN Cortney Dable Department of Psychology and Neuroscience Duke University Durham, NC Antonios Dakanalis Department of Brain and Behavioral Sciences University of Pavia Pavia, Italy Alison M. Darcy Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA Martina de Zwann Clinic for Psychosomatics and Psychotherapy Hannover Medical School Hannover, Germany Joseph Donahue Department of Psychology SUNY at Albany Albany, NY

ix

Valerie J. Douglas Neuropsychiatric Research Institute Department of Clinical Neuroscience University of North Dakota School of Medicine and Health Sciences Fargo, ND Alice V. Ely Department of Psychiatry University of California, San Diego La Jolla, CA Lauren E. Ehrlich Department of Psychology SUNY at Albany Albany, NY Marta Ferrer-​García Department of Clinical Psychology and Psychobiology University of Barcelona Spain Eike Fittig Institut fur Klinische Psychologie und Psychotherapie Technische University Dresden Dresden, Germany Ellen E. Fitzsimmons-​Craft Department of Psychiatry Washington University School of Medicine St. Louis, MO E. Leigh Gibson Clinical and Health Psychology Research Center Department of Psychology University of Roehampton London, UK Neha J. Goel Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA Kathryn H. Gordon Neuropsychiatric Research Institute Department of Clinical Neuroscience University of North Dakota School of Medicine and Health Sciences Fargo, ND

x

Contributors

Sasha Gorrell Department of Psychology SUNY at Albany Albany, NY Anna I. Guerdjikova Lindner Center of HOPE, Mason, OH Department of Psychiatry & Behavioral Neuroscience University of Cincinnati College of Medicine Cincinnati, OH José Gutiérrez-​Maldonado Department of Clinical Psychology and Psychobiology University of Barcelona Spain Katherine A. Halmi Department of Psychiatry Weill Cornell Medical College Cornell University White Plains, NY Amy Harrison University College London London, UK Caroline E. Haut Department of Psychiatry University of Minnesota Minneapolis, MN Anja Hilbert Department of Medical Psychology and Medical Sociology University of Leipzig Medical Center Leipzig, Germany Jasmine Hill Department of Psychology and Neuroscience Duke University Durham, NC Jill L. Holm-​Denoma Department of Psychology University of Denver Denver, CO Caroline Hubble Department of Psychology and Neuroscience Duke University Durham, NC

Kristian Hütter Institut fur Klinische Psychologie und Psychotherapie Technische University Dresden Dresden, Germany Corinna Jacobi Institut fur Klinische Psychologie und Psychotherapie Technische University Dresden Dresden, Germany Anna M. Karam Department of Psychiatry Washington University School of Medicine St. Louis, MO Walter H. Kaye Department of Psychiatry University of California, San Diego La Jolla, CA Paul E. Keck Jr. Department of Psychiatry University of Cincinnati College of Medicine Cincinnati, OH Pamela K. Keel Department of Psychology Florida State University Tallahassee, FL Daniel Le Grange Department of Psychiatry University of California, San Francisco San Francisco, CA Jennifer D. Lundgren Department of Psychology University of Missouri, Kansas City Kansas City, MO Annika P. C. Lutz Universite du Luxembourg Luxembourg Susan L. McElroy Lindner Center of HOPE, Mason, OH Department of Psychiatry & Behavioral Neuroscience University of Cincinnati College of Medicine Cincinnati, OH Philip S. Mehler University of Colorado Denver, CO

James E. Mitchell Neuropsychiatric Research Institute Fargo, ND Nicole Mori Lindner Center of HOPE, Mason, OH Department of Psychiatry & Behavioral Neuroscience University of Cincinnati College of Medicine Cincinnati, OH Lisa Opitz Department of Medical Psychology and Medical Sociology University of Leipzig Medical Center Leipzig, Germany Molly Orcutt Neuropsychiatric Research Institute Fargo, ND Carol B. Peterson Department of Psychiatry University of Minnesota Minneapolis, MN Emily M. Pisetsky Department of Psychiatry University of Minnesota Minneapolis, MN Renne Rienecke Department of Pediatrics and Department of Psychiatry and Behavioral Sciences Medical University of South Carolina Charleston, SC Department of Psychiatry University of Michigan Ann Arbor, MI Giuseppe Riva Centro Studi e Ricerche di Psicologia della Comunicazione Università Cattolica del Sacro Cuore Milan, Italy Athena Robinson Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA

Contributors

xi

Shiri Sadeh-​Sharvit Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA Debra L. Safer Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA Heather Shaw Oregon Research Institute Eugene, OR Emilie Sohl Department of Psychology and Neuroscience Duke University Durham, NC Kristine Steffen Neuropsychiatric Research Institute Fargo, ND Eric Stice Oregon Research Institute Eugene, OR Marian Tanofsky-​Kraff Department of Medical and Clinical Psychology Uniformed Services University of the Health Sciences Bethesda, MD C. Barr Taylor Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA Claus Vögele Institute for Health and Behaviour University of Luxembourg Luxembourg

xii

Contributors

Tracy D. Wade Department of Psychology Flinders University Adelaide, South Australia Denise E. Wilfley Department of Psychiatry Washington University School of Medicine St. Louis, MO G. Terence Wilson Graduate School of Applied and Professional Psychology Rutgers University Piscataway, NJ Stephen A. Wonderlich Neuropsychiatric Research Institute Department of Clinical Neuroscience University of North Dakota School of Medicine and Health Sciences Fargo, ND Angelina Yiu Department of Psychology Temple University Philadelphia, PA Jee Yoon Department of Psychology and Neuroscience Duke University Durham, NC Nancy Zucker Department of Psychiatry and Behavioral Sciences Duke University Durham, NC

CONTENTS

Introduction 1 W. Stewart Agras and Athena Robinson

Part One 

• Phenomenology

and Epidemiology 

1. The Classification of Eating Disorders  9 Kathryn H. Gordon, Jill M. Holm-​Denoma, Valerie J. Douglas, Ross Crosby, and Stephen A. Wonderlich 2. Research Domain Criteria: The Impact of RDoC on the Conceptualization of Eating Disorders  24 Cara Bohon 3. Epidemiology and Course of Eating Disorders  34 Pamela K. Keel

Part Two 

• Approaches

Disorders 

to Understanding the Eating

4. Appetitive Regulation in Anorexia Nervosa and Bulimia Nervosa  47 Alice V. Ely and Walter H. Kaye 5. Genetic Influences on Eating Disorders  80 Tracy D. Wade and Cynthia M. Bulik 6. Psychosocial Risk Factors for Eating Disorders  106 Corinna Jacobi, Kristian Hütter, and Eike Fittig 7. Dieting and the Eating Disorders  126 Eric Stice and Heather Shaw 8. Mood, Emotions, and Eating Disorders  155 Claus Vögele, Annika P. C. Lutz, and E. Leigh Gibson 9. Cultural Influences on Body Image and Eating Disorders  187 Eileen P. Anderson-Fye

Part Three 

• Assessment

Disorders 

and Comorbidities of the Eating

10. Psychological Assessment of the Eating Disorders  211 Drew A. Anderson, Joseph Donahue, Lauren E. Ehrlich, and Sasha Gorrell 11. Medical Complications of Anorexia Nervosa and Bulimia Nervosa  222 Philip S. Mehler 12. Psychological Comorbidities of Eating Disorders  229 Katherine A. Halmi

xiii

Part Four 

• Prevention

and Treatment 

13. Prevention: Current Status and Underlying Theory  247 C. Barr Taylor, Ellen E. Fitzsimmons-​Craft, and Neha J. Goel 14. Cognitive-Behavioral Therapy for Eating Disorders  271 G. Terence Wilson 15. Interpersonal Psychotherapy for the Treatment of Eating Disorders  287 Natasha L. Burke, Anna M. Karam, Marian Tanofsky-​Kraff, and Denise E. Wilfley 16. Family Therapy for Eating Disorders  319 Daniel Le Grange and Renne Rienecke 17. Dialectical Behavior Therapy and Emotion-Focused Therapies for Eating Disorders  334 Eunice Y. Chen, Angelina Yiu, and Debra L. Safer 18. Self-​Help and Stepped Care Treatments for Eating Disorders  351 Carol B. Peterson, Emily M. Pisetsky, and Caroline E. Haut 19. Pharmacotherapy for Eating Disorders  359 Susan L. McElroy, Anna I. Guerdjikova, Nicole Mori, and Paul E. Keck Jr. 20. Cognitive Remediation Therapy for Eating Disorders  395 Amy Harrison 21. Costs and Cost-​Effectiveness in Eating Disorders  410 Scott J. Crow

Part Five 

• Emerging

Topics 

22. Selective Eating: Normative Developmental Phase or Clinical Condition?  419 Nancy Zucker, Courtney Arena, Cortney Dable, Jasmine Hill, Caroline Hubble, Emilie Sohl, and Jee Yoon 23. Emerging Syndromes  438 Kelly C. Allison and Jennifer D. Lundgren 24. Eating Disorders and Problematic Eating Behaviors After Bariatric Surgery  458 Molly Orcutt, Kristine Steffen, and James E. Mitchell 25. Virtual Reality: Applications to Eating Disorders  470 José Gutiérrez-​Maldonado, Marta Ferrer-​García, Antonios Dakanalis, and Giuseppe Riva 26. Mobile Device Applications for the Assessment and Treatment of Eating Disorders  492 Alison M. Darcy and Shiri Sadeh-​Sharvit 27. Internet-​Based Interventions for Eating Disorders  505 Anja Hilbert, Lisa Opitz, and Martina de Zwann Afterword  520 W. Stewart Agras and Athena Robinson Index  525

xiv

Contents

Introduction

W. Stewart Agras and Athena Robinson

Abstract This chapter provides a brief introduction to and overview of the contents of the Handbook. Several issues are highlighted, including changes since the previous edition of this volume, namely, the revised Diagnostic and Statistical Manual (DSM-​5); the research domain criteria (RDoC), and recent technological innovations such as Internet treatment and the use of virtual reality related to eating disorders. Chapters on selective eating, bariatric surgery, and cognitive remediation have also been added. Themes carried forward from the previous edition of the Handbook are presented in updated chapters reviewing etiological, maintenance, assessment, comorbidity, medical complications, and pharmacotherapy, as well as evidence-​based prevention and treatment considerations. Key Words:  classification, diagnosis, eating disorder, history, overview, treatment, technology

Introduction

This book is divided into five sections: phenomenology and epidemiology of the eating disorders; approaches to understanding the disorders; assessment and comorbidities of the disorders; prevention and treatment; and emerging topics. The first section deals with classification and epidemiology of the disorders, together with a consideration of the effect of the impact of the new research domain criteria (RDoC) promoted by the National Institute of Mental Health, on the conceptualization of the eating disorders. The second section describes research basic to understanding the eating disorders including biological, psychosocial risk factors, dieting, and mood in the genesis of eating disorders. The third section describes assessment of the eating disorders, medical and psychological comorbidities, and medical management. The fourth section deals with prevention and treatment of the eating disorders including psychotherapeutic and psychopharmacologic approaches and a consideration of the cost-​ effectiveness of existing treatments. The final section contains chapters on emerging topics such as selective eating, a childhood problem that

extends into adult life, eating disorders in relation to bariatric surgery and the use of technology in treatment and assessment.

History of the Eating Disorders

Whether the eating disorders have historical continuity has been much debated (Habermas, 2005; Keel & Klump, 2003). Unfortunately, the historical record does not provide sufficiently detailed case descriptions to enable certain diagnosis. It is clear that self-​starvation and self-​induced vomiting, combined with asceticism and religious preoccupations apparently driving these symptoms, were present in medieval times (Bynum, 1987; Harrison, 2003), as well as cases of binge eating, often on strange foods, which is probably why they were recorded. Opinion is divided as to whether such individuals would meet present-​day diagnostic criteria for an eating disorder or whether true eating disorder syndromes emerged only in the 19th and 20th centuries when detailed case histories became available (Habermas, 2005). Given the biological underpinnings of the eating disorders, for example, heritability, two explanations come to mind: First, eating disorders 1

such as anorexia nervosa (AN) and bulimia nervosa (BN) may have been present throughout the centuries but the historical record is insufficient to fully confirm this possibility. Second, cultural conditions changed at some point, interacting with the genetic component, to produce full-​fledged eating disorder syndromes. One possible cultural change is the focus on weight and shape together with attempts to alter these features that became increasingly common in young women from the mid-​19th century onward (Habermas, 2005). Hence, there are good descriptions of AN beginning in the mid-​19th century (Gull, 1874) although BN was first described in detail much later (Russell, 1979) and BED, a provisional diagnosis in DSM-​IV, only became a full disorder in DSM-​5. Moreover, the impetus for research in BN was the increase in cases seen in North American clinics in the mid-​1970s. Systematic study of the eating disorders began in the last third of the 20th century, although AN had been described in the 19th century and various treatments for that disorder were tried, none of them particularly successful, during the next 100 years. Since the 1970s research into the eating disorders has grown exponentially. The first issue of the International Journal of Eating Disorders, the premier journal in the field, appeared in the fall of 1981, encouraging further research and other journals including Eating Behaviors; Eating: The Journal of Treatment and Prevention; Eating and Weight Disorders; Journal of Eating Disorders; and the European Eating Disorders Review have followed. As the field is now maturing, the purpose of this volume is to update the state of treatment and research. The relatively recent recognition of the eating disorders means that research has lagged behind that of more established fields such as depression and anxiety disorders. For example, research on treatment of BN only began in the late 1970s with both pharmacologic and psychotherapeutic studies (Fairburn, 1981; Pope & Hudson, 1982; Schneider & Agras, 1985; Wermuth, Davis, Hollister, & Stunkard, 1977).

Recent Changes

Three important events have occurred between the editions of this volume. First, DSM-​ 5 was published. Second, the research domain criteria (RDoC) were defined. Third, the use of technology in the assessment and treatment of eating disorders has increased. In DSM-​5 “Binge Eating Disorder” was moved from a provisional to a full 2

Introduction

disorder, the criteria for the diagnoses of BN and BED were loosened, and amenorrhea was removed as a criterion for AN. The RDoC are aimed at correcting the problem that research to date has failed to produce enough knowledge about psychopathologic processes useful for the prevention and treatment of mental disorders. One reason for this is that the diagnoses emanating from clinician consensus described in the DSM may not represent actual entities, hence approaches to understanding these “disorders” have little chance of discovering useful psychopathologic processes. The RDoC approach aims to uncouple DSM diagnoses from research questions and to consider domains that may stretch across the disorders classified in the DSM. This radical approach has spurred a great deal of discussion and some dissent. The third change is in the use of technologic advances that have led to the development of Internet-​based treatment for the eating disorders together with mobile applications (apps) as aids to therapy allowing for improved self-​ monitoring. Other advances such as the use of virtual reality for assessment and treatment of some aspects of the eating disorders are also examined. Each of these changes is likely to alter our perception and understanding of the eating disorders and their treatment in the years to come.

The Eating Disorders: Boundary Problems

One problem in classifying the eating disorders is that the disorders tend to merge over time. For example, it is not uncommon for patients with AN to begin to binge eat and purge, thus meeting criteria for BN when they no longer meet weight criteria for AN. Indeed, about 25% of participants with BN in treatment trials had been diagnosed with AN in the past (Agras, Walsh, Fairburn, Wilson, & Kraemer, 2000; Fairburn & Cooper, 2011). Such individuals tend to have worse treatment outcomes than those who have not had past AN, suggesting that the psychopathologic processes active in AN continue to affect outcome. To a lesser extent, there is crossover between BN and BED. When there is a shift between syndromes, the question arises: Should the diagnosis change or should it remain in the previous diagnostic grouping? Although there is considerable controversy over this point, it would seem sensible to preserve the original diagnosis rather than assuming, as a diagnostic change does, that there has been recovery from one syndrome and development of a new one. More problematic again is the fact that the residual grouping EDNOS, from DSM-​IV, was the most common ED diagnosis (Fairburn & Cooper,

2011; Vo, Accurso, Goldschmidt, & Le Grange, 2016). This group was largely composed of subclinical variants of AN, BN, and BED, often with mixed symptoms together with more tentatively identified entities such as (self-​ induced) vomiting disorder and night eating syndrome. Loosening the binge eating (and purging) criteria and the introduction of the category Other Specified Feeding and Eating Disorder (OSFED) in DSM-​5 is expected to reduce the number of EDNOS-​type cases that would have been seen in DSM-​IV (Machado, Goncalves, & Hoek, 2012). A further boundary problem is the relationship of the eating disorders to overweight and obesity. Here, the boundary between BED and obesity is the most complex because a substantial proportion of those with BED are also overweight or obese. A  family study helped to clarify the relationship between these two disorders (Hudson et al., 2006). The authors found an aggregation of BED within families, probably due to interacting genetic and environmental variables. In addition, relatives of those with BED had a markedly higher prevalence of severe obesity than relatives of those without BED. These findings suggest that BED is a familial disorder caused by factors distinct from those that cause obesity, and that these BED-​specific family factors also increase the risk of severe obesity. Hence obesity may be conceptualized as an entity separate from BED although BED is a risk factor for the development of obesity, especially severe obesity.

Family and Genetic Studies

Family and twin studies suggest that the eating disorders are heritable, with familial and environmental factors specific to individuals (nonshared environment) interacting with genes to produce disorders. The estimated contributions of genetic and nonshared environmental variables differ considerably from study to study, hence the relative contribution of genes and environment to the eating disorders is unclear. Moreover, epigenetic factors (the influence of environment on gene expression) provide a pathway for the effects of early life stressors. Whether or not genetic studies will provide useful leads for treatment is debatable, given the complexity of eating and its disorders. Following the path that other psychiatric disorders pioneered, it is now recognized that the acquisition and analysis of large well-​specified samples, including eating disorders and eating disorder symptoms is needed.

Risk Factors and Prevention of Eating Disorders

Risk factors can be ascertained, usually after preliminary studies finding associations either retrospectively or concurrently between a disorder and particular variables, in two main ways. First a risk factor can be identified from prospective studies. Second, a causal risk factor can be identified experimentally by altering the strength of the risk factor and ascertaining the effect of such alteration on the occurrence of the disorder or an important component of the disorder. The most difficult ED to study is AN, because the incidence of this disorder is relatively low, requiring very large-​scale prospective population studies to identify sufficient cases and the putative risk factors. However, our knowledge of risk factors for BN and to a lesser extent for BED has developed mainly by means of prospective studies with a few experimental studies aimed at identifying causal risk factors. Knowledge of risk factors is crucial to the development of effective prevention programs. Among the factors that form the basis for a number of prevention studies in adolescents and young women are an elevated perceived pressure to be thin emanating from family, peers, and the media; internalization of the thin-​ideal espoused for women by Western culture; and elevated body mass index and body dissatisfaction coupled with dieting. These risk factors have predicted eating pathology in a number of prospective studies. Prevention studies now constitute a promising research field with some notable successes. Importantly, many prevention programs can make use of media and the Internet to deliver the intervention, thus reducing cost and providing easy access to the programs. Interestingly, there is mixed evidence that dieting is a risk factor for BN and BED despite the fact that it is universally regarded as a risk factor. Specifically, while some prospective studies show increases in binge eating and bulimic symptoms post dietary restraint, some experimental studies show that dietary restriction can reduce binge eating and bulimic symptoms. It may be that a third variable elicited by the assessment of dieting may be a risk factor although it is unclear what that factor might be.

Treatment of the Eating Disorders

The relatively low prevalence of AN combined with the reluctance of many patients with the disorder to seek or follow through with treatment makes treatment research for this disorder difficult. Agras, Robinson

3

Many of the controlled studies that have been completed have sample sizes too small to allow conclusions about the effectiveness of treatment to be made. Hence, at this time there are no first-​line evidence-​ based pharmacological or psychotherapeutic treatments available for persistent AN. This is disappointing, given the fact that of all the eating disorders AN has the longest history, even in modern times. The most promising treatment at this time is a family-​based approach for adolescents first developed at the Maudsley Hospital in London, UK (Agras, et  al., 2014; Lock, Agras, Bryson, & Kraemer, 2005). This treatment is now supported by a number of controlled studies demonstrating that for adolescents it is more effective than individual therapy and a generic family therapy, hence it can be regarded as a first-​line evidence-​based treatment. Moreover, early treatment may reduce the number of persistent cases. The situation is somewhat better for BN with a number of well-​designed studies comparing various treatments. Although only fluoxetine is FDA approved for use in BN, most antidepressants have been shown to be effective in reducing binge eating and purging (Hay, 2013; McElroy, Guerdjikova, Mori, & Keck, 2015). However, cognitive-​ behavioral therapy (CBT) appears to be more effective than medication in comparative studies (Agras et al., 1992; Mitchell et al., 1990). Similarly, CBT is more effective than interpersonal therapy (IPT) at the end of treatment, but not at follow-​up (Agras et al., 2000) with IPT apparently acting more slowly than CBT. Hence, CBT can be recommended as a first-​line evidence-​based therapy for BN with IPT or medication as secondary choices. More recently, guided self-​ help treatments based on CBT have been found effective in both adults and adolescents and may form the basis for a cost-​effective first step in the treatment of BN followed by CBT if needed. Despite these developments, only about 25% to 35% of patients with BN who are treated with CBT will recover. Hence, the search for more effective treatments or combinations of treatments for BN needs to continue. Considerable progress has been made in developing evidence-​based treatments for BED because effective treatments for BN have been adapted for this condition. Both CBT and IPT have been shown to be effective for BED in well designed studies, with more than 60% of individuals recovering both at the end of treatment and at follow-​up Wilfley et al., 2002). Interestingly, IPT is as effective as CBT both at the end of treatment and at 4

Introduction

follow-​up, and has lower dropout rates than CBT. However, neither CBT nor IPT has much effect on weight, an important issue because the majority of patients with BED are overweight. Individuals who stop binge eating and who maintain abstinence from binge eating during follow-​up will lose about 5  kg. Here, medications such as the antiepileptic drug topiramate and similar compounds may be useful because such medications have larger effects on weight than does CBT or IPT and also reduce binge eating (Brownley, et  al. 2016). Recently the FDA approved lisdexamphetamine (LDX) for the treatment of BED, again showing effectiveness in reducing binge eating and weight. Further research combining medication and psychotherapy is needed. Hence, CBT, IPT, and antidepressants, antiepileptics, and LDX can be regarded as evidence-​based treatments for BED, with CBT and IPT as first-​line treatments. More recently a large-​ scale study compared IPT, behavioral weight loss treatment (BWL), and guided self-​help (CBTgsh) for BED (Wilson, Wilfley, Agras, & Bryson, 2010). At the end of treatment there were no differences among the three groups in reducing binge eating. However, the BWL group lost more weight than the other two groups. At 1-​year follow-​up there were no differences between groups on binge eating reduction, weight losses, or psychopathology, but at the 2-​year follow-​up both IPT and CBTgsh were superior to BWL in reducing binge eating. The authors concluded that CBTgsh may be useful as a first step in the treatment of BED, with IPT or CBT being used for those who do not improve with guided self-​help. Indeed, the recent release of the National Institute of Clinical Excellence (NICE) guidelines for eating disorder treatment suggest use of guided self-​help in the initial treatment of BN and BED (NICE, 2017).

Technology: Assessment and Treatment

The advent of Internet-​ based and mobile applications in the last few years holds promise for extending the reach of therapists and bringing treatment to areas where no evidence-​based care is available. In a recent review (Agras, Fitzsimmons-​ Craft, & Wilfley, 2017) of technology-​ based assessment and treatment, the authors concluded, “There is not a strong enough evidence-​base to support widespread usage of Internet treatments in the clinic. The extant studies provide a signal that effectiveness studies involving comparisons with known effective treatments are feasible.” (p.  34). Most studies did not take advantage of

the Internet to personalize treatment. Hence, treatment over the Internet is in the early stage of development. Moreover some aspects of Internet treatment raise ethical concerns. For example, Internet assessment and treatment without a therapist may not identify important safety concerns such as low weight, suicidal ideation, and electrolyte abnormalities, or identify newly emerging psychopathology during treatment. Moreover, it is questionable whether a patient whose identity is unknown should be engaged in treatment. In the United States, state licensing regulations vary concerning treatment by out-​of-​state providers. Mobile applications will face these issues once they cross the line from assessment to treatment. Overall, this book delineates the considerable progress made in understanding and treating the eating disorders while drawing attention to the various gaps in our knowledge with suggestions as to how to address them.

References

Agras, W. S., Rossiter, E. M., Arnow, B., Schneider, J. A., Telch, C. F., Raeburn, S. D.,   .  .  .  Koran L. M. (1992). Pharmacologic and cognitive-​behavioral treatment for bulimia nervosa: A controlled comparison. American Journal of Psychiatry, 149, 82–​87. Agras, W. S., Walsh, B. T., Fairburn, C. G., Wilson, G. T., & Kraemer, H. C. (2000). A multicenter comparison of cognitive-​behavioral therapy and interpersonal psychotherapy for bulimia nervosa. Archives of General Psychiatry, 57, 459–​466. Agras, W. S., Lock, J., Brandt, H., Bryson, S. W., Dodge, E., Halmi, K. A.,  . . .  Wilfley, D. (2014). JAMA Psychiatry, 71, 1279–​1286. Agras, W. S., Fitzsimmons-​Craft, E. E., Wilfley, D. E. (2017). The evolution of cognitive-​behavioral therapy for eating disorders. Behaviour Research and Therapy, 88, 26–​36. Brownley, K. A., Berkman, N. D., Peat, C. M., Lohr, K. N., Cullen, K. E. & Bulik, C. M. (2016). Binge eating disorder in adults:  A  systematic review and meta-​analysis. Annals of Internal Medicine, 165, 409–​420. Bynum, C. (1987). Holy feast and holy fast:  The religious significance of food to medieval women. Berkeley: University of California. Fairburn, C. G. (1981). A cognitive-​behavioural approach in the management of bulimia. Psychological Medicine, 11, 707–​711. Fairburn, C. G., & Cooper, Z. (2011). Eating disorders, DSM-​5 and clinical reality. British Journal of Psychiatry, 198, 8–​10. Gull, W. W. (1874). Anorexia nervosa. Transactions of the Clinical Society London, 7, 22–​28.

Habermas, T. (2005). On the uses of history in psychiatry:  Diagnostic implications for anorexia nervosa. International Journal of Eating Disorders, 38, 167–​182. Harrison, K. (2003). Saint Therese of Lisieux. London, UK: Weidenfeld & Nicholson. Hay, P. A systematic review of evidence for psychological treatments in eating disorders. (2013). International Journal of Eating Disorders, 40, 321–​336. Hudson, J. I., Lalonde, J. K., Berry, J. M., Pindyck, L. J., Bulik, C. M., Crow, S.,  . . .  Pope, H. G. Jr. (2006). Binge-​eating disorder as a distinct familial phenotype in obese individuals. Archives of General Psychiatry, 63, 313–​319. Keel, P. K., & Klump, K. L. (2003). Are eating disorders culture-​ bound syndromes? Implications for conceptualizing their etiology. Psychological Bulletin, 129, 747–​769. Lock, J. Agras, W. S., Bryson, S., & Kraemer, H. C. (2005). A comparison of short and long-​term family therapy for adolescent anorexia nervosa. Journal of the American Academy of Child & Adolescent Psychiatry, 44, 632–​639. Machado, P. P., Goncalves, S., Hoek, H. W. (2012). DSM-​ 5 reduces the proportion of EDNOS cases:  Evidence from community samples. International Journal of Eating Disorders, 46, 60–​65. McElroy, S. L., Guerdjikova, A. I., Mori, N., Keck, P. E. (2015). Psychopharmacologic treatment of eating disorders:  Emerging findings. Current Psychiatry Reports, 17, 35–​42. Mitchell, J. E., Pyle, R. L., Eckert, E. D., Hatsukami, D., Pomeroy, C., & Zimmerman, R. (1990). A comparison study of antidepressants and structured intensive group psychotherapy in the treatment of bulimia nervosa. Archives of General Psychiatry, 47, 149–​157. National Institute for Health and Care Excellence (2017). Eating disorders:  recognition and treatment. NICE guideline (NG69). Pope, H. G., & Hudson, J. I. (1982). Treatment of bulimia with antidepressants. Psychopharmacology, 78, 167–​179. Russell, G. F. M. (1979). Bulimia nervosa: An ominous variant of anorexia nervosa. Psychological Medicine, 9, 429–​448. Schneider, J. A., & Agras, W. S. (1985). A cognitive-​behavioral group treatment of bulimia. British Journal of Psychiatry, 146, 66–​69. Wermuth, B. M., Davis, K. L., Hollister, L. E., & Stunkard, A. J. (1977). Phenytoin treatment of the binge-​eating syndrome. American Journal of Psychiatry, 134, 1249–​1253. Wilfley, D. H., Welch, R. R., Stein, R. I., Spurrell, E. B., Cohen, L. R., Saelens, B. E.,  . . .  Matt, G. E. (2002). A randomized comparison of group cognitive-​behavioral therapy and group interpersonal psychotherapy for the treatment of overweight individuals with binge eating disorder. Archives of General Psychiatry, 59, 713–​721. Wilson, G. T., Wilfley, D. E., Agras, W. S., & Bryson, S. (2010). Psychological treatments of binge eating disorder. Archives of General Psychiatry, 67, 94–​101. Vo, M., Accurso, E. C., Goldschmidt, A. B., & Le Grange, D. (2016). The Impact of DSM-​5 on eating disorder diag­ noses. International Journal of Eating Disorders, 50, 578–​581. doi:10.1002/​eat.22628

Agras, Robinson

5

PART 

Phenomenology and Epidemiology

1



CH A PT E R

 The Classification of Eating Disorders

1

Kathryn H. Gordon, Jill M. Holm-​Denoma, Valerie J. Douglas, Ross Crosby, and Stephen A. Wonderlich

Abstract The purpose of this chapter is to elucidate the key issues regarding the classification of eating disorders. To this end, a review of nosological research in the area of eating disorders is presented, with a particular focus on empirically based techniques such as taxometric analysis, latent class analysis, and factor mixture modeling. This is followed by a section outlining areas of overlap between the current Diagnostic and Statistical Manual of Mental Disorders–​Fifth Edition (DSM-​5) eating disorder categories and their symptoms. Next, eating disorder classification models that are alternatives to the DSM-​5 are described and critically examined in light of available empirical data. Finally, areas of controversy and considerations for change in next version of the DSM (i.e., the applicability of DSM criteria to minority groups, children, and males; the question of whether clinical categories should be differentiated from research categories) are discussed. Key Words:  classification, diagnostic model, eating disorder, latent class analysis, nosology, taxometrics

Introduction

Taxonomy (the science of classification) is often undervalued as a glorified form of filing—​with each species in its folder, like a stamp in its prescribed place in an album; but taxonomy is a fundamental and dynamic science, dedicated to exploring the causes of relationships and similarities among organisms. Classifications are theories about the basis of natural order, not dull catalogues compiled only to avoid chaos (Gould, 1989, p. 98). Sound classification systems are the cornerstone of scientific progress. The universal language of classification systems allows scientists to communicate in an efficient, standardized manner about variables in their discipline. This function of classification is extremely important, and makes it possible to construct a collective knowledge base on which scientists can build and advance the field. However, as Stephen Jay Gould articulates in the quote above, classification systems, at their best, are not merely arbitrary organization systems. Rather, they are like

Mendeleev’s periodic table of elements for the field of chemistry:  theoretically driven, parsimonious, and instrumental for scientific growth. Within the disciplines of psychiatry and psychology, one of the most commonly used classification systems for mental disorders is the Diagnostic and Statistical Manual of Mental Disorders—​Fifth Edition (DSM-​5; American Psychiatric Association [APA], 2013). The broad objectives of this chapter are (1) to examine how well the DSM-​5 eating disorder (ED) classification system performs in terms of the qualities that Gould and others (e.g., Waller & Meehl, 1998) have articulated and (2) to illuminate pathways for improvement on the current system. The chapter begins with a brief description of the DSM’s current system for classifying EDs and a review of research on nosological issues. Next, the overlap between diagnostic entities is reviewed, and alternative diagnostic models for EDs are presented. Finally, the chapter concludes with suggestions for change and future directions. 9

The Current DSM Classification of Eating Disorders

The DSM-​5 was updated to include two main types of disorder characterized by disturbed eating behaviors: feeding disorders and EDs. There are five categories of EDs:  anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), other specified feeding or eating disorder (OSFED), and unspecified feeding or eating disorder (UFED). Anorexia nervosa is diagnosed when an individual does not consume enough caloric energy to maintain a minimal healthy body weight, exhibits intense fear about weight gain and/​or fatness despite being underweight, and has distorted perceptions related to weight and shape (e.g., does not recognize one is severely underweight, experiences undue influence of shape or weight on mood and self-​evaluation. Anorexia nervosa is divided into two subtypes:  a binge eating/​purging type for those who engage in binge eating (i.e., an episode wherein one experiences a sense of loss of control while eating and consumes an objectively large quantity of food) and/​ or purging (i.e., self-​induced vomiting or laxative or diuretic use) and a restricting type for individuals who do not regularly engage in binge eating or purging behavior (APA, 2013). In addition to categorical distinctions, DSM-​5 includes a dimensional measure of severity for AN based on body mass index (BMI; ≥17  kg/​m2  =  mild, 16–​16.99  kg/​m2  =  moderate, 15–​15.99 kg/​m2 = severe, 12 vs. n = 38 girls 30; BITE+; EAT-​40; BITE; BSQ; BSQ; at 2 years GHQ; RSE; Family SCAN interview APGAR additionally

Pathological body dissatisfaction, negative perception of parental attitudes (feeling of being ignored/​not loved enough by mother)

5. Fairburn et al. 2005

N = 2,992 female dieters

19.8 years

2 years

n = 104; AN: n = 10; BN: n = 19; EDNOS: n = 75

EDE interview

Low BMI (3.0), ED onset rate was significantly lower in the intervention group, with the NNT equal to 5.

Is Prevention Harmful?

An important consideration to address when discussing ED prevention programs is the concern that such programs may inadvertently be harmful, as opposed to beneficial, for participants. (This is a different issue as to whether or not public health obesity/​weight loss programs may confer some risk for increasing EDs, as discussed previously.) This concern stems from two early prevention research studies in which results indicated an increase in ED risk factors over the course of the study (Carter, Stewart, Dunn, & Fairburn, 1997; Mann et al., 1997). However, a meta-​analysis later concluded that there is no evidence that prevention programs are harmful (Pratt & Woolfenden, 2002). Many prevention studies have been conducted since, and there is no evidence that they are associated with adverse effects. There has also been some concern (e.g., from human subjects committees) that asking young adolescents about “ED behaviors” might be harmful in that it would expose adolescents to attitudes or behaviors they had previously not considered or heighten their focus on weight and shape issues. In response to this concern, Celio, Bryson, Killen, and Taylor (2003) compared results from 115 sixth-​ grade girls who responded to questions on risky weight control behaviors and attitudes at baseline and at 12-​ month follow-​ up with the responses of 107 girls who had not been part of the baseline assessment. Results revealed no differences in scores between the two groups on the “follow-​up” assessment, and rates of unhealthy weight regulation behaviors decreased over time in the group assessed on two occasions. Thus, there is no empirical support suggesting that surveys of ED risk factors and behaviors increase risk for such outcomes. Further, and of critical importance to countering these concerns, the many large prevention trials

conducted using older adolescents and college students have largely reduced ED risk factors rather than increased them.

Moderators and Mediators of Eating Disorder Prevention Programs

Examination of moderators and mediators in prevention studies is important for the progress and future success of prevention programs. Moderators refer to study or participant characteristics present at baseline (e.g., overweight status, risk status, age, gender, race/​ethnicity, program format) that predict differential response to an intervention. Mediators refer to process variables that should change prior to noted change in the outcome (e.g., thin-​ideal internalization) and that thus provide information on mechanisms of change. Hence, moderators specify for whom or under what conditions the prevention program works, and mediators identify mechanisms through which a prevention program might achieve its effects (Kraemer, Wilson, Fairburn, & Agras, 2002). As noted by Stice, Shaw, et  al. (2007), there is consistent evidence that participant characteristics do moderate outcomes, with stronger effects for programs targeting individuals who were at higher risk and age 15 or older. This is likely because the inclusion of low-​risk participants and/​or younger participants reduces the ability to detect statistically significant and clinically meaningful changes in eating pathology due to already low levels in these groups. In addition, older adolescents likely benefit more from current prevention programs, as these programs often focus on skills, such as cognitive dissonance (CD) and media literacy, that require more advanced cognitive skills that younger individuals may not have fully developed. It has also been hypothesized, but not empirically examined, that individuals at risk for ED onset, which includes older adolescents, may be more motivated to participate and engage in prevention program material, leading to greater effects for targeted preventions and better outcomes for high-​risk subgroups within universal programs. Stice, Shaw, et  al. (2007) also found that programs targeting female-​only populations were more effective but only for body dissatisfaction and dieting; there were no significant differences in effects between female-​ only and mixed-​sex programs for BMI, thin-​ideal internalization, negative affect, or overall eating pathology. Thus, while female-​only programs may be generally more effective, this appears to depend on the outcome assessed. As with programs focusing on Taylor, Fitzsimmons-Craft, Goel

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high-​risk and older samples, the larger effects for female-​only programs may be due to the greater level of eating disturbance associated with females and to higher levels of motivation to participate in ED prevention programs. In regard to program characteristics that moderate outcomes, there is some evidence to suggest that interactive programming (as opposed to didactic) is more effective, as are programs delivered by trained interventionists (Stice, Shaw, et  al., 2007). Additionally, programs that promote body acceptance and CD skills appear more effective than programs without such skills, while programs that focus on more general risk factors without a focus on specific EDs risk factors, such as programs teaching coping skills or self-​ esteem promotion, seem to be less effective. However, while meta-​analyses provide an overall description of moderators as they pertain to the field of ED prevention, relatively few studies directly examine moderators, limiting our ability to determine if (and which) programs are most effective for specific populations. Taylor et  al. (2006) did examine moderators of StudentBodies and found that the program was most effective for individuals with BMIs greater than 25 at baseline and, at one study site, that the program was more effective for women with baseline compensatory behaviors. Stice, Marti, Shaw, et al. (2008) also examined moderators of both their CD and healthy weight regulation programs and found support for two general program moderators (baseline level of risk as indicated by body image distress and bulimic symptoms for both programs) and for program specific moderators, including thin-​ideal internalization for the CD program and emotional eating and body mass for the healthy weight regulation program. Overall, these findings reported by Taylor et  al. (2006) and Stice et  al. (Stice, Marti, Shaw, et  al., 2008; Stice, Shaw, et al., 2007) suggest that initial elevations in general ED risk factors, in a population that may be more motivated to change, and in heightened levels of program-​specific/​target risk factors moderate outcomes. These findings are of note given that both studies found moderating effects for bulimic behaviors (e.g., compensatory behaviors) and for elevated weight status, suggesting that it is possible to reduce onset of EDs in more than one high-​risk group. However, Völker, Jacobi, Trockel, and Taylor (2014) examined moderators and mediators of the StudentBodies program, finding that intervention effects on binge eating were weaker for participants 254

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with higher baseline BMI or lower baseline purging and that effects on ED pathology were weaker for participants with higher baseline purging or restrictive eating. No moderators of effect on restrictive eating were identified. In a review of trials of the StudentBodies program, Beintner, Jacobi, and Taylor (2014) found that after adjusting for program adherence, intervention outcomes were only moderated by participant’s age, with smaller effects in one sample of adolescents. Thus, these more recent findings are inconsistent with past work on intervention moderators. Future research should therefore focus on replication of existing findings using comparable measures so as to work toward building a more consistent and complete picture of moderators in ED prevention. Finally, Manwaring et  al. (2008) investigated the possibility that adherence to specific StudentBodies components might mediate outcome, finding that total weeks participation and frequency of using the online pages/​ journals predicted changes in restraint but not other ED symptoms, but that in participants with some compensatory behaviors, discussion board and booster session use was actually associated with lower weight/​shape concerns during follow-​up. Stice, Presnell, and colleagues (2007) examined mediators of the CD and healthy weight programs, finding some evidence to support thin-​ ideal internalization as a partial mediator for the CD program. Of interest, these researchers noted that in about one-​third of their CD participants, change in thin-​ideal internalization occurred after change in the outcome measures and that change in the healthy weight mediators was inconsistently associated with outcomes, suggesting that continued examination of mediators, and elaboration on the expected change pathways/​causal pathways is needed, as additional mediators likely contribute to change in the ED risk factor outcomes. As noted by the researchers, examination of demand characteristics may also provide insight into the inconsistent findings. Overall, as concluded by Stice, Presnell, et al. (2007) these findings have important implications for prevention programs in that although both programs had program-​ specific mediators, both programs did result in reduction of ED risk factors in the long-​term. This lends support to the notion that different pathways may be involved in the onset of EDs and that future programs may want to find ways to maximally target more than one risk pathway in order to achieve even greater reduction of risk factors and ED onset.

Examples of Effective Approaches

In the following section we discuss three programs:  a CD program (the Body Project), an Internet-​based program (StudentBodies), and peer/​ school-​ based prevention programs (e.g., Healthy Schools, Healthy Kids [HS-​ HK]) that have been shown, using long-​term data (e.g., at least 1-​year long-​term follow-​up data provided) from controlled clinical studies with sufficiently large samples needed to have adequate power to detect differences. We also discuss an emerging area of prevention programming that targets both the reduction of EDs and overweight and review recent work supporting such programs.

Cognitive Dissonance Programs

For the past 15 years, Stice and colleagues have been developing, evaluating, and refining a CD program, the Body Project, designed to reduce thin-​ ideal internalization and other ED risk factors (e.g., body dissatisfaction, negative affect) in females who indicate body image concerns. As previously described, CD programs are relatively short-​term (two to four 1-​hour sessions) and focus on reducing thin-​ideal internalization using dissonance techniques that require participants to take standpoints that are counter to their beliefs; over time, in order to reduce the distress associated with supporting an opinion counter to their original beliefs, participants change their beliefs (e.g., less adherence to and internalization of the thin ideal). The first CD study from Stice and colleagues evaluated three 1-​hour sessions of CD administered to at-​risk college women as compared with a wait-​ list control group, with findings indicating that CD participants had greater decreases in ED risk factors, including body dissatisfaction, thin-​ ideal internalization, bulimic symptoms, and negative affect (Stice et al., 2000). A second study included an active control condition as well as a wait-​list control condition in order to verify that the previous findings were not due to demand characteristics; this active control group included healthy weight regulation materials that focused on reducing body image concerns by providing healthy weight control skills. Findings again provided support for CD with participants in the CD condition evidencing greater reductions in thin-​ideal internalization and body dissatisfaction in comparison to wait-​list and healthy weight control participants and greater reductions in dieting, bulimic symptoms, and negative affect in comparison with wait-​list controls (Stice et  al., 2001). A third study was designed to replicate these

findings, particularly given that healthy weight participants in the second study showed improvements along with CD participants. In this study, Stice and colleagues (2003) used a larger sample and longer follow-​up periods; participants were also somewhat younger (mean age 17) than those in the previous studies (mean ages 18 and 19, respectively) in order to deliver the program at a time of peak ED onset. Findings again provided support for CD, with participants in CD evidencing greater short-​term (post-​test) reduction in thin-​ideal internalization, negative affect, bulimic symptoms, and body dissatisfaction than healthy weight controls and greater long-​term (6-​month) reduction in body dissatisfaction and thin-​ideal internalization in comparison to healthy weight controls. Both active conditions showed greater short-​and long-​term reductions in bulimic symptoms and negative affect relative to the wait-​list control condition (Stice et al., 2003). Additional efficacy trials have demonstrated that CD produces greater reductions in ED risk factors and symptoms, impairment, mental health service use, and ED onset over 3-​year follow-​up relative to assessment-​ only control conditions and three alternative interventions. For example, Stice, Marti, Spoor, et al. (2008) compared their CD program to a healthy weight program, an expressive writing program, and assessment-​only control condition in a sample of adolescent girls with body dissatisfaction. Findings from the 1-​year, 2-​year, and 3-​year follow-​up studies revealed support for the CD program. Of note was that, compared with the assessment-​only group, there was a 60% reduction in ED onset for CD participants (6% onset in CD group vs. 15% in assessment only controls) through 3-​year follow-​up. Randomized controlled trials from other research groups further established the short-​ term efficacy of CD in reducing ED pathology in high risk and unselected samples of college women (e.g., Becker, Smith, & Ciao, 2005; Green, Scott, Diyankova, Gasser, & Pederson, 2005; Roehrig, Thompson, Brannick, & van den Berg, 2006). Effectiveness trials have also shown that CD produces similar effects when delivered by endogenous providers under real-​world conditions. For example, Stice et al. (2011) demonstrated that CD, implemented by school-​ based counselors, produced significantly greater decreases in body dissatisfaction at 2-​year follow-​up and ED symptoms at 3-​year follow-​up than an educational brochure condition among female high school students with body image concerns. College-​aged peer leaders can also be trained to lead the intervention (e.g., Becker, Taylor, Fitzsimmons-Craft, Goel

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Bull, Schaumberg, Cauble, & Franco, 2008; Becker, Smith, & Ciao, 2006; Becker et  al., 2010). These effectiveness studies report significant reductions in ED risk factors and pathology, although effect sizes are typically smaller compared to trials where research staff implement the intervention. To address this issue, an enhanced version of CD was recently created, where college clinicians receive enhanced training and supervision, and it was shown to produce larger intervention effects at 1-​year follow-​up compared with previous effectiveness studies (Stice, Butryn, Rohde, Shaw, & Marti, 2013). Cognitive dissonance, through the Body Project manual (Stice, Rohde, & Shaw, 2012), is now widely available, and intervention materials are also available online (www.bodyprojectsupport. org). Indeed, the program appears highly disseminable and was adopted for use within sororities on college campuses across the United States through the Reflections program, a peer-​led CD program that can be delivered in two 2-​hour sessions (Perez, Becker, & Ramirez, 2010). Other exciting adaptations of CD have emerged in recent years as well, including a version of the Body Project that is delivered over the Internet (eBody Project). The eBody Project also reduces ED risk factor and symptoms and weight gain prevention effects that persisted through 2-​year follow-​up (Stice, Rohde, Durant, & Shaw, 2012; Stice, Durant, Rohde, & Shaw, 2014).

Stanford/​Washington University StudentBodies™ Studies

During the past 20 years, researchers at Stanford and Washington University in St. Louis have been exploring issues related to prevention using Internet-​based, psychoeducational, interactive programs. In an early study from this group, Killen et al. (1993) evaluated the effectiveness of a prevention curriculum designed to modify the eating attitudes and unhealthful weight regulation practices of young adolescent girls. Nine hundred sixty-​seven 6th-​and 7th-​grade girls were randomized to experimental healthy weight regulation curriculum or no-​treatment control classes. There was a significant increase in knowledge among girls receiving the intervention but no overall effect. This study and a subsequent longitudinal prospective study in older adolescents demonstrated that students with higher scores on a measure of weight and shape concerns were at risk for developing EDs. The group then began to focus on targeted/​ selective programs. Early efforts along this line demonstrated the effectiveness of computer-​based 256

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psychoeducational programs (Celio et  al., 2000; Springer et al., 1999; Winzelberg et al., 2000). These studies suggested that an Internet-​based program can reduce risk factors in college-​ age women and set the stage for a more ambitious study. In the next study, 480 college-​age women were randomized to StudentBodies or a wait-​ list group and were followed for 3 years (Taylor et al., 2006). There was a significant reduction in WCS scores in the StudentBodies group compared with the control group at post-​intervention (p < .001), 1 year (p < .001), and 2 years (p < .001). The slope for reducing WCS score was significantly greater in the treatment compared with the control group (p = .02). Over the course of follow-​up, 43 participants developed subclinical or clinical EDs. While there was no overall significant difference in onset of EDs between the intervention and control groups, the intervention significantly reduced the onset of EDs in two subgroups identified through moderator analyses: (1) participants with an elevated BMI (≥ 25, calculated as weight in kilograms divided by height in meters squared) at baseline and (2) at one site, participants with baseline compensatory behaviors (e.g., self-​induced vomiting, laxative use, diuretic use, diet pill use, driven exercise). No intervention participants with an elevated baseline BMI developed an ED, while the rates of onset of ED in the comparable BMI control group (based on survival analysis) were 4.7% at 1  year and 11.9% at 2 years. In the subgroup with a BMI of 25 or higher, the cumulative survival incidence was significantly lower at 2 years for the intervention compared with the control group (95% confidence interval, 0% for intervention group; 2.7% to 21.1% for control group). For the San Francisco Bay Area site sample with baseline compensatory behaviors, 4% of participants in the intervention group developed EDs at 1 year and 14.4% by 2 years. Rates for the comparable control group were 16% and 30.4%, respectively. In sum, this study demonstrated that, among college-​age women with high weight and shape concerns, an 8-​ week, Internet-​ based cognitive-​behavioral intervention can significantly reduce weight and shape concerns for up to 2 years and decrease risk for the onset of EDs, at least in some high-​risk groups. Jacobi et  al. (2011) further analyzed the data from Taylor et al. (2006) and identified three factors that moderated the intervention in individuals with high weight and shape concerns: a history of being teased, current or lifetime depression, and/​ or nonclinical levels of compensatory behaviors.

Taylor et  al. (2016) then examined the effects of StudentBodies, adapted to specifically address these three risk factors (based on Taylor et  al., 2006). Four hundred thirty-​ nine college and university students with one or more of these risk factors were randomized to the intervention or wait-​list control and followed for up to 2  years. The ED attitudes and behaviors improved more in the intervention than control group (p  =  .02, d  =  .31). Although ED onset rate was 27% lower in the intervention group, this difference was not significant (p = .28, NNT = 15). In the subgroup with very high weight shape concerns, about 50% of the sample, ED onset rate was significantly lower in the intervention than control group (20% vs. 42%, p = .025). For the 27 individuals with depression at baseline, depressive symptomatology improved more in the intervention than control group (p = .016, d = .96). Thus, this study suggests that StudentBodies might be most effective when applied to subgroups of individuals who have very high weight and shape concerns and additional attributes. In a companion study, Kass et al. (2014) sought to determine whether adding “guided self-​help” to StudentBodies provided to students with high weight and shape concerns, but at lower risk than those identified for the Taylor et  al. (2016) study, improved outcomes. Women with high weight/​ shape concerns (N  =  151) were randomized to StudentBodies with a guided discussion group (n = 74) or no discussion group (n = 77). Regression analyses showed weight/​ shape concerns were reduced significantly more among guided discussion group than no discussion group participants (p  =  .002; d  =  .52); guided discussion group participants had 67% lower odds of having high-​risk weight/​shape concerns post-​intervention (p = .02). There were no differences in binge eating at post-​ intervention between the two groups, and no moderators emerged as significant. Results suggest the guided discussion group improves the efficacy of StudentBodies in reducing weight/​shape concerns in college students at high risk for an ED. In other studies, the Stanford-​ Washington University in St. Louis research group returned to the issue of how to provide both universal and targeted interventions. The goal was to find ways to provide general healthy weight regulation programs to all high-​school age students while providing targeted interventions to students at higher risk. Following a study by Abascal et al. (2004) that showed that students could be successfully allocated to various risk groups using an online program, Luce

et al. (2005) provided online assessment and feedback to 174 10th-​grade students based on weight/​ shape concerns and overweight risk. The algorithm identified 111 no-​risk (NR), 36 ED risk (EDR), 16 overweight risk (OR), and 5 both risks. Fifty-​ six percent of the EDR and 50% of the OR groups elected to receive the recommended targeted curricula. Significant improvements in weight and shape concerns were observed in all groups, and the study demonstrated that an Internet-​delivered program can be used to assess risk and provide simultaneous universal and targeted interventions in classroom settings. In the meantime, the protocol has been expanded to include boys and to address overweight (Jones et  al., 2008). In a pilot study, 100 8th-​grade boys and girls were sorted by an Internet-​ based algorithm into two groups based on risk for developing an ED; male students participated as one general group. Participants in each group were also assigned to an online discussion group that corresponded to their group assignment and were encouraged to post messages to group members of similar risk. All three groups showed significant increases in knowledge related to the program content and reported increased physical activity levels from pre-​to post-​ intervention. Females in the high-​risk group also showed significant reductions in weight and shape concerns. Participants were enthusiastic about using the online health program; almost all reported that they would prefer an online format to a traditional classroom format. Another study showed that a paper-​and-​pencil program designed to reduce family/​ parental critical comments about eating and shape resulted in reduced critical comments from parents (by their report) (Bruning-​Brown, Winzelberg, Abascal, & Taylor, 2004). Taken together, these studies suggest that universal and targeted prevention programs can be provided simultaneously and might benefit from involvement of education programs aimed at parents/​families. In Germany, Jacobi and her group translated StudentBodies into German and adapted media more relevant to the German population (Jacobi et  al., 2007). Because many of the American StudentBodies programs have also been provided to German populations and examined in controlled studies, Beintner et  al. (2008) undertook a meta-​ analysis of studies using StudentBodies done in the United States and in Germany. Pre–​post data from these programs across a large number of eating pathology variables resulted in effect sizes in the moderate range for most variables. The respective Taylor, Fitzsimmons-Craft, Goel

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controlled effect sizes for the German and US studies were:  drive for thinness, 0.42, 0.35; bulimia, 0.22, 0.29; restraint, 0.30, 0.26; WCS, 0.58, 0.36. This analysis suggests that programs with similar content and format, addressing similar populations in Germany and the United States, have similar outcomes. Overall, data from this group has demonstrated that an Internet-​based program can reduce risk factors for high-​risk individuals and even reduce onset of EDs. The Stanford-​ Washington University in St. Louis group has since combined the prevention programs into an integrated universal, targeted, indicated prevention/​intervention for EDs (Wilfley et al., 2013).

Peer Support/​School-​Based Programs

Following on several key aspects of ecological and social systems theories, in which inclusion and targeting of critical social relationships and interactions is indicated in order to achieve enduring change on ED risk factors, several studies have focused on the school and peer environments. For example, Becker and colleagues (Becker et al., 2005, 2006, 2008) have worked with sorority systems, which are believed to be high-​risk populations, to develop and examine the effectiveness of peer-​led media advocacy (MA) and CD programs on the risk for EDs in sorority members. The focus on peer-​led programs at the college level stems from research indicating that peers contribute to body image satisfaction and, more broadly, from the notion that colleges tend to promote peer leadership, particularly in organized groups such as those in the athletic domain or in the sorority and fraternity systems. Findings provide support for both the CD and MA peer-​led programs for high-​risk females and support for the peer-​led CD program for both high-​and low-​risk females. These findings provide particular support for a peer-​led CD program, as this appears to have a positive effect on both low-​and high-​risk participants. McVey, Davis, Tweed, and Shaw (2004) have also developed and examined a universal, school-​ based program that draws from several ecological approaches to reducing risk behaviors. In these studies, described below, an ecological approach was used to address the multiple systems (e.g., teachers, peers, parents) that may influence risk for ED onset in youth. The program was implemented in a number of different classes throughout the academic year (e.g., math, drama, English, and health classes). 258

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McVey and colleagues (2004) examined a six-​ session life-​skills program focused on promoting self-​esteem and improving body image satisfaction and global self-​esteem, with the additional goals of reducing negative attitudes shown to be associated with risk for EDs, including thoughts related to unhealthy eating and perfectionism. Participants included 258 preadolescent girls (n  =  182 in prevention group; mean age = 11.8). Findings revealed short-​term (pre–​post) reductions in unhealthy dieting attitudes and improvement in self-​esteem and body satisfaction; these changes were not maintained at the long-​ term (12-​ month) follow-​ up. This work was followed by two additional studies, again focused on young girls in grades 7 and 8, who participated in 10-​session support/​discussion groups facilitated by a school nurse and by trained peers. Sessions included more focused discussion related to healthy body image messages, promoting healthier norms within peer groups, and combating unhealthy appearance messages and expectations. Findings from these two studies revealed inconsistent support for this program as one study with 214 girls found decreases in dieting and improved body esteem over time for program participants but not in control participants (McVey et al., 2004), while another similar replication study involving 282 girls failed to find differences in improvements on these outcomes between the control and intervention groups over time (McVey, Lieberman, Voorberg, Wardrope, Blackmore, & Tweed, 2003). A large-​scale study involving 982 middle school students expanded on this earlier work by including males and including a focus on teachers and parents (McVey, Tweed, & Blackmore, 2007). Materials were provided not only to students but also to teachers, and to some extent, parents, with the idea that it is important to address and reduce teachers’ and parents’ own unhealthy eating and weight attitudes and perceptions so that they may more effectively address and, over time, combat unhealthy attitudes and behaviors, including teasing, in students. Of note was that this program also included a focus on males, as these researchers noted that males are indeed at growing risk for ED attitudes and behaviors, and due to evidence that males are more likely than females to initiate teasing (Stein, 1999). Findings revealed that the program was associated with lower internalization of media messages for males and females, decreases in the number of students trying to lose weight, and decreased disordered eating scores for female students, although effects on weight loss behaviors did not persist at

6-​month follow-​up. Analyses on a high-​risk group, defined as students currently trying to lose weight, revealed a significantly greater decrease in body dissatisfaction, media internalization, and disordered eating for these students in comparison to low-​risk students; of note was that low-​risk students did not evidence much increase in body dissatisfaction over time, which is important as such dissatisfaction may have been expected to increase as students were entering puberty. Findings, however, failed to show a reduction in weight-​related teasing or improvements in body size acceptance. Additional analyses also failed to reveal program influence on teachers’ perceptions of the school environment or on their own behaviors and attitudes; a number of reasons, including time and other demands on teachers’ abilities to learn and deliver program material may have contributed to the lack of findings for teachers, as well as the limited findings for student outcomes such as teasing. Overall, despite the limited findings for some outcomes and the lack of intervention effect for teachers reported by McVey et al. and the somewhat inconsistent effects on disordered eating across studies (McVey et al., 2004; McVey, Lieberman, Voorberg, Wardrope, & Blackmore, 2003; McVey, Lieberman, Voorberg, Wardrope, Blackmore, & Tweed, 2003; McVey et al., 2007), these studies and the work from Becker and colleagues (Becker et al., 2005, 2006, 2008) suggest that programs that include peer-​ based and/​ or school-​ based approaches to ED prevention may be important steps toward reducing risk for EDs in several systems that influence attitudes and behaviors (e.g., peer and school environments). These programs may be particularly appealing to institutions that want to deliver effective universal programs given that Becker et al. found equal improvements for low-​and high-​risk participants who received the CD program (Becker et al., 2006) and McVey et al. (2007) found equal effects on many outcomes for males and females.

Eating Disorder and Obesity Prevention

In some, but not all studies, elevated weight status has been associated with increased risk of onset of BN and binge ED (BED; Jacobi, Hayward, et al., 2004); weight status has also been linked to disordered eating attitudes and behaviors in young children and adolescents (Goldschmidt, Aspen, Sinton, Tanofsky-​Kraff, & Wilfley, 2008), yet most adolescent obesity prevention programs do not assess eating pathology (Carter & Bulik, 2008). Despite these

studies and reviews that indicate that overweight children and adolescents may already be endorsing unhealthy eating attitudes and behaviors, some have argued that the attention put on reducing and maintaining weight, particularly in those in the higher BMI ranges, has increased the rate of EDs. In addition, others feel that the message that the majority of young people need to remain “thin” or be thinner reinforces the thin-​body ideal and would seem to counter the general ED prevention message that self-​esteem should not be determined by body size (Neumark-​Sztainer, 2005). However, despite these concerns, it is becoming critical to comprehensively respond to the high prevalence of obesity, EDs, and disordered eating behaviors among youth, and researchers in both the obesity and ED fields have proposed using an integrated approach to prevention that addresses the spectrum of weight-​ related disorders within interventions (Haines & Neumark-​Sztainer, 2006; Kass, Jones, et al., 2017). The identification of risk factors that are shared between these weight-​related disorders is an essential step to developing effective prevention interventions. Neumark-​ Sztainer et al. (2007) provide preliminary support for the existence of shared risk factors for obesity and EDs, with recent empirical research supporting this contention. Specifically, the authors examined and found preliminary evidence that dieting, media use, body image dissatisfaction, and weight-​related teasing may have relevance for the development of the spectrum of weight-​related disorders. Future etiological research designed to specifically test these and other potentially shared risk factors across different age and racial/​ethnic groups remains warranted and would provide important insights into the relevant factors to be addressed in interventions aimed at preventing a broad spectrum of weight-​ related disorders. Several preventive interventions have been developed based on addressing both ED and obesity prevention. Austin and colleagues (Austin, Field, Wiecha, Peterson, & Gortmaker, 2005; Austin et al., 2007) evaluated the effects of a program designed to promote healthful nutrition and physical activity on disordered weight-​control behaviors in early adolescent girls and boys (Planet Health). Austin et al. (2007) randomized 749 girls and 702 boys in grades 6 and 7 from 13 middle schools to the intervention (5-​2-​1 Go!). At follow-​up in girls, there was a significant effect for disordered weight-​control behaviors for girls, with 3.6% (15 of 422) of girls in control schools compared with 1.2% (4 of 327) of girls Taylor, Fitzsimmons-Craft, Goel

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in intervention schools reporting engaging in disordered weight-​control behaviors (p = .04). No intervention effect was observed in boys. Other studies also provide support for targeting both overweight and ED risk through one program. Jones et al. (2014) provided a program to 9th-​grade students which had two tracks for universal and targeted delivery and was designed to enhance healthy living skills, encourage healthy weight regulation, and improve weight/​shape concerns among high school adolescents. Three hundred thirty-​six 9th-​grade students in two high schools in the San Francisco Bay area and in St. Louis were invited to participate. Students who were overweight (BMI > 85th percentile) were offered the weight management track; students who were normal weight were offered the healthy habits track. The BMI percentile and zBMI significantly decreased among students in the weight management track. The BMI percentile and zBMI did not significantly change among students in the healthy habits track, demonstrating that these students maintained their weight. Weight/​shape concerns significantly decreased among participants in both tracks who had elevated weight/​shape concerns at baseline. The results are promising but need to be replicated and examined in controlled trials. Stice and colleagues (Stice, Marti, Spoor, et al., 2008; Stice et al., 2006) in their studies of CD also found support for their healthy weight regulation program as an effective ED prevention approach. While this program was originally intended to serve as an active control condition only, participation in the healthy weight program was found to be associated with a 55% reduction in the onset of overweight and 61% reduction of ED onset in comparison to the assessment-​only control group and to be associated with reduction in other ED risk factors, such as bulimic symptoms; these findings are in concordance with earlier studies suggesting that healthy weight skills may indeed promote a reduction in ED risk (Killen et al., 1996; Matusek et al., 2004; Stice et al., 2003). Thus, a clear direction for future studies would be to evaluate a CD program that includes healthy weight regulation material. Taken together, these studies suggest that interventions designed to promote healthy weight regulation and/​or prevent EDs may help with weight maintenance and do not seem to be harmful.

Settings and Special Populations

The apparent association between ED risk and certain activities such as sports has been long noted, with some programs having been developed to 260

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target the unique pressures associated with high-​ risk activities, such as ballet, gymnastics, cheerleading, and other sports. Furthermore, it should be noted that research has demonstrated that certain racial and cultural groups can be particularly at-​risk of developing EDs. In this section we review some preventive activities in these domains.

Dance

Piran (1999) developed and evaluated a program aimed at preventing EDs in a world-​class, residential ballet school for female and male students ages 10 to 18. The focus of the intervention was on the school environment, which was reengineered to allow students to “feel” comfortable with the processes of puberty and growth and to promote their right to feel both safe and positive in their diverse bodies. The focus of body shape was replaced with an emphasis on stamina and body condition. Teachers were prohibited from making evaluative comments about body shape to students, and staff members were available to help students regarding concerns about body shape. The effectiveness of the program was examined by comparing scores from two cohorts of 7th-​to 9th-​and 10th-​to 12th-​ grade students who had been in the school following implementation of the program with an earlier cohort that had not been exposed to the program. Scores on two items measuring weight and shape, the EAT and EDI, were lower in the intervention cohorts compared to the baseline cohort. These data provide evidence that a schoolwide intervention can be effective in reducing ED risk in a high-​risk environment.

Cheerleading

Whisenhunt, Williamson, Drab-​ Hudson, and Walden (2008) targeted cheerleading coaches as potential change agents by training them to recognize the symptoms of EDs and reduce the pressures for thinness among their squads. At 8-​month follow-​ up, there was self-​ reported improvement in coaches’ behavior, but no sustained knowledge about EDs.

Athletes

As a subgroup, some types of athletes (e.g., swimmers, gymnasts, figure skaters) are much more likely to develop EDs than the regular population (Bonci et al., 2008). Athletes may be at particular risk because of the pressure from coaches and others to lose weight or maintain an often very low weight for real or perceived need to improve performance

(Bratland-​Sanda & Sundgot-​Borgen, 2012). Bonci et al. (2008) estimated that 62% of female athletes and 33% of male athletes are affected by disordered eating. Martinsen and Sundgot-​ Borgen (2013) assessed the prevalence of EDs among adolescent elite athletes in comparison to nonathletes and determined that there was a significantly higher estimated prevalence of ED among the female athletes at 14% in comparison with female nonathletes at 5.1% and an estimated rate of prevalence of 3.2% for the male athletes (data on the males was limited due to the relatively low number of cases of ED identified in the male sample). Martinsen et al. (2014) demonstrated that an intervention to reduce ED risk was effective among the female athletes, and subsequently, Martinsen et  al. (2015) developed a program to teach coaches how to identify and prevent EDs. Coaches taking the course demonstrated greater knowledge about these issues compared with coaches who did not take the course. Buchholz, Mack, McVey, Feder, and Barrowman (2008) evaluated the effectiveness of a selective prevention program designed to reduce pressures to be thin in sports, and to promote positive body image and eating behaviors in young female athletes belonging to gymnastic clubs. The intervention focused on competitive female gymnasts (ages 11–​18 years), parents, and coaches. Four clubs were randomized to receive a 3-​month intervention program and three to a control group, with a total of 62 female gymnasts (intervention n  =  31; control n  =  31) completing the self-​report post-​test. The program resulted in athletes perceiving a reduction in pressure from their sports clubs to be thin, though no changes were found in body esteem, the EAT, or the SATAQ. No significant change was observed over time on mothers’ measures.

Diabetes

In terms of common medical conditions, preventing EDs in females with type I or type II diabetes may be particularly important. Females with type I  or II diabetes are at particular risk of EDs (Crow, Kendall, Praus, & Thuras, 2000; Jones, Lawson, Daneman, Olmsted, & Rodin, 2000). Unfortunately, we could find no prevention studies.

Sexual Minorities

Sexual minorities are another population particularly vulnerable to developing EDs. The Minority Stress Model posits that this may be the case due to unique stressors that sexual minorities face as a result of inhabiting a predominantly heterosexual culture

(Meyer, 2003). Research has demonstrated that in comparison to heterosexual males, self-​ identified bisexual and gay men tend to exhibit higher rates of body image dissatisfaction (M. Morrison, T. Morrison, & Sager, 2004), ED behaviors (Austin et al., 2009), and EDs (Feldman & Meyer, 2007), however, the prevalence rates for these domains for lesbian and bisexual females in comparison to heterosexual females is less clear (Feldman & Meyer, 2007; Wichstrom, 2006). Brown and Keel (2015) investigated the acceptability and efficacy of a 2-​ session CD intervention (the PRIDE Body Project) compared to wait-​ list control in reducing ED risk factors among gay college males. Participants found the intervention highly acceptable, and the CD intervention was associated with significantly greater decreases in a variety of ED risk factors from pre-​to post-​intervention, with nearly all improvements maintained at 4-​week follow-​up.

Racial/​Ethnic Minorities

Researchers have determined that EDs can affect individuals across various racial and ethnic stratifications (Shaw, Ramirez, Trost, Randall, & Stice, 2004). Shuttlesworth and Zotter (2011) determined that low levels of ethnic identity represented a risk factor for the development of binge eating and bulimic pathology in Black women, while high levels of ethnic identity represented a risk factor for both binge eating and more global eating psychopathology for White women. As another example, Regan and Cachelin (2006) evaluated the frequency of ED symptoms among a multiethnic sample and determined that binge eating was significantly more common among Black and Hispanic women than their male counterparts and that Black, White, and Hispanic women were more likely to engage in purging behaviors compared with Asian women. We could find no examples of prevention programs specifically targeting these or other minority groups, or evidence of adapting existing prevention programs to racial/​ethnic minority status. However, Rodriguez, Marchand, Ng, & Stice (2008), found that their CD program reduced ED pathology and risk factors similarly across their diverse sample of White, Asian-​American, and Hispanic female adolescents (though sample sizes for minority participants were small).

Public Health/​Policy and Mass Media Models

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EDs (e.g., Austin, 2012). Such approaches focus on changing norms, environment, and policies that may reduce pressure to be thin and other factors in the environment that might promote EDs. One major public health focus has been on reducing exposure of populations to very thin models on the assumption that very thin models serve as media role models for young women and increase the risk of AN. A  meta-​analysis found significant effect sizes between exposure to media images depicting the thin-​ideal body and body image concerns in women (Grabe, Ward, & Hyde, 2008). Following the death of two South American models, one of whom had a BMI of 13.4 and another of whom died on the catwalk, and under pressure from legislators, fashion organizers in Italy, Spain, and Brazil banned models with BMIs lower than 18.5. In addition, models also have to carry a medical certificate to prove that they are healthy. Similar regulations have since been adopted by many other countries. Some experts have recommended that the fashion industry should be a more highly regulated workplace to ensure the health of the employees, including requiring mandated healthy weights (Record & Austin, 2016). In an effort to use mass media to improve body image and resist the thin-​body ideal, DOVE has undertaken a number of important activities as part of their Campaign for Real Beauty (www.campaignforrealbeauty.com). In 2004, DOVE launched an ad campaign featuring “real women” whose appearances were outside the stereotypical norms of beauty. The ads asked viewers to judge the women’s looks (Oversized? Outstanding? Or Wrinkle? Wonderful). In 2005, DOVE introduced a second phase, which included advertising featuring six women of varying sizes and shapes. (Ironically, an article suggested that many of the “real women” presented in the DOVE campaign had actually been digitally altered [Collins, 2008].) The next phase, launched in 2007, addressed issues of women and aging. Other efforts have focused on helping young girls realize that what they see in movies and magazines represents an unrealistic standard of beauty, including through the use of “viral films.” The “viral” films include Evolution, which depicts the transformation of a real women into a model and promotes awareness of how unrealistic perspectives of beauty are created, and Onslaught, a film that shows the barrage of beauty images that girls absorb ever day. DOVE’s “Real Beauty Sketches” ad, launched in 2013, examines the issue of how we view ourselves compared with how others see us. At the time of its 262

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launch, the DOVE “Real Beauty Sketches” was the most viewed online ad (111 million views). DOVE has also developed a Self-​Esteem Fund, which sponsors self-​esteem building workshops with “inspirational celebrities,” and online tools to educate parents, mentors, and young women. In the United States, this company also sponsors ME!, a program associated with the Girl Scouts designed to build self-​confidence in girls ages 8 to 17 with educational resources and hands-​on activities designed to promote self-​esteem and self-​confidence. The impact of these programs on improving self-​esteem is not known, but the campaign was associated with a 13% increase in worldwide sales of DOVE skin and hair products, suggesting some positive response to these strategies. In addition, in one small study, Oswalt and Wyatt (2007) evaluated a campaign that included defining 10 messages related to sabotaging body image and 10 ways to enhance body image. These messages were then displayed on campus buses, billboards, and magnets. Following the campaign, students were asked to evaluate the impact of these messages, with results indicating a modest impact. For instance, only 36% of the sample agreed or strongly agreed with the statement, “The messages in this campaign positively influenced the way I think about my body.” Thus, although it is important for these societal-​level programs to be initiated and maintained in order to achieve enduring reduction in ED risk factors, the impact of initial efforts is not yet established and remains a source for future research. Indeed, these programs provide an important opportunity for researchers to possibly disseminate effective prevention materials by working with companies and organizations whose goals and mission statements may support such programs. Although many other “environmental” and public health approaches have been recommended, except as applied to specific settings and populations as discussed above, we could find no evidence as to their effectiveness.

Proanorexia and Bulimia Websites and Social Media

The Internet hosts thousands of websites that promote AN (pro-​ANA) and/​or BN (pro-​MIA). Such websites may include pictures of very thin women who are described as “beautiful” and also provide tips on how to hide EDs. A Belgian study that sampled 711 7th-​, 9th-​, and 11th-​grade students found that about 12.6% of girls and 5.9% of boys visited proanorexia websites (Custers & Van

den Bulck, 2009). Girls visiting proanorexia websites had higher drive for thinness, worse perception of appearance, and elevated levels of perfectionism. Bardone-​Cone and Cass (2007) constructed a prototypical proanorexia website, and randomly assigned 235 female undergraduates to view either the proanorexia website or one of two comparison websites related to female fashion (using average-​ sized models) or home décor. Study participants exposed to the proanorexia website endorsed more negative affect, lower social self-​esteem, and lower appearance self-​efficacy following the experimental manipulation than those who viewed a comparison website. In addition, these women perceived themselves to be heavier and reported an increased likelihood of exercising, thinking about their weight in the near future, and engaging in more image comparison. Like other Internet-​ based activities, pro-​ ANA websites have evolved into pro-​ ANA communities, and the messages are now available in a variety of places including Snapchat, Twitter, Facebook, Pinterest, and Tumblr. While not directly related to prevention, but illustrating the importance of social media use in the ED population, Saffran et  al. (2016) explored Facebook use among 415 individuals with a history of receiving treatment for an ED in a group setting (e.g., inpatient, residential, outpatient group). Participants reported having an average of 10–​19 Facebook friends from treatment and spending up to 30 minutes per day interacting on Facebook with individuals from treatment or ED-​related organizations. More comparison to treatment peers on Facebook was associated with greater ED psychopathology and ED-​related impairment. Conversely, positive interaction with treatment peers on Facebook was associated with lower ED psychopathology and ED-​related impairment. Few participants (19.5%) reported that a therapist asked about the impact of Facebook on pathology. Whatever impact these sites might have, it is not possible to remove them from the Internet and as such, educators, parents, therapists and others are advised to discuss their use with at-​risk populations.

Preventing Anorexia Nervosa

Although there has been impressive progress in preventing ED, most of the studies have focused on combined onset of subclinical, clinical BED, BN, and/​or EDNOS. The low prevalence of AN (2%–​3% of the population) makes it nearly impossible to demonstrate a population-​ based effect, although interventions in

high-​risk populations may be of benefit. A focus on indicated prevention might be the most preferable approach in which adolescents with early features of AN, such as failure to gain weight in the context of other factors such as excessive exercise or perfectionism, are targeted. The type of preventive intervention is also less certain for AN than for BN or BED. However, based on the success of family-​based interventions for adolescents with AN (Keel & Haedt, 2008; Lock & le Grange, 2005; Wilson, 2005), such preventive efforts might focus on parents. To examine this, Jones et al. (2012) developed an online program, modeled after the family-​based therapy model, to help parents and at-​risk students reduce their AN risk. Twenty-​four percent of 791 girls screened met the risk criteria for AN. Parents accessed the majority of the online sessions and rated the program favorably. At post-​ assessment, 16 of 19 participants evidenced reduced risk status. Participants remained stable or increased in ideal body weight and reported decreased ED attitudes and behaviors. However, surprisingly few parents were willing to enroll in the program suggesting the program was not really practical. An alternative approach is to focus on high-​risk environments, such as was done with Piran (1999). Finally, attempts to reduce media glamorization of the thin-​body ideal, as discussed above, would seem important to reducing AN, although the benefit of this tactic is difficult to demonstrate in scientific studies.

Dissemination/​Implementation and Cost–​Benefit Issues

Most of the prevention interventions shown to be effective have been designed for implementation and dissemination. Becker et al. (2016) describe the dissemination and implementation of the Body Project across six diverse stakeholder partnerships that span academic, nonprofit, and business sectors at national and international levels, including a train-​the-​trainer approach (Greif, Becker, & Hildebrandt, 2015). Many of the school-​based programs have been designed for implementation. Much less has been written about the cost of these programs. Moessner and colleagues recently examined the costs of five school-​based dissemination strategies for an Internet-​based intervention for the prevention and early intervention of EDs (Moessner et al., 2016). Three hundred ninety-​ five schools were randomly assigned to one of five dissemination strategies. Strategies varied with Taylor, Fitzsimmons-Craft, Goel

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respect to intensity from only sending advertisement materials and asking the school to distribute them among students to organizing presentations and workshops at schools. Effects were defined as the number of page visits, the number of screenings conducted, and the number of registrations to the Internet-​ based intervention. More expensive strategies proved to be more cost-​effective. Cost per page visit ranged from €2.83 (introductory presentation plus workshop) to €20.37 (dissemination by student representatives/​peers). Costs per screening ranged from €3.30 (introductory presentation plus workshop) to €75.66 (dissemination by student representatives/​peers), and costs per registration ranged from €6.86 (introductory presentation plus workshop) to €431.10 (advertisement materials only). The authors note that the dissemination of an Internet-​ based intervention for prevention and early intervention is challenging and expensive. Kass, Balantekin, et al. (2017) estimated the costs of implementing a stepped-​care model for online screening, prevention, and treatment among college students. Calculations showed that the cost to prevent one ED case among those at highest risk is less than the cost of a “wait and treat” approach, even when accounting for the rate of failure. Estimates of the stepped-​ care model against standard care were also estimated to yield savings. In sum, the stepped-​care model was estimated to result in cost savings compared with standard care; however, the authors noted that future research is needed to systematically measure the costs and benefits of such a comprehensive stepped-​care model for EDs actually implemented on the college campus.

Conclusion

In conclusion, due to well-​designed studies and recent meta-​analytic reviews, we now know more about what does and does not appear to be effective in regard to ED prevention programs; these conclusions provide both guidance for future program development (e.g., cognitive-​behavioral, dissonance, and/​or healthy weight regulation material appear more effective than psychoeducation or life-​ skills alone programs) as well as highlight areas in which greater improvement is needed as discussed in the preceding text. It is critical for programs be informed by both theory and risk factor research and that these programs include skills that target and reduce risk for overweight (e.g., healthy weight regulation material) in order to ensure public health prominence for ED prevention programs. Programs that are delivered in high school environments or 264

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in schools, and that target multiple systems (e.g., peers, media, teachers/​coaches, and families) and the varied developmental needs of children and adolescents over time (i.e., onset of puberty, transitions to high school or college, increasing exposure to peer pressure and media messages about appearance, increased pressure to be thin or lean/​muscular within competitive sports) are most needed in order to ensure that a positive social support system in which weight and eating concerns are deemphasized is developed and strengthened over time. Of note is the programmatic research, developed over the past decade and informed by risk factor research and theories, from several research groups that has led to the development of programs and techniques that reduce risk factor scores and the onset of EDs, at least in older adolescent and college women at high risk for the development of EDs. Furthermore, prevention programs have not been found to cause harm. By building on the gains made in ED prevention over the past two decades and continuing to consider important issues pertaining to dissemination of materials and translation of findings to real-​world settings, it appears possible that researchers have the opportunity to achieve significant reductions in risk for EDs and ED onset in the coming decade.

Future Directions

In spite of the major gains associated with several of the reviewed programs, more work must be done to increase the effectiveness of ED prevention programs. Critical next steps appear to be (1)  developing and evaluating programs that are effective for younger age groups (i.e., preadolescent and early adolescent youth) in order to reduce and ultimately prevent the emergence of early concerns about weight and shape and early signs of disordered eating that may lead to later eating pathology during adolescents; (2) enhancing individually based programs to be incorporated into environmentally focused (e.g., school-​based) programs and to engage additional individuals who may have important and relevant developmental influences on youth, including parents, siblings, teachers, coaches, and physicians; (3) using recent mediator and moderator findings and developing effective screening tools in order to ensure that the appropriate programs are delivered to individuals presenting with different risk factors and/​or varied levels of risk for ED onset; (4) ensuring that programs are developed that target the issues relevant to disordered eating onset in males and in special

at-​risk populations, such as athletes, adolescents with type I diabetes, sexual minorities, and racial/​ ethnic minorities; and (5)  determining whether programs that focus on a broad range of risk factors and behaviors, including problems with affect regulation, binge drinking, and excessive weight concerns, can effectively reduce ED and comorbidity onset. Recent work also suggests that ED prevention efforts may be best paired with obesity prevention programs; this is appealing from a public health perspective and also recognizes the shared risk factors and overlap between disordered eating and overweight. Addressing these issues and building on two decades of important studies might actualize the public health goal of preventing EDs.

References

Abascal, L., Bruning-​Brown, J., Winzelberg, A. J., Dev, P., & Taylor, C. B. (2004). Combining universal and targeted prevention for school-​ based eating disorder programs. International Journal of Eating Disorders, 35, 1–​9. Allen, K. L., Byrne, S. M., Crosby, R. D., & Stice, E. (2016). Testing for interactive and non-​linear effects of risk factors for binge eating and purging eating disorders. Behavior Research and Therapy, 27, 40–​47. doi: 10.1016/​j.brat.2016.08.019 Aronson, E. (1980). Persuasion via self-​ justification:  Large commitments for small rewards. In L. Festinger (Ed.), Retrospection on social psychology (pp.  3–​21). Oxford, UK: Oxford University Press. Austin, S. B., Field, A. E., Wiecha, J., Peterson, K. E., & Gortmaker, S. L. (2005). The impact of a school-​based obesity prevention trial on disordered weight-​control behaviors in early adolescent girls. Archives of Pediatrics Adolescent Medicine, 159, 225–​230. Austin, S. B., Kim, J., Wiecha, J., Troped, P. J., Feldman, H. A., & Peterson, K. E. (2007). School-​ based overweight preventive intervention lowers incidence of disordered weight-​control behaviors in early adolescent girls. Archives of Pediatrics Adolescent Medicine, 161, 865–​869. Austin, S. B., Ziyadeh, N. J., Corliss, H. L., Rosario, M., Wypij, D., Haines, J.,  . . .  Field, A. E. (2009). Sexual orientation disparities in purging and binge eating from early to late adolescence. Journal of Adolescent Health, 45, 238–​245. Austin, S. B. (2012). A public health approach to eating disorders prevention: Its time for public health professionals to take a seat at the table. BMC Public Health, 12, 843. doi: 10.1186/​ 1471-​2458-​12-​854 Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice-​Hall. Bardone-​Cone, A. M., & Cass, K. M. (2007). What does viewing a pro-​anorexia website do? An experimental examination of website exposure and moderating effects. International Journal of Eating Disorders, 40, 537–​548. Becker, C. B., Bull, S., Schaumberg, K., Cauble, A., & Franco, A. (2008). Effectiveness of peer-​led eating disorders prevention:  A  replication trial. Journal of Consulting and Clinical Psychology, 76, 347–​354. Becker, C. B., Smith, L., & Ciao, A. C. (2005). Reducing eating disorder risk factors in sorority members: A randomized trial. Behavior Therapy, 36, 245–​254.

Becker, C. B., Smith, L. M., & Ciao, A. C. (2006). Peer facilitated eating disorders prevention: A randomized effectiveness trial of cognitive dissonance and media advocacy. Journal of Counseling Psychology, 53, 550–​555. Becker, C. B., Wilson, C., Williams, A., Kelly, M., McDaniel, L., & Elmquist, J. (2010). Peer-​facilitated cognitive dissonance versus healthy weight eating disorders prevention:  A  randomized comparison. Body Image, 7, 280–​288. Becker, C. B., Perez, M., Kilpela, L. S., Diedrichs, P. C., Trujillo, E., & Stice, E. (2016). Engaging stakeholder communities as body image intervention partners: The Body Project as a case example. Eating Behaviors, 62–67. doi: 10.1016/​ j.eatbeh.2016.03.015 Beintner, I., Jacobi, C., & Taylor, C. B. (2012). Effects of an Internet‐based prevention programme for eating disorders in the USA and Germany: A meta‐analytic review. European Eating Disorders Review, 20, 1–​8. Beintner, I., Jacobi, C., & Taylor, C. B. (2014). Participant adherence to the Internet-​ based prevention program StudentBodies™ for eating disorders:  A  review. Internet Interventions, 1, 26–​32. Beintner, I., Jacobi, C., Winzelberg, A. J., & Taylor, C. B. (2008). Wirksamkeit eines Internet-​gestützten Präventionsprogrammes in Deutschland und den USA. Unpublished manuscript. Bonci, C. M., Bonci, L. J., Granger, L. R., Johnson C. L., Malina, R. M., Milne, L. W.,  . . .  Vanderbunt E. M. (2008). National Athletic Trainers’ Association position statement: Preventing, detecting, and managing disordered eating in athletes. Journal of Athletic Training, 43, 80–​108. Bratland-​Sanda, S., & Sundgot-​Borgen, J. (2012). Eating disorders in athletes:  Overview of prevalence, risk factors and recommendations for prevention and treatment. European Journal of Sports Science, 13, 499–​508. Brown, T. A., & Keel, P. K. (2015). A randomized controlled trial of a peer co-​led dissonance-​based eating disorder prevention program for gay men. Behaviour Research and Therapy, 74, 1–​10. Bruning-​Brown, J., Winzelberg, A. J., Abascal, L. B., & Taylor, C. B. (2004). An evaluation of an Internet-​delivered eating disorder prevention program for adolescents and their parents. Journal of Adolescent Health, 35, 290–​296. Buchholz, A., Mack, H., McVey, G., Feder, S., & Barrowman, N. (2008). BodySense: An evaluation of a positive body image intervention on sport climate for female athletes. Eating Disorders, 16, 308–​321. Bulik, C. M., Kleiman, S. C., & Yilmaz, Z. (2016). Genetic epidemiology of eating disorders. Curr Opin Psychiatry, 6, 383–388. doi: 10.1097/YCO.0000000000000275 Carter, F. A., & Bulik, C. M. (2008). Childhood obesity prevention programs: How do they affect eating pathology and other psychological measures? Psychosomatic Medicine, 70, 363–​371. Carter, J. C., Stewart, D. A., Dunn, V. J., & Fairburn, C. G. (1997). Primary prevention of eating disorders:  Might it do more harm than good? International Journal of Eating Disorders, 22, 167–​172. Cash, T. F. (1997). The body image workbook. Oakland, CA: New Harbinger. Celio, A. A., Bryson, S., Killen, J. D., & Taylor, C. B. (2003). Are adolescents harmed when asked risky weight control behavior and attitude questions? Implications for consent procedures. International Journal of Eating Disorders, 34, 251–​254. Celio, A. A., Winzelberg, A. J., Wilfley, D. E., Eppstein-​Herald, D., Springer, E. A., Dev, P., & Taylor, C. B. (2000). Reducing

Taylor, Fitzsimmons-Craft, Goel

265

risk factors for eating disorders: Comparison of an Internet-​ and a classroom-​ delivered psychoeducational program. Journal of Consulting and Clinical Psychology, 68, 650–​657. Ciao, A. C., Loth, K., & Neumark-​ Sztainer, D. (2014). Preventing eating disorder pathology: Common and unique features of successful eating disorders prevention programs. Current Psychiatry Reports, 16, 453. doi:  10.1007/​ s11920-​014-​0453-​0 Clarke, G. N., Hornbrook, M., Lynch, F., Polen, M., Gale, J., Beardslee, W., O’Connor, E., & Seeley, J. (2001). A randomized trial of a group cognitive intervention for preventing depression in adolescent offspring of depressed parents. Archives of General Psychiatry, 58, 1127–​1134. Collins, L. (2008, May 12). Pixel perfect: Pascal Dangin’s virtual reality. The New Yorker. Coughlin, J. W., & Kalodner, C. (2006). Media literacy as a prevention intervention for college women at low-​or high-​risk for eating disorders. Body Image, 3, 35–​43. Crow, S., Kendall, D., Praus, B., & Thuras, P. (2000). Binge eating and other psychopathology in patients with type II diabetes mellitus. International Journal of Eating Disorders, 20, 222–​226. Culbert K. M., Racine, S. E., & Klump, K. L. (2015). Research Review:  What we have learned about the causes of eating disorders:  A  synthesis of sociocultural, psychological, and biological research. Journal of Child Psychology and Psychiatry, 56, 1141–​1164. doi: 10.1111/​jcpp.12441 Custers, K., & Van den Bulck, J. (2009). Viewership of pro-​ anorexia websites in seventh, ninth and eleventh graders. European Eating Disorders Review, 17, 214–​219. doi: 10.1002/​erv.910 Doris, E., Shekriladze, L., Javakhishvili, N., Jones, R., Treasure, J., & Tchanturia, K. (2015). Is cultural change associated with eating disorders? A systematic review of the literature. Eating and Weight Disorders, 10, 149–​160. doi:  10.1007/​ s40519-​01500189-​9 Fairburn, C. G., & Cooper, Z. (1993). The eating disorder examination (12th ed.). New York, NY: Guilford Press. Feldman, M. B., & Meyer, I. H. (2007). Eating disorders in diverse lesbian, gay, and bisexual populations. International Journal of Eating Disorders, 40, 218–​226. Festinger, L. (1957). A theory of cognitive dissonance. Palo Alto, CA: Stanford University Press. Festinger, L. (1962). Cognitive dissonance. Scientific American, 207, 93–​102. Field, A. E., Camargo, C. A., Taylor, C. B., Berkey, C. S., & Colditz, G. A. (1999). Relation of peer and media influences to the development of purging behaviors among preadolescent and adolescent girls. Archives of Pediatrics Adolescent Medicine, 153, 1184–​1189. Frederickson, B., & Roberts, T. A. (1997). Objectification theory:  Toward understanding women’s lived experiences and mental health risks. Psychology of Women Quarterly, 21, 173–​206. Goldschmidt, A. B., Aspen, V. P., Sinton, M. M., Tanofsky-​Kraff, M., & Wilfley, D. E. (2008). Disordered eating attitudes and behaviors in overweight youth. Obesity, 16, 257–​264. Grabe, S., Ward, L. M., & Hyde, J. S. (2008). Role of the media in body image concerns among women: A meta-​analysis of experimental and correlational studies. Psychological Bulletin, 134, 460–​476. Green, M., Scott, N., Diyankova, I., Gasser, C., & Pederson, E. (2005). Eating disorder prevention:  An experimental

266

Prevention

comparison of high level dissonance, low level dissonance, and no-​treatment control. Eating Disorders, 13, 157–​170. Greif, R., Becker, C. B., & Hildebrandt, T. (2015). Reducing eating disorder risk factors: A pilot effectiveness trial of a train-​ the-​trainer approach to dissemination and implementation. International Journal of Eating Disorders, 48, 1122–​1131. Guarda, A. S. (2008). Treatment of anorexia nervosa:  Insights and obstacles. Physiology and Behavior, 94, 113–​120. Haines, J., & Neumark-​Sztainer, D. (2006). Prevention of obesity and eating disorders: A consideration of shared risk factors. Health Education Resource, 21, 770–​782. Halliwell, E., & Diedrichs, P. C. (2014). Testing a dissonance body image intervention among young girls. Health Psychology, 33, 201. Halmi, K. A., Casper, R. C., Eckert, E. D., Goldberg, S. C., & Davis, J. M. (1979). Unique features associated with age of onset of anorexia nervosa. Psychiatry Research, 1, 209–​215. doi:10.1016/​0165-​1781(79)90063-​5 Horowitz, J. L., & Garbe, J. (2006). The prevention of depressive symptoms in children and adolescents: A meta-​analytic review. Journal of Consulting and Clinical Psychology, 74, 401–​415. Ikeda, J. P., Crawford, P. B., & Woodward-​Lopez, G. (2006). BMI screening in schools:  Helpful or harmful. Health Education Resources, 21, 761–​769. Jacobi, C., Hayward, C., de Zwaan, M., Kraemer, H. C., & Agras, W. S. (2004). Coming to terms with risk factors for eating disorders:  Application of risk terminology and suggestions for a general taxonomy. Psychological Bulletin, 130, 19–​65. Jacobi, C., Abascal, L., & Taylor, C. B. (2004). Screening for eating disorders and high-​risk behavior: Caution. International Journal of Eating Disorders, 36, 280–​295. Jacobi, C., Morris, L., Beckers, C., Bronisch-​Holtze, J., Winter, J., Winzelberg, A. J., & Taylor, C. B. (2007). Maintenance of Internet-​based prevention: A randomized controlled trial. International Journal of Eating Disorders, 40, 114–​119. Jacobi, C., Bryson S. W., Wilfley, D., Kraemer, H. C., & Taylor, C. B. (2011). Who is really at risk: Identifying risk factors for subthreshold and full syndrome eating disorders in a high-​risk sample. Psychological Medicine, 41, 1939–​1949. doi: 10.1017/​S0033291710002631 Johnson, C., Burke, C., Brinkman, S., & Wade, T. (2016). Effectiveness of a school-​ based mindfulness program for transdiagnostic prevention in young adolescents. Behaviour Research and Therapy, 81, 1–​11. doi: 10.1016/​ j.brat.2016.03.002. Jones, J. M., Lawson, M. L., Daneman, D., Olmsted, M. P., & Rodin, G. (2000). Eating disorders in adolescent females with and without type 1 diabetes:  Cross sectional study. British Medical Journal, 320, 1563–​1566. Jones, M., Luce, K. H., Osborne, M. I., Taylor, K., Cunning, D., Doyle, A. C.,  . . .  Taylor, C. B. (2008). Randomized, controlled trial of an Internet-​facilitated intervention for reducing binge eating and overweight in adolescents. Pediatrics, 121, 453–​462. Jones, M., Taylor, L. K., Kass, A. E., Burrows, A., Williams, J., Wilfley, D. E., & Taylor, C. B. (2014). Healthy weight regulation and eating disorder prevention in high school students:  a universal and targeted Web-​based intervention. Journal of Medical Internet Research, 16, e57. doi: 10.2196/​ jmir.2995 Jones, M., Völker, U., Lock, J., Taylor, C. B., & Jacobi, C. (2012). Family-​ based early intervention for anorexia

nervosa. European Eating Disorders Review, 20, e137–​43. doi: 10.1002/​erv.2167 Kass, A. E., Balantekin, K. N., Fitzsimmons-​Craft, E. E., Jacobi, C., Wilfley, D. E., & Taylor, C. B. (2017). The economic case for digital interventions for eating disorders among college students. International Journal of Eating Disorders, 50(3), 250– 258. doi: 10.1002/eat.22680 Kass, A. E., Jones, M., Kolko, R. P., Altman, M., Fitzsimmons-​ Craft, E. E., Eichen, D. M., . . . Wilfley, E. E. (2017). Universal prevention efforts should address eating disorder pathology across the weight spectrum: Implications for screening and intervention on college campuses. Eating Behaviors, 25, 74–80. doi: 10.1016/​j.eatbeh.2016.03.019 Kass, A. E., Trockel, M., Safer, D. L., Sinton, M. M., Cunning, D., Rizk, M. T.,  . . .  Taylor, C. B. (2014). Internet-​based preventive intervention for reducing eating disorder risk: A randomized controlled trial comparing guided with unguided self help. Behaviour Research and Therapy, 63, 90–​98. Keel, P. K., & Haedt, A. (2008). Evidence-​based psychosocial treatments for eating problems and eating disorders. Journal of Clinical Child and Adolescent Psychology, 37, 39–​61. Killen, J. D., Taylor, C. B., Hammer, L. D., Litt, I., Wilson, D. M., Rich, T.,  . . .  Varady, A. (1993). An attempt to modify unhealthful eating attitudes and weight regulation practices of young adolescent girls. International Journal of Eating Disorders, 13, 369–​384. Killen, J. D., Taylor, C. B., Hayward, C., Haydel, K. F., Wilson, D. M., Hammer, L.,  . . .  Strachowski, D. (1996). Weight concerns influence the development of eating disorders: A 4-​ year prospective study. Journal of Consulting and Clinical Psychology, 64, 936–​940. Killen, J. D., Taylor, C. B., Hayward, C., Wilson, D. M., Haydel, F., Hammer, L. D.,  . . .  Kraemer, H. (1994). Pursuit of thinness and onset of eating disorder symptoms in a community sample of adolescent girls: A three-​year prospective analysis. International Journal of Eating Disorders, 16, 227–​238. Kraemer, H. C., Wilson, G. T., Fairburn, C. G., & Agras, W. S. (2002). Mediators and moderators of treatment effects in randomized clinical trials. Archives of General Psychiatry, 59, 877–​883. Leippe, M. R. (1994). Generalization of dissonance reduction:  Decreasing prejudice through induced compliance. Journal of Personality and Social Psychology, 67, 395–​413. Lock, J., & le Grange, D. (2005). Family-​based treatment of eating disorders. International Journal of Eating Disorders, 37, S64–​67; discussion S87–​S69. Loucas, C. E., Fairburn, C. G., Whittington, C., Pennant, M. E., Stockton, S., & Kendall, T. (2014). E-​therapy in the treatment and prevention of eating disorders:  A  systematic review and meta-​analysis. Behaviour research and therapy, 63, 122–​131. Luce, K. H., Osborne, M. I., Winzelberg, A. J., Das, S., Abascal, L. B., Celio, A. A.,  . . .  Taylor, C. B. (2005). Application of an algorithm-​driven protocol to simultaneously provide universal and targeted prevention programs. International Journal of Eating Disorders, 37, 220–​226. Lynch, F. L., Hornbrook, M., Clarke, G. N., Perrin, N., Polen, M. R., O’Connor, E., & Dickerson, J. (2005). Cost-​ effectiveness of an intervention to prevent depression in at-​ risk teens. Archives of General Psychiatry, 62, 1241–​1248. Mann, T., Nolen-​ Hoeksema, S., Huang, K., Burgard, D., Wright, A., & Hanson, K. (1997). Are two interventions worse than none? Joint primary and secondary prevention

of eating disorders in college females. Healthy Psychology, 16, 215–​225. Manwaring, J. L., Bryson, S. W., Goldschmidt, A. B., Winzelberg, A. J., Luce, K. H.,  . . .  Taylor, C. B. (2008). Do adherence variables predict outcome in an online program for the prevention of eating disorders? Journal of Consulting and Clinical Psychology, 76, 341–​346. Martinsen, M., Bahr, R., Børresen, R., Holme, I., Pensgaard, A. M., & Sundgot-​Borgen, J. (2014). Preventing eating disorders among young elite athletes:  A  randomized controlled trial. Medicine Science in Sports and Exercise, 46, 435–​447. doi: 10.1249/​MSS.0b013e3182a702fc Martinsen M., Sherman, R. T., Thompson, R. A., & Sundgot-​ Borgen, J. (2015). Coaches’ knowledge and management of eating disorders:  A  randomized controlled trial. Medical Science in Sports and Exercise, 47, 1070–​1078. doi: 10.1249/​ MSS.0000000000000489 Martinsen, M., & Sundgot-​Borgen, J. (2013). Higher prevalence of eating disorders among adolescent elite athletes than controls. Medicine and Science in Sports and Exercise, 45, 1188–​1197. Matusek, J. A., Wendt, S. J., & Wiseman, C. V. (2004). Dissonance thin-​ideal and didactic healthy behavior eating disorder prevention programs:  Results from a controlled trial. International Journal of Eating Disorders, 36, 376–​388. McLean, S. A., Paxton, S. J., Wertheim, E. H. (2016). The role of media literacy in body dissatisfaction and disordered eating: A systematic review. Body Image, 19, 9–​23. doi: 10.1016/​ j.bodyim.2016.08.002 McVey, G. L., Davis, R., Tweed, S., & Shaw, B. F. (2004). Evaluation of a school-​based program designed to improve body image satisfaction, global self-​ esteem, and eating attitudes and behaviors:  A  replication study. International Journal of Eating Disorders, 36, 1–​11. McVey, G. L., Lieberman, M., Voorberg, N., Wardrope, D., & Blackmore, E. (2003). School-​based peer support groups: A new approach to the prevention of disordered eating. Eating Disorders, 11, 169–​185. McVey, G. L., Lieberman, M., Voorberg, N., Wardrope, D., Blackmore, E., & Tweed, S. (2003). Replication of a peer support program designed to prevent disordered eating: Is a life skills approach sufficient for all middle school students? Eating Disorders, 11, 187–​195. McVey, G. L., Tweed, S., & Blackmore, E. (2007). Healthy Schools-​Healthy Kids: A controlled evaluation of a comprehensive universal eating disorder prevention program. Body Image, 4, 115–​136. Meyer, I. H. (2003). Prejudice, social stress, and mental health in lesbian, gay and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129, 674–​697. Micali, N., Hagberg, K. W., Petersen, I., & Treasure, J. L. (2013). The incidence of eating disorders in the UK in 2000-​ 2009:  Findings from the General Practice Research Database. BJC Open, 3, e002646. doi:10.1136/​ bmjopen-​2013-​002646 Morrison, M. A., Morrison, T. G., & Sager, C. L. (2004). Does body dissatisfaction differ between gay men and lesbian women and heterosexual men and women? A meta-​analytic review. Body Image, 1, 127–​138. Moessner, M., Minarik, C., Ozer, F., & Bauer, S. (2016). Effectiveness and cost-​ effectiveness of school-​ based dissemination strategies of an Internet-​ based program for the prevention and early intervention in eating

Taylor, Fitzsimmons-Craft, Goel

267

disorders:  A  randomized trial. Preventive Science, 17, 306–​ 313. doi: 10.1007/​s11121-​015-​0619-​y Musiat, P., Conrod, P., Treasure, J., Tylee, A., Williams, C., & Schmidt, U. (2014). Targeted prevention of common mental health disorders in university students:  Randomised controlled trial of a transdiagnostic trait-​focused web-​based intervention. PLoS One, 9, e93621. doi:  10.1371/​journal. pone.0093621 Neumark-​ Sztainer, D. (2005). Can we simultaneously work toward the prevention of obesity and eating disorders in children and adolescents? International Journal of Eating Disorders, 38, 220–​227. Neumark-​Sztainer, D., Sherwood, N. E., Coller, T., & Hannan, P. J. (2000). Primary prevention of disordered eating among preadolescent girls:  Feasibility and short-​ term effect of a community-​based intervention. Journal of the American Dietetic Association, 100, 1466–​1473. Neumark-​Sztainer, D., Wall, M. M., Haines, J. I., Story, M. T., Sherwood, N. E., & van den Berg, P. A. (2007). Shared risk and protective factors for overweight and disordered eating in adolescents. American Journal of Preventive Medicine, 33, 359–​369. O’Dea, J. A. (2005). Prevention of child obesity: “First, do no harm.” Health Education Resource, 20, 259–​265. Ogden, C. L., Carroll, M. D., Fryar, C. D., & Flegal, K. M. (2015). Prevalence of obesity among adults and youth: United States, 2011–​2 015. NCHS Data Brief, 219, 1–​8 . Oswalt, S. B., & Wyatt, T. J. (2007). Mirror, mirror, help me like my body:  Examining a body image media campaign. Californian Journal of Health Promotion, 5, 135–​147. Perez, M., Becker, C. B., & Ramirez, A. (2010). Transportability of an empirically supported dissonance-​ based prevention program for eating disorders. Body Image, 7, 179–​186. Peterson, R. D., Grippo, K. P., & Tantleff-​Dunn, S. (2008). Empowerment and powerlessness: A closer look at the relationship between feminism, body image and eating disturbance. Sex Roles, 58, 639–​648. Pike, K. M., Hilbert, A., Wilfley, D. E., Fairburn, C. G., Dohm, F. A., Walsh, B. T., & Striegel-​Moore, R. (2007). Toward an understanding of risk factors for anorexia nervosa:  A  case-​ control study. Psychological Medicine, 10, 1–​11. Piran, N. (1999). Eating disorders: A trial of prevention in a high risk school setting. Journal of Primary Prevention, 10, 75–​90. Piran, N. (2010). A feminist perspective on risk factor research and on the prevention of eating disorders. Journal of Treament and Prevention, 18, 183–​198. Pratt, B. M., & Woolfenden, S. R. (2002). Interventions for preventing eating disorders in children and adolescents. Cochrane Database Systematic Reviews, (2):CD002891. Puhl, R. M., & Heuer, C. A. (2010). Obesity stigma: Important considerations for public health. American Journal of Public Health, 100, 1019–​1028. doi: 10.2105/​ AJPH.2009.159491. Record, K. L., & Austin, S. B. (2016). “Paris thin”:  A  call to regulate life-​threatening starvation of runway models in the US fashion industry. American Journal of Public Health, 106, 205–​206. doi: 10.2105/​AJPH.2015.302950 Regan, P. C., & Cachelin, F. M. (2006). Binge eating and purging in a multi-​ethnic community sample. International Journal of Eating Disorders, 39, 523–​526. Rodriguez, R., Marchand, E., Ng, J., & Stice, E. (2008). Effects of a cognitive dissonance-​based eating disorder prevention

268

Prevention

program are similar for Asian American, Hispanic, and White participants. International Journal of Eating Disorders, 41, 618–​625. Roehrig, M., Thompson, J. K., Brannick, M., & van den Berg, P. (2006). Dissonance-​based eating disorder prevention program: A preliminary dismantling investigation. International Journal of Eating Disorders, 39, 1–​10. Saffran, K., Fitzsimmons-​Craft, E. E., Kass, A. E., Wilfley, D. E., Taylor, C. B., & Trockel, M. (2016). Facebook usage among those who have received treatment for an eating disorder in a group setting. International Journal of Eating Disorders, 49, 764–​777. doi: 10.1002/​eat.22567 Sanci, L., Coffey, C., Olsson, C., Reid, S., Carlin, J. B., & Patton, G. (2008). Childhood sexual abuse and eating disorders in females:  Findings from the Victorian Adolescent Health Cohort Study. Archives of Pediatrics and Adolescent Medicine, 162, 261–​267. Shaw, H., Ramirez, L., Trost, A., Randall, P., & Stice, E. (2004). Body image and eating disturbances across ethnic groups: More similarities than differences. Psychology of Addictive Behaviors, 18, 12–​18. Sherwood, N. E., Harnack, L., & Story, M. (2000). Weight-​loss practices, nutrition beliefs, and weight-​loss program preferences of urban American Indian women. Journal of the American Dietetic Association, 100, 442–​446. Shuttlesworth, M. E., & Zotter, D. (2011). Disordered eating in African American and Caucasian women: The role of ethnic identity. Journal of Black Studies, 42, 906–​922. Speranza, M., Atger, F., Corcos, M., Loas, G., Guilbaud, O., Stéphan, P.,  . . .  Jeammet, P. (2003). Depressive psychopathology and adverse childhood experiences in eating disorders. European Psychiatry, 18, 377–​383. Springer, E. A., Winzelberg, A. J., Perkins, R., & Taylor, C. B. (1999). Effects of a body image curriculum for college students on improved body image. International Journal of Eating Disorders, 26, 13–​20. Stein, N. (1999). Classrooms and courtrooms:  Facing sexual harassment in K-​ 12 schools. New  York, NY:  Teachers College Press. Stice, E., & Agras, W. S. (1998). Predicting onset and cessation of bulimic behaviors during adolescence:  A  longitudinal grouping analysis. Behavior Therapy, 29, 257–​276. Stice, E., Butryn, M. L., Rohde, P., Shaw, H., & Marti, C. N. (2013). An effectiveness trial of a new enhanced dissonance eating disorder prevention program among female college students. Behaviour Research and Therapy, 51, 862–​871. Stice, E., Chase, A., Stormer, S., & Appel, A. (2001). A randomized trial of a dissonance-​based eating disorder prevention program. International Journal of Eating Disorders, 29, 247–​262. Stice, E., Durant, S., Rohde, P., & Shaw, H. (2014). Effects of a prototype Internet dissonance-​based eating disorder prevention program at 1-​and 2-​year follow-​up. Health Psychology, 33, 1558–​1567. Stice, E., Marti, C. N., & Rohde, P. (2013). Prevalence, incidence, impairment, and course of the proposed DSM-​5 eating disorder diagnoses in an 8-​year prospective community study of young women. Journal of Abnormal Psychology, 122, 445–​457. doi:10.1037/​a0030679 Stice, E., Marti, N., Shaw, H., & O’Neil, K. (2008). General and program-​specific moderators of two eating disorder prevention programs. International Journal of Eating Disorders, 41, 611–​617.

Stice, E., Marti, C. N., Spoor, S., Presnell, K., & Shaw, H. (2008). Dissonance and healthy weight eating disorder prevention programs:  Long-​ term effects from a randomized efficacy trial. Journal of Consulting and Clinical Psychology, 76, 329–​340. Stice, E., Mazotti, L., Weibel, D., & Agras, W. S. (2000). Dissonance prevention program decreases thin-​ideal internalization, body dissatisfaction, dieting, negative affect, and bulimic symptoms: A preliminary experiment. International Journal of Eating Disorders, 27, 206–​217. Stice, E., Presnell, K., Gau, J., & Shaw, H. (2007). Testing mediators of intervention effects in randomized controlled trials:  An evaluation of two eating disorder prevention programs. Journal of Consulting and Clinical Psychology, 75, 20–​32. Stice, E., Rohde, P., Durant, S., & Shaw, H. (2012). A preliminary trial of a prototype Internet dissonance-​based eating disorder prevention program for young women with body image concerns. Journal of Consulting Clinical Psychology, 80, 907–​916. Stice, E., Rohde, P., Gau, J., & Shaw, H. (2009). An effectiveness trial of a dissonance-​based eating disorder prevention program for high-​risk adolescent girls. Journal of Consulting and Clinical Psychology, 77, 825. Stice, E., Rohde, P., & Shaw, H. (2012). The Body Project:  A  dissonance-​ based eating disorder intervention (2nd ed.). Programs That Work. New  York, NY:  Oxford University Press. Stice, E., Rohde, P., Shaw, H., & Gau, J. (2011). An effectiveness trial of a selected dissonance-​based eating disorder prevention program for female high school students:  Long-​term effects. Journal of Consulting and Clinical Psychology, 79, 500. Stice, E., & Shaw, H. (2004). Eating disorder prevention programs:  A  meta-​analytic review. Psychological Bulletin, 130, 206–​227. Stice, E., Shaw, H., Becker, C. B., & Rohde, P. (2008). Dissonance-​based interventions for the prevention of eating disorders:  Using persuasion principles to promote health. Preventive Science, 9, 114–​128. Stice, E., Shaw, H., Burton, E., & Wade, E. (2006). Dissonance and healthy weight eating disorder prevention programs: A randomized efficacy trial. Journal of Consulting and Clinical Psychology, 74, 263–​275. Stice, E., Shaw, H., & Marti, C. N. (2007). A meta-​analytic review of eating disorder prevention programs: Encouraging findings. Annual Review of Clinical Psychology, 3, 207–​231. Stice, E., Trost, A., & Chase, A. (2003). Healthy weight control and dissonance-​based eating disorder prevention programs: Results from a controlled trial. International Journal of Eating Disorders, 33, 10–​21. Striegel-​Moore, R. H., Fairburn, C. G., Wilfley, D. E., Pike, K. M., Dohm, F. A., & Kraemer, H. (2005). Toward an understanding of risk factors for binge-​eating disorder in black and white women:  A  community-​based case-​control study. Psychological Medicine, 35, 907–​917. Taylor, C. B., Bryson, S., Luce, K. H., Cunning, D., Doyle, A. C., Abascal, L. B.,  . . .  Wilfley, D. E. (2006). Prevention of eating disorders in at-​risk college-​age women. Archives of General Psychiatry, 63, 881–​888. Taylor, C. B., Kass, A., Trockel, M. E., Cunning, D., Weisman, H., Bailey, J.,   .  .  .  Wilfley, D. E. (2016). Reducing eating disorder onset in a very high risk sample with significant comorbid depression:  A  randomized controlled trial.

Journal of Consulting and Clinical Psychology, 84, 402–​414. doi: 10.1037/​ccp0000077 Tiggemann, M. (2013). Objectification theory:  Of relevance for eating disorder researchers and clinicians? Clinical Psychologist, 17, 35–​45. Tiggemann, M., & Kuring, J. K. (2004). The role of body objectification in disordered eating and depressed mood. British Journal of Clinical Psychology, 43, 299–​311. Völker, U., Jacobi, C., Trockel, M. T., & Taylor, C. B. (2014). Moderators and mediators of outcome in Internet-​ based indicated prevention for eating disorders. Behaviour Research and Therapy, 63, 114–​121. Volpe, U., Tortorella, A., Manchia, M., Monteleone, A. M., Albert, U., & Monteleone, P. (2016). Eating disorders: What age at onset? Psychiatry Research, 238, 225–​227. doi:10.1016/​ j.psychres.2016.02.048 Wade, T. D., Davidson, S., & O’Dea, J. A. (2003). A preliminary controlled evaluation of a school-​based media literacy program and self-​esteem program for reducing eating disorder risk factors. International Journal of Eating Disorders, 33, 371–​383; discussion 384–​377. Watson, H. J., Joyce, T., French, E., Willan, V., Kane, R. T., Tanner‐Smith, E. E., . . . Egan, S. J. (2016). Prevention of eating disorders: A systematic review of randomized, controlled trials. International Journal of Eating Disorders, 49(9), 833–862. doi:10.1002/​eat.22577 Wertheim, E. H., Koerner, J., & Paxton, S. J. (2001). Longitudinal predictors of restrictive eating and bulimic tendencies in three different age groups of adolescent girls. Journal of Youth and Adolescence, 30, 69–​81. Whisenhunt, B. L., Williamson, D. A., Drab-​Hudson, D. L., & Walden, H. (2008). Intervening with coaches to promote awareness and prevention of weight pressures in cheerleaders. Eating and Weight Disorders, 13, 102–​110. Wichstrom, L. (2000). Psychological and behavioral factors unpredictive of disordered eating:  A  prospective study of the general adolescent population in Norway. International Journal of Eating Disorders, 28, 33–​42. Wichstrom, L. (2006). Sexual orientation as a risk factor for bulimic symptoms. International Journal of Eating Disorders, 39, 448–​453. Wilfley, D. E., Agras, W. S., & Taylor, C. B. (2013). Reducing the burden of eating disorders: A model for population‐based prevention and treatment for university and college campuses. International Journal of Eating Disorders, 46, 529–​532. Wilfley, D. E., & Cohen, L. R. (1997). Psychological treatment of bulimia nervosa and binge eating disorder. Psychopharmacology Bulletin, 33, 437–​454. Wilksch, S. M., Durbridge, M. R., & Wade, T. D. (2008). A preliminary controlled comparison of programs designed to reduce risk of eating disorders targeting perfectionism and media literacy. Journal of the American Academy of Child and Adolescent Psychiatry, 47, 939–​947. Wilksch, S. M., & Wade, T. D. (2009). Reduction of shape and weight concern in young adolescents: A 30-​month controlled evaluation of a media literacy program. Journal of the American Academy of Child and Adolescent Psychiatry, 48, 651–​681. Wilksch, S. M., Paxton, S. J., Bryne, S. M., Austin, S. B., Mclean, S. A., Thompson, K. M.,  . . .  Wade, K. D. (2015). Prevention across the spectrum:  A  randomized controlled trial of three programs to reduce risk factors for both eating disorders and obesity. Psychological Medicine, 45, 1811–​ 1823. doi:10.1017/​S003329171400289X

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Wilson, G. T. (2005). Psychological treatment of eating disorders. Annual Review of Clinical Psychology, 1, 439–​465. Wilson, G. T., & Fairburn, C. G. (1993). Cognitive treatment for eating disorders. Journal of Consulting and Clinical Psychology, 61, 261–​269.

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Winzelberg, A. J., Eppstein, D., Eldredge, K. L., Wilfley, D., Dasmahapatra, R., Dev, P., & Taylor, C. B. (2000). Effectiveness of an Internet-​based program for reducing risk factors for eating disorders. Journal of Consulting and Clinical Psychology, 68, 346–​350.



CH A PT E R

 Cognitive-​Behavioral Therapy for Eating Disorders

14

G. Terence Wilson

Abstract This chapter discusses cognitive-​behavioral therapy (CBT) as applicable to all eating disorders in adults and adolescents. It reviews the most recent manual-​based enhanced CBT (CBT-​E), which not only appears to be more effective than the previous protocol but also is applicable to all eating disorders and enhances individualizing treatment even within specific diagnoses. The chapter considers the effectiveness of CBT compared to behavior weight loss treatment, pharmacotherapy, and interpersonal psychotherapy (IPT). It considers patient access to evidence-​based CBT and discusses effective dissemination and implementation of competently administered CBT-​E as a research priority. It describes and considers the effectiveness of a guided self-​help form of CBT (CBTgsh), which provides a brief, cost-​ effective, acceptable, and scalable intervention. It describes possible further development of CBTgsh as a scalable e-​therapy (using Internet and mobile devices) given that it is a program-​based intervention that can be widely implemented by nonspecialists. Key Words:  cognitive-​behavioral therapy, treatment outcome, transdiagnostic, bulimia nervosa, binge eating disorder, guided self-​help, cost-​effectiveness, treatment scalability, Internet treatment, dissemination

The present chapter focuses on cognitive-​ behavioral therapy (CBT) for eating disorders in adults and adolescents. As formulated in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-​5) of the American Psychiatric Association, the eating disorders are anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED). In addition CBT is also well suited to the treatment of what DSM-​5 labels as “Other Specified Feeding or Eating Disorder” in which all the required diagnostic criteria for the disorders listed above are met with the exception of one or two specified criteria, for example, BN or BED of “low frequency and/​or limited duration” (American Psychiatric Association, 2013, p. 353).

Bulimia Nervosa Treatment Model

The standard CBT model of BN spells out the psychopathological processes that are hypothesized

to maintain the disorder (Fairburn, 2008). The core psychopathology is assumed to be abnormal overevaluation of the importance of body shape and weight that then leads to dysfunctional dieting and other extreme, unhealthy weight-​control behaviors such as purging. The dysfunctional dieting, in turn, predisposes the person to binge eating. Purging is primarily a function of the person trying to compensate for the caloric intake involved in binge eating but can also come to serve as a means of trying to reduce or cope with feelings of negative affect. The CBT treatment derives directly from this model and is a theory-​driven, manual-​based intervention that is targeted at eliminating the psychopathological processes that maintain the disorder, namely, replacing dysfunctional dieting with a regular and healthy pattern of eating, ceasing purging and other extreme forms of weight control, and decreasing overevaluation of body shape and weight (Fairburn, Marcus, & Wilson, 1993; Wilson, Fairburn, & 271

Agras, 1997). The model and the derivative manual-​ based treatment were subsequently revised and extended by Fairburn (2008) as “enhanced behavior therapy” (CBT-​E). A major change from the original first-​generation treatment was the reformulation of it as an intervention not specifically for BN but for all eating disorder psychopathology. A transdiagnostic treatment, CBT-​E focuses on the common processes that maintain different forms of eating disorder psychopathology as opposed to the traditional categorical diagnoses of DSM-​IV and DSM-​ 5. Treatment planning is guided not by matching therapy to different diagnoses, but by “personalized treatment formulations” (Fairburn, Cooper, & Shafran, 2008). This formulation provides an especially good fit with CBT as a treatment in that it underscores the importance of the functional analysis of individual cases of eating disorder—​a seminal feature of behavior therapy from its beginnings. Fairburn (2008) described two main versions of CBT-​E: a “focused” (CBT-​Ef ) and a “broad” treatment (CBT-​Eb). The former is very similar to the earlier 1993 manual but has two main changes. First, it details a revised strategy and methods for addressing overevaluation of body weight and shape. Second, it provides an explicit treatment module for what is called “mood intolerance” as a specific trigger of binge eating and purging. The latter, CBT-​Eb, is based on a broader model of the problems (comorbid disorders) that are widely believed to maintain eating disorders or at the very least complicate their treatment. These are perfectionism, low self-​esteem, and interpersonal difficulties, and CBT-​Eb provides an expanded range of strategies for treating these additional maintaining mechanisms. It must be emphasized that a major advantage of CBE-​E is that it greatly assists the therapist in individualizing the treatment within the general framework of a structured protocol so that it matches the patient’s problems. It has long been argued—​albeit widely rebutted (e.g., Shafran et al., 2009; Wilson, 1996)—​that the use of treatment manuals necessarily results in an inflexible and uniform therapy approach with all patients. Finally, CBT-​E directly addresses the all-​important issue of the patient’s motivation for addressing and working to overcome their eating disorder. It engages even the most ambivalent patients by providing a comprehensible and credible account of why their eating problem is self-​perpetuating and what needs to be changed to overcome it. As Fairburn (2008) has explained, competently conducted CBT-​E is inherently motivating. There is no need to add some 272

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alternative treatment to CBT in order to achieve optimal results (Wilson & Schlam, 2004). It is important to emphasize that the Fairburn (2008) model of the maintenance of BN—​ and eating disorder psychopathology in general—​ is supported by the findings of scientific research on the underlying psychopathology of eating disorders. In their influential analysis of the efficacy of evidence-​based CBT for mental disorders as a whole, Layard and Clark (2014) reached the following conclusion:  “Much of the success of CBT results from its foundation in basic psychological research   .  .  .  researchers ask the question ‘What keeps the problem going?’ The psychological processes they identify when answering this question then become the main targets of therapy” (p. 136). Consider the example of dysfunctional dieting, or what is often referred to as “dietary restraint,” that has been shown to be a key risk factor and maintaining mechanism in BN. It is a core component of the CBT model and a primary and early target of CBT strategies for eating disorders. The goal is to reduce dietary restraint and help the patient accept that eating normally and flexibly does not result in a loss of control. The inclusion of so-​called forbidden or trigger foods into a regular meal pattern is planned and deliberate. Controlled outcome research has shown that reducing dietary restraint is a partial mediator of change in the treatment of BN (Wilson, Fairburn, Agras, Walsh & Kraemer, 2002). This model can be contrasted with the addiction approach to eating disorders. The core principle of the latter is the need for dietary restriction—​increased restraint. Specific foods that are alleged to trigger binge eating and loss of control must be avoided. It becomes irrelevant what techniques are then used to promote food avoidance, as it addresses the wrong problem. This approach is diametrically opposed to the CBT formulation of maintaining mechanisms. No evidence exists showing the efficacy of the addiction model for eating disorders (Wilson, 2010).

Treatment Efficacy

The literature on controlled randomized trials of manual-​based CBT for BN has been extensively reviewed in the past, as summarized in my chapter in the 1st edition of this Handbook—​Wilson (2010). Arguably the most comprehensive analysis of the evidence on the efficacy of treatment for eating disorders was the NICE guidelines from the United Kingdom (National Institute for Clinical Excellence, 2004). The NICE guidelines comprise

a series of recommendations that are the product of an interdisciplinary and rigorous process that includes professional mental health organizations, academic institutions, and NICE itself. The recommendations are given a grade ranging from “A” (reflecting strong empirical support provided by well-​ conducted RCTs) to “C” (reflecting expert opinion in absence of strong empirical data). The NICE guidelines assigned manual-​based CBT for BN a rarely given methodological grade of “A.” Research studies published since 2010 have provided stronger support for the efficacy of CBT for BN. Comparative Treatment Research Research prior to 2010 had shown that CBT was more effective than either antidepressant medication or other psychological treatment (Wilson, 2010). The focus here is on two major more recent comparative treatment outcome studies. The first was randomized controlled trial in Copenhagen that compared CBT-​Ef with psychoanalytic psychotherapy in the treatment of 70 patients with BN (Poulsen et al., 2014). The CBT-​E comprised 20 individual sessions over 5 months whereas psychoanalytic psychotherapy entailed more than 70 weekly sessions over a 2-​year period. The investigators ensured that both treatments were implemented in a highly competent fashion. Therapists received initial training from the experts who had developed each of the two treatments, and the therapists were then closely supervised. In CBT-​E this was off-​site via videoconferencing from Oxford. The psychoanalytic psychotherapy therapists were experienced in their approach (17  years on average), whereas the CBT-​E therapists were much less experienced—​2 years on average. Adherence ratings conducted by independent raters were strong and specific for each treatment. The results of this study were strikingly unambiguous. After 5 months (post-​treatment for CBT-​ E) 42% of CBT-​E patients had completely ceased binge eating and purging versus only 6% of those in the psychoanalytic psychotherapy condition. At the 2-​year point (post-​treatment for psychoanalytic psychotherapy) the respective numbers of patients in remission were 44% for CBT-​E and 15% for psychoanalytic psychotherapy. At 5 months CBT-​E had also produced significantly greater improvements in other eating disorder features and general psychopathology than psychoanalytic psychotherapy. It has been commonplace in the comparative outcome literature to attribute differences between

therapies to allegiance effects rather than fundamental effects of the treatments themselves (Luborsky et al., 1999). In this well-​designed study by Poulsen et al. (2014) the putative role of allegiance effects can be dismissed. As Hollon and Wilson (2014) highlight in their critical analysis of this study, the psychoanalytic psychotherapy treatment enjoyed every comparative advantage such as more sessions over a much longer time period, implemented at its home site in Copenhagen, and the use of more experienced therapists. Finally, two aspects of the efficacy of CBT-​E should be stressed: First, a remission rate higher than earlier studies using the first-​generation CBT manual (e.g., Agras, Walsh, Fairburn, Wilson, & Kraemer, 2000), and second, the impressive maintenance of improvement in CBT-​E over the 2-​year period. The second recent comparative outcome study was a transdiagnostic comparison of CBT-​E with interpersonal psychotherapy (IPT) (Fairburn et al., 2015). The choice of IPT makes for a stringent comparison, given that IPT is the leading alternative to CBT as a treatment for BN. The Agras et al. (2000) study showed that CBT was significantly more effective than IPT at post-​ treatment, but IPT showed continued improvement and the difference at a 1-​year follow-​up was no longer significant. Similarly, Fairburn, Jones, Hope, O’Connor, & Peveler (1993) found comparable effects between the two treatments although IPT was slower in achieving its results. In addition, IPT is an effective treatment for BED (discussed later). The participants in the study were 138 eating disorder patients with a BMI between 17.5 and 40. Fifty-​three (40.8%) had a diagnosis of BN, 6.2% had BED, and 53.1% were designated as “other eating disorder” patients. Treatment consisted of 20 50-​ minute individual sessions. The main result at post-​treatment was that 65.5% of CBT-​ E patients were in remission (defined as a global Eating Disorder Examination [EDE] score below 1.74) versus 33.3% of IPT patients. Among CBT-​E patients, 44.8% reported no binge eating or purging compared with only 21.7% of IPT participants. At the 60-​week follow-​up the proportion of CBT-​E patients had increased slightly to 69.4%, whereas IPT participants increased to 49%. The difference between CBT-​E and IPT on the primary outcome measure of remission was statistically significant at both post-​ treatment and follow-​ up. Fairburn et  al. (2015) emphasize that the CBT-​E results in this study provide an impressive replication of the results in an earlier study of CBT-​E (Fairburn et al., Wilson

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2009—​see Wilson, 2010). In that study the rate of remission from both binge eating and purging in the BN patients was 45.6% at follow-​up, a figure higher than that obtained with the earlier version of CBT. The study has several strengths. As in the Poulsen et  al. (2013) trial, specific steps were taken to rule out any explanation in terms of allegiance effects. Training and weekly supervision was the same for both therapies, and independent ratings of treatment fidelity indicated that both were competently implemented. Patient ratings of suitability and expectancy were comparable. Finally, Fairburn et al. (2015) point out that both CBT-​E and IPT were originally developed by the Oxford group, who are known to be advocates of both treatments. Indeed, in CBT-​Eb the treatment of specific interpersonal problems is primarily based on the principles and procedures of IPT (Fairburn, 2008).

Generalizability of Treatment Effects from Controlled Research to Routine Clinical Care Settings

A long-​standing criticism of randomized controlled trials (RCTs) of psychological treatments has been that they have tended to exclude patients with more multiple and more complex problems. The reason? The RCTs typically have focused on a single diagnostic category and participants in the study are recruited by the investigators. In response it has been well documented that more recent RCTs have included patients with severe psychopathology and high rates of psychiatric comorbidity. One of the most common reasons for screening out potential participants in RCTs is that the individual’s problems are not severe enough—​do not meet strictly defined DSM-​IV or DSM-​5 criteria—​to warrant inclusion. One of the strengths of the RCTs on BN summarized here is that deliberate efforts were made to include participants who were representative of patients typically treated in “real-​world” clinical service settings. For example, the Fairburn et al. (2009) and Fairburn et al. (2015) trials of CBT-​E used broad eligibility criteria so as not to be selective. Furthermore, study participants were recruited from a long-​established community clinic in which the full range of eating disorder patients seeking help were treated. In order to determine the degree to which the RCT samples were broadly representative of the “real-​ world” population, a comparison was made of the participants recruited for the RCT with patients 274

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from the same geographical catchment area seen in the 12 months before and after the RCT (Wales, Palmer, & Fairburn, 2009). The results showed that the three different samples of patients were strikingly similar. It is clear that controlled treatment trials can be designed to be representative on routine care patient populations. Three additional studies have investigated the outcome of CBT-​E implemented in routine clinical care settings. In a public-​outpatient eating disorders program for youth and adults in Perth, Australia, Byrne, Fursland, Allen, and Watson (2011) analyzed the treatment outcome of 125 patients including all eating disorders. Of the total sample those with a BN diagnosis numbered 40. At post-​ treatment 32.5% of the full sample (using an intent-​to-​treat analysis) were in full remission, namely, no eating disorder symptoms over the previous 28 days; 45% were in either full or partial remission. Of those who completed treatment, 50% were in full remission. Significant improvements were also evident on measures of depression, anxiety, stress, interpersonal problems, self-​esteem, and quality of life. Overall the results were very similar to those reported in the original Fairburn et  al. (2009) CBT-​E trial in the UK. The single main difference between the two trials was the significantly higher dropout in the Australian sample—​40% versus 22.1%. A second study evaluated the results in 272 BN and eating disorder not otherwise specified (EDNOS) patients treated with CBT-​E in a National Health Service eating disorders clinic in Wales (Knott, Woodward, Hoefkens, & Limbert, 2015). Of the total sample, 74 (27.2%) had BN. A positive treatment outcome defined in terms of global EDE-​Q score of less than one standard deviation above the community mean was achieved by 78% of patients who completed treatment and 39.7% using an intent-​to-​treat analysis. The post-​ treatment results were similar to both the Fairburn et al. (2009) and Byrne et al. (2011) findings, using a comparable definition. Also noteworthy is that Knott et al. (2015) reported a 40% attrition rate—​ comparable to Byrne et al. (2011) and much higher than the Fairburn et al. (2009) RCT. The third study of CBT-​E conducted in an NHS setting in England yielded roughly comparable results to Byrne et al. (2011) and Knott et al. (2015) both in terms of outcome and attrition rate (Turner, Marshall, Stopa, & Waller, 2015). Collectively, these findings provide convincing evidence that the findings on CBT-​E from RCTs can, and do, generalize to routine clinical practice.

Predictors and Moderators

In general robust predictors or moderators of treatment outcome in the treatment of BN have yet to be identified. A notable exception to this pattern has been early response to treatment. Fairburn, Agras, Walsh, Wilson, and Stice (2004) showed that what has been called an early response to CBT—​ in this case a significant reduction in purging by week 4—​was a strong predictor of outcome at post-​ treatment. This finding was replicated in a second large multisite study in which a 70% reduction in purging by session 6 (week 4)  predicted therapeutic success or failure at post-​treatment (Agras et al., 2000). One of the advantages of CBT-​E is that the protocol requires the therapist to “take stock” or systematically evaluate the effects of treatment early in the course of therapy (after the first 7 sessions). The goal is to identity nonresponders who, the research indicates, are unlikely to show subsequent improvement. If the patient is progressing, no alteration of CBT-​Ef need be made. The absence of significant improvement, however, indicates that the barriers to change must be identified and treatment modified accordingly. For example, the focus of treatment might be shifted to one or more of the additional maintaining mechanisms included in CBT-​Eb. Cooper et al. (2016) conducted a detailed analysis of the findings from the Fairburn et al. (2015) study comparing CBT-​E and IPT in order to identify predictors and moderators of change. Two significant predictors of treatment outcome at the 60-​week follow-​up assessment emerged. One was that patients with a longer history of their eating disorder were significantly less likely to benefit from either treatment. This finding is consistent with the results of a review and meta-​analysis of the relevant literature by Vall and Wade (2015). The second finding was that higher levels of overevaluation of the importance of body shape and weight at baseline predicted a poorer outcome in both CBT-​ E and IPT. This result replicates previous research showing overevaluation of body shape and weight to be a negative prognostic factor (Fairburn, Peveler, Jones, Hope, & Doll, 1993). The only significant moderator of outcome was that patients with lower self-​esteem at pretreatment were more likely to respond successfully to CBT-​E than IPT. Given the high prevalence of self-​esteem problems in BN patients, this finding, assuming it is replicated in other studies, indicates a significant advantage of CBT-​E.

Guided Self-​Help

As detailed later in this chapter, greater adoption and implementation of CBT would be advanced if the intervention were to be made briefer and less complex than the full CBT-​E protocol. Guided self-​ help based on the principles and procedures of CBT (CBTgsh), provides such an option; CBTgsh combines a self-​help manual with a limited number of brief therapy sessions (Fairburn, 1995, 2008). Prior reviews are consistent in showing that CBTgsh can be an effective intervention for BN as compared with a minimal control condition such as a waiting list (e.g., Banasiak, Paxton, & Hay, 2005; Ljotsson et al., 2007; Sysko & Walsh, 2007). Schmidt et  al. (2007) compared guided self-​help based on cognitive-​behavioral principles using the Schmidt and Treasure (1993) manual in the treatment of adolescents (ages 13 to 20 years) with BN with the Maudsley model of family therapy. Both treatments resulted in significant improvement in binge eating and purging at the end of treatment (6  months) and a follow-​up at 12  months. Abstinence rates for binge eating and purging combined at 12  months were 36% for CBTgsh and 41% for family therapy. The CBTgsh resulted in significantly more rapid reduction in binge eating. Moreover, CBTgsh was associated with greater acceptability and lower cost than family therapy. As the authors point out, the absence of a control group precludes attributing the results specifically to the treatment, although CBTgsh was more cost-​ effective than the comparison therapy. The Mitchell et al. (2011) multisite study is the largest controlled study of CBTgsh of BN. A complete program of manual-​based CBT (20 individual, 50-​minute sessions) was contrasted with CBTgsh (eight, 20-​minute sessions using the Fairburn, 1995 book) over an 18-​week period. Patients who did not show a minimum of 70% reduction in purging by session 6 were offered fluoxetine (60 mg). The rates of patients who received fluoxetine were 65% in the full CBT treatment and 34% in CBTgsh. At the 18-​week post-​treatment assessment, the abstinence rates (cessation of both binge eating and purging) were 15% and 11% for full CBT and CBTgsh, respectively. The remission rates (defined as no longer meeting DSM-​IV criteria) were 57% and 52%, respectively. It should be noted that the patients randomized to CBTgsh conditions were significantly more likely to have endorsed a history of anorexia nervosa, shown to be a negative prognostic indicator in some studies (Agras et al., 2000). Given the lack of a significant difference in outcome between Wilson

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the two treatment conditions, Mitchell et al. (2011) concluded, “Therapist-​ assisted self-​ help was an effective first-​level treatment” (p. 391), which is in line with the NICE (2004) recommendation. The Mitchell et  al. (2011) study had several strengths. Adequately powered and conducted by a very experienced group of investigators, it included state-​ of-​ the-​ art assessment of outcome (Eating Disorder Examination [EDE] interviews), manual-​ based treatments, centralized training of therapists, and weekly supervision using audiorecordings of therapy sessions. Total therapist contact time was 16 to 17 h for CBT and 2 to 3 h for CBTgsh. Moreover, therapists who administered CBTgsh had less experience and training in CBT and eating disorder treatment. A discrepant finding, as the authors point out, is the low abstinence rate in the full CBT condition compared with other major RCTs (e.g., Agras et al., 2000). In sum, despite the limited number of comparative outcome studies, the findings on CBTgsh for BN are promising. They warrant future research and clinical application.

Binge Eating Disorder

Binge eating disorder was added to the list of formal eating disorder diagnoses in DSM-​5 (Attia et al., 2013). Initially the standard CBT treatment for BED was basically the Fairburn et  al. (1993) manual. Although the manual was developed primarily for treating BN, it contained modifications designed for application to binge eating in both normal weight and overweight or obese patients. As a transdiagnostic treatment, CBT-​E is now directly applicable to BED (Fairburn, 2008).

Therapeutic Efficacy

Manual-​based CBT has been the most intensively studied form of psychological treatment of BED. The NICE (2004) guidelines concluded that CBT was currently the treatment of choice for BED. This clinical recommendation was assigned a methodological grade of “A,” indicating strong empirical support from RCTs. Research has consistently shown that manual-​based CBT produces remission rates in binge eating between 50% and 70% that are generally well maintained at follow-​ up. The treatment also reliably results in reduction in specific eating disorder and general psychopathology that are generally maintained at a 1-​year follow-​up. Manual-​based CBT, however, does not produce clinically significant improvement in body weight (Wilson, 2010). As is the case with all eating 276

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disorders, the patients in these studies typically have had significant comorbid psychiatric disorders and psychosocial problems. CBT Versus Behavioral Weight Loss Treatment Early treatment outcome studies of BED compared CBT with behavioral weight loss treatment (BWL). At the time it was argued by obesity researchers that standard obesity treatment was effective for BED, that BWL was effective, and that there was no need for specialty psychological therapies such as CBT. Subsequent research, however, showed that manual-​based CBT is more effective overall than BWL (Devlin, Goldfein, Petkova, Liu, & Walsh, 2007; Munsch et  al., 2007). Grilo, Masheb, and Wilson (2011) randomly assigned 125 obese patients with BED to 16 sessions of either group CBT, BWL, or a sequential condition in which CBT was administered first, followed by BWL (CBT _​BWL). Attrition rates were relatively high (24% for CBT; 31% for BWL; 40% for CBT _​BWL), especially in the combined condition. No significant differences in remission rates emerged, although CBT produced significantly greater reductions in frequency of binge eating at the 6-​and 12-​month follow-​ups. CBT Versus Pharmacotherapy Despite some inconsistent findings, treatment with antidepressant medication has been shown to be superior to pill placebo (Reas & Grilo, 2008). Hence, comparison with CBT provides another comparative test of the specific efficacy of CBT. In an RCT, Grilo, Masheb, and Wilson, (2005) found that CBT was significantly more effective than either fluoxetine or placebo in producing remission from binge eating. Grilo, Crosby, Wilson, and Masheb (2012) subsequently reported the 12-​ month follow-​up data of 91 of the original 108 study participants:  CBT plus fluoxetine and CBT plus pill-​placebo did not differ on any outcome measure, and CBT plus placebo was superior to fluoxetine-​only on most measures. The pattern of results provides robust evidence of the longer-​term effectiveness of CBT but not fluoxetine through 12 months after treatment. The greater efficacy of CBT compared to pharmacological treatment is also evident in an analysis of RCTs of combined pharmacological treatments for BED (Grilo, Reas, & Mitchell, 2016). Combining medication with CBT produced superior outcomes to pharmacotherapy only, but does not significantly enhance the outcome yielded by CBT only.

Guided Self-​Help

As described above for BN, CBTgsh for BED has typically consisted of 8 or 10 brief treatment sessions using the Fairburn (1995) manual Overcoming Binge Eating. The guidance has been provided by counselors who have had different levels of training and expertise in this form of CBT. The largest controlled treatment study of CBTgsh for BED compared it with BWL and IPT in a large sample of 205 overweight and obese patients with the eating disorder (Wilson, Wilfley, Agras, & Bryson, 2010). Both BWL and IPT consisted of 20 sessions of individual treatment administered over a 6-​month period, whereas CBTgsh comprised 10 sessions over this period, 9 of which had a maximum duration of 25 minutes. Interpersonal psychotherapy was selected as an alternative specialty psychological therapy, as two previous RCTs had shown comparable efficacy between manual-​based CBT and IPT on remission from binge eating, reductions in body shape and weight concerns, and associated psychopathology (Wilfley et  al., 1993; Wilfley et al., 2002). Post-​ treatment findings showed no significant differences among the three treatments on remission from binge eating (Wilson et al., 2002). The remission rates were as follows: IPT = 64%, BWL = 54%, and CBTgsh = 58%. At the 2-​year follow-​up, however, both CBTgsh and IPT not only successfully maintained their improvement, but were also significantly superior to BWL in producing remission from binge eating. Behavioral weight loss therapy produced greater weight loss than either IPT or CBTgsh at post-​treatment, but not at follow-​up. The results provide further evidence that CBT is more effective than BWL in eliminating binge eating in overweight and obese patients. Moreover, at no point did IPT differ from CBTgsh on any of the outcome measures. The design of this RCT also provided a test of the allegiance bias hypothesis in interpreting comparative outcome trials (Wilson, Wilfley, Agras, & Bryson, 2011). One of the two treatment sites had extensive experience and expertise in IPT, the other in CBT and CBTgsh. The absence of any site × treatment effect rules out an allegiance bias interpretation. Moreover, there were no significant individual effects on any measure across both treatments. A second study evaluated the efficacy of CBTgsh versus treatment-​as-​usual (TAU) in a sample of 123 patients with recurrent binge eating in a large health maintenance organization in the United States (Striegel-​Moore et al., 2010). Of the full sample, 48% met diagnostic criteria for BED. Treatment

comprised eight sessions over a 12-​week period. The remission rates from binge eating at the 12-​month follow-​up were 64.0% and 44.6% for CBTgsh and TAU respectively. The diagnosis of BED did not moderate outcome. Also, CBTgsh resulted in significant improvement on other indices of eating-​ related psychopathology as well as depression and functional impairment. A replication and extension of this study in the same setting evaluated the impact of less intensive procedures for recruiting and assessing patients to more closely approximate the routine service in “real-​world” settings (DeBar et al., 2011). The pattern of results in this sample of 160 female members of the health maintenance organization replicated that from the Striegel-​Moore et al. (2010) study. At the 12-​month follow-​up, CBTgsh resulted in significantly greater remission from binge eating (35%) than TAU (14%). However, the magnitude of the effects of CBT was lower than in the previous trial.

Predictors and Moderators

As in BN, rapid response to treatment has been found to be a clinically significant predictor of treatment outcome in BED. Grilo, Masheb, and Wilson (2006) found that rapid response had different prognostic significance and time courses across different treatments for binge eating disorder. It predicted remission rates of 73% for manual-​based CBT versus 46% for fluoxetine. Rapid response to CBT predicted improvement that was sustained or even improved further during the remaining course of treatment. In contrast, when rapid response occurred in pharmacotherapy, some of the improvement tended to be lost, although it was reasonably maintained during the remaining treatment course. Importantly, in CBT clinically important findings were observed for patients without a rapid response to treatment. In CBT, patients without a rapid response showed a subsequent pattern of continued improvement throughout treatment, although it did not reach the very high levels of improvement achieved by the rapid responders. A second study was an analysis of the findings from the Grilo et al. (2011) trial comparing CBT and BWL. Rapid response to treatment, defined as 70% or greater reduction in binge eating by week 4, was evident in 67% of CBT patients and 47% of BWL patients. Those treated with CBT did equally well regardless of rapid response in terms of reduced binge eating, but did not show weight loss. In patients treated with BWL, however, rapid responders were significantly more likely to achieve Wilson

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binge eating remission (62% vs. 13%) and greater reductions in binge eating frequency, eating disorder psychopathology, and weight loss. An analysis of the findings from the Wilson et al. (2010) trial similarly showed that rapid response predicts the outcome of CBTgsh. Defined as 70% or more reduction of binge eating by week, rapid response in CBTgsh but not IPT or BWL predicted significantly greater rates of remission from binge eating than nonrapid responders over the course of the 2-​year follow-​up (Hilbert, Hildebrandt, Agras, Wilfley, & Wilson, 2015). Based on this finding, Hilbert et al. (2015) suggested that CBTgsh be used as a first-​line treatment in a stepped-​care model of treatment of BED. Failure to find rapid response might then lead to implementing IPT, given its equal efficacy with both rapid and nonrapid responders. Overvaluation of body shape and weight, defined as undue influence of shape and weight on self-​evaluation, has been shown to be consistently associated with great severity of eating disorder psychopathology and predictive of treatment outcome in BED (Grilo, 2013). In an analysis of the Grilo et al. (2011) study, overvaluation was shown to be a significant predictor of nonremission from binge eating and great frequency of binge eating at the 12-​month follow-​up even after controlling for treatment group differences in depression and self-​esteem (Grilo, White, Gueorguieva, Wilson, & Masheb, 2012). Analyses of the data from the Grilo et al. (2005) comparison of CBT with fluoxetine revealed that overvaluation was both a predictor and moderator of treatment outcome. It predicted binge eating remission. Perhaps more importantly, it moderated remission rates by being significantly related to a poorer outcome in participants receiving medication only (Grilo, Masheb, & Crosby, 2012). Similarly, participants with overvaluation enjoyed significantly great reductions in eating disorder psychopathology and depression if treated with CBT as opposed to medication. The findings from Wilson et al. (2010) also bear importantly on the moderation of treatment outcome in BED. A latent transition analysis identified four different classes within the diagnosis of BED (Sysko, Hildebrandt, Wilson, Wilfley, & Agras, 2010). Class 1 was characterized by a lower mean body mass index and increased physical activity. Class 2 patients reported the most binge eating, shape and weight concerns, compensatory behaviors, and negative affect. Class 3 patients reported 278

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similar binge eating frequencies to class 2 with lower levels of specific eating disorder psychopathology and compensatory activities. And class 4 was characterized by the highest average body mass index, the most overeating episodes, fewest binge eating episodes, and an absence of compensatory behaviors. A latent transition analysis found a greater probability of total remission from binge eating among patients who received IPT in class 2 and CBTgsh in class 3. The comparatively greater efficacy of IPT for class 2 containing the patients with the most eating disorder psychopathology is consistent with a previous moderator analysis of this trial. Although CBTgsh and IPT had equal effects across the full sample, CBTgsh did significantly less well in those patients who had higher eating disorder psychopathology on the EDE. Interpersonal psychotherapy had comparable effects with both the high and low eating disorder psychopathology subgroups (Wilson et al., 2010). This finding has often been interpreted to mean that IPT is the more robust of the two treatments given its apparent broader efficacy. It would be premature to draw this conclusion, however. The CBTgsh in that study was the first-​generation protocol based solely on Fairburn’s (1995) self-​help manual. That manual explicitly eliminated any focus on body shape and weight concerns. Later studies of CBTgsh have included a specific module designed to treat overvaluation (e.g., DeBar et  al., 2011; Striegel-​ Moore et  al., 2010). Moreover, Fairburn (2013) has since published a second edition of Overcoming Binge Eating that includes specific strategies for addressing overvaluation of body shape and weight among other additions to the more limited previous manual. Whether or not this more complex and multifaceted form of CBTgsh enhances effectiveness remains to be determined in relevant RCTs.

Anorexia Nervosa

Particularly in adults, AN is the most difficult eating disorder to treat and to study, given its low prevalence and the difficulty in recruiting individuals with AN to participate in research studies (Agras et  al., 2004). The different treatments that have been used with AN, including CBT, all received a methodological grade of “C” in the NICE (2004) guidelines with the single exception of the Maudsley method of family therapy. The focus here is on studies conducted since the first edition of this Handbook. The first study evaluated the efficacy of CBT-​E in a sample of 99 adult AN patients recruited from

consecutive referrals to clinics in the UK and Italy, respectively (Fairburn et al., 2013). All had an entry BMI of less than 17.5. The therapy consisted of 40 individual sessions of CBT-​Ef over 40 weeks with no concurrent treatment. The therapists had experience in treating eating disorders and received 6 months of initial training in CBT-​Ef from Fairburn and Cooper in the UK and Dalle-​Grave and Fairburn in Italy. Weekly supervision sessions were conducted throughout the study by Fairburn (UK) and Dalle-​ Grave (Italy). All sessions were recorded and used as part of supervision to ensure competent implementation of CBT-​Ef. Three main findings emerged. First, 64% of patients from both samples completed the full treatment. The remaining third of patients either dropped out or were withdrawn due to lack of progress or concern about their physical health. Second, completers showed substantial improvement in weight and eating disorder psychopathology at post-​treatment. The mean weight gain was 16.5 lbs, with over 60% meeting criteria for the World Health Organization’s healthy BMI range. Third, treatment-​induced improvements were generally well maintained over a 60-​week follow-​up period despite little exposure to further treatment. Although the lack of any control condition is a limitation of the study, the results provide preliminary support for the treatment and justify further evaluation of CBT-​Ef in subsequent RCTs. A second study, adopting the same design, evaluated the efficacy of CBT-​Ef in the treatment of 49 adolescents (ages 13 to 17) who met DSM-​IV criteria for AN with the exception of amenorrhea (Dalle-​ Grave, Calugi, Doll, & Fairburn, 2013). Treatment consisted of 40 sessions over 40 weeks. In parallel findings to the Fairburn et al. (2013) study of adults with AN, two-​ thirds of the adolescent patients completed the treatment. The completers showed significant improvement in eating disorder psychopathology and weight gain. The mean BMI centile increase was 26.9, with a third of patients gaining enough weight to reach 95% of their expected weight. The results were well maintained over the 60-​week follow-​up. A third study evaluated the efficacy of an inpatient CBT-​ E treatment in 32 AN patients who had suffered from the disorder for greater than 7 years and 34 whose duration was less than 7 years (Calugi, El Ghoch, & Dalle-​ Grave, 2017). The treatment was administered over a fixed period of 20 weeks—​13 weeks inpatient followed by 7 weeks in a day-​hospital. Both groups showed significant

improvement in eating disorder psychopathology and increased BMI. More than 40% of patients who completed treatment met criteria for a full response defined as a BMI > 18.5. Improvements were mostly maintained at a 12-​month follow-​up. Over 80% of eligible patients agreed to the treatment, and 85% completed treatment indicating good acceptability. Collectively, the three studies summarized above encourage the further development and application for CBT-​E as a treatment for adults and adolescents with AN. A large, multisite RCT in Germany compared CBT-​ E with manual-​ based focal psychodynamic therapy and “optimized treatment as usual” (TAU) in the treatment of 242 adult patients with AN (Zipfel et  al., 2014). Treatment was 10  months in duration. CBT-​E in this study is described as a combination of focal and broad forms (Fairburn, 2008). Treatment as usual included outpatient psychotherapy and structured care from a family doctor. Outcome was evaluated at post-​treatment and 3-​and 12-​month follow-​ups. All three groups showed weight gain at post-​treatment:  0.93  kg/​m for CBT-​E, 0.73  kg/​m for focal psychodynamic therapy, and 0.69 kg/​m for TAU. At the 12-​month follow-​ up BMI values had increased further in all three groups. No between-​ group differences on BMI—​ the primary outcome measure of the study—​were statistically significant either at post-​ treatment or follow-​up. At the 12-​month follow-​ up, patients who had received focal psychodynamic therapy showed a significantly higher recovery rate than TAU. Recovery was defined using a post hoc, combined measure of assessor ratings of patients’ psychiatric status and BMI; CBT-​E did not differ from either of the other two groups. The results of this study are disappointing. The only significant difference in favor of one of the two manual-​based specialty therapies in this trial was the 12-​month superiority of focal psychodynamic therapy over TAU on a post hoc combined outcome measure. On all other measures TAU did comparably well. And CBT-​E did not improve on TAU on any measure of efficacy. In her commentary on this study Bulik (2014) noted that at post-​treatment and the 12-​month follow-​up the mean BMI across the three treatment groups was still in the underweight range. Over 25% of patients still suffered from the full AN disorder—​29% in the focal psychodynamic therapy group, 26% in CBT-​E, and 27% in TAU. The Zipfel et al. (2014) RCT had several strengths. It is the largest, multisite controlled study Wilson

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ever of the psychological treatment of AN. Another novel feature was the comparison of two prominent specialty psychological therapies with TAU. Yet there are methodological features of the study that demand caution in interpreting the findings. It is imperative that comparative outcome studies take the necessary steps to ensure that the specialty treatments in question are implemented in a competent fashion by appropriately trained and supervised therapists (Fairburn & Cooper, 2011). Studies described earlier in this chapter provide specific examples of how this is accomplished (e.g., Fairburn et al., 2015; Poulsen et al., 2014). The Zipfel et al. (2014) study does not provide the necessary information. For example, the initial training of CBT-​E therapists was limited to a 2-​day workshop by Fairburn. The inadequacies of brief workshop trainings are well documented. Then it is unclear whether subsequent training and supervision of study therapists met the criteria of ensuring competence in the implementation of CBT-​E. As a result of these RCT design issues, it is unclear whether to attribute the Zipfel et al. (2014) findings to the treatment in question or the manner in which both specialty therapies were implemented. Future comparative research will need to take account of these concerns.

Effectiveness and Scalability of CBT

The analyses and controversies surrounding the effects of psychological therapies and what currently constitutes “evidence-​based treatment” have centered almost exclusively on efficacy. Future analyses of evidence-​based treatments must necessarily take account of a much broader range of dimensions on which to evaluate and then select for use the diverse range of psychological and pharmacological therapies. This is especially the case given the compelling need to improve the dissemination and implementation of such treatments on both local and global levels (discussed later).

Efficacy: Short-​and Long-​Term Results

A major advantage of the CBT treatments summarized above is that many of the studies supporting their use across the different eating disorders have reported follow-​up findings of 1 year or more. The only alternative therapy with significant follow-​ up findings—​albeit less than CBT—​is IPT. Consider the evidence on pharmacological treatment. The evidence is limited to short-​term treatment trials—​ with CBT proving superior 280

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even on this limited basis. Reviews by Bodell and Devlin (2010) and Reas and Grilo (2008) of treatment of BED underscored the fact that both the longer-​ term effects of pharmacotherapy and the impact of discontinuation of medication are generally unknown. They are not recommended in the NICE (2004) guidelines. Yet the clinical reality still is that antidepressants and other medications are widely prescribed in the United States (e.g., Grilo, Crosby, Wilson et al., 2012). In early 2015 the Food and Drug Administration in the United States approved the drug lisdexamphetamine (Vyvanse) for treatment of adults with BED. The data on which this decision was apparently based were short-​term—​post-​treatment assessment was at 11 weeks (McElroy et al., 2015). Moreover, the study had very restrictive medical and psychopathological inclusion criteria that do not permit generalizability to routine clinical settings.

Cost-​Effectiveness

The cost-​effectiveness of treatment is increasingly becoming a consideration in selecting treatments, and CBTgsh is an example of a well-​documented cost-​ effective intervention. For example, in the Wilson et al. (2010) study, CBTgsh and IPT were comparably effective in the total sample. However, CBTgsh consisted of only 10 treatment sessions compared with 20 for IPT. Nine of the 10 sessions were 25 minutes or less, resulting in total therapist contact time of 4 to 5 hours versus 18 to 19 hours for IPT. The CBTgsh therapists were beginning graduate students versus more senior doctoral level therapists implementing IPT. Furthermore, their training was significantly shorter than their IPT counterparts, and, finally, weekly supervision was on an “as needed” basis as opposed to required individual weekly supervision meetings in IPT. In sum, in several ways CBTgsh was far less costly than IPT although not less effective overall. In the treatment trial for adolescents in England, Schmidt et al. (2007) reported that their CBTgsh intervention was less costly but not less effective than the comparison family therapy condition. A formal cost-​ effectiveness analysis was conducted on the findings of the Striegel-​Moore et al. (2010) study of CBTgsh (Lynch et al., 2010). The results were that CBTgsh plus TAU produced significantly more binge-​free days and a lower total societal cost over the 12  months following treatment. The lower costs of CBTgsh were due to the reduced use of TAU services within the health maintenance

organization and were obtained despite the relatively high level of therapist supervision.

Clinical Range/​Reach

The transdiagnostic nature of CBT-​ E offers major advantages in extending the clinical range or reach of CBT. It is the only evidence-​based treatment for all eating diagnoses. It is applicable not just to adults but also to adolescents who are not underweight (Dalle-​Grave et al., 2013). A transdiagnostic treatment such as CBT-​E allows a mental health provider to be trained in one specialty treatment rather than multiple different treatment protocols and still be versatile enough to treat all eating disorders. This reduces the burden of providing training across different disorders and hence is more cost-​effective to boot. Also, CBT has been shown to be applicable and effective across different treatment settings such as specialty eating disorder clinics, general health maintenance organizations, and community care centers in different countries.

Brevity

Brief treatment is advantageous not only because by definition it is more cost-​effective but also because it offers a more realistic alternative for many routine clinical care settings that do not have the resources or organization to permit full-​length treatments typically evaluated in RCTs. As pointed out earlier in this chapter, CBT-​E has been shown to be effective in “real-​world” clinical care settings. However, as Agras, Fitzsimmons-​Craft, and Wilfley (2017) caution, some of these studies (e.g., Turner et  al., 2015) have used a greater number of treatment sessions than would be feasible in other routine care settings. Promoting the practical advantages of brief treatments does not necessarily mean settling for less than optimal treatment. First, there is evidence that brief CBTgsh can be as effective as lengthier manual-​based CBT treatment for BN and BED) (Mitchell et al., 2011; Schmidt et al., 2007; Wilson et al., 2010). Second, it is also important to take the larger implementation context into account. Even if a treatment such as CBTgsh were less effective than full CBT-​E it might still be valuable. As Kazdin and Blase (2011) have pointed out, an “intervention with a larger (effect size) is not invariably better than one with a smaller one. An intervention with a weak but reliable effect that can reach large numbers with little cost would be worth having” (p. 33).

Task-​Sharing

It is well documented how people have very limited access to mental health treatment both on a global level and even in the United States (Kazdin & Rabbitt, 2013). It is also increasingly accepted that one way of addressing this problem is to provide a much greater number of trained mental health providers than is currently the case. However, relying on trained professionals with advanced degrees, as is the practice in the United States, can never meet the need for more mental health providers (Kazdin & Blase, 2011). One solution is task-​ shifting/​ sharing—​ training less-​ qualified people, including peers, to take on tasks that have previously been undertaken by more highly qualified individuals. Patel, Chowdhary, Rahman, and Verdeli (2011) have underscored that “relying on mental health professionals to deliver [evidence-​based treatments] will only address a tiny fraction of the treatment gap and task-​shifting these interventions to more available and affordable members of the health workforce or community is widely acknowledged to be the only sustainable way of addressing this barrier” (p. 524). Task-​sharing does not merely increase the number of available mental health providers. It also offers an optimal means of addressing the challenge of serving diverse cultural, ethnic, and racial populations. Instead of current practice of training mainly White mainstream students through contact and supervision with diverse minority groups as is typically done in the United States, task-sharing allows treatment to be implemented by members of the same minority or cultural group. These providers are then familiar with specific cultural beliefs that may influence response to treatments developed in the in the United States and elsewhere, and proficient in the specific language of the patients being treated (Chowdhary et al., 2014). Task-​sharing has been documented to be effective in major RCTs in the treatment of depression and other disorders in places such as India and rural Pakistan (Patel et al., 2011; Patel et al., 2017). Yet currently there is minimal evidence on the use of task-​ shifting/​ sharing in the treatment of eating disorders. What is clear even at this early stage is that effective treatment can be provided by a wide range of counselors. This includes nonspecialist “facilitators” with no formal clinical qualifications (Carter & Fairburn, 1998), clinically inexperienced graduate students (Wilson et al., 2010; Zandberg & Wilson, 2013), physicians (Banasiak et  al., 2005), Wilson

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and Masters level psychological therapists (Byrne et al., 2011; Striegel-​Moore et al., 2010). It should also be noted that inexperienced undergraduate college students with appropriate training have been shown to be effective in implementing an evidence-​ based eating disorder prevention program for their peers (Kilpela et  al., 2014). Ultimately, whether nonprofessionals can provide effective treatment for individuals with eating disorders, as has been documented in other mental disorders such as severe depression (Patel et al., 2017), remains to be seen.

Ethnic, Racial, and Cultural Considerations

Eating disorders occur among a wide range of diverse ethnic and racial populations in the United States. Clinical research on the acceptability and efficacy of standard evidence-​based therapies such as CBT in these minority groups is sparse. In the biggest analysis to date, Thompson-​Brenner et  al. (2013) examined the role of race and ethnicity as possible predictors and moderators in the data from 11 RCTs on BED in the United States. The main finding was the absence of significant differences among different ethnic and racial groups in terms of treatment outcome. African Americans showed a greater attrition rate than other groups, however. The authors caution that the overall number of ethnic and racial participants across the 11 RCTs was still small, possibly limiting the identification of significant findings. A qualitative study using focus group methodology was conducted to evaluate the acceptability of CBTgsh for Mexican American women with BED, BN, or recurrent binge eating in Los Angeles, California (Shea et al., 2012). The main finding was that these women deemed CBTgsh to be acceptable. They liked the CBT content and the self-​help focus, which was seen as empowering, and responded that they would recommend the treatment to family and friends. The study also identified specific cultural themes that would be helpful in implementing the treatment:  cultural expectations regarding eating and body image; family dynamics; and culturally specific foods and eating patterns. A second study then evaluated the acceptability and effectiveness of CBTgsh that had been culturally adapted by incorporating the foregoing results (Cachelin et al., 2014). The program resulted in a 35.5% remission rate from binge eating and 38.7% rate for diagnostic remission. Improvements in body shape and weight concerns and self-​esteem were also obtained. Satisfaction with the treatment 282

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was high. The findings of this exploratory study provide proof-​of-​concept for the implementation of culturally adapted CBTgsh for ethnic and racial minority groups.

Scalability

A major asset of CBT is its capacity to “scale up” treatment so as to provide greater access to treatment for large numbers of people who have no access to mental healthcare—​both in low-​resource countries (Patel et al., 2011) and even in a high-​ resource country such as the United States (Kazdin & Rabbitt, 2013). In order to provide greater access to care Kazdin and Blase (2011) urged the adoption of improved means of delivering psychological treatment. They called for (1) the use of nonprofessional providers (task-​ sharing) to complement highly trained professionals; (2) self-​help strategies; and (3) technological innovations. More than any other form of psychological therapy, CBT provides realistic means of making these innovations. Cognitive-​behavioral therapy has lent itself well to task-​sharing and, particularly with respect to eating disorders, the effective use of self-​help treatment. It is important to stress that guided CBTgsh is not simply a brief form of regular therapist-​administered treatment. It is a different mode of treatment. A consistent finding has been that guided self-​help provided by a counselor is more effective than “pure” self-​ help without the accompanying support from a counselor (Wilson & Zandberg, 2012). Fairburn and Patel (2014) emphasize that the guidance or support need not be from a highly trained or professional therapist. In order to be scalable, the treatment is “program-​led” rather than “therapist-​ led.” The guidance should be supportive or facilitative help that can be provided by a nonspecialist. Thus far, CBTgsh has been mainly delivered in the form of Fairburn’s (1995) a self-​help book. It can also be provided via the Internet. The latter is more scalable and has the added advantage of being able to be personalized to match the characteristics of the individual patient’s specific eating problems. Internet-​ based CBT treatments have been shown to be effective a number of different disorders including anxiety and depressive disorders (Andersson, 2009; Andrews, Cuijpers, Craske, McEvoy, & Titov, 2010). The evidence on e-​therapy (Internet and mobile devices) for eating disorders was reviewed by Loucas et al. (2014) using the methodology employed by NICE in the UK. The authors concluded that although some positive

findings emerged, “the value of e-​therapy for eating disorders must be viewed as uncertain” (p. 122). The current enthusiasm for e-​therapy has outpaced the research studies of sufficient quality and rigor. Loucas et  al. (2014) call for improved research, a judgment also registered in another incisive review of e-​therapy by Agras et al. (2017).

Dissemination and Implementation of CBT

There is consensus in the field of mental health that patients are not receiving evidence-​based treatments in usual clinical care (Kazdin, 2017). Even when patients do receive these treatments there is evidence that they are often delivered in suboptimal fashion (Shafran et al., 2009; Wolitzky-​Taylor, Zimmermann, Arch, De Guzman, & Lagomasino, 2015). The research–​practice gap in mental health is striking. Eating disorders are no exception (Lilienfeld et al., 2013). Suffice it to note a few examples. Wallace and von Ranson (2012) administered a Web-​based survey to an international sample of eating disorders practitioners revealing that only roughly half reported using empirically supported treatments with AN, BN, or BED. Consistent with other surveys, most practitioners stated that they selectively folded evidence-​based treatments into their preferred eclectic approaches as opposed to implementing empirically supported treatments in the form that had been evaluated in controlled research trials. Another survey of 80 clinicians treating eating disorder patients, and who reported using CBT, revealed that only a minority actually implemented techniques that define CBT (Waller, Stringer, & Meyer, 2012). As has been repeatedly demonstrated, a majority of the clinicians combined some CBT techniques with other non-​evidence-​based methods in an eclectic approach. Waller et  al.’s sobering conclusion was that “clinicians’ use of the label CBT is not a reliable indicator of the therapy that is being offered” (p. 171). Lilienfeld et  al. (2013) attributed this this evidence of a research–​practice gap to an “attitudinal factor” among clinicians in which they ignored empirically supported evidence in favor of their subjective judgment and personal clinical experience. The solution to this problem they argued would be recommending better education and training of practitioners in the superiority of actuarial prediction versus intuitive and subjective clinical judgment (Kahneman, 2011; Wilson, 1996). Certainly practitioners should receive accurate and

state-​of-​the-​art education in behavioral science and decision-​making, but this alone will not change clinicians’ behavior. The solution lies in establishing institutional standards of accountability that require practitioners to implement empirically supported treatments where the data exist (Wilson & Shafran, 2005). A move in this direction was contained in the 2015 annual report entitled “Health of the 51%: Women” from the chief medical officer of the National Health System (NHS) in the United Kingdom. In the report she recommended that the NHS England should commission services to provide CBT-​E for eating disorders. Another reason for the research–​practice gap is the inadequacy of current training in evidence-​ based interventions. We need innovative and improved training methods in evidence-​based psychological treatments (Herschell, Kolko, Baumann, & Davis, 2010). Training-​as-​usual, comprising a workshop plus a treatment manual, does not reliably increase necessary therapist skills. A major reason is that follow-​ up supervision is impractical or unavailable. The train-​the-​trainer model has been promoted as an alternative. In this approach a member of a clinical staff is trained to train and supervise other members of the staff. The goal is to provide continuing feedback and monitoring of treatment integrity. Preliminary findings indicate that the model can be used in the treatment (Zandberg & Wilson, 2013) and prevention (Kilpela et al., 2014) of eating disorders. Videoconferencing technology provides another means of facilitating dissemination and implementation of CBT. For example, in the Poulsen et  al. (2014) study conducted in Copenhagen described above, the CBT-​ E therapists were trained and supervised by CBT experts in Oxford using videoconferencing technology. The most ambitious solution to training more competent therapists is “Web-​centered training” (Fairburn & Patel, 2014). In this form of training, a specially designed training website provides detailed instruction on the treatment’s use as well as its strategies and procedures. Web-​centered training may be used alone or accompanied by guidance. If the latter is provided by nonspecialists, as recommended by Fairburn and Patel (2014), Web-​ centered training would be scalable. Web-​centered training is currently being tested to establish its effectiveness and scalability (Fairburn & Patel, 2014, 2017). Wilson

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References

Agras, W. S., Brandt, H. A., Bulik, C. M., Dolan-​Sewell, R., Fairburn, C. G., Halmi, K. A.,  . . .  Wilfley, D. E. (2004). Report of the National Institute of Health Workshop on Overcoming Barriers to Treatment Reearch in Anorexia Nervosa. International Journal of Eating Disorders, 35, 509–​521. Agras, W. S., Crow, S. J., Halmi, K. A., Mitchell, J. E., Wilson, G. T., & Kraemer, H. (2000). Outcome predictors for the cognitive-​behavioral treatment of bulimia nervosa: Data from a multisite study. American Journal of Psychiatry, 157, 13. Agras, W. S., Fitzsimmons-​ Craft, & Wilfley, D. E. (2017). Evoulation of cognitive-​behavioral therapy for eating disorders. Behaviour Research and Therapy, 88, 26–​36. Agras, W. S., Walsh, B. T., Fairburn, C. G., Wilson, G. T., & Kraemer, H. C. (2000). A multicenter comparison of cognitive-​behavioral therapy and interpersonal psychotherapy for bulimia nervosa. Archives of General Psychiatry, 57, 459–​466. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author. Andersson, G. (2009). Using the Internet to provide cognitive behavior therapy. Behaviour Research and Therapy, 47, 175–​180. Andrews, G., Cuijpers, P., Craske, M. G., McEvoy, P., & Titov, N. (2010). Computer therapy for the anxiety and depressive disorders in effective, acceptable and practical health care: A meta-​analysis. PLoS ONE, 5, e13196. Attia, E., Becker, A., Bryant-​Waugh, R., Hoek, H., Kreipe, R., Marcus, M.,  . . .  Wonderlich, S. (2013). Feeding and eating disorders in DSM-​5. American Journal of Psychiatry, 170, 1237–​1239. Banasiak, S. J., Paxton, S. J., & Hay, P. (2005). Guided self-​help for bulimia nervosa in primary care:  A  randomized controlled trial. Psychological Medicine, 35, 1283–​1294. Bodell, P., & Devlin, M. (2010). Pharmacotherapy for binge-​ eating disorder. In C. Grilo & J. Mitchell (Eds.), The treatment of eating disorders (pp. 402–​414). New  York, NY: Guilford Press. Bulik, C. (2014). The challenges of treating anorexia nervosa. Lancet, 383, 105–​106. Byrne, S. M., Fursland, A., Allen, K. L., & Watson, H. (2011). The effectiveness of enhanced cognitive behavioural therapy for eating disorders:  An open trial. Behaviour Research and Therapy, 49, 219–​226. Cachelin, F. M., Shea, M., Phimphasone, P., Wilson, G. T., Thompson, D. R., & Striegel, R. H. (2014). Culturally adapted cognitive behavioral guided self-​help for binge eating:  A  feasibility study with Mexican Americans. Cultural Diversity and Ethnic Minority Psychology, 20, 449–​457. Calugi, S., El Ghoch, M., & Dalle-​Grave, R. (2017). Intensive enhanced cognitive behavioural therapy for severe and enduring anorexia nervosa:  A  longitudinal outcome study. Behaviour Research and Therapy, 89, 41–​48. Carter, J. C., & Fairburn, C. G. (1998). Cognitive-​behavioral self-​help for binge eating disorder:  A  controlled effectiveness study. Journal of Consulting and Clinical Psychology, 66, 616–​623. Chowdhary, N., Jotheeswaran, A. T., Nadkarni, A., Hollon, S. D., King. M., Jordans, M. J. D.,  . . .  Patel, V. (2014). The methods and outcomes of cultural adaptations of psychological treatments for depressive disorders:  a systematic review. Psychological Medicine, 44, 1131–​1146.

284

Cognitive-Behavioral Therapy

Cooper, Z., Allen, E., Bailey-​Straebler, S., Basden, S., Murphy, R., O’Connor, M. E., & Fairburn, C. G. (2016). Predictors and moderators of response to enhanced cognitive behaviour therapy and interpersonal psychotherapy for the treatment of eating disorders. Behaviour Research and Therapy, 84, 9–​13. Dalle-​Grave, R., Calugi, S., Doll, H. A., & Fairburn, C. G. (2013). Enhanced cognitive behaviour therapy for adolescents with anorexia nervosa:  An alternative to family therapy? Behaviour Research and Therapy, 51, R9–​R12. DeBar, L. L., Striegel-​Moore, R. H., Wilson, G. T., Perrin, N., Yarborough, B. J., Dickerson, J.,  . . .  Kraemer, H. (2011). Guided self-​help treatment for recurrent binge eating: Replication and extension. Psychiatric Services, 62, 367–​373. Devlin, M., Goldfein, J., Petkova, E., Liu, L., & Walsh, B. T. (2007). Cognitive behavioral therapy and fluoxetine for binge eating disorder; two-​year follow-​up. Obesity Research, 15, 1702–​1709. Fairburn, C. G. (1995). Overcoming binge eating. New  York, NY: Guilford Press. Fairburn, C. G. (2008). Cognitive behavior therapy and eating disorders. New York, NY: Guilford Press. Fairburn, C. G. (2013). Overcoming binge eating (2nd ed.). New York, NY: Guilford Press. Fairburn, C. G., Agras, W. S., Walsh, B. T., Wilson, G. T., & Stice, E. (2004). Prediction of outcome in bulimia nervosa by early change in treatment. American Journal of Psychiatry, 161, 2322–​2324. Fairburn, C. G., Bailey-​Straebler, S., Basden, S., Doll, H. A., Jones, R., Murphy, R.,  . . .  Cooper, Z. (2015). A transdiagnostic comparison of enhanced cognitive behaviour therapy (CBT-​E) and interpersonal psychotherapy in the treatment of eating disorders. Behaviour Research and Therapy, 70, 64–​71. Fairburn, C. G. & Cooper, Z. (2011). Therapist competence, therapy quality and therapist training. Behaviour Research and Therapy, 50, 373–​378. Fairburn, C. G., Cooper, Z., Doll, H. A., O’Connor, M. E., Bohn, K., Hawker, D. B.,   .  .  .  Palmer, R. L. (2009). Transdiagnostic cognitive-​ behavioral therapy for patients with eating disorders: A two-​site trial with 60-​week follow-​ up. American Journal of Psychiatry, 166, 311–​319. Fairburn, C. G., Cooper, Z., Doll, H. A., O’Connor, M. E., Palmer, R. L., & Dalle-​Grave, R. (2013). Enhanced cognitive behaviour therapy for adults with anorexia nervosa: A UK-​ Italy study. Behaviour Research and Therapy, 51, R2–​R8. Fairburn, C. G., Cooper, Z., & Shafran, R. (2008). Enhanced cognitive behavior therapy for eating disorders (“CBT-​ E”): An overview. In C. G. Fairburn (Ed.), Cognitive behavior therapy and eating disorders (pp. 23–​34). New  York, NY: Guilford Press. Fairburn, C. G., Jones, R., Hope, R. A., O’Connor, M., & Peveler, R. C. (1993). Psychotherapy and bulimia nervosa:  Longer-​ term effects of interpersonal psychotherapy, behaviour therapy, and cognitive behavior therapy. Archives of General Psychiatry, 50, 419–​428. Fairburn, C. G., Marcus, M. D., & Wilson. G. T. (1993). Cognitive behaviour therapy for binge eating and bulimia nervosa:  A  comprehensive treatment manual. In C. G. Fairburn & G. T. Wilson (Eds.), Binge eating:  Nature, assessment and treatment (pp. 361–​404). New  York, NY: Guilford Press. Fairburn, C. G., & Patel, V. (2014). The global dissemination of psychological treatments: A road map for research and practice. American Journal of Psychiatry, 171, 495–​498.

Fairburn, C. G., & Patel, V. (2017). The impact of digital technology on psychological treatments and their dissemination. Behaviour Research and Therapy, 88, 19–​25. Fairburn, C. G., Peveler, R. C., Jones, R., Hope, R. A., & Doll, H. (1993). Predictors of 12-​ month outcome in bulimia nervosa and the influence of attitudes to shape and weight. Journal of Consulting and Clinical Psychology, 61, 696–​698. Grilo, C. M. (2013). Why no cognitive body image feature such as overvaluation of shape/​weight in the binge eating disorder diagnosis? International Journal of Eating Disorders, 46, 208–​211. Grilo, C. M., Crosby, R. D., Wilson, G. T., & Masheb, R. M. (2012). 12-​month follow-​up of fluoxetine and cognitive behavioral therapy for binge eating disorder. Journal of Consulting and Clinical Psychology, 80, 1108–​1113. Grilo, C. M., Masheb, R. M., & Crosby, R. D. (2012). Predictors and moderators of response to cognitive behavioral therapy and medication for the treatment of binge eating disorder. Journal of Consulting and Clinical Psychology, 80, 897–​906. Grilo, C. M., Masheb, R., & Wilson, G. T. (2005). Efficacy of cognitive behavioral therapy and fluoxetine for the treatment of binge eating disorder: A randomized double-​blind placebo-​controlled trial. Biological Psychiatry, 57, 301–​309. Grilo, C. M., Masheb, R. M., & Wilson, G. T. (2006). Rapid response to treatment for binge eating disorder. Journal of Consulting and Clinical Psychology, 74, 602–​613. Grilo, C. M., Masheb, R. M., & Wilson, G. T. (2011). Cognitive-​behavioral therapy, behavioral weight loss, and sequential treatment for obese patients with binge-​eating disorder: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 79, 675–​685. Grilo, C. M., Reas, D. L., & Mitchell, J. E. (2016). Combining pharmacological and psychological treatments for binge eating disorder:  Current status, limitations, and future directions. Current Psychiatry Reports, 18, 55. Grilo, C. M., White, M. A., Gueorguieva, R., Wilson, G. T., & Masheb, R. M. (2012). Predictive significance of the overvaluation of shape/​weight in obese patients with binge eating disorder:  findings from a randomized controlled trial with 12-​month follow-​up. Psychological Medicine, 43, 1335–​1344. Grilo, C. M., White, M. A., Wilson, G. T., Gueorguieva, R., & Masheb, R. M. (2012). Rapid response predicts 12-​month post-​ treatment outcomes in binge-​ eating disorder:  theoretical and clinical implications. Psychological Medicine, 42, 807–​817. Herschell, A. D., Kolko, D., Baumann, B., & Davis, A. (2010). The role of therapist training in the implementation of psychosocial treatments: A review and critique with recommendations. Clinical Psychology Review, 30, 448–​460. Hilbert, A., Hildebrandt, T., Agras, W. S., Wilfley, D. E., & Wilson, G. T. (2015). Rapid response in psychological treatments for binge eating disorder. Journal of Consulting and Clinical Psychology, 83, 649–​654. Hollon, S. D., & Wilson, G. T. (2014). Psychoanalysis or cognitive-​behavioral therapy for bulimia nervosa: The specificity of psychological treatments. American Journal of Psychiatry, 171, 13–​16. Kahneman, D. (2011). Thinking, fast and slow. New  York, NY: Farrar, Straus, & Giroux. Kazdin, A. E. (2017). Addressing the treatment gap: A key challenge for extending evidence-​based psychosocial interventions. Behaviour Research and Therapy, 88, 7–​18.

Kazdin, A. E., & Blase, S. (2011). Rebooting psychotherapy research and practice to reduce the burden of mental illness. Perspectives on Psychological Sciences, 6, 21–​37. Kazdin, A. E., & Rabbitt, S. M. (2013). Novel models for delivering mental health services and reducing the burdens of mental illness. Clinical Psychological Science, 1, 170–​191. Kilpela, L., Hill, K., Kelly, M. C., Elmquist, J., Ottoson, P., Keith, D.,  . . .  Becker, C. B. (2014). Reducing eating disorder risk factors: A controlled investigation of a blended task-​ shifting/​ train-​ the-​ trainer approach to dissemination and implementation. Behaviour Research and Therapy, 63, 70–​82. Knott, S., Woodward, D., Hoefkens, A., & Limbert, C. (2015). Cognitive behaviour therapy for bulimia nervosa and eating disorders not otherwise specified: Translation from randomized controlled trial to a clinical setting. Behavioural and Cognitive Psychotherapy, 6, 641–​654. Layard, R., & Clark, D. M. (2014). Thrive. London, UK: Penguin Books. Lilienfeld, S. O., Ritschel, L. A., Jay-​Lynn, S., Brown, A. P., Cautin, R. L., & Latzman, R. D. (2013). The research-​ practice gap:  Bridging the schism between eating disorder researchers and practitioners. International Journal of Eating Disorders, 46, 386–​394. Ljotsson, B., Lundin, C., Mitsell, K., Carlbring, P., Ramklint, M., & Ghaderi, A. (2007). Remote treatment of bulimia nervosa and binge eating disorder:  A  randomized trial of Internet assisted cognitive behavioural therapy. Behaviour Research and Therapy, 45, 649–​661. Loucas, C. E., Fairburn, C. G., Whittington, C., Pennant, M. E., Stockton, S., & Kendall, T. (2014). E-​therapy in the treatment and prevention of eating disorders:  A  systematic review and meta-​analysis. Behaviour Research and Therapy, 63, 122–​131. Luborsky, L, Diguer, L., Seligman, D. A., Rosenthal, R., Krause, E. D., Johnson, S.,  . . .  Schweizer, E. (1999). The researcher’s own therapy allegiances: A “wild card” in comparison of treatment efficacy. Clinical Psychology:  Science and Practice, 6, 9–​106. Lynch, F. L., Dickerson, J., Perrin, N., DeBar, L., Wilson, G. T., Kraemer, H., & Striegel-​Moore, R. (2010). Cost-​effectiveness of treatment for recurrent binge eating. Journal of Consulting and Clinical Psychology, 78, 322–​333. McElroy, S. L., Hudson, J. I., Mitchell, J. E., Wilfley, D., Ferreira-​Cornwell, M. C., Gao, J.,  . . .  Gasior, M. (2015). Efficacy and safety of lisdexamfetamine for treatment of adults with moderate to severe binge-​eating disorder: A randomized clinical trial. JAMA Psychiatry, 72, 235–​246. Mitchell, J., Agras, W. S., Crow, S., Halmi, K., Fairburn, C. G., Bryson, S.,  . . .  Kraemer, H. (2011). Stepped-​care and cognitive behavioral therapy for bulimia nervosa:  Randomised trial. British Journal of Psychiatry, 19, 391–​397. Munsch, S., Biedert, E., Meyer, A., Michael, T., Schlup, B., Tuch, A.,  . . .  Margraf, J. (2007). A randomized comparison of cognitive behavioral therapy and behavioral weight loss treatment for individuals with binge eating disorder. International Journal of Eating Disorders, 40, 102–​113. National Institute for Clinical Excellence. (2004). Eating disorders—​Core interventions in the treatment and management of anorexia nervosa, bulimia nervosa and related eating disorders. NICE Clinical. Guideline No. 9. London, UK: NICE. www. nice.org.uk. Patel, V., Chowdhary, N., Rahman, A., & Verdeli, H. (2011). Improving access to psychological treatments: Lessons from

Wilson

285

developing countries. Behaviour Research and Therapy, 49, 523–​528. Patel, V., Weobong, B., Weiss, H., Anand, A., Bhat, B., Katti, B.,  . . .  Fairburn, C. F. (2017). The Healthy Activity Program (HAP), a lay counselor-​delivered brief psychological treatment for severe depression, in primary care in India: A randomized controlled trial. Lancet, 389, 176–​185. Poulsen, S., Lunn, S., Daniel, S. I. F., Folke, S., Bork-​Mathiesen, B., Katznelson, H., & Fairburn, C. G. (2014). A randomized controlled trial of psychoanalytic psychotherapy or cognitive-​behavioral therapy for Bulimia Nervosa. American Journal of Psychiatry, 171, 109–​116. Reas, D. L., & Grilo, C. M. (2008). Review and meta-​analysis of pharmacotherapy for binge eating disorder. Obesity, 16, 2024–​2038. Schmidt, U., Lee, S., Beecham, J., Perkins, S., Treasure, J., Yi., L.,  . . .  Johnson-​Sabine, E. (2007). A randomized controlled trial of family therapy and cognitive-​behavioral guided self-​ care for adolescents with bulimia nervosa or related disorders. American Journal of Psychiatry, 164, 591–​598. Schmidt, U., & Treasure, J. (1993). Getting better bit(e) by bit(e). East Sussex, UK: Psychology Press. Shafran, R., Clark, D. M., Fairburn, C. G., Arntz, A., Barlow, D. H., Ehlers, A.,   .  .  .  Wilson, G. T. (2009). Mind the gap:  Improving the dissemination of CBT. Behaviour Research and Therapy, 47, 902–​907. Shea, M., Cachelin, F., Uribe, L., Striegel-​ Moore, R., H., Thompson, D., & Wilson, G. T. (2012). Cultural adaptation of a cognitive-​behavioral therapy-​guided self-​help program for Mexican American women with binge eating disorders. Journal of Counseling and Development, 90, 308–​312. Striegel-​Moore, R. H., Wilson, G. T., DeBar, L., Perrin, N., Lynch, F., Rosselli, F., & Kraemer, H. C. (2010). Cognitive behavioral guided self-​help for the treatment of recurrent binge eating. Journal of Consulting and Clinical Psychology, 78, 312–​321. Sysko, R., Hildebrandt, T., Wilson, G. T., Wilfley, D. E., & Agras, W. S. (2010). Heterogeneity moderates treatment response among patients with binge eating disorder. Journal of Consulting and Clinical Psychology, 78, 681–​690. Sysko, R., & Walsh, B. T. (2007). Guided self-​help for bulimia nervosa. In J. Latner & G. T. Wilson (Eds.), Self-​help for obesity and binge eating. New York, NY: Guilford Press. Thompson-​Brenner, H., Franko, D. L., Thompson, D. R., Grilo, C. M., Boisseau, C. L., Roehrig, J. P.,  . . .  Wilson, G. T. (2013). Race/​ethnicity, education, and treatment parameters as moderators and predictors of outcome in binge eating disorder. Journal of Consulting and Clinical Psychology, 81, 710–​721. Turner, H., Marshall, E., Stopa, L., & Waller, G. (2015). Cognitive-​behavioral therapy for outpatients with eating disorders: Effectiveness for a transdiagnostic group in a routine clinical setting. Behaviour Research and Therapy, 68, 70–​75. Vall, E., & Wade, T. (2015). Prediction of treatment outcome in individuals with eating disorders:  A  systematic review and meta-​analysis. International Journal of Eating Disorders, 48, 946–​971. Wales, J. A., Palmer, R. L., & Fairburn, C. G. (2009). Can treatment trial samples be representative? Behaviour and Research Therapy, 47, 893–​896. Wallace, L. M., & von Ranson, K. M. (2012). Perceptions and use of empirically-​supported psychotherapies among eating

286

Cognitive-Behavioral Therapy

disorder professionals. Behaviour Research and Therapy, 50, 215–​222. Waller, G., Stringer, H., & Meyer, C. (2012). What cognitive behavioral techniques do therapists report using when delivering cognitive behavioral therapy for eating disorders? Journal of Consulting and Clinical Psychology, 80, 171–​175. Wilfley, D. E., Agras, W. S., Telch, C. F., Rossiter, E. M., Schneider, J. A., Cole, A. G.,  . . .  Raeburn, S. D. (1993). Group cognitive-​ behavioral therapy and group interpersonal psychotherapy for the nonpurging bulimic individual:  A  controlled comparison. Journal of Consulting and Clinical Psychology, 61, 296–​305. Wilfley, D. E., Welch, R. R., Stein, R. I., Spurrell, E. B., Cohen, L. R., Saelens, B. E.,  . . .  Matt, G. E. (2002). A randomized comparison of group cognitive-​behavioral therapy and group interpersonal psychotherapy for the treatment of overweight individuals with binge eating disorder. Archives of General Psychiatry, 59, 713–​721. Wilson, G. T. (1996). Manual-​ based treatments:  The clinical application of research findings. Behaviour Research and Therapy, 34, 295–​315. Wilson, G. T. (2010). Cognitive behavior therapy for eating disorders. In W. S. Agras (Ed.), Handbook of eating disorders. New York, NY: Oxford University Press. Wilson, G. T., Fairburn, C. G., & Agras, W. S. (1997). Cognitive-​ behavioral therapy for bulimia nervosa. In D. M. Garner & P. Garfinkel (Eds.), Handbook of treatment for eating disorders (pp. 67–​93). New York: Gilfoprd Press. Wilson, G. T., Fairburn, C. G., Agras, W. S., Walsh, B. T., & Kraemer, H. D. (2002). Cognitive behavior therapy for bulimia nervosa:  Time course and mechanisms of change. Journal of Consulting and Clinical Psychology, 70, 267–​274. Wilson, G. T., & Schlam, T. R. (2004). The transtheoretical model and motivational interviewing in the treatment of eating and weight disorders. Clinical Psychology Review, 24, 361–​378. Wilson, G. T. & Shafran, R. (2005). Eating disorders guidelines from NICE. Lancet, 365, 79–​81. Wilson, G. T., Wilfley, D. E., Agras, W. S., & Bryson, S. W. (2010). Psychological treatments for binge eating disorder. Archives of General Psychiatry, 67, 94–​101. Wilson, G. T., Wilfley, D. E., Agras, W. S., & Bryson, S. W. (2011). Allegiance bias and therapist effects:  Results of a randomized controlled trial of binge eating disorder. Clinical Psychology, 18, 119–​125. Wilson, G. T., & Zandberg, L. J. (2012). Cognitive-​behavioral guided self-​help for eating disorders: Effectiveness and scalability. Clinical Psychology Review, 32, 343–​357. Wolitzky-​Taylor, K., Zimmermann, M., Arch, J. J., De Guzman, E., & Lagomasino, I. (2015). Has evidence-​based psychosocial treatment for anxiety disorders permeated usual care in community mental health settings? Behaviour Research and Therapy, 72, 9–​17. Zandberg, L. J., & Wilson, G. T. (2013). Train-​ the-​ trainer:  Implementation of cognitive behavioral guided self-​help for recurrent binge eating in a naturalistic setting. European Eating Disorders Review, 21, 230–​237. Zipfel, S., Wild, B., Grob, G., Friederich, Hans-​Christof, Teufel, H.,  . . .  Herzog, W. (2014). Lancet, 383, 127–​137.



CH A PT E R

 Interpersonal Psychotherapy for the Treatment of Eating Disorders

15

Natasha L. Burke, Anna M. Karam, Marian Tanofsky-​Kraff, and Denise E. Wilfley

Abstract Interpersonal psychotherapy (IPT) is a focused, time-​limited treatment that targets interpersonal problem(s) associated with the onset and/​or maintenance of eating disorders. It is supported by substantial empirical evidence documenting the role of interpersonal factors in the onset and maintenance of eating disorders. Interpersonal psychotherapy is a viable alternative to cognitive-​ behavioral therapy for the treatment of bulimia nervosa and binge eating disorder. The effectiveness of IPT for the treatment of anorexia nervosa requires further investigation. The utility of IPT for the prevention of obesity is promising. Future research directions include enhancing the delivery of IPT for eating disorders, increasing the availability of IPT in routine clinical care settings through dissemination and implementation efforts, exploring IPT adolescent and parent-​child adaptations in diverse and high-​ risk groups, and further exploring IPT for the prevention of eating and weight-​related problems that may promote full-​syndrome eating disorders or obesity. Key Words:  interpersonal relationships, social functioning, eating disorder, obesity, interpersonal psychotherapy (IPT), group therapy

Introduction

Interpersonal psychotherapy (IPT) is a brief, time-​limited therapy that focuses on improving interpersonal functioning and, in turn, psychiatric symptoms, by relating symptoms to interpersonal problem areas and targeting strategies to improve these problems (Freeman & Gil, 2004; Klerman, Weissman, Rounsaville, & Chevron, 1984). Originally developed by Gerald Klerman and colleagues (Klerman et  al., 1984) for the treatment of unipolar depression, IPT is an efficacious treatment for bulimia nervosa (BN) (Fairburn et  al., 1991; Fairburn, Peveler, Jones, Hope, & Doll, 1993) and binge eating disorder (BED) (Wilfley et  al., 1993; Wilfley, Frank, Welch, Spurrell, & Rounsaville, 1998; Wilfley et  al., 2002; Wilson, Wilfley, Agras, & Bryson, 2010). There are limited data from randomized-​controlled trials on the effectiveness of IPT in the treatment of anorexia nervosa (AN).

This chapter provides an overview of interpersonal theory and its foundation for IPT. It provides a brief review of the literature supporting the central role that interpersonal functioning plays in the development, manifestation, and maintenance of eating disorders. The delivery of IPT for eating disorders is also explained, along with a description of the major tenets of the treatment. Empirical evidence supporting IPT’s efficaciousness for the treatment of BN and BED is reviewed, as is the limited data on the use of IPT for AN. A  discussion of an adaptation of IPT for obesity prevention follows. Where appropriate, we provide vignettes as examples. Finally, more recent changes to the delivery of IPT are described, and future directions are proposed.

Interpersonal Theory

Interpersonal psychotherapy is grounded in theories developed by Meyer, Sullivan, and Bowlby, 287

which hypothesize that interpersonal functioning is recognized as a critical component of psychological adjustment and well-​being. In the 1950s, Meyer postulated that psychopathology was rooted in maladjustment to one’s social environment (Frank & Spanier, 1995; Klerman et al., 1984; Meyer, 1957). During the same time period, Sullivan (who was responsible for popularizing the term “interpersonal”) theorized that a patient’s interpersonal relationships, rather than intrapsychic processes alone, established the relevant focus of therapeutic attention. Sullivan believed that individuals could not be understood in isolation from their interpersonal relationships and posited that enduring patterns in these relationships could either encourage self-​ esteem or result in anxiety, hopelessness, and psychopathology. Interpersonal psychotherapy is also associated with the work of John Bowlby (1982), the originator of attachment theory. Bowlby emphasized the importance of early attachment to the later development of interpersonal relationships and emotional well-​being. He also hypothesized failures in attachment resulted in later psychopathology. The interpersonal roles of major interest to IPT occur within the nuclear family (as parent, child, sibling, partner); the extended family; the friendship group; the work milieu (as supervisor, supervisee, or peer); and the neighborhood or community. Incorporating aspects of the theories posited by Meyer, Sullivan, and Bowlby, IPT acknowledges a two-​ way relationship between social functioning and psychopathology; disturbances in social roles can serve as antecedents for psychopathology, and mental illness can produce impairments in the individual’s capacity to perform social roles (Bowlby, 1982). Therefore, IPT is derived from a theory in which interpersonal functioning is recognized as a critical component of psychological adjustment and well-​being. It should be noted that IPT makes no assumptions about the causes of psychiatric illness; however, IPT does assume that the development and maintenance of some psychiatric illnesses occur in a social and interpersonal context and that the onset, response to treatment, and outcomes are influenced by the interpersonal relations between the patient and significant others. We describe the major tenets of IPT for eating disorders in this chapter. However, the extensive empirical background and theoretical foundation, as well as the strategies and techniques of IPT, are fully described in a comprehensive book by Myrna Weissman and her colleagues (Weissman, Markowitz, & Klerman, 2000). 288

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The Interpersonal Model for Eating Disorders

The interpersonal model for eating disorders suggests that problems with social functioning cause difficulties with low self-​esteem and negative affect, which then lead to binge eating behaviors (Wilfley, Pike, & Striegel-​Moore, 1997). Data support this model. Eating disorders have been consistently associated with poor interpersonal functioning (Arcelus, Haslam, Farrow, & Meyer, 2013; Wilfley, Stein, & Welch, 2005) including interpersonal problem-​ solving difficulties, negative attitudes toward emotional expression, and fear of intimacy and interpersonal distrust (Arcelus et  al., 2013). Individuals with eating disorders report past difficult social experiences, problematic family histories, and specific interpersonal stressors more often than non-​ eating-​disordered individuals (Fairburn et al., 1998; Fairburn, Welch, Doll, Davies, & O’Connor, 1997). Persons with bulimic symptoms tend to experience a wide range of social problems, including loneliness, lack of perceived social support, and poor self-​esteem and social adjustment, and also often demonstrate difficulty with social problem-​solving skills (Crow, Stewart Agras, Halmi, Mitchell, & Kraemer, 2002; Ghaderi & Scott, 1999; Grissett & Norvell, 1992; Gual et al., 2002; Johnson, Spitzer, & Williams, 2001; O’Mahony & Hollwey, 1995a; Rorty, Yager, Buckwalter, & Rossotto, 1999; Steiger, Gauvin, Jabalpurwala, Seguin, & Stotland, 1999; Troop, Holbrey, Trowler, & Treasure, 1994; Wilfley, Wilson, & Agras, 2003). For individuals with BED, greater interpersonal problems are related to earlier onset of binge eating behaviors and persistent, ineffective interpersonal styles (Blomquist, Ansell, White, Masheb, & Grilo, 2012). Indeed, individuals with BED tend to lack interpersonal problem-​solving skills (Svaldi, Dorn, & Trentowska, 2011), and have interpersonal hostility and distress (Duchesne et  al., 2012) and negative marital interactions (Whisman, Dementyeva, Baucom, & Bulik, 2012). Heightened sensitivity to interpersonal interactions appears to be a common component among individuals with symptoms of eating disorders (Evans & Wertheim, 1998; Humphrey, 1989; Steiger et  al., 1999; Tasca, Taylor, Ritchie, & Balfour, 2004; Troisi, Massaroni, & Cuzzolaro, 2005). Laboratory paradigms suggest that interpersonal distress may trigger overeating (Steiger et  al., 1999; Tanofsky-​Kraff, Wilfley, & Spurrell, 2000) and potentially perpetuate binge eating, as evidenced in both clinical and nonclinical samples

(Ansell, Grilo, & White, 2012; Hartmann, Zeeck, & Barrett, 2010; Ivanova, Tasca, Proulx, & Bissada, 2015). When assessed via ecological momentary assessment, interpersonal problems moderate the relation between negative affect and binge eating in adults (Ambwani, Roche, Minnick, & Pincus, 2015) and predict increases in negative affect and loss of control eating in youth (Ranzenhofer et al., 2014). Similarly, negative affect mediates the relation between social problems and loss of control eating in non-​ treatment-​ seeking youth (Elliott et al., 2010). Further, interpersonal difficulties, low self-​esteem, and negative affect are likely interconnected in a reciprocal fashion (Fairburn et al., 1998; Fairburn et al., 1997; Gual et al., 2002) and serve to perpetuate a cycle, with each factor exacerbating the other and combining to precipitate and/​or maintain dysfunctional bulimic or binge eating patterns (Herzog, Keller, Lavori, & Ott, 1987; Lavender et al., 2016). Individuals with AN also report difficulties with psychosocial functioning (Hartmann et al., 2010; O’Mahony & Hollwey, 1995b; Raykos, McEvoy, Carter, Fursland, & Nathan, 2014; Ruuska, Koivisto, Rantanen, & Kaltiala-​Heino, 2007) compared with controls and individuals at elevated risk for eating disorders (O’Mahony & Hollwey, 1995b). For individuals with BED, BN, AN, and subclinical eating pathology, negative affect partially explains the association between interpersonal problems and eating disorder psychopathology (Ivanova, Tasca, Hammond, et al., 2015; Ivanova, Tasca, Proulx, et al., 2015). Most recently, Stice and colleagues (2017) report that interpersonal functioning and negative affect are two of the most robust risk factors for all types of eating disorders (Stice, Gau, Rohde, & Shaw, 2017). Interpersonal functioning is also implicated in eating disorder treatment outcomes with interpersonal problems at the start of treatment relating to poorer treatment outcomes (Jones, Lindekilde, Lubeck, & Clausen, 2015; Vall & Wade, 2015). Therefore, in theory, the use of an interpersonally focused intervention appears to be especially suitable for the treatment of eating disorders (Rieger et al., 2010). Interpersonal psychotherapy is designed to improve interpersonal functioning and self-​esteem, reduce negative affect and, in turn, decrease eating disorder symptoms.

Interpersonal Psychotherapy for Eating Disorders

The core tenets of IPT are maintained in the treatment of eating disorders.

Basic Interpersonal Psychotherapy Concepts

Interpersonal psychotherapy has been adapted for a range of clinical disorders (Weissman et  al., 2000), but a number of basic concepts are common across all adaptations of IPT, including treatment for eating disorders. Specifically, adaptations for IPT all focus on interpersonal problem areas and maintain a similar treatment structure. Given the time-​limited nature of IPT, treatment success hinges on the therapist’s rapid discernment of patterns in interpersonal relationships and the linking of these patterns to symptoms that may have precipitated and continue to maintain the disorder. Thus, in IPT for the treatment of eating disorders, treatment centers on facilitating a patient’s awareness of the links among their relationship interactions, negative affect, and disordered eating symptoms. Early identification of the problem area(s) and treatment goals by the therapist and patient is crucial. Throughout every session, interpersonal functioning is continuously linked to the onset and maintenance of the eating disorder. Interpersonal Problem Areas A primary aim of IPT is to help patients identify and address current interpersonal problems. By focusing on current as opposed to past relationships, IPT makes no assumptions about the etiology of an eating disorder. Treatment focuses on the resolution of problems within four social domains that are associated with the onset and/​or maintenance of the eating disorder:  (1)  interpersonal deficits, (2) interpersonal role disputes, (3) role transitions, and (4)  grief. Interpersonal deficits apply to those patients who are either socially isolated or who are involved in chronically unfulfilling relationships. For clients with this problem area, unsatisfying relationships and/​or inadequate social support are frequently the result of poor social skills. Interpersonal role disputes refer to conflicts with a significant other (e.g., a partner, other family member, coworker, or close friend) that emerge from differences in expectations about the relationship. Role transitions include difficulties associated with a change in life status (e.g., graduation, leaving a job, moving, marriage/​divorce, retirement, changes in health). The problem area of grief is identified when the onset of the patient’s symptoms is associated with either the recent or past loss of a person or a relationship. Making use of this framework for defining one or more interpersonal problem areas, IPT for eating disorders focuses on identifying and changing the

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maladaptive interpersonal context in which the eating problem has developed and been maintained. The four problem areas are discussed in detail in the section “Intermediate Phase.” Treatment Structure Interpersonal psychotherapy for eating disorders is a time-​delineated treatment that typically includes 15–​20 sessions over 4–​5  months. Regardless of the exact number of sessions, IPT is delivered in three phases. The initial phase is dedicated to identifying the problem area(s) that will be the target for treatment. The intermediate phase is devoted to working on the target problem area(s). The termination phase is devoted to consolidating gains made during treatment and preparing patients for future work on their own.

Implementing Interpersonal Psychotherapy for Eating Disorders

The three phases of IPT for eating disorders are discussed in detail. The Initial Phase Sessions 1–​5 typically constitute the initial phase of IPT for eating disorders. The patient’s current eating disorder symptoms are assessed, and a history of these symptoms is obtained. The clinician provides the patient with a formal diagnosis. The eating disorder diagnosis and expectations for treatment are discussed. An assignment of the “sick role” (described in further detail below) during this phase serves several functions, including granting the patient the permission to recover, delineating recovery as a responsibility of the patient, and allowing the patient to be relieved of other responsibilities in order to recover. The therapist explains the rationale of IPT, emphasizing that therapy will focus on identifying and altering current dysfunctional interpersonal patterns related to eating disorder symptomatology. In order to determine the precise focus of treatment, the clinician conducts an “interpersonal inventory” with the patient and, in doing so, develops an interpersonal formulation that specifically relates to the patient’s eating disorder. In the interpersonal formulation, the therapist links the patient’s eating disorder to at least one of the four interpersonal problem areas. The patient’s concurrence with the clinician’s identification of the problem area and agreement to work on this area are essential in order to begin the intermediate phase of treatment. Indeed, a collaborative effort is promoted throughout the interpersonal inventory and all therapy sessions. 290

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Diagnosis and Assignment of the Sick Role Following a psychiatric assessment, the patient is formally diagnosed with an eating disorder and assigned what is termed the “sick role.” The assignment of the sick role is theoretical and serves a practical purpose. Consistent with the medical model, receiving a formal diagnosis reinforces the understanding that the patient has a known condition that can be treated. Accurate diagnosis is essential to successful treatment. Providing a diagnosis also explicitly identifies the patient as being in need of help. The sick role is assigned not to demean the patient but rather to temporarily exempt the individual from other responsibilities in order to devote full attention to recovery. This is particularly important for individuals with a tendency to set aside their own needs and desires in order to care for and please others. If appropriate, the IPT therapist might explicitly highlight the patient’s excessive caretaking tendencies and encourage the patient to redirect this energy from others toward self-​recovery. The Interpersonal Inventory A primary and critical component of the initial phase of IPT is the interpersonal inventory. The interpersonal inventory involves a thorough examination of the patient’s interpersonal history. Although clinicians have historically taken up to three sessions to complete the interpersonal inventory, we recommend conducting a longer (approximately 2-​hour) first session to complete the entire interpersonal inventory. This allows for patients to get “on board” early in terms of their understanding of IPT and how their eating disorder fits into the IPT rationale (Tanofsky-​Kraff & Wifley, 2009; Wilfley, 2008; Wilfley, MacKenzie, Welch, Ayres, & Weissman, 2000). The interpersonal inventory is essential for adequate case formulation and development of an optimal treatment plan. The clinical importance of investing the time to conduct a comprehensive interpersonal inventory cannot be overemphasized; accurate identification of the patient’s primary problem area(s) is often complicated and is crucial to success in treatment. Table 15.1 illustrates the tasks that should ideally be covered during the first session (Dounchis, Welch, & Wilfley, 1999). The interpersonal inventory involves a review of the patient’s current close relationships, social functioning, relationship patterns, and expectations of relationships. Interpersonal relationships—​both patterns and changes—​are explored and discussed with

Table 15.1  Tasks of the Initial Session(s) Discuss chief complaint and eating disorder symptoms Obtain history of symptoms Place patient in the sick role Establish whether or not there is a history of prior treatments for the eating disorder or other psychiatric Problems Assess patient’s expectations about psychotherapy Reassure patient about positive prognosis Explain IPT and its basic assumptions Complete an Interpersonal Inventory (detailed review of important relationships)  

I. review past interpersonal functioning (e.g., family, school, social)   II. examine current interpersonal functioning (e.g., family, work, social)   III. identify the interpersonal precipitants of episodes of eating disorder symptoms Translate eating disorder symptoms into interpersonal context Explain IPT techniques Contract for administrative details (i.e., length of sessions, frequency, duration of treatment, appointment times) Provide feedback to patient regarding general understanding of her interpersonal difficulties via IPT Problem area (i.e., define interpersonal deficits—​ loneliness and social isolation) Collaborate on a contract regarding the treatment goals Explain tasks in working toward treatment goals Adapted from Dounchis et al., (1999).

reference to the onset and maintenance of eating disorder symptoms. For each significant relationship, the following information is assessed:  frequency of contact, activities shared, satisfactory and unsatisfactory aspects of the relationship, and ways that the patient wishes to change the relationship. The therapist obtains a chronological history of significant life events, fluctuations in mood and self-​esteem, interpersonal relationships, and eating disorder symptoms. Throughout this process, the therapist works collaboratively with the patient to make connections between life experiences and eating disorder

development and symptoms. This exploration provides an opportunity for the patient to clearly understand the relationship between life events, social functioning, and the eating disorder, and thereby clarifies the rationale behind IPT. Upon completion of the interpersonal inventory, the therapist and patient collaboratively identify a primary interpersonal problem area. In some cases, more than one problem area may be identified. Table 15.2 illustrates an example of a “Life Chart” (Fairburn, 1997) developed by an individual with BED and the therapist during the interpersonal inventory (Wilfley, 2008; Wilfley et al., 2000). The Interpersonal Formulation Following completion of the interpersonal inventory, the clinician will have developed an individualized interpersonal formulation that includes the identification of the patient’s primary problem area. Although some patients may present for treatment with difficulties in several problem areas, the time-​limited nature of the treatment necessitates a focused approach. Therefore, the clinician should focus treatment on not only the problem area(s) that appears to impact the patient’s interpersonal functioning most but also those most closely linked to the eating disorder. The therapist, with the agreement of the patient, should assign one, or at most two, problem area(s) on which to develop a treatment plan. We recommend that therapists put the agreed-​on goals in writing and formally present this write-​up to patients. The presentation of documented goals can be a very effective technique that serves as a treatment “contract” (Tanofsky-​Kraff & Wifley, 2009; Wilfley et  al., 2000). The goals developed at this stage are referenced at future sessions and guide the day-​to-​day work of the treatment. If more than one problem area is identified, the patient may choose to work simultaneously on both or may decide to first address the problem area that seems most likely to respond to treatment. For example, when a patient has role disputes and interpersonal deficits, clinical attention might first be focused on role disputes, since interpersonal deficits reflect long-​term patterns that may require considerably more time and effort to change. Once the role dispute has been resolved, the therapist and patient decide how to best address the more entrenched interpersonal deficits. Once the primary problem area(s) have been identified and the treatment goals have been agreed on, the initial phase of treatment is considered complete.

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Table 15.2  Example of a Personal Historical Timeline of a Patient with BED Age

Problems

5

Normal weight

6

Begins gaining weight

Relationships

Events/​circumstances

Moods

Tonsils are removed

14

Grandfather died

Feels sad at funeral but does not cry because she thinks it would be a sign of weakness

15

Concerns about weight; first binge; prescribed amphetamines to lose weight

Sister gets married, borrows money from parents, and files for bankruptcy with her husband

Perceives parents as being extremely disappointed in sister

16

Less concern about weight Meets boyfriend, 23, who because “boyfriend's works at a gas station ex-​wife was a lot heavier than me” but began binge eating

Does not tell parents about boyfriend given father’s high-​profile job and position in the community

Fearful of parents’ disappointment; worries about their finding out

18

Binge eating when alone

Becomes engaged

Graduates from high school; goes to technical school

Loses weight

Tells sisters, not parents

Abortion

Boyfriend breaks off the engagement

Boyfriend “steals” back the ring (seen on his new girlfriend); throws herself into work as a secretary; is promoted repeatedly

Meets new boyfriend, who works as a salesman; he says he is separated from his wife, who is pregnant

Boyfriend’s wife pickets her parents’ house; parents do not make mention of this

More comfortable about weight (“boyfriend's wife was a lot heavier than me”)

Binge eating when alone Lies to family and friends, (“food was my only friend telling them that they got when he was away”); never married ate when with him

27

28

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Binge eating as an outlet

Moves to Minnesota with Secrecy (wanting boyfriend to be “perfect & not disappoint my parents”); homesick

Spouse of coworker tells her he is cheating on her

Throws boyfriend out of the house; on his way out he takes her ring from her jewelry box

Gets pregnant, marries the father, an alcoholic, who is “cruel and verbally abusive”

Lies to mother that she got pregnant after the wedding; birth of first child

Husband occasionally shoves “I channeled my energy her into my son”

Interpersonal Psychotherapy

Does not feel guilty about the relationship

Compliant, scared

Hateful

Table 15.2 Continued Age

Problems

Relationships

Events/​circumstances

Moods

32

“Eating a lot”

Husband hits her; she stands up to husband only once, to ask him to choose between her and alcohol

Does not tell anyone (“Nobody had a clue that we didn’t have a wonderful marriage”)

Scared

Husband no longer drinks but continues being verbally abusive

Continuing Den Mother activities; very active in church

Emotionally distant (“I made it happy for me”)

Has sex with husband Husband invests $20,000 approximately 2 times a year of their joint money in real estate—​all money lost; patient begins saving “every penny,” sending $5,000 to her sister to open a savings account; became a workaholic

Fearful husband will hit her; obedient; proud at holding onto her feelings; derives esteem from keeping her trouble from her children and others

39

41

Eating as a way to “hold everything together”

46

260 lb., highest weight ever; blood pressure increasing with increasing weight

47

Loses 60 lbs.

50

Sexual relationship with husband ends; although she does not express anger, he yells at her, saying he can do whatever he wants with his money Marital therapy with clergy for 3 months

Patient files for divorce Meets current boyfriend

51

Regains 30 lbs.

Moves in with current boyfriend

52

Binge eating at night on objectively large amounts of food at least 3 times per week. Begins psychotherapy

Does not tell family members she is seeking psychological help

Mother dies

Funeral is “a lot less stressful [than my grandfather’s] because I knew it was ok to cry” Feels satisfied with their relationship

Works 14+ hour days, not pausing to eat or rest during the day

Adapted from Wilfley (2008). Interpersonal Psychotherapy for Binge Eating Disorder (BED) Therapist’s Manual and Wilfley et al. (2000). Interpersonal Psychotherapy for Group. New York: Basic Books.

The Intermediate Phase The intermediate phase typically contains 8–​10 sessions and constitutes the “work” stage of the treatment. As currently conceptualized, an essential

task throughout the intermediate phase of IPT for eating disorders is to assist the patient in understanding the connection between difficulties in interpersonal functioning and the eating disorder

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behaviors and symptoms. Therapeutic strategies and goals of this phase are shaped by the primary problem area targeted in the treatment (see Table 15.3; Wilfley, Dounchis, & Welch, 2004). The following sections describe the implementation of specific treatment strategies based on the identified problem area (Wilfley et al., 2005). Problem Areas The four problem areas addressed in treatment are grief, role transitions, interpersonal role disputes, and interpersonal deficits. Grief  Grief is identified as the problem area when the onset of the patient’s symptoms is associated with the death of a loved one, either recent or past. Grief is not limited to the physical death of a loved one. Grief can also result from the loss of a significant relationship or the loss of an important aspect of one’s identity. The goals for treating complicated bereavement include facilitating mourning and helping the patient to find new activities and relationships to substitute for the loss. Reconstructing the relationship, both the positive and negative aspects, is central to the assessment of not only what has been lost but also what is needed to counter the idealization that so commonly occurs. As patients become less focused on the past, they should be

encouraged to consider new ways of becoming more involved with others and establishing new interests (Wilfley et al., 2005). The distribution of the IPT problem areas among individuals with eating disorders has been reviewed by Wilfley and colleagues (2003). For 12% of BN patients, grief has been identified as their primary problem area, while approximately 6% of individuals with AN and 6% with BED present with grief. Role Transitions Role transition includes any difficulties resulting from a change in life status. Common role transitions include a career change (i.e., promotion, firing, retirement, changing jobs), a family change (marriage, divorce, birth of a child, child moving out), the beginning or end of an important relationship, a move, graduation, or diagnosis of a medical illness. The goals of therapy include mourning and accepting loss of the old role, recognizing the positive and negative aspects of both the old and new roles, and restoring the patient’s self-​esteem by developing a sense of mastery in the new role. Key strategies in achieving these goals will include a thorough exploration of the patient’s feelings related to the role change as well as encouraging the patient to develop new skills and adequate social support for the new role (Wilfley et al., 2005). Thirty-​six percent of patients with BN (Wilfley et al., 2003) and 3.7% of individuals with

Table 15.3  Interpersonal Problem Areas Main Problem Area

Description

IPT Strategies

Grief

•  Pathological grief stemming from fears of being unable to tolerate the painful affect associated with the loss

•  Facilitate the patient’s mourning process •  Help the patient reestablish interest in relationships to substitute for what has been lost

Interpersonal role disputes

•  Disputes with partner, children, or other family members, friends, or coworkers

•  Identify the dispute •  Choose a plan of action •  Modify expectations and faulty communication to bring about a satisfactory resolution

Role transitions

•  Economic or family change including •  Mourn and accept the loss of the old role(s) children leaving for college, new job, divorce, •  Restore self-​esteem by developing a sense of retirement, parent’s caretaker mastery regarding the demands of the new role(s)

Interpersonal deficits

•  A long-​standing history of social isolation, •  Reduce the patient’s social isolation low self-​esteem, loneliness, and an inability to •  Encourage the formation of new form or maintain intimate relationships relationships

Adapted from Wilfley, Dounchis, and Welch (2004). Interpersonal psychotherapy of anorexia nervosa. In K. M. Miller, & J. S. Mizes (Eds.), Comparative treatment of eating disorders. New York: Springer Publishing Company, and Dounchis et al. (1999). Using group interpersonal psychotherapy (IPT-​G) for the treatment of binge eating disorders. Paper presented at the Academy of Eating Disorders Annual Meeting, San Diego.

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BED in Wilfley and colleagues’ (2000) trial were identified with the problem area of role transitions. Among individuals with AN, approximately 17% present with role transitions as the primary problem area (Wilfley et al., 2003).

Therapeutic Strategies

Interpersonal Role Disputes  Such disputes are conflicts with a significant other (e.g., a partner, other family member, employer, coworker, teacher, or close friend), which emerge from differences in expectations about the relationship. The goals of treatment include clearly identifying the nature of the dispute and exploring options to resolve it. It is important to determine the stage of the dispute; once the stage of the dispute becomes clear, it may be important to modify the patient’s expectations and remedy faulty communication in order to bring about adequate resolution. It may be particularly helpful to explore how nonreciprocal role expectations relate to the dispute. If resolution is impossible, the therapist assists the patient in dissolving the relationship and in mourning its loss (Wilfley et al., 2005). This problem area is identified in approximately 64% of individuals with BN and 33% of those with AN (Wilfley et al., 2003). Interpersonal role disputes were present in 29.6% of the patients in the Wilfley et al. (2000) BED trial.

Therapeutic Stance As with most therapies, IPT places importance on establishing a positive therapeutic alliance between therapist and patient. The IPT therapeutic stance is one of warmth, support, and empathy. Further, throughout all phases of the treatment, the clinician is active and advocates for the patient rather than remaining neutral. Issues and discussions are framed positively so that the therapist may help the patient feel at ease throughout treatment. Such an approach promotes a safe and supportive working environment. Confrontations and clarifications are offered in a gentle and timely manner, and the clinician is careful to encourage the patient’s positive expectations of the therapeutic relationship. Finally, the therapist conveys a hopeful and optimistic attitude about the potential for the patient to recover.

Interpersonal Deficits  Interpersonal deficits include patients who are socially isolated or who are in chronically unfulfilling relationships. The goal is to reduce the patient’s social isolation by helping enhance the quality of existing relationships and encouraging the formation of new relationships. To help these patients, it is necessary to determine why they have difficulty in forming or maintaining relationships. Carefully reviewing past significant relationships will be particularly useful in making this assessment. During this review, attention should be given to both the positive and negative aspects of the relationships, as well as an investigation of potentially recurrent patterns in these relationships. It may also be appropriate to examine the nature of the patient–​therapist relationship, since this may be the patient’s only close relationship and it is present to be observed (Wilfley et  al., 2005). For patients with BN and AN, this problem area is seen in approximately 16% and 33%, respectively (Wilfley et al., 2003). Based on one study, interpersonal deficits appeared to be the most commonly identified problem area among individuals with BED; 60.5% of patients presented with interpersonal deficits (Wilfley et al., 2000).

In addition to general therapeutic techniques, there are several strategies therapists can use to maximize IPT’s effectiveness.

Focusing on Goals  Because IPT is a directed, goal-​ oriented therapy, therapists should maintain a focus each week on how the patient is working on his/​her agreed-​on goals between sessions. Phrases such as “moving forward on your goals” and “making important changes” are used to encourage patients to be responsible for their treatment while also reminding them that altering interpersonal patterns requires attention and persistence. Sometimes during the course of therapy, unfocused discussions arise. The therapist should sensitively, but firmly, redirect the discussion to the key interpersonal issues. By explicitly addressing goals each week, the patient can work toward necessary changes. This goal-​oriented focus has been supported by research on IPT maintenance treatment for recurrent depression, which has demonstrated that the clinician’s ability to maintain focus on interpersonal themes is associated with better outcomes (Klerman et al., 1984; Markowitz, Skodol, & Bleiberg, 2006; Weissman et al., 2000). In IPT for eating disorders, it is essential that the clinician facilitate and strengthen the recognition of connections between patients’ problematic eating and difficulties in their interpersonal lives. The example that follows illustrates how the IPT therapist initiates the discussion about goals and helps a patient in treatment for BN with interpersonal deficits work on her goals.

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Therapist: Ellie, I would like to check in with you to see how your work on your goals is progressing. Last week, you mentioned that you are starting to become more aware of interpersonal difficulties that trigger your binge eating and purging. Ellie: I have been paying more attention to what is happening when I binge. It seems as though there are a lot of times that I feel the urge to binge, whether it is feeling put down at work, feeling angry at my husband, or feeling overwhelmed about taking care of the kids. I think that I am beginning to better understand what happens with me when I get the urge to binge. I feel overwhelmed—​I have so much going on in my life, I do not know how I will ever overcome the desire to binge. Therapist: I imagine that it must feel very frightening when you have so much going on—​it can seem as though gaining control over your eating might be impossible. However, you have taken a very important first step, Ellie. It is great that you have begun to identify triggers to your binge eating. From your work, it is clear that a lot of things are playing into your desire to binge. How were you able to become more aware of what was happening with you when you felt the urge to binge? Ellie:  I think that instead of just binge eating as soon as I  feel the urge, I  think I  have become aware that something changes for me when I have the urge to binge. Lately, I have been trying hard to stop and see what is going on and what I am feeling before I binge. Even though I have still had binge episodes this week, I think that at least once or twice I seemed to have lost the desire to binge once I stopped and thought about what was going on in that moment. Therapist: What specifically did you notice was happening with you? Ellie: I noticed that I was feeling frustrated about my work and how angry I feel at my husband when he makes me feel like I am an inadequate wife and parent. I realized that I often do not stand up for myself and let the people in my life know what my needs are. I  don’t feel like I  know how to do this and end up expressing—​or is it suppressing?—​my frustration through food. Therapist: This is very important work you are doing, Ellie—​good job! You have identified some really important interpersonal triggers for your binge eating. As you continue to become more and more aware of the circumstances surrounding your urge to binge, we can begin to work on helping you find more effective ways to manage your feelings and relationships so that you are less likely to binge. 296

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As this dialogue between Ellie and her therapist illustrates, a crucial component to IPT for eating disorders is helping to facilitate and strengthen the connections patients make between their problematic eating and difficulties they have in their interpersonal lives. Focusing on specific goals provides the structure for this to be accomplished. Ellie’s ability to have insight to make links between her interactions, mood, and disordered eating is due to the therapist’s persistence in emphasizing the connection between Ellie’s interpersonal functioning to her eating patterns throughout all phases of the treatment. Making Connections During the intermediate phase, it is crucial that the therapist assist patients in recognizing, and ultimately becoming more aware of, the connections between eating difficulties and interpersonal events between sessions. As patients learn to make these connections, the therapist should guide them to develop strategies to alter the interpersonal context in which the disordered eating symptoms occur. As a result, the cycle of the eating disorder is interrupted. Patients are encouraged to make connections between interpersonal functioning and eating patterns that are positive as well. For example, an individual may recognize that communication improved with a significant other and, as a result, the patient did not engage in eating disorder behaviors. To encourage positive and negative connections, clinicians should ask the patient about his/​her eating patterns between sessions and, if there were any changes, inquire about any recognized links between eating patterns and interpersonal functioning. In the following vignette, which is also in the intermediate phase, the therapist encourages a patient with interpersonal role disputes in treatment for AN to talk about the connections she has made between her desire to restrict her food intake and difficulties she experiences with her divorced parents: Therapist: Ashley, have you noticed any connections between your eating and how things went with your parents this past week? Ashley: Well, my parents have been arguing a lot—​ mostly about where I  am going to spend the summer vacation. I just can’t stand it. Whenever they talk badly about the other to me, I’m not hungry at all and I just want to starve myself. Maybe this is a way to make them notice how their fighting gets to me. I don’t know.

Therapist: This is terrific work Ashley! One of the things we have been working on is getting you to become more aware of what is happening when you feel the urge to restrict most intensely. You have just made an important connection between your stress and dislike related to your parents’ arguments and your wanting to restrict. How do think restricting your eating affects your mood? Ashley: Well, focusing on not eating helps me not to think about all the stuff going on between my parents. I feel kind of numb. I guess I never realized that connection until we started working together. All I cared about was how much I wanted to be thin. Therapist: Now that you can more clearly see that connection, how would you like to start working on your relationships with your mother and father? Redirecting Issues Related to  Eating Disorder Symptoms During treatment sessions, patients with eating disorders may raise issues relating to eating disorder symptoms that are distressing (for example, binge episodes, overconcern about eating, shape, and weight) or want to engage in extended discussion related to these behaviors. These issues are relevant insofar as they reflect the clinical status of the patient’s eating disorder. However, the therapist must be cognizant of how these issues are being discussed during the sessions and vigilantly keep the session focused on the patient’s treatment goals by gently, but firmly, redirecting discussion to work on the treatment goals. For example, a female patient who avoids intimacy with her husband may attribute her avoidance to body dissatisfaction related to her obesity. She may wish to discuss her body concerns at great length to circumvent actual difficulties in communication with her husband, or she is not yet aware that her relationship difficulties with her husband are an important issue and that body concern is what she experiences as most distressing. Dialogue related to eating disorder symptoms should be consistently and repeatedly linked to its functional role with regard to the identified interpersonal problem area(s). Therapist: How are you today, Terry? Terry: I have been busier than usual and that has made me very stressed. I was asked to cover the late shift twice this week and since we have been understaffed, I was the only nurse to cover all of the patients during my shift. I had no time to eat dinner, which was probably good for me, but then I came home both nights and had huge binges. I  found myself in the kitchen eating anything and everything that I could find. I was

so frantic that I didn’t even bother to heat up—​I ate a huge container of soup cold! Therapist: Last week you talked about how eating is a way for you to relieve stress and to relax. Instead of allowing yourself a break or sharing your feelings with family or friends, you tend to turn to food. Terry: That is exactly what I do—​and what I did this week. It was unbelievable and I was so disgusted with how I  was shoving food in by the mouthful—​ cookies, chips, leftover pizza. Have you ever eaten cold pizza? It does not even taste good! I just wanted  . . .  Therapist:  I am going to interrupt you for a moment, Terry, so that I  can refocus you for a moment, back to your goals. How has your work in finding down time to take care of yourself been coming along? Terry: I think it has been going somewhat better. I signed up to join a book club through my church. It hasn’t started yet, but I did go buy the book we’re supposed to read and I  started reading a few pages. I’m hoping that my work schedule does not conflict with the nights that the club will be meeting. Therapist: As we talked about last week, for a long time you’ve been feeling that you need to take care of everyone else—​make everyone else happy—​and, in doing so, you’ve put yourself last and not tended to your own needs. By not taking care of yourself, you get very stressed and use food to cope. I wonder if as you practice identifying your own needs and addressing them—​like you have in joining the book club—​you will feel less exhausted and more personally cared for. By taking time out for yourself, you will feel calmer and be less likely to turn to food. Joining the book club—​and beginning to read—​is already one way you are taking care of yourself. I have noted that you only had two overeating episodes this past week. When we first started working together, you were having binge episodes almost nightly during similarly stressful times. By redirecting the patient away from the specifics of her binge episode, and toward her interpersonal problem area, the therapist is able to keep the patient focused on her goals. General Therapeutic Techniques The IPT therapist differs from providers of other modalities in that throughout the course of treatment, he/​she maintains a constant focus on the interpersonal context of the patient’s life and its link to the eating disorder symptoms. Although this approach is unique to IPT, a number of the therapeutic techniques used in IPT are similar to those used in other therapies. Such techniques include exploratory questions,

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encouragement of affect, clarification, communication analysis, and use of the therapeutic relationship. 1.  Exploratory Questions. Use of general, open-​ ended questions often facilitates the free discussion of material. This is especially useful during the beginning of a session. For example, the clinician might open a session with, “Tell me about your relationship with your husband.” Once this has generated discussion, progressively more specific questioning should follow. For instance, after the patient describes an interpersonal interaction with her husband, the therapist might follow-​up by asking, “What happened with (or what changes did you notice in) your eating patterns after you talked with your husband?” 2.  Encouraging Affect. Interpersonal psychotherapy’s focus throughout the therapeutic process involves affect evocation and exploration (Wilfley et al., 2000). This is particularly relevant for patients with eating disorders because problematic eating often serves to regulate negative affect. The IPT therapist should assist patients in (1)  acknowledging and accepting painful emotions, (2) using affective experiences to facilitate desired interpersonal changes, and (3)  experiencing suppressed affect (Wilfley, 2008; Wilfley et al., 2000). a.  Encourage acceptance of painful affects. Patients with eating disorders are often emotionally constricted in situations when others would typically experience strong emotions. In the case of BN and BED, individuals use food to cope with negative affect. Therapy provides an arena to experience and express these feelings versus using food to cope with these feelings. As the feelings are expressed, it is important for the IPT therapist to validate and help the patient accept them (Wilfley, 2008). b.  Teach the patient how to use affect in interpersonal relationships. Although the expression of strong feelings in the session is seen as an important starting point for much therapeutic work, the expression of feelings outside the session is not a goal in and of itself. The goal is to help the patient act more constructively (e.g., not binge eating or purging) in interpersonal relationships, and this may involve either expressing or suppressing affects, depending on the circumstances. A goal for the patient in IPT is to learn when her/​his needs are met by expressing affect and when they are better met by suppressing affect. 298

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However, a primary goal is helping patients to identify, understand, and acknowledge their feelings whether or not they choose to verbalize them to others. The following is an example: “The therapist immediately noticed that Sara was silent and withdrawn at the beginning of the session. Initially, she denied any relationship between her nonverbal behavior and the therapist’s observation. The therapist was persistent and she eventually acknowledged that she was feeling hurt because her father had not acknowledged her son’s first birthday. She spent some time clarifying and expressing her feelings of anger and rejection with regard to her own relationship with her father. The issue that emerged in the session was “when do you stop wanting something from a parent that you can never get from them?” Even though she became aware of and expressed many painful feelings regarding her relationship with her father, Sara’s goal was not to go out and express these feelings to her father directly at this time. Instead, Sara and her therapist began to discuss how she can find herself more fulfilled and satisfied by working to make other choices in terms of who to turn to for support and care” (Wilfley, 2008). c.  Help the patient experience suppressed affects. Many who struggle with eating disorders are emotionally constricted in situations where strong emotions are normally felt. An example may be the patient who is unassertive and does not feel anger when their rights are violated. On the other hand, they may feel anger but may lack the courage to express it in an assertive manner. Sometimes patients will deny being upset, when it is clear that an upsetting interaction has just occurred. The therapists might say, “Although you said you were not upset, it appears to me that you have shut down since you talked about the situation with your husband.” In this way, the therapist will attempt to draw out affect when it is suppressed (Wilfley, 2008). 3.  Clarification. Clarification is a useful technique that can (1) increase the patient’s awareness about what she/​ he has actually communicated, and (2) draw awareness to contradictions that may have occurred in the patient’s presentation of interactions or situations. An example might involve contradictions between the patient’s affect and speech: “While you were telling me how upset you

are about your father, you had a smile on your face. What do you think that’s about?” 4.  Communication Analysis. The technique of communication analysis is used to (1)  identify potential communication difficulties that the patient may be experiencing and (2)  assist the patient in modifying ineffective communication patterns. In using communication analysis, the therapist asks the patient to describe, in great detail, a recent interaction or argument with a significant other. As the patient describes the interactions, the therapist garners information by using probes, such as the examples below (Mufson, Dorta, Moreau, & Weissman, 2004; Young & Mufson, 2003): “What did you specifically say?” “What did he/​she say in response?” “Then what happened?” “How did you feel?” “Do you think you might be able to tell him/​her how you felt? “Thinking back to how the interaction turned out, did you send the message that you wanted to convey?” “How do you think it made him/​her feel?” As part of communication analysis, the clinician then assists the patient in identifying ways in which the interaction could have gone differently and how the different manifestations might impact the other person’s feelings and reactions. Therapeutic queries to facilitate this process include (Mufson et al., 2004; Young & Mufson, 2003): “How do you think this interaction might have manifested differently?” “What could have been said differently by either you or the other person?” “How might it have changed the way that felt and/​or the interaction itself?” The objective is for the clinician and patient to collaboratively work to identify difficulties in communication that may be impacting the process and outcome of the interaction and to find more effective strategies. 5.  Use of the Therapeutic Relationship. The premise behind this technique is that all individuals have characteristic patterns of interacting with others. The technique involves exploring the patient’s thoughts, feelings, expectations, and behavior in the therapeutic relationship and relating these to the patient’s characteristic way of behaving and/​ or feeling in other relationships. This technique is

particularly relevant to and useful for patients with interpersonal deficits and interpersonal role disputes. Use of this technique offers the patient the opportunity to understand the nature of his/​her difficulties in interacting with others and provides the patient with helpful feedback on his/​her interactional style. The following is an example of using the therapeutic relationship. Therapist: Joe, I  know it was hard for you last week to talk about how your girlfriend does not understand that it is important for you to have time with your friends. Did you have a chance to discuss this with her over the past week? Joe: No. I  was really busy. She would have just argued with me if I brought it up anyway. Therapist: As we have talked about before, I am wondering if you approach her about the topic differently this week, she might be more open to your point of view. Joe: I doubt it. I am really busy this week, too. Therapist: It feels to me like you do not want help with this situation, so I am feeling a little frustrated right now. I am wondering if other people in your life might feel the same way. What do you think? In a nonjudgmental and straightforward manner, the therapist not only models clear communication with Joe, but also uses the therapeutic relationship to identify a potentially dysfunction communication pattern. The Termination Phase By the end of the intermediate phase, patients are often acutely aware that treatment will soon be ending. The clinician should begin to discuss termination explicitly and address any anxiety the patient may be experiencing. In doing so, the patient should be prepared for emotions that may arise with termination, including grief related to the ending of treatment. At times, patients may deny any emotion with regard to the end of treatment and appear to have little reaction to termination. Nevertheless, the therapist should clearly address termination, as the patient may be unaware of or avoiding affect related to the end of treatment. The termination phase typically lasts 4–​5 sessions. During this phase, the patient should be encouraged to reflect on the progress that has been made during therapy—​both within sessions and outside of the therapeutic milieu—​ and to outline goals for remaining work after the formal end of treatment. Interpersonal psychotherapy does not assume that the work toward changes

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in interpersonal functioning is complete after the last session of the therapy. Rather, patients and therapist collaboratively summarize and draft the remaining work for the patient to continue outside of the therapeutic milieu. Patients are encouraged to identify early warning signs of relapse (e.g., binge eating, overeating and excessive dietary restriction, negative mood) and to prepare plans of action. Patients are reminded that eating disorder symptoms tend to arise in times of interpersonal stress and are encouraged to view such symptoms as important early warning signals. The identification of potential strategies to cope with such situations is designed to increase the patient’s sense of competence and security. Nevertheless, it is also essential to assist patients in identifying warning signs and symptoms that may indicate the need for professional intervention in the future. Use of a Group The group setting frequently provides an optimal modality for conducting IPT (Wilfley et al., 2000). Data from randomized trials suggest that both individual and group milieus of IPT are equally effective in the treatment of BN (Nevonen & Broberg, 2006) and BED (Wilfley et  al., 2002; Wilfley, Wilson, & Agras, 2008). Following an individual session to conduct a thorough interpersonal inventory, the group is an ideal milieu to work on interpersonal skills with other patients struggling with similar eating problems. It also offers the therapist an opportunity to observe and identify characteristic interpersonal patterns with other individuals. Furthermore, when another group member recognizes and verbally identifies a dysfunctional pattern of communication in a fellow patient, it can be powerful for the patient as well as the other group members (Wilfley et al., 2000). The following vignette provides an illustration from a group of adolescents with binge eating patterns. Therapist: Sheila, you have done a great job of telling us what happened this week at school. It sounds like it was pretty upsetting when you saw Christine, your best friend, sitting with people who she knows you do not get along with. You recognized that it was not the right time to talk to her, so you just walked away and sat with someone else. But it is still understandably upsetting to you. The rest of the group has suggested that you tell Christine what is causing you to feel upset with her. Sheila, what might you say? Sheila: I don’t know. I guess I would say, “Christine, the other day you were sitting with Amy and Joyce. You 300

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know those girls talk about me behind my back. Why were you sitting with them?” Therapist: That’s a good start. What do others think? Becca: I guess I  would have felt bad if I  was Christine. Therapist: How so? Becca: Well, Christine might have felt accused of doing something wrong. I guess she might have felt as though you think she is not allowed to hang around with whomever she wants. I think that is how I might have taken it. Therapist: Thanks, Becca. What do you think, Sheila? Sheila: I did not mean to tell her that she cannot hang out with other people. I just wanted her to know that it made me feel bad that she was spending time with girls who are not nice to me. Therapist: Does anyone have thoughts about how Sheila might better express what she really feels? Lisa: I guess you could say, “Christine, I felt upset the other day when you were sitting with  . . . ” I can’t remember their names. “They talk about me behind my back. When you were sitting with them, I felt like you weren’t my friend.” The group setting allows patients to experiment with different ways of communication within the safe confines of the group. Members can use the sessions to discuss problems they are having with their significant relationships and how these problems relate to their eating patterns. This often allows for patients to recognize that they are not alone in their difficulties, thereby helping to reduce feelings of isolation (Wilfley et al., 2000).

Review of Outcome Studies and Relevant Empirical Literature Interpersonal Psychotherapy for Bulimia Nervosa

Interpersonal psychotherapy has shown to be effective for the treatment of BN. Although cognitive-​behavioral therapy (CBT) is currently the most extensively researched, best-​established treatment for BN (Wilson & Fairburn, 2001), IPT is the only psychological treatment for BN that has demonstrated long-​term outcomes that are comparable to those of CBT (Wilson & Shafran, 2005). Currently, all controlled studies of IPT for BN have been compared to CBT for BN. In early studies, similar short-​ and long-​ term outcomes for binge eating reduction between CBT and IPT

were reported (Fairburn et  al., 1995; Fairburn et al., 1993). In a subsequent multisite study comparing CBT and IPT for BN, patients receiving CBT demonstrated higher rates of abstinence from binge eating and lower rates of purging in the shorter-​ term, post-​ treatment (Agras, Walsh, Fairburn, Wilson, & Kraemer, 2000). By 8-​ and 12-​month follow-​up, however, patients in CBT demonstrated maintenance or slight relapse while IPT participants experienced slight improvement such that rates of these behaviors were equivalent in both groups. The more impressive, immediate effect of CBT compared to IPT may be explained in part by a relative lack of focus on eating disorder symptomatology in the research version of individual IPT for BN that was used in this study (Tanofsky-​Kraff & Wifley, 2009; Wilfley et  al., 2003). Despite the relatively slower response rates, IPT patients rated their treatment as more suitable and expected greater success than did CBT patients. Therefore, a potential strength of IPT may be that many patients with BN perceive the interpersonal focus of IPT as especially relevant to their eating disorder and to their treatment needs, perhaps more so than a cognitive-​behavioral focus on distortions related to weight and shape (Tanofsky-​ Kraff & Wifley, 2009; Wilfley et al., 2003). Currently, IPT is considered an alternative to CBT for the treatment of BN (Wilson & Shafran, 2005). Although it has been recommended that therapists inform patients of the slower response time for improvements compared to CBT (Wilson, 2005), it is our contention that a lack of integration of BN symptoms with the interpersonal focus is likely responsible for the delayed response to IPT in the Oxford trial (Fairburn et  al., 1995; Fairburn et  al., 1993) and the less robust results in the multisite study (Agras et  al., 2000). Therefore, future research linking symptoms to interpersonal functioning is required. Given the increasing need for short-​term, effective therapies by clinicians with limited resources, a brief, 10-​session version of IPT was pilot tested with adult patients with BN (Arcelus, Whight, Brewin, & McGrain, 2012). When compared to conventional IPT (16–​20 sessions) and a wait-​list control, the abbreviated 10-​session IPT was as effective in reducing eating disorder symptomatology as the traditional IPT and more effective than the wait-​ list control post intervention. These results provide very preliminary support that efficacy of IPT for BN can potentially be reached more rapidly than the conventionally recommended 16–​20 sessions.

However, given the small sample size, lack of randomization, and short follow-​up duration, future research should experimentally examine brief IPT for BN to determine whether the abbreviated intervention is as effective as conventional IPT (Arcelus et al., 2012). An emerging literature has provided some insight into predictors of success with IPT for the treatment of eating disorders. In the multicenter trial conducted by Agras and colleagues (2000), a follow-​ up analysis found that while patients responded with higher abstinence rates when randomized to CBT as opposed to IPT, African American participants showed greater reductions in binge episodes when treated with IPT compared to CBT (Chui, Safer, Bryson, Agras, & Wilson, 2007). Although further investigation is clearly necessary, it is possible that IPT may be especially appropriate for African American women with BN, which speaks to the need for further study of IPT with different racial and ethnic groups. Researchers from this same study also examined the impact of therapeutic alliance on patient expectation of improvement (Constantino, Arnow, Blasey, & Agras, 2005). Expectation of improvement was positively associated with outcome for both CBT and IPT, emphasizing the important role of patient expectations in both treatments. Lastly, in a study of postremission predictors of relapse in women with BN, the finding that worse psychosocial functioning was associated with a greater risk for relapse may support the rationale for IPT (Keel, Dorer, Franko, Jackson, & Herzog, 2005). Indeed, the authors suggested that their findings may partly help to explain the long-​ term effectiveness of IPT for BN.

Interpersonal Psychotherapy for Binge Eating Disorder

Based on the initial success of IPT in BN (Fairburn et  al., 1991), IPT for BED was developed and tested in the early 1990s. Wilfley and colleagues first adapted IPT to a group format for adult patients with BED (Wilfley et  al., 1993; Wilfley et  al., 2000). During their work, they found that a number of patients presented with chronically unfulfilling relationships that were well suited to be addressed in the group format. Therefore, new strategies were adapted to specifically address such interpersonal deficits. For example, in the current format of group IPT for BED, group members with interpersonal deficits are strongly encouraged to use the group as an interpersonal “laboratory”; therapists can observe, firsthand, patients interacting with one

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another, and patients can practice improved ways of communicating within the group. As described previously, this social milieu is designed to decrease social isolation, support the formation of new social relationships, and serve as a model for initiating and sustaining social relationships outside of the therapeutic context (Wilfley et al., 1998). Additionally, self-​stigmatization is common among patients with BED, and this stigmatization contributes to the maintenance of the disorder. By its very nature, group therapy offers a radically altered social environment for these individuals, who typically maintain shameful eating behaviors hidden from close others in their social network. By participating in a group with others suffering from the same types of psychiatric and physical issues, individuals with BED are offered a unique opportunity to feel both understood and accepted in IPT. For the treatment of BED among adults, IPT has been demonstrated to be effective in randomized-​ controlled studies. Cognitive-​ behavioral therapy for BED has also been shown to have specific and robust treatment effects (Devlin et al., 2005; Grilo, Masheb, & Wilson, 2005; Kenardy, Mensch, Bowen, Green, & Walton, 2002; Nauta, Hospers, Kok, & Jansen, 2000; Ricca et  al., 2001; Telch, Agras, Rossiter, Wilfley, & Kenardy, 1990; Wilfley et al., 1993). In two randomized trials comparing IPT with CBT, IPT had similar effects to CBT in the treatment and management of BED. The first study, comparing group CBT and IPT, revealed that both treatments were more effective than a wait-​list control group at reducing binge eating and had equivalent, significant reductions in binge eating in both the short-​ and long-​term (Wilfley et al., 1993). In a second substantially larger sample size, both CBT and IPT demonstrated equivalent 4-​ month and 1-​ year follow-​ up efficacy in reducing binge eating and associated specific and general psychopathology, with approximately 60% of the patients remaining abstinent from binge eating at 1-​year follow-​up (Wilfley et al., 2002). In contrast to the literature on IPT for BN, the time course of almost all outcomes with IPT was identical to that of CBT and all participants in both groups significantly improved from baseline. In a follow-​up analysis of treatment predictors for the 2002 study, patients with a greater extent of interpersonal problems at baseline and midtreatment showed poorer treatment response to both treatments (Hilbert et al., 2007). An important caveat of this finding, however, is that not surprisingly, 302

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those individuals with greater interpersonal problems were also those who had more Axis I and Axis II psychiatric disorders and lower self-​esteem than those with less severe problems. These individuals are likely in need of augmented or extended treatment. Supporting this assertion, in IPT adapted for individuals with borderline personality disorder, many of whom presented with comorbid depression, Markowitz and colleagues suggest that extending IPT effectively improves the disorder (Markowitz et al., 2006). Further, in a follow-​up analysis of the Wilfley et al. (2002) trial approximately 4 years after treatment cessation, individuals in both treatments maintained reductions in binge eating and disordered eating cognitions (Hilbert et al., 2012). However, between the 1-​year and 4-​ year follow-​up periods, those randomized to IPT maintained or improved eating disorder symptoms compared to the CBT group, whose symptoms worsened. Overall, however, 52% of those in CBT and 76% of those in IPT reached recovery at this long-​term follow-​up, though groups did not significantly differ at any time point. Eighty percent of patients in both CBT and IPT remitted to subclinical rates of binge eating behavior, and 58% saw improvements in related eating disorder psychopathology. These data suggest evidence for good long-​term maintenance of change for BED patients treated with IPT. Results from a multisite trial that compared individual IPT to behavioral weight loss treatment or CBT guided self-​help for the treatment of BED points to the importance of making a clear connection between interpersonal problems and binge eating symptoms in the delivery of IPT (Wilson et al., 2010). Similar to Wilfley et al.’s 2002 trial (Wilfley et  al., 2002), in this multisite study the clinicians linked interpersonal functioning to disordered eating symptoms throughout the course of IPT. Findings from this study revealed that IPT was most acceptable to patients; the dropout rate was significantly lower in IPT compared with the other two interventions (Wilfley et  al., 2008). Interpersonal psychotherapy and CBT guided self-​help were significantly more effective than behavioral weight loss in eliminating binge eating after 2  years (Wilson et  al., 2010). Furthermore, compared to the other two programs, IPT produced greater binge episode reductions for patients with low self-​esteem and greater disordered eating behaviors and cognitions, while CBT guided self-​ help was generally effective only for those with low eating disorder

psychopathology. It is notable that in this trial, as with the Wilfley et  al. study (Hilbert et  al., 2007; Wilfley et  al., 2002), individuals with more psychopathology showed greater improvements in IPT than CBT guided self-​help. This is in concert with Hilbert and colleagues’ follow-​up data suggesting that greater disordered eating serves as a moderator in predicting poorer outcome in CBT (Hilbert et al., 2007). A trial comparing group psychodynamic interpersonal psychotherapy (an attachment-​based therapy similar to IPT) and group CBT for treatment of BED were comparable in reducing binge eating, negative mood, total interpersonal problems (Tasca, Mikail, & Hewitt, 2005), and most interpersonal problem areas (Tasca, Balfour, Presniak, & Bissada, 2012). Overall, group psychodynamic interpersonal psychotherapy was similar, but slightly better, than CBT for those with more cold/​distant personality types and attachment avoidance. The Tasca trial was limited to primarily Caucasian participants (Tasca et al., 2012); however, there are interesting findings with a more racially diverse participant base. In general, compared to Caucasian participants, individuals of other ethnic minorities demonstrated less retention in the multisite study by Wilfley and colleagues (Wilfley et  al., 2008). Although there was no treatment by ethnicity effects in this regard, there was very low attrition for minority participants in IPT and very high dropout rates by minorities in CBT guided self-​help. The small sample size of minority participants across sites precludes definitive conclusions. Nevertheless, this pattern is in concert with the finding that IPT was particularly helpful for African American participants in the previously described multisite study for individuals with BN (Chui et al., 2007). It is possible that the personalized nature of IPT (e.g., problem areas and goals are developed based on each individual’s social environment) is modifiable to, and thus particularly acceptable to, persons of various cultures and backgrounds. A number of recommendations may be drawn from the research presented. It is possible, from a cost-​ effectiveness viewpoint, that CBT guided self-​help could be considered the first-​line treatment for the majority of individuals with BED, and that IPT is recommended for patients with low self-​esteem and high eating disorder psychopathology. Alternatively, IPT may be considered a first-​line treatment for BED. This recommendation is based on a number of factors: IPT has been shown to be effective across multiple research sites,

is associated with high retention across different patient profiles (e.g., high negative affect, minority groups), and demonstrated superior outcomes to behavioral weight loss overall, and to CBT guided self-​help among a subset of patients with high disordered eating psychopathology and low-​self-​esteem. Therapists and patients should consider these alternatives when deciding the best approach to treating their disorder. Finally, behavioral weight loss should not be considered as a first choice when treating individuals with BED. In summary, the literature suggests that IPT represents an efficacious treatment alternative to CBT for BED. If delivering IPT for BED in a group format, as with all group therapies, developing member cohesion is paramount to the achievement of treatment success.

Interpersonal Psychotherapy for Anorexia Nervosa

In general, there are very few effective treatments for AN (Wilson, Grilo, & Vitousek, 2007). Although behavioral family therapy is perhaps considered the treatment of choice for adolescents with early onset of the disorder, these data are not especially informative when making recommendations for adults. With regard to IPT, there is a relative lack of research examining its utility for AN. Indeed, there have been no controlled studies yet that have demonstrated the efficacy of IPT for AN. To date, only one group has tested IPT for AN (McIntosh et al., 2005). Fifty-​six women with AN were randomized to IPT, CBT, or a control comparison (nonspecific, supportive clinical management). In contrast to the impressive effects of IPT for both BN and BED, this study found that IPT was associated with either modest or no improvement in AN symptoms compared to nonspecific, supportive clinical management (McIntosh et al., 2005). Of the three therapies, nonspecific, supportive clinical management was the most effective approach. Importantly, the authors posited that their findings may be a result of the relative lack of focus on eating disorder symptoms in their adaptation of IPT (McIntosh, Bulik, McKenzie, Luty, & Jordan, 2000) and suggest that future studies implementing IPT for AN involve consistent connections between the interpersonal problem areas and the core symptoms of the disorder (McIntosh et al., 2005). Particularly given the ego syntonic nature of AN, the lack of focus on eating disorder symptoms may have blunted IPT’s impact and avoided the essential work of the therapy (McIntosh et al.,

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2005). The short timeframe for the IPT work, a relative lack of symptom-​focus, and the brief length of follow-​up may have also contributed to the study outcome. Indeed, in a long-​term follow-​up of this study (on average 6.7 years after treatment), supportive clinical management was no longer superior to IPT or CBT. Rather, all three groups were similar in eating disorder symptomology, anthropometrics, and general psychopathology (Carter et al., 2011). Though initial post-​treatment results suggested that those randomized to IPT were least likely to have a positive outcome (i.e., the best global outcome rating) compared with the other treatments, by long-​ term follow-​ up, those in IPT evidenced the best global outcomes. Findings were reversed for supportive clinical management; post-​treatment, patients in this group had the best global outcome, but faired the worse at long-​term follow-​up. Those in CBT had a more stable trajectory across time. These findings suggest that IPT may be of benefit to individuals with AN and, similar to other eating pathologies, some individuals continue to improve even after the course of treatment. Given the importance of interpersonal functioning in etiological theories of AN (McIntosh et al., 2000), continued exploration of IPT’s utility in treatment of the disorder is clearly warranted. In particular, investigation of IPT for AN that includes a focus on eating disorder symptoms as they relate to interpersonal problems is needed. It may be that for AN, IPT is optimally delivered in the context of other adjunctive treatments (e.g., pharmacological, nutritional), rather than as a “stand alone” treatment. Staging of treatment may also be important; for AN, IPT may be more suitable for the maintenance and relapse prevention stages of treatment than for the weight regain phase (Jacobs, Welch, & Wilfley, 2004).

Choosing Treatment Modality

When determining the treatment approach for patients with eating disorders, the clinician and patient should together evaluate the advantages and disadvantages of using IPT, CBT, or another therapeutic approach, such as pharmacologic treatment. In making this decision, it is crucial for therapists to explore their own comfort level in terms of their expertise, theoretic knowledge, and propensity toward administering an interpersonally focused treatment (Wilfley et  al., 2000). IPT, like CBT, is a specialty treatment and should be administered only by trained practitioners. However, it has been argued that experienced therapists who have been trained in other 304

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treatment modalities tend to learn IPT quickly and are often able to implement IPT with a high degree of integrity despite minimal IPT-​specific training (Birchall, 1999). Furthermore, some therapists may consider IPT to be more acceptable than CBT. Although not specific solely to IPT, a naturalistic study of psychotherapy outcome in which 145 clinicians provided information about their eating disorder patients found that compared to CBT, psychodynamic approaches that included IPT produced better global outcomes (Thompson-​Brenner & Westen, 2005). Although there are limited data exploring the influence of therapist comfort on treatment outcome, it is possible that some clinicians are more comfortable administering treatments other than CBT, and this is reflected in the outcome of their work (Tanofsky-​ Kraff & Wifley, 2009). To date, there are more data in support of the efficacy of CBT for eating disorders. A  recent meta-​analysis comparing IPT to CBT for eating disorders reveals a small, but significant effect in favor of CBT in the short-​term, though the number of available comparison studies was small and the long-​ t erm effects unclear (Cuijpers, Donker, Weissman, Ravitz, & Cristea, 2016). To the latter point, although CBT has been shown to produce more rapid effects for BN, IPT produces equivalent outcomes over the long term for adults with this disorder. Interpersonal psychotherapy for BED appears to be equally as effective as CBT. Based on the evolving literature, IPT may be well suited for patients presenting with or without exacerbated difficulties in social functioning. Although greater problems were associated with poorer outcomes for both CBT and IPT in the Hilbert et al. (2007) study, the moderator effect that patients presenting with greater psychopathology seem to respond well to IPT in the more recent multisite study (Wilfley et al., 2008), suggest that IPT (or another specialized treatment such as CBT) may be well suited for individuals with a broad range of disordered eating and general psychopathology. Moreover, IPT may be enhanced for individuals with exacerbated psychological problems (Markowitz et al., 2006). It is also possible that IPT may be especially fitting for some minority groups, such as African Americans. Finally, it is possible that some patients may express discomfort or difficulties with elements of CBT (e.g., keeping food diaries); IPT should be considered for these patients as well (Tanofsky-​K raff & Wifley, 2009).

Interpersonal Psychotherapy for the Prevention of Excessive Weight Gain

Interpersonal psychotherapy has been developed for the prevention of excessive weight gain in adolescents who report loss of control (LOC) eating patterns. Pediatric LOC refers to the sense that one cannot control what or how much one is eating, regardless of whether the reported amount of food consumed is unambiguously large (Tanofsky-​Kraff, 2008). Loss of control is associated with excess body weight and health complications (Radin et  al., 2015). Common among youth, LOC eating predicts excessive weight and fat gain over time (Sonneville et al., 2013; Tanofsky-​Kraff et al., 2006; Tanofsky-​Kraff et  al., 2009), as well as worsening metabolic problems beyond the contribution of body weight (Tanofsky-​Kraff et al., 2012). Loss of control eating is also related to, and predictive of, increased psychological problems and the development of subsequent clinical eating pathology such as BED (Goldschmidt et al., 2015; Sonneville et al., 2013; Tanofsky-​Kraff et al., 2011). The manual for IPT for the prevention of excess weight gain was adapted directly from IPT for the prevention of depression in adolescents (IPT Adolescent Skills Training, IPT-​ AST) (Young, Mufson, & Davies, 2006; Young, Mufson, & Schueler, 2016) and group IPT for BED (Wilfley et  al., 2000), and evolved from the outcome data of psychotherapy trials for the treatment of BED. An unexpected finding of IPT and most psychological treatments for BED has been that individuals with BED who cease to binge eat tend to maintain their body weight during and/​or following treatment (Agras et al., 1995; Agras, Telch, Arnow, Eldredge, & Marnell, 1997; Devlin et  al., 2005; Wilfley et  al., 1993; Wilfley et al., 2002; Wilson et al., 2010). Therefore, it has been hypothesized that treatment of LOC eating among youth may reduce excessive weight gain and prevent full-​syndrome eating disorders (Tanofsky-​ Kraff et al., 2007). A number of factors suggest that IPT is particularly appropriate for the prevention of obesity in high-​risk adolescents with binge or LOC eating patterns. Specifically, youth frequently use peer relationships as a crucial measure of self-​evaluation (Mufson et al., 2004). The importance of perceived social interactions and social standing on body weight gain over time was revealed in a prospective cohort study (Lemeshow et  al., 2008). Adolescent girls who rated themselves lower on a subjective social-​standing scale were 69% more likely to gain more weight over time compared with girls who

rated themselves higher on the scale (Lemeshow et  al., 2008). Furthermore, overweight teens are more likely to experience negative feelings about themselves, particularly regarding their body shape and weight, compared with normal weight adolescents (Fallon et al., 2005; Schwimmer, Burwinkle, & Varni, 2003; Striegel-​ Moore, Silberstein, & Rodin, 1986), perhaps because of their elevated rates of appearance-​ related teasing, rejection, and social isolation (Hayden-​ Wade et  al., 2005; Neumark-​Sztainer et al., 2002; Puhl, 2011; Strauss & Pollack, 2003). The social isolation that overweight teens report may be directly targeted by IPT. Finally, IPT is posited to increase social support, which has been demonstrated to improve weight maintenance in overweight adults (Wing & Jeffery, 1999) and children (Wilfley et al., 2007). Indeed, data suggest that low social problems predict better response to weight loss treatment in children (Wilfley et al., 2007). Interpersonal psychotherapy for the prevention of excessive weight gain for adolescents at high-​risk for adult obesity, delivered in a group format, maintains the key components of traditional IPT: (1) a focus on interpersonal problem areas that are related to the target behavior (for example, LOC eating in the present adaptation); (2) the use of the interpersonal inventory at the outset of treatment to identify interpersonal problems that are contributing to the targeted behavior; and (3)  the three-​staged structure of the intervention (initial, middle, and termination). The primary activities of IPT for the prevention of excess weight gain are to provide psychoeducation about risk factors for excessive weight gain and to teach general skill-​building to improve interpersonal problems. For prevention of excess weight gain, IPT differs from other adaptations in that it was developed to specifically address the particular needs of adolescents at high risk for adult obesity due to their current BMI percentile and report of LOC eating behaviors. Based on IPT-​AST, this adaptation is presented to teenagers as “Teen Talk” in order to be nonstigmatizing. As designed by Young (Young & Mufson, 2003; Young et al., 2006; Young et al., 2016), this preventive adaptation of IPT focuses on psychoeducation, communication analysis, and role-​playing. Specific interpersonal communications skills are taught, including “Strike while the iron is cold,” “Use ‘I’ statements,” “Be specific” (when talking about a problem), “Don’t give up,” and “Put yourself in their shoes” (Young & Mufson, 2003; Young et  al., 2006; Young et  al., 2016). To encourage

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identification and acknowledgment of affect, the skill “Use ‘I’ statements” has been changed to “Use ‘I feel’ statements.” In addition, the skill “Put yourself in their shoes” has been amended to “Put yourself in their shoes (and communicate it to them)” to facilitate development of empathic communication. Two additional skills have been added to further develop effective communication abilities. First, “What you don’t say speaks volumes,” has been added to teach adolescents how their body language has the ability to impact communication regardless of their words. Second, “Have a few solutions in mind and be willing to compromise” has been added to facilitate assertive communication and problem-​solving skills. During the interpersonal inventory, a “closeness circle” (Mufson et al., 2004) is used to identify the close relationships of the participant. Since this adaptation was designed for adolescents ranging from age 12 to 17, sessions are geared toward the adolescents’ developmental level. For example, younger adolescents, who may be uncomfortable talking about themselves, may respond better to hypothetical situations and games, whereas older teenagers may more readily discuss their own interpersonal issues from the outset. Based on IPT for BED, IPT for excess weight gain prevention maintains focus throughout the program on linking negative affect to LOC eating, overeating, times when individuals eat in response to cues other than hunger, and overconcern about shape and weight. Further, a timeline of personal eating and weight-​related problems and life events is discussed individually with participants prior to the group program. Similar to both IPT-​AST and IPT for BED, this adaptation is delivered in a group format. Twelve weeks in duration, IPT for preventing obesity is longer than IPT-​AST (8 sessions), but shorter than group IPT for BED (typically 16 to 20 sessions). Similar to IPT-​AST, group size is smaller than in IPT-​BED (5 vs. 9 members), enabling therapists to keep adolescents engaged. As with group IPT for BED (Wilfley et al., 2000), participants meet individually with the therapist(s) for a brief midtreatment meeting to discuss progress made on proposed therapeutic goals, areas that are particularly challenging, and plans for continued work through the second half of the group. The following case example of “Kay” briefly illustrates the presentation and treatment of an adolescent group participant. For a more detailed case presentation, we recommend a recent article 306

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by Tanofsky-​Kraff and colleagues (Tanofsky-​Kraff, Shomaker, Young, & Wilfley, 2016). For sample cases of adults with eating disorders across diagnostic categories, we recommend referring to a book by Denise Wilfley and colleagues (Wilfley et al., 2000) as well as chapters on IPT for eating disorders (e.g., Jacobs et al., 2004; Wilfley et al., 2003). Presentation:  Kay is a 14-​ year-​ old African American female with a BMI at the 85th percentile for her age and sex (Ogden, Carroll, Kit, & Flegal, 2014). At intake, she reported engaging in an average of 5–​6 episodes of LOC eating per month over the 3 months prior to intake. She specifically recalled engaging in two such episodes in the past month, both when alone and feeling “bored.” She reported feeling anger, distress, and regret following her LOC eating episodes. However, she was only able to connect her episodes to feelings of boredom. Kay endorsed some distress surrounding her shape and weight as well as feeling “fat” much of the time, but reported few attempts at dieting. She reported eating in response to a number of negative emotions, with a very strong desire to eat when feeling down, sad, stressed out, worried, or bored. Although she presented with few symptoms of depression, Kay did experience some subclinical threshold symptoms of anxiety. Although she reported feeling shy when meeting new people, she also endorsed having close friendships with peers in whom she could confide. During her pretreatment meeting, Kay reported a number of family stressors. In the months prior to intake, she had reluctantly returned to her mother’s home in the Midwest to attend the local middle school, after having attended boarding school for three years on the West Coast. She reported generally poor relationships with her parents, who had divorced when she was a baby. Kay indicated that because she and her mother were “a lot alike” and both very stubborn, they argued frequently. Most often, their arguments concerned Kay’s dislike of her stepfather, whom she referred to as obnoxious and racist. She reported that her mother no longer “thinks for herself,” but rather just agrees with her stepfather. Fights with her mother typically involved Kay saying something hurtful in the “heat of the moment” and/​or walking away without resolution. Kay reported being left with emotions of both rage and guilt. During these times, she would often overeat and experience a lack of control over how much she was eating. Following the eating episode, she reported that her negative feelings eventually “went away.” Despite living in a nearby city, her biological father had little contact with her following her parents’ divorce. She had spoken with him 1–​2 times per month for many years

and up until intake. Kay reported feeling abandoned by her father and attributed his lack of availability to his own social anxiety. Nonetheless, she wished for a closer relationship, but never discussed her desire with him for fear that he would not be receptive. Problem area: Kay’s IPT problem area was conceptualized as a role dispute. Moving home from boarding school—​halfway across the country—​decreased her independence and exacerbated the typical changes adolescents experience during developmentally appropriate individuation from their parents. Kay struggled with being unable to communicate successfully with either parent—​or her stepfather—​regarding her opinions and needs. In response to such disputes, Kay would experience negative affect and eat to cope with her emotions. Goals: The therapists and Kay generated and agreed on the following therapy goals for the 12-​week intervention. The first goal was that Kay would work on gaining perspective to feel less frustrated with her parents and work on remaining calm in the moment. Second, she would aim to express her feelings of being let down and hurt by her father. If possible, she would consider discussing these feelings with him. Kay’s work in treatment would involve clarifying her role within the family, vis-​à-​vis her mother and stepfather, and learning how to negotiate and express herself with them in a more functional manner.

IPT intervention

Initial phase: Kay was very engaged during the initial phase. She actively participated in the role-​play exercises and was open about her frustration with moving back home to live with her mother and stepfather. She also shared how she had a tendency to vacillate between speaking her mind and avoiding arguments by walking away, particularly with her mother. She reported overeating and feeling unable to stop, most often in response to avoiding arguments with her mother and feeling angry. Specifically, she shared that not only would her mother side with her stepfather during family arguments, but that her mother believed Kay was not intelligent. Her mother would often express her opinion about Kay’s intelligence with her stepfather and other friends. Kay was encouraged to role-​play a conversation with her mother in which she discussed her feelings. However, she remained skeptical that her mother would be responsive. While the therapists encouraged Kay to practice such a conversation in the group, they also recommended that she think about how to better tolerate her mother’s behavior if, in fact, she was unresponsive. Middle phase:  Kay spent more time role-​playing conversations that she might have with both her

mother and her father. The therapists encouraged Kay to initiate a discussion with her parents during which she would be specific about her frustrations while also trying to keep in mind an understanding of their perspectives. Initially, Kay was reluctant to follow up on this work. She was therefore encouraged to examine her pattern of anger and then avoidance, particularly with her mother. During the seventh session, Kay became frustrated with the therapists’ persistence and grew sullen and angered. She returned the next session to report that she was angry, confused, and disappointed to have learned about some of her mother’s past behaviors of which Kay did not approve. The therapists encouraged Kay to take “a leap of faith” and try talking with her mother. After in-​session practicing, Kay approached her mother and talked about her feelings in a calm manner. She was very pleased with her mother’s receptiveness to the discussion. By the end of the middle phase, Kay was also spending some time with her father. Moreover, she had opened up a dialogue with him regarding some of her feelings of disappointment with her. Much to her surprise her father was more receptive to her self-​expression than she had expected. Throughout this phase, Kay was frequently queried about her eating patterns. Initially, she noticed that that the frequency of her LOC eating episodes had decreased. Then, she became more cognizant of the times she would binge eat. For example, after finding out that an old friend was ill, she became very upset and was able to link her feelings to LOC eating. Termination phase: Kay reported that not only was she sharing her feelings more often, but that she was overeating less frequently. She was supportive of other group members in taking their own “leaps of faith” by describing how overwhelmed she felt before speaking with her parents, but how much better she felt after the conversations. By the final session, Kay was quite sad about the ending of the group. She reported that she was going to miss the support of the therapists and group members and realized that she still had a great deal of work to continue. The therapists focused on the work she had accomplished and assured her that she had achieved the skills necessary to continue making improvements. Along with the therapists and the other members, Kay outlined the future work that she would continue after the groups ended. Specifically, she planned to continue dialogues with her mother and seek to develop a closer relationship with her father, with the recognition of his emotional limitations. Following treatment, Kay reported no longer experiencing episodes of LOC while eating. Moreover, her BMI percentile had decreased 5  percentage points

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Table 15.4  IPT for the Prevention of Excess Weight Gain Sample Case Conceptualizations and Courses of Treatment Example LOC eating Interpersonal Participant precipitant(s) functioning

Problem area

Goal

Initial Phase

Middle Phase

Termination Phase

Case #1

Sadness, stress and worry

Repeated heated arguments with mother

Role dispute

Gain perspective to decrease frustration and remain calm when communicating with mother

Sharing feelings of frustration with mother; in group role-​play of discussions with mother

Discuss resistance to speaking with mother; with group encouragement, began productive dialogues with mother

Emphasis on improved communication skills; discussion of transferring use of skills to other close interpersonal relationships; gaining other outside supports

Case #2

Avoiding conflict and negative affect

Does not express negative feelings or discomfort with conflict in multiple relationships

Interpersonal deficits

Become more comfortable with conflict and work on expressing feelings

Discuss discomfort surrounding interactions involving conflict

Practice sharing feelings via role-​ playing; encouraged to communicate feelings with less tense relationship

Emphasis on improved communication skills; focus on future generalizing of skills to several situations

Case #3

Boredom and Expresses emotions/​ frustration needs to family (especially parents) in nonproductive manner

Role dispute

Use more constructive communication to express self

Communication analysis and in group role-​play of poor interactions

Continued role-​playing specific situations and trying out discussions with siblings

Emphasis on improved communication skills; focus on future sharing of deeper personal conflicts with parents

Tanofsky-​Kraff, M., Wilfley, D. E., Young, J. F., Mufson, L., Yanovski, S. Z., Glasofer, D. R., & Salaita, C. G. (2007). Preventing Excessive Weight Gain in Adolescents: Interpersonal Psychotherapy for Binge Eating. Obesity, 15(6), 1345–​1355. doi:10.1038/​oby.2007.162. Reprinted with permission of John Wiley & Sons.

to the 80th percentile for her age and sex (Ogden, Carroll, Kit, & Flegal, 2014). The courses of treatment for this individual, along with two other case examples, are illustrated in Table 15.4 (Tanofsky-​ Kraff et al., 2007). In a pilot study testing IPT for preventing excess weight gain compared with a standard health education program (Bravender, 2005), IPT was shown to be both feasible and acceptable to adolescent girls with and without LOC eating who were at risk for excessive weight gain (Tanofsky-​Kraff et al., 2010). Further, at 1-​year follow-​up, girls in IPT experienced less than expected increases in their BMI for their age and BMI percentile compared with girls in health education (Tanofsky-​Kraff et  al., 2010). In addition, among girls who reported LOC eating at baseline, those in IPT evidenced a significantly greater decrease in LOC eating episodes compared with those in health education (Tanofsky-​ Kraff et al., 2010). An adequately powered randomized-​ controlled trial with adolescent girls who endorsed at least one LOC eating episode at baseline provided additional evidence on the effectiveness of IPT for the prevention of excess weight gain and insights on concurrent psychological benefits (Tanofsky-​Kraff et al., 2017; Tanofsky-​Kraff et al., 2014). Similar to the pilot study, girls in the randomized-​ controlled trial were assigned to either IPT or health education groups. As expected based on their stage of development, all girls gained in BMI at 1-​year follow-​up (Tanofsky-​Kraff et  al., 2014). However, girls in both groups decreased in adiposity and the age-​adjusted BMI metrics of BMIz and BMI percentile with no significant between group differences. Similarly, regardless of group assignment, depression and anxiety symptoms significantly improved at the 1-​year follow-​up (Tanofsky-​Kraff et al., 2014). Psychosocial functioning and average number of LOC eating episodes were similar for girls in both IPT and health education; however, girls in IPT had significantly fewer binge eating episodes at 1-​year follow-​up compared with girls in health education (Tanofsky-​Kraff et  al., 2014). Though only one girl in IPT developed a probable eating disorder at 1-​year follow-​up compared with three in health education, odds of developing a probable eating disorder did not differ significantly by group at 1-​year follow-​up (Tanofsky-​Kraff et al., 2014). Follow-​up at 3 years provided additional insights. At 3 years, compared to baseline, girls decreased in BMIz and increased in adiposity with no significant between group differences (Tanofsky-​Kraff et  al., 2017). However, baseline anxiety and baseline

social adjustment problems moderated these effects (Tanofsky-​Kraff et  al., 2017). For BMIz, girls in IPT and health education with lower self-​reported anxiety at baseline and lower social adjustment problems at baseline displayed similar decreases in BMIz over 3  years. In contrast, girls in IPT with higher self-​reported anxiety at baseline and higher social adjustment problems at baseline evidenced a significantly steeper decline in BMIz over the course of 3 years compared with girls in health education. Self-​reported social adjustment problems did not moderate the 3-​year increases in adiposity by group; however, self-​ reported anxiety did. Girls in IPT with higher self-​reported anxiety at baseline did not gain in adiposity at 3 years, which is in stark contrast to girls in health education with higher anxiety and girls in both groups with lower anxiety, who all experienced significant adiposity gains over time (Tanofsky-​Kraff et al., 2017). Parent-​reported data generally mirrored these findings. Baseline depression symptoms and baseline number of LOC eating episodes were not significant moderators of BMIz or adiposity over time (Tanofsky-​Kraff et al., 2017). Overall, IPT was not significantly better than health education for BMIz or adiposity at 1-​or 3-​ year follow-​ up (Tanofsky-​ Kraff et  al., 2017; Tanofsky-​Kraff et  al., 2014). As both groups were active interventions, it is possible that, on the whole, social support provided by both groups conferred adequate interpersonal benefits to affect weight outcomes (Tanofsky-​Kraff et  al., 2017; Tanofsky-​ Kraff et  al., 2014). However, at 3-​year follow-​up, girls with higher anxiety or social adjustment problems at baseline evidenced greater improvements in BMIz if they were randomized to IPT, and only girls with higher anxiety randomized to IPT did not gain fat over time. Therefore, consistent with IPT theory, IPT may be particularly promising for girls in preventing excess weight gain over time for those with high anxiety and social problems (Tanofsky-​ Kraff et al., 2017). Both IPT and health education groups benefitted from improvements in mood and decreases in LOC eating episodes, though IPT for the prevention of excess weight gain may be particularly beneficial for decreases in classic binge episodes (Tanofsky-​Kraff et  al., 2017; Tanofsky-​Kraff et al., 2014). In addition, IPT may be particularly helpful for girls from ethnic minority backgrounds, as those who were in IPT had significantly greater reductions in LOC eating episodes compared with those in health education (Tanofsky-​Kraff et  al., 2014). This is consistent with the benefits IPT seems to confer on racial and ethnic minorities

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from eating pathology research (Chui et al., 2007; Wilfley et al., 2008). Indeed, qualitative investigations with African American youth, their caregivers, and community leaders provided support for the acceptability of IPT for the prevention of excess weight gain as an intervention for the prevention of excess weight gain and provided guidance on culturally relevant adaptations (Cassidy et al., 2016; Cassidy et al., 2013). Such adaptations included integrating parents into the intervention, adding a nutrition education component, and reframing some communication skills to better reflect the communication styles favored by the African American community (Cassidy et  al., 2016; Cassidy et  al., 2013). For example, some suggested that “Using “I” statements” may need changes in order to respect parental authority and align with cultural standards of communication, yet core tenets of IPT would remain the same (Cassidy et  al., 2016; Cassidy et  al., 2013). Considering the known obesity-​related health disparities in the African American population (Ogden et al., 2014; Ogden, Carroll, Lawman, et al., 2016) and the lack of long-​term effective interventions based on strictly behavioral factors, IPT may be particularly effective in reducing disordered eating and improving weight outcomes for African American youth (Cassidy et al., 2016; Cassidy et al., 2013). Indeed, the design and structure of IPT is inherently adaptable for addressing concerns that may be particularly salient to this population. A culturally adapted manualized intervention has been developed (Cassidy et al., 2016), and a pilot of the intervention is being developed. Interpersonal psychotherapy for preventing excess weight gain and eating disorders has also been adapted for use in for adolescent dependents of military service members, a group with a similar prevalence of obesity to civilian youth but with unique interpersonal stressors. Factors such as frequent moves and parental deployments put such youth at unique risk for interpersonal conflicts and potentially maladaptive coping strategies such as LOC eating. Indeed, military youth with LOC eating may be especially vulnerable to disordered eating and poorer health outcomes (Schvey et  al., 2015). Yet, carrying out prevention research in military communities is a challenge, in part due to families’ frequent relocation and the constraints of the military health system. With military and civilian partners, Tanofsky-​Kraff and colleagues tested the feasibility of IPT compared to a health education group for reducing LOC eating, mood symptoms, 310

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and excess weight gain in a military health system clinic. In this pilot study, youth randomized to IPT appeared to show improvements in mood symptoms relative to those in health education. There were no between-​group differences in excess weight gain at 1-​year follow-​up. Overall, despite the challenges of conducting research trials with military families, IPT was feasible within military treatment facilities and evidenced similar results as with civilian trials. An adequately powered randomized-​controlled trial is currently underway with adolescents from military families to investigate the effectiveness of this preventative adaptation of IPT and will be the first to examine the effects of IPT in adolescent boys.

Future Directions

Several important areas require further study. An important next step is to determine whether IPT for eating disorders can be translated from specialty care centers to the primary care setting, schools, and other typically nonresearch clinical practice milieus. In an effort to continually improve IPT and broaden its utility, we propose other research directions in this section (Tanofsky-​Kraff & Wifley, 2009).

Enhancing Interpersonal Psychotherapy for Bulimia Nervosa and Binge Eating Disorder

As efforts to more frequently and consistently link eating disorder symptoms to interpersonal functioning has evolved in the use of IPT for BED, clinical researchers involved in developing IPT for BN should also consider stressing this link during the delivery of IPT so that it offers the utmost potency. Since IPT does appear to have specific effects in BN and good long-​term maintenance of change, it seems prudent to evaluate methods for improving its efficiency and clinical effectiveness. For instance, it may be that the slower and less potent effects observed in IPT as compared to CBT were due to the manner in which IPT was implemented. Specifically, in order to minimize procedural overlap with CBT, the research application of IPT for BN has not included an ongoing focus on making links between symptomatology and interpersonal functioning, which is in stark contrast to how IPT was developed and tested for depression. In future studies, the efficacy and efficiency of IPT may be enhanced by including a specific focus on the core symptoms of BN and their connection with interpersonal issues throughout the course of treatment. Such refinements of the content and delivery of IPT may further strengthen its usefulness in the treatment of BN.

In its current form, IPT already seamlessly incorporates aspects of other therapeutic modalities. For example, the collaborative, interpersonal formulation of the eating disorder symptoms during the interpersonal inventory is one of the ways in which IPT may resemble the behavior therapies more than it does the supportive or psychodynamic therapies. Therefore, some aspects of CBT may enhance the efficacy of IPT (Tanofsky-​Kraff & Wifley, 2009). For example, IPT therapists might wish to encourage self-​monitoring as a method for patients to become more aware of their negative affect surrounding eating disorder symptoms. Such an approach is already being tested in other treatment modalities. Indeed, Fairburn and colleagues have found the inclusion of an interpersonal module useful when administering a recently modified version of CBT for eating disorders (Enhanced CBT for Eating Disorders; Fairburn, 2008).

Adolescent and Child/​Parent Adaptations

Given the robust efficacy of IPT for adolescents with depressive disorders, and the promise of IPT for the prevention of excess weight gain, future research should involve additional adolescent adaptations (Tanofsky-​Kraff & Wifley, 2009). Adolescence is a key developmental period for cultivating social and interpersonal patterns, which may explain why adolescents appear to relate well to IPT. From its inception, Mufson and colleagues made important adolescent-​ relevant adaptations to the treatment (Mufson et al., 2004). For example, IPT for adolescent depression includes a parent component and the assignment of a “limited sick role,” since youth are required to attend school and reducing their activities is likely to exacerbate their interpersonal difficulties. Given that this foundation has been established, the use of IPT for adolescents with BN and BED warrants investigation. Using IPT for younger children may also be a promising approach. A pilot study of family-​based IPT for the treatment of depressive symptoms in 9-​to 12-​year-​old children was found to be feasible and acceptable to families (Dietz, Mufson, Irvine, & Brent, 2008), and a randomized controlled trial provided evidence of the efficacy of family-​based interpersonal psychotherapy in the treatment of depression for children 7–​12  years old (Dietz, Weinberg, Brent, & Mufson, 2015). The moderating influence of social problems on weight loss outcome in a family-​based program (Wilfley et al., 2007) suggests that targeting interpersonal functioning in the nuclear family milieu may serve as

a point of intervention for the treatment of eating and weight-​ related problems during middle childhood (Tanofsky-​Kraff & Wifley, 2009), particularly for children with greater eating pathology (Goldschmidt et  al., 2014). A  pilot study testing a family-​based adaptation of IPT for preventing excess weight gain is near completion.

Developing Interpersonal Psychotherapy for the Prevention of Eating and Weight-​ Related Problems

Given the increasingly high rates of obesity, it may be reasonably posited that the increases in disordered eating will continue as well, considering that overweight is a significant risk factor for the development of eating pathology (Fairburn et al., 1998; Fairburn et al., 1997). Therefore, the use of IPT to prevent obesity and full-​syndrome eating disorders should be explored by targeting other behaviors that promote both conditions (Tanofsky-​Kraff & Wifley, 2009). Since not all overweight individuals report binge or LOC eating, reducing emotional eating and eating in the absence of hunger may also be suitable for IPT modalities. Studies suggest that LOC eating among youth is associated with eating in response to negative affect (Goossens, Braet, & Decaluwe, 2006), including anger and frustration, depression, and anxiety (Tanofsky-​Kraff et al., 2007), and predictive of increases in depressive symptoms and disordered eating attitudes (Tanofsky-​Kraff et  al., 2011). In studies of adolescents, emotional eating is significantly correlated with constructs of disturbed eating (van Strien, 1996; Van Strien, Engels, Van Leeuwe, & Snoek, 2005) and symptoms of depression and anxiety (Van Strien et al., 2005). Data also suggest that emotional eating may be associated with overweight among youth (Braet & Van Strien, 1997) and overeating in cross-​sectional structural models (Van Strien, Engels, Van Leeuwe, & Snoek, 2005). Considering that in controlled trials IPT for BED effectively reduces eating in response to negative affect in adults (Wilfley et  al., 1993; Wilfley et  al., 2002), and negative affect predicts onset of BED and other eating disorders (Stice et al., 2017), preventive adaptations targeting negative affect (Stice et  al., 2017) and emotional eating require investigation. Eating in the absence of hunger has been associated with overweight (Lansigan, Emond, & Gilbert-​Diamond, 2015; Moens & Braet, 2007) and excessive weight gain over time (Lansigan et al., 2015; Shunk & Birch, 2004), though not all have found support for its contribution to weight or fat

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gain in adolescence (Kelly et  al., 2015). However, reported eating in the absence of hunger has been shown to be associated with dietary restraint (Shomaker et  al., 2010), LOC eating, emotional eating, and elevations in general psychopathology (Tanofsky-​Kraff et al., 2008). Of concern are data indicating that eating in the absence of hunger is a stable trait throughout youth (Birch, Fisher, & Davison, 2003; Fisher & Birch, 2002). Promising findings indicate that young children may be trained to better regulate food intake (Johnson, 2000), and a number of intervention studies targeting eating in the absence of hunger are currently underway. Interpersonal psychotherapy may serve as a natural extension on this work; in particular, negative affect associated with interpersonal problems might be linked to eating in the absence of hunger. Then, recognition of internal physiological hunger cues may be taught so that patients learn to differentiate true hunger from when they are already sated. Finally, there has been a growing interest in and awareness of the role that social and interpersonal factors may play in behavioral health problems (Glass & McAtee, 2006). For obesity in particular, moving away from focusing solely on individual behavioral changes (e.g., diet and exercise) and toward the greater social context has not been the norm. Interpersonal psychotherapy may be particularly well suited for developing new approaches for the prevention of obesity and eating disorders on a broader social level (NIH, 2011; Tanofsky-​Kraff & Wifley, 2009).

Disseminating and Implementing Interpersonal Psychotherapy

Evidence-​based psychotherapies such as IPT exist; however, they are not routinely used in service settings due to barriers in clinician training (Fairburn & Wilson, 2013). The field of mental healthcare recognizes the important need to reduce this gap in training that would likely lead to improvements in care (Ravitz et  al., 2014). Initial efforts have been made to disseminate and evaluate IPT in clinical settings. The Veterans Health Administration developed a national initiative to promote the dissemination of evidence-​ based practices in their care settings, including IPT for depression (Stewart et  al., 2014). The Veterans Affairs IPT training program involved a 3-​day workshop and 6  months of weekly telephone consultation with an IPT expert, and results were promising with a high rate of training program completion (93%) and therapist 312

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competency in IPT. Moreover, veterans treated experienced significant reductions in depressive symptoms and reported improvements in quality of life (Stewart et al., 2014). The Veterans Health Administration’s national training and implementation efforts provide support for the feasibility and effectiveness of the broad dissemination of IPT to clinical care settings. Wilfley, Wilson, Agras, and colleagues are currently examining the dissemination and implementation of IPT for eating disorders in college counseling centers across the United States in two separate trials. In the first trial, Wilfley and colleagues are examining the short-​ and long-​term effectiveness of two methods of training therapists in IPT (Wilfley et al., 2016; National Institute of Mental Health, Washington University School of Medicine). The first training method includes a more traditional format, composed of an in-​person workshop and 12  months of expert consultation. The second method involves training a counseling center staff member in IPT who is then taught to train other staff members within his/​her site (i.e., a train-​ the-​ trainer approach). Patient outcomes will then be assessed to examine implementation effects. The second trial is in development and seeks to create and evaluate the effectiveness of a novel online training platform of IPT for eating disorders (Wilfley, 2015). If successful, training via an online platform will allow accessibility and flexibility, invaluable features considering practicing therapists’ limited time and resources and the financial constraints of service settings. Other benefits of online training include trainees’ abilities to reinforce learning with access to repeatedly review and reference training material. An advantage is that an online training platform can be updated regularly, eliminating the barrier of incorporating and distributing new information. Future research should continue to examine the dissemination and implementation of IPT given the important implications these efforts have on training competent clinicians in the treatment of evidence–​based treatment of eating disorders. In addition, considering IPT is effective in treating a range of mental health problems (e.g., depression and anxiety; Cuijpers et al., 2016), it is an efficient intervention to disseminate (Kazdin, Fitzsimmons-​Craft, & Wilfley, 2016). The flexibility of IPT to address a range of psychopathology and its inherent adaptability to one’s cultural and social norms makes it well suited for widespread dissemination and implementation efforts (Kazdin et al., 2016).

Conclusion

Interpersonal psychotherapy for eating disorders is a focused, time-​ limited treatment that targets interpersonal problems associated with the onset and/​ or maintenance of the eating disorder. The interpersonal focus is highly relevant to individuals with eating disorders, many of whom experience difficulties in interpersonal functioning. Depending on the individual’s primary problem area, specific treatment strategies and goals are incorporated into the treatment plan. The primary problem area is determined by conducting a thorough interpersonal inventory, a unique aspect of IPT, and by devising an individualized interpersonal formulation for each patient. Interpersonal psychotherapy has resulted in significant and well-​maintained improvements for the treatment of BN and BED. Data support the utility of IPT for the prevention of excess weight gain in adolescent girls, particularly those with higher social problems and anxiety. Further investigation is required to determine whether IPT is suitable for and effective in the treatment of AN. Adaptations of IPT should be explored for adolescent populations and the treatment of other eating-​and weight-​ related problems. Finally, an important next step is to disseminate IPT into routine clinical care settings.

Glossary Interpersonal inventory: Conducted at the initiation of treatment, the therapist conducts a thorough review of the patient’s interpersonal history and links psychosocial functioning to the eating disorder symptoms. Life chart: An outline of life events and the development and maintenance of eating disorder symptoms. Problem areas: Focus of treatment is on the resolution of problems within four social domains that are associated with the onset and/​or maintenance of the eating disorder: (1) interpersonal deficits, (2) interpersonal role disputes, (3) role transitions, and (4) grief. Sick role: Role delineated by the therapist to allow the patient to be relieved of other responsibilities in order to recover. Treatment phases: Interpersonal psychotherapy is divided into three phases: The initial phase is dedicated to identifying the problem area(s) that will be the target for treatment. The intermediate phase is devoted to working on the target problem

area(s). The termination phase is devoted to consolidating gains made during treatment and preparing for future work.

Acknowledgments

NIDDK grant 1R01DK080906-​01A1 (MTK). USUHS grant R072IC (to MTK). NIMH grant 5R01MH064153-​ 06 (DEW). NIMH grant 1K24MH070446 (DEW). Disclaimer:  The opinions and assertions expressed herein are those of the authors and are not to be construed as reflecting the views of USUHS or the US Department of Defense.

Abbreviations AN: Anorexia nervosa BED: Binge eating disorder BN: Bulimia nervosa CBT: Cognitive-​behavioral therapy IPT: Interpersonal psychotherapy IPT-​AST: Interpersonal psychotherapy-​Adolescent skills training LOC: Loss of control (over eating)

References

Agras, W. S., Telch, C. F., Arnow, B., Eldredge, K., Detzer, M. J., Henderson, J., & Marnell, M. (1995). Does interpersonal therapy help patients with binge eating disorder who fail to respond to cognitive-​behavioral therapy? Journal of Consulting and Clinical Psychology, 63, 356–​360. Agras, W. S., Telch, C. F., Arnow, B., Eldredge, K., & Marnell, M. (1997). One-​year follow-​up of cognitive-​behavioral therapy for obese individuals with binge eating disorder. Journal of Consulting and Clinical Psychology, 65, 343–​347. Agras, W. S., Walsh, B. T., Fairburn, C. G., Wilson, G. T., & Kraemer, H. C. (2000). A multicenter comparison of cognitive-​behavioral therapy and interpersonal psychotherapy for bulimia nervosa. Archives of General Psychiatry, 57, 459–​466. Ambwani, S., Roche, M. J., Minnick, A. M., & Pincus, A. L. (2015). Negative affect, interpersonal perception, and binge eating behavior: An experience sampling study. International Journal of Eating Disorders, 48, 715–​726. doi:10.1002/​eat.22410 Ansell, E. B., Grilo, C. M., & White, M. A. (2012). Examining the interpersonal model of binge eating and loss of control over eating in women. International Journal of Eating Disorders, 45, 43–​50. doi:10.1002/​eat.20897 Arcelus, J., Haslam, M., Farrow, C., & Meyer, C. (2013). The role of interpersonal functioning in the maintenance of eating psychopathology: A systematic review and testable model. Clinical Psychology Review, 33, 156–​167. doi:10.1016/​ j.cpr.2012.10.009 Arcelus, J., Whight, D., Brewin, N., & McGrain, L. (2012). A brief form of interpersonal psychotherapy for adult patients with bulimic disorders:  A  pilot study. European Eating Disorders Review, 20, 326–​330. doi:10.1002/​erv.2164 Birch, L. L., Fisher, J. O., & Davison, K. K. (2003). Learning to overeat:  Maternal use of restrictive feeding practices

Burke, Karam, Tanofsky-Kraff, Wilfley

313

promotes girls’ eating in the absence of hunger. American Journal of Clinical Nutrition, 78, 215–​220. Birchall, H. (1999). Interpersonal psychotherapy in the treatment of eating disorder. European Eating Disorders Review, 7, 315–​320. Blomquist, K. K., Ansell, E. B., White, M. A., Masheb, R. M., & Grilo, C. M. (2012). Interpersonal problems and developmental trajectories of binge eating disorder. Comprehensive Psychiatry, 53, 1088–​1095. doi:10.1016/​ j.comppsych.2012.05.003 Bowlby, J. (1982). Attachment and loss (2nd ed., Vol. 1). New York, NY: Basic Books. Braet, C., & Van Strien, T. (1997). Assessment of emotional, externally induced and restrained eating behaviour in nine to twelve-​year-​old obese and non-​obese children. Behaviour Research and Therapy, 35, 863–​873. Bravender, T. (2005). Health, education, and youth in Durham: HEY-​Durham curricular guide (2nd ed.). Durham, NC: Duke University Press. Carter, F. A., Jordan, J., McIntosh, V. V. W., Luty, S. E., McKenzie, J. M., Frampton, C. M. A.,  . . .  Joyce, P. R. (2011). The long‐term efficacy of three psychotherapies for anorexia nervosa: A randomized, controlled trial. International Journal of Eating Disorders, 44, 647–​654. doi:10.1002/​eat.20879 Cassidy, O., Eichen, D. M., Burke, N. L., Patmore, J., Shore, A., Radin, R. M.,  . . .  Tanofsky-​Kraff, M. (2016). Adapting interpersonal psychotherapy for the prevention of excessive weight gain:  Considerations for urban African American girls. Manuscript submitted for publication. Cassidy, O., Sbrocco, T., Vannucci, A., Nelson, B., Jackson-​ Bowen, D., Heimdal, J.,   .  .  .  Tanofsky-​Kraff, M. (2013). Adapting interpersonal psychotherapy for the prevention of excessive weight gain in rural African American girls. Journal of Pediatric Psychology, 38, 965–​977. doi:10.1093/​jpepsy/​ jst029 Chui, W., Safer, D. L., Bryson, S. W., Agras, W. S., & Wilson, G. T. (2007). A comparison of ethnic groups in the treatment of bulimia nervosa. Eating Behaviors, 8, 458–​491. doi:10.1016/​ j.eatbeh.2007.01.005 Constantino, M. J., Arnow, B. A., Blasey, C., & Agras, W. S. (2005). The association between patient characteristics and the therapeutic alliance in cognitive-​behavioral and interpersonal therapy for bulimia nervosa. Journal of Consulting and Clinical Psychology, 73, 203–​211. Crow, S. J., Stewart Agras, W., Halmi, K., Mitchell, J. E., & Kraemer, H. C. (2002). Full syndromal versus subthreshold anorexia nervosa, bulimia nervosa, and binge eating disorder:  A  multicenter study. International Journal of Eating Disorders, 32, 309–​318. Cuijpers, P., Donker, T., Weissman, M. M., Ravitz, P., & Cristea, I. A. (2016). Interpersonal psychotherapy for mental health problems: A comprehensive meta-​analysis. American Journal of Psychiatry, 173, 680–​687. doi:10.1176/​appi. ajp.2015.15091141 Devlin, M. J., Goldfein, J. A., Petkova, E., Jiang, H., Raizman, P. S., Wolk, S.,  . . .  Walsh, B. T. (2005). Cognitive behavioral therapy and fluoxetine as adjuncts to group behavioral therapy for binge eating disorder. Obesity Research, 13, 1077–​1088. Dietz, L. J., Mufson, L., Irvine, H., & Brent, D. A. (2008). Family-​ based Interpersonal Psychotherapy (IPT) for depressed preadolescents:  An open treatment trial. Early Intervention Psychiatry, 2, 154–​161.

314

Interpersonal Psychotherapy

Dietz, L. J., Weinberg, R. J., Brent, D. A., & Mufson, L. (2015). Family-​ based interpersonal psychotherapy for depressed preadolescents:  examining efficacy and potential treatment mechanisms. Journal of the American Academy of Child and Adolescent Psychiatry, 54, 191–​199. doi:10.1016/​ j.jaac.2014.12.011 Dounchis, J. Z., Welch, R. R., & Wilfley, D. E. (1999). Using group interpersonal psychotherapy (IPT-​G) for the treatment of binge eating disorders. Paper presented at the Academy of Eating Disorders Annual Meeting, San Diego, CA. Duchesne, M., de Oliveira Falcone, E. M., de Freitas, S. R., D’Augustin, J. F., Marinho, V., & Appolinario, J. C. (2012). Assessment of interpersonal skills in obese women with binge eating disorder. Journal of Health Psychology, 17, 1065–​1075. doi:10.1177/​1359105311432326 Elliott, C. A., Tanofsky-​Kraff, M., Shomaker, L. B., Columbo, K. M., Wolkoff, L. E., Ranzenhofer, L. M., & Yanovski, J. A. (2010). An examination of the interpersonal model of loss of control eating in children and adolescents. Behaviour Research and Therapy, 48, 424–​428. doi:10.1016/​ j.brat.2009.12.012 Evans, L., & Wertheim, E. H. (1998). Intimacy patterns and relationship satisfaction of women with eating problems and the mediating effects of depression, trait anxiety and social anxiety. Journal of Psychosomatic Research, 44, 355–​365. Fairburn, C. G. (1997). Interpersonal psychotherapy for bulimia nervosa. In D. M. Garner & P. E. Garfinkel (Eds.), Handbook of treatment for eating disorders (Vol. 2, pp. 278–​ 294). New York, NY: Guilford. Fairburn, C. G. (2008). Cognitive behavior therapy and eating disorders. New York, NY: Guilford Press. Fairburn, C. G., Doll, H. A., Welch, S. L., Hay, P. J., Davies, B. A., & O’Connor, M. E. (1998). Risk factors for binge eating disorder:  A  community-​ based, case-​ control study. Archives of General Psychiatry, 55, 425–​432. doi:10.1001/​ archpsyc.55.5.425 Fairburn, C. G., Jones, R., Peveler, R. C., Carr, S. J., Solomon, R. A., O’Connor, M. E.,  . . .  Hope, R. A. (1991). Three psychological treatments for bulimia nervosa: A comparative trial. Archives of General Psychiatry, 48, 463–​469. Fairburn, C. G., Norman, P. A., Welch, S. L., O’Connor, M. E., Doll, H. A., & Peveler, R. C. (1995). A prospective study of outcome in bulimia nervosa and the long-​term effects of three psychological treatments. Archives of General Psychiatry, 52, 304–​312. Fairburn, C. G., Peveler, R. C., Jones, R., Hope, R. A., & Doll, H. A. (1993). Predictors of 12-​month outcome in bulimia nervosa and the influence of attitudes to shape and weight. Journal of Consulting and Clinical Psychology, 61, 696–​698. Fairburn, C. G., Welch, S. L., Doll, H. A., Davies, B. A., & O’Connor, M. E. (1997). Risk factors for bulimia nervosa:  A  community-​based case-​control study. Archives of General Psychiatry, 54, 509–​517. doi:10.1001/​ archpsyc.1997.01830180015003 Fairburn, C. G., & Wilson, G. T. (2013). The dissemination and implementation of psychological treatments:  Problems and solutions. International Journal of Eating Disorders, 46, 516–​ 521. doi:10.1002/​eat.22110 Fallon, E. M., Tanofsky-​Kraff, M., Norman, A. C., McDuffie, J. R., Taylor, E. D., Cohen, M. L.,  . . .  Yanovski, J. A. (2005). Health-​related quality of life in overweight and nonoverweight black and white adolescents. Journal of Pediatrics, 147, 443–​450.

Fisher, J. O., & Birch, L. L. (2002). Eating in the absence of hunger and overweight in girls from 5 to 7 y of age. American Journal of Clinical Nutrition, 76, 226–​231. Frank, E., & Spanier, C. (1995). Interpersonal psychotherapy for depression: Overview, clinical efficacy, and future directions. Clinical Psychology, 2, 349–​369. Freeman, L. M. Y., & Gil, K. M. (2004). Daily stress, coping, and dietary restraint in binge eating. International Journal of Eating Disorders, 36, 204–​212. Ghaderi, A., & Scott, B. (1999). Prevalence and psychological correlates of eating disorders among females aged 18–​30  years in the general population. Acta Psychiatrica Scandinavica, 99, 261–​266. Glass, T. A., & McAtee, M. J. (2006). Behavioral science at the crossroads in public health: Extending horizons, envisioning the future. Social Science and Medicine, 62, 1650–​1671. Goldschmidt, A. B., Best, J. R., Stein, R. I., Saelens, B. E., Epstein, L. H., & Wilfley, D. E. (2014). Predictors of child weight loss and maintenance among family-​based treatment completers. Journal of Consulting and Clinical Psychology, 82, 1140–​1150. doi:10.1037/​a0037169 Goldschmidt, A. B., Loth, K. A., MacLehose, R. F., Pisetsky, E. M., Berge, J. M., & Neumark-​ Sztainer, D. (2015). Overeating with and without loss of control:  Associations with weight status, weight-​related characteristics, and psychosocial health. The International Journal of Eating Disorders, 48, 1150–​1157. doi:10.1002/​eat.22465 Goossens, L., Braet, C., & Decaluwe, V. (2006). Loss of control over eating in obese youngsters. Behaviour Research and Therapy, 45, 1–​9. doi:10.1016/​j.brat.2006.01.006 Grilo, C. M., Masheb, R. M., & Wilson, G. T. (2005). Efficacy of cognitive behavioral therapy and fluoxetine for the treatment of binge eating disorder: A randomized double-​blind placebo-​controlled comparison. Biological Psychiatry, 57, 301–​309. Grissett, N. I., & Norvell, N. K. (1992). Perceived social support, social skills, and quality of relationships in bulimic women. Journal of Consulting and Clinical Psychology, 60, 293–​299. Gual, P., Perez-​Gaspar, M., Martinez-​Gonzalez, M. A., Lahortiga, F., de Irala-​Estevez, J., & Cervera-​Enguix, S. (2002). Self-​ esteem, personality, and eating disorders:  Baseline assessment of a prospective population-​based cohort. International Journal of Eating Disorders, 31, 261–​273. Hartmann, A., Zeeck, A., & Barrett, M. S. (2010). Interpersonal problems in eating disorders. International Journal of Eating Disorders, 43, 619–​627. doi:10.1002/​eat.20747 Hayden-​Wade, H. A., Stein, R. I., Ghaderi, A., Saelens, B. E., Zabinski, M. F., & Wilfley, D. E. (2005). Prevalence, characteristics, and correlates of teasing experiences among overweight children vs. non-​overweight peers. Obesity Research, 13, 1381–​1392. doi:10.1038/​oby.2005.167 Herzog, D., Keller, M., Lavori, P., & Ott, I. (1987). Social impairment in bulimia. International Journal of Eating Disorders, 6, 741–​747. Hilbert, A., Bishop, M. E., Stein, R. I., Tanofsky-​Kraff, M., Swenson, A. K., Welch, R. R., & Wilfley, D. E. (2012). Long-​term efficacy of psychological treatments for binge eating disorder. The British Journal of Psychiatry, 200, 232–​237. doi:10.1192/​bjp.bp.110.089664 Hilbert, A., Saelens, B. E., Stein, R. I., Mockus, D. S., Welch, R. R., Matt, G. E., & Wilfley, D. E. (2007). Pretreatment and process predictors of outcome in interpersonal and cognitive behavioral psychotherapy for binge eating disorder.

Journal of Consulting and Clinical Psychology, 75, 645–​651. doi:10.1037/​0022-​006X.75.4.645 Humphrey, L. L. (1989). Observed family interactions among subtypes of eating disorders using structural analysis of social behavior. Journal of Consulting and Clinical Psychology, 57, 206–​214. Ivanova, I. V., Tasca, G. A., Hammond, N., Balfour, L., Ritchie, K., Koszycki, D., & Bissada, H. (2015). Negative affect mediates the relationship between interpersonal problems and binge-​eating disorder symptoms and psychopathology in a clinical sample: A test of the interpersonal model. European Eating Disorders Review, 23, 133–​138. doi:10.1002/​erv.2344 Ivanova, I. V., Tasca, G. A., Proulx, G., & Bissada, H. (2015). Does the interpersonal model apply across eating disorder diagnostic groups? A structural equation modeling approach. Comprehensive Psychiatry, 63, 80–​87. doi:10.1016/​ j.comppsych.2015.08.009 Jacobs, M. J., Welch, R. R., & Wilfley, D. E. (2004). Interpersonal psychotherapy for anorexia nervosa, bulimia nervosa, and binge eating disorder. In T. Brewerton (Ed.), Clinical handbook of eating disorders: An integrated approach (pp. 449–​472). New York, NY: Marcel Dekker. Johnson, J. G., Spitzer, R. L., & Williams, J. B. (2001). Health problems, impairment and illnesses associated with bulimia nervosa and binge eating disorder among primary care and obstetric gynaecology patients. Psychological Medicine, 31, 1455–​1466. Johnson, S. L. (2000). Improving preschoolers’ self-​regulation of energy intake. Pediatrics, 106, 1429–​1435. Jones, A., Lindekilde, N., Lubeck, M., & Clausen, L. (2015). The association between interpersonal problems and treatment outcome in the eating disorders: A systematic review. Nordic Journal of Psychiatry, 69, 563–​573. doi:10.3109/​ 08039488.2015.1019924 Kazdin, A. E., Fitzsimmons-​Craft, E. E., & Wilfley, D. E. (2016). Addressing critical gaps in the treatment of eating disorders. Manuscript submitted for publication. Keel, P. K., Dorer, D. J., Franko, D. L., Jackson, S. C., & Herzog, D. B. (2005). Postremission predictors of relapse in women with eating disorders. American Journal of Psychiatry, 162, 2263–​2268. Kelly, N. R., Shomaker, L. B., Pickworth, C. K., Brady, S. M., Courville, A. B., Bernstein, S.,  . . .  Yanovski, J. A. (2015). A prospective study of adolescent eating in the absence of hunger and body mass and fat mass outcomes. Obesity, 23, 1472–​1478. doi:10.1002/​oby.21110 Kenardy, J., Mensch, M., Bowen, K., Green, B., & Walton, J. (2002). Group therapy for binge eating in Type 2 diabetes: A randomized trial. Diabetic Medicine, 19, 234–​239. Klerman, G. L., Weissman, M. M., Rounsaville, B. J., & Chevron, E. S. (1984). Interpersonal psychotherapy of depression. New York, NY: Basic Books. Lansigan, R. K., Emond, J. A., & Gilbert-​Diamond, D. (2015). Understanding eating in the absence of hunger among young children: A systematic review of existing studies. Appetite, 85, 36–​47. doi:10.1016/​j.appet.2014.10.032 Lavender, J. M., Utzinger, L. M., Cao, L., Wonderlich, S. A., Engel, S. G., Mitchell, J. E., & Crosby, R. D. (2016). Reciprocal associations between negative affect, binge eating, and purging in the natural environment in women with bulimia nervosa. Journal of Abnormal Psychology, 125, 381–​ 386. doi:10.1037/​abn0000135 Lemeshow, A. R., Fisher, L., Goodman, E., Kawachi, I., Berkey, C. S., & Colditz, G. A. (2008). Subjective social status in the

Burke, Karam, Tanofsky-Kraff, Wilfley

315

school and change in adiposity in female adolescents: findings from a prospective cohort study. Archives of Pediatrics and Adolescent Medicine, 162, 23–​28. Markowitz, J. C., Skodol, A. E., & Bleiberg, K. (2006). Interpersonal psychotherapy for borderline personality disorder:  Possible mechanisms of change. Journal of Clinical Psychology, 62, 431–​444. doi:10.1002/​jclp.20242 McIntosh, V. V., Bulik, C. M., McKenzie, J. M., Luty, S. E., & Jordan, J. (2000). Interpersonal psychotherapy for anorexia nervosa. International Journal of Eating Disorders, 27, 125–​139. McIntosh, V. V., Jordan, J., Carter, F. A., Luty, S. E., McKenzie, J. M., Bulik, C. M.,   .  .  .  Joyce, P. R. (2005). Three psychotherapies for anorexia nervosa: A randomized, controlled trial. American Journal of Psychiatry, 162, 741–​747. Meyer, A. (1957). Psychobiology:  A  science of man. Springfield, IL: Thomas. Moens, E., & Braet, C. (2007). Predictors of disinhibited eating in children with and without overweight. Behaviour Research and Therapy, 45, 1357–​1368. Mufson, L., Dorta, K. P., Moreau, D., & Weissman, M. M. (2004). Interpersonal psychotherapy for depressed adolescents (2nd ed.). New York, NY: Guilford Press. Nauta, H., Hospers, H., Kok, G., & Jansen, A. (2000). A comparison between a cognitive and a behavioral treatment for obese binge eaters and obese non-​ binge eaters. Behavior Therapy, 21, 441–​461. Neumark-​ Sztainer, D., Falkner, N., Story, M., Perry, C., Hannan, P. J., & Mulert, S. (2002). Weight-​teasing among adolescents:  Correlations with weight status and disordered eating behaviors. International Journal of Obesity and Related Metabolic Disorders, 26, 123–​131. doi:10.1038/​sj.ijo.0801853 Nevonen, L., & Broberg, A. G. (2006). A comparison of sequenced individual and group psychotherapy for patients with bulimia nervosa. International Journal of Eating Disorders, 39, 117–​127. NIH, O. R. T. F. (2011). Strategic plan for NIH obesity research. Bethesda, MD:  Author. Retrieved from https://​obesityresearch.nih.gov/​about/​StrategicPlanforNIH_​Obesity_​ Research_​Full-​Report_​2011.pdf O’Mahony, J. F., & Hollwey, S. (1995a). The correlates of binge eating in two nonpatient samples. Addictive Behaviors, 20, 471–​480. O’Mahony, J. F., & Hollwey, S. (1995b). Eating problems and interpersonal functioning among several groups of women. Journal of Clinical Psychology, 51, 345–​351. Ogden, C. L., Carroll, M. D., Kit, B. K., & Flegal, K. M. (2014). Prevalence of childhood and adult obesity in the United States, 2011–​2012. JAMA, 311, 806–​814. doi:10.1001/​ jama.2014.732 Ogden, C. L., Carroll, M. D., Lawman, H. G., Fryar, C. D., Kruszon-​Moran, D., Kit, B. K., & Flegal, K. M. (2016). Trends in obesity prevalence among children and adolescents in the United States, 1988–​1994 through 2013–​2014. JAMA, 315, 2292–​2299. doi:10.1001/​jama.2016.6361 Puhl, R. M. (2011). Weight stigmatization toward youth: A significant problem in need of societal solutions. Childhood Obesity, 7, 359–​363. doi:10.1089/​chi.2011.0500.pers Radin, R. M., Tanofsky-​Kraff, M., Shomaker, L. B., Kelly, N. R., Pickworth, C. K., Shank, L. M.,  . . .  Yanovski, J. A. (2015). Metabolic characteristics of youth with loss of control eating. Eating Behaviors, 19, 86–​89. doi:S1471-​015300099-​9 Ranzenhofer, L. M., Engel, S. G., Crosby, R. D., Anderson, M., Vannucci, A., Cohen, L. A.,  . . .  Tanofsky-​Kraff, M. (2014).

316

Interpersonal Psychotherapy

Using ecological momentary assessment to examine interpersonal and affective predictors of loss of control eating in adolescent girls. International Journal of Eating Disorders, 47, 748–​757. doi:10.1002/​eat.22333 Ravitz, P., Wondimagegn, D., Pain, C., Araya, M., Alem, A., Baheretibeb, Y.,   .  .  .  Leszcz, M. (2014). Psychotherapy knowledge translation and interpersonal psychotherapy:  Using best-​ education practices to transform mental health care in Canada and Ethiopia. American Journal of Psychotherapy, 68, 463–​488. Raykos, B. C., McEvoy, P. M., Carter, O., Fursland, A., & Nathan, P. (2014). Interpersonal problems across restrictive and binge-​purge samples:  Data from a community-​based eating disorders clinic. Eating Behaviors, 15, 449–​452. doi:10.1016/​j.eatbeh.2014.06.008 Ricca, V., Mannucci, E., Mezzani, B., Moretti, S., Di Bernardo, M., Bertelli, M.,  . . .  Faravelli, C. (2001). Fluoxetine and fluvoxamine combined with individual cognitive-​behaviour therapy in binge eating disorder: A one-​year follow-​up study. Psychotherapy and Psychosomatics, 70, 298–​306. Rieger, E., Van Buren, D. J., Bishop, M., Tanofsky-​Kraff, M., Welch, R., & Wilfley, D. E. (2010). An eating disorder-​specific model of interpersonal psychotherapy (IPT-​ ED):  Causal pathways and treatment implications. Clinical Psychology Review, 30, 400–​410. doi:10.1016/​j.cpr.2010.02.001 Rorty, M., Yager, J., Buckwalter, J. G., & Rossotto, E. (1999). Social support, social adjustment, and recovery status in bulimia nervosa. International Journal of Eating Disorders, 26, 1–​12. Ruuska, J., Koivisto, A. M., Rantanen, P., & Kaltiala-​Heino, R. (2007). Psychosocial functioning needs attention in adolescent eating disorders. Nordic Journal of Psychiatry, 61, 452–​ 458. doi:10.1080/​08039480701773253 Schvey, N. A., Sbrocco, T., Stephens, M., Bryant, E. J., Ress, R., Spieker, E. A.,  . . .  Tanofsky-​Kraff, M. (2015). Comparison of overweight and obese military-​dependent and civilian adolescent girls with loss-​of-​control eating. International Journal of Eating Disorders, 48, 790–​794. doi:10.1002/​eat.22424 Schwimmer, J. B., Burwinkle, T. M., & Varni, J. W. (2003). Health-​related quality of life of severely obese children and adolescents. JAMA, 289, 1813–​1819. Shomaker, L. B., Tanofsky-​Kraff, M., Zocca, J. M., Courville, A., Kozlosky, M., Columbo, K. M.,  . . .  Yanovski, J. A. (2010). Eating in the absence of hunger in adolescents: intake after a large-​array meal compared with that after a standardized meal. American Journal of Clinical Nutrition, 92, 697–​703. doi:10.3945/​ajcn.2010.29812 Shunk, J. A., & Birch, L. L. (2004). Girls at risk for overweight at age 5 are at risk for dietary restraint, disinhibited overeating, weight concerns, and greater weight gain from 5 to 9 years. Journal of the American Dietetic Association, 104, 1120–​1126. Sonneville, K. R., Horton, N. J., Micali, N., Crosby, R. D., Swanson, S. A., Solmi, F., & Field, A. E. (2013). Longitudinal associations between binge eating and overeating and adverse outcomes among adolescents and young adults:  Does loss of control matter? JAMA Pediatrics, 167, 149–​155. doi:10.1001/​2013.jamapediatrics.12 Steiger, H., Gauvin, L., Jabalpurwala, S., Seguin, J. R., & Stotland, S. (1999). Hypersensitivity to social interactions in bulimic syndromes: Relationship to binge eating. Journal of Consulting and Clinical Psychology, 67, 765–​775. Stewart, M. O., Raffa, S. D., Steele, J. L., Miller, S. A., Clougherty, K. F., Hinrichsen, G. A., & Karlin, B. E. (2014). National dissemination of interpersonal psychotherapy for

depression in veterans: therapist and patient-​level outcomes. Journal of Consulting and Clinical Psychology, 82, 1201–​ 1206. doi:10.1037/​a0037410 Stice, E., Gau, J. M., Rohde, P., & Shaw, H. (2017). Risk factors that predict future onset of each DSM-​5 eating disorder:  Predictive specificity in high-​risk adolescent females. Journal of Abnormal Psychology, 126, 38–​51. doi:10.1037/​ abn0000219 Strauss, R. S., & Pollack, H. A. (2003). Social marginalization of overweight children. Archives of Pediatrics and Adolescent Medicine, 157, 746–​752. Striegel-​Moore, R. H., Silberstein, L. R., & Rodin, J. (1986). Toward an understanding of risk factors for bulimia. American Psychologist, 41, 246–​263. Svaldi, J., Dorn, C., & Trentowska, M. (2011). Effectiveness for interpersonal problem-​solving is reduced in women with binge eating disorder. European Eating Disorders Review, 19, 331–​341. doi:10.1002/​erv.1050 Tanofsky-​Kraff, M. (2008). Binge eating among children and adolescents. In E. Jelalian & R. Steele (Eds.), Handbook of child and adolescent obesity (pp. 41–​57):  New  York, NY. Springer. Tanofsky-​Kraff, M., Cohen, M. L., Yanovski, S. Z., Cox, C., Theim, K. R., Keil, M.,  . . .  Yanovski, J. A. (2006). A prospective study of psychological predictors of body fat gain among children at high risk for adult obesity. Pediatrics, 117, 1203–​1209. doi:117/​4/​1203 Tanofsky-​Kraff, M., Ranzenhofer, L. M., Yanovski, S. Z., Schvey, N. A., Faith, M., Gustafson, J., & Yanovski, J. A. (2008). Psychometric properties of a new questionnaire to assess eating in the absence of hunger in children and adolescents. Appetite, 51, 148–​155. Tanofsky-​Kraff, M., Shomaker, L. B., Olsen, C., Roza, C. A., Wolkoff, L. E., Columbo, K. M.,  . . .  Yanovski, J. A. (2011). A prospective study of pediatric loss of control eating and psychological outcomes. Journal of Abnormal Psychology, 120, 108–​118. doi:10.1037/​a0021406 Tanofsky-​Kraff, M., Shomaker, L. B., Stern, E. A., Miller, R., Sebring, N., Dellavalle, D.,   .  .  .  Yanovski, J. A. (2012). Children’s binge eating and development of metabolic syndrome. International Journal of Obesity, 36, 956–​962. doi:10.1038/​ijo.2011.259 Tanofsky-​Kraff, M., Shomaker, L. B., Wilfley, D. E., Young, J. F., Sbrocco, T., Stephens, M.,  . . .  Yanovski, J. A. (2017). Excess weight gain prevention in adolescents:  Three-​ year outcome following a randomized-​ controlled trial. Journal of Consulting and Clinical Psychology, 85, 218–​227. doi:10.1037/​ccp0000153 Tanofsky-​Kraff, M., Shomaker, L. B., Wilfley, D. E., Young, J. F., Sbrocco, T., Stephens, M.,  . . .  Yanovski, J. A. (2014). Targeted prevention of excess weight gain and eating disorders in high-​risk adolescent girls:  A  randomized controlled trial. American Journal of Clinical Nutrition, 100, 1010–​ 1018. doi:10.3945/​ajcn.114.092536 Tanofsky-​Kraff, M., Shomaker, L. B., Young, J. F., & Wilfley, D. E. (2016). Interpersonal psychotherapy for the prevention of excess weight gain and eating disorders:  A  brief case study. Psychotherapy, 53, 188–​194. doi:10.1037/​ pst0000051 Tanofsky-​Kraff, M., & Wifley, D. E. (2009). Interpersonal psychotherapy (IPT) for bulimia nervosa and binge eating disorder. In C. Grilo & J. Mitchell (Eds.), The treatment of eating disorders (pp. 271–​293). New York, NY: Guilford Press.

Tanofsky-​Kraff, M., Wilfley, D. E., & Spurrell, E. (2000). Impact of interpersonal and ego-​related stress on restrained eaters. International Journal of Eating Disorders, 27, 411–​418. Tanofsky-​Kraff, M., Wilfley, D. E., Young, J. F., Mufson, L., Yanovski, S. Z., Glasofer, D. R., & Salaita, C. G. (2007). Preventing excessive weight gain in adolescents: Interpersonal psychotherapy for binge eating. Obesity, 15, 1345–​1355. doi:10.1038/​oby.2007.162 Tanofsky-​Kraff, M., Wilfley, D. E., Young, J. F., Mufson, L., Yanovski, S. Z., Glasofer, D. R.,  . . .  Schvey, N. A. (2010). A pilot study of interpersonal psychotherapy for preventing excess weight gain in adolescent girls at-​risk for obesity. International Journal of Eating Disorders, 43, 701–​706. doi:10.1002/​eat.20773 Tanofsky-​Kraff, M., Yanovski, S. Z., Schvey, N. A., Olsen, C. H., Gustafson, J., & Yanovski, J. A. (2009). A prospective study of loss of control eating for body weight gain in children at high risk for adult obesity. International Journal of Eating Disorders, 42, 26–​30. doi:10.1002/​eat.20580 Tasca, G. A., Balfour, L., Presniak, M. D., & Bissada, H. (2012). Outcomes of specific interpersonal problems for binge eating disorder:  Comparing group psychodynamic interpersonal psychotherapy and group cognitive behavioral therapy. International Journal of Group Psychotherapy, 62, 197–​218. doi:10.1521/​ijgp.2012.62.2.197 Tasca, G. A., Mikail, S., & Hewitt, P. L. (2005). Group psychodynamic interpersonal psychotherapy:  Summary of a treatment model and outcomes for depressive symptoms. In M. E. Abelian (Ed.), Focus on Psychotherapy Research (pp. 159–​188). Hauppauge, NY:  Nova Science Publishers. Tasca, G. A., Taylor, D., Ritchie, K., & Balfour, L. (2004). Attachment predicts treatment completion in an eating disorders partial hospital program among women with anorexia nervosa. Journal of Personality Assessment, 83, 201–​212. Telch, C. F., Agras, W. S., Rossiter, E. M., Wilfley, D. E., & Kenardy, J. (1990). Group cognitive-​behavioral treatment for the nonpurging bulimic: An initial evaluation. Journal of Consulting and Clinical Psychology, 58, 629–​635. Thompson-​Brenner, H., & Westen, D. (2005). A naturalistic study of psychotherapy for bulimia nervosa, Part 2: Therapeutic interventions in the community. Journal of Nervous and Mental Disease, 193, 585–​595. Troisi, A., Massaroni, P., & Cuzzolaro, M. (2005). Early separation anxiety and adult attachment style in women with eating disorders. British Journal of Clinical Psychology, 44(Pt 1), 89–​97. Troop, N. A., Holbrey, A., Trowler, R., & Treasure, J. L. (1994). Ways of coping in women with eating disorders. Journal of Nervous and Mental Disease, 182, 535–​540. Vall, E., & Wade, T. D. (2015). Predictors of treatment outcome in individuals with eating disorders: A systematic review and meta-​analysis. International Journal of Eating Disorders, 48, 946–​971. doi:10.1002/​eat.22411 Van Strien, T. (1996). On the relationship between dieting and “obese” and bulimic eating patterns. International Journal of Eating Disorders, 19, 83–​92. Van Strien, T., Engels, R. C., Van Leeuwe, J., & Snoek, H. M. (2005). The Stice model of overeating: Tests in clinical and non-​clinical samples. Appetite, 45, 205–​213. Weissman, M. M., Markowitz, J., & Klerman, G. L. (2000). Comprehensive guide to interpersonal psychotherapy. New York, NY: Basic Behavioral Science Books.

Burke, Karam, Tanofsky-Kraff, Wilfley

317

Whisman, M. A., Dementyeva, A., Baucom, D. H., & Bulik, C. M. (2012). Marital functioning and binge eating disorder in married women. International Journal of Eating Disorders, 45, 385–​389. doi:10.1002/​eat.20935 Wilfley, D. E. (2008). Interpersonal psychotherapy for binge eating disorder (BED) therapist’s manual. Unpublished manuscript. Wilfley, D. E. (2015). Harnessing technology for training clinicians to deliver Interpersonal Psychotherapy (IPT). Paper presented at the National Eating Disorders Association Conference, San Diego, CA. Wilfley, D. E., Agras, W. S., Telch, C. F., Rossiter, E. M., Schneider, J. A., Cole, A. G.,  . . .  Raeburn, S. D. (1993). Group cognitive-​behavioral therapy and group interpersonal psychotherapy for the nonpurging bulimic individual:  a controlled comparison. Journal of Consulting and Clinical Psychology, 61, 296–​305. Wilfley, D. E., Dounchis, J. Z., & Welch, R. R. (2004). Interpersonal psychotherapy of anorexia nervosa. In K. M. Miller & J. S. Mizes (Eds.), Comparative treatment of eating disorders. New York, NY: Springer. Wilfley, D. E., Frank, M. A., Welch, R. R., Spurrell, E. B., & Rounsaville, B. J. (1998). Adapting interpersonal psychotherapy to a group format (IPT-​G) for binge eating disorder:  Toward a model for adapting empirically supported treatments. Psychotherapy Research, 8, 379–​391. Wilfley, D. E., MacKenzie, K. R., Welch, R. R., Ayres, V. E., & Weissman, M. M. (2000). Interpersonal psychotherapy for group. New York, NY: Basic Books. Wilfley, D. E., Pike, K. M., & Striegel-​Moore, R. H. (1997). Toward an integrated model of risk for binge eating disorder. Journal of Gender, Culture, and Health, 2, 1–​3. Wilfley, D. E., Stein, R. I., Saelens, B. E., Mockus, D. S., Matt, G. E., Hayden-​Wade, H. A.,   .  .  .  Epstein, L. H. (2007). Efficacy of maintenance treatment approaches for childhood overweight:  A  randomized controlled trial. Journal of the American Medical Association, 298, 1661–​1673. Wilfley, D. E., Stein, R. I., & Welch, R. R. (2005). Interpersonal psychotherapy. In J. Treasure, U. Schmidt, & E. van Furth (Eds.), The essential handbook of eating disorders (pp. 137–​ 154). West Sussex, UK: John Wiley & Sons. Wilfley, D. E., Welch, R. R., Stein, R. I., Spurrell, E. B., Cohen, L. R., Saelens, B. E.,  . . .  Matt, G. E. (2002). A randomized comparison of group cognitive-​behavioral therapy and group interpersonal psychotherapy for the treatment of overweight individuals with binge-​eating disorder. Archives of General Psychiatry, 59, 713–​721.

318

Interpersonal Psychotherapy

Wilfley, D. E., Wilson, G. T., & Agras, W. S. (2003). The clinical significance of binge eating disorder. International Journal of Eating Disorders, 34, S96–​S106. Wilfley, D. E., Wilson, G. T., & Agras, W. S. (2008). A multi-​ site randomized controlled trial of interpersonal psychotherapy, behavioral weight loss, and guided self-​help in the treatment of overweight individuals with binge eating disorder. Paper presented at the Eating Disorders Research Society. Wilfley, D. E., Wilson, G. T., Van Buren, D. J., Welch, R. R., Eichen, D. M., Proctor, E. K.,   .  .  .  Agras, W. S. (2016). Facilitating the dissemination and implementation of an evidence-​ based psychological treatment for eating disorders within college counseling centers. Paper presented at the Annual Meeting of the Eating Disorders Research Society, New York, NY. Wilson, G. T. (2005). Psychological treatment of eating disorders. Annual Review of Clinical Psychology, 1, 439–​465. doi:10.1146/​annurev.clinpsy.1.102803.144250 Wilson, G. T., & Fairburn, C. G. (2001). Eating disorders. In P. N.  J. Gorman (Ed.), Treatments that work. New  York, NY: Oxford University Press. Wilson, G. T., Grilo, C. M., & Vitousek, K. M. (2007). Psychological treatment of eating disorders. American Psychologist, 62, 199–​216. doi:10.1037/​0003-​066X.62.3.199 Wilson, G. T., & Shafran, R. (2005). Eating disorders guidelines from NICE. Lancet, 365(9453), 79–​81. doi:10.1016/​ S0140-​673617669-​1 Wilson, G. T., Wilfley, D. E., Agras, W. S., & Bryson, S. W. (2010). Psychological treatments of binge eating disorder. Archives of General Psychiatry, 67, 94–​101. doi:10.1001/​ archgenpsychiatry.2009.170 Wing, R. R., & Jeffery, R. W. (1999). Benefits of recruiting participants with friends and increasing social support for weight loss and maintenance. Journal of Consulting and Clinical Psychology, 67, 132–​138. Young, J. F., & Mufson, L. (2003). Manual for interpersonal psychotherapy-​adolescent skills training (IPT-​AST). New York, NY: Columbia University. Young, J. F., Mufson, L., & Davies, M. (2006). Efficacy of interpersonal psychotherapy-​ adolescent skills training:  An indicated preventive intervention for depression. Journal of Child Psychology and Psychiatry and Allied Disciplines, 47, 1254–​1262. Young, J. F., Mufson, L., & Schueler, C. M. (2016). Preventing adolescent depression:  Interpersonal psychotherapy—​adolescent skills training. New York, NY: Oxford University Press.



CH A PT E R

 Family Therapy for Eating Disorders

16

Daniel Le Grange and Renne Rienecke

Abstract Family therapy is increasingly recommended as the treatment of choice for eating disorders among adolescents. The shift from blaming parents for causing an ED to seeing them as a necessary part of the recovery process was set in motion by Salvador Minuchin and colleagues, and then reinforced and expanded on by researchers at the Maudsley Hospital in London, UK, and in the United States and Australia. Data supporting the efficacy of family therapy for adolescent anorexia nervosa has been solidified, while family-​based approaches in the treatment of adolescents with bulimia nervosa show promise. Further research is needed to replicate the findings of existing studies and to further clarify the utility of parental involvement in the treatment of older adolescents, or transition age youth, with anorexia nervosa and bulimia nervosa. Key Words:  adolescent, anorexia nervosa, bulimia nervosa, family-​based treatment, eating disorder

History of Family Therapy in Eating Disorders

More than 125  years ago the family was first considered to be at the center of eating disordered behavior. Views regarding the role of parents in anorexia nervosa (AN) varied from the outset. On the one hand, the British physician William Gull (1874) considered parents as “generally the worst attendants,” while the French physician Charles Lasegue (1883) took a more inclusive stance in emphasizing that the “preoccupations of relatives” are important. Another colleague in France, Jean-​Martin Charcot (1889), described the influence of parents as “particularly pernicious.” These early reflections suggest that parents were not seen as playing a positive role in their child’s illness. In fact, some clinicians went one step further by blaming parents for the eating disorder (ED). The turn of the century did not alter the outlook regarding parents’ role in ED treatment and/​ or development. In fact, the emergence of the term “parentectomy” as a popular concept in the 1940s solidified the exclusion of parents from treatment

for the next several decades. This sentiment was in vogue until the 1960s, at which time the role of the family was revisited in a more positive light by Salvador Minuchin and his colleagues at the Child Guidance Center in Philadelphia (Minuchin et al., 1975; Minuchin, Rosman, & Baker, 1978). This group developed what is referred to as the psychosomatic family model, a model that exerted considerable influence on subsequent treatment efforts for AN. This model hypothesized that an adolescent will develop an ED only when a very specific family context is in place. The psychosomatic model characterizes this family context as rigid, enmeshed, overinvolved, and conflict avoidant. These processes fluctuate in concert with the adolescent’s symptomatic behavior. For AN to develop, the adolescent should also present with a situational vulnerability, such as being given the role as a go-​between in cross-​ generational alliances. Markedly distinct from previously established ideology, Minuchin and colleagues did not simply ascribe responsibility or blame for the ED to the parents. Instead, the psychosomatic model highlighted the evolving, 319

interactive nature of the development of the illness. However, the authors did believe that the psychosomatic family was a necessary component for the development of an ED, and that treatment should aim to change the way the family functions. This view still falls short of completely absolving the parents of any blame. Researchers at the Institute of Psychiatry and the Maudsley Hospital in London (Dare, 1983; Dare & Eisler, 1997) furthered this shift in thinking about the role of families in EDs. Whereas the psychosomatic model described dysfunctional family characteristics that were thought to be necessary for the development of an ED, Dare and Eisler were more interested in the family dynamics that arise in the midst of, or as a result of, an ED. Rather than focusing on families’ missteps and transgressions, this team of researchers developed a family therapy approach that considers the parents as a resource and places less emphasis on the etiology of the ED (Eisler et al., 1997; Eisler et al., 2000; Le Grange, Eisler, Dare, & Russell, 1992; Russell, Szmukler, Dare, & Eisler, 1987). The body of work put forth by the Maudsley group has changed the emphasis in treatment from pathologizing families to absolving them from being blamed for causing their child’s ED. The approach still requires families to change, as steps initially taken by parents to address their child’s ED may have been ineffective or may require revision.

Theoretical Model of Family Therapy in Adolescent Eating Disorders

It is fair to say that over the past 40 years family therapy has gradually established itself as one of the most prominent treatment approaches for adolescents with AN. The clinical and theoretical accounts of some of the pioneers of the family therapy field, such as Minuchin and his colleagues (1975) and Selvini Palazzoli (1974), have been enhanced as increasing empirical support for the efficacy of family therapy for adolescents becomes available. Le Grange and Eisler (2009) would argue that this development has undoubtedly been one of the most significant changes in the treatment of EDs that the field has witnessed in the past 10 to 15 years. Eisler (2005), however, points out that although data for the efficacy of family therapy are mounting, quite ironically there has also been growing evidence of fundamental flaws in the theoretical models on which the treatment approach is based. For instance, the influential psychosomatic family model of Minuchin et  al. (1978) postulates a 320

prerequisite interactive family context within which the ED develops. A  modest number of studies (e.g., Dare, Le Grange, Eisler, & Rutherford, 1994; Humphrey, 1989) have embarked on a course to systematically test Minuchin’s claim of a psychosomatic family. Researchers have attempted to determine whether certain characteristics are specific to families of a child with AN, and, therefore, whether these families can be considered “typical” AN families. These studies were unable to confirm any particular pattern that typifies families with eating-​ disordered offspring. In addition, it remains unclear whether such characteristics, if they do exist, are present prior to the onset of the ED, or if they are instead more indicative of the family’s response to the illness. Thus, our current state of knowledge does not provide sufficient evidence for the existence of the psychosomatic family. Instead, there is growing evidence that families with an ED offspring are a heterogeneous group with respect to sociodemographic characteristics, the emotional climate of intrafamilial relationships, and the patterns of interactions within the family (Eisler, 2005). Moreover, families in which there is a member suffering with an ED do not change or respond to the ED in predictable ways. Thus, there is a need for further investigation to identify what the specific targets of effective family interventions should be, how these targets may differ between families, and what processes accompany any changes that may occur. The role of family environment in the etiology of EDs is also unclear. However, there is little doubt that the presence of an ED has an important effect on family life (Bara-​Carrill & Nielsen, 2003). As time passes, food, eating, and related concerns begin to saturate family life, resulting in compromised family routines, coping, and problem-​ solving behaviors (Eisler, 2005). A  similar process is described for families with an alcoholic member (Steinglass & Horan, 1988) and for families coping with a wide range of chronic illnesses (Steinglass, 1998). According to the model of Steinglass et al., families reorganize themselves in a stepwise fashion in response to the challenges brought about by the illness. This alters the family’s routines and decision-​making processes until such time that the illness becomes the central organizing principle of the family’s life. Typically, families in this position will attempt to minimize the impact of the illness on either the sufferer or on other family members, and as a consequence increasingly focus their attention on the present moment while losing sight of

Family Therapy for Eating Disorders

the larger familial context. When this occurs, it becomes difficult for the family to meet their changing developmental needs. Steinglass and colleagues’ model can easily be applied to EDs. It is common for families dealing with an ED to comment that it feels as if time has come to a standstill because they have had to focus all their attention on the ED. However, although there may be similarities in the way families respond to an ED, it is quite difficult, if not impossible, to disentangle which family processes are cause or effect, or just incidental to the development of the ED.

Family Therapy for Adolescent Anorexia Nervosa

The past 20 years have now seen about a dozen published randomized controlled trials (RCTs) for adolescent AN.

The Seminal Study of Family Therapy

The first and perhaps most influential RCT of family therapy for EDs was conducted by Russell and colleagues at the Maudsley Hospital in London (Russell et al., 1987). In this study, the relative efficacy of family therapy versus individual supportive therapy was tested. Eighty female participants (ages 14–​55 years) were first admitted for weight restoration to the inpatient program. Admission lasted an average of 10 weeks, after which patients were discharged and randomly allocated to 1 year of either family therapy or the control individual supportive therapy. Participants were divided into four subgroups based on diagnosis and/​or age, while outcome was defined by the Morgan/​Russell outcome criteria (see Russell et al., 1987, p. 8). Findings were inconclusive for those participants with AN whose illness had lasted more than 3 years, or for patients with a diagnosis of bulimia nervosa (BN). However, findings for patients in one subgroup favored family therapy. This subgroup comprised 21 adolescents with AN who had a relatively young age at onset (on or before 18 years) and a short duration of illness (< 3 years). At 5-​year follow-​up, adolescents in this same subgroup continued to do well, with 90% of those who had received family therapy meeting criteria for a good outcome (Eisler et  al., 1997). Adolescents who had received the individual control treatment did not do as well, with almost half of this group still presenting with significant ED symptoms after 5 years. This was the first long-​term follow-​up study to demonstrate that the benefits of a psychosocial treatment for AN could be maintained 5 years after the end of treatment.

Building on this RCT from Russell and his group (1987), three subsequent studies compared different forms of family interventions. An important difference from the original work is that the following studies tested outpatient family therapy without prior hospitalization.

Outpatient Treatment: Family Therapy Without Prior Hospitalization

The first of these three studies was also conducted at the Maudsley Hospital. Le Grange et al. (1992) and Eisler et al. (2000) compared two forms of outpatient family treatment—​ conjoint family therapy (CFT) and separated family therapy (SFT)—​among a total of 58 adolescents with AN. Both CFT and SFT shared the same goals, and the treatment principles were similar to the family therapy used in the original Russell et al. (1987) study. The two forms of treatment differed in their structure:  In SFT the same therapist meets first with the adolescent on her own and then meets separately with the parents, whereas in CFT the adolescent and the parents are seen together. Also, unlike CFT, SFT did not include a family meal as part of the treatment protocol. Overall, results were similar in that significant improvements were reported for patients whether they were assigned to the conjoint or separated forms of family therapy. Using Morgan/​Russell outcome criteria, the majority of participants (> 60%) were classified as having a good or intermediate outcome at the end of treatment. The authors found that CFT was superior to SFT in that significantly more change was demonstrated in terms of individual psychological and family functioning for participants in this treatment modality (Eisler et al., 2000). One important difference found between the treatment groups was that families with high levels of parental criticism toward their affected offspring (as defined by expressed emotion), did worse in CFT. Similar to the follow-​ up in the first RCT (Eisler et al., 1997), participants in this trial continued to improve after treatment ended. At 5-​year follow-​up, irrespective of type of family therapy received, the majority of participants had either a good (75%) or intermediate outcome (15%), while only 10% failed to respond to treatment (Eisler, Simic, Russell, & Dare, 2007).

The First Family Therapy Trial Outside the United Kingdom

The first family therapy treatment trial outside the United Kingdom was conducted by Robin, Siegal, Gilroy, Dennis, and Sikand (1999) in Le Grange, Rienecke

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Detroit. In this study, 38 adolescents with AN were randomly assigned to either behavioral family systems therapy (BFST), a treatment that shares several similarities with the Maudsley conjoint family therapy, or to ego-​oriented individual therapy (EOIT). The latter consisted of weekly individual sessions for the adolescent and bimonthly collateral sessions with the parents. The main goal of this treatment is to support the adolescent’s ability to resolve challenges through strengthening ego development rather than resorting to self-​starvation as an option. At post-​treatment, patients in both BFST and EOIT demonstrated significant improvements, in that the majority (67%) reached their target weight and 80% regained menstruation. Patients continued to improve after the conclusion of treatment. At 1-​ year follow-​ up, three-​ quarters of patients reached their target weight, and 85% reported regular periods (Robin et al., 1999). The authors found that BFST was superior to EOIT in terms of physiological improvements, that is, changes in weight and menses, at both post-​ treatment and follow-​up, but that changes were similar for patients in BFST and EOIT in terms of psychological improvements, that is, eating attitudes, mood, and eating-​related family conflict. Robin, Siegal, and Moyes (1995) also reported results of observational ratings of family interaction in a subsample of this study. In this investigation they demonstrated significant reductions in maternal negative communication and a corresponding increase in positive communication for families in BFST but not for those in EOIT. Some differences between the Detroit and Maudsley family therapy studies warrant comment, as these could have had some impact on outcome. First, patients in the Detroit study were hospitalized at the outset of treatment if percentage of ideal body weight (% IBW) was below 75 (≈ 50% of the sample). Such patients remained in inpatient treatment until they reached 80% IBW. Patients in the Maudsley studies (Eisler et  al., 2000; Le Grange et  al., 1992) were treated on an outpatient basis from the outset and were only admitted to the inpatient unit if they were unresponsive to outpatient efforts to gain weight (4 out of 58 patients were admitted to the inpatient service during the study). Second, in the Detroit study, patients received an average number of 30 treatment sessions over a period of 12 to 18 months. The duration and intensity of treatment were lower in the Maudsley studies, with patients receiving an average number of 10 322

sessions over a period of 6 to 12  months. Finally, patients in the Maudsley studies appeared to have been ill for longer, received more prior treatment, and had higher rates of comorbid depression.

Development of a Treatment Manual for Family Therapy

Other than the RCT of Robin et  al. (1999) for adolescent AN, family therapy treatment studies have been limited to the Maudsley group. One reason for the limited use of this helpful treatment approach has been the absence of a treatment manual. The recent development of a clinician manual of family therapy for adolescent AN (Lock & Le Grange, 2013) has not only made dissemination of this treatment approach possible, but also allowed for improvements in the design of subsequent treatment studies. The authors of the manual refer to this form of treatment as family-​based treatment for AN (FBT-​AN) and provide details of the goals and techniques of this treatment in the clinician’s manual (Lock & Le Grange, 2013). Briefly, FBT-​ AN consists of three treatment phases. The first phase focuses entirely on weight restoration, and control over this process is given to the parents. The second phase commences when the patient is approaching a healthy weight and the parents feel reassured that handing control over eating back to the adolescent will not result in renewed weight loss. The third phase is shorter in duration and consists of a brief overview of adolescent developmental issues and a discussion of how the adolescent can meet these developmental challenges without reverting to self-​ starvation as a coping mechanism. This family therapy approach has changed the therapeutic focus from the traditional exploration of the etiology of the disorder to exploring how and where a family has become stymied by the ED. The therapist also helps the family to identify their strengths in order to extricate themselves from the problem and explore potential solutions. Emphasizing that the family is a resource, and part of the solution rather than the problem, is the most crucial element of this family therapy. More traditional therapies place the emphasis on making changes within the family. While this is not the primary objective of the Maudsley group’s treatment, families may indeed learn during the course of therapy that there are ways in which they function as a family that they want to change. This change, however, is secondary to the primary goal, which is to help the child overcome the ED (Eisler, 2005).

Family Therapy for Eating Disorders

All of the studies described in the text that follows have employed this manualized version of family therapy1.

about one-​third of patients across treatments remitted at the 4-​year mark (Le Grange et al., 2014).

The Stanford Dosage Study

A French group, led by Godart, set out to investigate whether adding an adjunctive family therapy to treatment us usual (TAU) post hospitalization, would provide superior outcomes to TAU. The TAU included individual sessions for the patient as well as meetings with a psychiatrist for the patient and her parents. Sixty female adolescents were randomized to one of these two treatments and then followed up 18 months later (Godard et al., 2012). The main outcome for this RCT was defined as Good + Intermediate vs. Poor on the Morgan/​ Russell Outcome categories (see Russell et al., 1987, p. 8). At 18 months follow-​up, the authors demonstrated a significant main effect favoring the adjunctive family therapy over TAU.

The first study to use FBT-​AN was conducted by Lock and his colleagues (2005) at Stanford University in California. These authors examined the treatment dose of FBT-​ AN and randomly assigned 86 adolescents to either a 6-​month, 10-​ session version of this treatment, or to a 12-​month, 20-​session version. At the 1-​year mark there were no differences in weight gain between these two doses of FBT-​AN. However, some moderators of treatment were identified. The longer version of this treatment was more efficacious for those patients who came from single-​parent families, and for patients who presented with higher levels of eating-​related obsessions and compulsions. In what is now the third long-​term follow-​up study for this patient sample, Lock and his colleagues (2006) found that FBT-​ AN was equally effective regardless of treatment dose 4 years after the end of the study. That is, 66% of patients achieved healthy body weights (mean body mass index > 20.5) and had Eating Disorder Examination scores within the normal range.

Chicago/​Stanford Adolescent Focused Therapy Versus FBT Study

Following the dose study, Lock and Le Grange and their respective teams at Stanford and Chicago conducted a study where 121 adolescents with AN were randomized to either FBT or adolescent focused therapy (AFT) (EOIT, as noted in the Robin et al. study, was renamed AFT) (Lock et al., 2010). Patients were provided 12 months of outpatient therapy followed by 6-​and 12-​month post-​ treatment assessments. Defining remission in terms of recovery in weight and eating disorder cognitions, FBT was statistically superior to AFT at both the 6-​and 12-​month follow-​up. In an attempt to tease out which treatment may work best for which patients (moderators), the authors identified two moderators of treatment outcome, namely, ED psychopathology as measured by the EDE global score, and ED-​related obsessions and compulsions as measured by the YBC-​ED total score. For both moderators, FBT is favored over AFT when EDE and YBC-​ED are high, but there is no difference in treatment outcome across these two treatments when EDE and YBC-​ED are low (Le Grange et al., 2012). A 4-​year follow-​up shows that rates of remission were relatively stable for both groups, with

The French Study

The Sydney Study

Challenging the notion that patients typically benefit from long hospital stays until weight has been restored, Madden and colleagues allocated 82 medically unstable patients to one of two groups; inpatient weight restoration (to 90% IBW) followed by outpatient FBT (WR) versus inpatient stay until medically stable followed by outpatient FBT (MS) (Madden et al., 2015). The authors’ main hypothesis was upheld in that remission (defined in terms of improvements in both weight and eating disorder cognitions), as well as secondary clinical outcomes, was similar across the two treatment groups after 12  months of outpatient FBT. These findings underscore the notion that most medically unstable adolescents require relatively brief periods of inpatient stays provided the hospital treatment is followed by targeted behaviorally focused family treatment such as FBT.

Six-​Site Study of Family-​Based Therapy and Systemic Family Therapy

In the largest RCT of family therapy for adolescents, Agras and his colleagues randomized 167 patients across six sites in the United States and Canada to either FBT or systemic family therapy (SyFT) (Agras et al., 2014). Testing the hypothesis whether involving families in treatment (SyFT) is sufficient as opposed to the more behaviorally focused FBT that aims to support parents in weight restoration of their adolescent, patients were provided 9  months of outpatient treatment and followed up at 12  months post treatment. Defining Le Grange, Rienecke

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remission only in terms of improvement in weight, the authors found no differences between the treatments at the 12-​ month follow-​ up assessment. However, they demonstrated that FBT brought about weight recovery more expeditiously, with fewer patients in FBT hospitalized during outpatient treatment, and overall treatment costs were less in FBT than was the case for SyFT.

The Melbourne Study

The most recent RCT for this patient population was conducted at the Royal Children’s Hospital in Melbourne, Australia (Le Grange et  al., 2016). Adolescents (N  =  107) were randomized to FBT or parent focused therapy (PFT). This study replicates the earlier Eisler et al. (2000) and Le Grange et  al. (1992) studies, but amplifies the distinction between the two treatments; FBT is delivered in conjoint format, whereas PFT is designed such that the adolescent is only seen by a nurse therapist (10 minutes) to determine medical stability and mental status, and the full therapy hour is conducted by the therapist with only the parents in attendance. Treatment was delivered in 18 sessions over a 6-​ month period, followed by assessments at 6 and 12  months post treatment. In terms of remission, defined as recovery in weight and cognitions, PFT was statistically superior to FBT at the end of treatment, and although clinically superior at 6 months as well, the difference between the two treatment groups was no longer statistically significant at follow-​up. The findings amplify the results of the earlier Maudsley studies (Eisler et  al., 2000; Le Grange et al., 1992) in that delivering family therapy in a separated model (PFT) is at least as efficacious, perhaps even more efficacious, than conjoint FBT. A  less “cumbersome” version of FBT (e.g., there is no family meal in PFT and meetings are only with the parents), might be easier to disseminate and implement in community practice. Taken together, it is increasingly clear that parental involvement in the treatment of adolescents with AN is not only advisable, but perhaps a prerequisite, for recovery to occur. While a behaviorally focused form of family therapy, such as FBT, proves to be most advantageous for this patient population, more generic forms of family therapy, such as systemic family therapy, seem quite feasible as well.

Family Therapy for Adolescent Bulimia Nervosa

Until recently, treatment development for adolescents with BN had received almost no attention, 324

and in contrast to adolescent AN, working with families in the treatment of adolescents with BN has been much more limited. A recent advance has allowed for the development of family-​based treatment for bulimia nervosa (FBT-​BN) (Le Grange & Lock, 2007). This treatment was adapted from FBT-​AN (Lock & Le Grange, 2013), and like its precursor, FBT-​BN was designed for adolescents. Arguments in favor of parental involvement in treatment for adolescents with BN are both theoretically and clinically persuasive. As reviewed earlier in this chapter, a convincing body of evidence now supports mobilizing parents to take charge of weight restoration in the treatment of adolescents with AN. Further, researchers have found that the binge-​purge subtype of AN respond favorably to family therapy. In treatment studies for adolescent AN, where the binge-​purge subtype typically constitutes about 20% of cases, family therapy has been found to be equally effective for weight gain as for curtailing binge and purge episodes (Eisler et  al., 2000; Lock, Agras, Bryson, & Kraemer, 2005). These data seem to suggest that parents are able to both alleviate bulimic symptoms in their children and reverse severe dieting. Although modified from the approach for adolescents with AN, FBT-​BN shares many key characteristics with FBT-​AN. Most prominently, both treatments emphasize parents’ love and understanding of their child and encourage the family to promote behavioral change around eating. While BN in adolescence may be experienced as egodystonic, patients nevertheless tend to deny the alarming nature of their symptoms and are therefore mostly unable to appreciate the seriousness of BN. Unlike a sense of pride that often accompanies starvation in AN, binge and purge symptoms in BN can lead to heightened feelings of shame and guilt. Such feelings tend to isolate these adolescents from parental support, which in turn can reinforce the symptomatic behavior. However, FBT-​BN regards the parents as a resource for resolving the ED, and attempts to alleviate misplaced blame that may be directed toward either the parents or the adolescent. In most instances, the adolescent suffering from BN is unable to recognize or effectively manage their dysfunctional eating behaviors. Consequently, the parents are encouraged to assist their adolescent in bringing about the necessary behavioral changes that will lead to recovery. Robin and colleagues (1999) conceptualize the teenager with AN as “unable to take care of herself.” If the adolescent with BN is defined in the same way, then the parents should be

Family Therapy for Eating Disorders

coached to work as a team with their offspring to develop ways to restore healthy eating. This collaborative effort between the adolescent and her parents shows respect and regard for the adolescent’s point of view and experience. Because of this collaborative stance, information about ED symptoms is shared between the parents and the adolescent in order to address struggles around eating and to understand the impact of the disorder on family relationships. The FBT-​BN does not delve into the possible causes of BN and is instead primarily focused on the ED symptoms. In other words, this treatment focuses on what can be done to resolve the disorder. Also, FBT-​ BN assumes that both parental guilt about having possibly caused the illness and anxiety about how best to address the symptomatic behavior serve to disable parents in their efforts. Consequently, a primary goal of treatment is to empower the parents and the adolescent in their collaborative attempts to disrupt the ED behaviors. Another important goal of treatment is to externalize the disordered behaviors from the affected adolescent. This separation of the adolescent from the disorder serves to promote parental action and decrease adolescent resistance to their assistance. Once these goals have been accomplished, the parents’ next task is to return control over eating to the adolescent in a way that is age appropriate; that is, control over eating may be different for a 12-​year-​ old versus an 18-​year-​old. Siblings are encouraged to play a supportive role only, and are therefore sheltered from the job assigned to the parents. Once the ED symptoms have resolved and the patient is eating on her own in an age-​appropriate way, parents will then assist her in negotiating predictable adolescent developmental tasks. The therapist aims to take a nondirective stance throughout treatment and in doing so joins the family as a consultant and sounding board, while decision-​making is left to the parents. This strategy facilitates parental ownership of decisions made in treatment and further promotes their empowerment. The FBT-​BN differs from FBT-​AN in a number of key ways. In family treatment for BN, (1) the emphasis is on regulating eating and curtailing purging as opposed to weight restoration; (2) treatment follows an approach that supports a collaborative effort between the adolescent and her/​his parents in addressing the ED, whereas in AN parents take charge of weight restoration; (3) the secretive nature, guilt, and shame typically associated with BN may make it more of a challenge for the family and therapist to remain symptom focused,

whereas the emaciation experienced in AN makes it relatively easier to keep treatment focused on weight restoration; and (4) the therapist and parents have to confront the challenges of comorbid illnesses in BN, which can more readily derail treatment than is usually the case in AN.

Studies of Family-​Based Treatment for Adolescent Bulimia Nervosa

As noted earlier, data in support of treatments for adolescents with BN are sparse. Family therapy was first applied to adolescents with BN in a small case series that was conducted by the Maudsley group (Dodge, Hodes, Eisler, & Dare, 1995). This study demonstrated significant reductions in bulimic behaviors through educating the family about the ED and helping the parents to disrupt binge eating and purging episodes. Following the case series by Dodge and her colleagues (1995), Le Grange and his colleagues (2003) provided a detailed description of an adolescent progressing in FBT-​BN. Both of these studies suggested that families can play a positive role in the recovery of adolescent BN, and that this is a promising avenue to pursue in the treatment for this population. These preliminary findings were recently extended with the publication of the first RCTs for adolescents with BN; all three studies using family treatments in their design (Le Grange, Crosby, Rathouz, & Leventhal, 2007; Le Grange, Lock, Agras, Bryson, & Jo, 2015; Schmidt et al., 2007). In the Le Grange et al. (2007) study, 80 patients with DSM-​IV BN and partial BN, ranging in age from 12 to 19 years (mean age = 16.1 years; mean duration of illness  =  20.6  months), were assigned to either FBT-​BN (n  =  41) or to individual supportive psychotherapy (SPT) (n = 39). Both treatments provided 20 therapy sessions over a 6-​month period with assessments at four time points:  baseline, mid-​treatment, end of treatment, and 6-​month follow-​up. There was no difference in adherence to treatment across FBT-​BN and SPT, with only 11% of patients dropping out of therapy prematurely. In terms of categorical outcomes, FBT-​BN demonstrated a clinical and statistical advantage over SPT at the end of treatment as well as at 6-​month follow-​up. At the end of treatment, significantly more patients in FBT-​ BN (39%) than in SPT (18%) were binge and purge abstinent. Abstinence rates were not as high at 6-​ month follow-​ up; however, significantly more patients in FBT-​ BN (29%) were binge and purge free compared to SPT (10%). Using random regression models, secondary Le Grange, Rienecke

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analyses of continuous outcome variables showed greater improvements for FBT-​BN on behavioral and attitudinal measures of ED psychopathology. Core bulimic symptoms also showed a more rapid rate of improvement for FBT-​BN. Taken together, these findings support the superiority of FBT-​BN over SPT in terms of the behavioral as well as attitudinal aspects of BN. The Le Grange RCT also explored nonspecific predictors, moderators, and mediators of outcome (Ciao, Accurso, Fitzsimmons-​Craft, & Le Grange, 2015; Le Grange et  al., 2008; Lock, Le Grange, & Crosby, 2008). The clearest predictor to emerge from these analyses was level of eating concern as measured by the Eating Disorder Examination (EDE). That is, patients with lower scores on the EDE Eating Concern subscale at baseline were more likely to have remitted (abstinence from both binge eating and purging) at the end of treatment and at follow-​up, regardless of which treatment they received. Four EDE variables (Weight Concern, Shape Concern, Eating Concern, and Global Score) significantly moderated the effects of treatment on partial remission status (no longer meeting study entry criteria). That is, partial remission rates were much higher for FBT-​BN participants with low EDE scores. For participants receiving SPT, rates of partial remission were similar regardless of EDE scores. As for mediators, changes in the EDE Restraint subscale score at mid-​treatment may mediate outcome for FBT-​BN, but not for SPT (Lock et  al., 2008), suggesting that FBT-​BN may exert its effects in part by changing disordered thinking. A study examining predictors of psychological change (Ciao et  al., 2015) found that adolescents taking psychotropic medications at baseline improved more quickly on the Eating Concerns subscale than adolescents not on medication. For patients in SPT, older adolescents showed faster reductions on the Eating Concerns subscale than younger adolescents. In addition, patients reporting a higher purge frequency at baseline showed faster improvement on the Eating Concerns subscale if they received FBT versus SPT. Finally, older adolescents reported faster improvement in self-​esteem compared to younger adolescents. Generally, few differences between treatments were found, suggesting that FBT and SPT were both effective in bringing about improvement in psychological symptoms for patients. These findings remain exploratory and a more detailed examination of these constructs awaits further testing in future controlled studies. 326

In the Schmidt and colleagues (2007) RCT, family therapy (n = 41) was compared to cognitive-​ behavioral therapy guided self-​care (n = 44) (CBT-​ GSC). Participants included adolescents and young adults ages 12 to 20 years (mean age = 17.6 years) meeting DSM-​IV criteria for BN or ED not otherwise specified (EDNOS). In terms of categorical outcomes, significantly more patients in CBT-​GSC were abstinent from binge eating at the end of treatment compared with patients receiving family therapy; however, this difference was no longer significant at 6-​month follow-​up. There were no differences in vomiting between the two treatment groups. Combining abstinence from binge eating and vomiting, there were no significant differences between family therapy (12.5%) and CBT-​GSC (19.4%) at the end of treatment or at 6-​month follow-​up (family therapy  =  41.4% vs. CBT-​GSC  =  36%). The only other differences reported were the direct cost of treatment, which was lower for CBT-​GSC. Schmidt and colleagues acknowledge that their sample size might have been too modest to detect differences between two active treatments. Further, they state that without a waiting-​list or attention placebo-​control group it would be difficult to rule out that improvement was simply due to nonspecific effects or the passage of time. Although no published manual is available for the family therapy used by Schmidt and her colleagues (2007), it appears to closely resemble FBT-​ BN. One key difference is that “family” was defined in family therapy as any “close other,” rather than restricting this definition to a parent or legal guardian. Twenty-​five percent of all participants used a “close other” in their treatment. The rationale for defining family in this way was likely due to the fact that the mean age of participants was at the upper end of adolescence (17.6 years), well above the age of consent in the United Kingdom (16 years of age). However, this definition of family might not be the most effective way to approach family-​based treatments with younger adolescents who are still legally dependent on parents. Notwithstanding these uncertainties, the abstinence rate for family therapy in Schmidt’s study was comparable to that achieved using FBT-​BN in Le Grange et al.’s 2007 study. In the largest RCT of adolescents with BN, 109 participants with DSM-​IV BN or partial BN received either CBT adapted for adolescents (CBT-​ A) (n = 58) or FBT-​BN (n = 51) (Le Grange et al., 2015). Participants were between the ages of 12 and 18 with a mean age of 15.8 years and an average duration of illness of 18.9 months. Treatments

Family Therapy for Eating Disorders

consisted of 18 sessions over 6 months, and assessments were conducted at baseline, end-​of-​treatment, and 6-​and 12-​month follow-​up. The primary outcome variable was abstinence from binge eating and purging over the previous 4 weeks. Abstinence rates were significantly higher for patients receiving FBT-​ BN at end of treatment (39.4%, versus 19.7% for CBT-​A) and at 6-​month follow-​up (44.0%, versus 25.4% for CBT-​A), although differences between treatment groups were no longer significant at 12-​ month follow-​up (FBT = 48.5%; CBT = 32.0%). The FBT-​BN was more effective in preventing hospitalization, with 2% requiring hospitalization during the study period, as opposed to 21% of patients receiving CBT-​A. An examination of moderators of treatment found that participants with lower levels of family conflict did better in FBT-​BN than CBT-​ A. The study suggests that FBT-​BN brings about symptom improvement more rapidly than CBT-​A, although both treatments are viable options for this patient population. Some questions require consideration when we examine issues pertaining to the dissemination of family-​based treatments for this patient population. For instance, a treatment that involves the family may not always be suitable, especially in older adolescents. For instance, 28% of eligible participants in Schmidt’s study refused participation because they did not want their families involved in treatment. The CBT-​GSC appeared to present fewer barriers, as fewer patients refused to participate. Further, patients fared as well in CBT-​GSC as they did in family therapy (Schmidt’s study) or FBT-​BN (Le Grange’s studies). Delivering CBT-​GSC was also more cost-​efficient than was the case for family therapy, which only serves to underscore the need for further evaluation of effective treatments given that treatment studies for adolescents with BN are still in their infancy. Collectively these results support the use of FBT-​ BN as an effective intervention for adolescents who are identified early in the course of their illness, before the degree of psychopathology reaches levels that might be less responsive to treatment. Thus CBT is clearly a viable alternative treatment for this patient population.

Acceptability of Family Therapy

Three studies have examined the acceptability of family therapy for adolescents with AN (Krautter & Lock, 2004; Le Grange & Gelman, 1998; Turkiewicz, Pinzon, Lock, & Fleitlich-​Bilyk, 2010), and one study has been published regarding

adolescents with BN (Zaitsoff et al., 2008). Family therapy that empowers parents to play a significant role in addressing their offspring’s ED is highly demanding, in part because the adolescent is initially not allowed to make independent decisions about her eating and weight-​ related behaviors, and may be quite resistant to her parents’ efforts. Therefore, the question of how acceptable this treatment is for both adolescents and parents is particularly salient. The initial report, a qualitative description of family therapy in a modest sample of adolescents with AN (Le Grange & Gelman, 1998), supported the notion that this form of treatment was ultimately acceptable for adolescents and their families. A larger study of patient satisfaction in family therapy for AN, employing both quantitative and qualitative evaluations, provided additional empirical support for this notion (Krautter & Lock, 2004). These authors found that adolescents and their parents rated treatment effectiveness as well as therapeutic alliance quite highly. However, it should be noted that almost a third (30%) expressed a desire for individual therapy in addition to the family therapy they received. A  small study of FBT in Brazil found that the treatment approach was acceptable and feasible for families (Turkiewicz et al., 2010). In adolescents with BN, therapeutic alliance and treatment acceptability were high for both FBT-​BN and SPT and did not differ between the two treatments (Zaitsoff et al., 2008).

Multifamily Therapy for Adolescent Anorexia Nervosa

Given the success of family-​based treatments for adolescents with EDs, in conjunction with the need for more concentrated forms of interventions for those cases who do not respond to outpatient work, multiple-​family day treatment programs have been developed in Dresden, Germany (Scholz & Asen, 2001) and in London, UK (Dare & Eisler, 2000). Multiple-​family day treatment for EDs builds on the effectiveness of treatment formats for family intervention with other serious disorders (e.g., schizophrenia). It uses the same general principles of parental empowerment while focusing only on the specific problems related to AN as used in the approach for single families described in the preceding text. Doing multiple-​family day treatment requires families to meet together for an extended weekend. During this time, a supportive community is created that aims to absolve families of any blame and provide opportunities to experiment with Le Grange, Rienecke

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behavioral change. Not only are expert consultants available but also this treatment format is an opportunity to share experiences with other families that are confronted with similar challenges. Realizing that one’s struggles are quite similar to those of other families allows for an intensive learning environment under relatively controlled and supportive conditions. After the initial extended weekend, meetings over the ensuing months occur in a group format for a single day. The goal of these meetings is for families to help each other with the dilemmas that AN presents to their families. In practice, single-​family sessions are also provided for families who participate in multiple-​family day treatment. Providing treatment in this way, multiple-​family day treatment may best be considered an attempt to boost the efficacy of single-​family therapy for more resistant or challenging cases (Le Grange & Eisler, 2009). Preliminary results from the research groups in London and Dresden are promising. As has been the case in the studies of family therapy for both AN and BN, treatment retention has been high for both sites. Feedback from parents and a majority of patients (80%) in Dresden indicated that working together with other families in a day hospital setting was experienced as helpful and desirable (Scholz & Asen, 2001). In particular, parents reported that the experience was helpful because of the collaborative nature of the program and the opportunity to share ideas with other families about how to cope with their common predicament. A qualitative study of patients and parents receiving MFT found that the majority felt it to be a positive experience (Voriadaki, Simic, Espie, & Eisler, 2015). Participants reported gaining better insight into the eating disorder. Adolescents reported enhanced motivation for recovery, and parents reported an improvement in self-​efficacy and family communication. Several uncontrolled studies have found improvements in weight and other measures of ED symptomatology. A retrospective chart review comparing 25 patients who received multiple family therapy (MFT) and treatment as usual (TAU) to 25 patients receiving only TAU, found that patients in both groups successfully gained weight, but patients receiving MFT reached a significantly higher % IBW (99.6% IBW) compared with patients receiving only TAU (95.4% IBW) (Gabel, Pinhas, Eisler, Katzman, & Heinmaa, 2014). A small study of 20 adolescent females with AN (n = 8) or EDNOS-​AN (n = 12) receiving MFT found significant improvements in body mass index, restriction, eating 328

concerns, weight concerns, and amount of exercise from pre-​to post-​treatment (Hollesen, Clausen, & Rokkedal, 2013). In addition, participants reported improvement on the drive for thinness and interoceptive awareness subscales of the Eating Disorder Inventory (EDI). Salaminiou, Campbell, Simic, Kuipers, & Eisler (in press) conducted an open trial of 30 families participating in MFT. Patients had diagnoses of AN (n = 27) or EDNOS (n = 3). Assessments were conducted at baseline and after 3 and 6  months into treatment. Patients’ weight improved significantly over time, as did scores on the Beck Depression Inventory, Rosenberg Self-​Esteem Scale, and several subscales of the Eating Disorder Inventory. Mothers’ scores on the Beck Depression Inventory also improved. In addition, dropout rates were low (n  =  2), and adolescents reported their satisfaction with the treatment as moderate, whereas both mothers and fathers rated their satisfaction as high. One barrier to receiving evidence-​based treatments for eating disorders is access to the limited number of providers and institutions that offer treatments such as MFT. Intensive treatment options offered over a short period of time may be a feasible option for families who do not have local access to specialized treatments. Rockwell, Boutelle, Trunko, Jacobs, & Kaye (2011) reported on outcomes for 19 patients participating in a 5-​day intensive family therapy program (IFT). The IFT incorporates FBT principles while also offering components of other forms of therapy, such as SyFT and CBT. Participants successfully gained weight, and all but one reported sustained weight gain at follow-​up, approximately 9 months after finishing IFT. A larger study of 74 adolescents compared families receiving single-​family IFT (S-​IFT) (n  =  20) to families receiving a multi-​family intensive family therapy (M-​ IFT) (n  =  54) (Marzola et  al., 2015). Participants met criteria for AN (n  =  44) or EDNOS-​restricting type (n = 30) and were followed up an average of 53.4 months after participating in S-​IFT or 22.5 months after receiving M-​IFT. The primary outcome variable was full remission, defined as reaching at least 95% of expected body weight (EBW), having scores on the Eating Disorder Examination-​Questionnaire (EDE-​Q) within 1 SD of community norms, and absence of binge eating or purging behaviors in the previous 28  days. Partial remission was defined as reaching at least 85% EBW, or being above 95% EBW but with an elevated global score on the EDE-​Q and the presence of binge eating or purging less than

Family Therapy for Eating Disorders

once per week. The majority of patients achieved either full (n  =  45) or partial (n  =  20) remission, and 91.1% reported IFT to be useful. No differences were found in treatment outcome for those who received S-​IFT versus M-​IFT. However, the majority of patients received some form of treatment after IFT, limiting the conclusions that can be drawn about the efficacy of the interventions. These results suggest that multiple-​ family day treatment is acceptable to families and a feasible treatment for further study. Larger controlled research studies are needed to further investigate the efficacy of MFT.

Family Therapy for Adults with Eating Disorders

Family-​ based treatment has recently been adapted for use with transition age youth (ages 17–​ 26) and young adults with anorexia nervosa and bulimia nervosa.

Family Therapy for Adults with Anorexia Nervosa

Compared to the adolescent literature, family therapy for adults with AN has received much less attention. Only two published studies have tested the efficacy of family therapy for adults, both conducted at the Maudsley Hospital (Dare, Eisler, Russell, Treasure, & Dodge, 2001; Russell et al., 1987). Russell and colleagues’ (1987) study, described in some detail earlier in this chapter, was the first to investigate family therapy for adults with AN. This was the first RCT of family therapy involving adult AN patients (n = 36, mean age at start of treatment  =  20.6  years). Participants were randomly assigned to either family therapy or a control individual therapy at the time that they were discharged from the hospital. Unlike the findings for adolescents with AN, family therapy showed no benefit over individual therapy for adults. In fact, in terms of weight gain, there was a trend in favor of individual therapy for those patients with an adult onset (mean age at onset = 24.6 years) as opposed to those with an early onset (mean age at onset = 14.3 years), although this trend had dissipated at 5-​year follow-​up. However, at follow-​up adult patients in individual therapy scored higher in terms of psychological adjustment (based on Morgan/​Russell outcome criteria) compared with patients in family therapy (Eisler et al., 1997). The second study of family therapy for adults with AN was administered on an outpatient basis only (Dare et  al., 2001). This RCT of 84 adult

patients was designed to assess the relative effectiveness of three specific psychotherapies—​family therapy, focal psychoanalytic psychotherapy, and cognitive analytic therapy—​versus routine care. At the end of treatment, no differences in outcome were reported for the three specific treatments. However, patients in family therapy and focal psychotherapy showed modest symptomatic improvements that were superior to the control treatment. Findings from this study were inconclusive perhaps in part because it was insufficiently powered to detect differential therapeutic effects. Moreover, no treatment manuals were used. Recently FBT has been adapted for use with transition age youth (Chen et al., 2010; Chen et al., 2016; Dimitropoulos, Herschman, Toulany, & Steinegger, 2016; Dimitropoulos, Lock, Le Grange, & Anderson, 2015). The transition to financial independence is taking longer than in previous generations (Gutmann, Pullum-​Pinon, & Pullum, 2002), leaving young persons dependent on their parents for longer, and leaving parents to continue playing a large and influential role in their young adult children’s lives. Consequently, transition age youth refers to young persons who may be experiencing significant life transitions such as individuating from their family of origin, going away to college, or transferring from pediatric to adult healthcare systems. Thus, adapting FBT for transition age youth would appear to be a promising intervention for a patient population that is difficult to treat. In a case study of four patients with AN, participants received 11–​20 treatment sessions over 6 to 12  months (Chen et  al., 2010). Assessments were conducted at baseline, end-​ of-​ treatment, and 6-​ month follow-​ up. Participants generally showed improvement in body mass index, scores on the EDE, global assessment of functioning, and the Beck Depression Inventory, and most found the treatment to be acceptable. An open trial assessed FBT in 22 adult females with AN (n = 10) or EDNOS-​AN (n  =  12) between the ages of 18 and 26 (Chen et  al., 2016). Participants received an average of 12 therapy sessions over 17 weeks, with assessments at baseline, mid-​treatment, end-​ of-​ treatment, and 6-​and 12-​ month follow-​ up. Improvements were found in body mass index, EDE global score, eating-​ related obsessions and compulsions, global assessment of functioning, and presence of comorbid Axis I disorders. In another study, FBT has also been adapted for use with transition age youth (FBT-​ TAY; Dimitropoulos et  al., 2015). Interviews with 15 Le Grange, Rienecke

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transition age youths with EDs revealed that they wanted continued support from their parents during this transitional period, and expressed a desire for that support to be of a collaborative nature as they continue to grow more autonomous (Dimitropoulos et al., 2016). Accordingly, adaptations made to FBT-​TAY include a longer course of treatment (about 25 sessions), a more collaborative therapeutic approach, more individual time in sessions with the patient prior to bringing in the rest of the family, and at times using more insight-​oriented examples to explain the concept of externalization of the illness from the patient. In addition, therapists direct the urgency of the situation toward both the parents and the young adult rather than primarily toward the parents, as is done in FBT with adolescents. Finally, therapists move patients through phase 2 more quickly to provide them with more time to practice eating independently, and spend more time on relapse prevention in phase 3, discussing with the patient how to prevent slips or relapses when living independently (Dimitropoulos et al., 2015). Taking these studies together, it would be difficult to draw a definitive conclusion about the efficacy of family therapy for transition age youth and adults. Further studies are clearly required to establish whether family therapy can be helpful for this patient population, although adaptations of FBT for transition age youth seems promising.

Family Therapy for Adults with Bulimia Nervosa

Family therapy has received the least amount of attention among adults with BN. A few studies have described single cases of family therapy for this age group (Madanas 1981; Roberto 1986; Root, Fallon, & Friedrich, 1986; Wynne 1980), and two larger studies have provided clear accounts of this treatment (Russell et  al., 1987; Schwartz, Barrett, & Saba, 1985). Findings from these studies were inconclusive, and it remains unclear whether family therapy is helpful for this patient population.

Conclusion

Despite a historical bias against the involvement of parents in the treatment of adolescents with EDs (Silverman, 1997), evidence in support of family interventions for AN has continued to mount over the past 40 years (Le Grange & Eisler, 2009). The published controlled studies involving adolescents with AN suggest that outpatient family therapy can 330

be quite effective. Based on the data currently available, more than two-​thirds of adolescent patients are successful in reaching a healthy weight by the end of treatment, and 80% will have further improved or remained recovered 5 years later (Eisler et al., 1997; Eisler et  al., 2007; Le Grange et  al., 2014; Lock, Couturier, & Agras, 2006). Although data have accumulated on the efficacy of FBT-​AN, the state of research on the treatment for adolescents with BN has lagged behind. However, results from the first three published RCTs suggest that parents can be helpful not only in restoring their child’s weight but also in supporting their child in decreasing binge eating and purging (Le Grange et al., 2007; Le Grange et al., 2015; Schmidt et al., 2007). Taken together, these results for adolescents with EDs are encouraging, but must be interpreted cautiously as replication is needed with larger sample sizes. This task may now be more readily accomplished with the manualization of both FBT-​ AN (Lock & Le Grange, 2013) and FBT-​BN (Le Grange & Lock, 2007). Another reason for cautious interpretation is the fact that the same form of family therapy was not consistently used across the studies described in this chapter. Nevertheless, treatments that encourage parents to take an active role in helping their child recover from an ED, rather than observing from the sidelines, appear to be promising interventions for adolescents with a short duration of illness who are medically suitable for outpatient treatment. Treatment studies for transition age youth and adults with AN are sorely needed, as the disorder seems to become more resistant to treatment over time. The lack of effective treatments for older age groups is especially alarming given the severe consequences of chronicity and the high mortality rate associated with AN (Crow et  al., 2009; Touyz & Hay, 2015). Despite the still significant gaps in our knowledge, FBT is only one exciting example of the enormous strides made in the field of ED treatment in the last 20 years.

Future Directions

Enthusiasm for FBT ought to be tempered by the fact that there is a dearth of research on other treatment approaches for adolescents with an ED. For example, in AN there are only three published studies comparing either EOIT/​AFT or treatment as usual with family therapy, while cognitive, interpersonal, and psychodynamic treatment approaches have not been systematically evaluated.

Family Therapy for Eating Disorders

The utility of individual procedural elements of FBT has not been sufficiently examined. Dismantling studies can highlight which part(s) of FBT are necessary and which part(s) might be superfluous. For instance, the therapeutic value of the family meal that is typically implemented early on in this treatment has not been determined (c.f. Le Grange et al., 2016; Lock et al., 2015). Likewise, the relative usefulness of phases two and three of FBT as opposed to the first phase of this treatment is not known (Lock et al., 2005). Matching patients and treatment modality is another challenge that requires attention. Although some advances in terms of treatment moderators have been noted (Le Grange et  al., 2008; Le Grange et al., 2012; Le Grange et al., 2016), there is little to guide clinicians who are attempting to determine the appropriateness of FBT for one family compared to another. Even less is known about the mechanisms of change in FBT (c.f. Byrne, Accurso, Arnow, Lock, & Le Grange, 2015; Lock et al., 2015). Finally, the uptake and implementation of manualized treatments among many clinicians in the community are often less than satisfactory (c.f. Accurso et al., under review; Couturier & Kimber, 2015). However, the development of published clinician manuals for both FBT-​AN and FBT-​BN provides an opportunity for the examination of effective dissemination of these treatment modalities.

Note

1. The Maudsley group has recently published a detailed manual describing family therapy for adolescent AN: http://​www. national.slam.nhs.uk/​services/​camhs/​camhs-​eatingdisorders/​ resources/​

References

Agras, W. S., Lock, J., Brandt, H., Bryson, S. W., Dodge, E., Halmi, K. A.,  . . .  Woodside B. (2014). Comparison of 2 family therapies for adolescent anorexia nervosa: a randomized parallel trial. JAMA Psychiatry, 71, 1279–​1286. Bara-​Carril, N., & Nielsen, S. (2003). Family, burden of care and social consequences. In J. L. Treasure, U. Schmidt, & E. van Furth (Eds.), Handbook of eating disorders (pp. 191–​206). Chichester, UK: Wiley. Byrne, C. E., Accurso, E. C., Arnow, K. D., Lock, J., & Le Grange, D. (2015). An exploratory examination of patient and parental self-​efficacy as predictors of weight gain in adolescent AN. International Journal of Eating Disorders, 48, 883–​888. Charcot, J. M., (1889). Lecture XVII: Isolation in the treatment of hysteria. Clinical lectures on the diseases of the nervous system delivered at the infirmary of la Salpetriere by Professor J. M. Charcot. (T. Savill, Trans.). London, UK: New Sydenham Society. Chen, E. Y., Le Grange, D., Doyle, A. C., Zaitsoff, S., Doyle, P., Roehrig, J. P., & Washington, B. (2010). A case series

of family-​ based therapy for weight restoration in young adults with AN. Journal of Contemporary Psychotherapy, 40, 219–​224. Chen, E. Y., Weissman, J. A., Zeffiro, T. A., Yiu, A., Eneva, K. T., Arlt, J. M., & Swantek, M. J. (2016). Family-​based therapy for young adults with AN restores weight. International Journal of Eating Disorders, 49, 701–​707. Ciao, A. C., Accurso, E. C., Fitzsimmons-​Craft, E. E., & Le Grange, D. (2015). Predictors and moderators of psychological changes during the treatment of adolescent bulimia nervosa. Behaviour Research and Therapy, 69, 48–​53. Couturier, J. L., & Kimber, M. S. (2015). Dissemination and implementation of manualized family-​ based treatment: A systematic review. Eating Disorders, 23, 281–​290. Crow, S. J., Peterson, C. B., Swanson, S. A., Raymond, N. C., Specker, S., Eckert, E. D., & Mitchell, J. E. (2009). Increased mortality in bulimia nervosa and other eating disorders. American Journal of Psychiatry, 166, 1342–​6134. Dare, C. (1983). Family therapy for families containing an anorectic youngster. Columbus, OH, IVth Ross Conference on Medical Research, Ross Laboratories: 28–​37. Dare, C., & Eisler, I. (1997). Family therapy for AN. In D. M. Garner & P. Garfinkel (Eds.), Handbook of treatment for eating disorders (pp. 307–​324). New York, NY: Guilford Press. Dare, C., & Eisler, I. (2000). A multi-​family group day treatment programme for adolescent eating disorders. European Eating Disorders Review, 8, 4–​18. Dare, C., Eisler, I., Russell, G., Treasure, J., & Dodge, L. (2001). Psychological therapies for adults with AN:  Randomized controlled trial of outpatient treatments. British Journal of Psychiatry, 178, 216–​221. Dare, C., Le Grange, D., Eisler, I., & Rutherford, J. (1994). Redefining the psychosomatic family:  Family process of 26 eating disorder families. International Journal of Eating Disorders, 16, 211–​226. Dimitropoulos, G., Freeman, V. E., Allemang, B., Couturier, J., McVey, G., Lock, J., & Le Grange, D. (2015). Family-​based treatment with transition age youth with AN: A qualitative summary of application in clinical practice. Journal of Eating Disorders, 3. doi: 10.1186/​s40337-​015-​0037-​3 Dimitropoulos, G., Herschman, J., Toulany, A., & Steinegger, C. (2016). A qualitative study on the challenges associated with accepting familial support from the perspective of transition-​age youth with eating disorders. Eating Disorders, 24, 255–​270. Dimitropoulos, G., Lock, J., Le Grange, D., & Anderson, K. (2015). Family therapy for transition youth. In K. L. Loeb, D. Le Grange, & J. Lock (Eds.), Family therapy for adolescent eating and weight disorders: New applications (pp. 230–​255). New York, NY: Routledge. Dodge, E., Hodes, M., Eisler, I., & Dare, C. (1995). Family therapy for bulimia nervosa in adolescents:  An exploratory study. Journal of Family Therapy, 17, 59–​77. Eisler, I. (2005). The empirical and theoretical base of family therapy and multiple family day therapy for adolescent anorexia nervosa. Journal of Family Therapy, 27, 104–​131. Eisler, I., Dare, C., Hodes, M., Russell, G., Dodge, E., & Le Grange, D. (2000). Family therapy for adolescent anorexia nervosa: The results of a controlled comparison of two family interventions. Journal of Child Psychology and Psychiatry, 41, 727–​736. Eisler, I., Dare, C., Russell, G. F. M., Szmukler, G. I., Le Grange, D., & Dodge, E. (1997). Family and individual therapy in

Le Grange, Rienecke

331

anorexia nervosa:  A  five-​year follow-​up. Archives of General Psychiatry, 54, 1025–​1030. Eisler, I., Simic, M., Russell, G. F. M., & Dare, C. (2007). A randomized controlled treatment trial of two forms of family therapy in adolescent anorexia nervosa:  A  five-​year follow-​up. Journal of Child Psychology and Psychiatry, 48, 552–​560. Gabel, K., Pinhas, L., Eisler, I., Katzman, D., & Heinmaa, M. (2014). The effect of multiple family therapy on weight gain in adolescents with anorexia nervosa:  Pilot data. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 23, 196–​199. Godart, N., Berthoz, S., Curt, F., Perdereau, F., Rein, Z., Wallier, J.,  . . .  Jeammet, P. (2012). A randomized controlled trial of adjunctive family therapy and treatment as usual following inpatient treatment for anorexia nervosa adolescents. PloS ONE, 7, e28249. doi:10.1371/​journal.pone.0028249 Gull, W. (1874). Anorexia nervosa (apepsia hysterica, anorexia hysterica). Transactions of the Clinical Society of London, 7, 222–​228. Gutmann, M. P., Pullum-​Pinon, S. M., & Pullum, T. W. (2002). Three eras of young adults home leaving in twentieth-​century America. Journal of Social History, 35, 533–​576. Hollesen, A., Clausen, L., & Rokkedal, K. (2013). Multiple family therapy for adolescents with anorexia nervosa:  A  pilot study of eating disorder symptoms and interpersonal functioning. Journal of Family Therapy, 35, 53–​67. Humphrey, L. (1989). Observed family interactions among subtypes of eating disorders using structural analysis of social behavior. Journal of Consulting and Clinical Psychology, 57, 206–​214. Krautter, T., & Lock, J. (2004). Is manualized family-​based treatment for adolescent anorexia nervosa acceptable to patients? Patient satisfaction at end of treatment. Journal of Family Therapy, 26, 65–​81. Lasegue, C. (1883). De l’anorexie hysterique. Archives Generales de Medecine, 21, 384–​403. Le Grange, D., Crosby, R., & Lock, J. (2008). Predictors and moderators of outcome in family-​based treatment for adolescent bulimia nervosa. Journal of the American Academy of Child and Adolescent Psychiatry, 47, 464–​470. Le Grange, D., Crosby, R. D., Rathouz, P. J., & Leventhal, B. L. (2007). A randomized controlled comparison of family-​ based treatment and supportive psychotherapy for adolescent bulimia nervosa. Archives of General Psychiatry, 64, 1049–​1056. Le Grange, D., & Eisler, I. (2009). Family interventions in adolescent anorexia nervosa. Child and Adolescent Psychiatric Clinics of North America, 18, 159–​173. Le Grange, D., Eisler, I., Dare, C., & Russell, G. F. (1992). Evaluation of family treatments in adolescent anorexia nervosa: A pilot study. International Journal of Eating Disorders, 12, 347–​357. Le Grange, D., & Gelman, T. (1998). The patient’s perspective of treatment in eating disorders: A preliminary study. South African Journal of Psychology, 28, 182–​186. Le Grange, D., Hughes, E. K., Court, A., Yeo, M., Crosby, R. D., & Sawyer, S. M. (2016). Randomized clinical trial of parent-​ focused treatment and family-​ based treatment for adolescent anorexia nervosa. Journal of the American Academy of Child & Adolescent Psychiatry, 55, 683–​692. Le Grange, D., & Lock, J. (2007). Treating bulimia in adolescents: A family-​based approach. New York, NY: Guilford Press.

332

Le Grange, D., Lock, J., Accurso, E., Agras, S., Darcy, A., Forsberg, S., & Bryson, S. (2014). Relapse from remission at four-​year follow-​up in two treatments for adolescent AN. Journal of the American Academy for Child and Adolescent Psychiatry, 53, 1162–​1167. Le Grange, D., Lock, J., Agras, W. S., Bryson, S. W., & Jo, B. (2015). Randomized clinical trial of family-​based treatment and cognitive-​behavioral therapy for adolescent bulimia nervosa. Journal of the American Academy of Child and Adolescent Psychiatry, 54, 886–​894. Le Grange, D., Lock, J., Accurso, E. C., Agras, W. S., Darcy, A., Forsberg, S., & Bryson, S. W. (2014). Relapse from remission at two-​to four-​year follow-​up in two treatments for adolescent anorexia nervosa. Journal of the American Academy of Child and Adolescent Psychiatry, 53, 1162–​1167. Le Grange, D., Lock, J., Agras, W. S., Moye, A., Bryson, S., Jo, B., & Kraemer, H. (2012). Moderators and mediators of remission in family-​based treatment and adolescent focused therapy for anorexia nervosa. Behavior Research and Therapy, 50, 85–​92. Le Grange, D., Lock, J., & Dymek, M. (2003). Family-​based therapy for adolescents with bulimia nervosa. American Journal of Psychotherapy, 67, 237–​251. Lock, J., Agras, W. S., Bryson, S., & Kraemer, H. C. (2005). A comparison of short-​and long-​term family therapy for adolescent anorexia nervosa. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 632–​639. Lock, J., Couturier, J., & Agras, W. S. (2006). Comparison of long term outcomes in adolescents treated with family therapy. Journal of the American Academy of Child and Adolescent Psychiatry, 45, 666–​672. Lock, J., & Le Grange, D. (2013). Treatment manual for anorexia nervosa:  A  family-​based approach (2nd ed.). New  York, NY: Guilford Press. Lock, J., Le Grange, D., Agras, W. S., Moye, A., Bryson, S. W., & Jo, B. (2010). Randomized clinical trial comparing family-​ based treatment with adolescent-​focused individual therapy for adolescents with anorexia nervosa. Archives of General Psychiatry, 67, 1025–​1032. Lock, J., Le Grange, D., & Crosby, R. (2008). Exploring mechanisms of change in family-​based treatment for adolescent bulimia nervosa. Journal of Family Therapy, 30, 260–​271. Lock, J., Le Grange, D., Agras, W. S., Fitzpatrick, K. K., Jo, B., Accurso, E.,   .  .  .  Stainer, M. (2015). Can adaptive treatment improve outcomes in family-​based therapy for adolescent anorexia nervosa? Feasibility and treatment effects of a multi-​site treatment study. Behavior Research and Therapy, 73, 90–​95. Madanas, C. (1981). Strategic family therapy. San Francisco, CA: Jossey-​Bass. Madden S., Miskovic-​Wheatley, J., Wallis, A., Kohn, M., Lock, J., Le Grange, D.,  . . .  Touyz, S. (2015). A randomized controlled trial of in-​patient treatment for anorexia nervosa in medically unstable adolescents. Psychological Medicine, 45, 415–​427. Marzola, E., Knatz, S., Murray, S. B., Rockwell, R., Boutelle, K., Eisler, I., & Kaye, W. H. (2015). Short-​term intensive family therapy for adolescent eating disorders: 30-​month outcome. European Eating Disorders Review, 23, 210–​218. Minuchin, S., Baker, B. L., Rosman, B. L., Liebman, R., Milman, L., & Todd, T. C. (1975). A conceptual model of psychosomatic illness in children:  Family organization and family therapy. Archives of General Psychiatry, 32, 1031–​1038.

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Minuchin, S., Rosman, B. L., & Baker, B. L. (1978). Psychosomatic families:  Anorexia nervosa in context. Cambridge, MA: Harvard University Press. Roberto, L. (1986). Bulimia: The transgenerational view. Journal of Marital and Family Therapy, 12, 231–​240. Robin, A., Siegal, P., & Moye, A. (1995). Family versus individual therapy for anorexia: Impact on family conflict. International Journal of Eating Disorders, 17, 313–​322. Robin, A., Siegal, P., Gilroy, M., Dennis, A., & Sikand, A. (1999). A controlled comparison of family versus individual therapy for adolescents with anorexia nervosa. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 1482–​1489. Rockwell, R. E., Boutelle, K., Trunko, M. E., Jacobs, M. J., & Kaye, W. H. (2011). An innovative short-​term, intensive, family-​based treatment for adolescent anorexia nervosa: Case series. European Eating Disorders Review, 19, 362–​367. Root, M. P. P., Fallon, P., & Friedrich, W. N. (1986). Bulimia: A systems approach to treatment. New York, NY: Norton. Russell, G. F., Szmukler, G. I., Dare, C., & Eisler, I. (1987). An evaluation of family therapy in anorexia nervosa and bulimia nervosa. Archives of General Psychiatry, 44, 1047–​1056. Salaminiou, E., Campbell, M., Simic, M., Kuipers, E., & Eisler, I. (in press). Intensive multi-​family therapy for adolescent anorexia nervosa:  An open study of 30 families. Journal of Family Therapy. Schmidt, U., Lee, S., Beecham, J., Perkins, S., Treasure, J., Yi, I.,  . . .  Eisler, I. (2007). A randomized controlled trial of family therapy and cognitive behavior therapy guided self-​ care for adolescents with bulimia nervosa and related disorders. American Journal of Psychiatry, 164, 591–​598. Scholz, M., & Asen, K. E. (2001). Multiple family therapy with eating disordered adolescents. European Eating Disorders Review, 9, 33–​42. Schwartz, R., Barrett, M., & Saba, G. (1985). Family therapy for bulimia. Handbook of psychotherapy for anorexia

nervosa and bulimia. New  York, NY:  Guilford Press, 280–​310. Selvini Palazzoli, M. (1974). Self-​starvation: From the intrapsychic to the transpersonal approach. Oxford, UK: Chaucer. Silverman, J. (1997). Anorexia nervosa: Historical perspective on treatment. In D. Garner & P. Garfinkel (Eds.), Handbook of treatment for eating disorders (2nd ed., pp. 3–​10). New York, NY: Guilford Press. Steinglass, P. (1998). Multiple family discussion groups for patients with chronic medical illness. Families, Systems, and Health, 16, 55–​70. Steinglass, P., & Horan, M. (1988). Families and chronic medical illness. Journal of Psychotherapy and the Family, 3, 127–​142. Touyz, S., & Hay, P. (2015). Severe and enduring anorexia nervosa (SE-​AN): In search of a new paradigm. Journal of Eating Disorders, 3, 26. Turkiewicz, G., Pinzon, V., Lock, J., & Fleitlich-​Bilyk, B. (2010). Feasibility, acceptability, and effectiveness of family-​based treatment for adolescent anorexia nervosa: An observational study conducted in Brazil. Revista Brasileira de Psiquiatria, 32, 169–​172. Voriadaki, T., Simic, M., Espie, J., & Eisler, I. (2015). Intensive multi-​family therapy for adolescent anorexia nervosa:  Adolescents’ and parents’ day-​to-​day experiences. Journal of Family Therapy, 37, 5–​23. Wynne, L. (1980). Paradoxical interventions:  Leverage for therapeutic change in individual and family systems. In T. Strauss, S. Bowers, S. Downey, S. Fleck, & I. Levin (Eds.), The Psychotherapy of Schizophrenia. New  York, NY: Plenum Press. Zaitsoff, S., Doyle, A. C., Hoste, R. R., Le Grange, D. (2008). How do adolescents with bulimia nervosa rate the acceptability and therapeutic relationship in family-​based treatment? International Journal of Eating Disorders, 41, 390–​398.

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C H A PT E R

 Dialectical Behavior Therapy and Emotion-​Focused Therapies for Eating Disorders

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Eunice Y. Chen, Angelina Yiu, and Debra L. Safer

Abstract This chapter provides a description and review of the research evidence for the adaptation of dialectical behavior therapy (DBT) and emotion-​focused therapies for eating disorders (EDs). First, the chapter briefly describes the standard DBT program as originally developed for women with borderline personality disorder (BPD) and the evidence for standard DBT with BPD. Second, the rationale for the adaptation of DBT for EDs is given and preliminary evidence for DBT and other emotion-​focused treatments is described. Finally, the Stanford DBT program for EDs is outlined. Given the promise of alternative treatments for eating disorders, further development, adaptation, and testing of transdiagnostic emotion regulation treatments is warranted. Key Words:  borderline personality disorder, dialectical behavior therapy, eating disorder, trial, evidence

Introduction

Standard dialectical behavior therapy (DBT) is an outpatient cognitive-​ behavioral therapy originally developed for women with borderline personality disorder (BPD), who frequently struggle with emotion dysregulation and recurrent suicidal behavior. Dialectical behavior therapy is a comprehensive skills-​based treatment and emphasizes the integration of opposing principles (the dialectic) such as behavior change (problem solving, contingency management, exposure-​based procedures, cognitive modification) with acceptance-​based practices such as Zen and contemplation practice (such as mindfulness and validation). The dialectical framework within DBT stresses wholeness, interrelatedness, and process. Over time, standard DBT has been adapted to address a variety of problem behaviors associated with emotion dysregulation, including eating disorders (EDs). The aims of this chapter are to (1) briefly review standard DBT as originally developed for women with BPD, including its biosocial theory; (2) review 334

the randomized controlled trial evidence of DBT for BPD; (3) present the rationale for the adaptation of DBT for EDs; (4) review the randomized controlled trial evidence for DBT and other emotion-​focused therapies for EDs; (5) describe the DBT model of maintenance and etiology of EDs; (6)  outline the DBT program as adapted for binge eating disorder (BED) and bulimia nervosa (BN); and (7) offer conclusions and future research directions.

Standard Dialectical Behavior Therapy Treatment

According to standard DBT, BPD is conceptualized as a disorder of pervasive emotion dysregulation. The biosocial theory is used to describe its etiology and maintenance, which postulates that BPD behaviors (e.g., intense and labile emotions, nonsuicidal self-​ injury, self-​ damaging behaviors, suicidal behaviors) develop due to the transaction over time between a biological vulnerability to emotion dysregulation and an environment experienced as emotionally invalidating. Emotional

vulnerability refers to high negative affect at baseline, heightened sensitivity to emotional stimuli, intense emotional responses, and a slow return to emotional baseline. An environment is labeled invalidating if it (1) indiscriminately rejects an individual’s communication of personal experience, particularly emotions; (2) intermittently reinforces an escalation of emotions; and (3) oversimplifies problem solving and meeting goals. These characteristics lead individuals to have difficulties validating their own internal experiences and to search the environment for ways to respond. As such, individuals may often react with extreme oscillations between emotional inhibition and intense responses in order to communicate private experience, as well as forming unrealistic goals. The pervasive emotion dysregulation that results includes several difficulties: inhibiting mood-​ dependent behaviors that may be inappropriate or impulsive; organizing behavior in the service of goals, independent of current mood; up-​or down-​regulating physiological arousal as needed; diverting attention away from emotionally evocative stimuli; and/​ or experiencing emotion without avoidance or an extreme secondary negative emotion. The affect dysregulation model within the biosocial theory posits that suicidal and self-​injurious behaviors function to reduce painful, intolerable emotional states in individuals who lack adaptive skills to modulate emotions. Engagement in suicidal and self-​injurious behavior may bring temporary relief, but such behavior typically leads to more distressing emotions or other negative consequences. For example, secondary emotions, such as shame, can arise from engagement in suicidal or self-​injurious behavior. Intolerance of painful emotions then causes the cycle of maladaptive emotion regulation behaviors to repeat itself. Standard DBT treatment (Linehan, 1993a; Linehan, 1993b; Linehan, 2014) is organized around the client’s level of severity and chronicity, with different treatment stages associated with particular treatment goals. The DBT stages involve (1)  Pretreatment, orientation and commitment to treatment; (2) Stage I, stopping out-​of-​control behaviors; (3) Stage II, replacing “quiet desperation” with nontraumatic emotional experiencing; (4) Stage III, reducing ongoing disorders and problems in living; and (5) Stage IV, resolving a sense of incompleteness to achieve freedom. Each stage of treatment is associated with a target hierarchy. Dialectical behavior therapy is unique from other therapies, as an overall target hierarchy, rather than a prescribed session

agenda, dictates the content of individual sessions. For BPD, the Stage I target hierarchy is to (1) cease life-​threatening behaviors (e.g., suicide attempts, increase in suicide ideation, nonsuicidal self-​injurious behaviors, homicidal threats and behaviors); (2) cease therapy-​interfering behaviors (e.g., missed sessions); (3)  cease quality-​of-​life-​interfering behaviors (e.g., EDs or other Axis I  disorders, homelessness); and (4) increase behavioral skills. Standard DBT functions to enhance a client’s use of skillful behavior both within and outside of therapy sessions, as well as both client and therapist’s motivation to engage with and deliver the treatment. This is accomplished by reducing reinforcement for dysfunctional or ineffective client behavior (which may include restructuring the environment to support progress and adaptive change), and generalizing behavior from the therapy setting to the natural environment. To fulfill these functions, the modes of treatment in standard DBT involve (1)  weekly individual psychotherapy; (2)  weekly group skills training; (3)  24-​hour telephone consultation; and (4) a weekly therapist consultation team. Each mode involves a different hierarchy of targets. The individual psychotherapist is responsible for the assessment and problem solving of skill deficit and motivational problems, as well as organizing other treatment modalities in service of these goals. Group skills training targets the acquisition of new behavioral skills in a structured psychoeducational format and includes four modules:  Mindfulness, Distress Tolerance, Emotion Regulation, and Interpersonal Effectiveness skills. Clients are instructed to use telephone consultation for coaching to generalize the use of skills to the natural environment, decrease suicidal behaviors and nonsuicidal self-​injury, and to repair possible ruptures to the client–​therapist relationship. Finally, the therapist consultation team enhances therapist motivation and skills and manages problems that arise in the delivery of DBT. In addition to the focus on treatment hierarchies that dictates the structure of individual sessions, dialectical strategies emphasize the balance between change and acceptance for each treatment strategy in standard DBT (e.g., core strategies, stylistic strategies, and case management strategies). Dialectical strategies highlight dichotomous relationships, such as feelings/​beliefs versus wise mind and good versus bad, and assist clients in finding balanced and synthesized responses. Dialectical strategies include the use of metaphors, stories, paradox, playing devil’s advocate, fluctuating between ambiguity and Chen, Yiu, Safer

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certainty, using cognitive restructuring, highlighting continual change, and validating a client’s intuitive wisdom. The core strategies balance acceptance (e.g., validation) and behavioral change (e.g., problem-​solving) strategies. The latter include chain analyses, which meticulously examine the topography, intensity, frequency, duration, situation, antecedents, and consequences of a problem behavior. In standard DBT, chains are typically conducted during individual psychotherapy. Repeated chain analyses of a problem behavior provide the client and therapist with information on the cues, maintaining factors and function of a problematic behavior. This enables the client and therapist to identify what prevented the client from being effective in a situation, and then to teach, role-​play, rehearse new skills (e.g., emotion regulation skills) or use cognitive modification or mindfulness to address faulty cognitions or clarify environmental contingencies. Having established a solution with the client and a plan to prevent future problem behavior, the therapist assesses the client’s commitment using a variety of commitment strategies such as evaluating pros and cons, playing devil’s advocate, and using “foot in the door/​door in the face” strategies. The client and therapist then troubleshoot this plan, and search for commitment to the revised plan. In every DBT encounter with a client, change strategies are balanced with acceptance strategies (e.g., validation) to build and maintain a strong therapeutic relationship. Validation strategies range on a continuum from listening in an interested fashion to being radically genuine, that is, treating the client as one would treat an equal, a sister, or a friend. Stylistic strategies also balance acceptance and change. Reciprocal communication, on the one hand, involves interpersonal warmth, responsiveness to a client’s concerns and strategic self-​disclosure, which models skills application as well as nonjudgmental sharing of one’s own vulnerabilities. On the other hand, irreverent communication involves an outrageous, humorous, or blunt style and is used when therapy becomes polarized and a therapist and client become deadlocked. Case management strategies include “consultation-​ to-​the-​client,” “environmental interventions,” and “consultation-​to-​the-​therapist.” The first teaches clients how to skillfully interact with the environment rather than organizing the environment to meet their needs. Environmental interventions are used when a client is in immediate danger or is 336

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powerless, with the therapist acting directly on the client’s behalf. Consultation-​to-​the-​therapist strategy involves individual therapists seeking consultation within their team for support and assistance in delivering DBT effectively. The preceding is a brief description of the standard DBT program for women with BPD. A more exhaustive description of Stage I DBT for BPD can be found in Linehan’s manuals (Linehan, 1993a, 1993b, 2014). As discussed later, standard DBT has been adapted to address a variety of problem behaviors associated with emotion dysregulation, including ED behavior, as described in the text that follows.

Efficacy of Dialectical Behavior Therapy with Borderline Personality Disorder

Standard DBT is currently the most empirically validated treatment for BPD and is generally considered the treatment-​of-​choice for individuals with BPD (Lieb, Zanarini, Schmahl, Linehan, & Bohus, 2004). Nine randomized controlled trials provide evidence for its efficacy ([1]‌Linehan, Armstrong, Suarez, Allmon, & Heard, 1991, with follow-​up reported in Linehan, Heard, & Armstrong, 1993; Linehan, Tutek, Heard, & Armstrong 1994; [2] Linehan et al., 1999; [3] Linehan et al., 2002; [4] Turner, 2000; [5] Koons et  al., 2001; [6] Verheul et al., 2003, van den Bosch, Verheul, Schippers, & van den Brink, 2002; [7] Linehan et al., 2006; [8] McMain et  al., 2009; [9] Carter, Willcox, Lewin, Conrad, & Bendit, 2010). Apart from trials conducted by the developer, five independent research teams conducted these trials (Carter et  al., 2010; Koons et  al., 2001; McMain et  al., 2009; Turner, 2000; van den Bosch et al., 2002) in three countries other than the United States—​ the Netherlands, Canada, and Australia ( Carter et al., 2010 McMain et al., 2009; van den Bosch et al., 2002). Standard DBT has been compared to treatment-​ as-​usual (Carter et  al., 2010; Koons et  al, 2001; Linehan et  al., 1991, 1999; Verheul et  al., 2003), treatment-​by-​experts (TBE; Linehan et  al., 2006; McMain et  al., 2009), comprehensive validation (Linehan et al., 2002), and client-​centered therapy (Turner, 2000). Compared to its control condition, DBT showed significantly greater reductions in suicide attempts, intentional self-​injury, and suicidal ideation (Koons et  al., 2001; Linehan et  al., 1991, 1999, 2002, 2006; Turner, 2000; Verheul et  al., 2003). Standard DBT also resulted in significantly less treatment dropout than control treatments (Linehan et al., 1991, 1999, 2006; Verheul

et  al., 2003) and clients receiving DBT were less likely to use inpatient (Linehan et al., 1991, 2006; Turner, 2000) or emergency room services (Linehan et  al., 2006). Treatment with DBT demonstrated improvements in secondary outcome variables (Linehan et  al., 2002), such as depressed mood (Linehan et al., 2006), with some studies showing that DBT significantly improved these variables compared to control conditions (Koons et al., 2001; Linehan et al., 1991, 1999; Turner, 2000). Two large randomized controlled trials compared DBT to TBE or general psychiatric management among suicidal BPD participants (Linehan et  al., 2006; McMain et  al., 2009). The first trial (Linehan et al., 2006) controlled for therapist availability, expertise, allegiance, gender, training and experience, consultation availability, and institutional prestige between treatment arms. After treatment and 1 year of follow-​up, DBT clients were half as likely to make a suicide attempt (23% vs. 46% of clients), were less likely to be to be hospitalized for suicidal ideation, were less likely to drop out (25% vs. 59%), and had lower medical risk across all suicide attempts and self-​injurious acts. Overall, DBT resulted in significant reductions of suicidal and self-​ injurious behaviors compared to the control condition. However, in a second trial conducted in Canada that compared DBT with general psychiatric management, it was found that both treatments were equivalent in reducing suicidal and self-​injurious behaviors, use of healthcare services, and improvements of BPD symptoms, with no significant differences in dropout rates (McMain et al., 2009). Treatment in both treatment arms was delivered by clinicians with expertise in treating BPD and clinicians delivering DBT were adherent to the treatment. Findings from both large, randomized controlled trials suggest that standard DBT is efficacious for individuals with suicidal BPD in reducing suicidal ideation, suicide attempts, and use of healthcare services and retaining individuals in treatment (Linehan et  al., 2006; McMain et al., 2009). In addition to the efficacy of DBT for BPD, evidence suggests that DBT is efficacious for BPD with co-​ occurring disorders, such as substance abuse (Linehan, Schmidt, Dimeff, Craft, Kanter, & Comtois, 1999; van den Bosch, Verheul, Schippers, & van den Brink, 2002), and DBT has also been adapted for a variety of populations not specifically selected for BPD (Dimeff & Koerner, 2007). These include randomized controlled trials for depressed older adults (Lynch, Morse, Mendelson, & Robins,

2003; Lynch et  al., 2007), treatment-​ resistant depressed individuals (Harley, Sprich, Safren, Jacobo, & Fava, 2008), adults with bipolar disorder I or II (van Dijk, Jeffrey, & Katz, 2013). Controlled trials using DBT have also been conducted, such as with suicidal adolescents with BPD features (Rathus & Miller, 2002).

Why Adapt Dialectical Behavior Therapy for Eating Disorders?

Dialectical behavior therapy offers an alternative for difficult-​to-​treat clients for whom existing treatments have failed. Currently the most empirically tested treatments for EDs, cognitive-​behavior therapy (CBT) and interpersonal psychotherapy (IPT), result in about 50% of BN and BED patients (Fairburn & Brownell, 2001; Keel & Brown, 2010) remaining symptomatic after treatment. Predictors of poor outcome in CBT for EDs may include co-​ occurring Axis I and II disorders or symptoms such as BPD and depressive symptoms (Grilo, Masheb, & Wilson, 2001; Stice & Agras, 1999; Wilfley et al., 2000). Standard DBT thus represents a viable option for ED clients with co-​occurring psychopathology or for whom existing treatments have failed, due to its efficacy for individuals with multiple and “difficult-​to-​treat” disorders. As described briefly, DBT is uniquely based on a broad affect regulation model. In other words, the precursors of binge eating are understood to be the result of affect rather than due directly to dietary restraint and weight and shape concerns (as in CBT) or as a result of difficulties with resolving interpersonal problems (as in IPT). Although this affect regulation model does not preclude the role of weight and shape concerns, interpersonal difficulties, thoughts about food or the self, or perfectionistic thinking in triggering affective states, this model parsimoniously focuses on affect as an important trigger leading to problematic ED behavior. The affect regulation model views binge eating and other types of ED behavior (e.g., vomiting) as the means (albeit maladaptive) by which individuals regulate emotions. Because standard DBT treatment is specifically designed to teach adaptive affect regulation skills and to target behaviors resulting from emotion dysregulation, a theoretical rationale exists for applying DBT to treating EDs. By using the biosocial theory, DBT also offers an etiological theory for the development of ED behaviors over time. This theory describes the areas needed for change but also encourages an attitude of effective compassion in the therapist. This theory Chen, Yiu, Safer

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is also validating to clients and serves to reduce some of the self-​judgment and blame these individuals possess with regard to their disorder. Eating disorder behaviors are viewed as a development over time from a transaction between a biologically emotionally vulnerable individual poorly matched with an environment experienced as invalidating. As noted, DBT is a protocol-​driven treatment in which sessions are organized by the highest ranking (or highest risk) target behavior that took place that day or over the last week. In addition, there are special protocols designed for addressing life-​threatening and therapy-​interfering behavior. Dialectical behavior therapy provides detailed guidance for therapists in managing crisis behaviors, which may be particularly, as individuals with EDs often engage in suicidal and nonsuicidal self-​ injurious behaviors (e.g., Claes & Muehlenkamp, 2014; Franko & Keel, 2006; Svirko & Hawton, 2007). In addition, DBT uniquely targets therapy-​ interfering behavior (e.g., the client/​ therapist missing sessions or being late to sessions, homework incompletion). The protocol-​driven nature of DBT offers flexibility within a session, thus allowing multiple problems besides the ED to be addressed. The fusion of behavior change strategies with novel acceptance-​based strategies, such as mindfulness skills, makes DBT unique among ED treatments. Mindfulness-​based approaches to thoughts and emotions contrast with older-​style cognitive restructuring techniques. Clients are taught to observe and describe their thoughts and feelings, to watch them come and go, and to note this constant passage. In particular, clients learn that thoughts and feelings are simply thoughts and feelings, which can be sat with and observed without being acted on. The nonjudgmental component of mindfulness is important for both clients and therapists. For example, clients with EDs are often judgmental about their appearance and themselves. Therapists may also become judgmental of client’s thoughts and behaviors, as ED behaviors may be trivialized or judged to be scheming, deceitful, or superficial. This can lead to invalidation of clients, a lack of motivation for treatment, and burnout of both clients and therapists. The nonjudgmental standpoint of DBT allows ED behaviors to be viewed nonpejoratively and thus usefully defined as responses that are within a client’s current skill repertoire but that can be replaced by more helpful or adaptive responses. 338

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Evidence for Dialectical Behavior Therapy Adaptations

Currently, DBT adaptations for EDs, compared to other emotion-​focused therapies for EDs has the largest evidence base. In particular, evidence from case series demonstrates that women with BPD and ED show improvements in ED symptoms with minimally adapted DBT in an outpatient setting (Chen, Matthews, Allen, Kuo, & Linehan, 2008; Palmer et al., 2003). Furthermore, evidence suggests that a DBT-​informed treatment in partial hospitalization and intensive outpatient programs for individuals with EDs with multiple diagnoses, including BPD, shows promise in reducing ED symptoms, as well as improving affect regulation among those with co-​occurring ED and BPD (Ben-​ Porath, Wisniewski, & Warren, 2009; Federici & Wisniewski, 2013). Additionally, a stepped-​ care trial for early weak responders to guided self-​help CBT with BED and BN compared minimally adapted standard DBT with group and individual CBT and found that both intensive treatments resulted in similar binge frequency reduction at end of treatment and at 1-​year follow up (Chen et al., 2016). Although there is evidence for the effectiveness of different adaptations of DBT for EDs, the only adaptation that has been supported through randomized controlled trials is the Stanford DBT model (Safer, Telch, & Chen, 2009; Telch, 1997a) for BED and BN. The Stanford DBT model for BED and BN differs from the standard DBT program for BPD in notable ways, which affects treatment structure and content. For example, the adapted Stanford version employs a single modality of treatment delivery (weekly 2-​hour group DBT for BED and or weekly 50-​to 60-​minute individual DBT for BN) versus standard DBT’s weekly individual therapy (50–​60 minutes) plus 2-​hour group skills training. The Stanford DBT Model for BED and BN was originally developed for adult women 18 to 65 years old. Exclusion criteria included (1)  current use of psychotropic medications, (2) psychotic or bipolar affective disorders diagnoses, (3)  current involvement in psychotherapy or weight loss treatments, (4) current suicidality, (5) current substance abuse or dependence, or (6) pregnancy. Clients with BPD were not specifically excluded. The Stanford DBT model (has been researched in one randomized-​controlled trial in a comparison with active comparison group therapy (ACGT) for BED (Safer, Robinson, & Jo, 2010), in two

randomized-​ controlled trials using wait-​ list controls, one for BED (Telch, Agras, & Linehan, 2001) and one for BN (Safer, Telch, & Agras, 2001a), as well as in an uncontrolled trial (Telch, Agras, & Linehan, 2000) for BED and two case reports (Safer et al., 2001b; Telch, 1997b). These results for the Stanford DBT model are supportive of its use. For example, in the first randomized controlled trial of DBT for BED, 16 of the 18 women (89%) who received DBT were abstinent from binge eating at the end of the 20-​week treatment compared to 2 of 16 (12.5%) wait-​list controls (Telch et al., 2001). The dropout rate was low, with only 9% (2 of 22) of the sample dropping out after initially beginning DBT. At post-​treatment, clients in DBT reported significantly improved weight and shape concerns and eating concerns and demonstrated reduced urges to eat on the Emotional Eating Scale (Arnow, Kenardy, & Agras, 1995), especially when angry. At the 3-​month follow-​up, 67% of the 18 participants in DBT were abstinent from binge eating and 56% of the 18 at the 6-​month follow-​ up. The DBT participants reported practicing on average 3.6 different skills per week an average of 4  days per week at the final assessment. The high abstinence rates were consistent with those of the smaller uncontrolled trial of DBT for BED, where 82% of the participants were abstinent from binge eating after 20 group sessions, with none dropping out after commencing treatment (Telch et al. 2000). Similar findings were found as part of a replication/​ extension study of the Stanford DBT model for BED, in which the client population was expanded to include both men and women and individuals on stable psychotropic medication (Safer et al., 2010). Sixty-​four percent of those who received DBT for BED were binge abstinent after 20 sessions, compared with 36% of those in the comparison group. These rates are similar to abstinence rates found in CBT and IPT for BED (Wilfley et al., 1993, 2002). Findings from a randomized controlled trial of group DBT for BN were also promising. In 20 weeks of individually delivered DBT for bulimic symptoms, abstinence from binge eating/​purging behaviors at the end of 20 weeks of treatment was 28.6% (4 of 14) for DBT and 0% (0 of 15) for the wait-​list control (Safer et  al., 2001a). These findings were similar to post-​treatment abstinence rates from the largest multisite CBT for BN trial (Agras, Walsh, Fairburn, Wilson, & Kraemer, 2000). DBT resulted in moderate to large effect-​size changes on the Emotional Eating Scale (Arnow et  al., 1995), reducing urges to eat when angry or frustrated,

anxious, or depressed. In addition, the Positive and Negative Affect Scale (Watson, Clark, & Tellegen, 1988) showed significant decreases in participant’s experience of negative affect. At post-​treatment the dropout rate in DBT was 0%, compared with 6.7% in the wait-​list control group. Preliminary evidence on other DBT adaptations for EDs includes DBT-​guided self-​help (DBTgsh), radically open-​ DBT (RO-​ DBT), and appetite-​ focused DBT. The DBTgsh protocol was developed to encourage the dissemination of DBT for BED in a cost-​effective way. In a randomized controlled trial that compared DBTgsh with a wait-​list control, it was found that those who received DBTgsh reported significantly fewer past-​month binge eating episodes at end of treatment and greater rates of abstinence at 6-​month follow-​up than those in the control condition (Masson, von Ranson, Wallace, & Safer, 2013). In contrast to DBTgsh for BED, RO-​DBT was developed for anorexia nervosa (AN)-​ restricting type and focuses on skills to reduce emotional overcontrol. Two preliminary trials of RO-​ DBT for AN found that standard DBT skills plus skills that address overcontrol resulted in increased BMI in inpatient (Lynch et  al., 2013) and outpatient (Chen et al., 2015) settings, which was maintained at 1-​year follow-​up (Chen et al., 2015), as well as improvements in ED-​related symptoms at the end of treatment (Chen et al., 2015; Lynch et al., 2013). Notably, Lynch and colleagues (2013) found that, within an inpatient setting, 90% of treatment completers achieved either full or partial remission of AN symptoms. Moreover, participants from both RO-​ DBT trials found the treatment acceptable, resulting in retention of 8/​9 patients (Chen et al., 2015) and 34/​ 47 patients (Lynch et  al., 2013), respectively. In addition to trials on DBTgsh for BED and RO-​DBT for AN, appetite-​focused DBT has been examined in a preliminary trial with BN. In a comparison of 12 weeks of appetite-​focused DBT with a 6-​week delayed treatment control (Hill, Craighead, & Safer, 2011), it was found that BN symptoms were significantly reduced among participants who received appetite-​ focused DBT, relative to the control condition at 6 weeks. Furthermore, at post-​treatment, 26.9% of individuals who received appetite-​focused DBT were binge/​purge abstinent for the past month, and 61.5% of individuals no longer met full or subthreshold BN criteria. Taken together, preliminary evidence DBT adaptations for AN and BN suggest that skills training targeting Chen, Yiu, Safer

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rigidity in AN and skills training targeting mindful eating in BN warrant further consideration. Finally, preliminary data from open trials, case series, and one randomized controlled trial (Parling, Cernvall, Ramklint, Holmgren, & Ghaderi, 2016) on other novel emotion-​ focused treatments for EDs are promising. These treatments include emotion acceptance behavior therapy for AN (Wildes et  al., 2014), emotion-​focused group therapy for inpatient AN (Tchanturia, 2011), emotion-​focused group therapy for BN (Wnuk, Greenberg, & Dolhanty, 2015) as well as acceptance and commitment therapy for AN (Berman, Boutelle, & Crow, 2009; Parling et al., 2016), inpatient EDs (Juarascio et al., 2013) and BED (Juarascio et al., 2017; Hill, Masuda, Melcher, Morgan, & Twohig, 2015).

Dialectical Behavior Therapy for Eating Disorders

We first describe the model of the etiology and maintenance of eating disorders in DBT for eating disorders.

Affect Regulation Model for Eating Disorders

Stress and negative mood are the most frequently cited precipitants of binge eating (Polivy & Herman, 1993). In DBT for EDs, binge eating is viewed as analogous to that of self-​injury in standard DBT treatment for individuals with BPD. Binge eating or bulimic behaviors are understood as the result of attempts to escape from primary or secondary aversive emotions that may be triggered by thoughts regarding food, body image, perfectionism, negative thoughts about the self, or interpersonal situations (Linehan & Chen, 2005). Binge eating and bulimic behavior function to quickly narrow attention and cognitive focus from these thoughts and to provide immediate escape from physiological responses and feelings. Over time, binge eating as an escape behavior becomes reinforced (Heatherton & Baumeister, 1991), particularly if there is a lack of adaptive emotion regulation skills. Disordered eating behaviors may then be further reinforced by secondary emotions, such as shame (e.g., Sanftner & Crowther, 1998), with binge eating as a long-​ term consequence of an overlearned dysfunctional response to dysregulated emotions. Research evidence supports the role of negative emotions and emotion regulation in binge eating. Self-​report studies of weight loss participants show that individuals with BED report higher urges to binge eat in response to negative emotions 340

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(emotional eating) than non-​binge-​eaters, independent of degree of overweight (Eldredge & Agras, 1996). Specifically, the most frequently cited emotion triggering binge eating is anxiety, followed by sadness, loneliness, and anger, with happiness being the least frequently cited (Masheb & Grilo, 2006). Furthermore, self-​defined binges in obese women with BED were significantly more associated with negative mood, relative to caloric deprivation (Agras & Telch, 1998). In an experience sampling study, binge eating was preceded by more aversive mood states (Greeno, Wing, & Shiffman, 2000). Using a similar methodology, greater diurnal fluctuation in depression and anxiety and higher frequency of these moods during eating and binge eating was reported in BED subjects compared with non-​BED subjects (Lingswiler, Crowther, & Stephens, 1987). In addition to eating in response to negative moods, individuals who binge eat also appear to evaluate situations as more stressful than non-​ED individuals (Hansel & Wittrock, 1997). This may be due to difficulties in identifying and making sense of emotional states, along with limited access to emotion regulation strategies (Whiteside et al., 2007).

Adaptation of the Biosocial Theory for Eating Disorders

In DBT, ED behaviors, just like BPD behaviors, are understood as resulting from a transaction over time between an individual biologically predisposed to be more emotionally vulnerable and a mismatch with an environment experienced (but not necessarily intended) as invalidating. This invalidating environment may punish emotional displays, leading individuals to engage in ED behaviors to manage their emotions and the secondary emotion of shame that may result. Sometimes, the invalidation may be specific to ED behaviors (e.g., “Why can’t you just stop eating?”), or take the form of weight-​ related teasing or overconcern with weight by peers and family. The invalidating environment may also be broader, including typical Western societal messages idealizing thinness and disparaging overweight, such that each is associated with polar moral values. Further invalidation may be introduced by the media with the notion that weight loss should not be difficult (e.g., “lose 10 pounds in 10 days” advertisements). Over time, the results of these transactions may include (1)  difficulties in identifying and regulating emotional arousal; (2)  difficulties in tolerating emotional distress without engaging in ED behavior; (3)  difficulties in trusting one’s own

emotional responses as valid, that is, engaging in self-​invalidation; and (4)  formation of unrealistic goals and expectations due to oversimplification of problem solving and goal setting by the invalidating environment. Self-​invalidation may make individuals particularly vulnerable to turning to body-​image-​ focused environments as sources of information about what the self “should” look like. This may increase the likelihood of establishing unrealistic expectations among overweight or normal-​weight clients regarding weight loss.

The Stanford Model

The Stanford model of DBT was developed to target clients whose primary focus of treatment is BED or BN symptoms that interfere with their quality of life. It was not intended for individuals with active suicidal or self-​injurious behaviors, who should be offered the full program of standard DBT. In this section, the Stanford model of DBT as adapted for BED (in a group format) and for BN (in an individual format) is described. As briefly noted above, the Stanford adaptation of DBT for BED or BN differs in three important ways from standard DBT for BPD. First, it differs in its structure. The Stanford DBT model combines two modalities in standard DBT (individual treatment and group skills treatment) into one modality, either a 2-​hour group treatment for BED or a 50-​to 60-​minute individual session for BN. As opposed to what is typically a year-​long treatment in standard DBT, the Stanford DBT model is briefer and uses 20 sessions of treatment covering three (e.g., Core Mindfulness, Emotion Regulation, and Distress Tolerance) as opposed to four skills-​training modules. Second, the Stanford DBT model differs from standard DBT in the use of specific ED behavior targets, resulting in adaptations to the treatment hierarchy, diary card, and behavioral chain analysis. Third, the Stanford model involves the addition of particular concepts and skills specific to ED clients (e.g., the concept of dialectical abstinence, use of skills such as mindful eating, urge surfing, alternate rebellion, etc.). Adaptations made for the Stanford DBT model were made primarily for research purposes. For instance, other efficacious treatments for BED and BN, such as CBT and IPT, have been researched using 20 sessions. Thus, for the Stanford DBT model to be compared with other efficacious treatments, a similar number of sessions are required. The Interpersonal Effectiveness module was removed due to time constraints and because of a

potential theoretical overlap with IPT. For clinicians and programs that are not limited by the constraints of time, resources, or research, there is no research-​ based reason not to include the Interpersonal Effectiveness module—​particularly given the data on IPT’s efficacy with BED.

Structure of Treatment (Session Structure, Number of Sessions, Modules Covered)

The DBT for BED/​BN combines elements of individual psychotherapy and group skills training from standard DBT. Dialectical behavior therapy for BED/​BN incorporates chain analysis strategies, typically conducted in individual psychotherapy in standard DBT, with skills training, typically offered in a group format in standard DBT. The format of each session is divided evenly. The first half, consisting of 50 to 60 minutes if treatment is carried out in a 2-​hour group format or 25 to 30 minutes if treatment is carried out in a 50-​to 60-​ minute individual format, is devoted to homework review and includes discussion of client diary cards and chain analyses (motivation and skills strengthening). During this review, each group member has between 5 and 10 minutes to report on his or her use of new skills in the past week and to describe specific successes or difficulties in applying the skills to replace the targeted problem eating behaviors. The length of time each member has for homework review varies given the total duration of the session (which may be 2 hours or 2½ hours) and the number in attendance so that sufficient time is available for everyone to share. Group members are encouraged to help one another identify solutions to problems encountered in using the skills and to “cheerlead” efforts made. Separated by a 5-​to 10-​minute break when using a group format, the second half of each session is devoted to teaching new content and practice of new skills (e.g., skills acquisition). Like skills-​ training groups in standard DBT, groups in the Stanford DBT model for BED are composed of 8 to 10 members and are taught by 2 skills trainers—​a leader and a coleader. As described, the Stanford DBT model for BED used a group format, and the Stanford DBT model for BN/​partial BN was carried out in an individual format. In the Stanford model, DBT for BN was administered individually due to difficulties in recruiting sufficient numbers to start a group in a timely fashion (as needed in a research study) and because most treatments for BN are individually delivered. Chen, Yiu, Safer

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Sequence of Treatment

The pretreatment stage of the Stanford model comprises a pretreatment interview as well as sessions 1 and 2. During the pretreatment interview, each participant meets individually with one of the cotherapists (or, for BN, the individual therapist) for 30 to 45 minutes before beginning therapy. The major goals of this pretreatment visit involves orienting the participant to the DBT program (e.g., dates of treatment), assessing prior group experience, introducing the affect regulation model of binge eating and the targets of treatment, describing the expectations for participants (e.g., regular timely attendance, listening to tapes of any missed sessions, completing homework assignments) and therapists, and orienting individuals to the goals of treatment. In session 1, a major goal is to obtain a commitment from each group member to cease binge eating (or for BN, the individual client’s commitment to cease binge eating and purging). Standard DBT commitment strategies are used, such as having therapists play devil’s advocate in order to have clients consider and argue why they cannot continue binge eating and have the quality of life that they desire. Other tasks of this session are to explain the biosocial theory, review and sign formal therapist and client agreements, and introduce the diary card and chain analysis. In session 2, after conducting homework review in the first half of the session, therapists introduce clients to the concept of dialectical abstinence, a concept originally developed in DBT for substance use disorders (Linehan & Dimeff, 1997). This concept is described in greater detail in what follows. After the introductory sessions, the modules covered, in sequence, are: the Core Mindfulness module (sessions 3–​5), the Emotion Regulation module (sessions 6–​12), and the Distress Tolerance module (sessions 14–​18). Sessions 19 and 20 are devoted to a review of the different skills modules and relapse prevention. Clients are asked to detail their plans for continuing to practice the skills taught, to outline their specific plans for skillfully managing emotions that may trigger binge eating in the future, and to consider what they need to do next to continue to build a satisfying and rewarding quality of life. Clients say their final goodbyes and perhaps conduct a goodbye ritual (e.g., writing cards) to mark the ending of treatment. 342

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Adaptations to Treatment Hierarchy, Diary Card, and Behavioral Chain Analysis

Adaptations from standard DBT were made to the treatment hierarchy and related tools to reflect the needs of the population for whom the Stanford DBT model was developed—​ clients whose ED symptoms (e.g., binge eating and/​or purging) are the primary treatment focus. For most clients with primary BN or BED, the highest treatment target is to prevent any behavior(s) that interfere with the successful delivery of treatment (e.g., life-​ threatening behaviors, therapy-​ interfering behaviors), followed by those outlined in the Path to Mindful Eating—​an additional target hierarchy adapted specifically for individuals with BED or BN (see Table 17.1). The Path to Mindful Eating hierarchy addresses mindless eating, which refers to inattention when eating, such as when eating popcorn while watching television, only to discover the popcorn is finished without awareness of how this happened. Mindless eating, in contrast to binge eating, is defined as occurring without the experience of a sense of loss of control. Food preoccupation is when one’s thoughts or attention are absorbed or focused on food to the point of interference with functioning (e.g., work). Capitulating involves giving up on one’s goals to stop binge eating and in using skillful behavior to cope with emotions. When capitulating, one acts as if there is no other option or way to cope with aversive emotions than with food. Finally, apparently irrelevant behaviors are those that do not seem relevant to binge eating and purging or that a client insists do not matter but are actually important given information from chain analyses. For example, purchasing extra dessert “for company” may not seem to matter, but the presence of extra dessert in the home may actually be linked to a client’s binge eating. The Stanford model of DBT for BED/​BN also involves adaptations to the standard DBT diary card Table 17.1  Path to Mindful Eating 1.

Stop binge eating (and purging—​for BN clients).

2.

Eliminate mindless eating.

3.

Decrease cravings, urges, preoccupation with food.

4.

Decrease capitulating.

5.

Decrease apparently irrelevant behaviors.

to allow clients to track any dysfunctional eating behaviors as outlined on the Path to Mindful Eating (Table 17.1). A sample diary card can be found in Table 17.2. Finally, the chain analysis used in DBT for BED or BN is the same as that of standard DBT. Clients are directed to fill them out each week on the highest disordered eating behavior since the previous session as listed in the Path to Mindful Eating.

Dialectical Behavior Therapy for Binge Eating and/​or Purging

A number of DBT concepts and skills were added in DBT for BED/​BN to specifically address the needs of clients who binge eat and/​or purge. As noted, many of these were originally developed for DBT for substance abuse (see Linehan & Dimeff, 1997; Marlatt & Gordon, 1985). Included are the concept of dialectical abstinence as well as ED specific skills such as mindful eating, urge surfing, alternate rebellion, and burning bridges. Each is reviewed in turn. Dialectical abstinence, introduced in session 2, is a synthesis of a 100% commitment to abstinence and a 100% commitment to relapse prevention strategies. Before a client engages in binge eating, there is an unrelenting insistence on total abstinence. After a client has engaged in binge eating, however, the emphasis is on radical acceptance, nonjudgmental problem solving and effective relapse prevention, followed by a speedy return to an unrelenting insistence on abstinence. Therapists liken clients to Olympic athletes (Safer et al., 2009; Telch, 1997a) with therapists as their coaches. As an Olympian, one only focuses on “going for the gold” as opposed to focusing on what might happen if one were to fall or telling oneself before the race “Maybe a bronze would be okay.” Similarly, clients must focus only on binge abstinence. Yet athletes and clients must be prepared for the possibility of failure. The key is to be prepared to fail well. The dialectical dilemma is that both success and failure exist. The dialectical abstinence solution involves 100% certainty that binge eating is out of the question and 100% confidence that one will never binge again. However, simultaneously, one keeps in mind (“Way, way back in the very farthest part so that it never interferes with your resolve”) that if one slips, one will deal with it effectively by accepting the behavior nonjudgmentally and picking oneself back up, knowing one will never slip again. In addition to the concept of dialectical abstinence, ED specific mindfulness skills of mindful eating, urge surfing, alternate rebellion, and burning

bridges were adapted for binge eating and/​or purging, and taught over sessions 3 to 5. Mindful eating, as opposed to mindless eating, is the experience of full participation in eating, which involves observing and describing the experience in one’s mind. It is eating with full awareness and attention (one-​ mindfully) but without self-​ consciousness or judgment. Urge surfing involves mindful, nonattached observation of urges to binge or to eat mindlessly. Clients are educated about how urges and cravings are classically conditioned responses that have been associated with a particular cue. Mindful urge surfing involves awareness without engaging in impulsive mood-​dependent behavior. One learns to “let go” or “detach” from the object of the urge, being fully in the moment, “riding the wave” of the urge and noticing its ebb and flow. Although similar to mindfulness of the current emotion, urge surfing is a mindfulness skill that involves nonjudgmental observing and describing of urges, cravings, and food preoccupation. Alternate rebellion involves being effective in satisfying a wish to rebel without destroying one’s overriding objective to stop binge eating. The purpose is not to suppress or judge the rebellion but to find creative ways to rebel that do not involve “cutting off your nose to spite your face.” Many clients with BED have described the desire to “get back” at society, friends, and/​or family perceived to be judgmental about their weight. For these clients, “getting back” often involves rebelling by consuming even more food. However, this is not effective, as it runs contrary to achieving the goal of binge abstinence and an improved quality of life. Therapists can encourage clients to observe the need to rebel, label it as such, and then, if the decision is to act on the wish, to do so effectively. Clients can be creative in thinking up alternate rebellion strategies. For example, a client who feels judged by society for being obese might “rebel” by buying attractive lingerie that makes her feel beautiful or mindfully sitting in a well-​regarded restaurant and openly, unselfconsciously treating herself to a healthy and delicious bowl of soup. Burning bridges is a radical acceptance skill that involves accepting at the deepest and most radical level the idea that one is really not going to binge eat, mindlessly eat, or abuse oneself with food ever again, thus burning the bridge to those behaviors. One accepts that they will no longer block, deny, or avoid reality with binge eating. Instead, one makes a commitment from deep within to accept reality and one’s experiences as they are. Chen, Yiu, Safer

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Table 17.2a.  Stanford DBT Model Diary Card Instructions for Completing Your Diary Card Urge to Binge: Refer to the legend and choose the number from the scale (0–​6) that best represents your highest rating for the day. The key characteristics to consider when making your rating are intensity (how strongly you felt the urge) and duration (how long the urge lasted). Binge Episodes: Write the number of binge episodes you had each day. A binge refers to an eating episode in which you felt a loss of control during the eating. Mindless eating: Write in the number of “mindless” eating episodes that you had each day. Mindless eating refers to not paying attention to what you are eating, although you do not feel the sense of loss of control that you do during binge episodes. A typical example of mindless eating would be sitting in front of the TV and eating a bag of microwave popcorn without any awareness of the eating (i.e., somehow, the popcorn was gone and you were only vaguely aware of having eaten it). Again, however, you didn’t feel a sense of being out of control during the eating. Apparently Irrelevant Behaviors (AIB): Circle either “yes” or “no” depending on whether you did or did not have any AIBs that day. If you did, briefly describe the AIB in the place provided or on another sheet of paper. An AIB refers to behaviors that, on first glance, do not seem relevant to binge eating and purging but that actually are important in the behavior chain leading to these behaviors. You may convince yourself that the behavior doesn’t matter or really won’t affect your goal to stop binging and purging when, in fact, the behavior matters a great deal. A typical AIB might be buying several boxes of your favorite Girl Scout cookies because you wanted to help out a neighbor’s daughter (of course, you could buy the cookies and donate them to the neighbor, rather than taking them home). Capitulating: Refer to the legend and choose the number from the scale (0–​6) that best represents your highest rating for the day. The key characteristics to consider when making your rating are intensity (strength of the capitulating) and duration (how long it lasted). Capitulating refers to giving up on your goals to stop binge eating and to skillfully cope with emotions. Instead, you capitulate or surrender to binge eating, acting as if there is no other option or way to cope than with food. Food Preoccupation: Refer to the legend and choose the number from the scale (0–​6) that best represents your highest rating for the day. Food preoccupation refers to your thoughts or attention being absorbed or focused on food. For example, your thoughts of a dinner party and the presence of your favorite foods may absorb your attention so much that you have trouble concentrating at work. Emotion Columns: Refer to the legend and choose the number from the scale (0–​6) that best represents your highest rating for the day. The key characteristics to consider when making your rating are intensity (strength of the emotion) and duration (how long it lasted). Used Skills: Refer to the legend and choose the number from the scale (0–​6) that best represents your attempts to use the skills each day. When making your rating, consider whether or not you thought about using any of the skills that day, whether or not you actually used any of the skills, and whether or not the skills helped. Weight: Weigh yourself once each week and record your weight in pounds in the space provided. Please write in the date you weighed. It is best if you choose the same day each week to weigh. Many women find that arriving a few minutes early to the session and weighing at the clinic is a good way to remember to weigh. Urge to Quit Therapy: Indicate your urge to quit therapy before the session and after the session each week. Both of these ratings should be made for the same session as the one in which you received the diary card. It is best to make both of these ratings as soon as possible following that day’s session. Use a 0 to 6 scale of intensity of the urge, with 0 indicating no urge to quit and a 6 indicating the strongest urge to quit. Completing the Skills Side of the Diary Card: How Often Did You Fill Out This Side? Place a check mark to indicate how frequently you filled out the skills side of the diary card during the week. Skills Practice: Go down the column for each day of the week and circle each skill that you practiced/​used that day. If you did not practice or use any of the skills that particular day, then circle that day on the last line, which states, “Did not practice/​use any skills.”

b.  Symptoms and Behaviors Diary Card Diary Card Day And Date

Initials Urgea to Binge Binge Episodes (0–​6) # OBE lg

Mindless Eating

AIBb

# SBE sm # episodes

Capitulatinga

Fooda Fooda Angera Sadnessa Feara Craving Preoccupation

Shamea Pridea

Happinessa

Usedc Skills

Circle one

(0–​6)

(0–​6)

(0–​6)

(0–​6)

Mon

yes/​no

Tues

yes/​no

Wed

yes/​no

Thurs

yes/​no

Fri

yes/​no

Sat

yes/​no

Sun

yes/​no

Use the following scale to indicate the highest rating for the day: 0 = urge/​thought/​feeling not experienced 1 = urge/​thought/​feeling experienced slightly and briefly 2 = urge/​thought/​feeling experienced moderately and briefly 3 = urge/​thought/​feeling experienced intensely and briefly 4 = urge/​thought/​feeling experienced slightly and endured 5 = urge/​thought/​feeling experienced moderately and endured 6 = urge/​thought/​feeling experienced intensely and endured b Describe Apparently Irrelevant Behaviors (AIB): c Used Skills: 0 = Not thought about or used 1 = Thought about, not used, didn’t want to 2 = Thought about, not used, wanted to 3 = Tried but couldn’t use them 4 = Tried, could do them, but they didn’t help 5 = Tried, could use them, helped 6 = Didn’t try, used them, didn’t help 7 = Didn’t try, used them, helped Weight _​_​_​_​_​_​_​_​ Date Weighed _​_​_​_​_​_​_​_​_​ Urge to quit therapy (0–​5): Before therapy session: _​_​_​_​_​ After therapy session: _​_​_​_​ NIMH 1997–​2000 ER BED TELCH a

How often did you fill out this side? _​_​_​Daily _​_​_​_​4–​6 × _​_​_​_​ 2–​3 × _​_​ _​ Once

ID

(0–​6)

(0–​6)

(0–​6)

(0–​6)

(0–​6)

(0-​7)

c.  The Skills Use Weekly Diary Card Skills diary card

Instructions: Circle the days you worked on each skill.

1. Diaphragmatic Breathing 2. Wise mind 3. Observe: just notice 4. Describe: put words on 5. Participate: enter into the experience 6. Mindful eating 7. Nonjudgmental stance 8. One-​mindfully: in-​the-​moment 9. Effectiveness: focus on what works 10. Urge surfing 11. Alternate rebellion 12. Mindful of current emotion 13. Loving your emotions 14. Reduce vulnerability: PLEASE 15. Build MASTERy 16. Build positive experiences 17. Mindful of positive experiences 18. Opposite-​to-​emotion action 19. Observing-​your-​breath 20. Half-​smiling 21. Awareness exercises 22. Radical acceptance 23. Turning the mind 24. Willingness 25. Burning your bridges 26. Distract 27. Self-​soothe 28. Improve the moment 29. Pros and cons 30. Commitment 30. Did not practice any skills

Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon Mon

Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues Tues

How often did you fill out this side? _​_​_​Daily _​_​_​4–​6 × _​_​_​ 2–​3 × _​_​_​_​ Once

Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs Wed Thurs NIMH 1997–​2000 ER BED TELCH

Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri Fri

Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat Sat

Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun Sun

Conclusion

In summary, this chapter briefly describes standard DBT and adaptations that have been made to offer an alternative treatment approach for EDs that have failed to respond to existing therapies. Dialectical behavior therapy is uniquely based on an affect regulation model, and fuses behavior change strategies with novel acceptance-​ based strategies such as mindfulness. Dialectical behavior therapy also includes distinctive protocols for addressing suicidal behavior, nonsuicidal self-​injury, and therapy-​ interfering behaviors, such as drop out, homework incompletion, and lack of attendance. Standard DBT is an efficacious evidence-​based treatment for BPD, with promising treatment development data for use with individuals with BPD and EDs. For individuals with BED or BN that primarily affects quality-​of-​life, an adaptation of standard DBT for individuals with BED and BN by researchers at Stanford University has been found to be efficacious in randomized controlled trials. The Stanford University DBT model involves 20 group (for BED) or individual (for BN) sessions. These sessions teach mindfulness, emotion regulation and distress tolerance skills, integrating these with the use of chain analyses (careful step-​by-​step behavioral analyses) for problem behaviors. This model uses a unique hierarchy of ED behaviors (the “Path to Mindful Eating”) to target, including (1) stopping binge eating (and purging, for clients with BN); (2)  eliminating mindless eating (eating without awareness); (3) decreasing cravings, urges, preoccupation with food; (4) decreasing capitulating (i.e., giving in to binge eating); and (5) decreasing apparently irrelevant behaviors (i.e., behaviors that appear not to matter but play a role in leading to a binge). Finally, the Stanford DBT model for BED and BN adds ED-​specific concepts and skills to the standard treatment. The ED-​specific DBT concepts include dialectical abstinence, which teaches clients to focus on attaining binge abstinence while simultaneously being aware that if one slips, this can be addressed effectively. Additional ED-​ specific DBT skills include mindful eating, urge surfing (i.e., surfing urges to binge eat), alternative rebellion (effectively managing urges to rebel without binge eating), and burning bridges (radical acceptance of a commitment to cease ED behavior).

Future Directions •  How does DBT fare compared with other emotion-​focused therapies for BED and BN?

•  What are the mechanisms of action for DBT, and how are they distinguished from mechanisms of action for CBT and IPT? •  Are there ways to combine elements of DBT with CBT and/​or IPT? •  How can maintenance of treatment gains in DBT be improved for individuals with BED or BN? •  What client or therapist or combinations of these features are associated with better or worse outcome in DBT for BED or BN? •  What are the mechanisms of action for the Stanford DBT model? Which components are particularly helpful for individuals with BED or BN? •  Can the Stanford DBT model be efficacious for adolescents with BED/​BN? •  Does DBT specifically change vulnerability to emotions in individuals with BED or BN? •  Further development and testing of DBT for adults with AN and BPD is needed. •  Further testing of self-​help DBT for EDs is needed.

References

Agras, W. S., & Telch, C. F. (1998). The effects of caloric deprivation and negative affect on binge eating in obese binge-​eating disordered women. Behavior Therapy, 29, 491–​503. Agras, W. S., Walsh, T., Fairburn, C. G., Wilson, G. T., & Kraemer, H. C. (2000). A multicenter comparison of cognitive-​behavioral therapy and interpersonal psychotherapy for bulimia nervosa. Archives of General Psychiatry, 57, 459–​466. Arnow, B., Kenardy, J., & Agras, W. S. (1995). The Emotional Eating Scale: The development of a measure to assess coping with negative affect by eating. International Journal of Eating Disorders, 18, 79–​90. Ben-​ Porath, D. D., Wisniewski, L., & Warren, M. (2009). Differential treatment response for eating disordered patients with and without a comorbid borderline personality diagnosis using a dialectical behavior therapy (DBT)-​informed approach. Eating Disorders, 17, 225–​241. doi:10.1080/​ 10640260902848576 Berman, M. I., Boutelle, K. N., & Crow, S. J. (2009). A case series investigating acceptance and commitment therapy as a treatment for previously treated, unremitted patients with anorexia nervosa. European Eating Disorders Review, 17, 426–​434. Carter, G. L., Willcox, C. H., Lewin, T. J., Conrad, A. M., & Bendit, N. (2010). Hunter DBT project: Randomized controlled trial of dialectical behaviour therapy in women with borderline personality disorder. Australian and New Zealand Journal of Psychiatry, 44, 162–​173. Chen, E. Y., Cacioppo, J., Fettich K., Gallop, R., McCloskey M. S., Olino T., & Zeffiro, T. A. (2016). An adaptive randomized trial of dialectical behavior therapy and cognitive behavior therapy for binge-​ eating. Psychological Medicine. Nov 17:1–​15. [Epub ahead of print]

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Chen, E. Y., Matthews, L., Allen, C., Kuo, J. R., & Linehan, M. M. (2008). Dialectical behavior therapy for clients with binge-​eating disorder or bulimia nervosa and borderline personality disorder. International Journal of Eating Disorders, 41, 505–​512. doi:10.1002/​eat.20522 Chen, E. Y., Segal, K., Weissman, J., Zeffiro, T. A., Gallop, R., Linehan, M. M.,  . . .  Lynch, T. R. (2015). Adapting dialectical behavior therapy for outpatient adult anorexia nervosa—​ A pilot study. International Journal of Eating Disorders, 48, 123–​132. Claes, L., & Muehlenkamp, J. J. (2014). Non-​suicidal self-​injury in eating disorders. Heidelberg, Germany and New  York, NY: Springer. Dimeff, L. A., & Koerner, K. (2007). Dialectical behavior therapy in clinical practice:  Applications across disorders and settings: New York, NY: Guilford Press. Eldredge, K. L., & Agras, W. S. (1996). Weight and shape over-​ concern and emotional eating in binge eating disorder. International Journal of Eating Disorders, 19, 73–​82. Fairburn, G., & Brownell, K. (2001). Eating disorders and obesity. New York, NY: Guilford Press. Federici, A., & Wisniewski, L. (2013). An intensive DBT program for patients with multidiagnostic eating disorder presentations:  A  case series analysis. International Journal of Eating Disorders, 46, 322–​331 [serial online]. Available from PsycINFO, Ipswich, MA. Accessed October 4, 2016. Franko, D. L., & Keel, P. K. (2006). Suicidality in eating disorders:  Occurrence, correlates, and clinical implications. Clinical Psychology Review, 26, 769–​782. Greeno, C. G., Wing, R. R., & Shiffman, S. (2000). Binge antecedents in obese women with and without binge eating disorder. Journal of Consulting and Clinical Psychology, 68, 95–​102. Grilo, C. M., Masheb, R. M., & Wilson, G. (2001). Subtyping binge eating disorder. Journal of Consulting and Clinical Psychology, 69, 1066–​1072. Hansel, S. L., & Wittrock, D. A. (1997). Appraisal and coping strategies in stressful situations: A comparison of individuals who binge eat and controls. International Journal of Eating Disorders, 21, 89–​93. Harley, R., Sprich, S., Safren, S., Jacobo, M., & Fava, M. (2008). Adaptation of dialectical behavior therapy skills training group for treatment-​resistant depression. Journal of Nervous and Mental Disorders, 196, 136–​143. Heatherton, T. F., & Baumeister, R. F. (1991). Binge eating as escape from self-​awareness. Psychological Bulletin, 110, 86–​108. Hill, D. M., Craighead, L. W., & Safer, D. L. (2011). Appetite-​ focused dialectical behavior therapy for the treatment of binge eating with purging: A preliminary trial. International Journal of Eating Disorders, 44, 249–​261. Hill, M. L., Masuda, A., Melcher, H., Morgan, J. R., & Twohig, M. P. (2015). Acceptance and commitment therapy for women diagnosed with binge eating disorder: A case-​series study. Cognitive and Behavioral Practice, 22(3), 367–​378. Juarascio A., Shaw J., Forman E., Timko C. A., Herbert J., Butryn M., Bunnell D., Matteucci A., Lowe M. (2013). Acceptance and commitment therapy as a novel treatment for eating disorders: an initial test of efficacy and mediation. Behavior Modification, 37, 459–​489. Juarascio, A. S., Manasse, S. M., Espel, H. M., Schumacher, L. M., Kerrigan, S., & Forman, E. M. (2017, in press). A

348

Dialectical Behavior Therapy

pilot study of an acceptance-​based behavioral treatment for binge eating disorder. Journal of Contextual Behavioral Science. Keel, P. K., & Brown, T. A. (2010). Update on course and outcome in eating disorders. International Journal of Eating Disorders, 43, 195–​204. Koons, C. R., Robins, C. J., Tweed, J. L., Lynch, T. R., Gonzalez, A. M., Morse, J. Q.,  . . .  Bastian, L. A. (2001). Efficacy of dialectical behavior therapy in women veterans with borderline personality disorder. Behavior Therapy, 32, 371–​390. Lieb, K., Zanarini, M. C., Schmahl, C., Linehan, M. M., & Bohus, M. (2004). Borderline personality disorder. Lancet, 364, 453–​461. Linehan, M. M. (1993a). Cognitive-​behavioral treatment of borderline personality disorder. New York, NY: Guilford Press. Linehan, M. M. (1993b). Skills training manual for treating borderline personality disorder. New York, NY: Guilford Press. Linehan, M. M. (2014). DBT® skills training manual. Second edition. New York, London: Guilford Press. Linehan, M. M., Armstrong, H. E., Suarez, A., Allmon, D., & Heard, H. L. (1991). Cognitive-​ behavioral treatment of chronically parasuicidal borderline patients. Archives of General Psychiatry, 48, 1060–​1064. Linehan, M. M., & Chen, E. Y. (2005). Dialectical behavior therapy for eating disorders. In S. Felgoise, A. M. Nezu, C. M. Nezu, M. A. Reinecke, & A. Freeman (Eds.), The encyclopedia for cognitive-​ behavioral therapy. New  York, NY: Springer. Linehan, M. M., Comtois, K. A., Murray, A. M., Brown, M. Z., Gallop, R. J., Heard, H. L.,  . . .  Lindenboim N. (2006). Two-​year randomized controlled trial and follow-​up of dialectical behavior therapy vs. therapy by experts for suicidal behaviors and borderline personality disorder. Archives of General Psychiatry, 63, 757–​766. Linehan, M. M., & Dimeff, L. A. (1997). Dialectical behavior therapy manual of treatment interventions for drug abusers with borderline personality disorder. Unpublished manuscript. University of Washington Seattle, WA. Linehan, M. M., Dimeff, L. A., Reynolds, S. K., Comtois, K. A., Welch, S. S., Heagerty, P., & Kivlahan, D. R. (2002). Dialectical behavior therapy versus comprehensive validation therapy plus 12-​step for the treatment of opioid dependent women meeting criteria for borderline personality disorder. Drug and Alcohol Dependence, 67, 13–​26. Linehan, M. M., Heard, H. L., & Armstrong, H. E. (1993). Naturalistic follow-​up of a behavioral treatment for chronically parasuicidal borderline patients. Archives of General Psychiatry, 50, 971–​974. Linehan, M. M., Schmidt, H., III, Dimeff, L. A., Craft, J. C., Kanter, J., & Comtois, K. A. (1999). Dialectical behavior therapy for patients with borderline personality disorder and drug-​dependence. American Journal of Addiction, 8, 279–​292. Linehan, M. M., Tutek, D. A., Heard, H. L., & Armstrong, H. E. (1994). Interpersonal outcome of cognitive behavioral treatment for chronically suicidal borderline patients. American Journal of Psychiatry, 151, 1771–​1776. Lingswiler, V. M., Crowther, J. H., & Stephens, M. A. (1987). Emotional reactivity and eating in binge eating and obesity. Journal of Behavioral Medicine, 10, 287–​299.

Lynch, T. R., Cheavens, J. S., Cukrowicz, K. C., Thorp, S. R., Bronner, L., & Beyer, J. (2007). Treatment of older adults with comorbid personality disorder and depression:  A  dialectical behavior therapy approach. International Journal of Geriatric Psychiatry, 22, 131–​143. Lynch, T. R., Gray, K. H., Hempel, R. J., Titley, M., Chen, E. Y., & O’Mahen, H. A. (2013). Radically open-​dialectical behavior therapy for adult anorexia nervosa: Feasibility and outcomes from an inpatient program. BMC Psychiatry, 13, 293. doi:10.1186/​1471-​244X-​13-​293 Lynch, T. R., Morse, J. Q., Mendelson, T., & Robins, C. J. (2003). Dialectical behavior therapy for depressed older adults:  A  randomized pilot study. American Journal of Geriatric Psychiatry, 11, 33–​45. Marlatt, G., & Gordon, J. R. (1985). Relapse prevention and maintenance strategies in the treatment of addictive behaviours. New York, NY: Guilford Press. Masheb, R. M., & Grilo, C. M. (2006). Emotional overeating and its associations with eating disorder psychopathology among overweight patients with binge eating disorder. International Journal of Eating Disorders, 39, 141–​146. Masson, P. C., von Ranson, K. M., Wallace, L. M., & Safer, D. L. (2013). A randomized wait-​list controlled pilot study of dialectical behaviour therapy guided self-​help for binge eating disorder. Behaviour Research and Therapy, 51, 723–​728. doi:10.1016/​j.brat.2013.08.001 McMain, S. F., Links, P. S., Gnam, W. H., Guimond, T., Cardish, R. J., Korman, L., & Streiner, D. L. (2009). A randomized trial of dialectical behavior therapy versus general psychiatric management for borderline personality disorder. American Journal of Psychiatry, 166, 1365–​1374. Palmer, R. L., Birchall, H., Damani, S., Gatward, N., McGrain, L., & Parker, L. (2003). A dialectical behavior therapy program for people with an eating disorder and borderline personality disorder:  Description and outcome. International Journal of Eating Disorders, 33, 281–​286. Parling, T., Cernvall, M., Ramklint, M., Holmgren, S., & Ghaderi, A. (2016). A randomised trial of acceptance and commitment therapy for anorexia nervosa after daycare treatment, including five-​year follow-​up. BMC Psychiatry, 16, 272. Polivy, J., & Herman, C. P. (1993). Etiology of binge eating: Psychological mechanisms. In C. G. Fairburn & G. T. Wilson (Eds.), Binge eating: Nature, assessment, and treatment (pp. 173–​205). New York, NY: Guilford Press. Rathus, J. H., & Miller, A. L. (2002). Dialectical behavior therapy adapted for suicidal adolescents. Suicide and Life Threatening Behaviors, 32, 146–​157. Safer, D. L., Robinson, A. H., & Jo, B. (2010). Outcome from a randomized controlled trial of group therapy for binge eating disorder: Comparing dialectical behavior therapy adapted for binge eating to an active comparison group therapy. Behavior Therapy, 41, 106–​120. Safer, D. L., Telch, C. F., & Agras, W. S. (2001a). Dialectical behavior therapy for bulimia nervosa. American Journal of Psychiatry, 158, 632–​634. Safer, D. L., Telch, C. F., & Agras, W. (2001b). Dialectical behavior therapy adapted for bulimia: A case report. International Journal of Eating Disorders, 30, 101–​106. Safer, D. L., Telch, C. F., & Chen, E. Y. (2009). Dialectical behavior therapy as adapted for binge eating disorder and bulimia. New York, NY: Guilford Press.

Sanftner, J. L., & Crowther, J. H. (1998). Variability in self-​ esteem, moods, shame, and guilt in women who binge. International Journal of Eating Disorders, 23, 391–​397. Stice, E., & Agras, W. S. (1999). Subtyping bulimic women along dietary restraint and negative affect dimensions. Journal of Consulting and Clinical Psychology, 67, 460–​469. Svirko, E., & Hawton, K. (2007). Self-​injurious behavior and eating disorders:  The extent and nature of the association. Suicide and Life-​Threatening Behavior, 37, 409–​421. Tchanturia, K. (2011). A brief emotion focused intervention for inpatients with anorexia nervosa: a qualitative study. Journal of health psychology, 16, 947–​958. Telch, C. F. (1997a). Emotion regulation skills training treatment for binge eating disorder:  Therapist manual. Unpublished manuscript. Stanford University. Telch, C. F. (1997b). Skills training treatment for adaptive affect regulation in a woman with binge-​eating disorder. International Journal of Eating Disorders, 22, 77–​81. Telch, C. F., Agras, W. S., & Linehan, M. M. (2000). Group dialectical behavior therapy for binge-​eating disorder: A preliminary, uncontrolled trial. Behavior Therapy, 31, 569–​582. Telch, C. F., Agras, W. S., & Linehan, M. M. (2001). Dialectical behavior therapy for binge eating disorder. Journal of Consulting and Clinical Psychology, 69, 1061–​1065. Turner, R. M. (2000). Naturalistic evaluation of dialectical behavior therapy-​ oriented treatment for borderline-​ personality disorder. Cognitive Behavioral Practice, 7, 413–​419. van den Bosch, L. M., Verheul, R., Schippers, G. M., & van den Brink, W. (2002). Dialectical behavior therapy of borderline patients with and without substance use problems:  Implementation and long-​ term effects. Addictive Behaviors, 27, 911–​923. Van Dijk, S., Jeffrey, J., & Katz, M. R. (2013). A randomized, controlled, pilot study of dialectical behavior therapy skills in a psychoeducational group for individuals with bipolar disorder. Journal of Affective Disorders, 145, 386–​393. Verheul, R., Van Den Bosch, L. M., Koeter, M. W., De Ridder, M. A., Stijnen, T., & Van Den Brink, W. (2003). Dialectical behavior therapy for women with borderline personality disorder:  12-​ month, randomised clinical trial in The Netherlands. British Journal of Psychiatry, 182, 135–​140. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect:  The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–​1070. Whiteside, U., Chen, E. Y., Neighbors, C., Hunter, D., Lo, T., & Larimer, M. E. (2007). Binge eating and emotion regulation: Do binge eaters have fewer skills to modulate and tolerate negative affect? Eating Behaviors, 8, 162–​169. Wildes, J. E., Marcus, M. D., Cheng, Y., McCabe, E. B., & Gaskill, J. A. (2014). Emotion acceptance behavior therapy for anorexia nervosa: A pilot study. International Journal of Eating Disorders, 47, 870–​873. Wilfley, D. E., Agras, W., Telch, C. F., Rossiter, E. M., Schneider, J. A., Cole, A. G.,   .  .  .  Raeburn, S. D. (1993). Group cognitive-​behavioral therapy and group interpersonal psychotherapy for the nonpurging bulimic individual:  A  controlled comparison. Journal of Consulting and Clinical Psychology, 61, 296–​305. Wilfley, D. E., Friedman, M. A., Dounchis, J. Z., Stein, R. I., Welch, R. R., & Ball, S. A. (2000). Comorbid

Chen, Yiu, Safer

349

psychopathology in binge eating disorder: Relation to eating disorder severity at baseline and following treatment. Journal of Consulting and Clinical Psychology, 68, 641–​649. Wilfley, D. E., Welch, R., Stein, R. I., Spurrell, E. B., Cohen, L. R., Saelens, B. E.,  . . .  Matt, G. E. (2002). A randomized comparison of group cognitive-​behavioral therapy and group

350

Dialectical Behavior Therapy

interpersonal psychotherapy for the treatment of overweight individuals with binge-​eating disorder. Archives of General Psychiatry, 59, 713–​721. Wnuk, S. M., Greenberg, L., & Dolhanty, J. (2015). Emotion-​ focused group therapy for women with symptoms of bulimia nervosa. Eating Disorders, 23, 253–​261.



CH A PT E R

 Self-​Help and Stepped Care Treatments for Eating Disorders

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Carol B. Peterson, Emily M. Pisetsky, and Caroline E. Haut

Abstract This chapter provides an overview of self-​help and guided self-​help treatments for eating disorders as well as stepped care models for treatment delivery. Empirical evidence suggests that although guided self-​help approaches may have relatively higher efficacy and retention rates than self-​help treatment, data from comparison trials are inconsistent. Robust treatment predictors, moderators, and mediators have not been identified other than rapid response as a predictor of outcome for cognitive-​behavioral guided self-​help, which may be useful in informing stepped care treatment. Stepped care models have received some empirical support and, in addition to potentially reducing treatment costs, may enhance efficacy by providing individuals who are not responsive to initial treatments with alternative or adjunctive interventions. Research using adaptive and tailored designs for treatment is needed to improve treatment efficacy and dissemination. Further research is needed in cost-​efficacy, implementation, clinician training models, and patient preferences and acceptability. Key Words:  self-​help, guided self-​help, stepped care, early response, treatment scalability

Outpatient treatment for eating disorders has historically involved traditionally delivered psychotherapy and/​ or pharmacotherapy in clinical settings. However, stepped care models were proposed given the difficulty in determining at the start of treatment which patients will benefit the most from which type of treatment (Fairburn & Peveler, 1990; Wilson, Vitousek, & Loeb, 2000). The potential efficacy of self-​help (SH) and guided self-​ help (GSH) interventions as components of stepped care treatment as well as stand-​alone interventions for eating disorders has paralleled findings in other areas of psychopathology treatment including depression and anxiety (Cuijpers, Donker, van Straten, Li, & Andersson, 2010). As the eating disorder treatment field has evolved, SH and GSH interventions have accumulated growing empirical support, demonstrating their potential efficacy in treating certain types of eating disorder symptoms

including binge eating and purging behaviors, and are included in the treatment recommendations provided by the National Institute of Clinical Excellence (NICE, 2004). Paralleling the accumulating body of research supporting SH and GSH as well as stepped care approaches, an increasing focus on identifying stepped care models of eating disorder treatment has been driven by the need for cost-​ effective delivery of evidence-​based treatments in the context of increasing healthcare costs. Stepped care models that do not involve SH/​GSH but follow algorithms based on predicted response/​ nonresponse in directing alternative and adjunctive treatments (e.g., combining psychotherapy and medication using specific sequences) may also improve treatment efficacy and reduce attrition. Self-​help and GSH treatments, whether administered in the context of stepped care treatment

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or independently, have the potential advantage of increasing treatment accessibility to eating disorder patients because of scalability and reduced treatment costs. As summarized by Perkins, Murphy, Schmidt, and Williams (2006), these approaches may also increase self-​efficacy, reduce treatment delays, minimize barriers to treatment associated with shame related to eating disorder symptoms, reinforce and consolidate learning, and allow the patient to access treatment resources in the case of symptom lapse or relapse (Perkins et al., 2006). Alternatively, limitations of SH and GSH include the risk of medical instability and/​or suicidality with intermittent or minimal clinical interaction; the potential inaccessibility of reading materials to individuals with learning disabilities, cognitive impairments, or language barriers; and patient preference for treatments that incorporate more frequent clinical contact.

Self-​Help and Guided Self-​Help Treatment

Although emerging interventions incorporate technology-​ based sources of treatment delivery (see c­ hapters 27 and 28), the majority of research investigating SH and GSH for eating disorders treatment has relied on written information in the form of books and has been administered individually. In most SH studies, participants are provided with treatment materials that they read and review on their own. In contrast, GSH treatment research has typically involved a nonspecialist clinician meeting briefly with the participant to provide support, encouragement, and information as an adjunct to the written SH materials. Several research trials have incorporated SH and GSH into stepped care designs. Each of these research areas is described in what follows, along with recommendations for future directions and clinical implications.

Overcoming Binge Eating

The SH treatment manual that has received the most empirical support is Overcoming Binge Eating (Fairburn, 1995), which can be delivered either as pure SH or GSH (typically referred to as CBTgsh when GSH used with this particular manual) with a trained practitioner reviewing progress and outcomes. Adapted from cognitive-​behavioral therapy (CBT; Fairburn, Marcus, & Wilson, 1993), the self-​ help manual includes two sections. The first provides psychoeducational information about binge eating, and the second specifies cognitive-​behavioral 352

strategies including monitoring eating behavior, planning meals and snacks, identifying behavioral alternatives to binge eating, reducing dietary restraint, and using problem-​ solving strategies (of note, an updated version of this manual includes additional information about weight and shape concerns; Fairburn, 2013). Earlier research using the Fairburn (1995) manual compared “pure” SH with CBTgsh among participants with bulimia nervosa (BN), binge eating disorder (BED), or mixed diagnostic samples (Carter & Fairburn, 1998; Ghaderi & Scott, 2003; Ghaderi, 2006; Loeb, Wilson, Gilbert, & Labouvie, 2000; Palmer, Birchall, McGrain, & Sullivan, 2002). Although no significant differences between groups were observed in several of these studies (see treatment review section below), Loeb et al. (2000) observed that GSH had a significantly greater reduction in binge eating frequency in comparison with SH, and two studies found higher attrition in SH compared with GSH (Carter, 1998; Palmer et al., 2002). Randomized studies comparing GSH using the Fairburn (1995; CBTgsh) manual with other treatments have found that CBTgsh is generally comparable or superior to other treatment conditions. Striegel-​Moore et  al. (2010) found that CBTgsh was associated with better binge eating outcome compared with treatment as usual in a health maintenance organization setting. Grilo and Masheb (2005) observed that CBTgsh produced significant improvements in binge eating remission compared with SH behavioral weight loss and also had fewer dropouts. Wilson, Wilfley, Agras, and Bryson (2010) found that CBTgsh produced comparable reductions in binge eating compared with interpersonal therapy (IPT) at 2-​year follow-​up and that both of these treatments were superior to behavioral weight loss (Wilson et al., 2010). In a primary care study, 104 obese patients with BED were randomized to sibutramine, placebo, SH using the Fairburn (1995) manual (shCBT) plus placebo, or shCBT plus sibutramine (Grilo et  al., 2014). Although the shCBT group had lower binge eating frequency at the 6-​month assessment, no other treatment differences were observed and treatment effects were modest. These findings replicated an earlier study showing modest effects of shCBT for binge eating in primary care (Grilo, White, Gueorguieva, Barnes, & Masheb, 2013). Similarly, in another primary care study involving participants with BN that compared fluoxetine or placebo with or without CBTgsh, attrition for the CBTgsh condition was extremely high (71%; Walsh, Fairburn,

Self-Help and Stepped Care Treatments

Mickley, Sysko, & Parides, 2004). Although outcome for fluoxetine was better than placebo, CBTgsh did not appear to provide any additive effect to medication for treatment outcome.

Getting Better Bit(e) by Bit(e) 1993

Several earlier trials compared a different SH treatment manual, Getting Better Bit(e) by Bit(e) (Schmidt & Treasure, 1993) in randomized designs. Treasure and colleagues (1994) compared this SH manual to CBT and wait-​list control in a sample of 81 adults with symptoms of BN. The CBT condition was associated with more reductions in self-​induced vomiting than the SH condition, but both treatments showed comparable reductions in binge eating and other eating disorder symptoms as well as remission rates (22%–​24% compared with 11% of the wait-​list group; Treasure et al., 1994). In a follow-​up sequential treatment study for BN (Treasure et al., 1996), the SH treatment followed by an abridged CBT (if needed) was compared with a standard CBT treatment. No differences were observed in outcome between the two conditions, and remission rates were comparable (30%). This treatment manual was also used in a randomized trial for adolescent BN comparing GSH with family therapy based on the Maudsley approach (Schmidt et al., 2007). Although GSH was preferred by the adolescent participants and associated with better outcome at the 6-​month assessment, no differences between the two treatments were observed at 1-​ year follow-​up, with abstinent rates ranging from 36% to 41%; direct costs of treatment were lower for GSH.

Psychoeducational Videotapes

Although most SH and GSH studies have used individual delivery models, a group design was used in a comparison study conducted by Peterson, Mitchell, Crow, Crosby, and Wonderlich (2009) based on the rationale that groups have the advantages of interpersonal support and further cost reduction. Participants with BED were randomized to SH, therapist-​ led, or therapist-​ assisted group CBT (or wait-​list). The therapist-​ led condition began with the therapist providing psychoeducation during the first half of each session followed by homework review and discussion. The therapist-​ assisted and SH groups watched a psychoeducational video during the first half and participated in either a therapist-​led (for the therapist-​ assisted condition) or self-​ led (for the SH condition) discussion and homework review.

At end of treatment, therapist-​led and therapist-​ assisted conditions were associated with higher binge eating abstinence rates than the SH condition, and all three groups were superior to the wait-​list control condition; however, there were no differences between the treatment conditions at 6-​month or 12-​month follow-​up. In addition, the therapist-​led group had a significantly higher proportion of participants complete the treatment compared with therapist-​assisted and SH groups (Peterson et al., 2009). Although the inclusion of a therapist produced better treatment response initially, this difference was not sustained at follow-​ up, and abstinence rates were modest.

Systematic Reviews and Meta-​Analyses

Perkins et  al. (2006) conducted a review of 15 studies using SH and GSH among adults with BED, BN, and eating disorder not otherwise specified (EDNOS). The authors found that when analyzed as a group, these treatments did not differ significantly from wait-​list conditions in symptom abstinence at end of treatment. However, SH and GSH were associated with significant reductions in eating disorder symptoms, interpersonal functioning, and some comorbid psychiatric symptoms (not including depression). The authors concluded that, compared with other treatments including therapist-​delivered psychotherapies, SH and GSH did not differ significantly at end of treatment or follow-​up on any outcome measure including attrition (Perkins, et al., 2006). The same year, Stefano, Bacaltchuk, Blay, and Hay (2006) published a meta-​analysis of 9 SH and GSH studies for BN and BED that met inclusion criteria for relevance and quality. In contrast to the Perkins et al. (2006) review, the authors concluded that participants who received any type of SH or GSH had better outcomes compared with wait-​list control conditions (Stefano et al., 2006). However, GSH was not clearly superior to SH. Both the Perkins et al. (2006) and Stefano et al. (2006) reviews cited significant limitations in the research literature. Although these reviews were conducted a decade ago, many of these criticisms remain relevant, including the exclusion of males from research trials, the inconsistencies in clinician training, and the fact that many of these studies (particularly the earlier ones) are underpowered. In addition, the inconsistencies in the findings between the two reviews may be the result of combining studies using different types of self-​help manuals, treatment designs, and assessment measures. Peterson, Pisetsky, Haut

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Treatment Predictors, Moderators, and Mediators

The identification of treatment moderators and predictors of outcome has the potential of increasing efficacy by pairing specific treatments with individuals who are most likely to respond to them. Identifying treatment mediators may facilitate enhanced efficacy through the understanding and targeting of mechanisms of action. Recently, Hilbert, Hildebrandt, Agras, Wilfley, and Wilson (2015) demonstrated that in contrast to behavioral weight loss and IPT in a randomized trial, rapid response, defined as greater than or equal to 70% reduction in binge eating by week 4, among participants receiving CBTgsh predicted short-​and long-​ term treatment outcome in BED (Hilbert et  al., 2015). Similarly, rapid response was the only significant predictor of treatment outcome among adult females with bulimic symptoms receiving CBTgsh (Vaz, Conceição, & Machado, 2014). Masheb and Grilo (2007) observed that rapid response was a significant predictor of outcome for CBTgsh and behavioral weight loss in terms of eating disorder pathology and binge eating remission; however, binge eating frequency was comparable between rapid responders and nonrapid responders in the CBTgsh condition. In a follow-​up analyses of their 2014 primary care study, Grilo, White, Masheb, and Gueorguieva (2015) found that rapid response was a robust predictor of outcome and suggested that these findings support the use of self-​help and medication treatment in the context of stepped care designs, in spite of their modest outcome in the main treatment outcome analyses (Grilo et al., 2015). In their treatment comparison trial, Wilson et al. (2010) found that CBTgsh was less efficacious for participants with greater eating disorder symptoms combined with low self-​esteem at baseline, who responded better to IPT. Using the same data set, Sysko, Hildebrandt, Wilson, Wilfley, and Agras (2010) conducted an empirical classification using latent class analysis and observed that CBTgsh had the highest efficacy for the class characterized by a greater frequency of binge eating episodes along with lower frequency of other eating disorder symptoms including purging (Sysko et al., 2010).

Summary

In summary, the results of the SH and GSH studies for the treatment of bulimic and binge eating symptoms are not straightforward. Although literature reviews often conclude that GSH is superior to SH, the data are inconsistent and the extent to 354

which any group differences are enduring is unclear. Similarly, although self-​help approaches appear to be comparable to other treatments when compared in randomized trials, these findings are not clearly robust. An additional uncertainty is the extent to which SH and GSH are acceptable to patients with eating disorders and if they are associated with higher rates of attrition. Nonetheless, overall, the research literature suggests that SH and GSH are promising for the outpatient treatment of binge eating and bulimic symptoms among adults and, possibly, adolescents. One clearly robust finding is that research participants who do not respond to CBT or CBTgsh as evidenced by a significant reduction in eating disorder behaviors (i.e., binge eating and/​or purging) by the end of the first month in treatment should be offered alternative or adjunctive treatments, as described below in the stepped care section. Other robust predictors and moderators for SH and GSH have not been identified. Another notable finding is that a minority and, perhaps, a sizable minority of outpatients with eating disorder symptoms characterized by binge eating (with or without purging) may remit with SH or GSH without the need for additional care. Finally, the findings of the Wilson et al. (2010) study are particularly important in highlighting that the 10-​session CBTgsh treatment produced comparable overall findings to a longer and more time intensive psychotherapy treatment, IPT, and that these effects endured through follow-​up. The implications are particularly important for cost-​ effectiveness as well as treatment access and potential scalability.

Stepped Care Treatment

The most rigorous BN stepped care study conducted in the eating disorders field is a multisite randomized trial in which participants were randomized to one of two conditions (Mitchell et al., 2011). In the CBT condition, participants received individual CBT (Fairburn et al., 1993) followed by the offer of adjunctive fluoxetine if they were still symptomatic after 6 sessions. In the stepped-​care condition, CBTgsh was followed by adjunctive fluoxetine and, if needed, individual CBT. Although remission rates were comparable at 1-​year follow-​ up for CBT (44%) and stepped care (32%), the stepped care condition had more significant reductions in binge eating and compensatory behavior as well as comorbid symptoms including depression. In addition, participants classified as treatment

Self-Help and Stepped Care Treatments

nonresponders at week 4 had higher abstinence rates in the stepped care (25%) than the CBT (4%) condition. The stepped care treatment was also more cost-​ effective (Crow, Agras, Fairburn, Mitchell, & Nyman, 2013). This study highlights the potential value of stepped care treatment for BN, especially the importance of providing alternative and/​or adjunctive treatment after 1 month for individuals receiving cognitive-​behavioral interventions who are not exhibiting significant reductions in symptoms. These findings are consistent with earlier work demonstrating that sequencing full IPT or medication trials for individuals who were not responsive to a full sequence of CBT did not yield significant improvement in treatment outcome and was associated with high rates of attrition (Mitchell et  al., 2002). Most other stepped care treatment research in eating disorders has not involved randomized designs. In a description of a clinically based stepped care model for bulimic symptoms in a specialized clinic, for example, Ramklint and colleagues observed that the majority of the participants were deemed suitable upon screening to receive CBTgsh initially and that the overall treatment outcome effect sizes were relatively larger for those who completed more CBTgsh sessions (Ramklint, Jeansson, Holmgren, & Ghaderi, 2012). Although attrition was significant, the authors suggest that CBTgsh may be helpful for approximately 30% of their sample. Emerging data support stepped care approaches for BED treatment (Amianto, Ottone, Daga, & Fassino, 2015). As noted by Hilbert et al. (2015), CBTgsh followed by interpersonal therapy for individuals who do not show rapid response (as defined by 70% or greater reduction in binge eating by week 4) may be an optimal stepped care design for the treatment of binge eating (Hilbert et al., 2015).

Specific Stepped Care Models

Most proposals of stepped care models for eating disorders advocate for CBT/​ CBTgsh as the first step in treatment (e.g., Dalle Grave, Ricca, & Todesco, 2001) and suggest incorporating the prediction of response or nonresponse to CBT or CBTgsh after the first month of treatment to guide treatment selection, with adjunctive or alternative treatment provided based on degree of symptom response (e.g., +/​-​65%–​70% reduction in binge eating). Consistent with Mitchell and colleagues (2011), adjunctive treatment may include medication. Alternative treatments after CBT/​CBTgsh nonresponse include IPT or dialectical behavior

therapy. Additional proposed alternative/​adjunctive treatments include mindfulness, appetite awareness training, and exercise as well as behavioral weight loss following remission from binge eating (Iacovino, Gredysa, Altman, & Wilfley, 2012). Other potential models include the use of the overvaluation of shape and weight as a specifier for BED (Grilo et al., 2008) and the overvaluation of shape and weight combined with low self-​esteem (Iacovino et al., 2012).

Summary

For over three decades, researchers and clinicians in the field of eating disorders have been emphasizing the potential utility of stepped care approaches for treatment. The rationale for the use of stepped care treatment is well founded, considering the potential for improved treatment outcome, reduced clinical burden, and increased cost-​effectiveness. In addition, the robust finding that nonresponse to CBT and CBTgsh after the first month of treatment is predictive of short-​and longer-​term outcome is particularly useful for stepped care designs in which cognitive-​behavioral interventions are provided as the first step. Notably, however, limited data using randomized designs are available to support the use of specific stepped care models for eating disorders, and most of the proposed stepped care models have been speculative or based on preliminary clinical data. Clearly, more efficacy and effectiveness data are needed to determine optimal stepped care interventions for eating disorder treatment.

Future Directions

Based on current research and clinical care, future directions for eating disorders treatment using SH, GSH, and stepped care include five categories. The first research and clinical priority is improving outcome by advancing individualized care. Greater access to “big data” as well as other data resources will optimize the identification of algorithms to determine potential sequencing models for individuals with eating disorders in clinical settings. In addition, state-​of-​the-​art research designs for adaptive treatment include sequential multiple assignment for randomized treatment (SMART) and other tailored treatment models that are responsive to both baseline patient characteristics and initial treatment response can potentially increase efficacy while reducing costs (Norcross & Wampold, 2011). Incorporating SH/​ GSH interventions into these designs, along with technology-​based components, may be especially effective and is clearly needed Peterson, Pisetsky, Haut

355

to advance eating disorder treatment. In addition, advances in the use of neurobiological variables and genotypes, along with behavioral phenotypes, in determining individual patient characteristics in tailoring treatment may result in substantial improvements in treatment effectiveness. Notably, these identifiers are likely to be “transdiagnostic,” given the limitations in the current psychiatric nosology. The second priority is scalability and dissemination (Wilson & Zandberg, 2012). The use of SH and GSH interventions bypasses a number of barriers to mental health treatment in general and eating disorder treatment in particular. Applying principles of implementation science (e.g., Betancourt & Chambers, 2016) will be essential for maximizing and optimizing dissemination in the context of SH/​ GSH as well as stepped care models. Evidence-​based approaches to dissemination can be used to guide public health policy treatment and prevention of eating disorders and comorbid conditions (Becker, Plasencia, Kilpela, Briggs, & Stewart, 2014; Paxton, 2013). In addition, overlapping with the first two categories, cost effectiveness (see ­chapter  22) is a critical consideration in the advancement of SH/​ GSH and stepped care treatment. Although cost savings is presumed in these types of treatment, rigorous data are needed to demonstrate the impact of these types of interventions on healthcare costs and to build a foundation for adoption of these treatments into clinical settings. In addition to healthcare costs, research on the use of SH/​ GSH and stepped care treatment for eating disorders should use a broader range of outcome variables beyond eating disorder symptoms including quality of life, health outcomes, clinician preferences, and patient acceptability (Peterson, Becker, Treasure, Shafran, & Bryant-​Waugh, 2016). The issue of patient acceptance is particularly important given the lower ratings of CBTgsh compared to IPT in a randomized trial (Wilson, et  al., 2010), although other studies have found higher levels of participant acceptability of GSH (e.g., Mitchell, et al., 2011; Striegel-​Moore, et al., 2010). An additional limitation in the current research is the paucity of stepped care studies examining transdiagnostic and anorexia nervosa patients. One study that was conducted with anorexia nervosa indicates that stepped care approaches may be used based on patient preference to increase participation in intensive treatment (Tasca et  al., 2012). Similarly, the use of evidence-​based approaches such as family-​based treatment for anorexia nervosa may be appropriate for adaptation to stepped care models (e.g., adjunctive treatment could be considered with 356

predicted nonresponse after the first month of treatment) that do not include self-​help components, which may not be appropriate for individuals who are underweight and potentially medically compromised. Finally, research is needed to determine optimal training models for clinicians and paraprofessionals to deliver these types of treatments, as well as determining the scalability of these types of training programs (Wilson, 2011). Zandberg and Wilson (2013) describe optimal training for GSH clinicians, as well as the possibility that this treatment can be delivered effectively by individuals without advanced degrees. Clearly, training models need to be examined empirically, along with optimal characteristics of GSH clinicians. Within the context of training and scalability, risk assessment for medical instability and suicidality is crucial.

Conclusions

The literature suggests that both SH and GSH are promising for the outpatient treatment of binge eating and bulimic symptoms and some patients may remit with SH or GSH without the need for additional treatment. Thus, SH and GSH provide treatment options for individuals with binge eating that appear to be cost-​effective and highly scalable, which is crucial given the difficulties many patients experience accessing specialist care. However, more work is needed to increase patient acceptability and retention in these types of treatments. Additionally, the research on CBT-​ based approaches indicates that patients who do not exhibit a significant reduction in eating disorder behaviors by the end of the first month should be offered alternative or adjunctive treatments such as psychopharmacology or a different psychotherapeutic modality. More research in adaptive and tailored treatment designs is needed to determine the optimal interventions and to provide individualized treatment in a stepped-​ care approach. Overall, this body of research indicates that SH, GSH, and stepped-​care approaches are empirically supported alternatives to the traditional full course of psychotherapy and pharmacotherapy delivered in specialist clinical settings, which will allow more patients to access treatment and providers to determine effective treatments more quickly.

References

Amianto, F., Ottone, L., Daga, G. A., & Fassino, S. (2015). Binge-​eating disorder diagnosis and treatment:  A  recap in front of DSM-​5. BMC Psychiatry, 15, 1. Becker, C. B., Plasencia, M., Kilpela, L. S., Briggs, M., & Stewart, T. (2014). Changing the course of comorbid eating

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disorders and depression: What is the role of public health interventions in targeting shared risk factors? Journal of Eating Disorders, 2, 1. Betancourt, T. S., & Chambers, D. A. (2016). Optimizing an era of global mental health implementation science. JAMA Psychiatry, 73, 99–​100. Carter, J. C., & Fairburn, C. G. (1998). Cognitive–​behavioral self-​help for binge eating disorder: A controlled effectiveness study. Journal of Consulting and Clinical Psychology, 66, 616. Crow, S. J., Agras, W. S., Fairburn, C. G., Mitchell, J. E., & Nyman, J. A. (2013). A cost effectiveness analysis of stepped care treatment for bulimia nervosa. International Journal of Eating Disorders, 46, 302–​307. Cuijpers, P., Donker, T., van Straten, A., Li, J., & Andersson, G. (2010). Is guided self-​help as effective as face-​to-​face psychotherapy for depression and anxiety disorders? A  systematic review and meta-​analysis of comparative outcome studies. Psychological Medicine, 40, 1943–​1957. Dalle Grave, R., Ricca, V., & Todesco, T. (2001). The stepped-​ care approach in anorexia nervosa and bulimia nervosa: Progress and problems. Eating and Weight Disorders-​ Studies on Anorexia, Bulimia and Obesity, 6, 81–​89. Fairburn, C. G. (1995). Overcoming binge eating. New  York, NY: Guilford Press. Fairburn, C. G. (2013). Overcoming binge eating: The proven program to learn why you binge and how you can stop. New York. NY: Guilford Press. Fairburn, C. G., Marcus, M. D., & Wilson, G. T. (1993). Cognitive-​behavioral therapy for binge-​eating:  A  comprehensive treatment manual. In G. T. Wilson & C. G. Fairburn (Eds.), Binge eating:  Nature, assessment, and treatment (pp. 361–​404). New York, NY: Guilford Press. Fairburn, C. G., & Peveler, R. C. (1990). Bulimia nervosa and a stepped care approach to management. Gut, 31, 1220–​1222. Ghaderi, A. (2006). Attrition and outcome in self-​help treatment for bulimia nervosa and binge eating disorder: A constructive replication. Eating Behaviors, 7, 300–​308. Ghaderi, A., & Scott, B. (2003). Pure and guided self‐help for full and sub‐threshold bulimia nervosa and binge eating disorder. British Journal of Clinical Psychology, 42, 257–​269. Grilo, C. M., Hrabosky, J. I., White, M. A., Allison, K. C., Stunkard, A. J., & Masheb, R. M. (2008). Overvaluation of shape and weight in binge eating disorder and overweight controls:  Refinement of a diagnostic construct. Journal of Abnormal Psychology, 117, 414. Grilo, C. M., & Masheb, R. M. (2005). A randomized controlled comparison of guided self-​help cognitive behavioral therapy and behavioral weight loss for binge eating disorder. Behaviour Research and Therapy, 43, 1509–​1525. Grilo, C. M., Masheb, R. M., White, M. A., Gueorguieva, R., Barnes, R. D., Walsh, B. T.,   .  .  .  Garcia, R. (2014). Treatment of binge eating disorder in racially and ethnically diverse obese patients in primary care:  Randomized placebo-​controlled clinical trial of self-​help and medication. Behaviour Research and Therapy, 58, 1–​9. Grilo, C. M., White, M. A., Gueorguieva, R., Barnes, R. D., & Masheb, R. M. (2013). Self-​help for binge eating disorder in primary care: A randomized controlled trial with ethnically and racially diverse obese patients. Behaviour Research and Therapy, 51, 855–​861. Grilo, C. M., White, M. A., Masheb, R. M., & Gueorguieva, R. (2015). Predicting meaningful outcomes to medication and self-​help treatments for binge-​eating disorder in primary

care:  The significance of early rapid response. Journal of Consulting and Clinical Psychology, 83, 387. Hilbert, A., Hildebrandt, T., Agras, W. S., Wilfley, D. E., & Wilson, G. T. (2015). Rapid response in psychological treatments for binge eating disorder. Journal of Consulting and Clinical Psychology, 83, 649. Iacovino, J. M., Gredysa, D. M., Altman, M., & Wilfley, D. E. (2012). Psychological treatments for binge eating disorder. Current Psychiatry Reports, 14, 432–​446. Loeb, K. L., Wilson, G. T., Gilbert, J. S., & Labouvie, E. (2000). Guided and unguided self-​help for binge eating. Behaviour Research and therapy, 38, 259–​272. Masheb, R. M., & Grilo, C. M. (2007). Rapid response predicts treatment outcomes in binge eating disorder: Implications for stepped care. Journal of Consulting and Clinical Psychology, 75, 639–644. Mitchell, J. E., Agras, S., Crow, S., Halmi, K., Fairburn, C. G., Bryson, S., & Kraemer, H. (2011). Stepped care and cognitive-​ behavioural therapy for bulimia nervosa: Randomised trial. British Journal of Psychiatry, 198, 391–​397. Mitchell, J. E., Halmi, K., Wilson, G. T., Agras, W. S., Kraemer, H., & Crow, S. (2002). A randomized secondary treatment study of women with bulimia nervosa who fail to respond to CBT. International Journal of Eating Disorders, 32, 271–​281. National Institute for Clinical Excellence (NICE). (2004). Eating disorders: Core interventions in the treatment and management of anorexia nervosa, bulimia nervosa and related eating disorders. Leicester UK: British Psychological Society & Royal College of Psychiatrists. Norcross, J. C., & Wampold, B. E. (2011). What works for whom:  Tailoring psychotherapy to the person. Journal of Clinical Psychology, 67, 127–​132. Palmer, R. L., Birchall, H., McGrain, L., & Sullivan, V. (2002). Self-​help for bulimic disorders: A randomised controlled trial comparing minimal guidance with face-​to-​face or telephone guidance. British Journal of Psychiatry, 181, 230–​235. Paxton, S. J. (2013). Dissemination in the Internet age: Taming a wild thing. International Journal of Eating Disorders, 46, 525–​528. Perkins, S. S., Murphy, R. R., Schmidt, U. U., & Williams, C. (2006). Self‐help and guided self‐help for eating disorders. Cochrane Database of Systematic Reviews, 3, CD004191. Peterson, C. B., Becker, C. B., Treasure, J., Shafran, R., & Bryant-​ Waugh, R. (2016). The three-​legged stool of evidence-​based practice in eating disorder treatment: research, clinical, and patient perspectives. BMC Medicine, 14, 1. Peterson, C. B., Mitchell, J. E., Crow, S. J., Crosby, R. D., & Wonderlich, S. A. (2009). The efficacy of self-​help group treatment and therapist-​led group treatment for binge eating disorder. American Journal of Psychiatry, 166, 1347–​1354. Ramklint, M., Jeansson, M., Holmgren, S., & Ghaderi, A. (2012). Guided self‐help as the first step for bulimic symptoms: Implementation of a stepped‐care model within specialized psychiatry. International Journal of Eating Disorders, 45, 70–​78. Schmidt, U., Lee, S., Beecham, J., Perkins, S., Treasure, J., Yi, I.,  . . .  Johnson-​Sabine, E. (2007). A randomized controlled trial of family therapy and cognitive behavior therapy guided self-​care for adolescents with bulimia nervosa and related disorders. American Journal of Psychiatry, 164, 591–​598. Schmidt, U, & Treasure, J. (1993). Getting better bit(e) by bit(e). A survival kit for sufferers of bulimia nervosa and binge eating disorder. Hove, UK: Brunner-​Routledge.

Peterson, Pisetsky, Haut

357

Stefano, S. C., Bacaltchuk, J., Blay, S. L., & Hay, P. (2006). Self‐help treatments for disorders of recurrent binge eating: A systematic review. Acta Psychiatrica Scandinavica, 113, 452–​459. Striegel-​Moore, R. H., Wilson, G. T., DeBar, L., Perrin, N., Lynch, F., Rosselli, F., & Kraemer, H. C. (2010). Cognitive behavioral guided self-​help for the treatment of recurrent binge eating. Journal of Consulting and Clinical Psychology, 78, 312. Sysko, R., Hildebrandt, T., Wilson, G. T., Wilfley, D. E., & Agras, W. S. (2010). Heterogeneity moderates treatment response among patients with binge eating disorder. Journal of Consulting and Clinical Psychology, 78, 681. Tasca, G. A., Keating, L., Maxwell, H., Hares, S., Trinneer, A., Barber, A. M.,  . . .  Bissada, H. (2012). Predictors of treatment acceptance and of participation in a randomized controlled trial among women with anorexia nervosa. European Eating Disorders Review, 20, 155–​161. Treasure, J., Schmidt, U., Troop, N., Tiller, J., Todd, G., Keilen, M., & Dodge, E. (1994). First step in managing bulimia nervosa: Controlled trial of therapeutic manual. BMJ, 308, 686–​689. Treasure, J., Schmidt, U., Troop, N., Tiller, J., Todd, G., & Turnbull, S. (1996). Sequential treatment for bulimia

358

nervosa incorporating a self-​care manual. British Journal of Psychiatry, 168, 94–​98. Vaz, A. R., Conceição, E., & Machado, P. P. (2014). Early response as a predictor of success in guided self‐help treatment for bulimic disorders. European Eating Disorders Review, 22, 59–​65. Walsh, B. T., Fairburn, C. G., Mickley, D., Sysko, R., & Parides, M. K. (2004). Treatment of bulimia nervosa in a primary care setting. American Journal of Psychiatry, 161, 556–​561. Wilson, G. T. (2011). Treatment of binge eating disorder. Psychiatric Clinics of North America, 34, 773–​783. Wilson, G. T., Vitousek, K. M., & Loeb, K. L. (2000). Stepped care treatment for eating disorders. Journal of Consulting and Clinical Psychology, 68, 564. Wilson, G. T., Wilfley, D. E., Agras, W. S., & Bryson, S. W. (2010). Psychological treatments of binge eating disorder. Archives of General Psychiatry, 67, 94–​101. Wilson, G. T., & Zandberg, L. J. (2012). Cognitive-​behavioral guided self-​help for eating disorders: Effectiveness and scalability. Clinical Psychology Review, 32, 343–​357. Zandberg, L. J., & Wilson, G. T. (2013). Train-​ the-​ trainer:  Implementation of cognitive-​ behavioural guided self-​help for recurrent binge eating in a naturalistic setting. European Eating Disorders Review, 21, 230–​237.

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CH A PT E R

 Pharmacotherapy for Eating Disorders

19

Susan L. McElroy, Anna I. Guerdjikova, Nicole Mori, and Paul E. Keck Jr.

Abstract This chapter addresses the pharmacotherapy of the eating disorders (EDs). Many persons with EDs receive pharmacotherapy, but pharmacotherapy research for EDs has lagged behind that for other major mental disorders. This chapter first provides a brief rationale for using medications in the treatment of EDs. It then reviews the data supporting the effectiveness of specific medications or medication classes in treating patients with anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), and other potentially important EDs, such as night eating syndrome (NES). It concludes by summarizing these data and suggesting future areas for research in the pharmacotherapy of EDs. Key Words:  antidepressant, antiepileptic, drug, antipsychotic, eating disorder, mood stabilizer, pharmacotherapy, stimulant, weight, loss

Introduction

Many persons with eating disorders (EDs) receive pharmacotherapy (Fazeli et  al., 2012; Grigoriadis, Kaplan, Carter, & Woodside, 2001; Mond, Hay, Rodgers, & Owen, 2007; Walsh et al., 2006). An increasing number of reviews (Yager & Powers, 2007) and guidelines (Aigner et al., 2011; American Psychiatric Association [APA], 2006; Hay et  al., 2014; National Institute for Clinical Excellence, 2004) summarize the role pharmacotherapy might play in treating patients with EDs. However, only two drugs have regulatory approval for the treatment of an ED (fluoxetine for bulimia nervosa [BN] and lisdexamfetamine dimesylate [LDX] for binge eating disorder [BED]), and pharmacotherapy research for EDs lags behind that for other major mental disorders. Indeed, no drug has regulatory approval for the treatment of anorexia nervosa (AN), and no drug has yet been specifically developed to treat an ED. In this chapter, we review research with specific medications or medication classes in treating patients with AN, BN, BED, and other potentially important EDs, such as night eating syndrome

(NES). We then summarize these data and suggest future areas for research.

Rationale for Using Pharmacotherapy in Treating Eating Disorders

There are several rationales for using pharmacotherapy to treat EDs. First, EDs are major mental disorders with genetic etiologic contributions and neurobiological abnormalities that do not always respond adequately to available psychological interventions (Bulik et al., 2007; Slof-​Op’t Landt et al., 2005). Some patients, including those with chronic or intractable illness, may need medication for optimal outcomes (Yager, 2007). Second, medications that are effective in conditions related to EDs might be effective in EDs themselves, or might be useful in managing co-​occurring conditions in ED patients (Woodside & Staab, 2006). Third, many medications have effects on appetite and weight, as well as the central or peripheral systems important in regulating eating behavior and weight control. These include drugs being developed for mood, psychotic, and other mental disorders; cachexia and obesity; and epilepsy. Some of these agents may 359

prove to have beneficial psychotropic properties and/​or useful effects on appetite or weight regulation, and might therefore have therapeutic effects in ED patients, including the substantial portion who are inadequately responsive to current treatments.

Pharmacotherapy of Anorexia Nervosa

Two primary randomized controlled trial (RCT) designs have been used to evaluate medications in AN:  studies aimed to restore weight in acutely ill underweight patients (weight restoration trials) and those aimed to maintain weight gain in patients whose weight has been restored to some degree (relapse prevention or weight maintenance trials). The primary outcome in the former has usually been a measure of weight gain or time to a certain amount of weight gain; in the latter, it often has been time to or rate of relapse. However, varied primary outcome measures have been used in both types of trials. Secondary outcomes have included measures of ED psychopathology, depressive and/​ or anxiety symptoms, overall clinical improvement, and treatment acceptability. Various biomarkers in addition to weight have also been assessed, such as vital signs, endocrine parameters, gastric emptying, menstrual function, and bone density. Importantly, in most studies, pharmacotherapy was given in conjunction with inpatient, supportive, and/​ or specialist psychotherapeutic treatment, which could mitigate any efficacy signal from medication. The medications most commonly evaluated in AN for weight restoration in RCTs have been antidepressants, antipsychotics, and appetite stimulants (Table 19.1). The only medications evaluated in AN for weight maintenance in RCTs have been fluoxetine and recombinant human growth hormone (rhGH). Other medications evaluated in RCTs include prokinetics, zinc, hormonal agents, benzodiazepines, relamorelin, lithium, opioid antagonists, and d-​cycloserine.

Antidepressants

At least four randomized, placebo-​ controlled trials of antidepressants in acutely ill, underweight patients with AN have been published (Claudino et  al., 2006). In the first trial, amitriptyline, up to 175 mg/​day, did not differ from placebo in 25 youth, ages 11 to 17  years, on weight, eating, or mood outcomes (Biederman et  al., 1985). There were no dropouts. In the second trial, 72 female inpatients with AN, ages 13 to 26 years, were randomized to amitriptyline (n = 23), cyproheptadine (n = 24), or placebo (n = 25) (Halmi, Eckert, LaDu, 360

Pharmacotherapy

& Cohen, 1986). Seventeen (74%) amitriptyline-​ treated patients and 16 (64%) placebo-​ treated patients achieved target weight. Among patients who achieved target weight, excluding noncompleters, the daily rate of weight increase was numerically, but not statistically significantly, higher in the amitriptyline group. Significantly fewer days were needed to achieve target weight with amitriptyline than placebo. Attrition was 30% for amitriptyline and 20% for placebo. In the third trial, clomipramine 50 mg/​day was not associated with greater weight gain than placebo in 16 female inpatients with AN after an 11-​week acute phase of treatment, after which medication was discontinued, or at 1-​ year and 4-​year follow-​up evaluations (Crisp, Lacey, & Crutchfield, 1987). In the fourth trial, 31 female inpatients with AN (ages 16–​45  years) who had achieved 65% of ideal body weight were randomly assigned to fluoxetine, up to 60 mg/​day, or placebo for 7 weeks on a clinical research unit (Attia, Haiman, Walsh, & Flater, 1998). Average (SD) body mass index (BMI) at randomization was 15 mg/​kg (4.2). Mean (SD) fluoxetine dose at treatment endpoint was 56.0 (11.2) mg/​day. There were no significant differences between fluoxetine and placebo on weight gain, ED psychopathology, obsessive-​ compulsive symptoms, measures of depression or anxiety, or clinical global improvement. In 2006, Claudino et al. published a Cochrane review evaluating evidence of efficacy and acceptability of antidepressant treatment for weight restoration in AN from seven RCTs: the four above-​ noted studies that compared antidepressants to placebo (Attia et al., 1998; Biederman et al., 1985; Halmi et al., 1986; Lacey & Crisp, 1980) and three studies that compared different antidepressant drugs with one another (Brambilla, Draisci, Peirone, & Brunetta, 1995a, 1995b; Ruggiero et  al., 2001). Due to methodological limitations, aggregation of data for meta-​analysis was not possible for most outcomes. However, it was concluded that the studies were not able to show any effect of antidepressants compared to placebo in the majority of outcomes, including weight gain, ED symptoms, associated anxious and depressive symptoms, or clinical global improvement. In the three comparative studies, the only findings were a greater effect for amineptine (an atypical tricyclic that selectively inhibits dopamine and, to a lesser extent, norepinephrine reuptake) compared to fluoxetine in reducing end-​ of-​ treatment Eating Disorder Inventory (EDI) scores, and a greater effect of nortriptyline compared to fluoxetine in decreasing mean Hamilton

Table 19.1  Medications Studied for Anorexia Nervosa in Randomized, Placebo-​Controlled Trials: Qualitative Results Medication

Maximum Dosage Studied (mg/​day)

Effect on Weight Restoration

Effects on Psychological Symptoms

Effect on Weight Maintenance

 Amitriptyline

175

−

−

NDA

 Clomipramine

50

−

−

NDA

 Fluoxetine

60

−

−

+/​−

 Olanzapine

15

++

+/​−

NDA

 Pimozide

6

+/​−

NDA

NDA

 Quetiapine

178a

−

−

NDA

 Risperidone

4

−

−

−

 Sulpiride

400

−

NDA

NDA

32

+/​−

NDA

NDA

 Tetrahydrocannabinol

30

−

NDA

NDA

 Dronabinol

5

+

−

NDA

30

+/​−

+/​−

NDA

−

−

NDA

 Estradiol

100 mcg twice weekly −

−

NDA

 Oxytocin

40 IU

NDA

+

NDA

 rhGH

15 mg/​kg

−

NDA

NDA

 Testosterone

300μg

−

+/​−

NDA

 Alprazolam

.75

NDA

−

NDA

 Lithium

NDAb

+

+/​−

NDA

 Relamorelin

100μg

+/​−

NDA

NDA

 Zinc

100

+

NDA

NDA

Antidepressants

Antipsychotics

Appetite Stimulants  Cyproheptadine Cannabinoids

Prokinetics  Cisapride Hormonal Agents  Dehydroepiandrosterone 100 mg

Other Agents

Key: ++ = ≥ 2 positive RCTs; + = ≥1 positive RCT; +/​− = mixed results; − = ≥1 negative RCTs and no positive RCTs; NDA = no data available; rhGH = recombinant human growth hormone. a

Mean dose.

b

Mean plasma lithium level = 1.0 mEq/​L.

Anxiety Scale (HAM-​A) scores. These isolated findings were of unclear significance. Two randomized, placebo-​ controlled relapse prevention studies have been conducted with the selective serotonin-​reuptake inhibitor (SSRI) fluoxetine in AN. In the first trial, 35 patients (34 inpatients) with restricting-​type AN with or without purging behavior (none had displayed binge eating during their lifetime) who had been restored to 76% to 100% of average body weight (with most above 90%) were randomized prior to hospital discharge to fluoxetine (n  =  16) or placebo (n  =  19) for 52 weeks (Kaye et  al., 2001). Only patients with restricting-​type AN were included because of prior open-​label data suggesting this subtype might respond better to fluoxetine than bulimic-​type AN (Kaye, Weltzin, Hsu, & Bulik, 1991). Fluoxetine was initiated at 20 mg/​day and adjusted to a maximum of 60 mg/​day. Adjunctive outpatient psychotherapy was allowed but not required; the number of participants who received psychotherapy was not provided. Fluoxetine-​ recipients were more likely to complete the trial: 10 (63%) patients remained on fluoxetine for 1 year, whereas only three (16%) patients remained on placebo for that period of time (p = .006). Four groups were compared: fluoxetine completers (n = 10), fluoxetine noncompleters (n  =  6), placebo completers (n  =  3), and placebo noncompleters (n =16). These four groups did not show differences in weight, obsessive-​ compulsive ED symptoms, anxiety, or depression. However, by paired t test, only patients remaining on fluoxetine for 1  year showed a significant increase in weight and reduction in ED psychopathology and mood symptoms. In the second trial, 93 patients with AN who had regained weight to a minimum BMI of 19.0 mg/​ kg2 after intensive inpatient or day program treatment were randomized to outpatient fluoxetine (n = 49) or placebo (n = 44) for up to 1 year (Walsh et  al., 2006). All patients also received individual cognitive-​ behavioral therapy (CBT) specifically designed to prevent relapse. Similar percentages of fluoxetine recipients and placebo recipients maintained a BMI ≥ 18.5 mg/​kg2 and stayed in the study for 1  year (fluoxetine, 26.5%; placebo, 31.5%; p = .57). In addition, there was no significant difference between fluoxetine and placebo in time-​to-​ relapse (hazard ratio [HR] 1.12; 95% confidence interval [CI] 0.65, 2.01; p = .64). The authors concluded that their study failed to demonstrate any benefit from fluoxetine in the treatment of patients with AN after weight restoration. 362

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In an uncontrolled but randomized and prospective 1-​year study evaluating treatment acceptance of medication versus psychotherapy, 122 outpatients with AN who were within 75% of their target weight received fluoxetine 60 mg/​day alone, CBT alone, or the combination (Halmi et  al., 2005). Similar percentages (17%–​18%) of patients were withdrawn (primarily for treatment failure) from the three conditions. However, among the remaining patients, there were more noncompleters in the fluoxetine alone group (56%) than the CBT alone (40%) or the combination (41%) groups. The authors concluded that fluoxetine given alone had a very low treatment acceptance rate. In sum, taken together, these studies have led some to conclude that antidepressants are ineffective for promotion or maintenance of weight gain in patients with AN. However, it has also been noted that these trials have methodological shortcomings that limit their interpretation. These include the use of small sample sizes leading to inadequate power to detect potential differences in effects; use of patients in various stages of illness; use of narrow entry criteria that limit generalizability of findings; and use of antidepressants in combination with other interventions designed specifically to promote weight gain or prevent weight loss (Walsh et al., 2006). Thus, the possibility that fluoxetine might be effective for relapse prevention if given at a different stage of illness (i.e., after a longer period of weight restoration) or as a sole intervention (i.e., not as an adjunct to a structured psychotherapy designed to prevent relapse) cannot be excluded. Another consideration is that findings with one class of antidepressant (e.g., SSRIs) may not generalize to other classes. For example, there are reports of AN patients responding to the unique antidepressant mirtazapine, which enhances norepinephrine and serotonin (5-​HT) release; stimulates 5-​HT1 receptors; blocks 5-​HT2, 5-​HT3, and histamine H1 receptors; and is associated with increased appetite and weight gain (Hrdlicka, Beranova, Zamecnikova, & Urbanek, 2008; Jaafar, Daud, Rahman, & Baharudin, 2007). There are also reports of patients with treatment-​resistant AN responding to antidepressants when given in conjunction with other agents, such as antipsychotics, mood stabilizers, and other antidepressants (Fountoulakis, Iacovides, Siamouli, Koumaris, & Kaprinis, 2006; Newman-​Toker, 2000; Reilly, 1977; Wang, Chou, & Shiah, 2006) (see the sections that follow).

Antipsychotics

Two randomized, placebo-​controlled, crossover trials of first-​generation antipsychotics for weight restoration in patients with AN have been conducted. In the first, 18 female inpatients with AN based on criteria of the Diagnostic and Statistical Manual, 3rd Edition (DSM-​III) were randomized to receive a single dose of pimozide (4 or 6 mg) or placebo in alternating 3-​week periods (Vandereycken & Pierloot, 1982). All patients received concomitant behavior therapy. Mean changes in weight were positive with pimozide but negative with placebo. A  crossover analysis showed a trend for the pimozide group to be associated with more weight gain (p  =  .067). After the first 3-​week period, for example, patients receiving pimozide (n  =  8) had a mean daily weight gain of 135 grams, whereas those receiving placebo (n = 10) had a mean daily weight gain of 80 grams. In the second study, 18 female inpatients with DSM-​III AN were randomized to sulpiride (300 or 400 mg/​day) or placebo in alternating 3-​week periods (Vandereycken, 1984). Crossover analyses showed no direct effects of sulpiride on weight change, clinical scales, or self-​ report questionnaires. However, individual analysis of the data showed numerically greater weight gain in both periods with sulpiride than placebo, suggesting that, as in the first trial, negative findings could be due to small sample size and inadequate power. Second-​generation (atypical) antipsychotics have been reported effective for AN in open-​label reports in children, adolescents, and treatment-​ resistant patients (Dunican & DelDotto, 2007; Duvvuri, Cromley, Klabunde, Boutelle, & Kaye, 2012; Mehler-​ Wex, Romanos, Kirchheiner, & Schulze, 2008). Olanzapine has been the most commonly used drug, but positive reports of aripiprazole, quetiapine, and risperidone have also appeared (Aragona, 2007; Court et  al., 2010; Frank, 2016; Newman-​Toker, 2000; Powers, Bannon, Eubanks, & McCormick, 2007; Umehara, Iga, & Ohmori, 2014). These drugs have been described as helpful for weight restoration; for many of the core psychological symptoms of AN, such as fear of fatness, difficulty eating, distorted body image, obsessive-​ compulsive features, and poor insight; and for many of the associated symptoms of AN, including binge eating, purging, hyperactivity, delusionality, depression, anxiety, and mood instability. Six randomized, placebo-​ controlled trials of second-​ generation antipsychotics for weight restoration have been conducted in AN. In the first RCT, 30 female outpatients with DSM-​IV AN (18

with restricting-​type AN and 12 with binge eating-​ purging type AN) received olanzapine (2.5 mg/​day for 1 month, then 5 mg/​day for 2 months) or placebo, in addition to CBT (Brambilla et al., 2007). Body mass index increased significantly but similarly in both groups. There were also no differences between groups in improvements in Eating Disorder Inventory-​2 (EDI-​2) individual item or total values, Yale-​ Brown-​ Cornell Eating Disorder Scale (YBC-​EDS) obsessiveness or total values, or Buss-​ Durkee Scale (BDS) total values for aggressiveness. However, measures of rituals (on the YBC-​EDS), direct aggressiveness (on the BDS), depression, and persistence (on the Temperament and Character Inventory) improved significantly with olanzapine compared with placebo. Olanzapine was well tolerated, with mild sleepiness as the only side effect. When stratifying for AN subtype, changes in BMI, depression, and direct aggression were significant among binge eating-​purging type patients, whereas change in persistence was significant among restricting-​ type patients. It was concluded that olanzapine might improve different symptoms in different subtypes of AN. In the second study, 34 patients with AN receiving day treatment were randomized to receive flexible dose olanzapine (n  =  16) or placebo (n  =  18) for 10 weeks (Bissada, Tasca, Barber, & Bradwejn, 2008). Twenty-​eight patients (14 in each group) completed the trial. Compared with placebo, olanzapine was associated with a greater rate of increase in BMI (p = .03) and a greater rate of decrease in obsessive symptoms (p = .02). Of the total sample, 87.5% of olanzapine recipients achieved weight restoration, compared with 55.6% of placebo recipients (p  =  .02). There were no differences in reductions between the groups on measures of anxiety, depression, or compulsions. The mean (SD) olanzapine dose over the 10-​week treatment period for study completers was 6.61 (2.32) mg/​day. No differences in adverse effects were observed between the two treatment conditions. There were no serious adverse effects. In the third RCT, 23 outpatients with AN who were 16  years of age or older were randomized to receive olanzapine or placebo (Attia et  al., 2011). Study drug was administered with medication management sessions aimed to enhance compliance. Seventeen (74%) patients completed the trial. End-​ of-​treatment BMI, with initial BMI as covariate, was significantly greater in patients receiving olanzapine. Psychological symptoms improved in both groups with no significant differences. Olanzapine

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was well tolerated with no adverse metabolic effects; sedation was the most common side effect. In the fourth RCT, 20 adolescent females with AN receiving comprehensive eating disorder treatment were randomized to receive olanzapine or placebo (Kafantaris et  al., 2011). Fifteen patients completed the study. Mean olanzapine dose was 8.5 mg/​day at week 10. Change in percent median body weight improved similarly in both treatment groups at midpoint and endpoint. Olanzapine and placebo also produced similar improvements in eating pathology, psychological functioning, and resting energy expenditure. Olanzapine was associated with a trend of increasing fasting insulin and glucose levels at 10 weeks. In the fifth study, 40 female AN patients 12 to 21 years of age who were receiving treatment in a specialized eating disorder program were randomized to receive risperidone or placebo for 11 weeks (Hagman et al., 2011). Patients had to be actively engaged in the specialized eating disorder treatment program to be enrolled in the study. Risperidone (mean dose 2.5 mg/​day) was associated with a significantly greater reduction of drive for thinness on the Eating Disorder Inventory-​2 (EDI-​2) (Garner, 1991) over the first 7 weeks, but this difference was not sustained at week 11. Risperidone was also associated with a significantly greater decrease on the EDI-​2 Interpersonal Distrust Subscale. There were no drug-​placebo differences on any other measure of psychological symptoms. There were no changes between risperidone and placebo for change in ideal body weight or BMI: 33% of risperidone patients and 45% of placebo patients reached target weight and maintained it for 4 weeks. Side effects of risperidone were fatigue and dizziness. Prolactin levels were significantly increased in risperidone-​treated patients at weeks 7 and 11. In the sixth study, 15 participants with AN were randomized to receive quetiapine (n  =  6) or placebo (n  =  9) for 8 weeks (Powers, Klabunde, & Kaye, 2012). Ten patients completed the study. Quetiapine (mean daily dose 177.7 mg) was not superior to placebo in reducing core ED, depressive, or obsessional symptoms. Additionally, there was no difference in change in BMI between study groups. No controlled studies of antipsychotics for weight maintenance in AN have yet been published, but there are open-​label reports. For example, Cassano et  al. (2003) treated 13 outpatients with treatment-​ resistant restricting-​ type AN for 6 months with haloperidol in addition to standard therapy. Body mass index increased significantly 364

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from baseline (15.7 mg/​kg2 ± 1.9) to endpoint (18.1 mg/​kg2 ± 2.5; p = .03). Significant improvement was also observed on the EDI (p  =  .02), Eating Attitude Test (EAT; p = .009), and CGI-​I scale (p  =  .001) scores. There are also reports of antipsychotics being helpful in AN patients with serious comorbid neuropsychiatric and medical disorders, including schizotypal personality disorder (Nagata, Ono, & Nakayama, 2007), autism (Fisman, Steele, Short, Byrne, & Lavallee, 1996), and epilepsy with chronic renal failure (Aragona, 2007). Of note, because second-​generation antipsychotics may cause glucose intolerance in AN (possibly by inducing insulin resistance), it has been recommended that AN patients receiving treatment with olanzapine have their glucose metabolism closely monitored (Yasuhara, Nakahara, Harada, & Inui, 2007). All RCTs of antipsychotics in the treatment of AN are limited by small sample size and, hence, inadequate power to detect potential clinically significant differences. Negative trials (Hagman et al., 2011; Kafantaris et al., 2011; Powers et al., 2012) could therefore represent failed trials. Some negative trials are further limited by requiring participants to be receiving comprehensive psychosocial treatment (Hagman et  al., 2011; Kafantaris et  al., 2011); with small sample sizes, it may be difficult to show medication effects beyond those of psychosocial treatment. Indeed, the mixed findings have led to different conclusions on the usefulness of antipsychotics in AN. Four groups, conducting meta-​ analyses of RCTs of antipsychotics in AN, have concluded that antipsychotics are not efficacious for weight gain or psychological symptoms in AN (Dold, Aigner, Klabunde, Treasure, & Kasper, 2015; Kishi, Kafantaris, Sunday, Sheridan, & Correll, 2012; Lebow, Sim, Erwin, & Murad, 2013; de Vos et al., 2014). Other experts, however, have argued that olanzapine in particular may be efficacious, especially if it has to be administered alone without adjunctive psychosocial treatment (Brewerton, 2012). Indeed, authors of negative trials have qualified their findings by reporting that some AN patients do respond well to second-​generation antipsychotics (Dold et al., 2015; Powers et al., 2012).

Antidepressant–​Antipsychotic Combinations

Anorexia nervosa has similarities with psychotic depression including depressive symptoms, delusional thinking, and hypercortisolism (Monteleone et  al., 2001; Parsons & Sapse, 1985; Steinglass, Eisen, Attia, Mayer, & Walsh, 2007). Psychotic

depression is characterized by better response to antidepressant–​antipsychotic combination therapy than to antipsychotic monotherapy. No controlled studies of antidepressant–​antipsychotic combinations have been published in AN, but there are open-​label reports of patients reporting to such regimens. These include descriptions of treatment-​ resistant AN patients responding to the addition of a second-​generation antipsychotic to an antidepressant (Marzola et al., 2015; Newman-​Toker, 2000). There are also reports of AN patients with depressive symptoms responding to the combination of olanzapine and mirtazapine (Fountoulakis et al., 2006; Wang et al., 2006). Randomized controlled trials of combination antipsychotic and antidepressant therapy in the treatment of AN are greatly needed.

Appetite Stimulants

Two randomized, placebo-​ controlled trials of cyproheptadine, an antiallergy and appetite-​ stimulating drug with high affinity for various serotonin, histamine, dopamine, adrenergic, and muscarinic receptors (Goudie, Cooper, Cole, & Sumnall, 2007), have been conducted. In the first study, 81 female inpatients with AN were randomized to one of four treatment combinations of cyproheptadine (12–​32 mg/​day) or placebo with or without behavioral therapy (Goldberg, Halmi, Eckert, Casper, & Davis, 1979). Mean weight gain did not differ between the groups receiving cyproheptadine (5.11 kg) versus placebo (4.32 kg). However, in a subgroup analysis, cyproheptadine was superior to placebo for weight gain in patients with a history of two or more birth delivery complications compared to those with none. In the second study, 72 female inpatients with AN were randomized to cyproheptadine (n = 24), amitriptyline (n = 23), or placebo (n = 25) (Halmi et  al., 1986). Eighty-​three percent of cyproheptadine recipients versus 64% of placebo recipients achieved their target weights. Among these patients, significantly fewer days were required to achieve target weight with cyproheptadine (mean [SD] = 36.5 [19.5]) than placebo (mean [SD]  =  45.0[18.3]; p < .05). In addition, cyproheptadine significantly increased treatment efficiency in the nonbulimic patients and significantly decreased treatment efficiency in the bulimic patients. (Treatment efficacy was the reciprocal of the number of days to target weight times the constant 90, the maximal length of treatment.) Attrition was 25% for cyproheptadine and 20% for placebo.

Cannabinoids

Two RCTs have examined cannabinoids in AN. In the first, a 4-​ week, double-​ blind, diazepam-​ controlled, crossover study in 11 female patients, tetrahydrocannabinol and diazepam were associated with comparable amounts of weight gain (Gross et  al., 1983). Patients had greater somatization, interpersonal sensitivity, and sleep disturbance during tetrahydrocannabinol treatment. Also, three patients had severe dysphoric reactions (including paranoia and feelings of loss of control) with tetrahydrocannabinol. In the second RCT, a crossover study in 24 patients with enduring AN, adjunctive dronabinol, given at 2.5 mg BID for 4 weeks, was superior to placebo for weight gain (Andries, Frystyk, Flyvbjerg, & Støving, 2014). Specifically, participants gained 0.73  kg (p < .01) during dronabinol treatment above that gained during placebo treatment. Also during dronabinol treatment, physical activity intensity increased by 20% (p = .01), resulting in an increased energy expenditure of 68.2 kcal/​day above placebo (p = .01); there was a transient increase in leptin levels at 3 weeks; and urinary free cortisol levels were decreased (Andries, Frystyk, Flyvbjerg, & Støving, 2015; Andries, Gram, & Støving, 2015). Changes in EDI-​2 scores during treatment with dronabinol or placebo were minimal, and there were no statistically significant differences on EDI-​ 2 scores between treatment periods. The drug was well tolerated without adverse psychiatric effects.

Prokinetics

Two randomized, placebo-​controlled trials of the prokinetic drug cisapride have been done in AN. In the first, 12 outpatients with DSM-​III-​R AN received cisapride 10 mg administered orally three times daily (n = 6) or placebo (n = 6) for 6 weeks after completing an 8-​week inpatient program (Stacher, Abatzi-​ Wenzel, et  al., 1993). All patients then received 6 weeks of open-​label cisapride. Gastric emptying was accelerated in all six patients receiving cisapride; gastric emptying was accelerated in three patients receiving placebo and slowed in the other three. Gastric retention symptoms and constipation were numerically improved in the cisapride group versus the placebo group. Mean weight (SD) gain with cisapride was greater than with placebo (7.3% [7.1] versus 1.7% [3.1] of ideal body weight, respectively). After the 6 weeks of cisapride treatment during the second period, gastric retention symptoms stayed reduced in the cisapride-​first patients and decreased in the placebo-​first patients. Five of the

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six placebo-​first patients gained weight. However, after their second 6 weeks of cisapride, only one of the six cisapride-​first patients gained more weight; the other five lost weight (mean change, –​3.0%). In the second study, 29 inpatients with AN were randomized to cisapride 10 mg three times daily or placebo for 8 weeks (Szmukler, Young, Miller, Lichtenstein, & Binns, 1995). Both gastric emptying and weight improved significantly but equally in both groups. However, patients receiving cisapride rated themselves as hungrier (p  =  .02) and more improved on a global measure of symptom change (p = .02). The correlation between gastric emptying and weight gain was modest (r = .30; p = .11). There were no correlations between gastric emptying and symptomatic measures. Cisapride’s access has since been restricted because of an association with potentially fatal cardiac arrhythmias (Wysowski, Corken, Gallo-​Torres, Talarico, & Rodriguez, 2001). Except for one small placebo-​controlled crossover study showing erythromycin 200 mg accelerated gastric emptying in 10 patients with AN (Stacher, Peters, et al., 1993), no other controlled studies of prokinetic agents in AN have been done. Open reports describe successful use of domperidone and metoclopramide to decrease symptoms and promote weight gain (Russell et al., 1983; Saleh & Lebwohl, 1980). In one case, however, excessive weight gain was described (Sansone & Sansone, 2003). Of note, if either domperidone or metoclopramide are used, patients should be monitored for extrapyramidal side effects.

Zinc

Two randomized, placebo-​ controlled trials of zinc supplementation have been conducted in patients with AN (Su & Birmingham, 2002). In the first study, six adolescents with AN who received elemental zinc 50 mg/​day for 6  months showed decreased depression and anxiety on the Zung Depression Scale (p < .05) and the Stale-​ Trait Anxiety Inventory (p < .05) compared with seven adolescents who received placebo (Katz et al., 1987). The zinc-​supported group also showed a greater weight gain and increase in height, improved taste function, greater advancement in sexual maturation, and better resolution of skin abnormalities, but these differences did not reach statistical significance. A fourteenth patient who dropped out of the trial was excluded from analysis. In the second trial, 35 female inpatients with AN who were considered completers had been randomized to zinc gluconate 366

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100 mg/​day (n = 16) or placebo (n = 19) until they achieved a 10% increase in BMI (Birmingham, Goldner, & Bakan, 1994). The rate of BMI increase in the zinc-​supplemented group was twice that of the placebo group (p = .03). However, 19 patients who did not complete the study (n = 10 receiving zinc) did not appear to be included in the efficacy analysis. In addition, antidepressants and major tranquilizers were used but their use was not quantitatively presented. Zinc was not associated with any harmful effects. Another study was a 12-​week crossover trial with 6 weeks of oral zinc sulphate 50 mg/​day alternating with 6 weeks of placebo to be given to children with AN (Lask, Fosson, Rolfe, & Thomas, 1993). Though described as double-​blind, this trial was unlikely to be randomized because of 26 patients enrolled, seven children received zinc supplementation, whereas 19 received standard treatment. Moreover, only three of seven trials of zinc supplementation were completed. Thus, no conclusions about zinc supplementation could be drawn from this study. Based on the above preliminary data, along with zinc’s low cost and benign side-​effect profile, some have argued that oral zinc administration during weight restoration should be routinely considered (Birmingham & Gritzner, 2006). The World Federation of Societies of Biological Psychiatry (WFSBP) pharmacotherapy of eating disorder guidelines also concluded there was evidence of efficacy of zinc in the treatment of AN (Aigner et al., 2011). Other guidelines, however, do not recommend routine zinc supplementation (Hay et  al., 2014). Further randomized, placebo-​ controlled studies are needed to better establish zinc’s efficacy, adverse event profile, and optimal dosing and treatment duration in the management of patients with AN.

Hormonal Treatments

Miller, Grieco, and Klibanski (2005) randomized 33 women with AN and relative testosterone deficiency to transdermal testosterone (150 or 300 μg) or placebo for 3 weeks. Serum total and free testosterone levels increased significantly in patients receiving testosterone. Significant improvement in depression was seen in depressed patients receiving testosterone, whereas there was no change in depressed patients receiving placebo (p  =  .02). Testosterone recipients showed improved spatial cognition (p  =  .0015). Weight, however, did not

change over the 3 weeks in either group. Attrition rate was 13%. Two randomized, placebo-​controlled studies of rhGH have been conducted in patients with AN. In the first, 15 inpatients with AN, ages 12 to 18 years, received rhGH .05 mg/​kg subcutaneously (n = 8) or an equivalent volume of placebo (n = 7) daily for 28 days in addition to a standard refeeding protocol (Hill et  al., 2000). Patients given rhGH reached medical/​cardiovascular stability (defined as normal orthostatic heart rate response to a standing challenge) significantly sooner than those receiving placebo (median 17 versus 37  days, p  =  .02). Numerical improvements were also seen in weight gain and hospitalization length in the rhGH group. There were no dropouts. In the second study, 21 women with AN were randomized to receive supraphysiological doses of rhGH (15 µg/​kg daily by subcutaneous injection) or placebo for 12 weeks (Fazeli et  al., 2010). Mean weight gain between groups (0.3 kg for rhGH versus 0.85 kg for placebo) was not significantly different. Total fat mass and percentage fat mass, however, decreased with rhGH and increased with placebo (p = .004). Bloch, Ish-​Shalom, Greenman, Klein, & Latzer (2012) randomized 26 premenopausal female patients with AN to dehydroepiandrosterone (DHEA), a hormone produced by the adrenal gland and brain that enhances production of androgens and estrogens, 50 mg twice daily or placebo in a 3:2 ratio for 6 months. All patients received psychotherapy, weekly nutritional assessments, and daily calcium carbonate 600 mg and vitamin D3 200 IU. Body mass index in DHEA-​treated patients was significantly increased at 4 months compared with placebo-​treated patients. However, the difference in BMI increase was not statistically significantly different across the 6 months of the study. There were also no drug-​placebo differences in depressive symptoms, bone mineral density, or bone mineral content. DHEA was well tolerated. Misra et  al. (2013) randomized 72 adolescent girls with AN to receive transdermal estradiol (100 mcg twice weekly) with cyclic progesterone or placebo patches and pills for 18 months. Thirty-​seven patients completed the trial. Changes in BMI did not differ between treatment groups. Estrogen replacement produced a decrease in trait anxiety scores but had no effect on state anxiety, eating attitudes, or body shape perception. Intranasal oxytocin was evaluated in 64 patients with AN in a single dose, within-​subject, crossover

trial conducted in a laboratory setting (Kim, Kim, Cardi, et al., 2014; Kim, Kim, Park, Pyo, & Treasure, 2014). Patients with AN showed significant reductions in attentional biases toward eating-​ related stimuli and negative shape stimuli, and the effect of oxytocin was correlated with autistic spectrum traits. However, oxytocin had no effect on amount of fruit juice consumed.

Ghrelin Agonists

In a phase 2 proof-​of-​concept study of the ghrelin agonist relamorelin in 22 females with AN, participants who received relamorelin 100 µg/​day for 4 weeks had significantly shorter gastric emptying time (p = .03) and greater weight gain (.86 kg versus .04  kg, respectively, p  =  .12) as compared with participants who received placebo (Fazeli et al., 2016).

Lithium

A 4-​week randomized, placebo-​controlled trial of lithium was conducted in 16 female inpatients with AN (Gross et al., 1981). All patients received behavior modification therapy, which included weekly group therapy, twice weekly individual therapy, and occasional tube findings. The eight patients receiving lithium showed significantly greater weight gain after 3 (p = .04) and 4 weeks (p = .03) of treatment than the eight patients receiving placebo. After 4 weeks, lithium-​treated patients also showed significantly more improvement on an item measuring “denial and minimization of illness” and ingested more fat per day. The mean (SD) plasma lithium level over the 4 weeks of treatment was 1.0 (0.1) mEq/​L. Lithium was well tolerated, and there were no serious adverse events. Many authorities are extremely reluctant to consider lithium for AN, given the drug’s low therapeutic index and need for monitoring, and AN’s association with dehydration, electrolyte abnormalities, and cardiac arrhythmias (Kolata, 1980). It should be noted, however, that case reports describe patients with AN and comorbid bipolar disorder responding to lithium alone or in combination with carbamazepine (Hudson, Pope, Jonas, & Yurgelun-​ Todd, 1985). There are also case reports of patients with treatment-​resistant AN responding to lithium (Barcai, 1977; Reilly, 1977; Stein, Hartshorn, Jones, & Steinberg, 1982). Use of lithium in AN requires careful monitoring of patients’ fluid, electrolyte, renal, cardiac, and thyroid status.

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Opioid Antagonists and Opioids

One placebo-​ controlled study of an opioid antagonist has been conducted in AN. Six AN patients treated with naltrexone, up to 200 mg/​day, or placebo in individual randomized crossover trials, showed significant reductions in binge eating and purging episodes, but not a significant increase in daily food intake, on naltrexone compared with placebo (Marrazzi, Bacon, Kinzie, & Luby, 1995). Although quantitative weight data were not provided, no patients lost weight on naltrexone. Naltrexone 25 to 75 mg/​day has also been used for successful weight restoration in hospitalized patients with chronic AN (Luby, Marrazzi, & Kinzie, 1987). In an open-​label trial, 12 inpatients with AN receiving behavioral treatment and antidepressants gained significantly more weight during constant naloxone infusion, up to 3.2 to 6.4 mg/​day for 5 weeks, compared with the 4 weeks post-​infusion (p < .01) (Moore, Mills, & Forster, 1981). Finally, tramadol, a synthetic opioid that binds μ-​opioid receptors and weakly inhibits the uptake of 5-​HT and norepinephrine, was reported to be helpful for a patient with intractable AN (Mendelson, 2001).

Anxiolytic Medications

D-​ cycloserine is a partial agonist at the N-​ methyl-​D-​aspartate (NMDA) glutamatergic receptor that may facilitate extinction of conditioned fear and may be helpful as a short-​term adjunctive intervention to exposure therapy for anxiety disorders, including phobias (Hofmann et al., 2006). Eleven patients with AN were randomly assigned to receive either D-​cycloserine 50 mg or placebo before each of four exposure therapy interventions (e.g., training meals) aimed to increase meal intake (Steinglass et al., 2007). A trend (p = .06) with a large effect size (d = 1.33) was seen for d-​cycloserine recipients to experience a greater decrease in self-​ reported depressive symptoms than placebo recipients from the baseline test meal to the final test meal (a mean of 28 days), but there were no other outcome differences between the groups. There were no adverse events with d-​cycloserine. This study was limited by small sample size. Also, patients assigned to d-​ cycloserine had significantly lower postmeal anxiety than those assigned to placebo at the baseline meal. In a randomized, placebo-​controlled, crossover study, one dose of alprazolam 0.75 mg was administered to 17 inpatients with AN (Steinglass, Kaplan, Liu, Wang, & Walsh, 2014). Within-​subject comparisons showed that alprazolam did not increase caloric intake during a laboratory test meal or 368

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reduce anxiety as compared with placebo, but did increase fatigue. The authors concluded that short-​ acting benzodiazepines may have a limited therapeutic role in AN.

Antiepileptic Drugs

There are no randomized, placebo-​controlled trials of an antiepileptic drug in AN, but open-​label reports have been published. A 16-​year-​old girl with “classical” AN beginning simultaneously with partial complex seizures showed both weight gain and seizure control with phenytoin treatment (Szyper & Mann, 1978). A  13-​year-​old girl with AN and epilepsy responded to the combination of valproate and clonazepam (Tachibana, Sugita, Teshima, & Hishikawa, 1989). Case reports of topiramate in AN are mixed:  Topiramate improved the concurrent AN of a patient with bipolar disorder (Guille & Sachs, 2002), but reports of development or exacerbation of AN after topiramate initiation for epilepsy or migraine have also been described (Lebow et al., 2015; Rosenow, Knake, & Hebebrand, 2002). Additionally, ED patients have misused topiramate to lose weight (Chung & Reed, 2004; Colom et al., 2001).

Nutritional Supplements

A study of nutritional supplementation of fluoxetine aimed to enhance serotonergic neurotransmission was ineffective in promoting weight gain in AN (Barbarich et  al., 2004). Twenty-​six patients with AN receiving fluoxetine were randomized to receive a nutritional supplement containing tryptophan, vitamins, minerals, and essential fatty acids, or a nutritional placebo. There were no significant differences in weight gain or in mean changes in anxiety or obsessive and compulsive symptoms between the two groups.

Other Medications

In a long-​term randomized, placebo-​controlled, crossover trial in four patients with AN, the alpha 2-​ adrenergic agonist clonidine had no effect on rate of weight gain, but was associated with lowered blood pressure, reduced pulse rate, and sedation (Casper, Schlemmer, & Javaid, 1987).

Pharmacotherapy of Bulimia Nervosa

Two primary pharmacotherapy RCT designs have been used to evaluate medications in BN: short-​ term acute studies of patients who are actively binge eating and purging and long-​ term maintenance studies of patients whose bulimic symptoms have

responded to an acute intervention. In addition, pharmacotherapy studies in BN have been done as monotherapy trials, in which medication alone is compared with placebo, another medication, or a psychological treatment, and as combination therapy trials, where medication plus a psychological treatment is compared with the psychological treatment alone and/​or the medication alone. Primary outcomes in the acute trials have usually been measures of the frequency of binge eating episodes and/​or inappropriate compensatory behaviors (e.g., vomiting), or rates of response or remission of bulimic symptoms. Primary outcomes in the maintenance trials have usually been time to relapse or rate of relapse. Secondary outcomes have been measures of ED psychopathology, mood symptoms, global clinical improvement, and treatment adherence. The two major classes of drugs studied thus far in BN in randomized, placebo-​controlled trials have been antidepressants and antiepileptics (Table 19.2). Drug classes that have received less study include 5-​HT3 antagonists, opioid antagonists, hormonal agents, and stimulants.

Antidepressants

Many different antidepressant classes have been evaluated in BN in randomized, placebo-​controlled trials; these include SSRIs, tricyclics, monoamine oxidase inhibitors, and atypical agents. Drugs from each of these classes have been shown superior to placebo for reducing the frequency of both binge eating and purging episodes in BN (Shapiro et al., 2007; Yager & Powers, 2007) (Table 19.2). As noted earlier, an antidepressant, fluoxetine, is the only medication with regulatory approval for the treatment of BN. In 2003, Bacaltchuk and Hay published a Cochrane Review of randomized, placebo-​ controlled trials of antidepressants in patients with BN. Nineteen studies were included: six trials with tricyclics (imipramine, desipramine, and amitriptyline; Agras, Dorian, Kirkley, Arnow, & Bachman, 1987; McCann & Agras, 1990; Mitchell & Groat, 1984; Mitchell et al., 1990; Pope, Hudson, Jonas, & Yurgelun-​Todd, 1983; Walsh, Hadigan, Devlin, Gladis, & Roose, 1991); five with monoamine-​ oxidase inhibitors (phenelzine, isocarboxazid, moclobemide, and brofaromine; Carruba et  al., 2001; Kennedy et al., 1993, 1988; Rothschild et al., 1994; Walsh, Stewart, Roose, Gladis, & Glassman, 1984), five with the SSRI fluoxetine (FBNCSG, 1992; Kanerva et  al., 1994; Mitchell et  al., 2001; Walsh et  al., 2000; Wheadon et  al., 1992), and

three with atypical drugs (mianserin, trazodone, and bupropion; Horne et  al., 1988; Pope, Keck, McElroy, & Hudson, 1989; Sabine, Yonace, Farrington, Barrant, & Wakeling, 1983). Study durations ranged from 6 to 16 weeks. Meta-​analysis showed that the pooled relative risk for remission of binge eating episodes was 0.87 (95% CI = 0.81, 0.93; p < .001), favoring antidepressants. The number needed to treat (NNT) for a mean treatment duration of 8 weeks, taking the 92% nonremission rate in the placebo controls as a measure of the baseline risk, was 9 (95% CI = 6, 16). The relative risk for clinical improvement, defined as a 50% or greater reduction in binge episodes, was 0.63 (95% CI = 0.55, 0.74). The NNT for a mean duration of 9 weeks was 4 (95% CI = 3, 6), with 67% unimproved in the placebo group. There was no evidence of statistically significant differences in efficacy among the different classes of antidepressants. However, remission rates were low and a considerable fraction of patients did not show a reduction of at least 50% in bulimic symptoms. Patients receiving tricyclics dropped out due to any cause more frequently than those receiving placebo, though the opposite was found for fluoxetine. The authors concluded that, in general, a single antidepressant agent is clinically effective for the treatment of BN when compared with placebo, but the effect is modest. Importantly, among the studies reviewed was the first pivotal RCT of fluoxetine in 387 women with BN in which 60 mg/​day was shown to be superior to placebo for reducing binge eating and vomiting episodes, while 20 mg/​day was shown to have an intermediate effect (FBNCSG, 1992). Fluoxetine 60 mg/​day was also superior to placebo for reducing depression, carbohydrate craving, and pathological eating attitudes and behaviors. Also reviewed was the single study of bupropion showing that though efficacious for reducing binge eating and purging, this agent was associated with an increased risk of seizures (Horne et al., 1988). It is therefore contraindicated for the treatment of BN and AN. Antidepressants have been studied both against and in combination with a variety of psychological interventions in BN, most commonly CBT but also intensive inpatient psychotherapy and nutritional counseling (Bacaltchuk, Hay, & Trefiglio, 2001; Shapiro et  al., 2007). Designs and results have varied, making firm conclusions difficult to make. In 2001, Bacaltchuk et  al. published a Cochrane Review of RCTs in which antidepressants were compared with psychological treatments or the combination of antidepressants

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Table 19.2  Medications Studied for Bulimia Nervosa in Randomized, Placebo-​Controlled trials: Qualitative Results Medication

Maximum Dosage Studied (mg/​day)

Reduction in Binge Eating

Reduction in Purging

 Amitriptyline

150

++

++

 Desipramine

300

++

++

 Imipramine

300

++

++

 Brofaromine

200

−

++

 Isocarboxazid

60

++

++

 Moclobemide

600

−

−

 Phenelzine

90

+++

+++

 Fluoxetine

60

++++

++++

 Fluvoxamine

300

++

++

 Bupropion

450

++

++

 Mianserin

60

−

−

 Trazodone

400

++

++

 Carbamazepine

NDAa

−

−

 Topiramate

400

+++

+++

 Dexfenfluraminec

60

++

++

 Flutamide

500

++

−

 Lithium

600–​1200b

−

−

 Naltrexone

200

+/​-​

+/​-​

 Ondansetron

24

++

++

 Spironolactone

150

−

−

Tricyclic Antidepressants

Monamine Oxidase Inhibitors

SSRIs

Other Antidepressants

Antiepileptics

Other Agents

Key: ++++ = ≥2 positive RCTs and evidence for maintenance of efficacy; +++ = ≥2 positive RCTs; ++ = ≥1 positive RCT; +/​ -​ = mixed data; − = only negative data; NDA = no data available; SSRI = selective serotonin reuptake inhibitor. a

Plasma carbamazepine levels = 6–​10 μg/​mL.

b

Mean plasma lithium level = .62 mEq/​L.

c

Removed from the market for safety concerns.

with psychological treatments was compared to each treatment alone for reducing symptoms in BN. The main efficacy outcome was remission of bulimic symptoms. Three comparisons were made. In the first, which included five trials and 237 patients, antidepressants alone were compared with psychological treatments alone (Agras et  al., 1992; Goldbloom et  al., 1997; Leitenberg et  al., 1994; Mitchell et  al., 1990; Walsh et  al., 1997). In the second, which included five trials and 247 patients, antidepressants alone were compared with antidepressant–​psychological treatment combinations (Agras et al., 1992; Goldbloom et al., 1997; Leitenberg et al., 1994; Mitchell et al., 1990; Walsh et  al., 1997). In the third, which included seven trials and 343 patients, psychological treatments alone were compared with combination treatment (Agras et al., 1992; Beaumont et al., 1997; Fichter et  al., 1991; Goldbloom et  al., 1997; Leitenberg et  al., 1994; Mitchell et  al., 1990; Walsh et  al., 1997). The first comparison found remission rates for antidepressant treatment alone were 20% versus 39% for psychological treatment alone (relative risk = 1.28; 95% CI = 0.98, 1.67). Dropout rates were higher for antidepressants alone than psychological treatments alone (relative risk  =  2.18; 95% CI  =  1.09, 4.35). The number needed to harm (NNH) for a mean treatment duration of 17.5 weeks was 4 (95% CI  =  3, 11). The second comparison found remission rates for the combination of 42% versus 23% for antidepressants alone (relative risk  =  1.38; 95% CI  =  0.98, 1.93). The third comparison found remission rates of 36% for psychological treatments alone versus 49% for the combination (relative risk = 1.21; 95% CI = 1.02, 1.45). Dropout rates were higher for the combination compared with psychological treatments alone (relative risk =.57; 95% CI =.38, .88). The NNH was 7 (95% CI  =  4, 21). Using a conservative approach, the only statistically significant difference between groups was that combination therapy was superior to psychological treatment alone. The authors concluded that the effectiveness of combined antidepressant–​psychological approaches was superior to psychotherapy alone, but that the number of trials might be insufficient to show combination therapy or psychotherapy alone superior to antidepressants alone. They also concluded that psychotherapy was more acceptable to patients and that the addition of antidepressants to psychotherapy reduced its acceptability. At least two randomized, controlled relapse-​ prevention trials have been done with antidepressants

in BN. In the first, 72 patients with BN successfully treated with intensive inpatient psychotherapy were randomized to receive fluvoxamine (n  =  33) or placebo (n  =  39) as outpatients for 12 weeks (Fichter, Krüger, Rief, Holland, & Döhne, 1996). Fluvoxamine was begun 3 weeks before hospital discharge, for a total of 15 weeks of treatment. The relapse rate was significantly lower for fluvoxamine than placebo, as shown by (1)  10% versus 46% deterioration on the Psychiatric Status Rating Scale for Bulimia Nervosa, (2) 111% versus 270% increase in self-​reported binge eating episodes in the last week, and (3)  50% versus 175% increase on the Structured Interview for Anorexia and Bulimia Nervosa (SIAB) subscale of bulimic behavior. In addition, at the end of relapse-​prevention, the fluvoxamine group had significantly more patients reporting no binge eating episodes in the past week than the placebo group (p < .05). However, the dropout rate was high (33%), with 14 (38%) fluvoxamine recipients stopping drug prematurely compared with five (14%) placebo recipients. In the second study, 232 outpatients with DSM-​ IV BN, purging type, received single-​blind treatment with fluoxetine 60 mg/​day for 8 weeks; 150 (65%) met response criteria (a decrease greater than or equal to 50% from baseline in vomiting episode frequency during one of the two preceding weeks) and were randomly assigned to continue fluoxetine 60 mg/​day (n = 76) or switch to placebo (n = 74) for 52 weeks (Romano, Halmi, Sarkar, Koke, & Lee, 2002). Fluoxetine-​treated patients exhibited a significantly longer time to relapse (defined as a return to baseline vomiting frequency that persisted for 2 weeks) than placebo-​treated patients (χ2  =  5.79, f  =  1, p < .02). Endpoint analysis showed statistically significant differences favoring fluoxetine for vomiting episodes, binge eating episodes, obsessive-​ compulsive symptoms, and clinical global outcome. However, relapse rates and symptom measures increased over the trial in both treatment groups. In addition, the attrition rate was very high, with 63 (83%) fluoxetine recipients and 68 (92%) placebo recipients discontinuing the study prematurely. Of note, several antidepressant classes have not yet been evaluated in randomized, placebo-​ controlled trials in BN. These include serotonin norepinephrine reuptake inhibitors (SNRIs; e.g., desvenlafaxine, duloxetine, milnacipran, and venlafaxine), norepinephrine reuptake inhibitors (NRIs; e.g., reboxetine), and novel agents such as vilazodone and vortioxetine. Open-​label data, however, suggest milnacipran, reboxetine, and, to a lesser

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extent, duloxetine, may be effective in BN, including in treatment-​resistant cases (El-​Giamal et  al., 2000, 2003; Fassino, Daga, Boggio, Garzaro, & Piero, 2004; Hazen & Fava, 2006; Noma, Uwatoko, Yamamoto, & Hayashi, 2008).

Antiepileptic Drugs

Three randomized, placebo-​controlled studies of antiepileptic drugs have been conducted in BN—​ one with carbamazepine and two with topiramate. In the first RCT of an AED in BN, 16 patients with DSM-​III BN and at least one binge episode per week and no binge-​free internals of longer than 3 weeks during the previous year received carbamazepine in a crossover design (Hudson & Pope, 1988; Kaplan, 1987; Kaplan, Garfinkel, Darby, & Garner, 1983). The first six patients received 6-​ week intervals of placebo–​carbamazepine–​placebo or carbamazepine–​placebo–​carbamazepine over 18 weeks. The next 10 patients received two 6-​ week intervals of placebo–​carbamazepine or carbamazepine–​placebo over 12 weeks. There was no significant difference in response between carbamazepine and placebo. One patient had a complete remission of binge eating, one patient had a marked response, and three additional patients improved on carbamazepine compared with baseline but did not show a difference on drug compared with placebo. Of note, the patient who had a remission had comorbid cyclothymic disorder; she showed marked improvement in both her mood and her bulimic symptoms while receiving carbamazepine. The first study of topiramate in BN was a 10-​ week trial in 69 acutely ill patients (Hedges et al., 2003; Hoopes et al., 2003). Twenty-​two (63%) of 35 topiramate recipients and 18 (53%) of 34 placebo recipients completed the trial. Topiramate (median dose 100 mg/​day; range 25 to 400 mg/​day) was superior to placebo in reducing the frequency of binge eating and purge days (days during which at least one binge eating or purging episode occurred; p  =  .004); the bulimia/​uncontrollable overeating (p = .005), body dissatisfaction (p = .007), and drive for thinness (p  =  .002) subscales of the EDI; the bulimia/​food preoccupation (p = .019) and dieting (p = .031) subscales of the EAT; the mean HAM-​A score (p = .046); and body weight (mean decrease of 1.8  kg for topiramate versus 0.2  kg increase for placebo; p  =  .004). Significantly more topiramate recipients than placebo recipients reported improvement on the Patient Global Improvement scale (p  =  .004). The percentage of patients who achieved ≥ 50% reduction in the number of binge 372

Pharmacotherapy

eating and/​or purge days was significantly greater for the topiramate group (52%) than the placebo group (24%; p = .012). Remission rates from binge eating and purging were numerically, but not significantly, higher for topiramate (23%) than placebo (6%); attrition rates were numerically lower for topiramate (34%) than placebo (47%). One patient discontinued topiramate for an adverse event (nausea). The most common side effects associated with topiramate were fatigue, flu-​ like symptoms, and paresthesias. In the second study, 60 patients who had BN for at least 12 months received topiramate (n = 30; titrated to 250 mg/​day by the sixth week with the dosage, then held constant) or placebo (n = 30) for 10 weeks (Nickel et al., 2005). Topiramate was associated with significant decreases in the frequency of binge eating/​purging (defined as a > 50% reduction; 37% for topiramate and 3% for placebo); body weight (difference in weight loss between the two groups = 3.8 kg); and all scales on the SF 36 Health Survey (all p’s < .001). Five (17%) patients on topiramate and six (20%) patients on placebo were considered dropouts. All patients tolerated topiramate well. In addition, topiramate has been reported to reduce binge eating and/​or purging in BN patients with treatment-​resistant illness, those with comorbid mood or personality disorders, and those receiving the drug as adjunctive therapy in combination with antidepressants, mood stabilizers, and/​ or antipsychotics (Barbee, 2003; Bruno, Riganello, & Marino, 2009; Felstrom & Blackshaw, 2002). There is also a report of topiramate decreasing binge eating in a woman with BN and epilepsy (Knable, 2001). Her BN antedated her epilepsy and had not responded to 5 years of treatment with phenytoin, which had been effective in preventing her seizures. Regarding other antiepileptics in BN, an open-​ label trial in 12 patients found zonisamide reduced binge eating and purging symptoms but was associated with a high dropout rate (Guerdjikova, Blom, Martens, Keck, & McElroy, 2013). There was no change in body weight. Valproate was effective in three hospitalized women with BN and comorbid rapid-​cycling bipolar disorder who were previously inadequately unresponsive to lithium and antipsychotics (Herridge & Pope, 1985; Hudson & Pope, 1988; McElroy, Keck, & Pope, 1987). Two patients received valproate alone, and one received valproate in combination with lithium. All three patients showed marked improvement of both bulimic and mood symptoms. As noted earlier, carbamazepine

was reported to be effective in a patient with BN and comorbid cyclothymic disorder (Hudson & Pope, 1988; Kaplan, 1987; Kaplan et  al., 1983). Finally, lamotrigine has been reported to be helpful in patients with BN and co-​occurring affective dysregulation (Trunko, Schwartz, Marzola, Klein, & Kaye, 2014).

5-​HT3 Receptor Antagonists

Faris et al. (2000) conducted a 4-​week randomized, placebo-​ controlled trial of ondansetron, a potent and selective antagonist of the 5-​HT3 receptor, in 26 women with severe BN. To be enrolled, patients had a minimum frequency of seven coupled episodes of binge eating followed by self-​ induced vomiting per week for at least 6  months. Ondansetron (n = 14), which was self-​administered in 4-​mg capsules up to six per day upon the urge to binge eat or vomit, was associated with a significantly greater decrease in frequency of binge eating/​ vomiting episodes (p < .001) and with a significant increase in normal meals consumed (p < .03) compared with placebo (n  =  12). The drug was also associated with significant improvement in the time spent engaging in bulimic behaviors (p < .05). There was no difference in weight change between groups. One patient receiving ondansetron discontinued due to accidental injury.

Hormonal Treatments

One RCT of an antiandrogenic compound has been conducted in women with BN. Forty-​ six women meeting the DSM-​ IV criteria for BN, purging type, were randomized to flutamide (n  =  9), citalopram (n  =  15), flutamide plus citalopram (n = 10), or placebo (n = 12) for 3 months (Sundblad, Landén, Eriksson, Bergman, & Eriksson, 2005). Final flutamide and citalopram doses were 500 mg/​day and 40 mg/​day, respectively. Ten patients did not complete the trial. On a self-​ rated global assessment of symptom intensity, all three active treatment groups were superior to placebo. A comparison of all flutamide-​recipients versus placebo-​recipients showed significant reductions in global ratings (p = .03) and binge eating (p = .02) but not vomiting. Binge eating was significantly reduced only in the group given the combination of flutamide and citalopram (p  =  .04); vomiting was not significantly decreased in any group. Dry skin was the most common side effect with flutamide. Two patients discontinued flutamide for moderate but reversible increases in serum transaminase levels.

In an open-​label study, the effects of an antiandrogenic oral contraceptive (30 μg ethinyl estradiol plus 3 mg drospirenone; Yasmin) were evaluated in 21 women with BN and 17 age-​and BMI-​matched controls (Naessén, Carlström, Byström, Pierre, & Hirschberg, 2007). Before treatment, women with BN had a higher frequency of menstrual disturbances, higher acne and hirsutism scores, and higher levels of testosterone, but lower meal-​related cholecystokinin (CCK) secretion than controls. After 3  months of treatment, meal-​related hunger and gastric distention were decreased in BN women. Meal-​ related CCK secretion was unchanged in BN women but decreased in control women. Testosterone and free testosterone were decreased in patients and controls. Frequency of self-​induced vomiting decreased during treatment (p < .05), but binge eating and weight phobia were not significantly changed. Compared with nonresponders, the six (29%) responders had significantly higher levels of total and free testosterone, binge eating, and self-​ induced vomiting at baseline, but lower levels of weight phobia. Reduced frequency of vomiting correlated with reduced testosterone levels (r’s = .50, p < .05). The authors concluded that antiandrogenic oral contraceptives might be a treatment strategy for women with BN and hyperandrogenic symptoms. There is one RCT of oxytocin in BN (Kim, Eom, Yang, Kang, & Treasure, 2015). In a single dose, placebo-​controlled, crossover study, 34 BN patients, along with 35 AN patients and 33 healthy controls, received oxytocin 40 IU intravenously followed by an emotion recognition task and an apple juice drink. The BN patients showed a decrease in 24-​hour caloric consumption and enhanced emotion recognition, while AN patients showed no response on either outcome. In healthy controls, oxytocin produced enhanced emotional sensitivity but no impact on calorie consumption.

Opioid Antagonists

Four RCTs of opioid antagonists in the treatment of BN have been conducted. In the first, 16 normal weight women with DSM-​III BN completed a 6-​week, placebo-​controlled, crossover trial of naltrexone (50 mg/​day) (Mitchell et  al., 1989). No significant differences in frequency of binge-​eating or vomiting episodes between active drug and placebo were found. In a subsequent study, 28 women with DSM-​III-​R BN and 41 obese patients with binge eating were randomized to receive naltrexone (100–​150 mg/​d), imipramine, or placebo for 8 weeks (Alger, Schwalberg, Bigaouette, Michalek,

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& Howard, 1991). Among all patients, there was no change in frequency or duration of binge eating. Among the 22 BN patients who completed, naltrexone was associated with a significant reduction in binge-​eating duration (p = .02), but not binge-​ eating frequency. In a study of 13 patients with BN receiving naltrexone up to 200 mg/​day or placebo in individualized crossover 6-​week trials, significant reductions in binge eating, purging, urges to binge eat, and urges to purge were seen with active drug (Marrazzi, Bacon, et al., 1995). In a fourth study of 41 women, intravenous administration of the opioid antagonist naloxone selectively suppressed the consumption of sweet high-​fat foods in obese and lean subjects with BN (n = 20), but not in controls (n = 21; Drewnowski, Krahn, Demitrack, Nairn, & Gosnell, 1995). Open studies suggest some BN patients, including those resistant to antidepressants and psychotherapy and those with type 1 diabetes, may respond when treated with doses of naltrexone up to 400 mg/​day (Raingeard, Courtet, Renard, & Bringer, 2004). In a comparison of standard-​dose (50–​100 mg/​day) versus high-​dose (200–​300 mg/​day) naltrexone in 16 patients with antidepressant-​resistant BN, participants in the standard-​dose group had no significant change in frequency of binge eating or purging after 6 weeks of treatment, whereas participants in the high-​dose group had significant reductions in both behaviors (Jonas & Gold, 1988).

Drugs for Attention Deficit Hyperactivity Disorder

In a double-​blind, randomized, crossover trial, eight patients with BN were given methylamphetamine or placebo intravenously followed by a test meal and separated by a 1-​ week interval (Ong, Checkley, & Russell, 1983). Significantly fewer mean (SD) calories were consumed after methylamphetamine (224 [111]) than after placebo (943 [222]; p < .02). In addition, “the frequency of bulimia” was significantly lower after methylamphetamine (zero of eight patients) than after placebo (four of eight patients; p < .05). Importantly, a growing number of case reports have described the successful use of methylphenidate in treating patients with BN, including those resistant to psychotherapy and antidepressants and those with comorbid cluster B personality disorders or ADHD (Drimmer, 2003; Dukarm, 2005; Guerdjikova & McElroy, 2013; Keshen & Ivanova, 2013; Schweickert, Strober, & Moskowitz, 1997; Sokol, Gray, Goldstein, & Kaye, 1999). 374

Pharmacotherapy

Lithium

In a RCT in 91 patients with BN, lithium (mean level .62 mEq/​L) was not superior to placebo in decreasing binge eating episodes, except possibly in depressed patients (Hsu, Clement, Sandhouse, & Ju, 1991). Importantly, there were no serious adverse events. Case reports have described the successful treatment with lithium of patients with BN and comorbid bipolar disorder (McElroy, Kotwal, Keck, & Akiskal, 2005). Lithium was effective for eating and mood disorder symptoms in a woman with BN who became manic on imipramine (Shisslak, Perse, & Crago, 1991). In another report, one of two women with BN and rapid cycling bipolar disorder responded to lithium with imipramine; the other woman failed lithium alone (Leyba & Gold, 1988). In yet another report, two of three men with BN and bipolar (n = 2) or cyclothymic (n  =  1) disorders responded to lithium alone (n = 1) or lithium plus imipramine (n = 1); one patient failed lithium alone (Pope, Hudson, & Jonas, 1986).

Weight-​Loss Drugs

Three RCTs of fenfluramine or its isomer dexfenfluramine in BN were conducted before the drug was removed from the worldwide market in 1997 because of concerns it caused cardiac valvular abnormalities (Colman, 2005; Gardin et al., 2000). In one study, fenfluramine was compared with desipramine in a 15-​week randomized, placebo-​controlled crossover trial in 22 outpatients with BN (Blouin et al., 1988). Both drugs reduced binge eating and vomiting frequency, but a greater proportion of patients responded to fenfluramine than to desipramine. In another study, 42 patients with BN were randomized to dexfenfluramine or placebo for 12 weeks (Russell, Checkley, Feldman, & Eisler, 1988). Dexfenfluramine was associated with significantly greater decreases in binge eating and self-​induced vomiting, but not in measures of depressive symptoms. In the third trial, however, dexfenfluramine plus CBT was not superior to placebo plus CBT in reducing bulimic or depressive symptoms in 43 women with BN (Fahy, Eisler, & Russell, 1993). No other RCTs of weight-​loss drugs in BN have been published. However, misuse of the lipase inhibitor orlistat by patients with BN has been reported (Deb, Gupta, & Varshney, 2014; Fernández-​Aranda et al., 2001; Malhotra & McElroy, 2002).

Prokinetic Agents

In the only RCT with a prokinetic agent, 29 patients with BN were randomized to receive erythromycin up to 500 mg three times daily or placebo for 6 weeks (Devlin et al., 2012). Thirteen patients in each group completed the trial. Treatment with erythromycin showed no beneficial clinical effect:  Patients receiving erythromycin had weekly mean (SD) binge eating/​vomit frequencies of 11.4 (10.7)/​11.3 (10.9), while those receiving placebo had weekly binge eating/​vomit frequencies of 7.2 (4.1)/​7.6 (4.4).

Antipsychotics

There are no published RCTs of antipsychotics in BN. Case reports of the successful use of aripiprazole in the treatment of patients with BN have been described (Takaki & Okabe, 2015; Trunko, Schwartz, Duvvuri, & Kaye, 2011). However, there are also reports of second-​generation antipsychotics inducing or exacerbating BN symptoms in patients receiving the drugs (Brewerton & Shannon, 1992; Crockford, Fisher, & Barker, 1997; Gebhardt et al, 2007).

Other Medications

A randomized, placebo-​ controlled trial in 93 women with DSM-​IV BN found no effect with spironolactone, a diuretic with mineralocorticoid and aldosterone antagonistic properties (von Wietersheim et al., 2008). By contrast, in an open-​ label trial, the gamma-​aminobutyric acid (GABA) B agonist baclofen, given at 60 mg/​day for 10 weeks, reduced binge eating in two of three patients with BN (Broft et al., 2007). However, a case of a woman with an alcohol use disorder and BN reported that alcohol craving but not food craving responded to high-​dose baclofen (Weibel, Lalanne, Riegert, & Bertschy, 2015). Finally, in a 12-​week, open-​label trial of a N-​acetylcysteine (NAC) in eight patients with BN, no patient improved and NAC was associated with a high discontinuation rate (Guerdjikova, Blom, Mori, & McElroy, 2013).

Pharmacotherapy of Binge Eating Disorder

Randomized, placebo-​ controlled studies of BED have been conducted primarily with four drug classes: ADHD medications, antidepressants, weight-​loss agents, and antiepileptics (Table 19.3). In most studies, medication was used as monotherapy; in a few studies medication was used adjunctively with psychological interventions. To date,

most BED trials have been short term (6–​21 weeks) and conducted in patients who were actively binge eating. The primary outcome has usually been a measure of binge eating episode or binge eating day frequency, rate of response or cessation of binge eating behavior, or change in Binge Eating Scale (BES) scores (Gormally, Black, Dasson, & Rardin, 1982). Secondary outcomes have included measures of ED psychopathology (often assessed with the Three Factor Eating Questionnaire) (Stunkard & Messick, 1985); mood, anxiety, obsessive-​ compulsive, and impulsive symptoms; global clinical improvement; weight, BMI, and other metabolic parameters; and adherence. Only one placebo-​ controlled maintenance monotherapy trial in a group of BED patients whose binge eating had responded to an acute intervention has been conducted (Hudson, McElroy, Ferreira-​Cornwell, Radewonuk, & Gaisor, 2017).

Drugs for Attention Deficit Hyperactivity Disorder

A prodrug of d-​amphetamine, LDX is approved for treatment of children and adults with ADHD; it is the only drug that has regulatory approval for the treatment of BED. Specifically, it is approved in the United States for adults with moderate-​to-​ severe BED. This approval was based on two 12-​ week phase 3 studies that each found that LDX, titrated to 50 mg/​day or 70 mg/​day, was efficacious for reducing binge eating (McElroy et al., 2016). An earlier phase 2 study found that LDX at 50 mg/​day and 70 mg/​day, but not 30 mg/​day, was efficacious for reducing binge eating (McElroy et al., 2015). All three studies also found that LDX was superior to placebo for inducing cessation of binge eating and for reducing ED psychopathology, obsessive-​compulsive features of binge eating, and body weight. In the phase 2 study, LDX was also superior to placebo for reducing trait impulsivity (McElroy et al., 2017). The tolerability and safety profile of LDX was consistent with previous findings in adults with ADHD. The anti–​binge eating effect of LDX was shown to persist for 6 months in a double-​blind, placebo-​ controlled, randomized withdrawal study (Hudson et al., 2015). Patients who responded to 12 weeks of open-​label treatment with LDX 50 or 70 mg/​ day (n = 275) were randomized to receive continued LDX or switched to placebo for 6  months. Based on a Cox proportional hazards model, the estimated hazard for relapse with LDX was 11 times less than placebo (hazard ratio  =  0.09). Specifically, 5% of

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Table 19.3  Medications Studied for Binge Eating Disorder in Randomized, Placebo-​Controlled Trials: Qualitative Results Medication

Maximum Dosage Studied (mg/​day)

Reduction of Binge Eating

Reduction of Body Weight

120

+

+

+++

+++

200

−

+

 Citalopram

60

+

+

 Escitalopram

30

+

+

 Fluoxetine

80

+

+

 Fluvoxamine

300

+

+

 Sertraline

200

+

+

120

+

+

300

−

+

+++

−

+

++

++

++

ADHD Medications  Atomoxetine  Lisdexamfetamine

70

Tricyclic Antidepressants  Imipramine SSRI Antidepressants

SNRI Antidepressants  Duloxetine Other Antidepressants  Bupropion Weight-​loss Drugs  Dexfenfluraminea  Orlistat

30 360

 Sibutramine

a

15

Antiepileptics  Lamotrigine

400

−

+/​−

 Topiramate

400

++

++

 Zonisamide

600

+

+

Key: +++ = ≥2 positive RCTs and evidence from ≥1 RCT for maintenance of efficacy; ++ = ≥ 2 positive RCTs; + = ≥1 positive RCT; +/​− = mixed data; − = only negative data; ADHD = attention deficit hyperactivity disorder; SSRI = selective serotonin reuptake inhibitor. a

Removed from the market for safety concerns.

LDX-​treated patients relapsed as compared with 34.4% of placebo-​treated patients. In a 12-​month open-​label safety and tolerability study in 604 BED patients, the safety and tolerability of LDX was consistent with its safety profile for treatment of ADHD (Gaisor et al., 2017). The most common adverse events were dry mouth, headache, insomnia, and upper respiratory tract infection. 376

Pharmacotherapy

There were minor increases in pulse and blood pressure and a modest decrease in body weight. There was no evidence of new safety concerns, including after abrupt discontinuation of LDX. In the only RCT of a nonstimulant ADHD drug in BED, 40 patients were randomized to receive atomoxetine, a highly selective NRI, or placebo for 10 weeks (McElroy, Guerdjikova, et al., 2007).

Atomoxetine was flexibly dosed from 40 to 120 mg/​day; the mean (SD) dose at endpoint evaluation was 106(21) mg/​day. Compared with placebo-​ treated patients (n  =  20), atomoxetine-​treated patients (n = 20) showed a significantly greater rate of reduction in binge eating episode frequency (the primary outcome measure), as well as decreases in binge day frequency, weight, BMI, and measures of global severity, obsessive features of binge eating, and hunger. Fifteen patients (six receiving atomoxetine) did not complete the 10-​week trial. The most common side effects associated with atomoxetine were dry mouth, nausea, nervousness, insomnia, headache, constipation, and sweating. Three atomoxetine recipients discontinued because of increased depressive symptoms, constipation, and nervousness (n = 1 each, respectively). The only other selective NRI studied in BED has been reboxetine. In a 12-​week open-​label trial in nine patients, significant reductions were seen in binge eating frequency and BMI (Silveira, Zanatto, Appolinário, & Kapezinski, 2005).

Antidepressants

To date, at least 10 randomized, placebo-​ controlled studies of antidepressants have been published in patients with BED as defined by all or most of the DSM-​IV criteria (Arnold et al., 2002; Grilo, Masheb, & Wilson, 2005; Guerdjikova et al., 2008; Guerdjikova et  al., 2012; Hudson et  al., 1998; Laederach-​Hofmann et  al., 1999; McElroy et al., 2000, 2003; Pearlstein et al., 2003; White & Grilo, 2013). Eight studies evaluated antidepressant monotherapy, and two compared antidepressants in combination with weight loss therapy (Laederach-​ Hofmann et al., 1999) or CBT (Grilo, Masheb, & Wilson, 2005). All studies were small, consisting of 15 to 85 patients; of short duration, ranging from 6 to 16 weeks; and had substantial dropout rates. Antidepressant families studied included SSRIs (n = 7), tricyclics (n = 1), SNRIs (n = 1), and bupropion (n  =  1). The SSRI doses were comparable to those used in BN. A study of fluoxetine used doses up to 80 mg/​day (Arnold et al., 2002) and a study of escitalopram used supratherapeutic doses (up to 30 mg/​day; Guerdjikova et al., 2008). When viewed collectively, SSRIs led to greater reductions in binge eating, ED psychopathology, and body weight than placebo, but were associated with substantial dropout rates (16%–​57%; Brownley, Berkman, Sedway, Lohr, & Bulik, 2007). Also, most weight reductions would not be considered clinically significant. In the only study of

bupropion, 61 overweight or obese patients received the drug or placebo for 8 weeks (White & Grilo, 2013). Bupropion was similar to placebo in reducing binge eating but associated with greater weight loss. Moreover, bupropion was well tolerated and there were no seizures. In the only study of BED with a co-​occurring depressive disorder, duloxetine (mean dose 78.7 mg/​day) was superior to placebo in reducing binge eating, global severity of BED and depressive symptoms, and body weight after 12 weeks of treatment (Guerdjikova et  al., 2012). Similarly, a retrospective chart review found that the SNRI venlafaxine was effective for reducing binge eating and body weight in 33 patients with BED and obesity (Malhotra, King, Welge, Brunsman-​ Lovins, & McElroy, 2002). A meta-​analysis of seven of these studies (one with a tricyclic, six with SSRIs) showed significantly higher binge eating remission rates for the antidepressant group compared with the placebo group:  40.5% versus 22.2% (relative risk  =  0.77 [95% CI  =  0.65, 0.92; p  =  .003]) (Stefano, Bacaltchuk, Blay, & Appolinario, 2008). Evaluating studies that used the Hamilton Depression Rating Scale to evaluate change in depressive symptoms, a statistically significant difference between groups was also seen favoring antidepressants (SMD  =  –​ 0.38 [95% CI = –​74, –​0.03; p = .03]). However, no differences between groups were found in the mean frequency of binge eating episodes at the end of treatment (SMD = –​0.36 [95% CI = –​0.74, 0.01; p = 0.06]), in BMI (SMD = 0.03 [95% CI = –​ 0.49, 0.55]), or in treatment discontinuation for any reason (relative risk  =  1.35 [95% CI  =  0.61, 3.00]). In light of the frequent chronicity of BED, it was concluded that the data were not sufficient to formally recommend antidepressants as a single first-​line therapy for short-​term remission of binge eating episodes and weight reduction in BED patients. Controlled combination therapy studies have had contrasting results. In one, diet counseling with psychological support plus imipramine was superior to diet counseling and psychological support plus placebo for 8 weeks in decreasing binge eating (p < .01) and weight (p < .001; Laederach-​Hofmann et  al., 1999). In the other, a 16-​week trial, CBT with placebo and CBT with fluoxetine were both superior to fluoxetine alone and placebo alone for decreasing binge eating (Grilo, Masheb, & Wilson, 2005). There was no difference between fluoxetine and placebo. No treatment was effective for weight loss.

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Open-​ label data have suggested some BED patients who initially respond to an antidepressant with decreased binge eating and weight loss may maintain these beneficial effects for up to 6 months with continuation of the antidepressant (Leombruni et al., 2006; Leombruni, Pierò, et al., 2008). The only randomized, placebo-​controlled maintenance trial of an antidepressant published in BED, however, suggested that benefits may not be maintained over longer periods of antidepressant treatment. In that study, 116 BED patients who achieved a 75% or greater reduction in binge frequency after a 5-​month initial phase of group behavioral weight control therapy received maintenance weight control treatment for up to 24 months. Patients were randomized twice: to fluoxetine or placebo, and to CBT or no CBT. Results showed fluoxetine appeared to be effective for depressive symptoms, but not for binge eating or weight reduction (Devlin et al., 2005; Devlin, Goldfein, Petkova, Liu, & Walsh, 2007). Of note, several promising types of antidepressants have not yet been studied in BED in randomized, placebo-​controlled trials. These include several SNRIs, vilozodone, and vortioxitine.

Weight-​Loss Agents

A number of weight-​loss agents have received at least some systematic study in obese patients with BED. Three randomized, placebo-​controlled studies have been conducted with the lipase inhibitor orlistat. In the first study, 50 patients with BED and obesity were randomized to 12 weeks of guided self help CBT (CBTgsh) with orlistat 120 mg three times daily or placebo (Grilo, Masheb, & Salant, 2005). Binge eating remission rates were significantly higher for orlistat plus CBTgsh (64% vs. 36%) at post-​treatment but not at 3-​month follow-​ up (52% in both groups). Rates for achieving at least 5% weight loss were significantly higher for orlistat plus CBTgsh than placebo plus CBTgsh at both post-​treatment (36% vs. 8%) and 3-​month follow-​up (32% vs. 8%). In the second study, 89 patients with BED and obesity were randomized to orlistat 120 mg three times daily (n = 44) or placebo (n  =  45), in combination with a mildly reduced calorie diet, for 24 weeks (Golay et  al., 2005). At endpoint, the mean percentage weight loss (the primary outcome measure) for orlistat-​treated patients was significantly greater than for placebo-​treated patients (–​7.4% vs. –​2.3%; p = .0001). Waist circumference, hip circumference, total percentage body fat, total cholesterol level, diastolic blood 378

Pharmacotherapy

pressure, and insulin level were also significantly improved with orlistat. Effectiveness of orlistat for binge eating behavior was less clear:  at 24 weeks, the mean number of weekly binge eating episodes was numerically but not significantly decreased (1.0 for orlistat-​treated patients vs. 1.7 for placebo-​ treated patients). Also, similar rates of patients in both groups who completed the study continued to suffer from BED (23% for orlistat vs. 29% for placebo). However, the Eating Disorder Inventory 12 score at week 24 was significantly lower for orlistat than placebo (p = .011). In addition, fat intake was significantly lower in orlistat-​treated patients at week 12; total caloric intake was significantly lower at week 24. Eighteen patients discontinued the study prematurely: five (11%) in the orlistat group and 13 (29%) in the placebo group. No patient discontinued orlistat because of an adverse event. Data on side effects were otherwise not reported. In the third study, 79 obese Spanish-​speaking-​ only Latino/​as with BED (n = 40) or without BED (n = 39) at a community mental health center were randomly assigned to 4 weeks of orlistat 120 mg three times daily plus behavioral weight loss therapy (BWLT) or placebo plus BWLT (Grilo & White, 2013). Seventy-​ eight percent of patients completed the trial. Among BED patients, remission of binge eating did not differ between orlistat (60%) and placebo (70%), and there was no difference in improvement in ED psychopathology, BMI, or depressive symptoms. Orlistat plus BWLT produced greater weight loss than placebo plus BWLT in patients with obesity alone, but not in patients with BED. Of note, there are reports of patients with binge eating who misuse orlistat (Cochrane & Malcolm, 2002; Deb et  al., 2014; Malhotra & McElroy, 2002). The glucagon-​like peptide-​1 (GLP-​1) receptor agonist liraglutide 1.8 mg daily sc injection was tested in 44 nondiabetic obese participants with subclinical binge eating behavior, defined as a BES score ≥ 18, in a 12-​week trial (Robert et al., 2015). Participants were randomized to receive liraglutide (n = 21) plus diet and exercise or to diet and exercise alone (n  =  21). Participants receiving liraglutide showed significant reductions in binge eating behavior, body weight, BMI, waist circumference, systolic blood pressure, fasting glucose, and total cholesterol. This study was limited by the lack of use of placebo. Of note, we found no studies of liraglutide 3 mg daily sc injection in BED, the dose of liraglutide approved for the treatment of obesity (Bray, Frühbeck, Ryan, & Wilding, 2016).

In another open-​label study, phentermine, up to 30 mg/​day, in combination with fluoxetine, up to 60 mg/​day, and CBT was assessed in 16 obese women, 14 of whom met DSM-​ IV criteria for BED (Devlin, Goldfein, Carino, & Wolk, 2000). During the 20-​week active treatment phase, mean weekly binge eating frequency declined by 95% from baseline, with 12 (75%) patients showing complete remission. In addition, mean body weight and BMI declined by 8.6% and 8.7%, respectively, from baseline. After 6 months of maintenance treatment, 10 patients were still taking both medications (two patients were taking fluoxetine alone); though binge eating frequency was 63% lower than at the start of treatment, only five (42%) of 12 patients were free of binge eating. Only six patients completed 18  months of maintenance therapy; two were taking both medications and four were taking fluoxetine alone. Though binge eating remained improved, patients had regained most of the weight they had lost at the end of active treatment. In a 24-​week, open-​label trial in 23 obese or overweight women with current major depressive disorder, most of whom had clinically significant binge eating, the combination of naltrexone and bupropion (as sustained release formulations) reduced binge eating behavior, depressive symptoms, and body weight at 16 and 24 weeks (McElroy, Guerdjikova, Kim, et  al., 2013). Mean (SD) percent weight loss was –​4.0 (4.6) at week 12 and –​5.3 (6.5) at week 24. Finally, two patients with BED and obesity have been described who had cessation of binge eating behavior and clinically significant weight loss in response to treatment with the combination of phentermine and topiramate (Guerdjikova, Fitch, & McElroy, 2015). Three weight-​loss agents that have been removed from the market because of safety concerns have also been evaluated in RCTs in BED. Thus, sibutramine, a reuptake inhibitor of norepinephrine, 5-​ HT, and, to a lesser extent, dopamine, was shown to reduce both binge eating and excessive body weight in BED in three placebo-​controlled, randomized trials (Appolinario et al., 2003; Milano et al., 2005; Wilfley et al., 2008). In the only RCT of dexfenfluramine, 28 women with BED and obesity received active drug, up to 30 mg/​day, or placebo for 8 weeks (Stunkard, Berkowitz, Tanrikut, Reis, & Young, 1996). The rate of binge eating fell three times more rapidly in the dexfenfluramine group than the placebo group, but no significant weight changes were observed. In a study of the selective endocannabinoid CB1 receptor inverse agonist rimonabant, 289

obese patients with BED were randomized to active drug or placebo for 6 months (Pataky et al., 2013). All patients were also prescribed a mild hypocaloric diet. Rimonabant-​treated patients showed a greater change in body weight (the primary outcome) compared with placebo-​ treated patients:  Patients receiving rimonabant lost 4.7% of their initial body weight while patients receiving placebo lost 0.4%. Rimonabant-​ recipients also showed significant reductions in BES scores.

Antiepileptic Drugs

Five randomized, placebo-​controlled studies of antiepileptic drugs (three for topiramate, one for zonisamide, and one for lamotrigine) in DSM-​ IV–​defined BED and two small crossover studies of phenytoin in the similar condition of compulsive or binge eating have been conducted (McElroy et al., 2009). The three RCTs of topiramate each found that topiramate reduced binge eating and excessive body weight in BED. In the first study, 61 BED patients with obesity received topiramate (n  =  30) or placebo (n = 31) for 14 weeks (McElroy, Arnold, et al., 2003). Topiramate (median dose 212 mg daily) was significantly superior to placebo in reducing binge eating frequency, as well as obsessive-​compulsive features of binge eating, global illness severity, body weight, and BMI. Topiramate-​treated patients experienced a 94% reduction in binge frequency and a mean weight loss of 5.9 kg, whereas placebo-​treated patients experienced a 46% reduction in binge frequency and a mean weight loss of 1.2 kg. Dropout rate, however, was high:  14 (47%) topiramate recipients and 12 (39%) placebo recipients failed to complete the trial. The most common side effects associated with topiramate were paresthesias, dry mouth, headache, and dyspepsia. The second controlled study was a multicenter trial in which 407 patients with BED and ≥ three binge eating days/​week, a BMI between 30 and 52  kg/​m2, and no current psychiatric disorders or substance abuse were randomized to receive topiramate or placebo for 16 weeks (McElroy, Hudson, et  al., 2007). Compared with placebo, topiramate (median final dose 300 mg daily) significantly reduced binge eating days/​week, binge eating episodes/​week, body weight, and BMI (all p’s < .001). Topiramate also significantly decreased obsessive-​compulsive features of binge eating, disinhibited eating, and hunger; trait impulsivity; and measures of overall, social, and family life disability. Significantly more topiramate-​treated subjects

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(58%) achieved remission compared with placebo-​ treated subjects (29%; p < .001). Discontinuation rates were 30% in each group; adverse events were the most common reason for topiramate discontinuation (16%; placebo, 8%). Paresthesias, upper respiratory tract infection, somnolence, and nausea were the most frequent topiramate side effects. The third controlled study of topiramate in BED was another multicenter trial in which 73 patients with BED and obesity were randomized to 19 sessions of CBT in conjunction with topiramate (n = 37) or placebo (n = 36) for 21 weeks (Claudino et al., 2007). Compared with patients receiving placebo, patients receiving topiramate showed a significantly greater rate of reduction in body weight, the primary outcome measure (p < .001). Topiramate recipients lost a mean of 6.8  kg While placebo recipients lost 0.9  kg. Rates of reduction of binge eating frequencies and BES and depression scores did not differ between the groups, but a greater percentage of topiramate-​ treated patients (84%) attained remission of binge eating as compared with placebo-​treated patients (61%; p = .03). There was no difference between groups in completion rates, though one topiramate recipient withdrew for an adverse effect. Paresthesias and taste perversion were more frequent with topiramate, whereas insomnia was more frequent with placebo. In the only RCT of zonisamide, 60 outpatients with DSM-​ IV BED and obesity received flexibly dosed (100–​600 mg/​day) zonisamide (n  =  30) or placebo (n  =  30) for 16 weeks (McElroy et  al., 2006). Compared with placebo, zonisamide was associated with a significantly greater rate of reduction in binge eating episode frequency (p  =  .021), body weight (p < .0001), BMI (p  =  .0001), and measures of global severity, obsessive-​ compulsive features, and disinhibited eating (all p’s < .0001). The mean (SD) zonisamide daily dose at endpoint evaluation was 436 (159) mg. Attrition rate, however, was high, with 18 (60%) zonisamide patients and 12 (40%) placebo patients not completing the 12-​ week treatment period. Eight zonisamide recipients discontinued for adverse events. The most common reasons for stopping zonisamide were cognitive complaints (n = 2), psychological complaints (n = 2), and bone fracture (n = 2). The most common side effects associated with zonisamide were dry mouth, somnolence, headache, nausea, nervousness, and altered taste. This trial was consistent with an earlier open-​ label study in which zonisamide was associated with reduced binge eating and body weight but 380

Pharmacotherapy

also with a high discontinuation rate (McElroy, Kotwal, Hudson, Nelson, & Keck, 2004). It is also consistent with an open-​label study of zonisamide given in conjunction with CBT in patients with threshold and subthreshold BED (Ricca, Castellini, LoSauro, Rotella, & Faravelli, 2009). In this study, 28 patients received zonisamide while 24 received CBT alone for 6  months. At end of treatment, zonisamide recipients showed greater reductions in BMI and BES scale scores. In the fifth RCT of an antiepileptic, 51 patients with BED were randomized to receive lamotrigine or placebo for 16 weeks (Guerdjikova et al., 2009). Lamotrigine (mean dose 236 mg/​day) and placebo had similar rates of reduction of weekly frequency of binge eating episodes and binge eating days, weight, and BMI; and measures of eating pathology, obsessive-​compulsive symptoms, impulsivity, and global severity of illness. However, lamotrigine was associated with a numerically greater amount of weight loss (1.17 vs. 0.15 kg) and significant reductions in fasting levels of glucose, insulin, and triglycerides. It was also well tolerated and associated with no serious adverse events. The two small placebo-​controlled crossover trials of phenytoin in patients with compulsive or binge eating had contrasting results (Hudson & Pope, 1988). In the negative trial, four obese patients with compulsive eating showed no significant differences between phenytoin and placebo on any outcome measure and no patient had a marked response to phenytoin (Greenway, Dahms, & Bray, 1977). In the positive study, 19 of 20 women with “binge eating syndrome” completed 12 weeks wherein they received phenytoin and placebo for 6 weeks each in a counterbalanced design (Wermuth, Davis, Hollister, & Stunkard, 1977). Twelve patients had final serum phenytoin levels of 10 to 20 μg/​mL; five had levels of 5 to 10 μg/​mL. Patients given phenytoin first experienced a 37% decrease in binge eating frequency (p < .01), but when administered placebo, binge eating frequency was unchanged. Patients given placebo first experienced no change in binge eating frequency, and they did experience a 39% decrease after switching to phenytoin (p < .01). Eight (42%) patients displayed a moderate or better response (≥ 50% reduction in binge eating episode frequency) on phenytoin, but only one patient experienced a remission of binge eating. When the two groups were compared, there were significantly fewer eating binges in the phenytoin–​placebo group than in the placebo–​phenytoin group (p < .02), indicating a carryover effect for the phenytoin-​first sequence.

There are no controlled relapse prevention studies of antiepileptics in BED, but an open-​ label extension trial has suggested that the anti–​binge eating and weight loss effects of topiramate may be maintained over the long term. The BED patients who completed the first RCT of topiramate (n = 35) were offered participation in a 42-​week open-​label extension study of the drug (McElroy, Shapira, et al., 2004). Forty-​four patients (31 who received topiramate in the open-​ label trial plus 13 who received topiramate in the double-​blind study only) received at least one dose of topiramate; 43 patients provided outcome measures at a median final dose of 250 mg/​day. Mean weekly binge eating frequency declined significantly from baseline to final visit for all 43 patients (–​3.2; p < .001), for the 15 patients who received topiramate during the controlled and open-​label studies (–​4.0; p < .001), and for the 15 patients who received topiramate only during the open-​label trial (–​2.5; p  =  .044). Patients also exhibited a statistically significant reduction in body weight. However, only 10 (32%) of the 31 patients entering the extension trial completed the 42 weeks of open-​label treatment; the most common reasons for topiramate discontinuation were protocol nonadherence (n = 11) and adverse events (n = 8). There are also open-​label descriptions of antiepileptics being helpful in difficult-​to-​treat patients with BED. Thus, topiramate has been reported to reduce binge eating and/​or overweight in BED patients with treatment-​resistant illness, comorbid depressive or bipolar disorders, traumatic brain injury, and those receiving the drug adjunctively with antidepressants and/​or mood stabilizers (De Bernardi, Ferraris, D’Innella, Do, & Torre, 2005; Dolberg, Barkai, Gross, & Schreiber, 2005; Kotwal, Guerdjikova, McElroy, & Keck, 2006; Schmidt do Prado-​Lima & Bacaltchuck 2002; Shapira, Goldsmith, & McElroy, 2000). Topiramate has been successfully used to reduce binge eating and weight gain after adjustable gastric banding or gastric bypass surgery (Guerdjikova, Kotwal, & McElroy, 2005; Zilberstein et al., 2004). There is also a successful case of lamotrigine in the treatment of a 61-​year-​old woman with BED, bipolar depression, and treatment-​resistant type 2 diabetes (Yamamoto, Kanahara, Hirai, Watanabe, & Iyo, 2013). By contrast, valproate has been reported to worsen binge eating and enhance weight gain in patients with BED and comorbid bipolar disorder (Shapira et al., 2000). In addition, a case series of nine obese patients with BED treated with oxcarbazepine had inconsistent findings (Leombruni,

Gastaldi et  al., 2008). Four patients showed a decrease in binge eating and three lost weight, but three reported no change in binge eating, two showed no weight change, and five gained weight. Five patients discontinued the drug, and seven reported side effects.

Opioid Antagonists

Two RCTs of opioid antagonists have been published in BED. In the first, 33 obese binge eaters and 22 normal weight bulimics were treated for 8 weeks with naltrexone (100–​150 mg/​day), imipramine, or placebo (Alger et  al., 1991). Naltrexone did not significantly reduce binge eating frequency or duration in the obese binge eaters. In the second trial, 62 patients with BED were randomized to the novel opioid antagonist ALKS-​33 (now called samidorphan; n = 26) or placebo (n = 36) for 6 weeks (McElroy, Guerdjikova, Blom, et  al., 2013). Both drug and placebo produced similar large reductions in binge eating episode frequency, raising the possibility of a failed rather than negative trial. However, there were also no differences between drug and placebo in other measures of binge eating, eating psychopathology, or body weight. In contrast, two favorable case reports of naltrexone in BED have been published. One was a positive on-​off-​on case of naltrexone monotherapy using doses of 200 and 400 mg/​day (Marrazzi, Markham, Kinzie, & Luby, 1995). The other was the successful augmentation of fluoxetine using naltrexone 100 mg/​day (Neumeister, Winkler, & Wöber-​Bingöl, 1999). Additionally, a Phase 2 placebo-​controlled study of intranasal naloxone spray has been reported in abstract form but not yet published (Alho et al., 2013). Specifically, 127 participants with BED were randomized to intranasal naloxone spray or intranasal placebo spray for 24 weeks. Naloxone 2 mg was administered before each binge eating episode up to a maximum of 4 mg/​day; 81% of participants completed the trial. Naloxone produced a significantly greater reduction than placebo in time spent binge eating. Also, BMI decreased significantly from week 12 to week 24 among naloxone recipients but not placebo recipients. There were no serious adverse events.

Baclofen

In one small crossover RCT in 12 individuals with binge eating, participants were randomized to receive baclofen (titrated to 60 mg/​d) for 48  days followed by placebo for 48  days, or the reverse

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(Corwin, Boan, Peters, & Ulbrecht, 2012). Relative to the placebo phase, baclofen produced a slight but statistically significant reduction in binge eating frequency. The BES and food craving scores were decreased similarly during baclofen and placebo phases. By contrast, baclofen produced a small but statistically significant increase in depressive symptoms. The most commonly reported side effects were tiredness, fatigue, and upset stomach. Of note, patients with BED who do not respond to 60 mg daily may respond to higher baclofen doses (up to 180 mg daily) (De Beaurepaire, Joussaume, Rapp, & Jaury, 2015).

marketed for the treatment of excessive daytime sleepiness and cataplexy in patients with narcolepsy (McElroy et  al., 2011). Sodium oxybate was associated with significant reductions in binge eating frequency, obsessive-​compulsive features of binge eating, BMI, and body weight. However, only five patients completed the 16-​week trial. Finally, in 12 obese patients with BED and bipolar disorder, lithium augmentation of topiramate improved mood and reduced both binge eating and body weight (Kotwal et al., 2006).

Chromium

Two RCTs of pharmacotherapy have been published in NES. In the first, 34 outpatients with NES were randomly assigned to receive sertraline (n = 17) or placebo (n = 17) for 8 weeks (O’Reardon et  al., 2006). Sertraline was flexibly dosed at 50 to 200 mg/​day. On the primary outcome measure, the Clinical Global Impression-​Improvement scale, sertraline was significantly superior to placebo:  12 (71%) sertraline-​ treated patients were classified as improved compared with three (18%) placebo-​treated patients. There was also significant improvement with sertraline in night eating symptoms, global severity ratings, frequency of nocturnal ingestions and awakenings, caloric intake after the evening meal, and quality of life ratings. In addition, overweight and obese patients receiving sertraline lost a significant amount of weight by week 8 (mean = –​2.9 kg) compared with overweight and obese patients receiving placebo (mean = –​0.3 kg). In the other RCT, 40 patients with NES were randomly assigned to receive escitalopram (n = 20) or placebo (n  =  20) for 12 weeks (Vanderwal, Gang, Griffing, & Gadde, 2012). At study endpoint, there was no difference in mean change of the Night Eating Questionnaire total score (the primary outcome measure). Similarly, there were no drug-​ placebo differences for changes in body weight or mood ratings. Finally, there are open-​label reports of agomelatine and of topiramate successfully reducing nighttime eating in patients with NES (Kucukgoncu, Midura, & Tek, 2015). Improvements in weight and sleep were also described.

Chromium is an essential nutrient that may improve mood, appetite, and glucose regulation. In one small RCT, 24 overweight or obese patients with BED were randomized to one of three treatments for 6  months each:  high-​dose (1,000 mcg daily) chromium (n  =  8), moderate-​ dose (600 mcg daily) chromium (n  =  9), or placebo (n  =  7) (Brownley et  al., 2013). Numerically greater reductions in binge frequency, body weight, and depressive symptoms were observed in chromium recipients compared with placebo recipients, but reductions were not statistically significant. Fasting glucose was significantly reduced in both chromium groups, with larger effects noticed with the higher dose of chromium. Chromium was well tolerated.

Antipsychotics

There are no published RCTs of antipsychotics in the treatment of BED. Indeed, second-​generation antipsychotics have been reported to induce or exacerbate binge eating, including BED, in patients receiving the drugs for psychotic disorders (Theisen et al., 2003).

Other Agents

The glutamate modulating agent memantine has been reported to reduce binge eating in BED in two open-​label trials. In the first, five women with BED and obesity received memantine 10 mg in the morning and 10 to 20 mg in the late afternoon (Hermanussen & Tresguerres, 2005). As a group, the women lost weight; on average, 1.2 kg per week. In the second trial, 16 patients received a mean endpoint memantine dose of 18.3 mg/​day. Although they did not lose weight as a group, weight loss was seen in the four patients who had a remission of binge eating (Brennan et al., 2008). In another open-​label study, 12 patients with BED were treated with sodium oxybate, which is 382

Pharmacotherapy

Pharmacotherapy of Night Eating Syndrome

Conclusions

Research into the pharmacotherapeutic treatment of EDs has lagged behind that into most other serious mental disorders. Only two medications have regulatory approval for use in an ED

(fluoxetine in BN and LDX in BED). No drug has been specifically developed to treat an ED. Many of the available pharmacotherapy studies in EDs are plagued by limitations, such as small sample size and inadequate power to detect effects, and unclear generalizability of findings to real-​world clinical situations. Moreover, some treatments may have been prematurely dismissed as ineffective or unsafe despite studies having these limitations (e.g., antipsychotics and mood stabilizers in AN). Some preliminary conclusions about the pharmacotherapy of EDs can nonetheless be made. Regarding AN, neither tricyclics nor the SSRI fluoxetine appear to be effective in promoting weight gain in underweight patients when used adjunctively with hospital care (Claudino et al., 2006). In addition, one well-​designed study showed that fluoxetine does not appear to be effective in maintaining weight gain in weight-​restored patients with AN when used in conjunction with CBT (Walsh et al., 2006). However, a smaller study showed fluoxetine might be helpful for weight maintenance in restricting AN when CBT is not a required treatment component (Kaye et al., 2001). Whether these findings can be generalized to antidepressants from other classes is presently unknown. Questions also remain as to the efficacy of antidepressants in weight restoration and weight maintenance in AN when used in combination with other classes of compounds (e.g., antipsychotics; see below); in AN with comorbid depressive, anxiety, or obsessive-​compulsive disorders; and/​or in treatment-​refractory, intractable, or chronic AN. By contrast, emerging placebo-​ controlled evidence shows olanzapine may be effective for weight restoration in AN, as well as some of the core and associated symptoms of AN (Attia et al., 2011; Bissada, Tasca, Barber, & Bradwejn, 2008; Brambilla, et al., 2007). Further controlled trials of olanzapine and other antipsychotics, both first and second generation, for weight restoration in AN are needed, as are RCTs of these agents for weight maintenance. An adequately sized randomized, placebo-​controlled trial comparing olanzapine with another second-​generation antipsychotic would be particularly informative. Other compounds that hold at least some promise for AN and need further study include cyproheptadine, dronabinol, relamorelin, rhGH, prokinetics, zinc, and d-​cycloserine. In contrast to AN, substantial evidence indicates SSRIs and antidepressants from several other classes are efficacious for BN (Bacaltchuk & Hay,

2003). Although the therapeutic effects of antidepressants in general on binge eating and purging are moderate, RCTs have shown fluoxetine may be useful in the primary care setting, may be effective when psychotherapy is inadequate, and may work over the long term (Romano et  al., 2002; Walsh et  al., 2000; Walsh, Fairburn, Mickley, Sysko, & Parides, 2004). Other available treatments that show promise for BN and merit further study are the antiepileptic topiramate and the 5-​HT3 receptor antagonist ondansetron (Faris et al., 2000; Hedges et  al., 2003; Nickel et  al., 2005). Antiandrogen agents in women with hyperandrogenism, naltrexone (at doses higher than used for substance abuse), and ADHD medications also warrant further evaluation. A considerate amount of double-​blind, placebo-​ controlled data show that LDX is efficacious for reducing binge eating in BED, as well as obsessive-​ compulsive features of binge eating and body weight. These effects may be maintained up to 6  months. Similar to BN, antidepressants appear to have a modest beneficial effect on binge eating in BED (Stefano et  al., 2008). They do not, however, appear to have clinically significant benefits on body weight, and their long-​term efficacy is unknown. Also similar to BN, a considerable amount of double-​blind, placebo-​controlled data show that topiramate is effective for binge eating in BED with obesity; these data further show that topiramate is effective for weight loss in this patient population (McElroy, Hudson, et al., 2007). One small open-​label study suggests topiramate’s anti–​ binge eating and weight loss effects in BED may persist for up to 1 year, but that drug discontinuation rates are high, in part due to adverse events (McElroy, Shapira, et  al., 2004). Orlistat, when used in combination with CBT or dietary therapy, may lead to weight loss and possibly reduced binge eating (Golay et  al., 2005; Grilo, Masheb, & Salant, 2005). Other available compounds that show promise for BED and merit further evaluation are zonisamide, naltrexone (especially at higher doses than used for substance abuse and in combination with antidepressants), stimulants other than LDX, and glutamate-​modulating agents (e.g., memantine). Pharmacotherapy research into NES has been extremely limited. One small controlled study has provided support for sertraline in NES, while another with escitalopram was negative. Open-​label data suggests topiramate may be helpful for this condition and merits further study.

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Future Directions

Further pharmacotherapy research into AN, BN, BED, and other EDs is greatly needed at many levels. Further trials need to be conducted for olanzapine and zinc in AN, ondansetron in BN, and zonisamide in BED to determine whether initial positive findings can be replicated. Randomized, placebo-​ controlled maintenance trials would be useful for olanzapine in AN and for topiramate in both BN and BED. Adequately sized RCTs of the ghrelin agonist relamorelin and the hormone oxytocin in patients with AN would be informative. Also, RCTs in which a novel medication strategy (e.g., maintenance olanzapine treatment of AN or maintenance topiramate treatment of BN or BED) is combined with a specific psychological treatment would be useful. There have been extremely few RCTs devoted to ED patients who have had partial or inadequate responses to pharmacotherapy or who have treatment-​ resistant illness. As has been done in other major mental disorders, trials are needed that explore strategies where medications are optimized, switched, augmented, or combined. For example, antipsychotics in combination with other agents, such as antidepressants, zinc, rhGH, or relamorelin, should be explored in randomized, placebo-​ controlled trials in treatment-​resistant or chronic AN. Similarly, studies of topiramate in combination with antidepressants or stimulants would be important in patients with treatment-​resistant or chronic forms of BN and BED (Brambilla et al., 2009). In addition, studies are needed in ED patients who have clinically important comorbidities, such as major depressive disorder, bipolar disorder, anxiety disorders, substance use disorders, borderline personality disorder, and diabetes (Woodside & Staab, 2006). For BED, further trials in patients with co-​ occurring obesity and obesity-​ related medical conditions (such as diabetes and hypertension) are needed. Available drugs that may hold promise for BN and BED and merit evaluation in RCTs include stimulants beyond LDX; nonstimulant medications for ADHD; the SNRIs desvenlafaxine, duloxetine, milnacipran, and venlafaxine; the novel antidepressants vilozidone and vortioxetine; 5-​HT3 receptor antagonists; and memantine and other glutamate-​ modulating agents. Also, RCTs of atomoxetine and zonisamide in BN would be informative. Recently approved weight-​loss drugs, including lorcaserin, naltrexone-​bupropion combination, phentermine-​ topiramate combination, and liraglutide 3 mg daily 384

Pharmacotherapy

sc injection, need to be evaluated in obese patients with BED or BN (Bray, Frühbeck, Ryan, & Wilding, 2016). Randomized, placebo-​ controlled trials of topiramate are probably warranted for NES. Studies of new compounds are also greatly needed in the treatment of EDs. Novel drugs in development for psychotic and bipolar disorders and diseases characterized by cachexia might be considered as potential candidates for study in the treatment of AN. Because hypercortisolemia usually accompanies AN, antiglucocorticoid agents might also represent potential therapeutic candidates (Parsons & Sapse, 1985). Novel compounds that might hold promise for both BN and BED include some of those in development for ADHD, mood disorders, addiction, and obesity. Thus, the norepinephrine-​ dopamine reuptake inhibitor dasotraline is currently being evaluated in patients in ADHD and those with BED (Childress & Tran, 2016; Koblan et al., 2015). Examples of such agents being developed for depression include serotonin-​ norepinephrine-​ dopamine (triple) reuptake inhibitors, serotonin-​ melatonin agents, and corticotropin-​ releasing hormone antagonists (Connolly & Thase, 2012). Examples of such compounds being developed for obesity include triple reuptake inhibitors (e.g., tesofensine), GLP-​1 receptor agonists beyond liraglutide, lipase inhibitors beyond orlistat (cetilistat), melanocortin-​4 receptor agonists (setmelanotide), neuropeptide Y5 receptor inhibitors, leptin receptor agonists (metreleptin), cannabinoid receptor antagonists beyond rimonabant; and the combination of bupropion with zonisamide (Kakkar & Dahiya, 2015; Kühnen et  al., 2016). Drugs with potential for both depression and obesity (e.g., triple reuptake inhibitors) might be especially promising candidates for BED. Some of the many drugs in development for epilepsy might also be considered as potential therapeutic agents for EDs, especially if they are associated with changes in appetite or body weight (French, Schachter, Sirven, & Porter, 2015). Pharmacotherapy research for EDs will need to be informed by advances in both clinical trial design and molecular genetics. Regarding the former, there is presently a lack of consensus about what constitutes ideal clinical trial design in ED pharmacotherapy research. This includes lack of agreement on assessment instruments; definitions of primary outcome and of response, remission, recovery, and relapse; stages of illness to be studied; metrics for reporting outcome; and how best to manage low completion rates (Brownley et  al., 2007; Bulik et al., 2007; Halmi et al., 2005; Shapiro et al., 2007;

Walsh et al., 2006). Regarding the latter, intensive research is needed to identify genes and endophenotypes that will predict response to treatment and facilitate novel drug discovery (Bulik et  al., 2007; Ramoz, Versini, & Gorwood, 2007; Yilmaz, Hardaway, & Bulik, 2015). Finally, for pharmacotherapy research in EDs to truly advance, it will need to be made a national priority. Such an advance will require collaborations among academia, the pharmaceutical industry, and governmental agencies. For example, one goal would be to form a network of sites devoted to conducting RCTs in EDs similar to the networks that have been successful in conducting RCTs in mood and psychotic disorders (Bowden et al., 2012; Lieberman et al., 2005; Rush, 2011). Another goal would be to foster public-​private partnership programs devoted to developing potential therapeutic compounds specifically targeting EDs, as has been done by the National Institute of Mental Health for mood, anxiety, and psychotic disorders (Brady, Winsky, Goodman, Oliveri, & Stover, 2009. In sum, pharmacotherapy has an important role in the management of EDs, especially in patients who refuse or are unresponsive to psychotherapy, patients with comorbid mental or medical disorders, and those with chronic or intractable EDs. However, the available pharmacotherapeutic armamentarium and its supporting evidence base for EDs is still far from adequate, and further study is needed to clarify which specific agents might be most useful for which patient subgroups. Novel medical treatments for EDs are greatly needed. In particular, rational drug discovery devoted to EDs needs to occur. In the meantime, current and future medications with psychotropic benefits and/​or effects on appetite and weight might be considered as potential therapeutic agents for these conditions.

References

Agras, W. S., Dorian, B., Kirkley, B. G., Arnow, B., & Bachman, J. (1987). Imipramine in the treatment of bulimia: A double-​ blind controlled study. International Journal of Eating Disorders, 6, 29–​38. Agras, W. S., Rossiter, E. M., Arnow, B., Schneider, J. A., Telch, C. F., Raeburn, S. D.,   .  .  .  Loran, L. M. (1992). Pharmacologic and cognitive-​behavioral treatment for bulimia nervosa: A controlled comparison. American Journal of Psychiatry, 149, 82–​87. Aigner, M., Treasure, J., Kaye, W., Kasper, S., WFSBP Task Force on Eating Disorders. (2011). World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for the pharmacological treatment of eating disorders. World Journal Biological Psychiatry, 12, 400–​443.

Alger, S. A., Schwalberg, M. D., Bigaouette, J. M., Michalek, A. V., & Howard, L. J. (1991). Effect of a tricyclic antidepressant and opiate antagonist on binge eating behavior in normo-​ weight bulimic and obese, binge-​ eating subjects. American Journal of Clinical Nutrition, 53, 865–​871. Alho, H., Lahti, T., Appelberg, B., et al. (2013). Opioid antagonist naloxone nasal spray treatment for patients with binge eating disorder: a randomized controlled trial. Poster # NR4-​29. Presented at American Psychiatric Association 166th Annual Meeting, May 18–​22, San Francisco, CA. American Psychiatric Association. (1980). Diagnostic and statistical manual of mental disorders, 3rd ed. Washington, DC: American Psychiatric Association. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders, 4th ed. Washington, DC: American Psychiatric Association. American Psychiatric Association. (2006). Treatment of patients with eating disorders. (3rd ed.). American Psychiatric Association. American Journal of Psychiatry, 163(Suppl 7), 4–​54. Andries, A., Frystyk, J., Flyvbjerg, A., & Støving, R. K. (2014). Dronabinol in severe, enduring anorexia nervosa: A randomized controlled trial. International Journal of Eating Disorders, 47, 18–​23. Andries, A., Frystyk, J., Flyvbjerg, A., & Støving, R. K. (2015). Changes in IGF-​I, urinary free cortisol and adipokines during dronabinol therapy in anorexia nervosa: Results from a randomised, controlled trial. Growth Hormone IGF Research, 25, 247–​252. Andries, A., Gram, B., & Støving, R. K. (2015). Effect of dronabinol therapy on physical activity in anorexia nervosa:  a randomised, controlled trial. Eating and Weight Disorders, 20, 13–​21. Appolinario, J. C., Bacaltchuk, J., Sichieri, R., Claudino, A. M., Godoy-​Matos, A., Morgan, C.,  . . .  Coutinho, W. (2003). A randomized, double-​ blind, placebo-​ controlled study of sibutramine in the treatment of binge-​eating disorder. Archives of General Psychiatry, 60, 1109–​1116. Aragona, M. (2007). Tolerability and efficacy of aripirazole in a case of psychotic anorexia nervosa comorbid with epilepsy and chronic renal failure. Eating Weight Disorders, 12, e54–​e57. Arnold, L. M., McElroy, S. L., Hudson, J. E., Welge, J. A., Bennett, A. J., & Keck, P. E. (2002). A placebo-​controlled, randomized trial of fluoxetine in the treatment of binge-​ eating disorder. Journal of Clinical Psychiatry, 63, 1028–​1033. Attia, E., Haiman, C., Walsh, B. T., & Flater, S. R. (1998). Does fluoxetine augment the inpatient treatment of anorexia nervosa? American Journal of Psychiatry, 155, 548–​551. Attia, E., Kaplan, A. S., Walsh, B. T., Gershkovich, M., Yilmaz, Z., Musante, D.,  . . .  Wang, Y. (2011). Olanzapine versus placebo for out-​patients with anorexia nervosa. Psychological Medicine, 41, 2177–​2182. Bacaltchuk, J., & Hay, P. (2003). Antidepressants versus placebo for people with bulimia nervosa. Cochrane Database of Systematic Reviews, Issue 4, CD003391. Bacaltchuk, J., Hay, P., & Trefiglio, R. (2001). Antidepressants versus psychological treatments and their combination for bulimia nervosa. Cochrane Database of Systematic Reviews, Issue 4, CD003385. Barbarich, N. C., McConaha, C. W., Halmi, K. A., Gendall, K., Sunday, S. R., Gaskill, J.,  . . .  Kaye, W. H. (2004). Use of nutritional supplements to increase the efficacy of fluoxetine

McElroy, Guerdjikova, Mori, Keck Jr.

385

in the treatment of anorexia nervosa. International Journal of Eating Disorders, 35, 10–​15. Barbee, J. G. (2003). Topiramate in the treatment of severe bulimia nervosa with comorbid mood disorders:  A  case series. International Journal of Eating Disorders, 33, 456–​472. Barcai, A. (1977). Lithium in adult anorexia nervosa: A pilot report on two patients. Acta Psychiatrica Scandinavica, 55, 97–​101. Beaumont, P. J., Russell, J. D., Touyz, S. W., Buckley, C., Lowinger, K., Talbot, P., & Johnson, G. F. (1997). Intensive nutritional counselling in bulimia nervosa:  A  role for supplementation with fluoxetine? Australian and New Zealand Journal of Psychiatry, 31, 514–​524. Biederman, J., Herzog, D. B., Rivinus, T. M., Harper, G. P., Ferber, R. A., Rosenbaum, J. F.,  . . .  Schildkraut, J. J. (1985). Amitriptyline in the treatment of anorexia nervosa:  A  double-​blind, placebo-​controlled study. Journal of Clinical Psychopharmacology, 5, 10–​16. Birmingham, C. L., Goldner, E. M., & Bakan, R. (1994). Controlled trial of zinc supplementation in anorexia nervosa. International Journal of Eating Disorders, 15, 251–​255. Birmingham, C. L., & Gritzner, S. (2006). How does zinc supplementation benefit anorexia nervosa? Eating and Weight Disorders, 11, 109–​111. Bissada, H., Tasca, G. A., Barber, A. M., & Bradwejn, J. (2008). Olanzapine in the treatment of low body weight and obsessive thinking in women with anorexia nervosa: A randomized, double-​blind, placebo-​controlled trial. American Journal of Psychiatry, 165, 1281–​1288. Bloch, M., Ish-​Shalom, S., Greenman, Y., Klein, E., & Latzer, Y. (2012). Dehydroepiandrosterone treatment effects on weight, bone density, bone metabolism and mood in women suffering from anorexia nervosa-​ a pilot study. Psychiatry Research, 200, 544–​549. Blouin, A. G., Blouin, J. H., Perez, E. L., Bushnik, T., Zuro, C., & Mulder, E. (1988). Treatment of bulimia with fenfluramine and desipramine. Journal of Clinical Psychopharmacology, 8, 261–​269. Bowden, C. L., Perlis, R. H., Thase, M. E., Ketter, T. A., Ostacher, M. M., Calabrese, J. R.,  . . .  Sachs, G. S. (2012). Aims and results of the NIMH systematic treatment enhancement program for bipolar disorder (STEP-​BD). CNS Neuroscience and Therapeutics, 18, 243–​249. Brady, L. S., Winsky, L., Goodman, W., Oliveri, M. E., & Stover, E. (2009). NIMH initiatives to facilitate collaborations among industry, academia, and government for the discovery and clinical testing of novel models and drugs for psychiatric disorders. Neuropsychopharmacology, 34, 229–​243. Brambilla F., Draisci, A., Peirone, A., & Brunetta, M. (1995a). Combined cognitive-​ behavioral, psychopharmacological and nutritional therapy in eating disorders. 1. Anorexia nervosa—​restricted type. Neuropsychobiology, 32, 59–​63. Brambilla F., Draisci, A., Peirone, A., & Brunetta, M. (1995b). Combined cognitive-​behavioral, psychopharmacological and nutritional therapy in eating disorders. 2. Anorexia nervosa—​ binge-​eating/​purging type. Neuropsychobiology, 32, 64–​67. Brambilla, F., Garcia, C. S., Fassino, S., Daga, G. A., Favara, A., Santonastaso, P.,   .  .  .  Monteleone, P. (2007). Olanzapine therapy in anorexia nervosa:  Psychobiological effects. International Clinical Psychopharmacology, 22, 197–​204. Brambilla, F., Samek, L., Company, M., Lovo, F., Cioni, L., & Mellado, C. (2009). Multivariate therapeutic approach to binge-​eating disorder: Combined nutritional, psychological

386

Pharmacotherapy

and pharmacological treatment. International Clinical Psychopharmacology, 24, 312–​317. Bray, G. A., Frühbeck, G., Ryan, D. H., & Wilding, J. P. (2016). Management of obesity. Lancet, 387, 1947–​1956. Brennan, B. P., Roberts, J. I., Fogarty, K. V., Reynolds, K. A., Jonas, J. M., & Hudson, J. I. (2008). Memantine in the treatment of binge eating disorder:  An open-​label, prospective trial. International Journal of Eating Disorders, 41, 520–​526. Brewerton, T. D. (2012). Antipsychotic agents in the treatment of anorexia nervosa:  Neuropsychopharmacologic rationale and evidence from controlled trials. Current Psychiatry Reports, 14, 398–​405. Brewerton, T. D., & Shannon, M. (1992). Possible clozapine exacerbation of bulimia nervosa. American Journal of Psychiatry, 149, 1408–​1409. Broft, A. I., Spanos, A., Corwin, R. L., Mayer, L., Steinglass, J., Devlin, M. J,  . . .  Walsh, B. T. (2007). Baclofen for binge eating:  An open-​label trial. International Journal of Eating Disorders, 40, 687–​691. Brownley, K. A., Berkman, N. D., Sedway, J. A., Lohr, K., & Bulik, C. M. (2007). Binge eating disorder treatment: A systematic review of randomized controlled trials. International Journal of Eating Disorders, 40, 337–​348. Brownley, K. A., Von Holle, A., Hamer, R. M., La Via, M., & Bulik, C. M. (2013). A double-​blind, randomized pilot trial of chromium picolinate for binge eating disorder: Results of the Binge Eating and Chromium (BEACh) study. Journal of Psychosomatic Research, 75, 36–​42. Bruno, A., Riganello, D., & Marino, A. (2009). Treatment with aripiprazole and topiramate in an obese subject with borderline personality disorder, obsessive-​compulsive symptoms and bulimia nervosa: A case report. Cases Journal, 2, 7288. Bulik, C. M., Hebebrand, J., Keski-​Rahkonen, A., Klump, K. L., Reichborn-​Kjeennerud, T., Mazzeo, S. E.,   .  .  .  Wade, T. D. (2007). Genetic epidemiology, endophenotypes, and eating disorder classification. International Journal of Eating Disorders, 40, S52–​S60. Carruba, M. O., Cuzzolaro, M., Riva, L., Bosello, O., Liberti, S., Castra, R.,  . . .  Nisoli, E. (2001). Efficacy and tolerability of moclobemide in bulimia nervosa: A placebo-​controlled trial. International Journal of Psychopharmacology, 16, 27–​32. Casper, R. C., Schlemmer, R. F., & Javaid, J. I. (1987). A placebo-​controlled crossover study of oral clonidine in acute anorexia nervosa. Psychiatry Research, 20, 249–​260. Cassano, G. B., Miniati, M., Pini, S., Rotondo, A., Banti, S., Borri, C.,  . . .  Mauri, M. (2003). Six-​month open trial of haloperidol as an adjunctive treatment for anorexia nervosa:  A  preliminary report. International Journal of Eating Disorders, 33, 172–​177. Childress, A., & Tran, C. (2016). Current investigational drugs for the treatment of attention-​deficit/​hyperactivity disorder. Expert Opinion on Investigational Drugs, 25, 463–​474. Chung, A. M., & Reed, M. D. (2004). Intentional topiramate ingestion in an adolescent female. Annals of Pharmacotherapy, 38, 1439–​1442. Claudino, A. M., de Oliveira, I. R., Appolinario, J. C., Cordás, T. A., Duchesne, M., Sichiere, R.,  . . .  Bacaltchuk, J. (2007). Double-​blind, randomized, placebo-​controlled trial of topiramate plus cognitive-​behavior therapy in binge-​eating disorder. Journal of Clinical Psychiatry, 68, 1324–​1332. Claudino, A. M., Hay, P., Lima, M. S., Bacaltchuk, J., Schmidt, U., & Treasure, J. (2006). Antidepressants for anorexia

nervosa. Cochrane Database Systematic Reviews, Issue 1, CD004365. Cochrane, C., & Malcolm, R. (2002). Case report of abuse of orlistat. Eating Behavior, 3, 167–​169. Colman, E. (2005). Anorectics on trial: A half century of federal regulation of prescription appetite suppressants. Annals of Internal Medicine, 143, 380–​385. Colom, F., Vieta, E., Benabarre, A., Martinez-​Arán, A., Reinares, M., Corbella, B.,  . . .  Gastó, C. (2001). Topiramate abuse in a bipolar patient with an eating disorder. Journal of Clinical Psychiatry, 62, 475–​476. Connolly, K. R., & Thase, M. E. (2012). Emerging drugs for major depressive disorder. Expert Opinion of Emerging Drugs, 17, 105–​126. Corwin, R. L., Boan, J., Peters, K. F., & Ulbrecht, J. S. (2012). Baclofen reduces binge eating in a double-​blind, placebo-​ controlled, crossover study. Behavioral Pharmacology, 23, 616–​625. Court, A., Mulder, C., Kerr, M., Yuen, H. P., Boasman, M., Goldstone, S.,  . . .  Berger, G. (2010). Investigating the effectiveness, safety and tolerability of quetiapine in the treatment of anorexia nervosa in young people: A pilot study. Journal of Psychiatric Research, 44, 1027–​1034. Crisp, A. H., Lacey, J. H., & Crutchfield, M. (1987). Clomipramine and “drive” in people with anorexia nervosa:  An inpatient study. British Journal of Psychiatry, 150, 355–​358. Crockford, D. N., Fisher, G., & Barker, P. (1997). Risperidone, weight gain, and bulimia nervosa. Canadian Journal of Psychiatry, 42, 326–​327. De Beaurepaire, R., Joussaume, B., Rapp, A., & Jaury, P. (2015). Treatment of binge eating disorder with high-​dose baclofen: A case series. Journal of Clinical Psychopharmacology, 35, 357–​359. De Bernardi, C., Ferraris, S., D’Innella, P., Do, F., & Torre, E. (2005). Topiramate for binge eating disorder. Progress in Neuro-​ Psychopharmacology and Biological Psychiatry, 29, 339–​341. Deb, K. S., Gupta, R., & Varshney, M. (2014). Orlistat abuse in a case of bulimia nervosa:  The changing Indian society. General Hospital Psychiatry, 36, e3–​e4. Devlin, J. J., Goldfein, J. A., Carino, J. S., & Wolk, S. L. (2000). Open treatment of overweight binge eaters with phentermine and fluoxetine as an adjunct to cognitive-​behavioral therapy. International Journal of Eating Disorders, 28, 325–​332. Devlin, M. J., Goldfein, J. A., Petkova, E., Jiang, H., Raizman, P. S., Wolk, S.,  . . .  Walsh, B. T. (2005). Cognitive behavioral therapy and fluoxetine as adjuncts to group behavioral therapy for binge eating disorder. Obesity Research, 13, 1077–​1088. Devlin, M. J., Goldfein, J. A., Petkova, E., Liu, L., & Walsh, B. T. (2007). Cognitive behavioral therapy and fluoxetine for binge eating disorder:  Two-​year follow-​up. Obesity (Silver Spring), 15, 1702–​1709. Devlin, M. J., Kissileff, H. R., Zimmerli, E. J., Samuels, F., Chen, B. E., Brown, A. J.,  . . .  Walsh, B. T. (2012). Gastric emptying and symptoms of bulimia nervosa: Effect of a prokinetic agent. Physiology and Behavior, 106, 238–​242. de Vos, J., Houtzager, L., Katsaragaki, G., van de Berg, E., Cuijpers, P., & Dekker J. (2014). Meta analysis on the efficacy of pharmacotherapy versus placebo on anorexia nervosa. Journal of Eating Disorders, 2, 27.

Dolberg, O. T., Barkai, G., Gross, Y., & Schreiber, S. (2005). Differential effects of topiramate in patients with traumatic brain injury and obesity:  A  case series. Psychopharmacology (Berl.), 179, 838–​845. Dold, M., Aigner, M., Klabunde, M., Treasure, J., & Kasper, S. (2015). Second-​generation antipsychotic drugs in anorexia nervosa:  A  meta-​analysis of randomized controlled trials. Psychotherapy and Psychosomatics, 84, 110–​116. Drewnowski, A., Krahn, D. D., Demitrack, M. A., Nairn, K., & Gosnell, B. A. (1995). Naloxone, an opiate blocker, reduces the consumption of sweet high-​fat foods in obese and lean female binge eaters. American Journal of Clinical Nutrition, 61, 1206–​1212. Drimmer, E. J. (2003). Stimulant treatment of bulimia nervosa with and without attention-​deficit disorder: Three case reports. Nutrition, 19, 76–​77. Dukarm, C. P. (2005). Bulimia nervosa and attention deficit hyperactivity disorder: A possible role for stimulant medication. Journal of Women’s Health, 14, 345–​350. Dunican, K. C., & DelDotto, D. (2007). The role of olanzapine in the treatment of anorexia nervosa. Annals of Pharmacotherapy, 41, 111–​115. Duvvuri, V., Cromley, T., Klabunde, M., Boutelle, K., & Kaye, W. H. (2012). Differential weight restoration on olanzapine versus fluoxetine in identical twins with anorexia nervosa. International Journal of Eating Disorders, 45, 294–​297. El-​Giamal, N., deZwaan, M., Bailer, U., Lennkh, C., Schussler, P., Strnad, A.,   .  .  .  Kasper, S. (2000). Reboxetine in the treatment of bulimia nervosa:  A  report of seven cases. International Clinical Psychopharmacology, 15, 351–​356. El-​Giamal, N., deZwaan, M., Bailer, U., Strnad, A., Schüssler, P., & Kasper, S. (2003). Milnacipran in the treatment of bulimia nervosa:  A  report of 16 cases. European Neuropsychopharmacology, 123, 73–​79. Fahy, T. A., Eisler, I., & Russell, G. F. (1993). A placebo-​ controlled trial of d-​fenfluramine in bulimia nervosa. British Journal of Psychiatry, 162, 597–​603. Faris, P. L., Kim, S. W., Meller, W. H., Goodale, R. L., Oakman, S. A., Hofbauer, R. D.,  . . .  Hartman, B. K. (2000). Effect of decreasing afferent vagal activity with ondansetron on symptoms of bulimia nervosa: A randomized, double-​blind trial. Lancet, 35, 792–​797. Fassino, S., Daga, G. A., Boggio, S., Garzaro, L., & Piero, A. (2004). Use of reboxetine in bulimia nervosa: A pilot study. Journal of Psychopharmacology, 18, 423–​428. Fazeli, P. K., Calder, G. L., Miller, K. K., Misra, M., Lawson, E. A., Meenaghan, E.,  . . .  Klibanski, A. (2012). Psychotropic medication use in anorexia nervosa between 1997 and 2009. International Journal of Eating Disorders, 45, 970–​976. Fazeli, P., Lawson, E. A., Faje, A. T., Eddy, K. T., Gaal, I., DeSanti, R.,  . . .  Klibanski, A. (2016). Short-​term treatment with a ghrelin agonist significantly improves gastric emptying in anorexia nervosa. Presented at The Endocrine Society Annual Meeting; April 1–​4, 2016; Boston, MA. Fazeli, P., Lawson, E. A., Prabhakaran, R., Miller, K. K., Donoho, D. A., Clemmons, D. R.,  . . .  Klibanski, A. (2010). Effects of recombinant human growth hormone in anorexia nervosa:  A  randomized, placebo-​ controlled study. Journal Clinical Endrocrinology Metabolism, 95, 4889–​4897. Felstrom, A., & Blackshaw, S. (2002). Topiramate for bulimia nervosa with bipolar II disorders. American Journal of Psychiatry, 159, 1246–​1247.

McElroy, Guerdjikova, Mori, Keck Jr.

387

Fernández-​Aranda, F., Amor, A., Jiménez-​Murcia, S., Giménez-​ Martínez, L., Turón-​Gil, V., & Vallejo-​Ruiloba, J. (2001). Bulimia nervosa and misuse of orlistat:  Two case reports. International Journal of Eating Disorders, 30, 458–​461. Fichter, M. M., Krüger, R., Rief, W., Holland, R., & Döhne, J. (1996). Fluvoxamine in prevention of relapse in bulimia nervosa:  Effects on eating-​ specific psychopathology. Pharmacopsychiatry, 30, 85–​92. Fichter, M. M., Leibl, K., Rief, W., Brunner, E., Schmidt-​ Auberger, S., & Engel, R. R. (1991). Fluoxetine versus placebo: A double-​blind study with bulimic inpatients undergoing intensive psychotherapy. Pharmacopsychiatry, 24, 1–​7. Fisman, S., Steele, M., Short, J., Byrne, T., & Lavallee, C. (1996). Case study: Anorexia nervosa and autistic disorder in an adolescent girl. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 937–​940. Fluoxetine Bulimia Nervosa Collaborative Study Group (FBNCSG). (1992). Fluoxetine in the treatment of bulimia nervosa:  A  multicenter, placebo-​controlled, double-​blind trial. Archives of General Psychiatry, 49, 139–​147. Fountoulakis, K. N., Iacovides, A., Siamouli, M., Koumaris, V., & Kaprinis, G. S. (2006). Successful treatment of anorexia with a combination of high-​dose olanzapine, fluoxetine, and mirtazapine. International Journal of Clinical Pharmacology Therapy, 44, 452–​453. Frank, G. K. (2016). Aripiprazole, a partial dopamine agonist to improve adolescent anorexia nervosa-​A case series. International Journal of Eating Disorders, 49, 529–​533. French, J. A., Schachter, S. C., Sirven, J., & Porter, R. (2015). The Epilepsy Foundation’s 4th biennial epilepsy pipeline update conference. Epilepsy Behavior, 46, 34–​50. Gaisor, M., Hudson, J., Quintero, J., Ferreira-​Cornwell, M. C., Radewonak, J., & McElroy, S. L. (2017). A phase 3, multicenter, open-​label, 12-​month extension safety and tolerability trial of lisdexamfetamine dimesylate in adults with binge eating disorder. Journal of Clinical Psychopharmacology, 50, 315–322. Gardin, J. M., Schumacher, D., Constantine, G., Davis, K. D., Leung, C., & Reid, C. L. (2000). Valvular abnormalities and cardiovascular status following exposure to dexfenfluramine or phentermine/​fenfluramine. JAMA, 283, 1703–​1709. Garner, D. M. (1991). Eating disorder inventory-​2:  Professional manual. Odessa, FL: Psychological Assessment Resources. Gebhardt, S., Haberhausen, M., Krieg, J. C., Remschmidt, H., Heinzel-​Gutenbrunner, M., Hebebrand, J.,   .  .  .  Theisen, F. M. (2007). Clozapine/​olanzapine-​induced recurrence or deterioration of binge eating-​related eating disorders. Journal of Neural Transmission, 114, 1091–​1095. Golay, A., Laurent-​ Jaccard, A., Habicht, F., Gachoud, J. P., Chabloz, M., Kammer, A.,  . . .  Schutz, Y. (2005). Effect of orlistat in obese patients with binge eating disorder. Obesity Research, 13, 1701–​1708. Goldberg, S. C., Halmi, K. A., Eckert, E. D., Casper, R. C., & Davis, J. M. (1979). Cyproheptadine in anorexia nervosa. British Journal of Psychiatry, 134, 67–​70. Goldbloom, D. S., Olmsted, M., Davis, R., Clewes, J., Heinmaa, M., Rockert, W.,  . . .  Shaw, B. (1997). A randomized controlled trial of fluoxetine and cognitive behavioral therapy for bulimia nervosa:  Short-​term outcome. Behavioral Research and Therapy, 35, 803–​811. Gormally, J., Black, S., Daston, S., & Rardin, D. (1982). The assessment of binge eating severity among obese persons. Addictive Behavior, 7, 47–​55.

388

Pharmacotherapy

Goudie, A. J., Cooper, G. D., Cole, J. C., & Sumnall, H. R. (2007). Cyproheptadine resembles clozapine in vivo following both acute and chronic administration in rats. Journal of Psychopharmacology, 21, 179–​190. Greenway, F. L., Dahms, W. T., & Bray, G. A. (1977). Phenytoin as a treatment of obesity associated with compulsive eating. Current Therapeutic Research, 21, 338–​342. Grigoriadis, S., Kaplan, A., Carter, J., & Woodside, B. (2001). What treatments patients seek after inpatient care:  A  followup of 24 patients with anorexia nervosa. Eating and Weight Disorders, 6, 115–​120. Grilo, C. M., Masheb, R. M., & Salant, S. L. (2005). Cognitive behavioral therapy guided self-​ help and orlistat for the treatment of binge eating disorder:  A  randomized, double-​ blind, placebo-​ controlled trial. Biological Psychiatry, 57, 1193–​1201. Grilo, C. M., Masheb, R. M., & Wilson, G. T. (2005). Efficacy of cognitive behavioral therapy and fluoxetine for the treatment of binge eating disorder: A randomized double-​blind placebo-​controlled comparison. Biological Psychiatry, 57, 301–​309. Grilo, C. M., & White, M. A. (2013). Orlistat with behavioral weight loss for obesity with versus without binge eating disorder: Randomized placebo-​controlled trial at a community mental health center serving educationally and economically disadvantaged Latino/​as. Behavior Research Therapy, 51, 167–​175. Gross, H., Ebert, M. H., Faden, V. B., Goldberg, S. C., Kaye, W. H., Caine, E. D.,  . . .  Zinberg, N. (1983). A double-​blind trial of delta 9-​tetrahydrocannabinol in primary anorexia nervosa. Journal of Clinical Psychopharmacology, 3, 165–​171. Gross, H., Ebert, M. H., Faden, V. B., Goldberg, S. C., Kaye, W. H., Caine, E. D.,  . . .  Kaye, W. H. (1981). A double-​blind controlled study of lithium carbonate in primary anorexia nervosa. Journal of Clinical Psychopharmacology, 1, 376–​381. Guerdjikova, A. I., Blom, T. J., Martens, B. E., Keck, P. E., Jr., & McElroy, S. L. (2013). Zonisamide in the treatment of bulimia nervosa:  An open-​ label, pilot, prospective study. International Journal of Eating Disorders, 46, 747–​750. Guerdjikova, A. I., Blom, T. J., Mori, N., & McElroy, S. L. (2013). N-​ acetylcysteine in bulimia nervosa:  Open-​ label trial. Eating Behavior, 14, 87–​89. Guerdjikova, A. I., Fitch, A., & McElroy, S. L. (2015). Successful treatment of binge eating disorder with combination phentermine/​ topiramate extended release. Primary Care Companion for CNS Disorders, 17. Guerdjikova, A. I., Kotwal, R., & McElroy, S. L. (2005). Response of recurrent binge eating and weight gain to topiramate in patients with binge eating disorder after bariatric surgery. Obesity Surgery, 15, 273–​277. Guerdjikova, A. I., & McElroy, S. L. (2013). Adjunctive methylphenidate in the treatment of bulimia nervosa co-​occurring with bipolar disorder and substance dependence. Innovative Clinical Neuroscience, 10, 30–​33. Guerdjikova, A. I., McElroy, S. L., Kotwal, R., Welge, J. A., Nelson, E., Lake, K.,  . . .  Hudson, J. I. (2008). High-​dose escitalopram in the treatment of binge-​eating disorder with obesity:  A  placebo-​ controlled monotherapy trial. Human Psychopharmacology, 23, 1–​11. Guerdjikova, A. I., McElroy, S. L., Welge, J. A., Nelson, E., Keck, P. E., & Hudson, J. I. (2009). Lamotrigine in the treatment of binge-​eating disorder with obesity: A randomized,

placebo-​controlled monotherapy trial. International Clinical Psychopharmacology, 24, 150–​158. Guerdjikova, A. I., McElroy, S. L., Winstanley, E. L., Nelson, E. B., Mori, N., & McCoy, J. (2012) Duloxetine in the treatment of binge eating disorder with depressive disorders:  A  placebo-​controlled trial. International Journal of Eating Disorders, 45, 281–​289. Guille, C., & Sachs, G. (2002). Clinical outcome of adjunctive topiramate treatment in a sample of refractory bipolar patients with comorbid conditions. Progress in Neuro -​ Psychopharmacology and Biological Psychiatry, 26, 1035–​1039. Hagman, J., Gralla, J., Sigel, E., Ellert, S., Dodge, M., Gardner, R.,  . . .  Wamboldt, M. Z. (2011). A double-​blind, placebo-​ controlled study of risperidone for the treatment of adolescents and young adults with anorexia nervosa:  A  pilot study. Journal of the American Academy of Child Adolescent Psychiatry, 50, 915–​924. Halmi, K. A., Agras, W. S., Crow, S., Mitchell, J., Wilson, G. T., Bryson, S. W.,  . . .  Kraemer, H. C. (2005). Predictors of treatment acceptance and completion in anorexia nervosa:  Implications for future study designs. Archives of General Psychiatry, 62, 776–​781. Halmi, K. A., Eckert, E., LaDu, T. J., & Cohen, J. (1986). Anorexia nervosa: Treatment efficacy of cyproheptadine and amitriptyline. Archives of General Psychiatry, 43, 177–​181. Hay, P., Chinn, D., Forbes, D., Madden, S., Newton, R., Sugenor, L.,   .  .  .  Ward, W. (2014). Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for the treatment of eating disorders. Australian and New Zealand Journal of Psychiatry, 48, 977–​1008. Hazen, E., & Fava, M. (2006). Successful treatment with duloxetine in a case of treatment refractory bulimia nervosa: A case report. Journal of Psychopharmacology, 20, 723–​724. Hedges, D. W., Reimherr, F. W., Hoopes, S. P., Rosenthal, N. R., Kamin, R., & Capace, J. A. (2003). Treatment of bulimia nervosa with topiramate in a randomized, double-​blind, placebo-​controlled trial, part 2: Improvement in psychiatric measures. Journal of Clinical Psychiatry, 64, 1449–​1454. Hermanussen, M., & Tresguerres, J. A. (2005). A new anti-​ obesity drug treatment: First clinical evidence that, antagonizing glutamate-​gated Ca2 + ion channels with memantine normalizes binge-​ eating disorders. Economics and Human Biology, 3, 329–​337. Herridge, P. L., & Pope, H. G., Jr. (1985). Treatment of bulimia and rapid-​cycling bipolar disorder with sodium valproate: A case report. Journal of Clinical Psychopharmacology, 5, 229–​230. Hill, K., Bucuvalas, J., McClain, C., Kryscio, R., Martini, R. T., Alfaro, M. P.,  . . .  Maloney, M. (2000). Pilot study of growth hormone administration during the refeeding of malnourished anorexia nervosa patients. Journal of Child and Adolescent Psychopharmacology, 10, 3–​8. Hofmann, S. G., Meuret, A. E., Smits, J. A., Simon, N. M., Pollack, M. H., Eisenmenger, K.,.  . . .  Pollack, M. H. (2006). Augmentation of exposure therapy with D-​cycloserine for social anxiety disorder. Archives of General Psychiatry, 63, 298–​304. Hoopes, S. P., Reimherr, F. W., Hedges, D. W., Rosenthal, N. R., Kamin, R., Karim, R.,  . . .  Karvois, D. (2003). Treatment of bulimia nervosa with topiramate in a randomized, double-​ blind, placebo-​ controlled trial, part  1:  Improvement in

binge and purge measures. Journal of Clinical Psychiatry, 64, 1335–​1341. Horne, R. L., Ferguson, J. M., Pope, H. G., Jr, Hudson, J. I., Lineberry, C. G., Ascher, J.,  . . .  Cato, A. (1988). Treatment of bulimia with bupropion:  A  multicenter controlled trial. Journal of Clinical Psychiatry, 49, 262–​266. Hrdlicka, M., Beranova, I., Zamecnikova, R., & Urbanek, T. (2008). Mirtazapine in the treatment of adolescent anorexia nervosa. Case-​control study. European Child and Adolescent Psychiatry, 17, 187–​189. Hsu, L. K., Clement, L., Sandhouse, R., & Ju, E. S. (1991). Treatment of bulimia nervosa with lithium carbonate: A controlled study. Journal of Mental and Nervous Disease, 179, 351–​355. Hudson, J. I., McElroy, S. L., Ferreira-​ Cornwell, M. C., Radewonuk, J., & Gaisor, M. (2017). Efficacy of lisdexamfetamine in adults with moderate to severe binge eating disorder: A randomized clinical trial. JAMA Psychiatry, 74, 903–910. Hudson, J. I., McElroy, S. L., Raymond, N. C., Crow, S., Keck, P. E., Jr., Carter, W. P.,  . . .  Jonas, J. M. (1998). Fluvoxamine in the treatment of binge-​eating disorder:  A  multicenter placebo-​controlled, double-​blind trial. American Journal of Psychiatry, 155, 1756–​1762. Hudson, J. I., Pope, H. G., Jr., Jonas, J. M., & Yurgelun-​ Todd, D. (1985). Treatment of anorexia nervosa with antidepressants. Journal of Clinical Psychopharmacology, 5, 17–​23. Hudson, J. I., & Pope, H. G., Jr. (1988). The role of anticonvulsants in the treatment of bulimia. In S. L. McElroy, & H. G. Pope Jr. (Eds.), Use of anticonvulsants in psychiatry (pp. 141–​153). Clifton, NJ: Oxford Health Care. Jaafar, N. R., Daud, T. I., Rahman, F. N., & Baharudin, A. (2007). Mirtazapine for anorexia nervosa with depression. Australia and New Zealand Journal of Psychiatry, 41, 768–​769. Jonas, J. M., & Gold, M. S. (1988). The use of opiate antagonists in treating bulimia:  A  study of low dose versus high dose naltrexone. Psychiatry Research, 24, 195–​199. Kafantaris, V., Leigh, E., Hertz, S., Berest, A., Schebendach, J., Sterling, W. M.,.  . . .  Malhotra, A. K. (2011). A placebo-​ controlled pilot study of adjunctive olanzapine for adolescents with anorexia nervosa. Journal of Child and Adolescent Psychopharmacology, 21, 207–​212. Kakkar, A. K. & Dahiya, N. (2015). Drug treatment of obesity: Current status and future prospects. European Journal of Internal Medicine, 26, 89–​94. Kanerva, R., Rissanen, A, & Sarna, S. (1994). Fluoxetine in the treatment of anxiety, depressive symptoms, and eating-​ related symptoms in bulimia nervosa. Nordic Journal of Psychiatry, 49, 237–​242. Kaplan, A. S. (1987). Anticonvulsant treatment of eating disorders. In P. E. Garfinkel & D. M. Garner (Eds.), The role of drug treatments for eating disorders (pp. 96–​123). New York: Brunner/​Mazel. Kaplan, A. S., Garfinkel, P. E., Darby, P. L., & Garner, D. M. (1983). Carbamazepine in the treatment of bulimia. American Journal of Psychiatry, 140, 1225–​1226. Katz, R. L., Keen, C. L., Litt, I. F., Hurley, L. S., Kellams-​ Harrison, K. M., & Glader, L. J. (1987). Zinc deficiency in anorexia nervosa. Journal of Adolescent Health Care, 8, 400–​406.

McElroy, Guerdjikova, Mori, Keck Jr.

389

Kaye, W. H., Nagata, T., Weltzin, T. E., Hsu, L. K., Sokol, M. S., McConaha, C.,   .  .  .  Deep, D. (2001). Double-​blind placebo-​controlled administration of fluoxetine in restricting and restricting-​purging-​type anorexia nervosa. Biological Psychiatry, 49, 644–​652. Kaye, W. H., Weltzin, T. E., Hsu, L. K., & Bulik, C. M. (1991). An open trial of fluoxetine in patients with anorexia nervosa. Journal of Clinical Psychiatry, 52, 464–​471. Kennedy, S. H., Goldbloom, D. S., Ralevski, E., Davis, C., Disouza, J. D., & Lofchy, J. (1993). Is there a role for selective monoamine oxidase inhibitor therapy in bulimia nervosa? A  placebo-​controlled trial of brofaromine. Journal of Clinical Psychopharmacology, 13, 415–​422. Kennedy, S. H., Piran, N., Warsh, J. J., Prendergast, P., Mainprize, E., Whynot, C.,  . . .  Lofchy, J. (1988). A trial of isocarboxazid in the treatment of bulimia nervosa. Journal of Clinical Psychopharmacology, 8, 391–​396. Keshen, A., & Ivanova, I. (2013). Reduction of bulimia nervosa symptoms after psychostimulant initiation in patients with comorbid ADHD:  Five case reports. Eating Disorders, 21, 360–​369. Kim, Y. R., Eom, J. S., Yang, J. W., Kang, J., & Treasure, J. (2015). The impact of oxytocin on food intake and emotion recognition in patients with eating disorders: A double blind single dose within-​subject cross-​over design. PLos One, 10, e0137514. Kim, Y. R., Kim, C. H., Cardi, V., Eom, J. S., Seong, Y., & Treasure, J. (2014). Intranasal oxytocin attenuates attentional bias for eating and fat shape stimuli in patients with anorexia nervosa. Psychoneuroendocrinology, 44, 133–​142. Kim, Y. R., Kim, C. H., Park, J. H., Pyo, J., & Treasure, J. (2014). The impact of intranasal oxytocin on attention to social emotional stimuli in patients with anorexia nervosa:  A  double blind within-​subject cross-​over experiment. PLoS One, 9, e90721. Kishi, T., Kafantaris, V., Sunday, S., Sheridan, E. M., & Correll, C. U. (2012). Are antipsychotics effective for the treatment of anorexia nervosa? Results from a systematic review and meta-​analysis. Journal of Clinical Psychiatry, 73, e757–​e766. Knable, M. (2001). Topiramate for bulimia nervosa in epilepsy. American Journal of Psychiatry, 158, 322–​323. Koblan, K. S., Hopkins, S. C., Sarma, K., Jin, F., Goldman, R., Kollins, S. H.,  . . .  Loebel, A. (2015). Dasotraline for the treatment of attention-​deficit/​hyperactivity disorder: A randomized, double-​blind, placebo-​controlled, proof-​of-​concept trial in adults. Neuropsychopharmacology, 40, 2745–​2752. Kolata, G. G. (1980). NIH shaken by death of research volunteer. Science, 209, 475–​476, 478–​479. Kotwal, R., Guerdjikova, A., McElroy, S. L., & Keck, P. E., Jr. (2006). Lithium augmentation of topiramate for bipolar disorder with comorbid binge eating disorder and obesity. Human Psychopharmacology, 21, 425–​431. Kucukgoncu, S., Midura, M., & Tek, C. (2015). Optimal management of night eating syndrome: Challenges and solutions. Neuropsychiatric Disease and Treatment, 11, 751–​760. Kühnen, P., Clément, K., Wiegand, S., Blankenstein, O., Gottesdiener, K., Martini, L. L.,   .  .  .  Krude, H. (2016). Proopiomelanocortin deficiency treated with a melanocortin-​ 4 receptor agonist. New England Journal of Medicine, 375, 240–​246. Lacey, J. H., & Crisp, A. H. (1980). Hunger, food intake and weight: The impact of clomipramine on a refeeding anorexia nervosa population. Postgrad Med J, 56(Suppl 1), 79–​85.

390

Pharmacotherapy

Laederach-​ Hofmann, K., Graf, C., Horber, F., Lippuner, K., Lederer, S., Michel, R.,   .  .  .  Schneider, M. (1999). Imipramine and diet counseling with psychological support in the treatment of obese binge eaters: A randomized, placebo-​controlled double-​blind study. International Journal of Eating Disorders, 26, 231–​244. Lask, B., Fosson, A., Rolfe, U., & Thomas, S. (1993). Zinc deficiency and childhood-​onset anorexia nervosa. Journal of Clinical Psychiatry, 54, 63–​66. Lebow, J., Chuy, J. A., Cedermark, K., Cook, K., & Sim, L. A. (2015). The development or exacerbation of eating disorder symptoms after topiramate initiation. Pediatrics, 135, e1312–​e1316. Lebow, J., Sim, L. A., Erwin, P. J., & Murad, M. H. (2013). The effect of atypical antipsychotic medications in individuals with anorexia nervosa: A systematic review and meta-​analysis. International Journal of Eating Disorders, 46, 332–​339. Leitenberg, H., Rosen, J. C., Wolf, J., Vara, L. S., Detzer, M. J., & Srebnik, D. (1994). Comparison of cognitive-​behavior therapy and desipramine in the treatment of bulimia nervosa. Behavior Research Therapy, 32, 37–​45. Leombruni, P., Gastaldi, F., Lavagnino, L., & Fassino, S. (2008). Oxcarbazepine for the treatment of binge eating disorder: A case series. Advances in Therapy, 25, 718–​724. Leombruni, P., Pierò, A., Brustolin, A., Mondelli, V., Levi, M., Campisi, S.,  . . .  Fassino, S. (2006). A 12 to 24 weeks pilot study of sertraline treatment in obese women binge eaters. Human Psychopharmacology, 21, 181–​188. Leombruni, P., Pierò, A., Lavagnino, L., Brustolin, A., Campisi, S., & Fassino, S. (2008). A randomized, double-​ blind trial comparing sertraline and fluoxetine 6-​ month treatment in obese patients with binge eating disorder. Progress in Neuropsychopharmacology and Biological Psychiatry, 32, 1599–​1605. Leyba, C. M., & Gold, D. D. (1988). The relation between rapid-​cycling cyclothymia and bulimia; Case reports of two women. South Dakota Journal of Medicine, 41, 21–​22. Lieberman, J. A., Stroup, T. S., McEvoy, J. P., Swartz, M. S., Rosenheck, R. A., Perkins, D. O.,  . . .  Hsiao, J. K. (2005). Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. New England Journal of Medicine, 353, 1209–​1223. Luby, E. D., Marrazzi, M. A., & Kinzie, J. (1987). Treatment of chronic anorexia nervosa with opiate blockade. Journal of Clinical Psychopharmacology, 7, 52–​53. Malhotra, S., King, K. H., Welge, J. A., Brunsman-​Lovins, L., & McElroy, S. L. (2002). Venlafaxine treatment of binge-​eating disorder associated with obesity:  A  series of 35 patients. Journal of Clinical Psychiatry, 63, 802–​806. Malhotra, S., & McElroy, S. L. (2002). Orlistat misuse in bulimia nervosa. American Journal of Psychiatry, 159, 492–​493. Marrazzi, M. A., Bacon, J. P., Kinzie, J., & Luby, E. D. (1995). Naltrexone use in the treatment of anorexia nervosa and bulimia nervosa. International Clinical Psychopharmacology, 10, 163–​172. Marrazzi, M. A., Markham, K. M., Kinzie, J., & Luby, E. D. (1995). Binge eating disorder:  Response to naltrexone. International Journal of Obesity Related Metabolic Disorders, 19, 143–​145. Marzola, E., Desedime, N., Giovannone, C., Amianto, F., Fassino, S., & Abbate-​Daga, G. (2015). Atypical antipsychotics as augmentation therapy in anorexia nervosa. PLos One, 10, e0125569.

McCann, U. D., & Agras, W. S. (1990). Successful treatment of nonpurging bulimia nervosa with desipramine: A double-​ blind, placebo-​ controlled study. American Journal of Psychiatry, 147, 1509–​1513. McElroy, S. L., Arnold, L. M., Shapira, N. A., Keck, P. E., Jr., Rosenthal, N. R., Karim, M.,   .  .  .  Hudson, J. I. (2003). Topiramate in the treatment of binge eating disorder associated with obesity:  A  randomized, placebo-​ controlled trial [published erratum appears in American Journal of Psychiatry 2003;160:612]. American Journal of Psychiatry, 160, 255–​261. McElroy, S. L., Casuto, L. S., Nelson, E. B., Lake, K. A., Soutullo, C. A., Keck, P. E., Jr.,  . . .  Hudson, J. I. (2000). Placebo-​ controlled trial of sertraline in the treatment of binge eating disorder. American Journal of Psychiatry, 157, 1004–​1006. McElroy, S. L., Guerdjikova, A. I., Blom, T. J., Crow, S. J., Memisoglu, A., Silverman, B. L.,  . . .  Ehrich, E. W. (2013). A placebo-​controlled pilot study of the novel opioid receptor antagonist ALKS-​33 in binge eating disorder. International Journal of Eating Disorders, 46, 239–​245. McElroy, S. L., Guerdjikova, A. I., Kim, D. D., Burns, C., Harris-​ Collazo, R., Landbloom, R.,  . . .  Dunayevich, E. (2013). Naltrexone/​bupropion combination therapy in overweight or obese patients with major depressive disorder: Results of a pilot study. Primary Care Companion CNS Disorders, 15. McElroy, S. L., Guerdjikova, A., Kotwal, R., Welge, J. A., Nelson, E. B., Lake, K. A.,  . . .  Hudson, J. I. (2007). Atomoxetine in the treatment of binge-​eating disorder:  A  randomized placebo-​controlled trial. Journal of Clinical Psychiatry, 68, 390–​398. McElroy, S. L., Guerdjikova, A. I., Martens, B., Keck, P. E., Jr., Pope, H. G., Jr., & Hudson, J. I. (2009). Role of antiepileptic drugs in the management of eating disorders. CNS Drugs, 23, 139–​156. McElroy, S. L., Guerdjikova, A. I., Winstanley, E. L., O’Melia, A. M., Mori, N., Keck, P. E., Jr.,  . . .  Hudson, J. I. (2011). Sodium oxybate in the treatment of binge eating disorder:  An open-​label, prospective study. International Journal of Eating Disorders, 44, 262–​268. McElroy, S. L., Hudson, J. I., Capece, J. A., Beyers, K., Fisher, A. C., & Rosenthal, N. R. (2007). Topiramate for the treatment of binge eating disorder associated with obesity: A placebo-​ controlled study. Biological Psychiatry, 61, 1039–​1048. McElroy, S. L., Hudson, J., Ferreira-​ Cornwell, M. C., Radewonuk, J., Whitaker, T., & Gaisor, M. (2016). Lisdexamfetamine dimesylate for adults with moderate to severe binge eating disorder: Results of two pivotal phase 3 randomized controlled trials. Neuropsychopharmacology, 41, 1251–​1260. McElroy, S. L., Hudson, J. I., Malhotra, S., Welge, J. A., Nelson, E. B., Keck, P. E., Jr. (2003). Citalopram in the treatment of binge-​eating disorder: A placebo-​controlled trial. Journal of Clinical Psychiatry, 64, 807–​813. McElroy, S. L., Hudson, J. I., Mitchell, J. E., Wilfley, D., Ferreira-​Cornwell, M. C., Gao, J.,  . . .  Whitaker, T. (2015). Efficacy and safety of lisdexamfetamine for treatment of adults with moderate to severe binge eating disorder: A randomized clinical trial. JAMA Psychiatry, 72, 235–​246. McElroy, S. L., Keck, P. E., Jr., & Pope, H. G., Jr. (1987). Sodium valproate:  Its use in primary psychiatric disorders. Journal of Clinical Psychopharmacology, 7, 16–​24. McElroy, S. L., Kotwal, R., Guerdjikova, A. I., Welge, J. A., Nelson, E. B., Lake, K. A.,   .  .  .  Hudson, J. I. (2006).

Zonisamide in the treatment of binge eating disorder with obesity:  A  randomized controlled trial. Journal of Clinical Psychiatry, 67, 1897–​1906. McElroy, S. L., Kotwal, R., Hudson, J. I., Nelson, E. B., & Keck, P. E., Jr. (2004). Zonisamide in the treatment of binge eating disorder: An open-​label, prospective trial. Journal of Clinical Psychiatry, 65, 50–​56. McElroy, S. L., Kotwal, R., Keck, P. E., Jr., & Akiskal, J. S. (2005). Comorbidity of bipolar and eating disorders:  Distinct or related disorders with shared dysregulations? Journal of Affective Disorders, 86, 107–​127. McElroy, S. L., Shapira, N. A., Arnold, L. M., Keck, P. E., Jr., Rosenthal, N. R., Wu, S. C.,   .  .  .  Hudson, J. I. (2004). Topiramate in the long-​term treatment of binge-​eating disorder associated with obesity [published erratum appears in Journal of Clinical Psychiatry 2005;66:138]. Journal of Clinical Psychiatry, 65, 1463–​1469. Mehler-​Wex, C., Romanos, M., Kirchheiner, J., & Schulze, U. M. (2008). Atypical antipsychotics in severe anorexia nervosa in children and adolescents:  Review and case reports. European Eating Disorders Review, 16, 100–​108. Mendelson, S. D. (2001). Treatment of anorexia nervosa with tramadol. American Journal of Psychiatry, 158, 963–​964. Milano, W., Petrella, C., Casella, A., Capasso, A., Carrino, S., & Milano, L. (2005). Use of sibutramine, an inhibitor of the reuptake of serotonin and noradrenalin, in the treatment of binge eating disorder: A placebo-​controlled study. Advances in Therapy, 22, 5–​31. Miller, K. K., Grieco, K. A., & Klibanski, A. (2005). Testosterone administration in women with anorexia nervosa. Journal of Clinical Endocrinology and Metabolism, 90, 1428–​1433. Misra, M., Katzman, D. K., Estella, N. M., Eddy, K. T., Weigel, T., Goldstein, M. A.,  . . .  Klibanski, A. (2013). Impact of physiologic estrogen replacement on anxiety symptoms, body shape perception, and eating attitudes in adolescent girls with anorexia nervosa:  Data from a randomized controlled trial. Journal of Clinical Psychiatry, 74, e765–​e771. Mitchell, J. E., Christenson, G., Jennings, J., Huber, M., Thomas, B., Pomeroy, C.,  . . .  Morley, J. (1989). A placebo-​ controlled, double-​ blind crossover study of naltrexone hydrochloride in outpatients with normal weight bulimia. Journal of Clinical Psychopharmacology, 9, 94–​97. Mitchell, J. E., Fletcher, L., Hanson, K., Mussell, M. P., Seim, H., Crosby, R.,  . . .  Al-​Banna, M. (2001). The relative efficacy of fluoxetine and manual-​based self-​help in the treatment of outpatients with bulimia nervosa. Journal of Clinical Psychopharmacology, 21, 298–​304. Mitchell, J. E., & Groat, R. (1984). A placebo-​controlled double-​ blind trial of amitriptyline in bulimia. Journal of Clinical Psychopharmacology, 4, 186–​193. Mitchell, J. E., Pyle, R. L., Eckert, E. D., Hatsukami, D., Pomeroy, C., & Zimmerman, R. (1990). A comparison study of antidepressants and structured intensive group psychotherapy in the treatment of bulimia nervosa. Archives of General Psychiatry, 47, 149–​157. Mond, J. M., Hay, P. J., Rodgers, B., & Owen, C. (2007). Health service utilization for eating disorders: Findings from a community-​based study. International Journal of Eating Disorders, 40, 399–​408. Monteleone, P., Luisi, M., Colurcio, B., Casarosa, E., Monteleone, P., Ioime, R.,  . . .  Maj, M. (2001). Plasma levels of neuroactive steroids are increased in untreated women

McElroy, Guerdjikova, Mori, Keck Jr.

391

with anorexia nervosa or bulimia nervosa. Psychosomatic Medicine, 63, 62–​68. Moore, R., Mills, I. H., & Forster, A. (1981). Naloxone in the treatment of anorexia nervosa:  Effect on weight gain and lipolysis. Journal of the Royal Society of Medicine, 74, 129–​135. Naessén, S., Carlström, K., Byström, B., Pierre, Y., & Hirschberg, A. L. (2007). Effects of an antiandrogenic oral contraceptive on appetite and eating behavior in bulimic women. Psychoneuroendocrinology, 32, 548–​554. Nagata, T., Ono, K., & Nakayama, K. (2007). Anorexia nervosa with chronic episodes for more than 30  years in a patient with a comorbid schizotypal personality disorder. Psychiatry and Clinical Neurosciences, 61, 434–​436. National Institute for Clinical Excellence (NICE). (2004). Eating disorders: Core interventions in the treatment and management of anorexia nervosa, bulimia nervosa and related eating disorders. Clinical guideline no 9. London, UK. Neumeister, A., Winkler, A., & Wöber-​Bingöl, C. (1999). Addition of naltrexone to fluoxetine in the treatment of binge eating disorder. American Journal of Psychiatry, 156, 797. Newman-​ Toker, J. (2000). Risperidone in anorexia nervosa. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 941–​942. Nickel, C., Tritt, K., Muehlbacher, M., Pedrosa Gil, F., Mitterlehner, F. O., Kaplan, P.,  . . .  Nickel, M. K. (2005). Topiramate treatment in bulimia nervosa patients:  A  randomized, double-​blind, placebo-​controlled trial. International Journal of Eating Disorders, 38, 295–​300. Noma, S., Uwatoko, T., Yamamoto, H., & Hayashi, T. (2008). Effects of milnacipran on binge eating:  A  pilot study. Neuropsychiatric Disease and Treatment, 4, 295–​300. Ong, Y. L., Checkley, S. A., & Russell, G. F. (1983). Suppression of bulimic symptoms with methylamphetamine. British Journal of Psychiatry, 143, 288–​293. O’Reardon, J. P., Allison, K. C., Martino, N. S., Lundgren, J. D., Moonseong, H., & Stunkard, A. J. (2006). A randomized, placebo-​controlled trial of sertraline in the treatment of night eating syndrome. American Journal of Psychiatry, 163, 893–​898. Parsons, J. M., & Sapse, A. T. (1985). Significance of hypercortisolism in anorexia nervosa. Journal of Orthomolecular Psychiatry, 14, 13–​18. Pataky, Z., Gasteyger, C., Ziegler, O., Rissanen, A., Hanotin, C., & Golay, A. (2013). Efficacy of rimonabant in obese patients with binge eating disorder. Experimental and Clinical Endocrinology and Diabetes, 121, 20–​26. Pearlstein, T., Spurell, E., Hohlstein, L. A., Gurney, V., Read, J., Fuchs, C.,   .  .  .  Keller, M. B. (2003). A double-​blind, placebo-​controlled trial of fluvoxamine in binge eating disorder: A high placebo response. Archives of Women’s Mental Health, 6, 147–​151. Pope, H. G., Hudson, J. I., & Jonas, J. M. (1986). Bulimia in men: A series of fifteen cases. Journal of Nervous and Mental Disease, 174, 117–​119. Pope, H. G., Jr., Hudson, J. I., Jonas, J. M., & Yurgelun-​Todd, D. (1983). Bulimia treated with imipramine:  Placebo-​ controlled, double-​ blind study. American Journal of Psychiatry, 140, 554–​558. Pope, H. G., Jr., Keck, P. E., Jr., McElroy, S. L., & Hudson, J. I. (1989). A placebo-​controlled study of trazodone in bulimia nervosa. Journal of Clinical Psychopharmacology, 9, 254–​259.

392

Pharmacotherapy

Powers, P. S., Bannon, Y., Eubanks, R., & McCormick, T. (2007). Quetiapine in anorexia nervosa patients:  An open label outpatient pilot study. International Journal of Eating Disorders, 40, 21–​26. Powers, P. S., Klabunde, M., & Kaye, W. (2012). Double-​blind placebo-​controlled trial of quetiapine in anorexia nervosa. European Eating Disorder Review, 20, 331–​334. Raingeard, I., Courtet, P., Renard, E., & Bringer, J. (2004). Naltrexone improves blood glucose control in type 1 diabetic women with severe and chronic eating disorders. Diabetes Care, 27, 847–​848. Ramoz, N., Versini, A., & Gorwood, P. (2007). Eating disorders: An overview of treatment responses and the potential impact of vulnerability genes and endophenotypes. Expert Opinion on Pharmacotherapy, 8, 2029–​2044. Reilly, P. P. (1977). Anorexia nervosa:  Lithium administration has contributed to the management of anorexia nervosa. Rhode Island Medical Journal, 60, 419–​456. Ricca, V., Castellini, G., Lo Sauro, C., Rotella, C. M., & Faravelli, C. (2009). Zonisamide combined with cognitive behavioral therapy in binge eating disorder: A one-​year follow-​up study. Psychiatry (Edgemont), 6, 23–​28. Robert, S. A., Rohana, A. G., Shah, S. A., Chinna, K., Wan Mohamud, W. N., & Kamaruddin, N. A. (2015). Improvement in binge eating in non-​diabetic obese individuals after 3 months of treatment with liraglutide: A pilot study. Obesity Research and Clinical Practice, 9, 301–​304. Romano, S. J., Halmi, K. A., Sarkar, N. P., Koke, S. C., & Lee, J. S. (2002). A placebo-​controlled study of fluoxetine in continued treatment of bulimia nervosa after successful acute fluoxetine treatment. American Journal of Psychiatry, 159, 96–​102. Rosenow, F., Knake, S., & Hebebrand, J. (2002). Topiramate and anorexia nervosa. American Journal of Psychiatry, 159, 2112–​2113. Rothschild, R., Quitkin, H. M., Quitkin, F. M., Stewart, J. W., Ocepek-​Welikson, K., McGrath, P. J.,.   .  .  .  Tricamo, E. (1994). A double-​blind placebo-​controlled comparison of phenelzine and imipramine in the treatment of bulimia in atypical depressives. International Journal of Eating Disorders, 15, 1–​9. Ruggiero, G. M., Laini, V., Mauri, M. C., Ferrari, V. M., Clemente, A., Lugo, F.,  . . .  Cavagnini, F. (2001). A single blind comparison of amisulpride, fluoxetine and clomipramine in the treatment of restricting anorectics. Progress in Neuro-​psychopharmacology and Biological Psychiatry, 25, 1049–​1059. Rush, A. J. (2011). Star-​D: Lessons learned and future implications. Depression and Anxiety, 28, 521–​524. Russell, D. M., Freedman, M. L., Feiglin, D. H., Jeejeebhoy, K. N., Swinson, R. P., & Garfinkel, P. E. (1983). Delayed gastric emptying and improvement with domperidone in a patient with anorexia nervosa. American Journal of Psychiatry, 140, 1235–​1236. Russell, G. F.  M., Checkley, S. A., Feldman, J., & Eisler, I. (1988). A controlled trial of d-​fenfluramine in bulimia nervosa. Clinical Neuropharmacology, 11(Suppl 1), S146–​S159. Sabine, E. J., Yonace, A., Farrington, A. J., Barrant, K. H., & Wakeling, A. (1983). Bulimia nervosa: A placebo-​controlled double-​blind therapeutic trial of mianserin. British Journal of Clinical Pharmacology, 15, 195–​202. Saleh, J. W., & Lebwohl, P. (1980). Metoclopramide-​induced gastric emptying in patients with anorexia nervosa. American Journal of Gastroenterology, 74, 127–​132.

Sansone, R. A., & Sansone, L. A. (2003). Metoclopramide and unintended weight gain. International Journal of Eating Disorders, 34, 265–​268. Schmidt do Prado-​ Lima P. A., & Bacaltchuck, J. (2002). Topiramate in treatment-​resistant depression and binge eating disorder. Bipolar Disorders, 4, 271–​273. Schweickert, L. A., Strober, M., & Moskowitz, A. (1997). Efficacy of methylphenidate in bulimia nervosa comorbid with attention-​deficit hyperactivity disorder:  A  case report. International Journal of Eating Disorders, 21, 299–​301. Shapira, N. A., Goldsmith, T. D., & McElroy, S. L. (2000). Treatment of binge-​eating disorder with topiramate: A clinical case series. Journal of Clinical Psychiatry, 61, 368–​372. Shapiro, J. R., Berkman, N. D., Brownley, K. A., Sedway, J. S., Lohr, K. N., & Bulik, C. M. (2007). Bulimia nervosa treatment:  A  systematic review of randomized controlled trials. International Journal of Eating Disorders, 40, 321–​336. Shisslak, C. M., Perse, T., & Crago, M. (1991). Coexistence of bulimia nervosa and mania: A literature review and case report. Comprehensive Psychiatry, 32, 181–​184. Silveira, R. O., Zanatto, V., Appolinário, J. C., & Kapezinski, F. (2005). An open trial of reboxetine in obese patients with binge eating disorder. Eating and Weight Disorders, 10, e93–​e96. Slof-​Op’t Landt, M. C., van Furth, E. F., Meulenbelt, I., Slagbloom, P. E., Bartels, M., Boomsma, D. I.,  . . .  Bulik, C. M. (2005). Eating disorders: From twin studies to candidate genes and beyond. Twin Research and Human Genetics, 8, 467–​482. Sokol, M. S., Gray, N. S., Goldstein, A., & Kaye, W. H. (1999). Methylphenidate treatment for bulimia nervosa associated with a cluster B personality disorder. International Journal of Eating Disorders, 25, 233–​237. Stacher, G., Abatzi-​Wenzel, T. A., Wiesnagrotzki, S., Bergmann, H., Schneider, C., & Gaupmann, G. (1993). Gastric emptying, body weight and symptoms in primary anorexia nervosa. Long-​term effects of cisapride. British Journal of Psychiatry, 162, 398–​402. Stacher, G., Peters, T. L., Bergmann, H., Wiesnagrotzki, S., Schneider, C., Granser-​Vacariu, G. V.,.  . . .  Kugi, A. (1993). Erythromycin effects on gastric emptying, antral motility and plasma motilin and pancreatic polypeptide concentrations in anorexia nervosa. Gut, 34, 166–​172. Stefano, S. C., Bacaltchuk, J., Blay, S. L., & Appolinario, J. C. (2008). Antidepressants in short-​term treatment of binge eating disorder: Systematic review and meta-​analysis. Eating Behaviors, 9, 129–​136. Stein, G. S., Hartshorn, S., Jones, J., & Steinberg, D. (1982). Lithium in a case of severe anorexia nervosa. British Journal of Psychiatry, 140, 526–​528. Steinglass, J. E., Eisen, J. L., Attia, E., Mayer, L., & Walsh, B. T. (2007). Is anorexia a delusional disorder? An assessment of eating beliefs in anorexia nervosa. Journal of Psychiatric Practice, 13, 65–​71. Steinglass, J. E., Kaplan, S. C., Liu, Y., Wang, Y. & Walsh, B. T. (2014). The (lack of ) effect of alprazolam on eating behavior in anorexia nervosa: A preliminary report. International Journal of Eating Disorders, 47, 901–​904. Steinglass, J. E., Sysko, R., Schebendach, J., Broft, A., Strober, M., & Walsh, B. T. (2007). The application of exposure therapy and D-​cycloserine to the treatment of anorexia nervosa: A preliminary trial. Journal of Psychiatric Practice, 13, 238–​245.

Stunkard, A., Berkowitz, R., Tanrikut, C., Reis, E., & Young, L. (1996). d-​Fenfluramine treatment of binge eating disorder. American Journal of Psychiatry, 153, 1455–​1459. Stunkard, A. J. & Messick, S. (1985). The three-​factor eating questionnaire to measure dietary restraint, disinhibition and hunger. Journal of Psychosomatic Research, 29, 71–​83. Su, J. C., & Birmingham, C. L. (2002). Zinc supplementation in the treatment of anorexia nervosa. Eating and Weight Disorders, 7, 20–​22. Sundblad, C., Landén, M., Eriksson, T., Bergman, L., & Eriksson, E. (2005). Effects of the androgen antagonist flutamide and the serotonin reuptake inhibitor citalopram in bulimia nervosa: A placebo-​controlled pilot study. Journal of Clinical Psychopharmacology, 25, 85–​88. Szmukler, G. I., Young, G. P., Miller, G., Lichtenstein, M., & Binns, D. S. (1995). A controlled trial of cisapride in anorexia nervosa. International Journal of Eating Disorders, 17, 347–​357. Szyper, M. S., & Mann, J. D. (1978). Anorexia nervosa as an interictal symptom of partial complex seizures. Neurology, 28, 335. Tachibana, N., Sugita, Y., Teshima, Y., & Hishikawa, Y. (1989). A case of anorexia nervosa associated with epileptic seizures showing favorable responses to sodium valproate and clonazepam. Japanese Journal of Psychiatry and Neurology, 43, 77–​84. Takaki, M., & Okabe, N. (2015). Ariprazole may be effective as an add-​on treatment in bulimic symptoms of eating disorders. Journal of Clinical Psychopharmacology, 35, 93–​95. Theisen, F. M., Linden, A., König, I. R., Martin, M., Remschmidt, H., & Hebebrand, J. (2003). Spectrum of binge eating symptomatology in patients treated with clozapine and olanzapine. Journal of Neural Transmission, 110, 111–​121. Trunko, M. E., Schwartz, T. A., Duvvuri, V., & Kaye, W. H. (2011). Aripiprazole in anorexia nervosa and low-​ weight bulimia nervosa: Case reports. International Journal of Eating Disorders, 44, 269–​275. Trunko, M. E., Schwartz, T. A., Marzola, E., Klein, A. S., & Kaye, W. H. (2014). Lamotrigine use in patients with binge eating and purging, significant affect dysregulation, and poor impulse control. International Journal of Eating Disorders, 47, 329–​334. Umehara, H., Iga, J., & Ohmori, T. (2014). Successful treatment of anorexia nervosa in a 10-​year-​old boy with risperidone long-​acting injection. Clinical Psychopharmacology and Neurosciences, 12, 65–​66. Vandereycken, W. (1984). Neuroleptics in the short-​term treatment of anorexia nervosa: A double-​blind placebo-​controlled study with sulpiride. British Journal of Psychiatry, 144, 288–​292. Vandereycken, W., & Pierloot, R. (1982). Pimozide combined with behavior therapy in the short-​term treatment of anorexia nervosa: A double-​blind, placebo-​controlled, cross-​over study. Acta Psychiatrica Scandinavica, 60, 446–​451. Vander Wal, J. S., Gang, C. H., Griffing, G. T., & Gadde, K. M. (2012). Escitalopram for treatment of night eating syndrome:  A  12-​ week, randomized, placebo-​ controlled trial. Journal of Clinical Psychopharmacology, 32, 341–​345. von Wietersheim, J., Müler-​Bock, V., Rauh, S., Danner, B., Chrenko, K., & Bühler, G. (2008). No effect on spironolactone on bulimia nervosa symptoms. Journal of Clinical Psychopharmacology, 28, 258–​260.

McElroy, Guerdjikova, Mori, Keck Jr.

393

Walsh, B. T., Agras, W. S., Devlin, M. J., Fairburn, C. G., Wilson, G. T., Kahn, C. M.,.  . . .  Chally, M. K. (2000). Fluoxetine for bulimia nervosa following poor response to psychotherapy. American Journal of Psychiatry, 157, 1332–​1334. Walsh, B. T., Fairburn, C. G., Mickley, D., Sysko, R., & Parides, M. K. (2004). Treatment of bulimia nervosa in a primary care setting. American Journal of Psychiatry, 161, 556–​561. Walsh, B. T., Hadigan, C. M., Devlin, M. J., Gladis, M., & Roose, S. P. (1991). Long-​term outcome of antidepressant treatment for bulimia nervosa. American Journal of Psychiatry, 148, 1206–​1212. Walsh, B. T., Kaplan, A. S., Attia, E., Olmsted, M., Parides, M., Carter, O. C.,   .  .  .  Rockert, W. (2006). Fluoxetine after weight restoration in anorexia nervosa:  A  randomized controlled trial [published erratum appears in Journal of the American Medical Association, 2006; 296, 934, and Journal of the American Medical Association 2007; 298,  2008]. Journal of the American Medical Association, 295, 2605–​2612. Walsh, B. T., Stewart, J. W., Roose, S. P., Gladis, M., & Glassman, A. H. (1984) Treatment of bulimia with phenelzine: A double-​blind, placebo-​controlled study. Archives of General Psychiatry, 41, 1105–​1109. Walsh, B. T., Wilson, G. T., Loeb, K. L. Devlin, M. J., Pike, K. M., Roose, S. P.,  . . .  Waternaux, C. (1997). Medication and psychotherapy in the treatment of bulimia nervosa. American Journal of Psychiatry, 154, 523–​531. Wang, T. S., Chou, Y. H., & Shiah, I. S. (2006). Combined treatment of olanzapine and mirtazapine in anorexia nervosa associated with major depression. Progress in Neuropsychopharmacology and Biological Psychiatry, 30, 306–​309. Weibel, S., Lalanne, L., Riegert, M., & Bertschy, G. (2015). Efficacy of high-​dose baclofen for alcohol use disorder and comorbid bulimia: A case report. Journal of Dual Diagnosis, 11, 203–​204. Wermuth, B. M., Davis, K. L., Hollister, L. E., & Stunkard, A. J. (1977). Phenytoin treatment of the binge eating syndrome. American Journal of Psychiatry, 134, 1249–​1253. Wheadon, D. E., Rampey, A. H., Jr., Thompson, V. L., Potvin, J. H., Massica, D. N., & Beasley, C. M., Jr. (1992). Lack of association between fluoxetine and suicidality in bulimia nervosa. Journal of Clincal Psychiatry, 53, 235–​241.

394

Pharmacotherapy

White, M. A., & Grilo, C. M. (2013). Bupropion for overweight women with binge-​eating disorder: A randomized, double-​ blind, placebo-​controlled trial. Journal of Clinical Psychiatry, 74, 400–​406. Wilfley, D. E., Crow, S. J., Hudson, J. I., Mitchell, J. E., Berkowitz, R. I., Blakesley, V., & Walsh, B. T. (2008). Efficacy of sibutramine for the treatment of binge eating disorder:  A  randomized multicenter placebo-​ controlled double-​blind study. American Journal of Psychiatry, 165, 51–​58. Wysowski, D. K., Corken, A., Gallo-​Torres, H., Talarico, L., & Rodriguez, E. M. (2001). Postmarketing reports of QT prolongation and ventricular arrhythmia in association with cisapride and Food and Drug Administration regulatory actions. American Journal of Gastroenterology, 96, 1698–​1703. Woodside, B. D., & Staab, R. (2006). Management of psychiatric comorbidity in anorexia nervosa and bulimia nervosa. CNS Drugs, 20, 655–​663. Yager, J. (2007). Management of patients with chronic, intractable eating disorders. In J. Yager & P. S. Powers (Eds.), Clinical manual of eating disorders (pp. 407–​439). Washington, DC: American Psychiatric Publishing. Yager, J., & Powers, P. S. (Eds.). (2007). Clinical manual of eating disorders. Washington, DC:  American Psychiatric Publishing. Yamamoto, T., Kanahara, N., Hirai, A., Watanabe, H., & Iyo, M. (2013). Lamotrigine in binge-​eating disorder associated with bipolar II depression and treatment-​resistant type 2 diabetes mellitus:  A  case report. Clinical Neuropharmacology, 36, 34–​35. Yasuhara, D., Nakahara, T., Harada, T., & Inui, A. (2007). Olanzapine-​ induced hyperglycemia in anorexia nervosa. American Journal of Psychiatry, 164, 528–​529. Yilmaz, Z., Hardaway, J. A., & Bulik, C. M. (2015). Genetics and epigenetics of eating disorders. Advanced Genomics Genetics, 5, 131–​150. Zilberstein, B., Pajecki, D., Garcia de Brito, A. C., Gallafrio, S. T., Eshkenazy, R., & Andrade, C. G. (2004). Topiramate after adjustable gastric banding in patients with binge eating and difficulty losing weight. Obesity Surgery, 14, 802–​805.



CH A PT E R

 Cognitive Remediation Therapy for Eating Disorders

20

Amy Harrison

Abstract Eating disorders (EDs) have been described as among the most difficult psychiatric disorders to treat. Intervening early appears to be associated with better prognosis, although a subgroup of 20% of individuals may develop a more severe and enduring form of illness, which is associated with higher rates of mortality. Many patients with EDs who come into contact with clinical services may have extreme ambivalence toward change, which is often observed through high treatment dropout rates and difficulties engaging in treatment. This chapter outlines cognitive remediation therapy (CRT) for eating disorders, a treatment enhancer designed to support individuals with severe and complex forms of illness. This chapter explores how CRT has been used, examines its efficacy, reflects on its place as part of an overall treatment package for patients with EDs, and finally, explores options for future research in the field. Key Words:  cognitive remediation therapy, efficacy, anorexia nervosa, historical development, CRT, ambivalence

Introducing Cognitive Remediation Therapy

Cognitive remediation therapy (CRT) is a therapeutic adjunct that aims to support patients to improve inefficiencies in thinking styles (Tchanturia, 2014). Somewhat uniquely, CRT focuses on the process of thinking, rather than the content; the “how,” rather than the “what.” To achieve this, CRT employs simple cognitive exercises to allow patients to practice and demonstrate different cognitive strategies and to then reflect on the thinking styles and strategies used (Tchanturia, Lounes, & Holttum, 2014). This metacognitive component involves the patient exploring links between their approach to the simple CRT tasks and the strategies they use to approach tasks in everyday life and encourages the patient to develop a range of tools that allow them to approach daily tasks with greater efficiency and confidence (Tchanturia & Lock, 2011). Patients are encouraged to practice

between sessions and to develop curiosity in relation to their cognitive skills. The therapist may be encouraged to also take part in the simple exercises and to use the nonthreatening cognitive tasks to facilitate discussion around the process of thinking, making clear links to everyday problem solving (Tchanturia, 2014). Throughout this chapter, a transdiagnostic approach is adopted (Fairburn, Cooper, & Shafran, 2003), with the term “EDs” used throughout, due to the frequent temporal movement between categorical diagnoses (Keel & Mitchell, 1997) and because many of the patients who may benefit from CRT are likely to have had experience of a number of different symptom presentations (Milos, Spindler, Schnyder, & Fairburn, 2005). However, where research has been conducted including a specific group of patients, the terms anorexia nervosa (AN) or bulimia nervosa (BN) are used in keeping with the original research. 395

Background: Historical Development of Cognitive Remediation Therapy for Eating Disorders

Originally, CRT was developed for people with acquired brain injuries with a focus on compensation strategies to help patients approach everyday tasks with greater efficiency; this work is summarized by Cicerone et  al. (2011). Following this, CRT was adapted and implemented to help people with schizophrenia develop more efficient cognitive strategies with the aim of improving established cognitive deficits in this patient group; findings supporting improved neuropsychological functioning, as reviewed by Wykes, Huddy, Cellard, McGurk, and Czobor (2011). Also, CRT has been used to support people with depression for whom cognitive inefficiencies are also established as a core feature of the illness (Porter, Bowie, Jordan, & Malhi, 2013) and, as in AN (Harrison, Tchanturia, Naumannn, & Treasure, 2012; Tchanturia, 2014; Tchanturia et  al., 2012; Tchanturia et  al., 2011), data indicate that some of these cognitive differences might remain despite symptom improvement (Douglas, Porter, Knight, & Maruff, 2011). Porter et  al. (2013) reviewed the published literature on CRT for major depressive disorder and found 10 studies had reported on the development and evaluation of cognitive-​remediation treatment packages for people with depression. In general, these studies reported medium sized improvements in cognitive functioning following treatment. Interestingly, it is well established that depression is a common comorbid diagnosis for people with EDs (Blinder, Cumella, & Sanathara, 2006; Kaye, Bulik, Thornton, Barbarich, & Masters, 2004). Subsequent to its use in brain injury, psychosis, and depression, CRT was adapted for working with people with eating disorders (EDs) and offered a unique component, which was a focus on core cognitive processes rather than ED symptoms (Tchanturia & Lock, 2011). The rationale for using cognitive remediation to support functioning in people with EDs was informed by an emerging literature demonstrating a number of cognitive inefficiencies in adults with EDs, in particular difficulties thinking and behaving in a flexible manner and a superior focus on detail (Tchanturia, 2014; Tchanturia et  al., 2012; Tchanturia et  al., 2011). For example, support for the presence of suboptimal set-​shifting skills is provided in a systematic review and meta-​ analysis conducted by Roberts, Tchanturia, Stahl, Southgate, and Treasure (2007), which included 15 studies and demonstrated, 396

Cognitive Remediation

depending on the task administered, small-​to large-​ sized differences in set-​shifting in those with EDs relative to non-​ED controls. An updated review suggested continued support for these findings (Westwood, Stahl, Mandy, & Tchanturia, 2016). Set-​shifting or cognitive flexibility has been defined as a form of self-​regulation in which the individual demonstrates their ability to “shift their course of thought or action according to the demands of the situation” (Lezak, 2004, p.  666). Indeed, set-​ shifting is the ability to shift set, or to move back and forth between multiple tasks, operations, or mental sets (Miyake et  al., 2000). In support of superior skills for detail processing, sometimes referred to as field independence, or an analytically oriented processing style (Witkin & Goodenough, 1977) alongside inefficiencies in global processing, sometimes referred to as field dependence, or a globally oriented information processing style (Witkin & Goodenough, 1977), a systematic review identified 12 studies involving patients with EDs and reported medium-​sized differences for these cognitive skills in those with EDs relative to non-​ED controls (Lang, Lopez, Stahl, Tchanturia, & Treasure, 2014). This profile of weak central coherence, where a focus on local, featural information dominates (Happé & Frith, 2006), is proposed to be an important maintaining factor for adults with EDs (Schmidt & Treasure, 2006; Treasure & Schmidt, 2013). Therefore, a treatment enhancer aimed at helping patients to improve their skills in this area may be a useful way of assisting them to benefit from evidence-​based treatments such as cognitive-​ behavioral therapy (CBT; Fairburn, 2008) and family therapy (Dare & Eisler, 1997; Lock, Le Grange, Agras, & Dare, 2001). There also appears to be emerging evidence of a similar neuropsychological profile in children and adolescents with EDs, with support provided from two systematic reviews on set-​shifting (Lang, Stahl, Espie, Treasure, & Tchanturia, 2014) and central coherence (Lang & Tchanturia, 2014). A  small amount of preliminary data suggests that young women whose ED onset occurred during adolescence and was associated with amenorrhea or irregular menses demonstrate greater cognitive difficulties and difference in brain structure in their early 20s (Chui et  al., 2008). In a small sample of 25 adolescents with AN, participants demonstrated poorer cognitive functioning than 26 non-​ED controls, and those with AN showed an improvement in cognitive ability after weight recovery which was more pronounced in those with restored menstruation

(Lozano-​Serra, Andrés-​Perpiña, Lázaro-​García, & Castro-​Fornieles, 2014). However, the literature is clearly less well developed in this younger cohort than it is for the adult population, and these reviews highlight both small sample sizes and variability in task selection and outcomes.

Cognitive Remediation as a Therapy Enhancer for Eating Disorders

It was initially proposed that ten 45-​minute sessions of individual, face-​to face CRT might offer a means of establishing a therapeutic relationship with patients with severe and enduring AN who, nutritionally compromised, require admission to an inpatient unit and may find the curious, collaborative, playful, and nonthreatening stance of CRT a useful introduction to further, higher intensity, psychological treatment (Tchanturia & Lock, 2011; Tchanturia, Lloyd, & Lang, 2013; Tchanturia et al., 2014). Additionally, it was also proposed that CRT might facilitate the development of useful cognitive skills that would enable patients to better use higher intensity treatments during their admission (Tchanturia et  al., 2013). Initial case studies and case series then set out to explore the potential benefits of CRT in AN. As previously mentioned, work conducted by clinical researchers in London, UK, initially focused on using the intervention with an adult inpatient population, which represented a severely unwell cohort with a predominantly enduring form of AN (Davies, & Tchanturia, 2005; Tchanturia, Whitney, & Treasure, 2006). After preliminary findings indicated its efficacy (Tchanturia, Davies, & Campbell, 2007), and patients provided positive reports of its usefulness and fresh focus on skills rather than symptoms (Whitney, Easter, & Tchanturia, 2008), a pilot case series was conducted, which indicated its relevance and possible efficacy for improving cognitive functioning in adults with AN (Tchanturia et al., 2008). By 2009, other research groups around the world began to use CRT in their patient populations and publish their findings (Cwojdzińska, Markowska-​Regulska, & Rybakowski, 2009) and group formats were developed (Genders & Tchanturia, 2010; Tchanturia & Doris, 2015). Also, CRT was trialed in outpatient settings (Pitt, Lewis, Morgan, & Woodward, 2010), and by 2011 it had been adapted for both adolescent inpatients and those accessing intensive day hospital treatment for EDs (Wood, Al-​Khairulla, & Lask, 2011; Pretorius et  al., 2012). Throughout its development, the improved understanding of the neuropsychological

profile of people with EDs continued to influence and update CRT (Tchanturia et al., 2013; Martinez, Cook-​Darzens, Chaste, Mouren, & Doyen, 2014; Tchanturia et  al., 2014) and the first randomized controlled trial (RCT) of CRT for AN highlighted its ability to retain patients in treatment, as well as improve inefficiencies in cognitive processing (Lock et al., 2013). That 33% of patients dropped out of CBT compared with a dropout rate of 13% in the group of patients receiving both CRT and CBT reflects one of the useful functions of CRT, such that this low-​intensity intervention might provide a collaborative, nonthreatening, and playful way to engage and begin to develop a rapport with severely underweight patients with EDs who may have already experienced a large number of previous treatments and might lack confidence and the desire to pursue further talking therapies (Tchanturia, Davies, Reeder, & Wykes, 2010). Cognitive remediation therapy is not proposed to be a panacea for EDs, rather it is a way of helping to engage patients with the most severe and enduring forms of illness who may not have previously taken part in treatment interventions to engage in the treatment program on offer. It shares a number of similarities with CBT, well known to have an evidence base for helping individuals with EDs overcome their difficulties (Fairburn et  al., 2015). It has also a number of features that differentiate it from CBT. Before moving to the section where the efficacy of CRT for EDs is explored, Table 20.1 suggests some ways in which the two treatments might be complementary and highlights some of their possible differences as a way of helping clinicians to reflect on the transferable skills they have from using other evidence-​ based treatments for EDs which can also be used in the delivery of CRT.

A Review of the Evidence to Date: Cognitive Remediation Therapy for Eating Disorders—​Randomized Controlled Trials in Adult Populations

A systematic review of the literature identified four RCTs conducted in adults with AN (Tchanturia et  al., 2014) and highlighted promising findings. The first published RCT was conducted in the United States in an adult outpatient setting and aimed to explore the feasibility of using CRT with a focus on reducing dropout rates in treatment for AN. Forty-​six outpatients with AN were randomly assigned to either eight sessions of CRT (n  =  23) or CBT (n  =  23) over 2  months, followed by 16 Harrison

397

Table 20.1  Similarities and Differences Between Cognitive Remediation Therapy and Cognitive-​Behavioral Therapy Cognitive-​Behavioral Therapy

Cognitive Remediation Therapy

Similarities Collaboration and a curious stance offered by the clinician Homework exercises Manualized format with defined interventions/​exercises Structured, time limited, relatively brief Aims to provide patients with tangible skills and knowledge Involves behavioral experiments Differences A focus on the content of cognition (albeit with the exception of where thinking errors are challenged)

A focus on the process, style of cognition, or the cognitive strategy used

Directive, goal focused

Patient led and directed

Behavioral experiments are used to challenge beliefs and form more useful and adaptive thoughts and behaviors to make changes to the “what” of cognition and behavior

Behavioral experiments are used to reflect on the patient’s current cognitive strategies and to try out alternative strategies to offer greater options in terms of the “how” of thinking and behavior

Requires a high degree of training to be delivered, particularly in a more high-​ intensity context

Requires a relatively lower level of training and is designed to be delivered by trainee therapists, graduate students, members of the nursing team as well as trained therapists

CBT sessions over 4  months. The authors found a lower dropout rate occurred in the CRT group (13%) compared with the CBT group (33%) and also found improvements in cognitive efficiencies in the CRT group compared with the CBT group at the end of the trial (Lock et al., 2013). In a second RCT conducted in The Netherlands, Dingemans et  al. (2014) randomly allocated 82 adult inpatients with severe and enduring AN to CRT plus treatment as usual (TAU; n = 41) or TAU only (n = 41). At the end of treatment and 6-​month follow-​ up, CRT was associated with significant improvements in quality of life. The authors conducted a moderation analysis, which indicated that patients with poorer baseline set-​shifting abilities benefited more from CRT and had better quality of life at follow-​up. Performance on tasks of set-​ shifting and global processing, however, improved significantly in both the CRT and TAU conditions, and the authors attributed this finding to practice effects or nonspecific ingredients of treatment. 398

Cognitive Remediation

A third RCT was conducted by Brockmeyer et  al. (2014) in Germany with the aim of exploring the feasibility and possible efficacy of CRT through randomly allocating 40 adult inpatients to tailored CRT (n = 20) or nonspecific neurocognitive therapy (NNT; n = 20); patients were offered a more intensive 30 sessions (21 computer-​assisted and 9 face-​to-​face) and assigned computer-​assisted homework. The NNT focused only on attention, memory, and deductive reasoning. The manual-​ based CRT was tailored and focused solely on set-​ shifting; as argued by the authors, central coherence was omitted to remove any potentially confounding factors with regard to the control condition. The primary outcome was performance on a computer-​ based task-​switching paradigm that assessed pre-​ intervention and post-​intervention. Overall, CRT participants significantly outperformed the NNT group in set-​shifting with a medium effect size, and overall patient feedback was more positive for CRT. The authors suggested that specific tailored

neurocognitive training is more effective and argue for the feasibility of CRT for AN. A fourth RCT (Steinglass et  al., 2014) compared CRT with exposure and response prevention for AN (AN-​EXRP), a new approach that targets maladaptive eating behavior by addressing eating-​ related anxiety. Adult inpatients (n = 32) who were weight restored (BMI over 18.5) were offered 12 sessions of AN-​EXRP or CRT, and the outcome measure was caloric intake at a test meal, which the authors found was higher in the AN-​EXRP group; this improvement was also significantly associated with eating-​related anxiety. However, because the inpatients in this study were weight restored, they differ significantly from participants in all the other studies mentioned earlier. To date, there are no published RCTs of CRT for children and adolescents with EDs, with Dahlgren and Rø (2014, p. 26) highlighting in their review that “it is imperative that adolescent RCTs are conducted to evaluate how CRT may be effective as a treatment for this young patient group.” The next section therefore explores the evidence reported to date regarding how CRT has been used to support young people with EDs.

A Review of the Evidence to Date: Cognitive Remediation Therapy for Eating Disorders in Child and Adolescent Populations

The first published article that explored the use of CRT for young people with EDs was provided by Cwojdzińska et al. (2009), who described a case study in which they used CRT with an adolescent patient with AN. They reported improved performance on the Wisconsin Card Sort Task (Heaton, Chelune, Talley, Kay, & Curtiss, 1993) indicating improved set-​ shifting, and this change was also observed alongside an improvement in ED symptoms. Early indications of the possible benefits of CRT for a younger population of individuals with EDs were further highlighted by Easter and Tchanturia (2011) in their qualitative study, which explored therapists’ views of CRT and they reported that CRT might have possible benefits for young people with EDs. This perspective is corroborated by Martinez et al. (2014), who have also highlighted the possible utility of CRT for adolescent patients with AN. Alongside these predictions around the possible uses of CRT for younger cohorts of individuals with EDs, a growing research literature has begun to develop and enhance the evidence base. Wood et  al. (2011) conducted a study that explored the possible benefit of CRT delivered in a group setting

across 10 sessions to adolescent inpatients aged 13–​19 with AN. The patients reported the group to be “fun and useful,” and the authors further corroborated the possible benefits of CRT for young people with EDs, suggesting that CRT might be a potentially useful addition to the treatment of young people with AN. Another study built on the evidence base for the possible benefits of CRT for young people, also focusing on its application in a group setting. Pretorius et al. (2012) reported on the delivery of seven CRT groups attended by a total of 30 adolescent outpatients with AN and found a nonsignificant small-​sized improvement in self-​reported cognitive flexibility, measured using the Cognitive Flexibility Scale (Martin & Rubin, 1995). Qualitative feedback on the acceptability of the group indicated that this was perceived as an acceptable and useful group treatment by patients. In 2013, Dahlgren, Lask, Landrø, and Rø conducted an uncontrolled feasibility trial exploring the possible impact of CRT on neuropsychological functioning in 22 adolescents with AN. After CRT, significant improvements in weight, symptoms of depression, and a range of neuropsychological outcomes including visual-​spatial memory, perceptual disembedding abilities and verbal fluency were observed. Dahlgren, Lask, Landrø, and Rø (2014) followed these findings up with a further study of 20 adolescent inpatients and outpatients with AN aged 13–​18. Patients received once or twice weekly individually tailored CRT sessions, and the results highlighted that the intervention was experienced as acceptable with no voluntary dropouts and 19 of 20 patients completed all sessions. Asch et al. (2014) reported on the effectiveness of weekly 1-​hour sessions of CRT offered over 10 weeks to 10 adolescent inpatients aged 12–​17 with AN. Patients’ set-​shifting skills were explored before and after treatment, and individuals were also asked to provide qualitative feedback on their experience of the intervention. Only 2 out of 10 patients (20%) completed all sessions. However, patients demonstrated improved set-​shifting after the intervention, which also appeared to be associated with improvements in body mass index, one physical predictor of recovery. Dahlgren et  al. (2014) collected self-​ report outcomes from 17 adolescent patients and their caregivers using the Inventory of Executive Function (BRIEF; Gioia, Isquith, Guy, & Kenworthy, 2000) before and after CRT and found that patients reported fewer executive functioning difficulties after CRT although this was not corroborated by parental reports. A  case study described Harrison

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by van Noort, Pfeiffer, Lehmkuhl, and Kappel (2015) also explored the possible benefits of 10 CRT sessions offered twice weekly to a 12-​year-​old girl with a severe form of AN over 5 weeks. There were no clear changes in neuropsychological functioning, but CRT appeared to be associated with an improvement in AN symptoms 7 months after CRT. While it is possible that other factors influenced this symptom reduction, the authors suggest that CRT may have played an important supplementary role in the context of the broader treatment offered. Van Noort, Kraus, Pfeiffer, Lehmkuhl, and Kappel (2016) offered CRT to a mixed sample of 20 inpatients and outpatients with AN, conducting a neuropsychological assessment before and after treatment. They also conducted the same assessment in a group of 20 non-​AN controls who did not receive CRT. There was an improvement in cognitive flexibility in the AN group after treatment relative to the control group, although there was no change in either group regarding central coherence or self-​reported cognitive flexibility. These initial studies in adolescent populations appear to suggest that CRT may be feasible to implement and experienced as acceptable by patients; CRT may be associated with relatively low levels of dropout in this younger patient group and may have some impact on patients’ neuropsychological functioning. Indeed, these promising early findings have led clinical research teams to begin to embed CRT into their treatment programs for young people with EDs. For example, Doyen et al. (2015) proposed that a 6-​month program of CRT should be offered to all adolescent inpatients with AN by the nursing team. In their manuscript, they also present an uncontrolled case series suggestive of improvements in cognitive functioning after, compared with before, treatment. However, at present, it is unclear the degree to which CRT enhances treatment as usual, and randomized designs would be needed to explore this further. Interestingly, CRT for EDs has continued to be developed in novel ways. Lang, Treasure, and Tchanturia (2015) present preliminary findings which suggest that a Web-​ based CRT self-​ help intervention disseminated to carers might be an acceptable form of treatment and provide a means through which patients and their families might be better able to understand thinking styles that may maintain EDs. Similarly, a family-​based face-​to-​face format, as described in Hutchinson, Roberts, and Lask (2014), was experienced as acceptable and was 400

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a potential means of helping adolescent patients to engage in therapy. Taken together, the evidence reviewed above suggests that exploring the possible benefits of CRT for younger cohorts of individuals with EDs will be an important focus for future research. Thus far, this chapter has explored the development of CRT and its evidence base for improving the cognitive inefficiencies reported in individuals with EDs. The next section explores how CRT can be implemented in a treatment setting.

Ways of Using Cognitive Remediation in Clinical Settings

Implementing CRT in a clinical service for people with EDs can be approached in a number of ways (Tchanturia & Lock, 2011). The literature reviewed here highlights that one priority for future research would be to conduct RCTs in an adolescent population, and in this case, it is recommended that a manualized approach be taken to allow clinicians and researchers to systematically evaluate the efficacy of CRT with a focus on neuropsychological performance and ED symptom outcome. The original CRT treatment manual (Tchanturia et  al., 2010) can be accessed freely in the “Publications” section located at the web address www.katetchanturia.com, and there are Spanish, Italian, French, and Japanese translations available at the same website. Readers may find the discussion in Tchanturia and Doris (2015) useful regarding adapting the delivery to a group setting for adults with EDs. Other research groups have also provided useful toolkits. Lindvall, Owen, and Lask (2011) provide a CRT Resource Pack adapted for children and adolescents with EDs, which can be accessed freely at http://​ous. prod.fpl.nhn.no/ ​ S iteCollectionDocuments/​ Fagfolk/​Forskning%20og%20utvikling/​R ASP/​ 1.-​7 .%20The%20CRT%20Recource%20Pack. pdf. Maiden, Baker, Espie, Simic, and Tchanturia (2014) have adapted the materials for group delivery in the child and adolescent population; known as the “Flexibility Group,” the resource can be accessed freely within the “Publications” section at the website www.katetchanturia.com, with further information discussed in Maiden, Baker, Espie, Simic, and Tchanturia (2015). At the same website, those interested in the adaptation for carers of people with EDs discussed above will also be able to access the materials adapted to using CRT with this population (Tchanturia & Lang, 2015).

The other way in which implementation can be approached is through offering CRT as part of the broader treatment package available for individuals with AN and the evidence reviewed thus far lends support for the use of CRT as a treatment enhancer for adults with AN, with particular benefits in terms of keeping patients in treatment and helping them to develop useful skills for later higher intensity therapeutic work. In this sense, CRT can be adapted to the treatment setting with regard to who delivers the treatment, how it is delivered and in what format (individual or group setting). In an inpatient setting, CRT could be offered on admission to the ward as a way to help the patient to settle in and start to engage in the milieu in a nonthreatening way, with a focus on skill development and strengths rather than eating, weight, and shape (Tchanturia, 2014). It will be important to reflect on how CRT fits within the overall formulation (Tchanturia & Lock, 2011). There is no clear evidence to suggest whether a group setting or an individual setting is more beneficial, and clinicians will make an informed decision around how to begin implementing CRT based on the context of their setting and service, the patients themselves, and the resources available. However, CRT is designed to be a low-​intensity treatment that can be offered by members of the nursing team and unqualified psychology graduates, including assistant psychologists, research assistants, and trainee clinicians with its delivery supervised by a qualified and licensed psychologist (Tchanturia, 2014). As with any treatment package, good supervision is vital. The section below provides more detail of how CRT can be delivered.

Outline of a Typical Cognitive Remediation Therapy Session

The exact session length and dose for efficacy are not currently known, but the majority of studies have focused on offering ten 45-​minute sessions (Tchanturia et  al., 2013), although this can be adapted depending on the patients’ abilities and needs at the time of treatment. At the start of each session, the clinician and patient(s) should set up an agenda and outline the exercises they will cover and the skills they aim to focus on. The number of exercises the therapist brings to the session should be based on how long the patient is able to concentrate depending on their physical state and the amount of time the patient requires to complete the tasks and enter into a discussion about the cognitive skills and strategies explored and this will vary according

to the individual. The session should aim to explore at least one exercise, which may also involve the therapist taking part, and then a discussion around the skills and strategies used should follow. In this meta-​cognitive exploration, the therapist should ask open questions, taking a curious and nonjudgmental stance, such as “How did you go about completing that task?” or “What strategy did you find yourself using here?” The clinician should then ask about whether there are any other ways in which the exercise could be completed, and what strengths and weaknesses alternative strategies might have. The clinician should then ask about how these strategies might relate to real-​life tasks and whether the patient has noticed themselves using these strategies and how this impacted their ability to complete the task. The clinician and the patient could then think about whether there might be an individualized behavioral experiment that would help the patient to build confidence around using alternative strategies (Tchanturia & Lock, 2011). A clear example of this exchange is offered in the next section. Consider a patient and therapist working on a global versus detailed thinking exercise in which the patient and therapist both view a photo of a complex scene, such as a busy tourist area in the city. The instruction is to explore the picture and write an account of what is going on. The therapist takes part, writing their own account at the same time as the patient. After the account is written the therapist and the patient share their observations. The therapist can then ask about the approach taken by the patient around completing the task and the strengths and limitations of that approach. For example, if the patient has written a long, detailed account of the scene, the therapist could ask about what the pros and cons of the strategy might be and whether there might be another way to approach the task. If the therapist has written a briefer account, giving the gist rather than the detail, the therapist and patient could explore the pros and cons of this strategy. The therapist might then ask whether the patient has found themselves using the same strategy in everyday tasks and whether there might be alternative approaches that they could consider. It may then be possible to set up an experiment to explore the use of an alternative strategy in an everyday task. If the patient is able and willing to, and there is time left in the allocated session time, then the patient and therapist might consider moving on to look at another task or exercise. As previously discussed, treatment manuals and comprehensive toolkits are readily available, and in Harrison

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addition to this, practitioners using CRT in routine work are also encouraged to develop and use additional tasks that they think will provide a useful talking point to think about thinking with their patients. In order to assist this discussion, Table 20.2 provides an outline of a range of tasks focused on improving functioning in the domains of central coherence, set-​shifting, and estimation skills. For further examples, readers are encouraged to refer to the published manuals and toolkits discussed previously.

Measurement of Outcome

As with all treatment interventions, it is important to investigate the potential impact of treatment on a range of outcomes such as symptoms, functioning, and quality of life. A range of different measures have been used to investigate the extent to which CRT impacts cognitive functioning in people with EDs, and this section aims to provide a brief overview of the self-​report and experimental measures previously used in research on CRT for ED and found to be sensitive to change, which clinicians and researchers may find useful when exploring the possible impact of CRT on cognitive functioning.

Self-​Report Measures of Outcome

The Cognitive Flexibility Scale (Martin & Rubin, 1995) is a 12-​item questionnaire that assesses participants’ perceptions of their set-​ shifting skills, namely the options and alternatives they feel are available to them in everyday situations. Possible scores range between 0 and 72, and a higher score is related to a higher level of cognitive flexibility. The measure has good test–​retest reliability (Martin & Rubin, 1995) and benefits from being a brief assessment tool requiring little cost in terms of time and material or equipment resources. This measure was used in a study exploring the impact of 20 4-​to 6-​session CRT groups delivered to adult women with AN accessing inpatient or intensive daycare services and was somewhat sensitive to change over time, highlighting a negligible sized improvement (d  =  0.18) in self-​reported set-​shifting skills (Tchanturia, Larsson, & Brown, 2016) at the end of the groups. The Detail and Flexibility Questionnaire (DFlex; Roberts, Barthel, Lopez, Tchanturia, & Treasure, 2011) is another useful measure to consider. This is a 24-​item self-​report scale that not only measures self-​ reported set-​shifting but also offers a subscale that measures the degree to which the individual feels 402

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they have a tendency to focus on detail when processing information. This measure has demonstrated strong discriminant validity with large effect sizes for the differences between those with EDs and non-​ED controls (Roberts et al., 2011) and the authors of the measure suggest that this scale is able to provide an estimation of the degree to which individuals function in terms of detail focused information processing and set-​shifting skills as manifested in the context of daily life. Arguably this measure only reflects one aspect of central coherence—​detailed information processing—​ and therefore may be able to offer less information regarding the extent to which the individual is able to use bigger-​ picture thinking skills. However, like the Cognitive Flexibility Scale, it offers a brief, low-​cost means of exploring these aspects of functioning before and after the delivery CRT and could be sent to patients to complete at a follow-​up time point with little cost and inconvenience to the patient themselves. In Tchanturia et al.’s (2016) study that reported on outcomes from 20 CRT groups delivered in inpatient and intensive daycare settings, this measure was more sensitive to change than the Cognitive Flexibility Scale, demonstrating significant, small-​sized improvements in self-​reported set-​shifting (d = 0.36) and a reduction in the detail-​ focused information processing style (d = 0.37) at the end of the groups. A disadvantage of relying on self-​report measures may be that participants require reasonable insight into their own cognitive functioning to be able to provide accurate answers and may also be subject to demand characteristics and other biases when completing the measures. Given that CRT aims to improve neuropsychological functioning, clinicians and researchers measuring CRT outcomes in ED populations are encouraged to also consider using experimental measures where possible, of which a range of suitable options are discussed below. It is strongly advised when conducting any neuropsychological assessment that aims to explore the possible impact of CRT on cognitive functioning to also collect an estimate of the patient’s intelligence quotient (IQ) at the start of treatment, perhaps using the full or abbreviated version of the Wechsler Adult Intelligence Scale (WAIS-​R; Wechsler, 1981) or the National Adult Reading Test (Nelson & Willison, 1991) which is positively correlated (r = 0.81) with the WAIS-​R (Crawford, Parker, Stewart, Besson, & De Lacey, 1989). This will allow an understanding of the extent of any inefficiencies in cognitive functioning relative to general intellectual functioning before CRT commences.

Table 20.2  Examples of Cognitive Remediation Therapy Exercises, Follow-​Up Questions Designed to Promote “Thinking About Thinking” and Ideas for Homework Task Domain Exercise Example

Follow-​Up Questions

Homework Suggestions

Set-​Shifting Stroop task

The patient is asked to switch between reading the color of the ink and the word written.

How did you approach this task? Which strategies did you find yourself using to complete it? Does this task remind you of any tasks you have to do in everyday life?

Inhibiting unhelpful information when accessing social media.

Clocks task

The patient is asked to switch between giving the time on a series of clocks using AM/​PM and the 24 hour clock

How hard was it to complete this task? What strategies did you find yourself using when having to make the switch? Are there any other ways that you could have approached the task? Is the switching part of the task something that you find difficult in everyday life? If so, can you give some examples?

Changing the radio station, genre of music you listen to, or switching to a different background or ring tone on your mobile phone. Taking a different route to work or school, sitting in a different seat on the ward.

Central Coherence—​Promoting “Bigger-​Picture” Thinking Describing a complex scene

The patient and the How did you approach this task—​what did therapist write a description you notice about your answer? of a photo of a busy scene What are the other ways in which you might have approached this task? What are the strengths and weaknesses of your approach and the alternatives you have mentioned? Have you noticed any other areas in your life where you use this approach? How might this help or hinder you? Are there any alternatives?

Practicing describing your day using one sentence; Reading an article and summarizing it using a headline.

Summarizing The patient and therapist a letter or work on a summary of news article the gist of a longer letter or news article, perhaps in bullet points, as a “Tweet” or short text message like those sent on mobile phones, or as a headline.

How did you approach the task and were Practicing summarizing a there any parts you found challenging? film/​movie in a sentence. What are the strengths and weaknesses of bigger-​picture thinking? How might you be able to incorporate bigger-​picture thinking into your daily life?

Geometric figures

How did you go about approaching the description of the drawing? What did you notice about your thinking styles during this task? Where there any challenges you faced during the task? What might an alternative approach be?

The patient describes a complex line drawing to the therapist, who is blind to the image and must reproduce it based on the patient’s verbal description.

Practicing describing an event to a friend or family member through focusing on providing the gist; writing down the main message of your week in your diary. (continued)

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Table 20.2 Continued Task Domain Exercise Example

Follow-​Up Questions

Homework Suggestions

Estimation Line bisection

The patient is asked to bisect a horizontal line at various points (for example, at 25%, 50%, 75%, 90%).

Leaving things unfinished or stopping when the task is “just good enough.” Throwing something away that you would ordinarily save “just in case.” Handing in some work that is not to your usual high standard.

Source: Adapted from Tchanturia and Hambrook (2010).

Experimental Measures of Outcome

Set-​Shifting A widely used measure of set-​shifting in the field of EDs is the Wisconsin Card Sort Test (WCST) (Grant & Berg, 1948; Heaton et  al., 1993). Tchanturia et  al. (2012) reported that across a sample of 542 participants, the measure detected medium to large-​ sized differences between individuals with EDs (both AN and BN) and non-​ED controls, with recovered participants showing an intermediate profile. This task measures cognitive or conceptual flexibility and is also a measure of reactive flexibility; it requires participants to sort cards into one of four categories. The participant must first discover the sorting rule, which will subsequently change during the task. The most common outcome measure used is the number of perseverative errors committed during the task, that is to say the number of times the participant continues applying a sorting rule despite the category having changed. In the ED population, Steinglass, Walsh, and Stern (2006); Ohrmann et al. (2004); Fassino et  al. (2002); and Tchanturia et  al. (2012) are examples of studies that have employed this measure. Westwood et  al.’s (2016) systematic review and meta-​analysis revealed a large-​sized difference in performance between those with EDs and non-​ ED controls (d = 0.52). An alternative task that might be useful because of its frequent use in studies exploring CRT for EDs is the Brixton Test (Burgess & Shallice, 1997), which also assesses the cognitive or conceptual domain of set-​shifting. The ability of this task to detect difficulties with set-​shifting in those with EDs was supported by Tchanturia et  al. (2011) whose sample of 601 participants highlighted medium-​to large-​ sized differences in performance on this measure for 404

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outpatients and inpatients, respectively, compared with non-​ED controls. Participants must predict the movement of a blue circle across 10 locations. The movement of the blue circle forms a pattern, which subsequently changes throughout the task. The participant must therefore adjust their responses in line with the changing pattern. The outcome measure indicative of set shifting ability is the total number of errors that are perseverative in nature. That is to say, those errors committed by the participant where they have continued with a rule despite the occurrence of a new pattern. Tchanturia, Brecelj, et  al. (2004); Tchanturia, Morris, Brecelj, Nikolau, & Treasure (2004); and Holliday, Tchanturia, Landau, Collier, and Treasure (2005) describe examples of studies that have used this measure with people with EDs, and Roberts et al. (2007) in their systematic review reported that this task detects a small-​sized difference (d = 0.21) between those with EDs and non-​ED controls, with people with EDs making a greater number of errors than non-​ED controls. The Trail Making Task (Kravariti, Morris, Rabe-​Hesketh, Murray, & Frangou, 2003; Reitan, 1958) is an additional measure that has been used across the ED literature. This task measures cognitive or conceptual flexibility; participants are required to connect a sequence of dots over three trials. The first trial is a control trial, in which the participant connects unlabeled dots. The second trial uses dots labeled with alphabetical information, and the participant connects the dots in alphabetical order. The third trial, known as Trail B involves an alphanumeric switching component that requires the participants to connect the labeled dots in a number, letter, number, letter sequence; for example, 1-​A-​2-​B-​3-​C and so on. The outcome measure indicative of set-​shifting ability is the time

taken to complete Trail B. Steinglass et al. (2006); Holliday et  al. (2005); Tchanturia, Brecelj, et  al. (2004); Tchanturia, Morris, et al. (2004); Murphy, Nutzinger, Paul, and Leplow (2002); Mathias and Kent (1998); and Kingston, Szmukler, Andrewes, Tress, and Desmond (1996) describe examples where this measure has been used to explore set-​ shifting in the ED population. In Roberts et  al.’s (2007) systematic review and meta-​analysis, these data equated to an effect size of 0.38, with ED participants taking significantly longer to complete Trial B than non-​ED controls. Central Coherence This section is broken down into tasks benefiting from global information processing strategies and tasks benefiting from detailed-​focused information processing strategies. Ideally, in any exploration of the possible impact of CRT, it is useful to include measures that explore both components of central coherence. Object Assembly (Wechsler, 1981) is an example of a task that benefits from global information-​ processing skills and is a performance task from the Wechsler Intelligence Scale (Wechsler, 1981). The participant is required to solve small jigsaw-​type puzzles depicting familiar objects, such as a butterfly or a horse. The outcome measures are the time taken to complete the puzzles and the total number of puzzles completed within a designated time. A shorter time suggests that the participant is able to create an integrated global representation of an item from its individual parts (Tokley & Kemps, 2007), which is why this can be a useful outcome measure regarding global processing strategies. Lang et al. (2014) found this task detected differences in central coherence between those with EDs and non-​ ED controls, with a medium effect size (d = 0.65). The Fragmented Pictures Task (Snodgrass, Smith, Feenan, & Corwin, 1987) is an alternative globally oriented task that might be useful to consider and this has shown to discriminate between those with EDs and non-​ED controls (Harrison et al., 2012). The (Group) Embedded Figures Task, or (G) EFT (Witkin, 1971; Witkin, Oltman, Raskin, and Karp, 2002), is a task that could be described as benefiting from detail-​oriented information-​processing skills and has been widely used to explore cognitive functioning in EDs. This task can either be administrated individually (EFT), or in a group (GEFT). The task requires the participant to identify simple shapes that are hidden within more complex shapes. The outcome measure is the number of seconds

taken to correctly locate the hidden shape. A shorter response latency indicates superior performance at detail processing. Lang et al. (2014), in their meta-​ analysis, found this task detected medium-​sized differences in performance between those with EDs and non-​ED controls (d  =  0.62), with individuals with EDs demonstrating superior detail-​oriented information-​ processing skills relative to non-​ ED controls. An alternative detail-​ oriented task is the Matching Familiar Figures Task (Kagan, Rosman, Day, Albert, & Phillips, 1964). This is a visual perceptual test, which was originally designed to measure cognitive impulsivity (Kagan et al., 1964), has been used to highlight the strength for detailed information processing in individuals with EDs (Southgate, Tchanturia, & Treasure, 2008). The task consists of 12 items, and the participant is required to identify the exact replica of a familiar object (e.g., a lion) among eight highly similar alternatives. The outcome measure is the time taken to correctly identify the identical figure. The number of incorrect responses may also be recorded. A more detail-​ focused cognitive style is associated with reduced response latencies and fewer errors. There were too few studies available to carry out a meta-​ analysis of this task in Lopez, Tchanturia, Stahl, and Treasure’s (2008) systematic review, however they reported effect sizes from 0.41 to 0.89 for those with EDs relative to non-​ED controls. No new uses of this task in ED populations have been reported since this review (Lang et al., 2014). The Rey-​ Osterrieth Complex Figure Test (Osterreith, 1944) is one of the most widely used measures in the ED research literature that has been used to explore central coherence, and this task arguably explores the individuals’ tendency toward a detailed or global processing strategy because it is possible to explore how the patient, through copying a complex figure, builds up the figure and whether they tend toward a more detail-​oriented or a more global-​oriented approach. In previous work, this figure has been used to explore a variety of cognitive processes, including visual perceptual organization, nonverbal memory, planning, problem solving, and motor function (Osterrieth, 1944). There are a variety of methods available for the administration and scoring of the task. Some researchers use the copy administration only, whereas others use a recall administration, which requires participants without prior warning to recall as much of 75% of the picture as possible after a designated interval, which may vary from 3 to 60 minutes. Regarding Harrison

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the measurement of coherence, the central coherence index is relevant. This index is based on the order in which the participant copies the figure, and on style—​that is, whether the figure was copied in a fragmented or continuous manner. A higher central coherence index relates to a more global strategy. Lang et al. (2014) found this measure detects medium-​sized differences in performance between those with EDs and non-​ED controls (d = 0.63). A number of factors will determine the battery of tasks used to evaluate potential changes in cognitive functioning after, compared to before, CRT and at follow-​up for individuals with EDs including patient burden, service resources, and financial limitations and the sensitivity of the task. However, it is hoped that the section above has provided sufficient information to inform these decisions for clinical research groups interested in using and evaluating CRT for EDs. The final section explores priorities for future research.

Future Work

Previous work highlights a paucity of evidence for the possible benefits of CRT for individuals with BN and this may be a focus of future research, given that individuals with BN have also demonstrated inefficiencies in set-​shifting (Harrison et al., 2012; Roberts, Tchanturia, & Treasure, 2010; Wu et  al., 2014) and the positive early findings from Dingemans et  al. (2014) RCT, whose mixed ED sample included individuals with bulimic symptom profiles. The literature reviewed in this chapter indicates that CRT may be of possible benefit for children and adolescents with EDs, and a priority for future work will be to conduct an RCT in this context. It would also be interesting to explore whether group or individual formats are most efficient in improving cognitive functioning in people with EDs and what “dose” of treatment is required for a clinically significant improvement because these questions are currently unanswered by the literature. Furthermore, it will be important to understand how long lasting any possible improvements in cognitive functioning are by conducting longer term follow-​up studies. In addition to this, it will be interesting to explore whether moving from the “cold cognitive” domain to the “hot cognitive” domain and including exercises around emotions and social functioning might be another important way of further developing the scope of CRT as a treatment enhancer that coaches people with EDs in the skills likely to be useful for successful recovery (Tchanturia et al., 2013). Although CRT 406

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has been demonstrated to help retain patients in treatment programs (Lock et  al., 2013), its possible impacts on motivation are not fully understood (Danner, Dingemans, & Steinglass, 2015) and future work should aim to explore this. Finally, although the RCTs in the adult population highlight improved neuropsychological functioning, it will be important to explore how this manifests in improved recovery rates, that is, to what degree do greater cognitive flexibility and bigger-​picture thinking contribute to overall recovery?

Conclusions

To summarize, CRT is a low-​intensity training package that aims to assist individuals with EDs to build on their cognitive abilities to support them to remain in treatment programs and develop the flexible and bigger-​picture thinking skills that may be necessary to move toward recovery. Cognitive remediation therapy can be a useful treatment enhancer provided in an individual or group setting for adults and young people with EDs, and four RCTs in the adult population and numerous case series in the child and adolescent population have demonstrated its positive impact on neuropsychological outcomes.

References

Asch, M., Esteves, J., De Hautecloque, D., Bargiacchi, A., Le Heuzey, M. F., Mouren, M. C., & Doyen, C. (2014). Cognitive remediation therapy for children and adolescents with anorexia nervosa in France: an exploratory study. L’Encephale, 40, 240–​246. Blinder, B. J., Cumella, E. J., & Sanathara, V. A. (2006). Psychiatric comorbidities of female inpatients with eating disorders. Psychosomatic Medicine, 68, 454–​462. Brockmeyer, T., Ingenerf, K., Walther, S., Wild, B., Hartmann, M., Herzog, W.,   .  .  .  Friederich, H. C. (2014). Training cognitive flexibility in patients with anorexia nervosa: a pilot randomized controlled trial of cognitive remediation therapy. International Journal of Eating Disorders, 47, 24–​31. Burgess, P. W., & Shallice, T. (1997). The Hayling and Brixton tests. Bury St Edmonds, UK: Thames Valley Test Company. Chui, H. T., Christensen, B. K., Zipursky, R. B., Richards, B. A., Hanratty, M. K., Kabani, N. J.,   .  .  .  & Katzman, D. K. (2008). Cognitive function and brain structure in females with a history of adolescent-​onset anorexia nervosa. Pediatrics, 122, e426–​e437. Cicerone, K. D., Langenbahn, D. M., Braden, C., Malec, J. F., Kalmar, K., Fraas, M.,  . . .  Ashman, T. (2011). Evidence-​ based cognitive rehabilitation: Updated review of the literature from 2003 through 2008. Archives of Physical Medicine and Rehabilitation, 92, 519–​530. Crawford, J. R., Parker, D. M., Stewart, L. E., Besson, J. A. O., & Lacey, G. (1989). Prediction of WAIS IQ with the National Adult Reading Test: Cross‐validation and extension. British Journal of Clinical Psychology, 28, 267–​273. Cwojdzińska, A., Markowska-​ Regulska, K., & Rybakowski, F. (2009). [Cognitive remediation therapy in adolescent

anorexia nervosa—​ case report]. Psychiatria Polska, 43, 115–​124. Dahlgren, C. L., Lask, B., Landrø, N. I., & Rø, Ø. (2013). Neuropsychological functioning in adolescents with anorexia nervosa before and after cognitive remediation therapy:  A  feasibility trial. International Journal of Eating Disorders, 46, 576–​581. Dahlgren, C. L., Lask, B., Landrø, N. I., & Rø, Ø. (2014). Developing and evaluating cognitive remediation therapy (CRT) for adolescents with anorexia nervosa:  A  feasibility study. Clinical Child Psychology and Psychiatry, 19, 476–​487. Dahlgren, C. L., & Rø, Ø. (2014). A systematic review of cognitive remediation therapy for anorexia nervosa-​development, current state and implications for future research and clinical practice. Journal of Eating Disorders, 2, 1. Danner, U. N., Dingemans, A. E., & Steinglass, J. (2015). Cognitive remediation therapy for eating disorders. Current Opinion in Psychiatry, 28, 468–​472. Dare C, & Eisler I. (1997). Family therapy for anorexia nervosa. In:  D. M. Garner, Garfinkel P, (Eds.), Handbook of Treatment for Eating Disorders (pp. 307–​324). New York: Guilford Press. Davies, H., & Tchanturia, K. (2005). Cognitive remediation therapy as an intervention for acute anorexia nervosa: A case report. European Eating Disorders Review, 13, 311–​316. Dingemans, A. E., Danner, U. N., Donker, J. M., Aardoom, J. J., Van Meer, F., Tobias, K.,  . . .  Van Furth, E. F. (2014). The effectiveness of cognitive remediation therapy in patients with a severe or enduring eating disorder: A randomized controlled trial. Psychotherapy and Psychosomatics, 83, 29–​36. Douglas, K. M., Porter, R. J., Knight, R. G., & Maruff, P. (2011). Neuropsychological changes and treatment response in severe depression. British Journal of Psychiatry, 198, 115–​122. Doyen, C., Contejean, Y., Risler, V., Asch, M., Amado, I., Launay, C.,   .  .  .  Kaye, K. (2015). Cognitive remediation therapy for children: Literature data and clinical application in a child and adolescent psychiatry department. Archives de Pediatrie, 22, 418–​426. Easter, A., & Tchanturia, K. (2011). Therapists’ experiences of cognitive remediation therapy for anorexia nervosa:  Implications for working with adolescents. Clinical Child Psychology and Psychiatry, 16, 233–​246. Fairburn, C. G. (2008). Cognitive behavior therapy and eating disorders. New York, NY: Guilford Press. Fairburn, C. G., Bailey-​Straebler, S., Basden, S., Doll, H. A., Jones, R., Murphy, R.,  . . .  Cooper, Z. (2015). A transdiagnostic comparison of enhanced cognitive behaviour therapy (CBT-​E) and interpersonal psychotherapy in the treatment of eating disorders. Behaviour Research and Therapy, 70, 64–​71. Fairburn, C. G., Cooper, Z., & Shafran, R. (2003). Cognitive behaviour therapy for eating disorders:  A  “transdiagnostic” theory and treatment. Behaviour Research and Therapy, 41, 509–​528. Fassino, S., Pieró, A., Daga, G. A., Leombruni, P., Mortara, P., & Rovera, G. G. (2002). Attentional biases and frontal functioning in anorexia nervosa. International Journal of Eating Disorders, 31, 274–​283. Genders, R., & Tchanturia, K. (2010). Cognitive remediation therapy (CRT) for anorexia in group format: A pilot study. Eating and Weight Disorders, 15, 234–​239. Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). Behavior rating inventory of executive function:  BRIEF. Odessa, FL: Psychological Assessment Resources.

Grant, D. A., & Berg, E. (1948). A behavioral analysis of degree of reinforcement and ease of shifting to new responses in a Weigl-​type card-​sorting problem. Journal of Experimental Psychology, 38, 404. Happé, F., & Frith, U. (2006). The weak coherence account: Detail-​ focused cognitive style in autism spectrum disorders. Journal of Autism and Developmental Disorders, 36, 5–​25. Harrison, A., Tchanturia, K., Naumann, U., & Treasure, J. (2012). Social emotional functioning and cognitive styles in eating disorders. British Journal of Clinical Psychology, 51, 261–​279. Heaton, R. K., Chelune, G. J., Talley, J. L., Kay, G. G., & Curtiss, G. (1993). Wisconsin card sort test manual:  Revised and expanded. Odessa, FL: Psychological Assessment Resources. Holliday, J., Tchanturia, K., Landau, S., Collier, D., & Treasure, J. (2005). Is impaired set-​ shifting an endophenotype of anorexia nervosa? American Journal of Psychiatry, 162, 2269–​2275. Hutchison, S., Roberts, A., & Lask, B. (2014). Family cognitive remediation therapy for child and adolescent anorexia nervosa. In K. Tchanturia (Ed.), Cognitive remediation therapy (CRT) for eating and weight disorders (pp. 147–​161). London, UK: Routledge. Kagan, J., Rosman, B. L., Day, D., Albert, J., & Phillips, W. (1964). Information processing in the child:  Significance of analytic and reflective attitudes. Psychological Monographs, 78, 1. Kaye, W. H., Bulik, C. M., Thornton, L., Barbarich, N., & Masters, K. (2004). Comorbidity of anxiety disorders with anorexia and bulimia nervosa. American Journal of Psychiatry, 161, 2215–​2221. Keel, P. K., & Mitchell, J. E. (1997). Outcome in bulimia nervosa. American Journal of Psychiatry, 154, 313. Kingston, K., Szmukler, G., Andrewes, D., Tress, B., & Desmond, P. (1996). Neuropsychological and structural brain changes in anorexia nervosa before and after refeeding. Psychological Medicine, 26, 15–​28. Kravariti, E., Morris, R. G., Rabe-​Hesketh, S., Murray, R. M., & Frangou, S. (2003). The Maudsley early onset schizophrenia study:  Cognitive function in adolescents with recent onset schizophrenia. Schizophrenia Research, 61, 137–​148. Lang, K., Lopez, C., Stahl, D., Tchanturia, K., & Treasure, J. (2014). Central coherence in eating disorders:  An updated systematic review and meta-​ analysis. World Journal of Biological Psychiatry, 15, 586–​598. Lang, K., Stahl, D., Espie, J., Treasure, J., & Tchanturia, K. (2014). Set shifting in children and adolescents with anorexia nervosa:  An exploratory systematic review and meta‐analysis. International Journal of Eating Disorders, 47, 394–​399. Lang, K., & Tchanturia, K. (2014). A systematic review of central coherence in young people with anorexia nervosa. Journal of Child and Adolescent Behaviour, 2, 140. Lang, K., Treasure, J., & Tchanturia, K. (2015). Acceptability and feasibility of self-​ help cognitive remediation therapy for anorexia nervosa delivered in collaboration with carers:  A  qualitative preliminary evaluation study. Psychiatry Research, 225, 387–​394. Lezak, M. D. (2004). Neuropsychological assessment. Oxford, UK: Oxford University Press. Lindvall, C., Owen, I., & Lask, B. (2011). Cognitive remediation therapy (CRT) for children and adolescents with anorexia nervosa: Resource pack. Oslo, Norway: University of Oslo.

Harrison

407

Lock, J., Agras, W. S., Fitzpatrick, K. K., Bryson, S. W., Jo, B., & Tchanturia, K. (2013). Is outpatient cognitive remediation therapy feasible to use in randomized clinical trials for anorexia nervosa? International Journal of Eating Disorders, 46, 567–​575. Lock, J., Le Grange, D., Agras, W. S., & Dare, C. (2001). Treatment manual for anorexia nervosa:  A  family-​ based approach. New York, NY: Guildford Press. Lopez, C., Tchanturia, K., Stahl, D., & Treasure, J. (2008). Central coherence in eating disorders:  a systematic review. Psychological Medicine, 38, 1393–​1404. Lozano-​ Serra, E., Andrés-​Perpiña, S., Lázaro-​García, L., & Castro-​ Fornieles, J. (2014). Adolescent anorexia nervosa: Cognitive performance after weight recovery. Journal of Psychosomatic Research, 76, 6–​11. Maiden, Z., Baker, L., Espie, J., Simic, M., & Tchanturia, K. (2014). Group cognitive remediation therapy for adolescents with anorexia nervosa:  The flexible thinking group. London, UK: South London and Maudsley NHS Foundation Trust. Maiden, Z., Baker, L., Espie, J., Simic, M., & Tchanturia, K. (2015). Group cognitive remediation therapy format for adolescents. In K. Tchanturia (Ed.), Brief group psychotherapy for eating disorders:  Inpatient protocols (pp. 51–​73). Cambridge, UK: Routledge. Martin, M. M., & Rubin, R. B. (1995). A new measure of cognitive flexibility. Psychological Reports, 76, 623–​626. Martinez, G., S. Cook-​Darzens, P. Chaste, Mouren, M. C., & Doyen, C. (2014). [Anorexia nervosa in the light of neurocognitive functioning: New theoretical and therapeutic perspectives]. L’Encephale, 2, 160–​167. Mathias, J. L., & Kent, P. S. (1998). Neuropsychological consequences of extreme weight loss and dietary restriction in patients with anorexia nervosa. Journal of Clinical and Experimental Neuropsychology, 20, 548–​564. Milos, G., Spindler, A., Schnyder, U., & Fairburn, C. G. (2005). Instability of eating disorder diagnoses:  prospective study. British Journal of Psychiatry, 187, 573–​578. Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–​100. Murphy, R., Nutzinger, D. O., Paul, T., & Leplow, B. (2002). Dissociated conditional-​associative learning in anorexia nervosa. Journal of Clinical and Experimental Neuropsychology, 24, 176–​186. Nelson, H. E., & Willison, J. (1991). National adult reading test (NART). Windsor: Nfer-​Nelson. Ohrmann, P., Kersting, A., Suslow, T., Lalee-​Mentzel, J., Donges, U. S., Fiebich, M.,  . . .  Pfleiderer, B. (2004). Proton magnetic resonance spectroscopy in anorexia nervosa:  correlations with cognition. NeuroReport, 15, 549–​553. Osterrieth, P. A. (1944). The test of copying a complex figure: A contribution to the study of perception and memory. Archives of Psychology, 30, 206–​356. Pitt, S., Lewis, R., Morgan, S., & Woodward, D. (2010). Cognitive remediation therapy in an outpatient setting: A case series. Eating and Weight Disorders, 15, 281–​286. Porter, R. J., Bowie, C. R., Jordan, J., & Malhi, G. S. (2013). Cognitive remediation as a treatment for major depression: A rationale, review of evidence and recommendations for future research. Australian and New Zealand Journal of Psychiatry, 47, 1165–​1175.

408

Cognitive Remediation

Pretorius, N., Dimmer, M., Power, E., Eisler, I., Simic, M., & Tchanturia, K. (2012). Evaluation of a cognitive remediation therapy group for adolescents with anorexia nervosa:  Pilot study. European Eating Disorders Review, 20, 321–​325. Reitan, R. M. (1958). Validity of the Trail Making Test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271–​276. Roberts, M. E., Barthel, F. M. S., Lopez, C., Tchanturia, K., & Treasure, J. L. (2011). Development and validation of the detail and flexibility questionnaire (DFlex) in eating disorders. Eating Behaviors, 12, 168–​174. Roberts, M. E., Tchanturia, K., Stahl, D., Southgate, L., & Treasure, J. (2007). A systematic review and meta-​analysis of set-​shifting ability in eating disorders. Psychological Medicine, 37, 1075–​1084. Roberts, M. E., Tchanturia, K., & Treasure, J. L. (2010). Exploring the neurocognitive signature of poor set-​shifting in anorexia and bulimia nervosa. Journal of Psychiatric Research, 44, 964–​970. Schmidt, U., & Treasure, J. (2006). Anorexia nervosa:  Valued and visible; A  cognitive‐interpersonal maintenance model and its implications for research and practice. British Journal of Clinical Psychology, 45, 343–​366. Snodgrass, J., Smith, B., Feenan, K., & Corwin, J. (1987). Fragmenting pictures on the Apple Macintosh computer for experimental and clinical applications. Behavior Research Methods, Instruments and Computers, 19, 270–​274. Southgate, L., Tchanturia, K., & Treasure, J. (2008). Information processing bias in anorexia nervosa. Psychiatry Research, 160, 221–​227. Steinglass, J. E., Albano, A. M., Simpson, H. B., Wang, Y., Zou, J., Attia, E., & Walsh, B. T. (2014). Confronting fear using exposure and response prevention for anorexia nervosa:  A  randomized controlled pilot study. International Journal of Eating Disorders, 47, 174–​180. Steinglass, J. E., Walsh, B. T., & Stern, Y. (2006). Set shifting deficit in anorexia nervosa. Journal of the International Neuropsychological Society, 12, 431–​435. Tchanturia, K. (Ed.). (2014). Cognitive remediation therapy (CRT) for eating and weight disorders. Hove, East Sussex, UK: Routledge. Tchanturia, K., Brecelj, M., Sanchez, P., Morris, R., Rabe-​ Hesketh, S., & Treasure, J. (2004). An examination of cognitive flexibility in eating disorders. Journal of the International Neuropsychological society, 10, 513–​520. Tchanturia, K., Davies, H., & Campbell, I. C. (2007). Cognitive remediation therapy for patients with anorexia nervosa:  preliminary findings. Annals of General Psychiatry, 6, 1. Tchanturia, K., Davies, H., Lopez, C., Schmidt, U., Treasure, J., & Wykes, T. (2008). Letter to the editor: Neuropsychological task performance before and after cognitive remediation in anorexia nervosa:  a pilot case-​series. Psychological Medicine, 38, 1371–​1373. Tchanturia, K., Davies, H., Reeder, C., & Wykes, T. (2010). Cognitive remediation programme for anorexia nervosa: A manual for practitioners. London, UK: South London and Maudsley NHS Trust. Tchanturia, K., Davies, H., Roberts, M., Harrison, A., Nakazato, M., Schmidt, U.,  . . .  Morris, R. (2012). Poor cognitive flexibility in eating disorders:  Examining the

evidence using the Wisconsin Card Sorting Task. PloS One, 7, e28331. Tchanturia, K., & Doris, E. (2015). Flexibility groups: Cognitive remediation therapy (CRT) in group format:  adults. In K. Tchanturia. (Ed.), Brief group psychotherapy for eating disorders:  Inpatient protocols (pp.  26–​50). Cambridge, UK: Routledge. Tchanturia, K., & Hambrook, D. (2010). Cognitive remediation therapy for anorexia nervosa. In C. Grillo & J. Mitchell (Eds.), The treatment of eating disorders: A clinical handbook. (Vol. 7, pp. 130). New York, NY: Guildford Press. Tchanturia, K., Harrison, A., Davies, H., Roberts, M., Oldershaw, A., Nakazato, M.,   .  .  .  Treasure, J. (2011). Cognitive flexibility and clinical severity in eating disorders. Plos One, 6, e20462. Tchanturia, K., & Lang, K. (2015). Cognitive remediation therapy for anorexia nervosa: A self-​help guide for use with carers. London, UK: South London and Maudsley NHS Trust. Tchanturia, K., Larsson, E., & Brown, A. (2016). Benefits of group cognitive remediation therapy in anorexia nervosa: Case series. Neuropsychiatrie, 30, 42–​49. Tchanturia, K., Lloyd, S., & Lang, K. (2013). Cognitive remediation therapy for anorexia nervosa: Current evidence and future research directions. International Journal of Eating Disorders, 46, 492–​495. Tchanturia, K., & Lock, J. (2011). Cognitive remediation therapy for eating disorders:  Development, refinement and future directions. In R. Adan & W. Kaye (Eds.), Behavioral neurobiology of eating disorders (pp. 269–​287). Berlin and Heidelberg, Germany: Springer. Tchanturia, K., Lounes, N., & Holttum, S. (2014). Cognitive remediation in anorexia nervosa and related conditions: A systematic review. European Eating Disorders Review, 22, 454–​462. Tchanturia K., Morris, R., Brecelj, M., Nikolau, V., & Treasure, J. (2004). Set shifting in anorexia nervosa: An examination before and after weight gain, in full recovery and the relationship to childhood and adult OCDP traits. Journal of Psychiatric Research, 38, 545–​552. Tchanturia, K., Whitney, J., & Treasure, J. (2006). Can cognitive exercises help treat anorexia nervosa? Eating and Weight Disorders, 11, e112–​e116. Tokley, M., & Kemps, E. (2007). Preoccupation with detail contributes to poor abstraction in women with anorexia nervosa. Journal of Clinical and Experimental Neuropsychology, 29, 734–​741.

Treasure, J., & Schmidt, U. (2013). The cognitive-​interpersonal maintenance model of anorexia nervosa revisited:  A  summary of the evidence for cognitive, socio-​ emotional and interpersonal predisposing and perpetuating factors. Journal of Eating Disorders, 1, 1. van Noort, B. M., Kraus, M. K. A., Pfeiffer, E., Lehmkuhl, U., & Kappel, V. (2016). Neuropsychological and behavioural short‐term effects of cognitive remediation therapy in adolescent anorexia nervosa:  A  pilot study. European Eating Disorders Review, 24, 69–​74. van Noort, B. M., Pfeiffer, E., Lehmkuhl, U., & Kappel, V. (2015). Cognitive remediation therapy for children with anorexia nervosa. Zeitschrift für Kinder-​und Jugendpsychiatrie und Psychotherapie, 43, 351–​355. Wechsler, D. (1981). WAIS-​R manual:  Wechsler adult intelligence scale-​revised. New  York, NY:  Psychological Corporation. Westwood, H., Stahl, D., Mandy, W., & Tchanturia, K. (2016). The set-​shifting profiles of anorexia nervosa and autism spectrum disorder using the Wisconsin Card Sorting Test: A systematic review and meta-​analysis. Psychological Medicine, 10, S0033291716000581. Whitney, J., Easter, A., & Tchanturia, K. (2008). Service users’ feedback on cognitive training in the treatment of anorexia nervosa:  a qualitative study. International Journal of Eating Disorders, 41, 542–​550. Witkin, H. A. (1971). Group embedded figures test. Palo Alto, CA: Consulting Psychologists Press. Witkin, H. A., & Goodenough, D. R. (1977). Field dependence and interpersonal behavior. Psychological Bulletin, 84, 661. Witkin, H., Oltman, P., Raskin, E., & Karp, S. (2002). Group embedded figures test manual. Redwood City, CA: Mindgarden. Wood, L., Al-​Khairulla, H., & Lask, B. (2011). Group cognitive remediation therapy for adolescents with anorexia nervosa. Clinical Child Psychology and Psychiatry, 16, 225–​231. Wu, M., Brockmeyer, T., Hartmann, M., Skunde, M., Herzog, W., & Friederich, H. C. (2014). Set-​shifting ability across the spectrum of eating disorders and in overweight and obesity:  A  systematic review and meta-​ analysis. Psychological Medicine, 44, 3365–​3385. Wykes, T., Huddy, V., Cellard, C., McGurk, S. R., & Czobor, P. (2011). A meta-​analysis of cognitive remediation for schizophrenia:  Methodology and effect sizes. American Journal of Psychiatry, 168, 472–​485.

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C H A PT E R

 Costs and Cost-​Effectiveness in Eating Disorders

21

Scott J. Crow

Abstract Costs and cost-​effectiveness are now well recognized as important aspects of the burdens of and treatment for eating disorders. Ample evidence indicates that, leading up to and following diagnosis, the cost burdens associated with eating disorders are high; this is true whether viewed from the perspective of a healthcare payer or from a societal perspective. On the other hand, it is important to note that studies involving cost modeling and direct cost collection in treatment have shown that treatment of eating disorders is quite cost-​effective. Cost is now increasingly examined as an outcome in eating disorder treatment trials. This remains an area of great need for further research. Key Words:  anorexia nervosa, bulimia nervosa, burden, cost, cost-​effectiveness, eating disorder, treatment

Introduction

Healthcare costs receive particular scrutiny in illnesses, such as eating disorders, that are perceived to be expensive to treat, difficult to treat, or both. The costs of eating disorders (EDs) have now been extensively described, and are clearly high, to individuals, to third-​party payers, and to society. As more effective treatments for eating disorders are developed, increasing interest will be turned to identifying treatments that are not only effective, but also cost-​effective. This chapter examines what is known about the various costs burdens associated with EDs and their treatment. It also examines the growing data on the cost-​effectiveness of specific treatments. Finally, it examines directions for future study in this area.

Estimates of the Individual Costs of Eating Disorders

Having an ED may carry costs for the specific individual affected, and these may be a fairly large part of the overall cost burden associated with EDs. Potential costs include the direct financial costs 410

associated with treatment; direct financial costs associated with symptoms of the illness, such as food for binge eating or substances used for purging; and time costs associated with symptoms of these illnesses or their treatment. These aspects of costs have been studied only rarely.

Personal Costs

To date, only one study has attempted to estimate the financial costs associated with bulimia nervosa (BN) symptoms (Crow et al., 2009). This study modeled annual food and purging-​ related costs of bulimia symptoms in 10 subjects based on 1-​week food records. Subjects in this study reported 2.5 objective binge episodes, 2.4 subjective binge episodes, and 3.6 purging episodes per week on average, and spent an average of $5,582.00 (2007 US dollars) per year on food. Food and purging-​ related costs represented 32.7% of all food costs, about $1,600 per year. However, these figures might be viewed as underestimates, as frequency of binge eating and purging was somewhat lower than average for many studies of BN.

A second study has made a limited attempt to measure time costs associated with BN (Crow et al., 2013). In this multicenter BN randomized-​ controlled trial (described later in this chapter), time costs to family members related to participants with BN were measured in a subset of participants. A family member or significant other was asked to complete time-​monitoring records at entry into treatment and after the first 18 weeks of treatment. The results showed that a substantial amount of time was lost to BN symptoms and their treatment by family members/​significant others (about 4 hours per week) and that this amount dropped by about 75% over the first 18 weeks of treatment.

Per-​Patient Financial Costs

Healthcare costs for those with eating disorders are elevated. For example, data from the Medical Expenditure Panel Survey show that costs were $1,869 higher in those with EDs than in those without (Samnaliev, Noh, Sonneville, & Austin, 2015). Several studies have examined cost per patient from a third-​party-​payer perspective using health plan data. Striegel-​Moore, Leslie, Petrill, Garvin, and Rosenheck (2000) accessed data through a US insurance database (MarketScan) containing annual inpatient and outpatient healthcare service use data of individuals insured through large employers. The above database is composed from privately insured paid medical and prescription drug claims. A data sample of 4  million was used in 1995 and diagnosed according to the International Classification of Disease, 9th edition. Treatment costs and out-​of-​ pocket patient expenses were assessed from insurance claims. Group differences in annual treatment costs of EDs—​anorexia nervosa (AN), BN, and binge eating disorder (BED)—​ were compared against schizophrenia and obsessive-​ compulsive disorder (OCD). A total of 21,567 insurance claims, comprising a total of 1,932 patients, were reported for EDs; this number accounted for 1.1% of all mental health claims. Inpatient treatment occurred much less frequently than outpatient treatment for all EDs. The average cost of inpatient treatment collapsed across EDs was $12,432 for female patients and $10,126 for male patients. The groups did not differ significantly in inpatient treatment costs. Outpatient treatment costs for female patients were $2,344 for AN, $1,882 for BN, and $1,582 for eating disorder not otherwise specified (EDNOS). Male outpatient treatment costs were $1,154 for AN, $1,206 for BN, and $1,150 for EDNOS.

Mean treatment costs for AN were significantly higher than for both schizophrenia and OCD. Treatment costs for BN were found to be significantly lower than schizophrenia, but significantly higher than OCD. The EDNOS treatment costs were significantly lower than schizophrenia and did not differ significantly from OCD. Subsequently, Striegel-​ Moore and colleagues (2005) examined prediagnosis and postdiagnosis costs in people with an eating disorder. Costs rose substantially in the year preceding diagnosis, and remained elevated in the year following diagnosis. A similar report from Mitchell et al. (2009) showed elevated costs (similar to those found in depression) following ED diagnosis. In this sample, costs were not statistically significantly elevated in the year preceding diagnosis. This might be simply due to a modest sample size, though, as numerical costs doubled in the year preceding diagnosis, but this change was not statistically significant. Toulany and colleagues (2015) reported a study of societal perspective costs of hospitalization for adolescent AN. The analysis used microcosting of data from 73 adolescents (a highly labor-​intensive method). Mean length of stay was about 38  days, and mean cost was $54,392 (2015 Canadian dollars). Body mass index (BMI) was inversely related to costs: hospital costs declined 15.7% for every 1-​ point increase in admit BMI. Finally, Bellows and colleagues (2015), using Veteran’s Administration data, showed markedly increased care costs in people with BED or EDNOS as compared with those without an eating disorder ($33,716 vs. $33,052 vs. $19,548, respectively). Taken together, these findings suggest elevated costs in ED of similar magnitude to that seen in other psychopathology. In addition, these elevations may precede the point of formal diagnosis.

Estimates of the National Cost of Eating Disorders

Relatively few cost-​of-​illness studies exist within the scientific literature examining the cost implications of EDs. This is surprising given the common view of EDs as expensive. Further, evidence suggests that use of healthcare in those with EDs is higher than in those without EDs and elevated to a degree similar to comparison subjects with other psychiatric disorders (Sansone, Wiederman, & Sansone, 1997; Striegel-​Moore et al., 2005). Only five formal cost-​of-​illness studies examining the cost implication of EDs exist; these are reviewed in this section. Crow

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The UK Office of Health Economics (Office of Health Economics, 1994) used national surveys of general practice and hospital use to assess both primary and tertiary care costs of EDs in the United Kingdom. The authors concluded that in 1990, 46,806 patients in the United Kingdom sought general practitioner consultation for AN. The average unit cost per consultation was used (9.85 Euros) to calculate the annual primary care cost in the United Kingdom of 580,000 Euros. For tertiary care cost, the total number of inpatient treatment bed days were used to assess the cost of AN. A total of 25,748 annual bed days occurred in 1990, with an average inpatient length of stay of 21.5 days for AN, for a total cost of 3.5  million Euros. This method may not have identified other medical use or outpatient care. Therefore, the overall cost of AN in the United Kingdom is likely to be grossly underestimated at 4.2 million Euros. Krauth, Buser, and Vogel (2002) examined both direct and indirect costs of ED in Germany. The study remains the only cost-​of-​illness research including indirect cost estimates for EDs. Data was accessed through statutory health insurance (SHI), statutory pension insurance (SPI), and epidemiological literature on anorexia and bulimia. Direct costs included inpatient treatment costs as well as rehabilitation (time spent in convalescent centers). Indirect costs were assessed through mortality and morbidity costs. Importantly, outpatient care, psychotherapy, and pharmaceuticals were not examined by this study. The estimated costs of EDs are thus an underestimate. The direct and indirect cost of anorexia nervosa was estimated to be 195 million Euros. Direct cost of illness estimates were 59 million Euros for inpatient expenses and 6 million Euros for both rehabilitation and convalescence costs, totaling 65 million Euros for direct treatment costs. Interestingly, indirect treatment costs were estimated to be vastly greater, totaling 130 million Euros (67% of total). Mortality costs were estimated at 123 million Euros, using the human capital approach. Bulimia nervosa was estimated at a cost of 124 million Euros to the German economy. Direct treatment costs were approximately 7  million for inpatient treatment costs and 3  million for rehabilitation and convalescent costs, totaling 10  million Euros. Indirect costs were estimated at being 92% of the overall cost of BN, totaling 112 million Euros. Overall, AN and BN in Germany combined to equal a total estimated cost of 319 million Euros (for a population of roughly 82 million). 412

Costs and Cost-Effectiveness

The publication by Matthers, Vos, and Stevenson (1999) is currently the most comprehensive cost-​ of-​illness study for EDs. Data were accessed from National Mental Health Surveys (1994–​1997) to assess years lost due to disability, public and private healthcare costs, pharmaceutical costs, and research and prevention funding. Annual cost of EDs in Australia (1994) was estimated to be $22  million (Aus). In addition, expenses on research, administration and prevention were estimated at $4  million (Aus) in 1994. Primary and inpatient care costs were estimated at $3 and $14 million, respectively. Two additional studies have been conducted to assess the costs of EDs. An Austrian study by Rathner and Rainer (1997) assessed the inpatient treatment cost of AN and BN, estimated at 140 million Austrian schillings in 1994. Furthermore, Nielsen et al. (1996) published a study in Denmark assessing the inpatient treatment costs of EDs. The researchers found the annual treatment cost in 1993 for inpatients with EDs was €6.4 million, 4.7 million of which was specifically incurred by AN. Overall, the national cost-​of-​illness literature on ED remains limited in size and scope, and the methodological inconsistencies used within the studies provide vastly differing cost estimates. At this point, these estimates are also relatively dated. An additional major limitation is the lack of estimates of indirect costs associated with EDs. Since the only study to examine this suggested indirect costs are almost triple direct costs accrued from EDs (Krauth et  al., 2002), research including indirect costs of EDs would likely drastically increase cost estimates as well as improve the validity and accuracy of cost-​ of-​illness studies. Indirect costs should be assessed in future studies to yield more thorough and accurate cost estimates. For now, cost-​of-​illness research findings for EDs likely remain gross underestimates.

Cost-​Effectiveness of Eating Disorder Treatments

Only a handful of studies have specifically examined the cost-​effectiveness of various treatments. In conducting such a study, the first question to be answered is:  Will the analysis involve direct data collection or modeling based on existing literature? Modeling studies are more readily conducted and can be quite valuable, but they introduce a greater number of uncertainties with regard to the assumptions made in the model. Thus, direct data collection is preferable. However, most ED treatment studies to date have only collected data primarily examining clinical effectiveness; only a few studies

(Byford et al., 2007; Crow et al., 2013) have been designed a priori for prospective examination of cost-​effectiveness (but more will be forthcoming). In a few other instances, studies have been designed to examine clinical effectiveness only and examinations of cost-​effectiveness have followed thereafter. One study has attempted to model cost outcomes in AN treatment (Crow & Nyman, 2004). This study made a number of assumptions regarding course of illness and mortality. In addition, assumptions were made about an integrated treatment approach versus a more typical “community” approach with regard to treatments provided, unit costs, and effectiveness. The unit of analysis (given the high mortality rate associated with AN) was the cost per year of life saved. This modeling analysis yielded an overall cost per year of life saved of $30,180. The authors concluded that this cost fell well within the typically accepted norms for the value of a year of life in other areas of medicine. Another study has reported attempts to assign unit costs to a BN treatment trial (Koran et  al., 1995). In this study, costs were assigned to the use observed in participants in a trial examining various lengths of cognitive-​behavioral therapy (CBT) treatment or desipramine treatment, either alone or in combination, in the treatment of BN. The effectiveness metric came from the data collected in the original trial. Cost-​effectiveness ratios were calculated to yield a cost per abstinent patient at 32-​week follow-​up; these suggested that medication treatment was more cost-​effective than psychotherapy alone or combination treatment. The cost-​effectiveness of telemedicine-​delivered CBT was examined in a randomized, controlled trial (Crow et al., 2009). This study included costs for both patient and therapist travel (in the face-​to-​ face condition), and showed that telemedicine cost was more cost-​effective than face-​to-​face treatment. Byford and colleagues (2007) reported on the cost-​effectiveness for different treatment strategies for AN. This multicenter trial with 167 participants examined cost-​effectiveness of inpatient, specialist outpatient, or generalist outpatient treatment over 2 years of follow-​up. Use and unit costs came from National Health Service data, while effectiveness results were generated by the trial. After 2  years, specialist outpatient treatment dominated (i.e., was more effective and cost less than) the alternative treatment. The cost-​ effectiveness of family-​ based therapy for AN was estimated in another study (Lock, Couturier, & Agras, 2008). This study estimated

costs for 81 participants in the trial; avenge cost per subject was $33,015. The cost-​effectiveness index (the costs for all subjects divided by the number of remitted subjects) was calculated using several remission definitions, and this ranged from approximately $34,000 to nearly $84,000, depending on the definition used. Egger et  al. (2016) compared cost-​effectiveness of focal psychodynamic therapy (FPT) and cognitive-​behavioral therapy-​enhanced (CBT-​E) in 156 people with AN across 10 months of treatment and 1 year of follow-​up. The authors concluded that FPT was more effective that CBT-​E and cost less as well (that is, FBT dominated). A fourth study examined the cost-​effectiveness of CBT versus a stepped series of interventions in the treatment of BN (Crow et  al., 2013). In this study involving 293 subjects, use was determined from study participation records as well as the completion of healthcare diaries. Unit costs came from the Center for Medicare Services, as well as the Red Book, in the case of drug prices (Thompson Healthcare, 2005). Effectiveness was defined as abstinence, generated from study records. The results of the trial showed that stepped care approaches were more effective and cost less than beginning with CBT (mean costs of $12,146/​abstinent subject for stepped vs. $20,317 for CBT). Of note, these costs per abstinent subject substantially exceeded the cost of treating a given subject (since only a fraction of subjects become abstinent). Fifth, Lynch and colleagues (2010) examined cost-​ effectiveness of CBT-​ based guided self-​ help (GSH) for 123 people with BN, BED, or recurrent binge eating in a randomized, controlled trial. The study used a limited societal perspective. The CBT-​ GSH was more effective and less costly than treatment as usual. Finally, one paper has reported on the results a cost-​effectiveness analysis of an integrated treatment program for EDs in a hospital setting (Williamson, Thaw, & Varnado-​ Sullivan, 2001). This study compared two strategies for treatment:  beginning with inpatient treatment, or using a “systematic, decision-​tree approach to treatment.” This study involved 51 subjects with either AN or BN who were assigned to one of those two treatment strategies. Costs came directly from hospital records. The results of this study showed that overall costs were nearly $10,000 less per case in the decision-​ tree treatment approach. Of note, however, since the costs were hospital-​based only, it seems certain that not all healthcare costs were captured; a Crow

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fuller accounting of outpatient and other medical costs might have resulted in a smaller or even larger advantage for the decision-​tree approach.

well-​designed cross-​effectiveness or cost-​utility components, so such data will be forthcoming.

Cost Utility of Eating Disorder Treatment

Aardoom, J. J., Dingemans, A. E., van Ginkel, J. R., Spinhoven, P., Van Furth, E. F., & Van den Akker-​van Marle, M. E. (2016). Cost-​utility of an internet-​based intervention with or without therapist support in comparison with a waiting list for individuals with eating disorder symptoms: a randomized controlled trial. International Journal of Eating Disorders, 49, 1068–​1076. doi: 10.1002/​eat.22587 Bellows, B. K., DuVall, S. L., Kamauu, A. W., Supina, D., Babcock, T., & LaFleur, J. (2015). Healthcare costs and resource utilization of patients with binge-​eating disorder and eating disorder not otherwise specified in the Department of Veterans Affairs. International Journal of Eating Disorders, 48, 1082–​1091. doi: 10.1002/​eat.22427 Byford, S., Barrett, B., Roberts, C., Clark, A., Edwards, V., Smethurst, N., & Gowers, S. G. (2007). Economic evaluation of a randomised controlled trial for anorexia nervosa in adolescents. British Journal of Psychiatry, 191, 436–​440. doi: 10.1192/​bjp.bp.107.036806 CDC/​National Center for Health Statistics (1995). International Classification of Diseases, 9th Edition. Crow, S. J., Agras, W. S., Halmi, K. A., Fairburn, C. G., Mitchell, J. E., & Nyman, J. A. (2013). A cost effectiveness analysis of stepped care treatment for bulimia nervosa. International Journal of Eating Disorders, 46, 302–​307. doi:  10.1002/​ eat.22087 Crow, S. J., Frisch, M. J., Peterson, C. B., Croll, J., Raatz, S. K., & Nyman, J. A. (2009). Monetary costs associated with bulimia. International Journal of Eating Disorders, 42, 81–​83. doi: 10.1002/​eat.20581 Crow, S. J., & Nyman, J. A. (2004). The cost-​effectiveness of anorexia nervosa treatment. International Journal of Eating Disorders, 35, 155–​160. doi: 10.1002/​eat.10258 Egger, N., Wild, B., Zipfel, S., Junne, F., Konnopka, A., Schmidt, U.,  . . .  Konig, H. H. (2016). Cost-​effectiveness of focal psychodynamic therapy and enhanced cognitive-​ behavioural therapy in out-​patients with anorexia nervosa. Psychological Medicine, 46, 3291–​3301. doi:  10.1017/​ S0033291716002002 Koran, L. M., Agras, W. S., Rossiter, E. M., Arnow, B., Schneider, J. A., Telch, C. F.,  . . .  Kraemer, H. C. (1995). Comparing the cost effectiveness of psychiatric treatments: Bulimia nervosa. Psychiatry Research, 58, 13–​21. Krauth, C., Buser, K., & Vogel, H. (2002). How high are the costs of eating disorders—​ anorexia nervosa and bulimia nervosa—​ for German society? European Journal of Health Economics, 3, 244–​250. doi:  10.1007/​ s10198-​002-​0137-​2 Lock, J., Couturier, J., & Agras, W. S. (2008). Costs of remission and recovery using family therapy for adolescent anorexia nervosa: A descriptive report. Eating Disorders, 16, 322–​330. doi: 10.1080/​10640260802115969 Lynch, F. L., Striegel-​Moore, R. H., Dickerson, J. F., Perrin, N., Debar, L., Wilson, G. T., & Kraemer, H. C. (2010). Cost-​ effectiveness of guided self-​ help treatment for recurrent binge eating. Journal of Consulting and Clinical Psychology, 78, 322–​333. doi: 10.1037/​a0018982 Matthers, C. D., Vos, E. T., & Stevenson, C. E. (1999). The burden of disease and injury in Australia. Canberra:  Australian Institute of Health and Welfare.

Cost utility is defined as the cost of improved quality of life, usually expressed as quality-​adjusted life years (QALYs). Three studies have examined the cost utility of ED treatments. The first examined cost per QALY in BN treatment in 72 people receiving inpatient treatment (Pohjolainen et al., 2010). Significant improvements in quality of life were seen with treatment, and in the base case analysis, the cost per QALY was 16,481 Euros. A second study looked at the cost utility of hospitalization for AN (Pohjolainen et  al., 2016). Again, substantial improvements in quality of life were observed in the 39 hospitalized participants. Cost per QALY in the base case analysis was 64,440 Euros. Aardoom and colleagues (2016) examined cost utility of online treatment for ED (FEATBACK) alone or with varying intensity of therapist support. All levels of active treatment showed benefit, with strongest support for cost-​utility of FEATBACK without therapist support.

Future Directions

The foregoing suggests several areas for future research efforts. First, updated estimates of the national costs associated with EDs from a wide variety of countries would be useful for ED advocates and for those planning healthcare services. Notably, the existing estimates are now relatively old. Additionally, the national costs of ED provide a potent argument for advocates of ED prevention efforts. Where possible, both direct and indirect cost should be examined. As noted before, time cost associated with EDs may be particularly important. Developing methodologies to measure individual indirect costs would help to provide a more accurate picture of the total illness-​associated burden and may help to form part of a stronger rationale for treatment that might be a powerful tool in individual treatments. The second broad area in which continued research is needed involves the cost-​ effectiveness of treatments. Several studies have examined this topic thus far, but the number of studies examining clinical effectiveness greatly outweighs the number examining cost-​effectiveness. Currently, studies of new treatments and new methods of treatment delivery are underway, and many of these have 414

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References

Mitchell, J. E., Myers, T., Crosby, R., O’Neill, G., Carlisle, J., & Gerlach, S. (2009). Health care utilization in patients with eating disorders. International Journal of Eating Disorders, 42, 571–​574. doi: 10.1002/​eat.20651 Nielsen, S., Moller-​ Madsen, S., Isager, T., Jorgensen, J., Pagsberg, K., & Theander, S. (1996). Utilization of psychiatric beds in the treatment of ICD-​ 8 eating disorders in Denmark, 1970–​1993. Paper presented at the AEP Conference, London. Office of Health Economics. (1994). Eating Disorders. London: OHE. Pohjolainen, V., Rasanen, P., Roine, R. P., Sintonen, H., Koponen, S., & Karlsson, H. (2016). Cost-​effectiveness of anorexia nervosa in QALYs. Nordic Journal of Psychiatry, 1–​5. doi: 10.1080/​08039488.2016.1224922 Pohjolainen, V., Rasanen, P., Roine, R. P., Sintonen, H., Wahlbeck, K., & Karlsson, H. (2010). Cost-​utility of treatment of bulimia nervosa. International Journal of Eating Disorders, 43, 596–​602. doi: 10.1002/​eat.20754 Rathner, G., & Rainer, B. (1997). [Annual treatment rates and estimated incidence of eating disorders in Austria]. Wien Klin Wochenschr, 109, 275–​280. Samnaliev, M., Noh, H. L., Sonneville, K. R., & Austin, S. B. (2015). The economic burden of eating disorders and related mental health comorbidities:  An exploratory analysis using the U.S. Medical Expenditures Panel Survey.

Preventive Medicine Reports, 2, 32–​34. doi:  10.1016/​ j.pmedr.2014.12.002 Sansone, R. A., Wiederman, M. W., & Sansone, L. A. (1997). Healthcare utilization among women with eating disordered behavior. American Journal of Managed Care, 3, 1721–​1723. Striegel-​Moore, R. H., Dohm, F. A., Kraemer, H. C., Schreiber, G. B., Crawford, P. B., & Daniels, S. R. (2005). Health services use in women with a history of bulimia nervosa or binge eating disorder. International Journal of Eating Disorders, 37, 11–​18. doi: 10.1002/​eat.20090 Striegel-​Moore, R. H., Leslie, D., Petrill, S. A., Garvin, V., & Rosenheck, R. A. (2000). One-​year use and cost of inpatient and outpatient services among female and male patients with an eating disorder: Evidence from a national database of health insurance claims. International Journal of Eating Disorders, 27, 381–​389. Thompon Healthcare. (2005). The Red Book. Thomson. Toulany, A., Wong, M., Katzman, D. K., Akseer, N., Steinegger, C., Hancock-​Howard, R. L., & Coyte, P. C. (2015). Cost analysis of inpatient treatment of anorexia nervosa in adolescents: Hospital and caregiver perspectives. CMAJ Open, 3, E192–​E197. doi: 10.9778/​cmajo.20140086 Williamson, D. A., Thaw, J. M., & Varnado-​ Sullivan, P. J. (2001). Cost effectiveness analysis of a hospital-​ based cognitive-​behavioral treatment program for eating disorders. Behavior Therapy, 32, 459–​477.

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PART 

Emerging Topics

5



CH A PT E R

 Selective Eating: Normative Developmental Phase or Clinical Condition?

22

Nancy Zucker, Courtney Arena, Cortney Dable, Jasmine Hill, Caroline Hubble, Emilie Sohl, and Jee Yoon

Abstract Selective eating (also referred to as picky or fussy eating) has been described as a normative developmental phase that a significant minority experience and, potentially, “grow out of” without formal intervention. This chapter reviews the literature on selective eating from the stance that this eating pattern is a clinical condition rather than a normative developmental phase. Construing selective eating as a clinical condition, it probes questions of definition, chronicity, and impairment that would warrant intervention. It explores the phenomenology of selective eating, suggesting that the experience of disgust has been relatively neglected in understanding the experience of selective eaters and that the inclusion of this feature may offer some novel hypotheses for both necessary treatment elements and novel conceptualizations about what it means to “outgrow” selective eating. Finally, assuming the hypotheses proposed are accepted, it suggests some necessary treatment elements to expand food variety in individuals with selective eating. Key Words:  selective eating, picky eating, food avoidance, disgust, sensory sensitivity

Selective eating, an eating pattern in which an individual eats a lower variety of food than is typical or potentially healthy, is arguably the most prevalent pattern of disordered eating, but one for which there is the least consensus. At issue are fundamental questions:  What is the definition of a selective eater? What is the phenomenology of a selective eater? Can selective eating can be considered a normative developmental phase? Is selective eating harmful? When or how should intervention should be undertaken, and if so, by whom? What does it mean to “grow out of” being a selective eater? There have been some excellent reviews written to better inform the nature of selective eating (for example, see Taylor, Wernimon, Northstone, & Emmett, 2015). Rather than repeating the excellent information depicted in these reviews, this chapter focuses on these controversies and the research that can inform preliminary steps that both address these questions and give directions for future research.

Notably, this chapter takes a somewhat nontraditional stance. Rather than considering selective eating as a normative developmental phase, we consider whether selective eating is a clinical condition and whether those children who “grow out of” selective eating manifest a different pattern of eating than those who persist.

Selective Eating: How Should We Define It?

“Selective eating” (hereafter SE) is a term that has been used to describe a pattern of eating typically characterized by the following criteria:  (1)  consumption of a narrow range of food, (2)  unwillingness to try new foods, (3)  absence of abnormal cognitions regarding weight and/​ or shape, (4)  absence of premorbid preoccupations regarding weight and/​or shape, (5) low, normal, or high weight (Lask & Bryant-​Waugh, 1999, p. 39). Selective eating has also been defined as an “extreme selectivity in preferred foods” (Nicholls, Christie, 419

Randall, & Lask, 2001). To add further clarity to the presentation of SE, we attempt to focus on children, adolescents, and adults who are selective, but whose food intake is adequate (i.e., their weight is normal or high). This focus is to avoid low weight status complicating the clinical picture. To develop a system for efficiently intervening with individuals with SE, it is first helpful to have a precise definition of the condition that is being treated. In the case of SE, there are at least three core questions that need to be resolved to define when SE is a clinical condition worthy of attention. First, what is the frequency with which SE occurs that is considered indicative of a clinical threshold of severity? Second, what is the duration for which this threshold should occur that may warrant concern? Third, what are the essential features that discriminate an individual with SE from one without? We attempt to address each of these questions in turn.

Frequency Threshold of Severity

Differences in how frequency is defined for SE across research cohorts may contribute to vast differences in the prevalence estimates of this eating pattern, let  alone our understanding of the phenomenology of SE. We argue that these differences in prevalence estimates contribute to misconceptions about SE, and lead to conceptualizations of SE as a normative developmental phase, rather than a behavioral pattern that is distinct and persistent for a subset of individuals. For instance, prevalence of SE has ranged from a low of 5.6% to a high of 59%. If nearly 60% of children were demonstrating a particular eating pattern, it would indeed be hard to argue that it was atypical. However, studies that document higher prevalence levels have typically used one item, and that one item permitted children who were “sometimes” selective to be grouped with those who were “often” or “always” selective. For example, Xue et al. (2015) documented prevalence estimates of 59% in 7-​to 12-​year-​olds by asking mothers whether their child was a picky eater, with responses including “never picky,” “somewhat picky,” and “always picky.” Picky eaters were defined as those who were “somewhat picky” or “always picky.” In a study of young children (4 to 24  months old), Carruth et  al. (Carruth, Ziegler, Gordon, & Barr, 2004) defined picky eater status as those whose caregivers endorsed either “somewhat picky” or “very picky” resulting in a picky eating category with a prevalence estimate of 19%–​ 50% (Carruth et  al., 2004). In Machado et  al.’s 2016 study (Machado, Dias, Lima, Campos, & 420

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Gonçalves, 2016), mothers were asked whether their child “does not eat well” or “refuses to eat” and had to respond with either not at all applicable, sometimes, or often applicable. Picky eaters were defined as those with an answer of sometimes or greater, a strategy that adhered to the methods employed by Cano et al. (2015). In fact, Machado et al. (2016) deliberately employed this strategy so that more typical eating disturbances and also more severe eating disturbances were captured. Prevalence estimates resulting from this definitional strategy ranged from 13% to 27%. Thus, across all these studies (and the majority of published research), a child who sometimes did not eat well or sometimes refused to eat could be combined with a child who often or always refused to eat or always did not eat well. We would argue that these are very different groups of children and that making a cutoff of “sometimes” is blurring the boundaries between transitory eating behaviors and those that persist and are associated with impairment. An alternative has been to use more data-​analytic strategies to better capture the nature of SE and arrive at perhaps more precise prevalence estimates. For example, in Tharner et al.’s (2014) study of 4-​ year-​olds in the Netherlands, the study in which the prevalence was cited as 5.6%, a version of the Child Eating Behaviour Questionnaire was used with 35 items relating to eating behavior, with answers ranging from 1 (never) to 5 (always) on a 5-​point Likert scale. Children classified as “fussy eaters” scored 1.5 standard deviations higher than remaining groups on subscales measuring food fussiness, slowness in eating, and satiety responsiveness. Notably, this group did not differ in energy intake compared with nonfussy eaters, though they exhibited a lower BMI than nonfussy groups (we return to this later). In terms of this discussion of a “pure” SE group defined by limited food variety, this group may include those who also consumed an insufficient quantity of food. The authors argue that this lower prevalence may be due to a data-​driven approach for defining SE rather than using a single question as employed in some studies. Micali et  al. (2011) conducted an elegant study in which factor analysis was used to define a group with SE. While these researchers also used a threshold of “sometimes,” an important difference in the study is that every item on the selective eating factor loading had to meet this threshold (five items assessing food selectivity, unwillingness to try new foods, need for special food preparation, and strong preferences). The resulting group represented about 7% of the sample and had between 1.6–​4.2

the odds of having comorbid psychiatric conditions or symptoms (approximately 3% to 7% of the sample in regard to psychiatric diagnoses and 30% of the sample in regard to somatic symptoms). These data-​driven approaches might capture more complex conceptualizations of SE by capturing multiple features and might lead to the development of screening tools. However, at a more fundamental level, these approaches make it challenging to understand the phenomenology of SE, or differentiate the “typical” from the severe, as different levels of severity (or important differences in presentation) may be collapsed into single categories. That said, these elegant approaches offer an intriguing and potentially less biased approach to defining SE. A potential compromise solution to this threshold confusion was proposed by Mascola, Bryson, and Agras (2010). Notably, the authors were addressing a different question: that of coming up with the definition of SE that would capture this behavioral pattern as a trait feature. However, the solution is interesting. Over duration of years, a child was considered as having SE if every year their mother rated them as picky at a level of sometimes or higher but at least 1 year had have a rating of often or higher. Thus, they combined a higher threshold item against the background of averagely endorsed ratings. Taylor, Wernimont, Northstone, and Emmett (2015) also derived a more optimal definition of SE. For children to be classified under SE, parents had to endorse the extreme rating (Yes, Very Choosy) at least at 2 time points. Using this classification, 3.5% of children were categorized under SE. From our perspective, this strategy represents an important advance in defining a more precise SE group. What is important about all these studies is that despite the variable definitions, the SE condition was associated with elevated psychological features and specific behavioral patterns with surprisingly marked consistency. Yet, if our goal here is to try to characterize the condition of SE that differentiates it from normative developmental patterns, then the thresholds previously described might not capture the essence of this eating behavior. Parents of children with SE at the more extreme ends of severity, by definition, would not characterize their children as “sometimes” engaging in SE. For these parents, SE is a daily problem that interferes with meal preparation and potentially the child’s health and well-​being. However, it is also hard for parents to endorse “always” as an item response:  one can always think of the exceptions to a given scenario.

For example, even children with the most limited of diets would consider trying a new type of candy (though never a new type of fruit, vegetable, or protein). These considerations guide our recommendations for future directions in this area.

Conclusions/​Considerations for Severity Threshold

There is a need for sensitivity analyses to determine the threshold of severity associated with impairment. This is discussed further in the next section. In addition, newly developed assessment tools (or adaptations of existing measures) should consider having an option of “almost always/​always” to allow caregivers to endorse a greater frequency of severity while avoiding the challenge of having to endorse a case that has no exceptions (as in the case of endorsing “always”). Future research should compare this more severe group with children who are sometimes selective to see whether these groups are different in kind or degree.

Consideration One:  Defining a Threshold of Selective Eating Severity Definitions of selective eating should use a cutoff of “often” or greater to distinguish children more likely to have persistent problems with this eating pattern. Given the subjective challenge individuals have endorsing an option of “always,” an option that permits “always/​almost always” might permit distinction between clinically meaningful differences in selective eating. Thus, rather, than selective eating being a typical developmental phase, it may be more precise to say that a significant minority are sometimes picky.

Duration

While information on the course of SE is useful in helping us understand the pathophysiology of this eating pattern, defining a necessary duration of SE that might warrant intervention is essential. What is needed is research that can quantify the length of time that an individual of a given age experiences impairment from SE. One of the more robust findings across studies of SE is that picky eating at Time One predicts picky eating at Time Two (Micali, Rask, Olsen, & Skovgaard, 2016): there is increasing evidence that SE can be a persistent condition for a subset of individuals. However, the question

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of duration is one of impairment: How long does SE need to persist for impairment in domains of physical health due to poor nutritional quality or psychosocial functioning to occur? In addition to more obvious concerns about nutritional deficiencies resulting from avoidance of entire food groups, unique forms of impairment are associated with or may result from SE (e.g., family conflict around meals). Of interest, the form impairment takes may differ depending on the age of the individual with SE, and so it is also unclear the duration at each age that the unique age-​specific forms of impairment needs to occur for a parent or individual to endorse their child’s eating as a problem. This is important because any attempt to define a clinical duration ideally would index a length of time that is associated with impairment in function that is developmentally sensitive. Consider the feature of being underweight. Studies of SE in toddlers and young children find that children with SE are more frequently underweight; however, studies of adults with SE have not found this association. This is a rather interesting observation and suggests perhaps that the underweight or lower weight of young SE children is due to parents restricting the quantity of preferred foods (perhaps because they are attempting to increase the variety of the children’s diet with healthier options). From an impairment standpoint, it would seem that consequences due to lower energy stores might not be as consequential once individuals with SE have more control over their food choices. Whether SE causes physical impairment is actually quite controversial. While we address the specific eating patterns of SE below, a repeated finding is that while the energy intake of SE children does not differ from that of their non-​SE peers, the quality of the diet is poor. Thus, while growth trajectories may not be affected, parents, nonetheless, and not inappropriately, worry about their child’s health. This appears to be a point of communication disconnection between parents and providers (Zucker, Copeland, & Egger, 2016). Pediatricians reassure the parent about the child’s continued growth trajectory. The parent worries about the consequences about the lack of certain nutrients from the child’s diet. What is needed are more sensitive boundaries to help parents and healthcare providers determine when lack of food variety has been going on for long enough as to impact health. Chatoor (2002) made the recommendation that if nutritional supplementation is required for the child to receive a diet of adequate nutrition, then impairment is implied. As 422

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we are discussing SE, this would be a child whose dietary quality is such that she/​he/​ze requires vitamin or mineral supplementation for health. One consideration is that if a child is missing an entire food group (which has been documented in several studies), then impairment in this domain is considered. One question related to this suggestion would be, Does the documented avoidance of a food group have to show up on a laboratory test as a vitamin deficiency for child to be considered impaired in terms of their diet quality? On the one hand, it seems illogical to “wait” for a vitamin deficiency to emerge if the parent knows the child is avoiding an entire food group. This would seem to invalidate the necessity of having government recommendations for the dietary composition and quantity needed to sustain health (for example, US Department of Health and Human Services, US Department of Agriculture, 2015). There continues to be much confusion about when to intervene for this condition—​and rightfully so, given broad research gaps. Although it is clear that selective eating is associated with a limited diet and inadequate nutrition, controversy remains in regard to whether or not such nutritional deficiencies can result in stunted growth over time. As mentioned, this chapter attempts to focus on those with SE who are normal or overweight. However, it worth noting that several studies have documented elevated growth faltering or underweight status in those with SE (for example, Tharner et al., 2014; Xue et al., 2015). Conversely, another study discovered that being picky was weakly associated with negative growth among toddlers and lack of diet variety was found to be unrelated to growth (Wright, Parkinson, Shipton, & Drewett, 2007). Significant effects on growth related to SE are inconsistently observed, yet SE is still associated with incomplete diets characterized by insufficient consumption of essential vitamins, minerals, and protein. A final consideration in the domain of physical impairment is that of gastrointestinal symptoms. This has not been consistently addressed, but somatic symptoms were found to be elevated in a third of SE in a study by Micali et al. (2016). However, anecdotally and logically, as evidenced by the foods that selective eaters avoid (whole grains, fruits, vegetables), the lack of dietary fiber and subsequent constipation may be problematic for these children and further impairment. A  recent study by Taylor et al. (Taylor, Northstone, Wernimont, & Emmett, 2016) confirmed this:  These authors

found that hard stools were more frequent in children with SE and this was mediated by the amount of dietary fiber the children consumed. Thus, the fundamental issue in the domain of physical health is whether to wait for a medical test that provides an abnormal value or for the child to fall off a growth curve before impairment in this domain is considered. Given the persistence of SE (discussed later), it would seem this is a very irresponsible strategy. The psychosocial impairment resulting from SE might differ according to the age of the individual. While many young children with SE may not experience impairing social consequences as a result of their eating (perhaps either because their eating choices are not that different from their peers and there are not as many social events that demand eating), yet elevated social anxiety has been documented in preschoolers with severe SE and elevated symptoms of social anxiety in moderate SE (Zucker et  al., 2015). In two studies of adults with SE, both reported elevated levels of social anxiety with increasing SE (Kauer, Pelchat, Rozin, & Zickgraf, 2015; Wildes, Zucker, & Marcus, 2012). This perhaps reflects that the eating choices of individuals with SE becomes increasingly atypical with age and/​or that social events that involve eating become increasingly harder to avoid or manage (for example, business lunches, dating, etc.), challenges not experienced to the same degree by young children with SE. Yet, younger individuals with SE are not completely devoid of psychosocial consequences. One important example of social consequences for children and young adolescents with SE is the effect that this pattern of eating has on family relationships. Increased family conflict and increased parental distress is perhaps the most consistent finding across studies of SE (Mascola et al., 2010; Zucker et al., 2015). This domain of impairment is essential for several reasons. First, SE may negatively impact parent–​child relations. Given pervasive misunderstanding of the etiology and phenomenology of SE, many parents feel guilty for their child’s eating, a feeling propagated by well-​intended but misguided advice from friends and family. Parents themselves, misunderstanding the barriers that make it challenging for their child to be adventurous with food, might interpret their child’s eating as resulting from their “stubborn temperament,” signs of a power struggle, etc. On the other hand, in the context of a healthy feeding dynamic, preparing food and having that meal be appreciated by family is one of

the most fundamental ways of giving and receiving nurturance. In the context of SE, there is a devastating loss of this intimate exchange while the aforementioned misunderstandings may create tension between parent and child. Family meals have been shown to be a broadly protective familial ritual that also may be compromised by SE. A  broad research base has demonstrated that family meals that are frequent and valued by the family as important can be protective of a variety of negative mental health outcomes and high-​risk behaviors (Eisenberg, Olson, Neumark-​ Sztainer, Story, & Bearinger, 2004; Fulkerson et al., 2006). Family meals are an efficient means for a child to gain a broad range of skills: conversational skills, teamwork, and manners are examples. Family meals also help children feel more emotionally connected and valued by family members (Neumark-​ Sztainer, Story, Ackard, Moe, & Perry, 2000). When a family has a child with SE, the lack of empirical research to guide parents in how to approach unpreferred foods may lead to conflict between parent and child, and for the child, to have negative associations with mealtimes in general, not just with the disliked foods. Over time, studies have reported oppositional behavior at mealtimes and attempts to avoid family meals altogether by children with SE, a reflection of ineffective strategies being employed (Mascola et al., 2010). Going back to our question of duration, the issue is how long should each of these impairing consequences (e.g., absence of an entire food group, social avoidance, family conflict) be endured prior to intervention. To our knowledge, only a few studies have examined the issue of persistence over time (Cano et  al., 2015; Mascola et  al., 2010; Micali et al., 2016; Taylor et al., 2015). A caveat in describing the results is that two of the studies employed the cutoff of “sometimes,” while the third required that “often” be endorsed at least once (Mascola et  al., 2010). In the study by Cano et  al. (2015), 4.2% of children age 1½ to 6 were found to have persistent SE across all time points, and these children were found to be at increased risk for the emergence of pervasive developmental disorders. There were no satisfying predictors of persistence using an SE group that included those who sometimes ate selectively, however, of interest, if the researchers had changed the cutoff to five and above (the cutoff consistent with an endorsement of “often” of at least one item), then prevalence at a given time point would range from 3.7% to 6%, a prevalence not unlike other psychiatric disorders. Cano et  al.

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(2015) reported that two-​ thirds of SE remitted within 3  years. Masola et  al. (2010) reported that 47% of their cohort remitted, and that those with SE duration of longer than 2  years demonstrated more severe SE than those who had SE for less than 2  years:  the former group had stronger food preferences and were more likely to refuse new foods. Combined, these studies confirm that SE can last for years and that a substantial percentage do not persistently have SE when consistency is examined over a span of years. Predictors of persistence have been rather elusive. Cano et  al. did not find a reliable predictor. Mascola et al. (2010) reported that picky eating was the most reliable predictor; and Micali et al. (2011) confirmed this latter finding but also identified some maternal mental health variables as potential modifiable risk factors, which are discussed later. Yet, there are further gaps in our understanding of the course of SE. There are virtually no studies of the prevalence of SE in teenagers, and only a few studies in adults.

Conclusion/​Considerations for Duration Threshold

From both the clinical and research perspectives, findings to date on the necessary duration to warrant intervention are challenging to translate. There is not clear evidence to support a sensitive duration of SE since studies to date have examined the question over years, yet impairment has been documented cross-​sectionally. While there is increasing verification that persistent SE beyond three time points is indicative of a worse outcome and may warrant intervention, this information would be small comfort to parents who endorsed an immediate impact of their child’s eating on family relationships. It is not reasonable to tell parents to wait and see if their child’s eating persists for years. Reexamination of data, with higher thresholds for defining severity might lead to more precise predictors of persistence of SE. In the meantime, the limited data available supports 2 years as a duration threshold: A child with SE for longer than 2 years, and according to the Cano data, certainly more than 3  years, would warrant a referral. However, the immediate signs of physical (e.g., hardened stools) and psychosocial (e.g., family relationships) necessitates the development and dissemination via pediatric primary care of interventions that can be disseminated on a broad scale immediately in response to parental concern and signs of impairment in the child. 424

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Consideration Two:  Defining a Threshold for Selective Eating Duration Children who have been persistent selective eaters for more than 2 years might warrant referral. However, the presence of impairment indicates that the level of severity is impacting function and might warrant referral even if the duration does not meet this threshold.

Essential Features

While the essential feature of SE is also probably the least contested, namely, individuals eating a limited variety of foods, it is also the most challenging aspect to define. There has been surprisingly little emphasis on what individuals with SE actually eat and whether the nature or limited variety of the specific foods selected result in physical health consequences. Rather, the research in this area has been criticized as focusing on the opinions of the mother to guide the definition as to whether a child is selective, rather than the behavior of the child. The concern is that individual differences in the mother (e.g., maternal anxiety, eating disorder, or own pickiness) are biasing these judgments rather than the objective behavior of the child. For our purposes, we attempt to focus on the objective behavior of the child to define a threshold of food selectivity for the core feature of SE, and then examine frequently reported behavioral features that might further inform the clinical picture. One option is to use vitamin, mineral, or fiber inadequacy as the benchmark for poor food variety. While energy consumption is also a critical consideration, this chapter attempts to focus on regular to overweight children to define benchmarks. Across studies, the most robust findings are that children designated as having SE (1) consume fewer vegetables, fewer fruits, and protein (particularly less meats and fish) than nonselective eaters; (2) consume lower levels of essential vitamins and minerals, particularly folate, and while more likely to have a nutritional deficiency, in general, the data on the latter is limited and mixed; (3) consume more sweets/​confectionery and savory snacks; (4)  have a total energy intake that is unlikely to differ from typical controls; and (5) and are more likely to have problems with hard stools, constipation, and other gastrointestinal issues, perhaps due to their low dietary fiber. The question is whether the existing literature can be employed to define thresholds of impaired dietary variety.

Indeed, the bulk of evidence supports dietary differences, and there is emerging evidence that such differences have clinical implications. Zimmer et al. (2012) reported that it is significantly more likely for a child with SE to be at risk for at least one critical nutrient deficiency as opposed to an average eater in a sample of children diagnosed with an autism spectrum disorder. In a study that analyzed the eating habits and related factors within a sample of healthy school-​ age Chinese children, researchers Xue et al. (2015) found that selective eaters consumed less energy, protein, and most vitamins and minerals than nonselective eaters; further, selective eaters had lower levels of iron and were lower in height, weight, and BMI for their age. Similarly, as summarized in a comprehensive review, Taylor et al. (2015) report that SE is associated with diets characterized by insufficient consumption of essential vitamins, minerals, and protein. Although overall energy intake tends to vary only slightly between children who are selective eaters and children who are nonselective eaters, it has been reported that selective eaters consume significantly less eggs and cooked and raw vegetables than nonselective eaters (Van der Horst et al., 2016). Notably, these food preferences appear to be rather stable:  14-​month-​old infants who were considered selective eaters demonstrated higher overall intake of savory snacks and sweets and lower intake of fish and vegetables, a pattern similar to older children who are selective eaters (Van der Horst et al., 2016). Such a lack of vegetables in a diet is also associated with a lack of fiber intake, an important observation, given the study by Taylor et al. on hard stools reported previously (2016). Notably, however, the count of the number of foods may not provide much discriminative validity. Jacobi et al. (Jacobi, Agras, Bryson, & Hammer, 2003) reported that while selective eaters were statistically different from nonselective eaters in the number of foods consumed, the means differ by only one food.

Conclusions/​Considerations for Food Variety in Selective Eating

Combined, the evidence indicates that selective eaters have lower dietary quality than nonselective eaters. Thus a tentative suggestion based on evidence is that if the child avoids an entire food group or, as suggested by Chatoor (2002), requires vitamin or mineral supplementation to meet daily requirements, then a threshold of impairment for food variety has been reached.

Consideration Three:  Defining a Threshold for Selective Eating Variety Children who are avoiding entire food groups, who require a vitamin and mineral supplement to meet dietary recommendations, or experience gastrointestinal consequences, such as constipation, may be exhibiting a level of poor food variety that impacts function.

Associated Features

There is rather robust evidence documenting associated behavioral features of individuals with SE. Among these, the fear of trying new foods, decided preferences about foods (both likes and dislikes), the tendency to gag when presented with a new food, and conflict over foods are the most reliably reported. Pace of eating has also been reported in several studies and is a particularly interesting feature that will consider from a behavioral standpoint. Each of these features is briefly discussed in turn. Food Neophobia Food neophobia, the fear of trying new foods, is robustly documented among selective eaters. However, it is important to note that this avoidance might not be observed across all food groups and, critically, might not be driven by fear. For instance, some children who avoid fruits, vegetables, and most proteins will be willing to try novel sweets/​confectionaries provided that the sweets do not contain fillings or fruit flavors. When queried about this avoidance, children often do not report that they are afraid something bad will happen if they eat it, they report finding the taste disgusting, report being likely to gag upon tasting a novel food that they find disgusting, or report with certainty that they will find the taste disgusting. Viewed from an anxiety lens, one could consider this a “fear of gagging.” However, one of the many interesting things about SE is the frequency with which gagging actually occurs when presented a novel or unpreferred food. Thus, gagging is not a low probability event and the expectation of gagging is not an irrational belief, features often reported to characterize fears in phobias (e.g., fear of flying in anticipation of a plane crash). This is a critical, often overlooked, feature of SE that is essential to understand the phenomenology of this condition. Thus, we return to this point when we discuss the phenomenology of SE.

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Decided Preferences Children labeled as selective eaters know what they like. Parents report loyalty to food brands to such a degree that anecdotally, parents report writing to food companies when preferred products are discontinued for fear that they will not be able to find a suitable replacement for a discontinued item. Also anecdotal (but interesting), is that these children have very “good taste.” If these children say that a particular French fry is a good tasting French fry (and better than other French fries), it probably is. Parents describe these children as very sensitive to the visual imperfections of food, rejecting even a previously liked food if its appearance differs from that of a prior presentation. This behavioral pattern bears some resemblance to features of other psychiatric disorders such as the “need for sameness” in autism spectrum disorders or the “just right” phenomena in obsessive-​compulsive disorder. We discuss the relevant aspects of the experience of each of these features in our section on the phenomenology of SE. Food Refusal/​Conflict Around Food Individuals with SE refuse to eat unpreferred or unfamiliar foods even in contexts in which such refusal has social or emotional consequences; those with SE cannot override their distaste of unknown foods to “get by” in a challenging or novel social circumstance. This is notable, as individuals without SE may suffer through an unpleasant meal if refusing would hurt the feelings of the host, if they are hungry enough, or if there are other interoceptive or contextual motivations. Those with SE seem impervious to these motivations, and it is informative to consider some hypotheses as to why this is the case. One hypothesis is that the sensory aversion experienced from these foods makes it challenging or seemingly impossible to attempt to taste novel foods without further social embarrassment or insulting the host (due to vomiting gagging, etc.). Alternatively, or in addition, individuals with SE might struggle with deficits in theory of mind, implying that they might not appreciate the social consequences or impact of their behavior on others, and thus this does not serve as a potent source of motivation to alter eating habits. There is virtually no data to inform either of these hypotheses. A final important consideration regarding the presence of food conflict is the implication that parents are not merely acquiescing to the children’s demands for food types (Zucker et al., 2015). This is 426

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a critical consideration: Numerous studies examining the emergence of healthy eating behaviors in children site parent modeling of healthy eating and the number of presentations of novel foods as contributory to a child’s subsequent SE. Importantly, this work has never been conducted in children precisely categorized as selective eaters, and whether the same strategies work, whether the strategies would work but with significantly longer durations, or whether novel strategies are needed, is currently unknown. In the meantime, parents are being blamed for not doing enough when they have no guidance as to what they should be doing. As conflict is an interpersonal feature, and thus not a feature of the individual, we label this feature in terms of the child’s presentation, that of food refusal. Slowness in Eating A slowed pace of eating has been described (Tharner et  al., 2014). This is a particularly interesting feature, as the motivations or etiology that contributes to a slowed eating pace might help contribute to more personalized treatment approaches. Further, the amelioration of this symptom would most likely be of great relief to parents, as the time taken for meal completion may be an added complication with managing a child with SE. Two diverging hypotheses about the origin of slowness in eating might contribute to very different conceptualizations about the nature of SE. One hypothesis is that slowness in eating is due to delays or atypicalities in oral-​motor development that makes it challenging to chew and swallow food. Of interest, a study by Jacobi et  al. (2003) examined the early eating/​feeding behavior of children who were classified as selective eaters at the age of 8. Examining data collected in infancy, these authors reported the sucking behavior of children later classified as selective eaters was weaker than that of typically developing children. Such early vulnerabilities in oral-​motor development might be further compromised by the food types selected by children with SE. Processed foods combined with lower (or absent) levels of fruits, vegetables, and proteins suggest that these children opt for foods that are easier to chew and swallow. Thus, over time, this food selection may further impede the development of oral-​motor strength and coordination. Data on this hypothesis is limited, although there is some evidence supporting that more severe SE is associated with oral-​motor difficulties (Zucker et al., 2015).

A second hypothesis regarding slowness in eating is that is it a behavioral strategy that children have learned as a way to avoid eating. By prolonging a meal, children may have been negatively reinforced by receiving permission to leave the family table early. Thus, behavioral management strategies would be necessary in this latter instance, while work with an occupational or speech therapist might be required in the prior instance. However, given the limited data in support of this feature, we do not include it in our associated features until further data is available.

Consideration Four: Defining Associated Features Individuals with SE engage in one or more of the following either most of the time or all of the time: 1.  food neophobia, 2.  decided food preferences, and/​or 3.  refusal of foods offered by others.

The Phenomenology of Selective Eating Sensory Sensitivities, and Disgust Experience

To understand the experience of individuals with SE, we argue that the role of anxiety has been overemphasized and that the interacting roles of sensory sensitivities and disgust experience have been neglected. To address this gap, we discuss the nature of disgust experience and why this experience may be relevant for SE, discuss how disgust experience explains the puzzling behaviors of SE, examine current limitations in the measurement of disgust for this group, hypothesize some potential contributions to enhanced disgust experience, and finally, describe implications of disgust for intervention. According to Curtis (2011), disgust is an adaptive emotional and behavioral system designed to protect the organism from infection by pathogens. Pathogens are often impossible for humans to detect directly (individuals do not usually see bacteria). Thus, the disgust system is sensitive to local signals that signify potential harm from contamination (e.g., feelings of nausea, smells, feelings of malaise). Of great interest, immune responses are up-​regulated in accordance with disgust experiences or likewise when the organism is vulnerable (as during pregnancy or, putatively, starvation) (Cloutier,

Kavaliers, & Ossenkopp, 2016; Stevenson, Case, & Oaten, 2011; Stevenson et al., 2012; Zelazniewicz, & Pawlowski, 2015). The associated experiences of disgust that accompany these elevated immune responses are thought to further protect the organism from harm due to infection. The adaptiveness and sensitiveness of the system implies that experiences of malaise up-​regulate immune responses and disgust sensitivity, which increases vulnerability to the experience of malaise. Indeed, the core features of the disgust experience are nausea, gagging, and changes in facial musculature that restrict access to nasal and oral entries. As disease or infection occurs after a body boundary has been crossed, eating is rather unique among human behaviors as being one of the few in which crossing a body boundary is necessary. Thus, the experience of disgust when one encounters spoiled foods is familiar. We argue that individuals with SE have a lower threshold for disgust experience that contributes to food avoidance. What is notable about SE is that they have an intense disgust reaction (example, gagging) to foods that are unfamiliar but that do not obviously signal the threat of contamination. In contrast, there are universal domains of disgust elicitors that reliably produce disgust experiences (e.g., feces, vomit, urine). It is further thought that other higher-​order disgust elicitors, particularly those labeled as moral disgust (e.g., incest), are potentially the result of second-​order conditioning due to the association of immoral acts with bodily products. In contrast, the disgust elicitors in SE might not be captured by current measures of disgust sensitivity, as these elicitors do not generate disgust in the general population. This was our own experience when applying a widely used disgust sensitivity scale (the Disgust Scale-​Revised; Olatunji et al., 2007) to a group of adults who self-​identified as selective eaters. While degree of SE severity was associated with increased frequency of gagging and the subjective experience of disgust as indexed by items directly assessing their experience of disgust (Figure 22.1b and 22.1c), the classic measure of disgust sensitivity was unable to discriminate between groups (Figure 22.1a). To clarify, while all groups with SE differed from the group with only slight SE, a widely used measure of disgust sensitivity cannot discriminate among these groups (Figure 22.1). Thus, there may be need for the development of measures that capture the experience of disgust with disgust elicitors of a lower threshold of pathogen severity (e.g., broccoli).

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(a)

Mean of Average Disgust Scale-Revised

b

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Less than half About half More than half the time the time the time

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Disgusted by new foods (1-Never to 5-Always)

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Gagging when trying new foods (1 Rarely to 5 Always)

4.00 c 3.50 3.00 b 2.50 a 2.00 a 1.50

a

1.00 Rarely or never

Less than half About half More than half the time the time the time

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Severity of Selective Eating

Figure 22.1  Disgust experience in selective eating in a sample of 999 adults who completed a Web-​based survey of food selectivity. 1a. Average scores on the Disgust-​Scale Revised discriminated between adults who were rarely or never selective, but not adults who ranged from less than half the time to all the time in degree of food selectivity. 1b. An item that asked adults whether they experience disgust when trying a new food resulted in significant differences in degree of food selectivity between all but the group of rarely/​ never and less than half the time. Different letters indicate significant differences between groups (p < .001). 1c. Frequency of gagging similarly discriminated between severity of selective eating, discriminating the two most severe groups (more than half the time/​ always) from each other and from lower frequency of selective eating. 

Otherwise, we may miss a potentially essential feature in the phenomenology of SE and not have precise ways to measure it.

Contributions To Disgust Experience: Sensory Sensitivities

Disgust sensitivity has been conceptualized as a trait feature that evidences individual variability. What is interesting about disgust, when conceptualized as a system for pathogen avoidance, is that certain developmental stages and life events up-​ regulate immune responses, and associated disgust experience, that may become more exaggerated, depending on one’s initial predilection to baseline disgust experience. In the context of SE, individual vulnerabilities that may be particularly germane to the enhancement of disgust experience are exteroceptive sensory sensitivities, particularly sensitivity to taste, texture, and smell. Once an individual has been infected with the pathogen, it is too late. Thus, organisms have developed refined systems to detect warnings of possible pathogen infection, such as visual cues and smells. It thus stands to reason that individuals with heightened visual acuity, with a visual system that biases details rather than global organizing frameworks, or with extreme sensitivity to smells might be vulnerable to enhanced disgust experience such that these individuals are more likely to notice visual flaws in foods or find a broader range of smells to be aversive (Figure 22.2). Individuals who are interoceptively sensitive may also be more likely to have enhanced disgust experience due to their greater sensitivity to the gut motility inherent in feelings of nausea, an aspect of disgust experience. Notably, some daily occurrences of a selective eater might worsen the experience of disgust. Anecdotally, selective eaters report often skipping lunch at school. Hypotheses about such avoidance include the potential embarrassment of eating the same lunch day after day and/​or because they might be overwhelmed by the visual cues and smells of other people’s lunches. As a result, they might go for long periods of time without eating. An interesting side note in relation to prolonged food avoidance and disgust experience is that smells might become potentiated in a state of hunger, a sensory alternation that would be adaptive in typically developing individuals: The enhanced smells of delicious foods might increase the likelihood of food consumption. In the context of SE, however, such enhanced smell intensity might further decrease the appeal of eating, resulting in a seemingly

contradictory context in which hunger can promote increased food avoidance or food rigidity. While some authors have posited that it is sensory sensitivity combined with particular temperament proclivities (such as harm avoidance) that promotes avoidance, it is also possible that the sheer intensity of a stimulus makes it aversive for the majority of individuals (e.g., a very loud noise). Thus interoceptive and exteroceptive sensitivity might be independent vulnerability factors that increase the intensity of experienced disgust. Sensitivity to exteroceptive sensory experiences (e.g., touch, taste, smell, texture) has been increasingly documented as an associated feature of SE (Blissett, & Fogel, 2013; Chatoor, 2002; Farrow & Coulthard, 2012; Kauer et al., 2015). This association is reported across the lifespan:  adults designated as selective eaters endorsed greater sensitivity to smell and texture (Wildes et  al., 2012), while another study of adults reported higher rates of rejection of foods that were “slimy or slippery” in texture, or that had been mixed or had “lumps” (Kauer et  al., 2015). Notably, this same study showed that picky eaters were higher in disgust sensitivity than nonpicky eaters (Kauer et  al., 2015). Yet the origins of these sensory aversions are poorly understood. There is accumulating evidence regarding the role of genetic variation in contributing to the intensity of taste experiences (Tepper, 2008). Individual variation in the density of tongue papillae, number of taste receptors, and genetic polymorphisms implicated in specific taste experience have all been explored as contributing to this variation in experienced taste intensity (de Krom, Bauer, Collier, Adan, & la Fleur, 2009). Among these, the “bitter gene” is perhaps the most commonly studied: studies have investigated the heritability of phenylthiocarbamide (PTC) and 6-​ n-​ propylthiouracil (PROP). Individuals that experience a bitter taste when given PTC and PROP are regarded as “super-​tasters,” indicating a heightened sensitivity to this flavor profile. A  majority of these super-​tasters have polymorphisms in the gene TAS2R38 (Tepper, 2008). To date, links between variation in genetic polymorphisms for taste sensation and SE are limited. However, in a condition that is so vastly misunderstood and for which parenting is, to date, unduly implicated, such findings of individual differences in taste experience are important to help paint a more complex picture of the phenomenology and etiology of SE.

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Enhanced sensitivity to events that affect visceral or sensory experiences (GERD, allergies, constipation) Emotional Experience (disgust) Enhanced Interoceptive Perception (gut motility) Hunger Enhanced Exteroceptive Sensory Perception (taste, smell texture, visual features)

Deficits in executive attention

Behavioral Response (e.g., gagging)

Avoidance of social eating

Decreased presentation of new foods by sensitive social environment

Novelty enhancing sensory experiences? Figure 22.2  A putative model of selective eating. Enhanced sensitivity to interoceptive and exteroceptive sensory experiences act as vulnerabilities to enhanced disgust experiences. Given the aversive social consequences of disgust sensitivity (e.g., gagging), these individual differences may make social eating more aversive, leading to further social avoidance. Behavioral features such as meal skipping and deficits in executive attention may further potentiate these pathways. Meanwhile, avoidance and the subsequent novelty of a broad range of foodstuffs may further increase aversive sensory experiences. 

Sensory Sensitivity and the Potentiation of Emotional Experience

Sensory sensitivities might contribute to the potentiation of emotional experiences more broadly. For example, sensory sensitivity might contribute to findings of elevated anxiety and SE (Farrow, & Coulthard, 2012). Researchers found that both anxiety and sensory sensitivity are associated with picky eating. Furthermore, child sensory sensitivity fully mediates the connection between anxiety and SE, suggesting that it is greater sensitivity to sensory information that explains why more anxious children are more likely to become selective eaters.

Medical Conditions and Sensory Sensitivity

Such sensitivity to interoceptive or exteroceptive experiences might further potentiate the effects of medical conditions that have been associated with SE, as the symptoms of these conditions may be experienced more potently. To date, the domain of gastrointestinal symptoms has been the most frequently investigated. More specifically, 430

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gastroesophageal reflux (GERD) has been reported in SE, though it is unclear whether this condition is more prevalent in those with SE (Seema & Aceves, 2016; Williams, Gibbons, & Schreck, 2005). One study of selective eaters found that 22% of the children had GERD, which is fairly high in such a young population (Williams et  al., 2005). Speculation about the connection between GERD and selective eating has to do with conditioned aversions to eating the particular foods that cause reflux. This similar conditioned aversion may also be at play in children who have had allergic reactions to certain foods. Many times, allergic reactions are associated with vomiting, diarrhea, and/​or abdominal pain, which might cause conditioned aversions to certain foods (Williams et  al., 2005). One of the significant issues in regard to allergies is that, often, food allergies in young children are overlooked by pediatricians, especially when the symptoms are internalized (silent reflux, abdominal pain, etc.), as opposed to externalized (vomiting, diarrhea, etc.) (Chatoor, 2002). The GERD symptoms might also be associated with eosinophilic esophagitis in SE and can

be complicated with allergic reactions (Spergel & Shuker, 2008). When considered against the backdrop of our model of sensory sensitivity, the addition of these medical conditions implies two factors that may be essential for stronger conditioned aversions to foods. First, sensory sensitive individuals might experience the medical consequences associated with gastrointestinal issues or allergic reactions more potently. Second, their sensory sensitivity might lead to broader generalization curves to a range of sensory features that are imperceptible to individuals with less sensory sensitivity. None of these hypotheses has, of yet, been tested.

Executive Functioning and Sensory Sensitivity

Deficits in executive functioning might further augment disgust experience. In a study by Zucker et al. (2015), one unexpected finding was that moderate levels of SE were associated with an increased frequency of the symptoms of ADHD. One hypothesis is that problems with shifting attention might make it challenging to regulate aversive sensory experiences so that these experiences become intensified. However, to date, there are no studies of neuropsychological function in individuals with SE. Compared to other related psychological features of selective eating, ADHD has been one of the least studied. Two studies in this area are notable. Pennell et al. (Pennell, Couturier, Grant, & Johnson, 2016) reported on two cases of young patients diagnosed concurrently with avoidant/​restrictive food intake disorder (ARFID) and attention deficit hyperactivity disorder (ADHD). These patients had to take stimulant medication, which posed a significant growth restriction. The appetite suppressant effect of stimulants exacerbated long-​standing SE behaviors. This demonstrates that although SE may not cause elevated levels of ADHD and vice versa, the two might be correlated or both might be caused by another factor. Also, it was noted that symptoms of ADHD, such as not being able to sit still for long or to focus on something to complete a given task, made it harder for SE to respond to treatment. The second research study examined a nationally representative community-​based sample. The researchers had conflicting findings to those described previously, demonstrating that ADHD symptoms were associated with binging and/​or purging behaviors, but were not related to picky or restrictive eating patterns (Bleck & DeBate, 2013). More studies are required to make any conclusions on this relationship.

Consequences of Disgust Experience: A Sensitized Social Environment

A sensitive social environment may unintentionally augment this avoidance. As noted in the classic writings on the function of emotional experience by Darwin (1872), the primary function of emotion is that of social communication. Perhaps this function is most relevant for the emotion of disgust, as the avoidance of pathogens is a group-​ level behavior as manifested in hygiene behaviors (e.g., washing hands, covering one’s mouth when sick). Thus, noticing signs of disgust from others is critical in avoiding pathogens that could impact the group. It is perhaps for this reason that individuals engage in some seemingly odd social behaviors surrounding the experience of disgust: They attempt to share that experience. “Smell this” is a rather common refrain when one encounters a disgusting stimulus: a reaction that one is unlikely to have when one views something scary or anger provoking. The take-​home point is that we notice expressions of disgust, particularly when such expressions are severe, resulting in gagging or vomiting on the part of the individual. This is critical to consider when incorporating the role of parents, either when implicated as contributions to SE or as necessary agents of change. In this chapter, we argue that parents have been unduly maligned as the role of disgust and sensory sensitivity has not been adequately incorporated, and further, that research on parent modeling, and so on, has not been conducted with a well-​defined group of selective eaters. A child who gags or vomits following the presentation of a new food would generate cautious behavior on the part of any sensitive parent. Yet, given the essential role that parents play on the establishment of eating habits and preferences in young children—​via provision of access to foods, feeding styles, reinforcement of child eating behaviors, and role modeling of their own eating—​while it is understandable that parental influences would be implicated in the emergence and/​or maintenance of SE, it is our contention that this claim is, at best, unfounded, and, at worst, unjust. Yet, despite the potential potency of child factors eliciting parent feeding behaviors, the focus on research and on lay publications regarding SE has been to implicate parents for not presenting foods enough times or in fun enough ways. This is despite a lack of evidence demonstrating whether more frequent presentation of a food results in food

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acceptance, let  alone liking, in SE. Consider the study by Wardle, Carnell, and Cook (2005). In a sample of 500 typically developing preschoolers in London, these authors reported that fruit and vegetable consumption by children was better explained by the child’s food neophobia than any parent feeding style. Another interesting study was conducted by Harris et al. (Harris, Fildes, Mallan, & Llewellyn, 2016), in which the authors investigated whether the feeding style of parents differed between monozygotic twins who were described as different in the level of food neophobia. Despite being reared in the same home environment, the parents describe very different feeding styles for these children depending on their eating presentation. In fact, not only has research on the number of presentations of a food needed to promote acceptance been conducted in typically developing children, but even this research has been limited. The frequently cited number of 10 to 15 presentations was conducted with typically developing children, and it was unclear the degree to which acceptance of a food differs from liking or voluntarily seeking that food. Combined, this research has very important messages for parents of a child with SE, the primary message being that we really do not have adequate research to guide the number presentations for food acceptance for SE and, second, that parents may have been unduly blamed for their child’s food selectivity.

Disgust and Evaluative Conditioning

The issue of the number of food presentations is particularly relevant if disgust experience is essential

to the phenomenology of SE. As previously mentioned, research on SE has focused on the role of anxiety in contributing to food avoidance. This is important because this emphasis may have led to inappropriate, or at least imprecise, guidance about the management of SE. In Figure 22.3 below, we present some preliminary data in a sample of 4,000 adults with SE defined as described earlier (SE all the time and occurring since childhood) on the relative role of anxiety relative to disgust in exploring associations with food avoidance. When we controlled for the effects of anxiety, associations of texture, smell, and gagging were all significantly associated with disgust with effect sizes ranged from small to medium. When the reverse analyses were done, examining the role of anxiety controlling for disgust, associations of food avoidance to smell, texture, and gagging were in the negligible to small effect size ranges. While these analyses are exploratory, they point to the putative importance of disgust experience in explaining many impairing features of SE. These exploratory findings also have putative importance for the treatment or management of SE. There are numerous empirically validated treatments for the management of anxiety disorders, in general, and specific phobias, in particular. In fact, individuals who practice behavior therapies or cognitively emphasized behavior therapies have developed exceedingly robust methods to help individuals with specific phobias learn to approach their fears and reduce their fear of stimuli that used to be

Disgust AND anxiety in SE 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0

Associations with Disgust*

Smell

Texture

*Controlling for Anxiety

Gagging

0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0

Associations with Anxiety&

Smell

&Controlling

Texture

Gagging

for Disgust

Figure 22.3  An exploratory analysis of 4,000 adults with selective eating of various severity that completed a Web-​based survey. When controlling for anxiety, disgust was significantly associated with gagging, and taste and smell sensitivities with moderate or large effect sizes. When the reverse analysis was done, anxiety was statistically or clinically insignificantly associated with gagging or sensory sensitivities. 

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fear provoking. In contrast, there are no empirically validated treatments for the management of disgust. The most robustly effective treatment for the management of specific phobias is exposure and response prevention. This classic behavioral treatment is based on fundamental learning principles such as classical conditioning. In the theoretical model that guides the development of this treatment, it is demonstrated that inherently fearful stimuli (the unconditioned stimulus such as a dog bite) becomes associated with neutral or harmless stimuli (the conditioned stimulus, a friendly, toothless dog). The friendly dog becomes reliably associated with the unconditioned stimulus, the biting, such that the sight of (or even the anticipation of ) the friendly dog elicits fear and avoidance behaviors such as refusal to visit homes or locales where a dog may be present. The focus of treatment is on creating new learning experiences that establish competing associations with the toothless, friendly dog. Frequent encounters with the friendly dog without any associated negative consequences create a new experience, the memory of which now competes for recollection with the original memory of dogs as harmful, a process that has been referred to as inhibitory learning (Craske, Treanor, Conway, Zbozinek, & Vervliet, 2014). Disgust in contrast, is considered a form of evaluative conditioning:  Individuals make judgments about whether things are liked or disliked, good or bad. Evaluative processes are thought to be more resistant to new learning (or, in the parlay of former learning models, to extinction). Consider a coworker whom you find irritating. According to an exposure model, frequent encounters with this individual would provide opportunities for new learning to occur that would compete with your conceptualization of this person as irritating. Yet exposure in the context of anxiety is built around the assumption that the beliefs are irrational, or, at least, of a low probability and thus disconfirming experiences can be encountered. However, in the case of evaluative conditioning, we are focused on altering an evaluation that can be construed as a high-​probability event (i.e., there is a high probability that you will find your coworker irritating) and repeated experiences might not only not provide disconfirming evidence, but might actually worsen your original conceptualization (with repeated encounters, your coworker might become increasingly more annoying). This description actually fits the anecdotal descriptions of selective eaters who have been “made” to eat foods by their parents. Not

only are these foods not a part of the regular diet of a formerly exposed selective eater, but these selective eaters report having a particularly strong loathing of these foods as a product of that aversive conditioning experience. Recontextualization has been considered an alternative in the approach to disgust:  meaning literally, “to place (as a literary or artistic work) in a different context,” as sensations, specifically, and emotions, more broadly, take on alternative meanings depending on the context in which they experienced (for example, a pounding heart in the context of running a race may be a part of a very different experience than a pounding heart in the context of an academic test). In applying this logic to the experience of disgust, two examples are salient. For example, parents have to interact with lots of disgust-​eliciting stimuli in the service of caring and loving for their child (changing diapers, cleaning up vomit or urine, wiping noses, etc.). After hundreds of exposures (at least to feces), if we asked the parent how she or he evaluated feces, most probably the answer would be “disgusting.” However, whether or not the feces are disgusting is irrelevant. This is an act performed in the service of something much greater and more meaningful, that of loving and caring for one’s child. Thus, this raises the intriguing possibility that the technology of values clarification and value-​guided action might have a particularly salient place for the management of SE. We return to this topic again when we talk about treatment. If disgust is an essential component to the experience of those with SE, then prior work suggesting that SE is caused by limited exposure to new foods might be misguided. It is important to note that there has been very little research investigating the number of presentations it takes for typically developing child to accept a new food, even less known about the number presentations for typically developing child to like a new food, and finally, to our knowledge, no studies that addressed this question in children, precisely defined with SE. First, as noted, given the problems with definition cited earlier, it is unknown whether strategies that seem to be effective for typically developing children will generalize to children with SE. It might be the case that given the experience of disgust, a larger number of presentations are needed, or, as suggested earlier, it might be that the manner or process of presentation is the relevant factor rather than frequency in managing disgust—​or, more likely, that both are essential.

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Second, there has been scant research that distinguishes between acceptance of a food and preference for that food. This distinction might be particularly critical for those with SE, whose choices seem to be constrained to foods that are “the best” of a category rather than just “good enough.” Thus, in our clinical experience, altering a child with SE’s willingness to taste a new food is a very different process from the ability to incorporate that food into the child’s daily eating routine. Research distinguishing these processes in SE has not been conducted.

The Management of Selective Eating

Our narrative about the phenomenology of SE guides our tentative recommendations for treatment elements of SE. We consider four domains: medical assessment, the family meal environment, values clarification, and mindfulness-​based sensory-​guided food exposure. We employ the context of “Food Scientists” to capitalize on the “sensory superpowers” of these children, and use that framework to engage in mindful interactions with food itself, and in the social context that surround the act of eating.

Medical Management

As mentioned earlier, pediatricians and general practitioners are in a tough spot when it comes to the management of SE. Given the imprecise definitions, high prevalence associated with this imprecision, and lack of treatment guidelines, pediatricians do not have any resources. Often, the appropriate focus is minimizing parent anxiety and avoiding unnecessary medical expenditures by conducting uninformative tests (Kerzner et  al., 2015). Satter (2000) provides an excellent framework to guide therapeutic decisions in primary care for feeding disorders, so we do not belabor those points here. However, we note that, clinically, we have observed undiagnosed allergies, anemia, and food intolerances that greatly advanced our management of subsequent eating problems. Thus, if the child has been always/​ almost always selective, particularly if the duration is above 2  years, then a discussion with one’s physician about such medical rule-​outs is appropriate.

Mealtime Environment: Behavior

Given the protective nature of family meals, one of the first objectives of management of SE is to restore the sanctity of family meals. In contrast to folklore recommendations of making the child “take a bite of a new food in order to leave the table,” we do not advise using family meals as a time for food 434

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adventures that involve tasting foods (i.e., the trying of new foods). Our reasoning is that the anticipation of a disgust experience (as when the child tastes the new food), would lead to aversive conditioning of family mealtimes and further detract from the potential joys of social meals. Rather, the initial focus of family meals is increasing the frequency of these eating occasions. Then, more subtle aspects of food exposures (e.g., the sight and smells of foods) can occur combined with the other advantages of social meals (manners, social skills, communication skills, etc.). This strategy also alleviates the guilt of parents who may feel pressured into trying to get their child to eat a new food when the opportunity arises. Table 22.1 lists the eventual goals of a family meal. The goal is one of recontextualizing the family mealtime environment so that eating is occurring in a context of relaxed acceptance of whatever eating behavior unfolds. Parents are helped to shape positive mealtime behavior by looking for small instances of adaptive social eating. However, there may be many preliminary steps to get to this point. For example, the smells of others’ foods may be so aversive, that initial work with the child is needed that employs our metaphor of the Food Scientist. Within this framework we may investigate the sensory habituation of smells (objectively describing how the intensity of smells changes or fluctuates over time). It is important to note that these and all other exposure experiences are conducted from an acceptance framework, meaning that the goal of these exposures is not to terminate an experience or demonstrate that something is better or worse than one anticipated, but rather to have an experience and not let the nature

Table 22.1  Guidelines for Conducting Family Meals when a Child is a Selective Eater • The SE is not expected to try new foods at mealtimes • The SE is expected to join the family at dinner and to remain at the table until everyone is finished. • If the SE does initiate trying a new food at a mealtime, he earns bonus points. • The SE is served a very small portion of the same foods as the other family members on a separate small plate. • The SE is not expected to try new foods at mealtimes

of that experience interfere with things that are meaningful and to use it as a way for individuals to learn more about themselves. One adopts a nonevaluative descriptive frame to increase the vividness of experiences and learn something about oneself and one’s body. Exposures are experiences to increase self-​knowledge and increase the approach in a valued life direction. The only caveat to these recommendations is that we try to help family members avoid providing any feedback during the meal itself. In this way, the focus is on the social aspects of the meal and the meal environment does not increase the selective eater’s self-​consciousness around eating. These strategies are all intended to change the context of meals so these events are experienced as pressure-​ free, engaging, and vitality-​ enhancing events in which families spend time together—​not events to consume one’s vegetables.

Mealtime Environment: Food

Yet, individuals do eat at family meals and knowing what to serve is of paramount importance to families trying to assist a selective eater. In this regard, we respect and adhere to tenets espoused by Ellen Satter in her trust model and use of division of responsibility, with some slight modifications (Satter, 2000). According to this model, parents are in charge of establishing a mealtime schedule, deciding what foods to serve, and preparing appropriate meals. Satter advises parents to ensure that at least one item that is served is “safe” for everyone. Thus, while everyone’s plate might look different, each plate is composed of at least one of the same elements. We adhere to the spirit of these instructions, following the tenets of the division of responsibility, ensuring that one item that is safe for everyone is served, but we give parents’ permission to “short-​order cook” menu items when nutritional deficiencies are an issue. Meals are thus a combination of challenging foods and safe foods including an item that is safe for everyone.

Values Clarification in Selective Eating

Given fundamental differences in evaluative versus fear conditioning, an essential aspect of intervention is helping individuals with SE to define those vital aspects of their imaginable or desired experience that would make engaging in really challenging activities (i.e., trying potentially aversive foods) worth it. Value-​guided action is an increasingly essential aspect of so-​ called third-​generation behavioral approaches to mental

illness. As such, the technologies to help individuals become emotionally connected to deeply felt aspirations are evolving. As one can imagine, this task is eminently more challenging for children and adolescents, whose capacity to think abstractly and ability to be influenced by future events is only beginning to develop. Yet, in our work, having individuals describe and be validated for the journey and to dignify the hard work they are about to undertake has been a seemingly vital aspect of the treatment package. Without this, the child is merely trying aversive foods. With it, they are pushing through a challenge to attain greatness. We employ all the usual suspects in this regard:  imagery; creating pie charts, the slices of which define the components of their self-​ definition; using proximal behavioral goals and rewards that are steps on this valued path. All of this, of course, needs empirical support. In the meantime, we find that children feel understood and more willing to do challenging things.

Sensory-​Based Exposures

An essential aspect of therapeutic eating experiences for selective eaters is that the relative evaluation of the food, whether it is liked or disliked, is irrelevant. Rather, the goal is to encourage the individuals with SE to employ their sensory acuity to notice all aspects of a food without judgment or bias. The goal for a food adventure can sometimes be just that:  to have a novel food experience and notice mindfully (present-​focused, objective/​nonjudgmental, one-​ mindfully) the sensory aspects of food stimuli. An added framework given our guiding metaphor of a Food Scientist, is that of observing the result of a manipulation, investigating which brand is the saltiest, and so forth. The goal of these exercises is to have a hypothesis and to investigate it; however, the contextual goal is to use the extended metaphor of scientific exploration to create a context of curiosity and objectivity around food investigations. These investigations are done in-​ session, with homework to practice the same food investigations at home. To facilitate generalization, at-​home practices can be facilitated via video-​ phone interfaces or home-​based sessions.

Growing Out of Selective Eating

In the research reviewed earlier, we offered some definitions that may help to define a group of selective eaters who do not “grow out of” this condition but rather persist in this pattern of eating over years. This raises an interesting question:  How do

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individuals grow out of SE? While there has been an absence of reliable predictors of persistence, our conceptualization about the phenomenology of SE may offer some potential hypotheses about this remittance and persistence. One hypothesis is that children who are mild or moderate selective eaters eventually undergo developmental changes in sensory experience that permit both the introduction of novel foods and increased preferences for a broader range of foodstuffs. An alternative (or complementary hypothesis) is that through the course of their development, individuals with mild or moderate SE encounter facets of their life experience that make it meaningful for them to endure aversive sensory experiences in the service of more meaningful life goals (e.g., as in the case of the nurse enduring the smell of gangrene to care for a patient). This change in framework allows greater sampling of foodstuffs and thus greater probabilities that foods will be discovered that are preferred. What are the barriers in severe SE? We offer two hypotheses for this. First, it could be that the sensory experiences and resulting disgust experience are so potent that it is more challenging or seemingly insurmountable to overcome, even in the service of valued life activities. Alternatively, or intriguingly, there could be fundamental deficits in the rewarding value of alternative sources of reinforcement, such that finding activities that are rewarding enough to compete with these aversive experiences is challenging. Exploring these barriers will be a fascinating avenue of research.

Summary

This chapter has conceptualized SE as a clinical condition. From this framework, existing research needs to be reevaluated by examining the extremes, exploring predictors of SE persistence, and examining how sensory sensitivity and neurocognitive functioning might explain persistence of SE. It is our intention with this chapter to spur novel conceptualizations of this condition that might promote less blaming of the social environment and increased appreciation for the complex biology that promotes protection of an organism in the face of unknown and unseen pathogens.

References

Bleck, J., & DeBate, R. D. (2013). Exploring the co-​morbidity of attention-​deficit/​hyperactivity disorder with eating disorders and disordered eating behaviors in a nationally representative community-​based sample. Eating Behaviors, 14, 390–​393.

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Selective Eating

Blissett, J., & Fogel, A. (2013). Intrinsic and extrinsic influences on children’s acceptance of new foods. Physiology & Behavior, 121, 89–​95. Cano, S. C., Tiemeier, H., Van Hoeken, D., Tharner, A., Jaddoe, V. W. V., Hofman, A.,  . . .  Hoek, H. W. (2015). Trajectories of picky eating during childhood:  A  general population study. International Journal of Eating Disorders, 48, 570–​579. Carruth, B. R., Ziegler, P. J., Gordon, A., & Barr, S. I. (2004). Prevalence of picky eaters among infants and toddlers and their caregivers’ decisions about offering a new food. Joural of the American Dietetic Association, 104, S57–​S64. Chatoor, I. M. (2002). Feeding disorders in infants and toddlers: Diagnosis and treatment. Child and adolescent psychiatric clinics of North America, 11(2), 163–​183. Cloutier, C. J., Kavaliers, M., & Ossenkopp, K. P. (2016). Rodent sex differences in disgust behaviors (anticipatory nausea) conditioned to a context associated with the effects of the toxin LiCl:  Inhibition of conditioning following immune stimulation with lipopolysaccharide. Pharmacology, Biochemistry, and Behavior. Craske, M. G., Treanor, M., Conway, C. C., Zbozinek, T., & Vervliet, B. (2014). Maximizing exposure therapy: An inhibitory learning approach. Behaviour Research and Therapy, 58, 10–​23. Curtis, V. (2011). Why disgust matters. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences, 366, 3478–​3490. Darwin, C. R. (1872). The expression of the emotions in man and animals (1st ed.). London: John Murray. de Krom, M., Bauer, F., Collier, D., Adan, R. A., & la Fleur, S. E. (2009). Genetic variation and effects on human eating behavior. Annual Review of Nutrition, 29, 283–​304. Eisenberg, M. E., Olson, R. E., Neumark-​Sztainer, D., Story, M., & Bearinger, L. H. (2004). Correlations between family meals and psychosocial well-​being among adolescents. Archives of Pediatrics and Adolescent Medicine, 158, 792–​796. Farrow, C. V., & Coulthard, H. (2012). Relationships between sensory sensitivity, anxiety and selective eating in children. Appetite, 58, 842–​846. Fulkerson, J. A., Story, M., Mellin, A., Leffert, N., Neumark-​ Sztainer, D., & French, S. A. (2006). Family dinner meal frequency and adolescent development:  Relationships with developmental assets and high-​ risk behaviors. Journal of Adolescent Health, 39, 337–​345. Harris, H. A., Fildes, A., Mallan, K. M., & Llewellyn, C. H. (2016). Maternal feeding practices and fussy eating in toddlerhood: A discordant twin analysis. International Journal of Behavioral Nutrition and Physical Activity, 13, 81. Jacobi, C., Agras, W. S., Bryson, S., & Hammer, L. D. (2003). Behavioral validation, precursors, and concomitants of picky eating in childhood. Journal of the American Academy of Child and Adolescent Psychiatry, 42, 76–​84. Kauer, J., Pelchat, M. L., Rozin, P., & Zickgraf, H. F. (2015). Adult picky eating:  Phenomenology, taste sensitivity, and psychological correlates. Appetite, 90, 219–​228. Kerzner, B., Milano, K., MacLean, W. C., Berall, G., Stuart, S., & Chatoor, I. (2015). A practical approach to classifying and managing feeding difficulties. Pediatrics, 135, 344–​353. Lask, B., & Bryant-​Waugh, R. (1999). Anorexia nervosa and related eating disorders in childhood and adolescence (2nd ed.). East Sussex, UK: Psychology Press.

Machado, B. C., Dias, P., Lima, V. S., Campos, J., & Gonçalves, S. (2016). Prevalence and correlates of picky eating in preschool-​aged children:  A  population-​based study. Eating Behaviors, 22, 16–​21. Mascola, A. J., Bryson, S. W., & Agras, W. S. (2010). Picky eating during childhood: A longitudinal study to age 11 years. Eating Behaviors, 11, 253–​257. Micali, N., Rask, C. U., Olsen, E. M., & Skovgaard, A. M. (2016). Early predictors of childhood restrictive eating: A population-​based study. Journal of Developmental and Behavioral Pediatrics, 37, 314–​321. Micali, N., Simonoff, E., Elberling, H., Rask, C. U., Olsen, E. M., & Skovgaard, A. M. (2011). Eating patterns in a population-​ based sample of children aged 5 to 7 years: Association with psychopathology and parentally perceived impairment. Journal of Developmental and Behavioral Pediatrics, 32, 572–​580. Neumark-​Sztainer, D., Story, M., Ackard, D., Moe, J., & Perry, C. (2000). The “family meal”: Views of adolescents. Journal of Nutrition Education, 32, 329–​334. Nicholls, D., Christie, D., Randall, L., & Lask, B. (2001). Selective eating:  Symptom, disorder or normal variant. Clinical Child Psychology and Psychiatry, 6, 257–​270. Olatunji, B. O., Williams, N. L., Tolin, D. F., Abramowitz, J. S., Sawchuk, C. N., Lohr, J. M., & Elwood, L. S. (2007). The Disgust Scale:  Item analysis, factor structure, and suggestions for refinement. Psychological Assessment, 19, 281–​297. Pennell, A., Couturier, J., Grant, C., & Johnson, N. (2016). Severe avoidant/​restrictive food intake disorder and coexisting stimulant treated attention deficit hyperactivity disorder. International Journal of Eating Disorders, 49, 1036–​1039. Satter, E. (2000). Child of mine: Feeding with love and good sense. Boulder, CO: Bull. Seema, S. & Aceves, M. (2016). Advances in GERD. Gastroenterology and Hepatology, 12, 516–​518. Spergel, J. M., & Shuker, M. (2008). Nutritional management of eosinophilic esophagitis. Gastrointestinal Endoscopy Clinics of North America, 18, 179–​194; xi. Stevenson, R. J., Case, T. I., & Oaten, M. J. (2011). Proactive strategies to avoid infectious disease. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences, 366, 3361–​3363. Stevenson, R. J., Hodgson, D., Oaten, M. J., Moussavi, M., Langberg, R., Case, T. I., & Barouei, J. (2012). Disgust elevates core body temperature and up-​ regulates certain oral immune markers. Brain, Behavior, and Immunity, 26, 1160–​1168. Taylor, C. M., Northstone, K., Wernimont, S. M., & Emmett, P. M. (2016). Picky eating in preschool children: Associations with dietary fibre intakes and stool hardness. Appetite, 100, 263–​271.

Taylor, C. M., Wernimon, S. M., Northstone, K., & Emmett, P. M. (2015). Picky/​fussy eating in children: Review of definitions, assessment, prevalence and dietary intakes. Appetite, 95, 349–​359. Tepper, B. J. (2008). Nutritional implications of genetic taste variation: The role of PROP sensitivity and other taste phenotypes. Annual Review of Nutrition, 28, 367–​388. Tharner, A., Jansen, P. W., Kiefte-​de Jong, J. C., Moll, H. A., van der Ende, J., Jaddoe, V. W. V.,  . . .  Franco, O. H. (2014). Toward an operative diagnosis of fussy/​picky eating: a latent profile approach in a population-​based cohort. International Journal of Behavioral Nutrition and Physical Activity, 11, 11. US Department of Health and Human Services, US Department of Agriculture. (2015, December). Dietary guidelines for Americans 2015–​2020 (8th ed.). van der Horst, K., Deming, D. M., Lesniauskas, R., Carr, B. T., & Reidy, K. C. (2016). Picky eating: Associations with child eating characteristics and food intake. Appetite, 103, 286–​293. Wardle, J., Carnell, S., & Cooke, L. (2005). Parental control over feeding and children’s fruit and vegetable intake: How are they related?. Journal of the American Dietetic Association, 105(2), 227–​232. Wildes, J. E., Zucker, N. L., & Marcus, M. D. (2012). Picky eating in adults: Results of a Web-​based survey. International Journal of Eating Disorders, 45, 575–​582. Williams, K. E., Gibbons, B. G., & Schreck, K. A. (2005). Comparing selective eaters with and without developmental disabilities. Journal of Developmental and Physical Disabilities, 17, 299–​309. Wright, C. M., Parkinson, K. N., Shipton, D., & Drewett, R. F. (2007). How do toddler eating problems relate to their eating behavior, food preferences, and growth? Pediatrics, 120, e1069–​e1075. Xue, Y., Lee, E., Ning, K., Zheng, Y., Ma, D., Gao, H.,   .  .  .  Zhang, Y. (2015). Prevalence of picky eating behaviour in Chinese school-​age children and associations with anthropometric parameters and intelligence quotient:  A  cross-​ sectional study. Appetite, 91, 248–​255. Zelazniewicz, A., & Pawlowski, B. (2015). Disgust in pregnancy and fetus sex:  Longitudinal study. Physiology & Behavior, 139, 177–​181. Zimmer, M. H., Hart, L. C., Manning-​Courtney, P., Murray, D. S., Bing, N. M., & Summer, S. (2012). Food variety as a predictor of nutritional status among children with autism. Journal of Autism and Developmental Disorders, 42, 549–​556. Zucker, N. L., Copeland, W., & Egger, H. (2016). Authors’ response. Pediatrics, 137, doi: 10.1542/​peds.2015-​3635B. Zucker, N., Copeland, W., Franz, L., Carpenter, K., Keeling, L., Angold, A., & Egger, H. (2015). Psychological and psychosocial impairment in preschoolers with selective eating. Pediatrics, 136, e582–​590.

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C H A PT E R

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23

Kelly C. Allison and Jennifer D. Lundgren

Abstract The Diagnostic and Statistical Manual, fifth edition, of the American Psychiatric Association (2013) has designated several disorders under the diagnosis of otherwise specified feeding and eating disorder (OSFED). This chapter evaluates three of these, night eating syndrome (NES), purging disorder (PD), and atypical anorexia nervosa (atypical AN). It also reviews orthorexia nervosa, which has been discussed in the clinical realm as well as the popular press. The history and definition for each is reviewed, relevant theoretical models are presented and compared, and evidence for the usefulness of the models is described. Empirical studies examining the disorders’ independence from other disorders, comorbid psychopathology, and, when available, medical comorbidities, are discussed. Distress and impairment in functioning seem comparable between at least three of these emerging disorders and threshold eating disorders. Finally, remaining questions for future research are summarized. Key Words:  OSFED, night eating syndrome, purging disorder, atypical anorexia, orthorexia nervosa

Introduction

The Diagnostic and Statistical Manual, 5th Edition (DSM-​ 5) of the American Psychiatric Association (2013) produced a new list of otherwise specified feeding and eating disorders (OSFED) since its last edition, and an even more general category of unspecified feeding and eating disorders (UFED). Previously, binge eating disorder (BED) fell into the eating disorder not otherwise specified (EDNOS) category, but this is now a full threshold eating disorder (ED), joining anorexia nervosa (AN) and bulimia nervosa (BN). In its place are several syndromes or variants of the standalone EDs, including night eating syndrome (NES), purging disorder (PD), and atypical anorexia nervosa (atypical AN). Not listed in the DSM-​5 but certainly represented in the literature and encountered in clinical practice is orthorexia nervosa (ON), which is also considered in this chapter. During the DSM-​IV (American Psychiatric Association, 2000) revision, Blashfield, Sprock, and 438

Fuller (1990) proposed five criteria as necessary for inclusion as a psychiatric disorder: Criterion I: “There should be at least 50 journal articles on the proposed diagnostic category in the last 10 years,  . . .  at least 25 of them should be empirical”  . . . . Criterion II: That there be (a) a set of diagnostic criteria which (b) include self-​report measures, structured interviews, and rating scales  . . . . Criterion III: There should be at least two empirical studies by independent research groups demonstrating high inter-​clinician correlations  . . . . Criterion IV: The proposed category represents a syndrome of frequently co-​occurring symptoms, described in at least two independent studies  . . . . Criterion V: There should be at least two independent empirical studies showing that the proposed category “can be differentiated from other categories with which it is likely to be confused.” (p. 17)

These guidelines, as well as calls for demonstration of empirical approaches for classification

(Wonderlich, Joiner, Keel, Williamson, & Crosby, 2007), were helpful in evaluating syndromes presented in this chapter. We review the history, definition, and relevant theoretical models for each, outline evidence for the usefulness of the models, and provide a summary of remaining questions for future research.

Research Status and Description of Night Eating Syndrome

Although night eating syndrome (NES) has been recognized for decades, research and clinical characterization of NES lacks longevity. The history, prevalence, and research diagnostic criteria for NES are reviewed below.

History and Prevalence

Night eating syndrome (NES) was first described in 1955 as a disorder of morning anorexia, evening hyperphagia, and insomnia, usually accompanied by depressed mood and stressful life circumstances (Stunkard, Grace, & Wolf, 1955). Night eating syndrome did not receive much research or clinical attention until the 1990s, coinciding with increasing rates of obesity and the search for factors related to excessive weight gain. In 1999, awakenings with ingestions (nocturnal ingestions) were added to those criteria originally described in 1955, and were published in a provisional set of criteria (Birketvedt et  al., 1999). However, as research advanced our understanding of NES, the diagnostic criteria for NES used by researchers often changed, making comparisons across studies difficult. Prevalence of NES in the general population has been reported between 1.5% and 5.8% (Colles, Dixon, & O’Brien, 2007; de Zwaan, Müller, Allison, Brähler, & Hilbert, 2014; Lamerz et al., 2005; Rand, Macgregor, & Stunkard, 1997; Striegel-​ Moore, Franko, Thompson, Affenito, & Kraemer, 2006; Tholin et al., 2009), with variance across the studies due in part to the different criteria and assessment methods used. Prevalence estimates in special populations suggest ranges of 6% (Stunkard et al., 1996) to 16% (Adami, Campostano, Marinari, Ravera, & Scopinaro, 2002) in weight loss samples of class  I  and II obesity. Among bariatric surgery candidates, the range in prospective interview studies is 9% (Allison et al., 2006) to 27% (Rand et al., 1997). A prevalence of 3.8% has been found among older adults in a large multicenter study of type 2 diabetes (Allison et al., 2007), 7% and 9.7% of patients in diabetes clinics (Hood, Reutrakul, & Crowley, 2014; Morse, Ciechanowski, Katon, &

Hirsch, 2006), 12% in two university outpatient psychiatric clinics (Lundgren et  al., 2006), and 8.6% of patients from a German sleep apnea clinic (Olbrich et al., 2009). Thus, prevalence rises among treatment-​seeking populations.

Current Research Diagnostic Criteria

Recognizing that widely accepted diagnostic criteria for NES were needed in order to advance our understanding and treatment of the syndrome, professionals from the ED, sleep, and obesity fields convened the First International Night Eating Symposium in April 2008. Table 23.1 shows the criteria that were established by consensus (Allison, Lundgren, O’Reardon et al., 2010). They built on the two core criteria, that is, a delayed circadian pattern of food intake manifested by evening hyperphagia and/​or nocturnal ingestions (Criterion I). Criterion II requires awareness of the eating episodes to differentiate it from somnambulistic eating typical of sleep-​related eating disorder (SRED). Criterion III lists specifiers that have been consistently associated with NES, three of which are required for diagnosis. Criteria IV, V, and VI require distress or impairment in functioning, duration of the symptoms of at least 3 months, and a rule-​out of other primary conditions that may be causing the night eating.

Models of Night Eating Syndrome

As NES has components of eating, sleep, and mood disorders, it has been conceptualized in several ways. These models include NES as (1) a distinct disorder, (2)  an extension of daytime EDs, (3)  on a continuum with sleep disorders, (4)  a variant of obesity, and (5)  secondary to other psychopathology.

Night Eating Syndrome as a Distinct Disorder

While the merits of NES as a psychiatric disorder have been questioned (Striegel-​Moore, Franko, et al., 2006), the evidence for its distinction as an independent construct has grown. A  number of empirical studies have described the unique eating patterns and related behaviors associated with NES, including item response theory analysis, circadian analyses of eating and neuroendocrine factors, and latent class analysis. An item response theory analysis was performed on 1,481 Night Eating Questionnaires (NEQ; Allison, Lundgren, et al., 2008), a screening tool for night eating symptoms, gathered across six studies, Allison, Lundgren

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Table 23.1  Research Diagnostic Criteria for Night Eating Syndrome I.  The daily pattern of eating demonstrates a significantly increased intake in the evening and/​or nighttime, as manifested by one or both of the following: A.  At least 25% of food intake is consumed after the evening meal B.  At least two episodes of nocturnal eating per week II.  Awareness and recall of evening and nocturnal eating episodes are present. III.  The clinical picture is characterized by at least three of the following features: A.  Lack of desire to eat in the morning and/​or breakfast is omitted on four or more mornings per week B.  Presence of a strong urge to eat between dinner and sleep onset and/​or during the night C.  Sleep onset and/​or sleep maintenance insomnia are present four or more nights per week D.  Presence of a belief that one must eat in order to initiate or return to sleep E.  Mood is frequently depressed and/​or mood worsens in the evening IV.  The disorder is associated with significant distress and/​or impairment in functioning. V.  The disordered pattern of eating has been maintained for at least 3 months. VI.  The disorder is not secondary to substance abuse or dependence, medical disorder, medication, or another psychiatric disorder. Reprinted with permission from Wiley Periodicals, Allison, K. C., Lundgren, J. D., O’Reardon, J. P., Geliebter, A., Gluck, M. E., Vinai, P., et al. Proposed diagnostic criteria for night eating syndrome. International Journal of Eating Disorders, 2010.

including two of NES participants, one of control participants, and three of special populations (e.g., bariatric surgery candidates, psychiatric clinic patients, and overweight older adults with type 2 diabetes) (Allison, Engel, et al., 2008). Endorsement of evening hyperphagia and/​ or nocturnal ingestions, initial insomnia, and nighttime awakenings showed high precision in identifying the night eating construct, while reports of morning anorexia and delayed morning meal did not provide additional meaningful information. It seemed that lack of appetite in the morning was common not just in the two night eating samples (71.4% and 75.5%), but also among the other four samples (24.5%, 59.2%, 58.8%, and 20%). This finding helped inform the decision for the new diagnostic criteria to include morning anorexia as one of five specifiers, three of which are required, but not as a required criterion. Two studies have effectively shown the delay in eating patterns experienced in NES. Boston, Moate, Stunkard, Allison, and Lundgren (2008) modeled 24-​hour caloric intake showing that persons with NES (n = 148) had significantly delayed meals that were spread out over a greater period of time than those of controls (n  =  68). Overall, there was less structure to their eating. In addition, participants with NES consumed significantly more calories across the 24 hours than the controls (2,555 vs. 2,229 kcal, respectively, p < .05). Boston et al. (2008) showed that both breakfast and lunch 440

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were significantly smaller among the NES group than controls, suggesting that “morning anorexia” extends across the lunch period, as well. Similarly, Goel and colleagues (2009) modeled the circadian aspects of food intake, macronutrient content, and neuroendocrine measures among a sample of 15 female night eaters and 14 control inpatient study participants. They found that energy (calories), carbohydrate, and fat intake were significantly delayed by about 1.5 hours, and protein was nonsignificantly delayed by about 0.5 hour. In addition, phase delays for food-​regulatory mechanisms of 1.0 to 2.8 hours were found for leptin and insulin and in the circadian melatonin rhythm (which regulates the sleep period). Circulating levels of ghrelin was the only rhythm to show a phase advance at 5.2 hours, while the glucose rhythm showed an inverted circadian pattern (a delay of 12.4 hours). These findings suggest that NES may result from dissociations between the central timing mechanism, that is, the suprachiasmatic nucleus (SCN, the body’s “master clock” that controls the timing of many basic functions) and peripheral oscillators (e.g., the stomach or liver), which help control timing of basic bodily functions independent of the SCN. With core features of NES identified by advanced statistical methods, a population-​based analysis of the classification of putative persons with NES was also reported. A large community sample of 8,250 persons ages 15 to 39 was studied by Striegel-​Moore and colleagues (2008) using latent class analysis to

identify the typologies of NES, and 2,068 persons who reported night eating behavior were included in the analysis. Food intake patterns were assessed via 24-​hour food recalls; nocturnal ingestions were not specifically assessed and, therefore, not represented in the classifications. A four-​class latent class analysis solution was identified:  (1)  nondepressed late night eaters (eating after 11  p.m., skipping breakfast, and consuming more than 50% of intake after 7 p.m.); (2) nondepressed evening eaters (consuming more than 50% of intake after 7 p.m. but no eating after 11 p.m.); (3) depressed late night eaters (eating after 11 p.m., with some eating more than 50% after 7 p.m., depression, disturbed sleep, tired, and loss of appetite); and (4) depressed evening eaters (same as group 2 plus depressed mood, feeling tired, and disturbed sleep). They also reported that the late night eating was associated with high energy and sodium intake and low protein intake. High body mass index (BMI) was not related to night eating in this sample, but those with night eating were more likely to be male, black, and younger than those without night eating. They also showed that evening overeating was associated with substance use. Striegel-​Moore et al. (2008) concluded that the latent class analysis showed validity for a definition of NES based on eating after 11 p.m., a cut that seemed to discriminate the syndrome better than did 7 p.m. More latent class analysis studies are needed using the new diagnostic criteria and in samples that span a larger age range to expand these findings.

Continuum with Other Eating Disorders

Binge eating disorder and BN represent the two EDs with the most potential for overlap with NES. In BED and BN, binge episodes often occur in the evening, after work or school, as this may be the most opportune time for secretive overeating. However, not many studies have documented the percentage of intake consumed after the evening meal in these groups or whether there is a delay in the circadian pattern of eating in these EDs. Raymond, Neumeyer, Warren, Lee, and Peterson (2003) provided one of the few 24-​hour dietary recall studies that examined the timing of binge episodes. They found that the BED group (n = 12) consumed significantly more in the evening (5 to 11  p.m.) on binge days than the control group (n = 8) at 1,380 kcal versus 964 kcal, respectively. While this difference was statistically significant, a difference of approximately 400 kcal certainly would not constitute an objectively large amount of

food. Energy intake from 11 p.m. to 5 a.m. did not differ between the groups. More recently, Schreiber-​ Gregory et  al. (2013) used ecological momentary assessment to track the time and day of binge episodes among a group of nine women with BED. The most common time was early afternoon, that is, 12 to 3 p.m., and the next most common time included the dinner hour, 6 to 9 p.m. Overall, the explanation that binge episodes are almost exclusively occurring in the evening does not seem to be supported empirically. Overlap between BED and NES in most studies ranges from 5% to 20% (Allison et al., 2007; Allison, Grilo, Masheb, & Stunkard, 2005, Striegel-​Moore, Dohm, et al., 2005; Stunkard et al., 1996). Reports of overlap with BN are very limited. Tzischinsky and Latzer (2004) found during a 3-​year period that 9% of BN and 16% of BED patients in an outpatient ED clinic reported nocturnal ingestions. In addition, a pilot study (Lundgren, Shapiro, & Bulik, 2008) reported that 35.5% of a BN clinical sample endorsed consuming at least 25% of their caloric intake after dinner, and 19.3% reported eating at least half of their intake after dinner. Ten (38.7%) reported at least occasional nocturnal ingestions, while 12.9% reported eating during awakenings at least half of the time. This overlap of night eating behaviors with BN is high, and more studies are needed to understand this relationship. However, there are important differences in the core criteria of NES and other EDs that differentiate them. First, the average caloric intake consumed during nocturnal ingestions is not objectively large, but is similar to regular snacks at approximately 300 to 400 kcal (Allison, Stunkard, & Their, 2004; Birketvedt et  al., 1999). Second, the circadian delay in the 24-​hour pattern of eating that is core to the NES diagnosis (Boston et  al., 2008; Goel et  al., 2009) has not been well documented in BED or BN. Ancillary ED symptoms also appear to differ between NES and other EDs. Alexithymia was measured in patients with NES as compared with controls, and no abnormal values or differences were found (Vinai et  al., 2015). Alexithymia is typically present among BED and the other EDs. Additionally, the presence of one’s belief that they need to eat to go to sleep/​resume sleep seems to represent a cognition specific to NES and has differentiated those with NES from those with BED (Vinai et al., 2014). Finally, some recent studies point to overlap between NES and BED while maintaining some Allison, Lundgren

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distinction. Meule, Allison, and Platte (2014) showed that the presence of emotional eating moderated the relationship between night eating symptoms, binge eating, and BMI, such that more severe night eating was related to more frequent binge episodes and higher BMI only at high levels of emotional eating, but not at low levels of emotional eating. Root et al. (2010) also compared the heritability of NES and BED among participants of the Swedish Twin Registry. They found that heritability for BE was 0.74 (95% CI = [0.36, 0.93]) for men and 0.70 (95% CI  =  [0.26, 0.77]) for women, while heritability for night eating was 0.44 (95% CI = [0.24, 0.61]) for men and 0.35 (95% CI = [0.17, 0.52]) for women. They also reported a genetic correlation of 0.66 (95% CI = [0.48, 0.96]) suggesting a high, but not complete, genetic overlap for liability to the disorders and leaving room for the contribution of environmental factors to influence the expression of these disorders.

Continuum with Sleep Disorders

The conceptual overlap between NES and sleep-​related eating disorder (SRED) has been less explored than its overlap with other EDs. The key criterion for SRED is involuntary eating during the main sleep period (Sateia, 2005). As such, the main difference between NES and SRED is the level of awareness during eating episodes. Persons who sleepwalk and eat are more likely to ingest odd or nonfood items, such as shaving cream instead of ice cream or cat food, and to injure themselves walking into obstacles or preparing foods (Schenck & Mahowald, 1994). In addition, they would be less likely to have memory or recall of nocturnal ingestions. Perhaps most importantly, treatment differs for the disorders, with dopaminergic agents in combination with codeine or clonazepam showing efficacy for SRED, as compared with selective serotonin reuptake inhibitors for NES (see Howell, Schenck, & Crow, 2009, for review). Preliminary studies for the effectiveness of topiramate for both disorders is positive (Winkelman, 2003, 2006), but randomized controlled trials for confirmation are needed. Finally, psychotherapies, such as cognitive-​ behavioral therapy, that seem promising for NES (Allison, Lundgren, Moore, O’Reardon, & Stunkard, 2010) would not be effective for a parasomnia where the eating behavior is truly involuntary. It is possible that SRED and NES occur along a continuum, as suggested by Howell and colleagues (2009). Clinical experience of the authors of this chapter suggests that a minority of NES patients 442

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report that they either (1) began eating during the night with little to no consciousness, but over time they gained awareness of the nocturnal eating or (2)  they occasionally experienced nocturnal ingestions with little awareness, but for the majority of ingestions they were awake and aware. While the disorders may be related, the contrasts certainly suggest that they are different syndromes that may sometimes co-​occur (Stunkard et al., 2009).

Continuum with Obesity

There is mixed evidence regarding the relationship between NES and obesity. Night eating syndrome has been described among persons of averageweight, overweight, and obesity (Birketvedt et al., 1999; Lundgren, Allison, O’Reardon, & Stunkard, 2008; Marshall, Allison, O’Reardon, Birketvedt, & Stunkard, et al., 2004). European epidemiological studies (Andersen, Stunkard, Sorensen, Petersen, & Heitmann, 2004, Tholin et al., 2009) as well as clinical studies (Aranoff, Geliebter, & Zammit, 2001; Colles et al., 2007; Lundgren, Allison, Crow, et al., 2006) have shown an increased risk for obesity among persons with NES, but two other studies based on American national databases did not show this increased risk (Striegel-​Moore et al., 2005; Striegel-​ Moore, Franko, Thompson, et al., 2006). These latter studies were not designed to assess night eating specifically, but were based on 24-​hour food records. It could be assumed that the repeated and persistent nature of the disorder contributes to weight gain among those with NES. But, counterintuitively, Lundgren and colleagues (2008) reported that nonobese persons with night eating reported an even higher proportion of eating after the evening meal (50%, SD = 15%), as compared with 35% (SD = 10%) reported in an overweight and obese sample of persons with NES (O’Reardon et al., 2004). Lundgren, Allison, et al. (2008) also reported that the nonobese night eaters reported more excessive exercise and daytime dietary restraint in comparison with nonobese control participants, although none of the participants met current criteria for BN in that study. The compensatory exercise and daytime restraint may help them keep their weight under control, while exaggerating the circadian delay of their eating. Thus, overall, there is no sound evidence that NES is solely a phenotype of obesity.

Night Eating Syndrome as Secondary to Other Psychopathology

As in BED, high psychiatric comorbidity rates have been associated with NES. Beck Depression Inventory scores are in the mild to moderate range

at 15.9 (SD = 10.6), which is comparable to scores of persons with BED (17.5, SD  =  9.0; Allison, Grilo, et  al., 2005), BN (15, SD  =  11.5), and PD (11, SD  =  9.2; Keel, Haedt, & Edler, 2005); see Figure 23.1. Self-​esteem is also lower in NES patients seeking weight loss than in patients without NES (Gluck, Geliebter, & Satov, 2001). Lifetime prevalence of other psychiatric disorders as assessed by the Structured Clinical Interview for the DSM (SCID) is high among those with NES at 74%, as compared with controls at 18% (Lundgren, Allison, et  al., 2008). This figure is similar to that found in persons with BED (70%) and BN (75%; Fink, Smith, Gordon, Holm-​Denoma, & Joiner, 2009). Overall, though, comorbidity alone is not necessarily a reason for exclusion as an independent diagnostic construct.

Evidence of Diagnostic Validity and Clinical Significance Using Models of Night Eating Syndrome Evidence from studies of differing methodologies supports a distinct classification for NES, which can be discriminated from other EDs based

on its unique circadian pattern of intake and lack of binge eating behaviors. Night eating syndrome may be found on a continuum with SRED, but several features discriminate the two disorders, particularly different treatment approaches. Night eating syndrome is found across persons of all BMIs and has not reliably been linked to obesity. Although persons with NES have high comorbidity rates with other psychiatric disorders, particularly mood disorders, this does not preclude NES from existing as an independent diagnosis. Despite this evidence for NES as a distinct diagnosis, much more information is needed to clarify remaining questions associated with its specific diagnostic features and its exact relationship with other eating and sleep disorders.

Research Needed to Clarify the Status of Night Eating Syndrome

With the establishment of research diagnostic criteria for NES, new studies are needed to validate those criteria and to investigate the usefulness of their parameters. First, the operational definition of evening hyperphagia has been set at 25%

20 18 16 14

Controls BED NES PD BN

Score

12 10 8 6 4 2 0

Dietary Restraint

Eating Concern

Shape Concern

Weight Concern

Cognitive Restraint

Disinhibition

Hunger

BDI

Figure 23.1  Disordered eating and depressed mood levels depicted across controls and groups with binge eating disorder, night eating syndrome, purging disorder, and bulimia nervosa. No statistical comparisons are provided, given the numbers are generated from different studies, but the levels support the repeated findings that all of these groups experience clinical levels of disordered eating and depressed mood in comparison with control groups and that their levels differ among the diagnoses in an inconsistent manner.  Data for the control, BED, and NES groups were extracted from Allison, Grilo, Masheb, & Stunkard, 2005. Data for the PD and BN groups were extracted from Keel, Haedt, & Edler, 2005.

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of daily caloric intake consumed after the evening meal. The “evening meal” was chosen as a marker instead of a specific time, because the dinner hour varies across cultures. O’Reardon et  al. (2004) found that night eaters who had verbally reported consuming at least half of their intake after dinner were actually eating about 35% (SD  =  10%), as reported through 7-​day food logs. Control participants were consuming 10% (SD  =  7%). One SD below the NES participants’ and two SD’s above the control participants’ proportion of nighttime food intake converges at 25%, creating a useful separation point between the groups. More studies should assess the clinical utility of this cut-​ point in different samples. More research is also needed to test the clinical utility of the frequency of nocturnal ingestions, which were set at two per week to match the frequency of binges required in the diagnoses of BN and BED. Previous studies either did not specify a number (Birketvedt et al., 1999) or used three per week (Lundgren, Allison, et  al., 2008, O’Reardon et al., 2006). There are no data on the relationship between frequency of nocturnal ingestions and levels of clinical distress. As the criteria stand, only one of the core criteria is needed for diagnosis. This makes conceptual sense as both evening hyperphagia and nocturnal ingestions are expressions of a delayed circadian pattern of eating. However, more data are needed on the timing of binge episodes for BN and BED to understand if an “evening hyperphagia subtype” is valid in an ED population. The presence or worsening of depressed mood across the 24-​hour day is currently included as a specifier of NES. As depressed mood is common in other EDs but is not included in their diagnostic items, more work is needed to assess the utility of this item for the diagnosis of NES. In addition, weight and shape concerns are not included in the research criteria. These concerns are higher among persons with NES than controls, but are significantly lower than persons with BED (Allison, Grilo, et al., 2005); Figure 23.1. Those with BED and NES did not differ from each other on eating concerns and dietary restraint on the Eating Disorder Examination, and both groups reported higher levels than controls. Thus, weight and shape concerns are elevated among individuals with NES, but how central this is to the disorder needs more investigation. Distress and impairment in functioning are required for all psychiatric diagnoses, and it has 444

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been included in the new criteria set for NES. However, it has not been formally included in most NES studies to date, so assessing its presence is encouraged. Not only are the psychosocial correlates of a psychiatric disorder important but also, increasingly, the health implications of a disorder are essential in establishing the importance of a diagnostic entity. While neuroendocrine abnormalities have been noted (Allison, Ahima, et al., 2005; Goel et al., 2009), it is not clear how these abnormalities are related to disease and mortality. However, night eating among diabetic patients has been associated with less adherence to diet, exercise, and glucose monitoring as well as higher hemoglobin A1C levels and more diabetic complications (Morse et al., 2006). Also, a review of the impact of night eating on bariatric surgery outcomes (Colles & Dixon, 2006) revealed that night eating behaviors often continue after surgery, and at least one study has shown that night eating after surgery is associated with greater BMIs and less treatment satisfaction (Latner, Wetzler, Goodman, & Glinski, 2004). Finally, Andersen and colleagues (2004) found that women, but not men, who endorsed night eating were more likely to gain weight over 6 years as compared to women without night eating. In general, more careful assessment of night eating behaviors is needed in relation to health outcomes, which would be aided by the development of new assessment tools based on the proposed diagnostic criteria. Longitudinal studies would also help identify the impact of NES on the development of disease and its impact on quality of life. Similar to BED, future NES research should also focus on genetic and brain-​imaging methods. Lundgren, Allison, and Stunkard (2006) found that NES runs in families. Specifically, the first-​degree relatives of patient with NES were 4.9 times more likely than the first-​degree relatives of controls to meet criteria for NES. Additionally, as noted above, heritability for night eating behaviors has been reported at .44 among the Swedish Twin Register cohort, with a high genetic correlation of.66 between night eating and binge eating behaviors (Root et al., 2010). Brain-​ imaging methods could also be useful in characterizing NES. Lundgren, Newberg, and colleagues (2008) used single photon emission computed tomography (SPECT) to compare the serotonin transporter (SERT) uptake in persons with NES to both healthy controls and to patients with major depressive disorder. Persons

with NES had significantly greater SERT uptake in the midbrain than did healthy controls (Lundgren, Newberg, et al., 2008). Patients with NES also had significantly greater SERT uptake ratios (effect size range 0.64–​0.84) in the midbrain, right temporal lobe, and left temporal lobe regions compared to patients with depression (Lundgren et  al., 2009). Finally, only one pilot study has used functional magnetic resonance imaging (fMRI) to examine response to food cues among seven adults with obesity with evening hyperphagia compared to seven without hyperphagia (Lundgren et al., 2013). The authors found that those with evening hyperphagia showed decreased inferior frontal gyrus activation from the pre-​to post-​meal condition in response to food cue images as compared with the control group. Overall, the differences they identified in activation patterns suggest that those with evening hyperphagia showed decreased activation of inhibitory brain regions, but more studies are needed to replicate this first finding. Additional future directions would be testing the behavioral features of night eating (e.g., impulsivity and reward dependence could be measured with delay discounting paradigms; e.g., McClure, Laibson, Lowenstein, & Cohen, 2004). Studies such as these will be important in differentiating NES from other eating and psychiatric disorders.

Research Status and Description of Purging Disorder

Similar to other emerging syndromes, purging disorder research and clinical descriptions have grown, particularly in the context of the development of the latest edition of the DSM. The research status and clinical descriptions of purging disorder are reviewed below.

History and Definition

As researchers began to study BN more systematically, several groups (e.g., Mitchell, Pyle, Hatsukami, & Eckert, 1986) noted that large proportions of their cohorts were not consuming enough food in a sitting to be considered objectively large, and therefore, were not meeting criteria for binge episodes, yet they were purging (e.g., vomiting or abusing laxatives) regularly. Persistent purging behavior in the absence of binge eating has subsequently been reported among adults (Wade, 2007) and adolescents (Binford & le Grange, 2005) in community (Hay, Fairburn, & Doll, 1996), clinical (Keel, Haedt, & Edler, 2005), and undergraduate (Fink et al., 2009) samples.

The name “purging disorder” (PD) was established by Keel et  al. (2005) and encompasses disordered eating behavior that has been reported under several names in the literature, including “compensatory eating disorder” (Tobin, Griffing, & Griffing, 1997), “subjective bulimia nervosa” (Keel et  al., 2001), and “purging-​only syndrome” (Wade, 2007). Eating disorder not otherwise specified, purging type (EDNOS-​P) has also been used to describe this group (Binford & le Grange, 2005), given that persons with these clinical features would have been diagnosed in the EDNOS category in the DSM-​IV and DSM-​IV-​TR classification systems. Currently, under the DSM-​5 classification system, PD is included as a specific example of a clinical presentation within the OSFED diagnostic category of the feeding and eating disorders (FEDs; American Psychiatric Association, 2013). Like most emerging syndromes, varying definitions are presented in the literature before a common set of diagnostic criteria is agreed on. In a review of the literature, Keel (2007) described 10 different definitions for syndromes of purging. At the time of Keel’s review, PD was generally defined as the regular occurrence of inappropriate compensatory behaviors (e.g., vomiting, laxative use, or diuretic misuse) for the purpose of weight or shape control in the absence of objective binge eating episodes and with a body weight greater than 85% of that expected (Keel, 2007). Sufferers often feel distressed after consuming even small amounts of food that are not acceptable to them and have an overwhelming urge to purge afterward. Aspects of the definition that have varied include (1) the frequency of purging, ranging from at least once per week to at least twice per week; (2) requirement that a loss of control over eating (i.e., subjective binge episode) precede the purging behavior; (3) the presence of undue influence of weight and shape on self-​evaluation; and (4) duration of illness, ranging from 3 to 6 months. In preparation for DSM-​5, Keel and Striegel-​ Moore (2009) provided an analysis of the validity and clinical utility of PD using Blashfield and colleagues’ (1990) criteria for establishing a disorder within the DSM system. In the context of their literature review and analysis, they proposed criteria for PD: (1) recurrent purging in order to influence weight or shape, such as self-​induced vomiting, misuse of laxatives, diuretics, or enemas; (2)  purging occurs, on average, at least once a week for three months; (3) self-​evaluation is unduly influenced by body shape or weight or there is an intense fear of Allison, Lundgren

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gaining weight or becoming fat; (4) the purging is not associated with objectively large binge episodes; and (5) the purging does not occur exclusively during the course of anorexia nervosa or bulimia nervosa (Keel & Striegel-​Moore, 2009). Notably, the definition of PD was abbreviated with its inclusion in the OSFED category within the “Feeding and Eating Disorders” section of DSM-​5. Within the DSM-​5, PD is defined as “recurrent purging behavior to influence weight or shape in the absence of binge eating” (APA, 2013).

Prevalence and Epidemiology

Epidemiological studies reveal lifetime prevalence estimates of 5.3% in an Australian female twin cohort (age range 28–​39 years) (Wade, Bergin, Tiggemann, Bulik, & Fairburn, 2006), 1.0% in an slightly younger Australian female twin cohort (age range 15–​19  years) (Fairweather-​Schmidt & Wade, 2014), 0.3% in an Australian young adult male cohort (20  years of age) using DSM-​5 criteria (Allen, Byrne, Oddy, & Crosby, 2013), 1.6% in an Australian young adult female cohort (20 years of age) using DSM-​5 criteria (Allen et  al., 2013), 3.7% in a US female twin cohort (age range 18–​29) (Munn-​Chernoff et  al., 2015), 1.1% in an Italian female cohort (Favaro, Ferrara, & Santonastaso, 2003), 8.2% in a large sample of adult Swedish females seeking treatment for EDs (Ekeroth, Clinton, Norring, & Birgegård, 2013), and a point prevalence of 0.85% in an adolescent Portuguese cohort (Machado, Machado, Goncalves, & Hoek, 2007). The relative frequency of these estimates in some samples, as compared with the other EDs, has varied, likely due to the differing diagnostic criteria used in each study as well as the nature of the population sampled. It is not surprising, for example, that the estimates found in non-​treatment-​seeking populations are lower than among those who are seeking treatment for disordered eating behavior. Purging disorder has been documented in both females and males, and appears to be more prevalent among females (Allen et  al., 2013). Little is known about gender or socioeconomic differences among individuals who suffer from PD versus those who suffer from other forms of disordered eating.

Models of Purging Disorder

Much work still remains in delineating the etiology, course, treatment, and outcome for PD, but there is emerging evidence that it can be differentiated from other disorders and is a clinically significant disorder (Keel & Striegel-​Moore, 2009). Its 446

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inclusion in the OSFED category suggests that the scientific community charged with evaluating the PD literature for the DSM system is taking a “wait and see” approach. Nonetheless, here we review the evidence for PD as (1) a distinct disorder and (2) on a continuum with other EDs. Purging Disorder as a Distinct Axis I Psychiatric Disorder Purging disorder can be damaging both physically and psychologically. The fact that it was recognized specifically as a form of EDNOS in DSM-​IV and under the OSFED category in DSM-​5 affirms that it is a clinically significant syndrome. Keel (2007) argues that because the purging types of AN and BN have been associated with greater medical problems (due to the effects of repeated vomiting and laxative abuse), comorbid psychopathology, and suicidality, that purging in the absence of very low body weight and binge episodes is independently quite dangerous. In addition, PD has been identified as a class separate from other EDs through latent structure analyses (Striegel-​Moore, Franco et  al., 2005; Sullivan, Bulik, & Kendler, 1998; Wade et al., 2006, Pinheiro, Bulik, Sullivan, & Machado, 2008; Swanson et al., 2014). Striegel-​ Moore, Franko, et al. (2005) indicated that the PD group was the largest of the three identified in the analysis. All members of the PD group endorsed vomiting, nearly half reported fasting, and over a third reported the use of diet pills. In addition, there was a higher proportion of persons identifying their race as White in the latent PD group than in the latent binge-​eating group, who had a larger proportion of reported Black racial identities (Striegel-​ Moore, Franko et al., 2005). There are conflicting findings on the most prevalent purging methods in PD. Vomiting has been most commonly reported, at 100% of the PD sample (Striegel-​Moore, Franko et  al., 2005), 98.5% (Binford & le Grange, 2005), and 82% (Ekeroth et  al., 2013). Wade (2007), however, reported higher rates of laxative abuse (62%) than vomiting (38%), followed by diuretic abuse (21%). In their adolescent sample, Binford and le Grange (2005) reported that driven exercise was also quite common at 66%, followed by fasting at 38%, and then laxative abuse at 14%. Excessive exercise was also commonly reported among adult females seeking treatment for eating disordered behavior (55%) (Ekeroth et  al., 2013). Thus, there appears to be heterogeneity of purging and nonpurging compensatory methods within the PD classification.

Several studies have shown that persons with PD have more severe eating disordered attitudes and behaviors and general psychopathology than persons without eating disorders. Specifically, Keel et  al. (2005, 2007) have shown that persons with PD have shown more severe pathology on all four scales of the Eating Disorder Examination (EDE) and all three scales of the Eating Inventory, and Wade (2007) replicated the finding on the EDE with the exception of similar levels of eating concern between those with PD and controls. Body image is more disturbed (Fink et  al., 2009; Keel et  al., 2005), and general psychopathology is also consistently greater in PD groups than in controls, including lifetime major depression, anxiety, and suicidality (Keel et al., 2005; Wade, 2007). Similar to comorbidity rates for lifetime diagnosis of major depressive disorder reported for NES earlier, 54% (Binford & le Grange, 2005), and 76% of persons with PD have reported the disorder. Using ecological momentary assessment, Haedt-​ Matt and Keel (2015) documented greater mean negative affect on purge days versus nonpurge days. Interestingly, their study found that on purge days, negative affect decreased after purging and might serve to negatively reinforce purging behavior. Individuals with PD are more likely than healthy controls to report symptoms of personality disorders, and they report greater impulsivity (Brown, Haedt-​ Matt, and Keel, 2011). Overall, as was shown with NES, PD has been identified through empirical methods with latent class analysis and has shown clinically greater levels of eating disordered and general psychopathology than persons without EDs. Purging Disorder on a Continuum with Other Eating Disorders Purging disorder is most similar to BN, with both purging and nonpurging compensatory behaviors being identified and normal body weight among those with PD. Binford and le Grange (2005) identified two possible theories, that PD represents (1) a prodromal state of BN or (2) a partial BN syndrome. There are various sources of evidence against PD as a precursor to BN. Binford and le Grange (2005) reported that duration of PD and BN of adolescents in their treatment sample were similar at 21 and 19 months. Keel et al. (2005) studied distinctive groups of BN, PD, and controls, requiring that their PD participants not have a previous diagnosis of BN. Remission rates from treatment for PD and BN did not differ between the groups at

a 6-​month follow-​up, and little diagnostic crossover was found, suggesting at least short-​term stability of the diagnoses. Longer-​term stability and crossover was examined in a longitudinal study of Australian adolescents enrolled in the Western Australian Pregnancy Cohort (Raine) Study (Allen et al., 2013). The prevalence of PD at baseline (age 14) was quite low in males (0.4%, n = 3), so diagnostic crossover was only reported for females. Of those females diagnosed with DSM-​5 PD at age 14 (n = 31), 3.2% met DSM-​5 criteria for AN, 25.9% met DSM-​5 criteria for BN, 6.4% met DSM-​5 criteria for BED, 0.0% met diagnostic criteria for atypical AN, 12.9% met DSM-​5 criteria for PD, and 51.6% no longer met criteria for any ED by ages 17 or 20. In contrast to the shorter-​term stability evidenced by Keel et al. (2005), this longitudinal study, based on DSM-​5 criteria, suggests that crossover from PD to BN is both statistically and clinically significant. Notably, in this same study, crossover from BED to BN was much higher at 52.2% (Allen et al., 2013). Despite the evidence of diagnostic crossover from PD to other EDs, PD as a partial BN syndrome or as a variant subtype of BN is more plausible. In several studies, PD groups have endorsed similar levels of disordered eating attitudes and behaviors (see Keel, 2007, and Keel & Striegel-​ Moore, 2009 for reviews); Figure 23.1. Differences on specific scales have sometimes varied, depending on sample characteristics and diagnostic criteria. If differences in the level of pathology were shown, the general trend was for PD to have less severe levels than the BN group. These differences on traditional ED assessment tools may be contributed, at least in part, to the assessment tools, given that large portions of many of them include questions regarding binge eating behavior, which is not present in PD. One possible avenue for differentiating PD and BN may lie in physiological functioning. A  feeding study has shown that women with PD report higher levels of postprandial fullness and gastrointestinal discomfort after a standardized meal than those with BN. Most interesting, women with PD also experienced a greater release of cholecystokinin (CCK; Keel, Wolfe, Liddle, De Young, & Jimerson, 2007), suggesting that physiological cues, such as premature abdominal discomfort in response to eating, may contribute to the purging behavior. The evidence for overlap between PD and AN is not very great, given the differences in body weight. Fink et al. (2009) used the Eating Disorder Inventory to compare eating pathology among AN, Allison, Lundgren

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BN, PD, BED, and controls, finding similarities between AN and PD for most scales, but higher purging ideation among the PD group than the AN group. It is possible that PD could be considered a form of atypical AN, another specific clinical presentation of OSFED defined in the DSM-​5. Atypical AN (reviewed later) is a condition for which all criteria are met for AN, except the individual is at or above normal weight despite significant weight loss. Ekeroth and colleagues (2013) reported that among treatment-​ seeking Swedish women, 10% of those who met DSM-​5 criteria for PD at baseline met criteria for atypical AN at the 12-​month follow-​up. In contrast with the crossover to BN rates reported above (Allen et al., 2013), only 5% of this treatment-​seeking sample crossed over to BN 1 year later.

psychiatric comorbidity, social support, etc.). Keel et al. (2007) have provided one of the only studies of the pathophysiology of PD thus far, with informative findings regarding differential functioning of CCK in PD as compared with BN. Much more work is needed in this area, as well as assessment using brain-​imaging technologies. Functional magnetic resonance imaging (fMRI) studies could aid in delineating similarities and differences between neural function in relation to reward sensitivity and food and body image cue reactivity among PD and the other EDs. Finally, there is also a dearth of treatment outcome studies, which are in obvious need, given the number of individuals who suffer from PD.

Evidence of Diagnostic Validity and Clinical Significance of Models of Purging Disorder

Clinical descriptions and research on atypical anorexia nervosa have only recently begun. Here we describe its definition, history, and prevealnce.

Keel and Striegel-​Moore (2009) present a strong argument for the clinical significance of PD, including significant evidence that PD is associated with psychosocial distress and impairment that is consistent with other EDs and different from healthy controls. Functionally, by placing PD in the OSFED category of FEDs within the DSM-​5, clinical significance is assumed, at least until the DSM is revised in the future. Much more needs to be learned about PD, however, including its etiology, distinct course, and treatment outcome in relation to the other eating disorders.

Research Needed to Clarify the Status of Purging Disorder

Relative to AN, BN, and BED, research on PD as an independent construct is still in its early stages. Its inclusion in DSM-​5 should spark new research to answer many of the unknown questions. An important factor that has yet to be explored specifically for PD is its etiology and a conceptual model of its development and maintenance. Studies such as Haedt-​Matt and Keel’s (2015) ecological momentary assessment of affect before and after purging is a great start in understanding the antecedents, consequences, and maintaining processes involved in PD. More research is needed to compare the unique and common risk and maintaining factors among PD and the other ED diagnoses. Given the mixed findings regarding the stability and diagnostic crossover of PD, longitudinal studies are needed to provide more information about the factors that predict crossover (e.g., genetic, personality, 448

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Research Status and Description of Aytpical Anorexia Nervosa

History and Definition

More than half of patients seeking care at ED treatment services did not meet threshold criteria for AN or BN using the previous DSM-​IV diagnostic criteria and were designated as having EDNOS (Eddy, Celio, Hoste, Herzog, & le Grange, 2008; Fairburn & Bohn, 2005). It was noted that those classified as having EDNOS reported comparable levels of distress and impairment as those in the threshold disorders. As such, in DSM-​5, the OSFED category was created to capture common presentations that were observed in the EDNOS category. In addition to NES and PD, one such clinical presentation was described as “atypical anorexia.” In atypical AN, all of the criteria for AN are met, except that despite significant weight loss, the individual’s weight is within or above the normal range. Anorexia nervosa is described in c­ hapter  1, and involves (1) restriction of energy intake relative to one’s energy requirements for weight maintenance, (2) experience of an intense fear of gaining weight or becoming fat, and (3) being subjected to an undue influence of body weight and shape on self-​evaluation (APA, 2013). These criteria have been operationalized in differing ways in the research literature for atypical AN. For example, Stice, Marti, and Rohde (2013) described it as experiencing at least a 10% weight reduction from a previously measured BMI (i.e., more than a typical weight reduction for behavioral

weight loss programs), definite fear of weight gain more than three-​quarters of the days for at least 3 months, and focusing on weight and shape as one of the main aspects of self-​evaluation. Fairweather-​Schmidt & Wade (2014) required participants, who were adolescent women twins, to meet all criteria for AN but, despite significant weight loss, have a BMI at or above 18.5  kg/​m2, which designates the lower boundary of “normal weight.” Significant weight loss was defined within this sample as a reduction of 1.3  kg/​m2 BMI units relative to BMI at each subsequent wave of data collection (3 years), and the weight loss had to have occurred independently of any episode of BN or BED. Given that the description of atypical AN in the DSM-​5 does not provide specific guidelines for cutoffs for weight loss, it is evident that a consensus definition of a clinically significant weight loss is needed to standardize these criteria.

Prevalence

The prevalence of atypical AN has mainly been reported among adolescent samples. Hammerle, Huss, Ernst, and Burger (2016) published a national school-​ based survey from Germany of grades 7 and 8 with 1,654 students (873 female, mean age: 13.4 yr). Using the Structured Interview for Anorexic and Bulimic Syndromes Survey (SIAB-​ S) and Eating Disorder Inventory-​2, they found a prevalence for atypical AN of 3.6%. Stice et  al. (2013) studied 496 adolescent girls recruited from US schools, with a baseline age between 12 and 15 years, interviewing them yearly for 8 years. They reported a prevalence of atypical AN of 2.8%, occurring increasingly in the later study years (ages 19–​20 years), which was similar to age of onset for AN in this sample. Additionally, 10 of 14 individuals with atypical AN showed remission within 1 year. Fairweather-​Schmidt and Wade (2014) assessed 699 adolescent female twins with a baseline age ranging between 12 and 15 years over the course of three assessments. They completed the EDE interview by phone. Overall, 5% of the sample met criteria for OSFED, with 1.9% of the sample meeting criteria for atypical AN across the three waves. Finally, Mustelin, Lehtokari, and Kski-​Rahkonen (2016) used the FinnTwin16 cohort, with an age range of 22 to 27  years, the oldest sample of the studies reviewed, to provide a two-​stage screening for EDs that included a questionnaire and interview. This community-​based sample consisted of

2,925 women. Of these, 292 screened positive for an ED, and an additional 130 female cotwins and a random sample of 210 screen-​negative participants were interviewed. Mustelin et  al. (2016) reported a prevalence of 1.5% (n  =  38) for all of OSFED (n = 14; 37%) and UFED (n = 24; 63%), including just five cases of atypical AN (0.2% of the entire sample), which was by far the lowest estimate of this disorder among the studies presented.

Evidence of Diagnostic Validity and Clinical Significance Using Models of Atypical Anorexia Nervosa

To our knowledge, the diagnostic validity of atypical AN has not been presented, and as mentioned above, different studies seem to use varying definitions to operationalize the degree of weight loss and/​or BMI cutoff point for inclusion in this diagnostic criteria. However, as presented below, most studies have presented evidence that individuals with atypical AN experience comparable levels of distress and impairment as their counterparts with threshold EDs. There is also evidence that atypical AN does not occur exclusively among individuals who have had AN, nor is it merely the precursor of crossing over into full AN. Stice et  al. (2013) reported that there was a recurrence rate of 21% for atypical AN over the 8-​year study, and only one participant exhibited diagnostic crossover, with that individual developing PD. No individuals with atypical AN developed AN during the eight years of this study. The atypical AN group reported mean monthly binge episodes at 0.3 and mean monthly compensatory behaviors at a total of 9.8. Those with atypical AN reported higher levels of functional impairment, emotional distress, and suicidality than non-​ED controls, with a medium effect size of .51. Overall, Stice et al. concluded that the level of impairment among those with atypical AN is similar to that experienced with full threshold DSM-​5 EDs, providing validity for atypical AN as a clinically significant disorder. Stice et al. (2013) further posited that there should there be a specific weight or BMI cut-​off, given those at lower BMIs with the diagnosis reported higher levels of impairment. Silén et al. (2015) studied 47 adolescents as part of a chart review of 34 patients with AN and 13 patients with atypical AN. Those with atypical AN were significantly older and heavier, but with a BMI of 16.7 kg/​m2, which is still underweight, and less likely to have psychiatric comorbidities. Patient with atypical AN were significantly more likely to recover Allison, Lundgren

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from their symptoms than those with AN. Silén et  al. (2015) suggest that these findings support retaining these distinct diagnostic categories, as they may have predictive value for treatment outcomes. Fairweather-​Schmidt and Wade (2014) studied women twins and found that those with atypical AN showed no difference in duration of core symptoms at diagnosis from those with AN and BN. Individuals with OSFED and threshold ED did not differ on EDE global or subscales. The authors reported that OSFED and threshold EDs had common generic and nonshared environmental influences and that only one genetic source contributes to both expressions of the EDs. However, there was significant differentiation between unique environmental risk factors between the groups, which may protect those with OSFED from development of threshold diagnostic symptoms. Overall, though, the authors believe that there is large degree of genetic overlap between the OSFED diagnoses (NES was not included) and threshold ED diagnoses. Davenport, Rushford, Soon, and McDermott (2015) studied 119 patients seeking treatment for AN. They separated the patients at a BMI of 18.5 kg/​m2 into AN (n = 75) and atypical AN (n = 44). Anorexia nervosa has been shown to have a negative impact on cognitive processing abilities, particularly knowledge about one’s own thinking, leading to rigid thinking and making psychotherapeutic interventions less effective, as described in the Self-​Regulatory Executive Function Model (Wells & Matthews, 1994). As such, the authors compared dysfunctional metacognition, as measured by the Metacognitions Questionnaire, between the AN and atypical AN groups. They reported that dysfunction was similar between the two groups, with drive for thinness distinguishing both from a community control group. Drive for thinness was positively predicted in the atypical AN group by negative beliefs about worry and, inversely by cognitive self-​consciousness. In many ways, the authors stated that the AN and atypical AN groups were indistinguishable. However, the majority of those with atypical AN reported that their lowest BMI since symptom onset was below 17.5 kg/​m2, and their current mean BMI was 21.0 kg/​m2, suggesting that the group as a whole was still quite lean and had met full threshold AN criteria previously. However, this study still showed that low body weight associated with AN is not the only factor driving these individuals’ difficulties with self-​awareness of their thought processes, suggesting that there may be other pathways influencing drive for thinness, 450

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independent of very low weight, that impact metacognition and, likely, one’s ability to fully engage in psychotherapy treatments. Sawyer, Whitelaw, Le Grange, Yeo, and Hughes, 2016 studied 42 adolescents with atypical AN and 118 with threshold AN presenting for treatment. In this group, in contrast to samples described earlier (e.g., Davenport et al., 2015), 71% of the atypical AN group had previously been overweight or obese, as compared with only 12% of the AN group. Weight loss in the atypical AN group had been larger at 17.6 kg than in the AN group (11.0 kg), and the former group had lost weight over a longer period of time. Despite the atypical AN group not meeting the extremely low weight criterion of AN, physical comorbidities were similar between the groups, including bradycardia and orthostatic instability. While there were fewer patients with amenorrhea in the atypical AN group as compared with the AN group, a third of the atypical AN group still experienced this symptom. Psychiatric comorbidities were also quite similar between groups, including suicidal ideation and other psychiatric disorders. However, the EDE global and subscale scores were higher in the atypical AN group as compared with the AN group. The authors conclude that the core features of abnormal disordered eating cognitions and weight loss, as opposed to a specific threshold for low weight, might be a more useful view of restrictive EDs. Schorr et  al. (2016) studied 77 patients with atypical AN as compared to patients with threshold AN defined by DSM-​IV (n = 37) and DSM-​5 (n  =  33), and 21 healthy controls on measures of bone health, body composition, and psychopathology. Both the AN and atypical AN groups reported comparable levels of psychopathology. As for bone health, the AN group had the poorest bone health, with the atypical AN group falling between the AN and comparison groups for bone mineral density. Among the AN and the atypical AN groups, history of amenorrhea was also predictive of poor bone health. Lowest lifetime BMI was correlated with bone mineral density, but history of overweight or obesity was not particularly protective against low bone mineral density. Chen et al. (2016) treated young adults with AN (n = 10) and atypical AN (n = 12) with family-​based treatment. While dropout rate was high, intent to treat analysis showed similar improvements in weight gain and eating disordered pathology for the group as a whole. Unfortunately, no comparisons were presented for outcomes specifically for the atypical AN group. This was certainly a good

place to start with treatment studies of atypical AN, but much more effort is needed in testing treatment efficacy for this group.

Research Needed to Clarify the Status of Atypical Anorexia Nervosa

Most of the studies reviewed here have examined largely female, adolescent samples. Additionally, the BMI of individuals in these samples with atypical AN remains in the low-​normal range, mostly between 20 and 21  kg/​m2. As this diagnostic category could potentially capture individuals who lose large amounts of weight through behavioral weight loss or bariatric surgery and subsequently develop an extreme fear of weight regain and espousing AN thoughts and beliefs, studies of older populations as well as these special weight loss treatment populations are needed, as the presentation of atypical AN may vary based on these characteristics. More epidemiological studies would also be useful to determine the presence of atypical AN across age groups and demographics. As reviewed in the beginning of the chapter, this disorder has not yet satisfied the first two criteria of Blashfield et al. (1990) in that the body of literature is not yet large and there is no consensus agreement on the criteria used to define the amount of weight loss required for atypical AN to be present. Additionally, more studies of the medical burden of atypical AN as compared with control groups of similar BMI would be helpful to add to the knowledge base for this disorder that would serve to supplement our knowledge of the impact of the eating disordered attitudes and behaviors on functioning and well-​ being. Finally, more treatment studies are needed to understand if atypical AN is more responsive to both psychological and pharmacological treatments than typical AN. If atypical AN is more responsive to a range of treatments, this difference could lend clinically relevant significance to the use of this diagnosis.

Research Status and Description of Orthorexia Nervosa

The final emerging syndrome to be evaluated is orthorexia nervosa (ON). As our review below demonstrates, this is the most tenuous of the syndromes discussed in this chapter.

History and Definition

Orthorexia nervosa is conceptualized as an obsessive preoccupation with “healthy eating” (Dunn & Bratman, 2016). In comparison to the other

emerging disorders of eating reviewed in this chapter, ON has the least amount of empirical evaluation on which to evaluate its validity as a clinically significant diagnostic construct. Its tenuous status is due in part to its introduction as a medical condition in a popular magazine, Yoga Journal (Bratman, 1997), rather than through a peer-​reviewed scientific journal. This is of importance because ON received significant media and public attention prior to the publication of any scientific evaluation, including the development of a common set of diagnostic criteria based on an adequate number of clinical observations, psychometrically sound assessment instruments, or studies to examine diagnostic reliability and validity. Consequently, ON was reified in the public prior to adequate scientific evaluation. Since its introduction in popular culture 20 years ago, a small literature on ON has begun to develop. Similar to other EDs, this literature includes case studies (Zamora, Bonaechea, Sánches, & Rial, 2005; Park et al., 2011; Saddichha, Babu, & Chandra, 2012; Moroze et al., 2015), assessment (i.e., versions of the “questionnaire for the diagnosis of orthorexia” [ORTO]) (e.g., Bratman & Knight, 2000; Donini et al., 2005), and prevalence estimates (e.g., Donini et al., 2004). Despite the growing number of published studies of ON, a critical limitation of this literature is that much of it is built on a weak scientific foundation wrought with methodological and measurement limitations. For example, the first scientific study of ON was published by Donini and colleagues in 2004. They sampled a diverse group of Italian individuals ranging from professional adults to adolescents as young as 16 years of age. Orthorexia nervosa was operationalized as scoring at or below the 25th percentile on an unidentified dietary assessment designed to capture “healthy” versus “unhealthy eating” across food groups, along with elevated Minnesota Multiphasic Personality Inventory (MMPI) scores on the psychasthenia clinical scale measuring anxious/​obsessive features. Based on this unusual diagnostic operationalization, they reported an ON prevalence of 6.9%. Clearly, given the lack of valid diagnostic criteria for ON at the time of the study, as well as their basis of a diagnosis on scores on two assessment instruments, the utility of this study (and others with similar methodology) in clarifying the nature of ON is limited. As is the case for any emerging syndrome, the development of standard diagnostic criteria is an iterative process that involves adding, removing, and modifying symptom presentation and Allison, Lundgren

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frequency based on research findings. The first comprehensive diagnostic criteria for ON were presented by Moroze and colleagues (2015). These included (1) an obsessional preoccupation with eating healthy foods that is manifested with at least two of seven behavioral, cognitive, or emotional symptoms such as guilt after eating “unhealthy” foods or spending a relatively excessive amount of money on foods because of their perceived quality and composition; (2)  impairment or distress due to the obsessional preoccupation with healthy eating, including malnutrition; and (3) the obsessional preoccupation with healthy food cannot be better explained by other medical condition, social/​religious observation, or food allergy. Recently, Dunn and Bratman (2016) published a review of the history and current status of the ON literature. They propose a modified diagnostic criteria set that are outlined in Table 23.2. Presumably, the Dun and Bratman (2016) criteria were introduced to add clarification to the diagnostic literature on ON. This latter criteria set, however, raises questions about the validity and clinical utility of the ON diagnosis. For example, the introduction to Criterion A  states that weight loss may ensue, but that it is not the primary goal. Criterion B3, however, introduces the notion that body image might be dependent on “healthy” eating

behavior. If an individual’s body image is dependent on the “healthy” eating behavior, it is quite possible that the primary goal of the “healthy” eating behavior is weight loss. Much research is necessary to evaluate these and the Moroze and colleagues (2015) criteria to determine the degree of diagnostic distinctness between ON and other FEDs (e.g., avoidant restrictive food intake disorder [ARFID] and AN), diagnostic stability and crossover, course, and treatment outcome. Importantly, valid and reliable assessment instruments will be needed, as the literature demonstrates an overreliance on a single self-​report assessment instrument (ORTO and its numerous versions).

Prevalence

The first empirical prevalence estimate was 6.9%, reported by Donini et  al. (2004), and reviewed above. Despite this study’s methodological limitations, it provides one of the lowest (and more likely) prevalence estimates in the literature. The majority of ON studies estimate prevalence in the range of 30%–​88% of those sampled (for review, see Dunn & Bratman, 2016). To date, in part due to a lack of standard research diagnostic criteria, most prevalence studies are based on self-​report using a version of the ORTO. Until research is available to evaluate the recently proposed diagnostic criteria

Table 23.2  Dunn and Bratman (2016) Diagnostic Criteria for ON Criterion A Obsessive focus on “healthy” eating as defined by a dietary theory or set of beliefs whose specific details may vary; marked by exaggerated emotional distress in relationship to food choices perceived as unhealthy; weight loss may ensue as a result of dietary choices, but this is not the primary goal. As evidenced by the following: 1.  Compulsive behavior and/​or mental preoccupation regarding affirmative and restrictive dietary practices believed by the individual to promote optimum health. 2.  Violation of self-​imposed dietary rules causes exaggerated fear of disease, sense of personal impurity and/​or negative physical sensations, accompanied by anxiety and shame. 3.  Dietary restrictions escalate over time and may come to include elimination of entire food groups and involve progressively more frequent and/​or severe “cleanses” (partial fasts) regarded as purifying or detoxifying. This escalation commonly leads to weight loss, but the desire to lose weight is absent, hidden, or subordinate to ideation about healthy eating. Criterion B The compulsive behavior and mental preoccupation becomes clinically impairing by any of the following: 1.  Malnutrition, severe weight loss, or other medical complications from restricted diet. 2.  Intrapersonal distress or impairment of social, academic, or vocational functioning secondary to beliefs or behaviors about healthy diet. 3.  Positive body image, self-​worth, identity, and/​or satisfaction excessively dependent on compliance with self-​defined “healthy” eating behavior. Reprinted from Eating Behaviors, 21, Dunn and Bratman, On orthorexia nervosa: A review of the literature and proposed diagnostic criteria, 11–​17, Copyright (2016), with permission from Elsevier.

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sets (Moroze et al., 2015; Dunn & Bratman, 2016) prevalence will remain largely unknown.

Models of Orthorexia Nervosa

In their review, Dunn and Bratman (2016) conclude that “there is sufficient evidence that ON is a distinct condition that is different from ARFID” (p. 16). Whether or not this is accurate remains to be clarified with empirical research. Blashfield et al. (1990) outlined five criteria by which DSM diagnoses should be evaluated: (1) ample literature on the syndrome, (2) clearly articulated diagnostic criteria and psychometrically sound assessment instruments to evaluate the criteria, (3) evidence that the diagnosis can be reliably determined across raters, (4) evidence that the syndrome can be differentiated from similar syndromes, and (5) evidence of the validity and clinical significance of the syndrome, including course, outcome, and treatment response. The Blashfield et al. (1990) criteria have been applied to a number of emerging syndromes, including NES and PD, described above. Despite the growing literature on ON, it does not yet meet these criteria—​notably because standard diagnostic criteria were only recently introduced in the literature, and as noted previously, there are serious methodological limitations to the literature that is currently available. If ON is to be considered as an independent diagnostic construct, it would behoove those who research it to develop a longer-​term research plan across multiple research teams using the Blashfield et al. (1990) criteria and the bodies of literature on other emerging syndromes (e.g., PD) as a guide. Other models of ON include considering it a variant of ARFID, AN, or an anxiety disorders such as obsessive-​compulsive disorder. Currently, obsessional preoccupation with eating “healthy” foods falls within the DSM-​5 ARFID category of FEDs, if it results in significant weight loss, significant nutritional deficiency, or interference in psychosocial functioning, which would encompass most clinically significant cases of ON. Arguably, if there is no medical or psychosocial impairment associated with the obsessional “healthy” eating behavior, the eating behavior would not constitute a psychiatric diagnosis. It is also possible that some individuals who present with ON symptoms might actually meet criteria for AN. This would be the case for those who minimize the role of “healthy” eating for body shape or weight. The Dunn and Bratman (2016) proposed diagnostic criteria for ON appear orthogonal to

AN, but further clarification with regard to the role of “healthy” eating on body image (criterion B3) is needed. Finally, it is possible that behaviors, cognitions, and emotions associated with ON are best explained as an anxiety disorder and potentially a variant of obsessive-​compulsive disorder. The literature on ON has highlighted the obsessive nature of the desire to eat “healthy,” and in fact several of the questions on the ORTO assess “worry” related to eating behaviors and food choice (e.g., worry about the thought of food).

Research Needed to Clarify the Status of Orthorexia Nervosa

Several areas of research could help improve the state of the ON literature. First, additional valid and reliable assessment instruments are needed to assess the recently proposed diagnostic criteria sets. Related to this, several aspects of the diagnostic criteria need clarification. For example, guidance is needed as to how to differentiate restriction for food quality versus restriction for reduced calories reliably, when there is clearly overlap between calories and quality (i.e., “healthy” foods are generally lower in calories than “unhealthy” foods). As noted above, the role of weight and shape concerns vis-​à-​ vis “body image” is another area for further clarification. Once these basic diagnostic and assessment questions are addressed in the literature, prevalence can be evaluated more accurately. Additionally, taxometric statistical approaches are needed to determine whether or not ON is distinct enough from other Axis I disorders, including ARFID, AN, and OCD to constitute a stand-​alone disorder. Finally, much research is needed on the etiology (genetic and psychosocial), diagnostic stability, and treatment outcome. In summary, of all of the emerging disorders reviewed in this chapter, ON is the most tenuous. Over the past 20  years, a small literature has emerged, but it is too soon to draw conclusions about the status of ON as an independent DSM diagnosis, given the methodological limitations and relative paucity of literature on ON, in comparison to the other FEDs.

Future Directions

As research on the diagnostic validity and utility of NES, PD, atypical AN, and ON continues, there are two primary areas that will likely make significant contributions to the literature. These include new genetic analyses and brain-​ imaging techniques. With regard to newer genetics methods, Allison, Lundgren

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both epigenetics (Delcuve, Rastegar, & Davie, 2009) and interspecies genetics (Kas, Kaye, Mathes, & Bulik, 2008) should be a priority in moving NES, PD, atypical AN, and ON research forward. Researchers are just beginning to understand the neural mechanisms that underlie behavioral choice and the hedonic effects of food (McClure et  al., 2004; Schienle et  al., 2009), and these methods should help further our understanding about the independence and interrelationships between these emerging syndromes and other forms of disordered eating.

Summary and Conclusions

In summary, there is strong evidence for NES as a threshold ED, as there is now a large cache of evidence that supports its validity as a stand-​alone disorder and its clinical utility. Purging disorder seems to be associated with negative consequences similar to those found in BN, but it is lacking a widely acknowledged criteria set and studies specific to PD (i.e., not just as part of an OSFED sample). Similarly, atypical AN needs much further study as a disorder that could stand independently from AN, the other pure restricting syndrome. Finally, ON has the least preponderance of evidence to support its validity as an eating disorder. While it appears distressing and interferes with daily functioning, much more scientific work is needed to understand whether it is a variant of AN or a distinct disorder.

References

Adami, G. F., Campostano, A., Marinari, G. M., Ravera, G., & Scopinaro, N. (2002). Night eating in obesity: A descriptive study. Nutrition, 18, 587–​589. Allen, K. L., Byrne, S. M., Oddy, W. H., & Crosby, R. D. (2013). DSM-​IV-​TR and DSM-​5 eating disorders in adolescents:  Prevalence, stability, and psychosocial correlates in a population-​based sample of male and female adolescents. Journal of Abnormal Psychology, 122(3), 720–​732. doi: 10.1037/​a0034004. Allison, K. C., Ahima, R. S., O’Reardon, J. P., Dinges, D. F., Sharma, V., Cummings, D. E.,  . . . . Stunkard, A. J. (2005). Neuroendocrine profiles associated with energy intake, sleep, and stress in the night eating syndrome. Journal of Clinical Endocrinology and Metabolism, 90, 6214–​6217. Allison, K. C., Crow, S., Reeves, R. R., West, D. S., Foreyt, J. P., DiLillo, V. G.,  . . .  Stunkard, A. J. (2007). The prevalence of binge eating disorder and night eating syndrome in adults with type 2 diabetes mellitus. Obesity, 15, 1285–​1291. Allison, K. C., Engel, S. G., Crosby, R. D., de Zwaan, M., O’Reardon, J. P., Wonderlich, S. A.,   .  .  .  Stunkard, A. J. (2008). Evaluation of diagnostic criteria for night eating syndrome using item response theory analysis. Eating Behaviors, 9, 398–​407. Allison, K. C., Grilo, C. M., Masheb, R. M., & Stunkard, A. J. (2005). Binge eating disorder and night eating

454

Emerging Syndromes

syndrome: A comparative study of disordered eating. Journal of Consulting and Clinical Psychology, 73, 1107–​1115. Allison, K. C., Lundgren, J. D., Moore, R. H., O’Reardon, J. P., & Stunkard, A. J. (2010). Cognitive behavior therapy for night eating syndrome:  a pilot study. American Journal of Psychotherapy, 64, 94–​106. Allison, K. C., Lundgren, J. D., O’Reardon, J. P., Geliebter, A., Gluck, M. E., Vinai, P.,  . . .  Stunkard, A. J. (2010). Proposed diagnostic criteria for night eating syndrome. International Journal of Eating Disorders, 43, 241–​247. Allison K. C., Lundgren, J. D., O’Reardon, J. P., Martino, N. S., Sarwer, D. B., Wadden, T. A.,  . . .  Stunkard, A. J. (2008). Psychometric properties of a measure of severity of the night eating syndrome. Eating Behaviors, 9, 62–​72. Allison, K. C., Stunkard, A. J., & Their, S. L. (2004). Overcoming the night eating syndrome: A step-​by-​step guide to breaking the cycle. Oakland, CA: New Harbinger. Allison, K. C., Wadden, T. A., Sarwer, D. B., Fabricatore, A. N., Crerand, C., Gibbons, L.,  . . .  Williams, N. N. (2006). Night eating syndrome and binge eating disorder among persons seeking bariatric surgery: Prevalence and related features. Obesity, 14(Suppl 2), 77S–​82S. American Psychiatric Association (APA). (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.) Washington, DC: Author. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author. Andersen, G. S., Stunkard, A. J., Sorensen, T. I. A., Pedersen, L., & Heitman, B. L. (2004). Night eating and weight change in middle-​aged men and women. International Journal of Obesity, 28, 1138–​1143. Aronoff, N. J., Geliebter, A., & Zammit, G. (2001). Gender and body mass index as related to the night-​eating syndrome in obese outpatients. Journal of the American Dietetics Association, 101, 102–​104. Binford, R. B., & le Grange, D. (2005). Adolescents with bulimia nervosa and eating disorder not otherwise specified-​purging only. International Journal of Eating Disorders, 38, 157–​161. Birketvedt, G., Florholmen, J., Sundsfjord, J., Osterud, B., Dinges, D., Bilker, W.,   .  .  .  Stunkard, A. J. (1999). Behavioral and neuroendocrine characteristics of the night-​ eating syndrome. JAMA, 282, 657–​663. Blashfield, R. K., Sprock, J., & Fuller, A. K. (1990). Suggested guidelines for including or excluding categories in the DSM-​ IV. Comprehensive Psychiatry, 31, 15–​19. Boston, R. C., Moate, P. J., Stunkard, A. J., Allison, K. C., & Lundgren, J. D. (2008). Modeling food intake diurnal rhythms by means of parametric deconvolution. American Journal of Clinical Nutrition, 87, 1672–​1677. Bratman, S. (1997, September/​October). The health food eating disorder. Yoga Journal, 42–​50. Bratman, S., & Knight, D. (2000). Health food junkies: Orthorexia nervosa:  Overcoming the obsession with healthful eating. New York, NY: Broadway. Brown, T. A., Haedt-​ Matt, A. A., & Keel, P. K. (2011). Personality pathology in purging disorder and bulimia nervosa. International Journal of Eating Disorders, 44, 735–​740. Chen, E. Y., Weissman, J. A., Zeffiro, T. A., Yiu, A., Eneva, K. T., Arlt, J. M., & Swantek, M. J. (2016). Family-​based therapy for young adults with anorexia nervosa restores weight. International Journal of Eating Disorders, 49, 701–​707.

Colles, S. L., & Dixon, J. B. (2006). Night eating syndrome:  Impact on bariatric surgery. Obesity Surgery, 16, 811–​820. Colles, S. L., Dixon, J. B., & O’Brien, P. E. (2007). Night eating syndrome and nocturnal snacking: Association with obesity, binge eating and psychological distress. International Journal of Obesity, 31, 1722–​1730. Davenport, E., Rushford, N., Soon, S., & McDermott, C. (2015). Dysfunctional metacognition and drive for thinness in typical and atypical anorexia nervosa. Journal of Eating Disorders, 3, 24. doi: 10.1186/​s40337-​015-​0060-​4. Delcuve, G. P., Rastegar, M., & Davie, J. R. (2009). Epigenetic control. Journal of Cellular Physiology, 219, 243–​250. de Zwaan, M., Müller, A., Allison, K. C., Brähler, E., & Hilbert, A. (2014). Prevalence and correlates of night eating in the German general population. PLoS One; 14:9:e97667. Donini, L., Marsili, D., Graziani, M., Imbriale, M., & Cannella, C. (2004). Orthorexia nervosa: A preliminary study with a proposal for diagnosis and an attempt to measure the dimension of the phenomenon. Eating and Weight Disorders, 9, 151–​157. Donini, L., Marsili, D., Graziani, M., Imbriale, M., & Cannella, C. (2005). Orthorexia nervosa:  Validation of a diagnosis questionnaire. Eating and Weight Disorders, 10, e28–​232. Dunn, T. M., & Bratman, S. (2016). On orthorexia nervosa: A review of the literature and proposed diagnostic criteria. Eating Behaviors, 21, 11–​17. Eddy, K. T., Celio Doyle, A., Hoste, R. R., Herzog, D. B., & le Grange, D. (2008). Eating disorder not otherwise specified in adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 47, 156–​164. Ekeroth, K., Clinton, D., Norring, C., Birgegård, A. (2013). Clinical characteristics and distinctiveness of DSM-​5 eating disorder diagnoses: Findings from a large naturalistic clinical database. Journal of Eating Disorders, 1, 31. Retrieved from http://​www.jeatdisord.com/​content/​1/​1/​31 Favaro, A., Ferrara, S., & Santonastaso, P. (2003). The spectrum of eating disorders in young women: A prevalence study in a general population sample. Psychosomatic Medicine, 65, 701–​708. Fairburn, C. G., & Bohn, K. (2005). Eating disorder NOS (EDNOS): An example of the troublesome “not otherwise specified” (NOS) category in DSM-​IV. Behavior Research and Therapy, 43, 691–​701. Fairweather-​Schmidt, A. K., & Wade, T. D. (2014). DSM-​5 eating disorders and other specified eating and feeding disorders:  Is there a meaningful Differentiation? International Journal of Eating Disorders, 47, 524–​533. Fink E. L., Smith, A. R., Gordon, K. H., Holm-​Denoma, J. M., & Joiner, T. E. (2009). Psychological correlates of purging disorder as compared with other eating disorders: An exploratory investigation. International Journal of Eating Disorders, 42, 31–​39. Gluck, M. E., Geliebter, A., & Satov, T. (2001). Night eating syndrome is associated with depression, low self-​ esteem, reduced daytime hunger, and less weight loss in obese outpatients. Obesity Research, 9, 264–​267. Goel, N., Stunkard, A. J., Rogers, N. L., Van Dongen, H. P. A., Allison, K. C., O’Reardon, J. P.,  . . .  Dinges, D. F. (2009). Circadian rhythm profiles in women with night eating syndrome. Journal of Biological Rhythms, 24, 85–​94. Haedt-​Matt, A. A., & Keel, P. K. (2015). Affect regulation and purging: An ecological momentary assessment study in purging disorder. Journal of Abnormal Psychology, 124, 399–​411.

Hammerle, F., Huss, M., Ernst, V., & Bürger, A. (2016). Thinking dimensional:  Prevalence of DSM-​5 early adolescent full syndrome, partial and subthreshold eating disorders in a cross-​sectional survey in German schools. BMJ Open, 6:e010843. doi: 10.1136/​bmjopen-​2015-​010843. Hay, P., Fairburn, C. G., & Doll, H. A. (1996). The classification of bulimic eating disorders: A community-​based cluster analysis. Psychological Medicine, 26, 801–​812. Hood, M. M., Reutrakul, S., & Crowley, S. J. (2014). Night eating in patients with type 2 diabetes:  Associations with glycemic control, eating patterns, sleep, and mood. Appetite, 79, 91–​96. Howell, M. J., Schenck, C. H., & Crow, S. J. (2009). A review of nighttime eating disorders. Sleep Medicine, 13, 23–​24. Kas, M. J. H., Kaye, W. H., Mathes, F., & Bulik, C. M. (2008). Interspecies genetics of eating disorder traits. American Journal of Medical Genetics, Part B, 150B, 318–​327. Keel, P. K. (2007). Purging disorder:  Subthreshold variant or full-​threshold eating disorder? International Journal of Eating Disorders, 40, 589–​594. Keel, P. K., Haedt, A., & Edler, C. (2005). Purging disorder: An ominous variant of bulimia nervosa? International Journal of Eating Disorders, 38, 191–​199. Keel, P. K., Mayer, S. A., & Harnden-​Fischer, J. H. (2001). Importance of size in defining binge eating episodes in bulimia nervosa. International Journal of Eating Disorders, 29, 294–​301. Keel, P. K., & Striegel-​Moore, R. H. (2009). The validity and clinical utility of purging disorder. International Journal of Eating Disorders, 42, 706–​719. Keel, P. K., Wolfe, B. E., Liddle, R. A., DeYoung, K. P., & Jimerson, D. C. (2007). Clinical features and physiological response to a test meal in purging disorder and bulimia nervosa. Archives of General Psychiatry, 64, 1058–​1066. Lamerz, A., Kuepper-​Nybelen, J., Bruning, N., Wehle, C., Trost-​ Brinkhues, G., Brenner, H.,   .  .  .  Herpertz-​Dahlmann, B. (2005). Prevalence of obesity, binge eating and night eating in a cross sectional field survey of 6-​year-​old children and their parents in a German urban population. Journal of Child Psychology and Psychiatry, 46, 385–​393. Latner, J. D., Wetzler, S., Goodman, E. R., & Glinski, J. (2004). Gastric bypass in a low-​income, inner-​city population: Eating disturbances and weight loss. Obesity Research, 12, 956–​961. Lundgren, J. D., Allison, K. C., Crow, S., O’Reardon, J. P., Berg, K. C., Galbraith, J.,  . . .  Stunkard, A. J. (2006). Prevalence of the night eating syndrome in a psychiatric population. American Journal of Psychiatry, 163, 156–​158. Lundgren, J. D., Allison, K. C., O’Reardon, J. P., & Stunkard, A. J. (2008). A descriptive study of non-​obese persons with night eating syndrome and a weight matched comparison group. Eating Behaviors, 9, 343–​351. Lundgren J. L., Allison K. C., & Stunkard, A. J. (2006). Familial aggregation in the night eating syndrome. International Journal of Eating Disorders, 39, 516–​518. Lundgren, J. D., Amsterdam, J., Newberg, A., Allison, K. C., Wintering, N., & Stunkard, A. J. (2009). Differences in serotonin transporter binding affinity in patients with major depressive disorder and night eating syndrome. Eating and Weight Disorders, 14, 45–​50. Lundgren, J. D., Newberg, A., Allison, K. C., Wintering, N., Plöessl, K., & Stunkard, A. J. (2008). 123I-​ADAM SPECT imaging of serotonin transporter binding in patients

Allison, Lundgren

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with night eating syndrome:  A  pilot study. Psychiatry Research: Neuroimaging, 162, 214–​220. Lundgren J. D., Patrician, T., Breslin, F., Martin, L., Donnelly, J. E., & Savage, C. (2013). Evening hyperphagia and food motivation:  a preliminary study of neural mechanisms. Eating Behaviors, 14, 447–​450. Lundgren, J. D., Shapiro, J. R., Bulik, C. (2008). Night eating patterns of patients with bulimia nervosa: A preliminary report. Eating and Weight Disorders, 13, 171–​175. Machado, P. P., Machado, B. C., Goncalves, S., & Hoek, H. W. (2007). The prevalence of eating disorders not otherwise specified. International Journal of Eating Disorders, 40, 212–​217. Marshall, H. M., Allison, K. C., O’Reardon, J. P., Birketvedt, G., & Stunkard, A. J. (2004). Night eating syndrome among nonobese persons. International Journal of Eating Disorders, 35, 217–​222. McClure, S. M., Laibson, D. I., Lowenstein, G., & Cohen, J. D. (2004). Separate neural systems value immediate and delayed monetary rewards. Science, 306, 503–​507. Meule, A., Allison, K. C., & Platte, P. (2014). Emotional eating moderates the relationship of night eating with binge eating and body mass. European Eating Disorder Review, 22, 147–​151. Mitchell, M. E., Pyle, R. L., Hatsukami, D., & Eckert, E. D. (1986). What are atypical eating disorders? Psychosomatics, 27, 21–​28. Moroze, R. M., Dunn, T. M., Craig Holland, J., Yager, J., Weintraub, P. (2015). Microthinking about micronutrients:  A  case of transition from obsessions about healthy eating to near-​fatal “orthorexia nervosa” and proposed diagnostic criteria. Psychosomatics, 56, 397–​403. Morse, S. A., Ciechanowski, P. S., Katon, W. J., & Hirsch, I. B. (2006). Isn’t this just bedtime snacking? The potential adverse effects of night-​eating symptoms on treatment adherence and outcomes in patients with diabetes. Diabetes Care, 29, 1800–​1804. Munn-​Chernoff, M. A., Keel, P. K., Klump, K. L., Grant, J. D., Bucholz, K. K., Madden, P. A.,  . . .  Duncan, A. E. (2015). Prevalence of and familial influences on purging disorder in a community sample of female twins. International Journal of Eating Disorders, 48, 601–​606. Mustelin, L., Lehtokari, V. L., & Keski-​Rahkonen, A. (2016). Other specified and unspecified feeding or eating disorders among women in the community. International Journal of Eating Disorders. doi:  10.1002/​eat.22586 [Epub ahead of print]. Olbrich, K., Mühlhans, B., Allison, K. C., Hahn, E. G., Schahin, S. P., & de Zwaan, M. (2009). Night eating, binge eating and related features in patients with obstructive sleep apnea syndrome. European Eating Disorders Review, 17, 120–​127. O’Reardon, J. P., Allison, K. C., Martino, N. S., Lundgren, J. D., Heo, M., & Stunkard, A. J. (2006). A randomized placebo-​ controlled trial of sertraline in the treatment of the night eating syndrome. American Journal of Psychiatry, 163, 893–​898. O’Reardon, J. P., Ringel, B. L., Dinges, D. F., Allison, K. C., Rogers, N. L., Martino, N. S., & Stunkard, A. J. (2004). Circadian eating and sleeping patterns in the night eating syndrome. Obesity Research, 12, 1789–​1796. Park, S. W., Kim, J. Y., Go, G. J., Jeon, E. S., Pyo, H. J., & Kwon, Y. J. (2011). Orthorexia nervosa with hyponatremia,

456

Emerging Syndromes

subcutaneous emphysema, pneumomediastimum, pneumothorax, and pancytopenia. Electrolytes and Blood Pressure, 9, 32–​37. Pinheiro, A. P., Bulik, C. M., Sullivan, P. F., & Machado, P. P. (2008). An empirical study of the typology of bulimic symptoms in young Portuguese women. International Journal of Eating Disorders, 41, 251–​258. Rand, C. S. W., Macgregor, A. M., & Stunkard, A. J. (1997). The night eating syndrome in the general population and among post-​operative obesity surgery patients. International Journal of Eating Disorders, 22, 65–​69. Raymond, N. C., Neumeyer, B., Warren, C. S., Lee S. S., & Peterson, C. B. (2003). Energy intake patterns in obese women with binge eating disorder. Obesity Research, 11, 869–​879. Root, T. L., Thornton L., M., Lindroos, A. K., Stunkard, A. J., Lichtenstein P, Pederson, N. L.,  . . .  Bulik, C. M. (2010). Shared and unique genetic and environmental influences on binge eating and night eating. Eating Behaviors, 11, 92–​98. Saddichha, S., Babu, G. N., & Chandra, P. (2012). Orthorexia nervosa presenting as prodrome of schizophrenia. Schizophrenia Research, 134, 110. Sateia M. J. (Ed.). (2005). International classification of sleep disorders (2nd ed.). Westchester, IL:  American Academy of Sleep Medicine. Sawyer S. M., Whitelaw, M., LeGrange, D., Yeo, M., & Hughes, E. K. (2016). Physical and psychological morbidity in adolescents with atypical anorexia nervosa. Pediatrics, 137:e20154080. Schenck, C. H., & Mahowald, M. W. (1994). Review of nocturnal sleep-​related eating disorders. International Journal of Eating Disorders, 15, 343–​356. Schienele, A., Schäfer, A., Herman, A., & Vaitl, D. (2009). Binge-​eating disorder:  Reward sensitivity and brain activation to images of food. Biological Psychiatry, 65, 654–​661. Schorr, M., Thomas, J. J., Eddy, K. T., Dichtel, L. E., Lawson, E. A., Meenaghan, E.,  . . .  Miller, K. K. (2016). Bone density, body composition, and psychopathology of anorexia nervosa spectrum disorders in DSM-​ IV vs DSM-​ 5. International Journal of Eating Disorders. doi:  10.1002/​eat.22603 [Epub ahead of print]. Schreiber-​ Gregory, D. N., Lavender, J. M., Engel, S. G., Wonderlich, S. A., Crosby, R. D., Peterson, C. B.,   .  .  .  Mitchell, J. E. (2013). Examining duration of binge eating episodes in binge eating disorder. International Journal of Eating Disorders, 46, 810–​814. Silén, Y., Raevuori, A., Jüriloo, E., Tainio, V. M., Marttunen, M., & Keski-​Rahkonen, A. (2015). Typical versus atypical anorexia nervosa among adolescents: Clinical characteristics and implications for ICD-​ 11. European Eating Disorders Review, 23, 345–​351. Stice, E., Marti, C. N., & Rohde, P. (2013). Prevalence, incidence, impairment, and course of the proposed DSM-​5 eating disorder diagnoses in an 8-​year prospective community study of young women. Journal of Abnormal Psychology, 122, 445–​457. Striegel-​Moore, R. H., Dohm, F. A., Hook, J. M., Schreiber, G. B., Crawford, P. B., & Daniels, S. R. (2005). Night eating syndrome in young adult women:  Prevalence and correlates. International Journal of Eating Disorders, 37, 200–​206.

Striegel-​ Moore, R. H., Franko, D. L., May, A., Ach, E., Thompson, D., & Hook, J. M. (2006). Should night eating syndrome be introduced in the DSM? International Journal of Eating Disorders, 39, 544–​549. Striegel-​Moore, R. H., Franko, D. L., Thompson, D., Affenito, S., & Kraemer, H. C. (2006). Night eating: Prevalence and demographic correlates. Obesity Research, 14, 139–​147. Striegel-​Moore, R. H., Franko, D. L., Thompson, D., Affenito, S., May, A., & Kraemer, H. C. (2008). Exploring the typology of night eating syndrome. International Journal of Eating Disorders, 41, 411–​418. Striegel-​Moore, R. H., Franko, D. L., Thompson, D., Barton, B., Schreiber, G. B., & Daniels, S. R. (2005). An empirical study of the typology of bulimia nervosa and its spectrum variants. Psychological Medicine, 35, 1563–​1572. Stunkard, A. J., Allison, K. C., Geliebter, A., Lundgren, J. D., Gluck, M. E., & O’Reardon, J. P. (2009). Development of criteria for a diagnosis:  Lessons from the night eating syndrome. Comprehensive Psychiatry, 50, 391–​399. Stunkard, A. J., Berkowitz, R., Wadden, T. A., Tanrikut, C., Reiss, E., & Young, L. (1996). Binge eating disorder and the night-​eating syndrome. International Journal of Obesity and Related Metabolic Disorders, 20, 1–​6. Stunkard, A. J., Grace, W. J., & Wolff, H. G. (1955). The night-​eating syndrome:  A  pattern of food intake among certain obese patients. American Journal of Medicine, 19, 78–​86. Sullivan, P. F., Bulik, C. M., & Kendler, K. S. (1998). The epidemiology and classification of bulimia nervosa. Psychological Medicine, 28, 599–​610. Swanson, S. A., Horton, N. J., Crosby, R. D., Micali, N., Sonneville, K. R., Eddy, K., & Field, A. E. (2014). A latent class analysis to empirically describe eating disorders through developmental stages. International Journal of Eating Disorders, 47, 762–​772. Tholin, S., Lindroos, A. K., Tynelius, P., Akerstedt, T., Stunkard, A. J., Bulik, C. M., & Rassmussen, F. (2009). Prevalence of night eating in obese and non-​obese twins. Obesity, 17, 1050–​1055. Tobin, D. L. Griffing, A., & Griffing, S. (1997). An examination of subtype criteria for bulimia nervosa. International Journal of Eating Disorders, 22, 179–​186.

Tzischinsky, O., & Latzer, Y. (2004). Nocturnal eating: Prevalence, features, and night sleep among binge eating disorder and bulimia nervosa patients in Israel. European Eating Disorders Review, 12, 101–​109. Vinai, P., Cardetti, S., Studt, S., Carpegna, G., Ferrato, N., Vallauri, P.,  . . .  Manconi, M. (2014). Clinical validity of the descriptor: “Presence of a belief that one must eat in order to get to sleep” in diagnosing the Night Eating Syndrome. Appetite, 75, 46–​48. Vinai, P., Provini, F., Antelmi, E., Marcatelli, M., Cardetti, S., Vinai, L.,  . . .  Allison, K. C. (2015). Alexithymia is not related to severity of night eating behavior:  a useful distinction from other eating disorders. Eating Behaviors, 17, 94–​98. Wade, T. D. (2007). A retrospective comparison of purging type disorders:  Eating disorder not otherwise specified and bulimia nervosa. International Journal of Eating Disorders, 40, 1–​6. Wade, T. D., Bergin, J. L., Tiggemann, M., Bulik, C. M., & Fairburn, C. G. (2006). Prevalence and long-​term course of lifetime eating disorders in an adult Australian twin cohort. Australian and New Zealand Journal of Psychiatry, 40, 121–​128. Wade T. D., Crosby, R., & Martin, N. G. (2006). Use of latent profile analysis to identify eating disorder phenotypes in an adult Australian twin cohort. Archives of General Psychiatry, 63, 1377–​1384. Wells, A., & Matthews, G. (1994). Attention and emotion: A clinical perspective. Hove, UK: Erlbaum. Winkelman, J. W. (2003). Treatment of nocturnal eating syndrome and sleep-​related eating disorder with topiramate. Sleep Medicine, 4, 243–​246. Winkelman, J. W. (2006). Efficacy and tolerability of open-​label topiramate in the treatment of sleep-​related eating disorder: A retrospective case series. Journal of Clinical Psychiatry, 67, 1729–​1734. Wonderlich, S. A., Joiner, T. E., Keel, P. K., Williamson, D. A., & Crosby, R. D. (2007). Eating disorder diagnoses: Empirical approaches to classification. American Psychologist, 62, 167–​180. Zamora, M. L. C., Bonaechea, B. B., Sánchez, F. G., & Rial, B. R. (2005). Orthorexia nervosa: A new eating behavior disorder? Actas Españolas de Psiquiatría, 33, 66–​68.

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C H A PT E R

 Eating Disorders and Problematic Eating Behaviors After Bariatric Surgery

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Molly Orcutt, Kristine Steffen, and James E. Mitchell

Abstract Bariatric surgery is the most effective treatment for severe obesity and its weight-​related comorbidities. As the use of bariatric surgery has increased, concerns have arisen about problematic eating behaviors (EBs) and eating disorders (EDs) in this population. This chapter describes the current literature detailing EDs and problematic EBs and weight control practices (WCPs) in the post-​bariatric-​surgery population. It begins with a description of EDs in this population. Next, it describes problematic EBs, followed by a review of postoperative gastrointestinal problems that influence EBs. Third, it reviews the WCPs that can evolve. Finally, it describes models of “food addiction” as they apply to eating-​related pathology in the post-​bariatric-​surgery population. Key Words:  Eating disorder, Obesity, Bariatric surgery, Food addiction, Eating behavior

Introduction

Obesity is increasing in prevalence worldwide, and is associated with numerous comorbidities including type 2 diabetes mellitus, sleep apnea, and cardiovascular disease (Picot et al., 2009). The most effective treatment for severe obesity and its weight-​ related comorbidities is bariatric surgery (Colquitt, Pickett, Loveman, & Frampton, 2014). At this time, the most frequently performed bariatric surgeries are sleeve gastrectomy (SG), Roux-​ en-​ Y gastric bypass (RYGB), and laparoscopic adjustable gastric banding (LAGB). The least common of these surgeries, LAGB, accounts for approximately 5.7% of bariatric procedures performed in the United States (ASMBS, 2016) and involves placing a band at the top of the stomach to anatomically restrict food intake. This surgery is being used less frequently over time, and many centers in the United States have stopped offering this procedure given problems with lack of adequate weight loss and long-​ term complications. Roux-​ en-​ Y gastric bypass accounts for approximately 23.1% of procedures performed in the Untied States (ASMBS, 458

2016) and involves surgically partitioning the stomach to create a small gastric pouch, which is connected to a distal portion of the small intestine, bypassing the first part of the small intestine, the duodenum. Finally, SG involves surgically dividing the stomach vertically to reduce its size by about 75%. Sleeve gastrectomy is currently the most common bariatric surgery performed in the United States and accounts for approximately 53.8% of bariatric surgeries performed (ASMBS, 2016). Historically, weight loss and remission of weight-​ related comorbidities were thought to be a result of purely anatomical changes secondary to the surgery (Noel, Still, Argyropoulos, Edwards, & Gerhard, 2016). For example, the decrease in stomach size in LAGB, RYGB, and SG leads to earlier satiety and an expected decrease in intake. Additionally, the alteration of the digestive tract in RYGB causes a reduction in the absorption of nutrients, leading to weight loss. However, a growing body of research suggests that the mechanisms by which the RYGB, and likely the SG, lead to weight loss, are through other physiological changes.

Postsurgical alterations in gastrointestinal (GI) physiology include changes in the activity of certain gut hormones, bile acids, inflammatory factors, and gut bacteria (microbiome) (Fouladi, Mitchell, Wonderlich, & Steffen, 2016; Makaronidis & Batterham, 2016; Sweeney & Morton, 2013). Emerging evidence suggests that these alterations in physiology are involved in bidirectional communication with the central nervous system (Cryan & Dinan, 2012). Further understanding of the mechanisms of weight loss and disease remission are likely to be an important focus of research, as evidence suggests that postsurgery outcomes may be at least partially dependent on the changes that occur in these variables and the interactions among them. Weight-​related outcomes following surgery range from substantial weight loss to modest or minimal weight loss and, rarely, excessive weight loss (Courcoulas et al., 2013). For example, median weight loss following RYGB is approximately 30% of baseline body weight within 3 years post-​surgery (Courcoulas et  al., 2013). In comparison, median weight loss of baseline body weight at 3 years with LAGB in the same study was 15.9% (Courcoulas et  al., 2013). Weight loss is followed by regain of variable amounts of weight in approximately 20%–​ 30% of individuals (Courcoulas et  al., 2013; de Hollanda et al., 2015; Hsu et al., 1998). Although less common, it is being increasingly recognized in clinical settings and a limited body of literature that a small subset of patients are diagnosed with eating disorders post bariatric surgery (Conceicao et al., 2013; Marino et al., 2012; Opozda, Chur-​Hansen, & Wittert, 2016) In particular, the current evidence suggests that the prevalence of eating disorder diagnosis in the post-​bariatric surgery population ranges from 0 to 17% (Opozda et  al., 2016). Indeed, a growing body of research indicates that traditional eating disorders (EDs) such as anorexia nervosa (AN) and bulimia nervosa (BN), can occur after bariatric surgery and in some cases patients present for treatment with very low BMIs and significant medical comorbidities (Conceicao et al., 2013; Marino et al., 2012). In addition, binge eating disorder (BED) is also common prior to bariatric surgery (4%–​49%) (Kalarchian et  al., 2016; Niego, Kofman, Weiss, & Geliebter, 2007; Opozda et al., 2016), and in a smaller percentage of patients (0–​17%) (Kalarchian et  al., 2016; Opozda et  al., 2016), the disorder either persists or develops de novo postoperatively. Some evidence suggests that eating with a sense of loss of control, a hallmark feature of BED, following bariatric surgery is the most

robust predictor of poor postsurgical weight outcomes (Kalarchian et al., 2016; Meany, Conceicao, & Mitchell, 2014). Eating disorders can have a significant impact on health and functioning post-​surgery. Furthermore, eating disorders, in particular AN and BN, may result in serious medical complications associated with low BMI and compensatory behaviors (Conceicao et al., 2013; Marino et al., 2012). Other eating disorder behaviors or problematic eating behaviors, such as loss of control (LOC) eating and grazing, may be associated with suboptimal weight loss, which may negatively influence remission of comorbidities associated with obesity (Conceicao, Bastos, et  al., 2014; Conceicao, Mitchell, Engel, et al., 2014; Conceicao, Mitchell, Vaz, et al., 2014; Conceicao, Utzinger, & Pisetsky, 2015; Kalarchian et al., 2016; Meany et al., 2014). In this chapter, we describe the current literature detailing EDs and problematic eating behaviors (EBs) and weight control practices (WCPs) in the post-​bariatric surgery population. We begin our discussion with a description of EDs in this population. Next, we describe problematic EBs, followed by a review of postoperative gastrointestinal problems that influence EBs. Third, we review the WCPs that can evolve. Finally, we describe models of “food addiction” as they apply to eating-​related pathology in the post-​bariatric surgery population.

Binge Eating Disorder

Binge eating disorder (BED) is the most common eating disorder in general (Swanson, Crow, Le Grange, Swendsen, & Merikangas, 2011), as well as the disorder most often diagnosed in the bariatric surgery population (Kalarchian et  al., 2016; Opozda et al., 2016). In the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM 5)  BED is defined as recurrent objective binge eating (OBE) episodes occurring at least once weekly for 3  months without the presence of compensatory behaviors (American Psychiatric Association [APA], 2013). An OBE is defined as the ingestion of an objectively large amount of food in a discrete period of time that is larger than what most people would eat in a similar situation. A  sense of LOC and distress regarding the OBE must be present. Additionally, DSM-​5 criteria specify that the OBEs need to be associated with at least three of the five following features:  eating more rapidly than normal; eating large amounts of food when not hungry; eating until uncomfortably full; eating alone due to embarrassment about how much one Orcut t, Steffen, Mitchell

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is eating; and feeling guilty, disgusted, or depressed after the OBE episode. Prevalence rates of BED vary widely from 4% to 49% among candidates for bariatric surgery (Kalarchian et  al., 2016; Niego et  al., 2007; Opozda et al., 2016). This wide range likely reflects to some extent the changes in diagnostic criteria from previous versions of the DSM to the current version, but primarily is attributable to the varying assessment methods and study designs used in generating these estimates (Conceicao, Utzinger et al., 2015; Kalarchian et al., 2016; Opozda et al., 2016). Research has been somewhat mixed as to whether or not preoperative BED is a predictor of outcomes post-​surgery, with a majority of studies not finding an association (Meany et  al., 2014). However, research does suggest that the BED diagnosis is associated with increased rates of comorbid psychopathology, which is concerning due to the association of multiple comorbidities and poor outcomes postoperatively (van Hout, Verschure, & van Heck, 2005). After surgery, BED diagnosis is further complicated by the surgically induced anatomical and physiological restrictions on the amount of food that can be ingested. Most patients become unable to ingest objectively large amounts of food in a discrete period of time (Meany et al., 2014). Therefore, it is impossible for individuals to ingest the amount of food necessary to meet criteria for an OBE episode, at least initially, after surgery. It has been argued that the amount of food necessary to meet criteria for an OBE should be considered in the context of the time since surgery and the type of surgery. The literature does suggest that the LOC over eating more modest amounts of food can continue after surgery, or more rarely can develop after surgery, and some have speculated that the experience of LOC, rather than the amount of food ingested, may be more important in defining binge eating (BE) (Meany et  al., 2014). Loss of control over eating smaller amounts of food has been termed subjective BE (SBE) (Conceicao, Mitchell, Vaz, et  al., 2014). Some have suggested that it may be important to identify both SBE and OBE, especially post-​ surgery (Colles, Dixon, & O’Brien, 2008a; Conceicao, Bastos, et  al., 2014; White, Kalarchian, Masheb, Marcus, & Grilo, 2010). Thus, future research should strive toward operationalizing appropriate diagnostic criteria for BED in the post-​bariatric surgery population and developing psychological and/​or pharmacological interventions to target symptoms of this disorder. 460

Conceicao and colleagues assessed both SBE and OBE in patients after bariatric surgery, and found that no OBE episodes were reported at 6  months after surgery. However, OBE episodes were reported after 2 years (Conceicao, Mitchell, Vaz, et al., 2014). Thus, the amount of food that can be ingested by individuals post-​ surgery does appear to increase over time (Sarwer et  al., 2008). Although OBE episodes are infrequent, SBE episodes appear to be quite common after surgery. In fact, Conceicao et  al. reported all individuals that had undergone restrictive and malabsorptive procedures reported having SBE episodes (Conceicao, Mitchell, Vaz, et al., 2014). Given the low frequency of OBE episodes after surgery, the prevalence of BED is fairly low, ranging from 0 to 17.2% (Opozda et  al., 2016). This is in contrast to the fairly high levels of LOC eating prior to and after bariatric surgery. Indeed, rates of LOC in bariatric patients prior to surgery range from 13.3% to 61% (Colles, Dixon, & O’Brien, 2008b; Devlin et  al., 2016; White et  al., 2010), and rates vary from 11.7% to 39% after surgery (Conceicao, Bastos, et al., 2014; Devlin et al., 2016; White et al., 2010). Rates appear to decrease as time from surgery increases with the lowest rate of LOC (11.7%) found 3  years postoperatively (Devlin et al., 2016). While the definitions of BE and LOC vary across studies, a growing body of literature indicates that the presence of LOC eating after surgery may be associated with worse weight outcomes (Colles et al., 2008a; Mitchell et al., 2016; White et al., 2010). In fact, postoperative LOC eating has been one of the only consistent predictors of weight loss outcomes following bariatric surgery. Therefore, LOC eating may be important to identify and treat postoperatively.

Bulimia Nervosa

Bulimia nervosa is defined in DSM-​5 as recurrent episodes of OBEs with a sense of LOC, recurrent inappropriate compensatory behaviors to prevent weight gain, and overvaluation of shape and weight (APA, 2013). Both OBEs and compensatory behaviors must occur at least once weekly for 3 months. Prior to surgery, studies suggest that the prevalence of BN is low, with one study reporting that approximately 0–​3% of individuals met DSM-​ IV criteria prior to surgery (de Zwaan et al., 2010; Mitchell et  al. 2015; Opozda et  al., 2016). It has been suggested that estimates of prevalence prior to surgery may be influenced by the patients’ motivation to maintain surgery eligibility, and therefore

Problematic Eating Behaviors After Bariatric Surgery

some patients may minimize or deny symptoms of BN (Mitchell et al., 2015; Opozda et al., 2016). There are few studies examining the effects of a history of or current diagnosis of BN on postoperative outcomes. A study by de Zwann and colleagues suggested that BN prior to surgery is associated with an increased likelihood of compensatory vomiting and SBEs after surgery (de Zwaan et  al., 2010). Similar to the diagnosis of BED after surgery, the diagnosis of BN after surgery is complicated by the majority of individuals being incapable of engaging in traditional OBEs for a period of time after surgery. Yet, as the study by de Zwaan and colleagues reported, SBEs and self-​induced vomiting still occur (de Zwaan et al., 2010). Case reports have also identified individuals who reported OBEs and/​or SBEs followed by self-​ induced vomiting (Conceicao, et al., 2013; Mitchell, 1985). Postoperative cases of BN are thought to be rare. A recent large prospective longitudinal study reported a prevalence rate of 0 at 2 and 3 years after surgery (Kalarchian et al., 2016). Case reports indicate that individuals who develop BN after bariatric surgery in general tend to be much older and have a later age of onset than individuals who have BN without a history of bariatric surgery (Conceicao, et al., 2013). The development of BN postoperatively may be influenced or triggered by postoperative experiences, and it is critical to consider behaviors that occur in the postoperative period in the context of the type of surgery and the length of time since surgery. For example, it is common for patients to have episodic vomiting after surgery (Kalarchian et  al., 2014). Vomiting may begin spontaneously or may be used in a voluntary manner intended to ease discomfort, but it can evolve into a mechanism of weight control (de Zwaan et al., 2010). To discern whether vomiting is a compensatory behavior, the reasons for and expected outcomes of vomiting should be elicited. Dumping is excessive diarrhea that occurs after ingestion of sweets and/​or large amounts of food. Dumping is another behavior that occurs commonly after surgery, but case reports indicate that it can become a compensatory behavior (Conceicao et  al., 2013). Assessment of whether dumping is self-​induced for weight loss or weight control is critical in determining whether it is a compensatory behavior. Evidence regarding the misuse of laxatives and diuretics after surgery is scarce. The available research suggests that use of laxatives or diuretics for weight control in this population is rare with a

prevalence of 0–​2% (Devlin et al., 2016), but more systematically collected data are needed. As with other compensatory behaviors, the motivation for using laxatives and diuretics must be elicited.

Anorexia Nervosa

Anorexia nervosa is characterized by restriction of energy intake leading to significantly low body weight (APA, 2013). The DSM-​ 5 defines significantly low body weight as a weight less than minimally normal in the context of age, sex, development, and physical health. Also, AN is distinguished by an intense fear of gaining weight and overvaluation of shape and weight. Individuals seeking bariatric surgery are obese, and would not meet criteria for diagnosis of AN immediately preoperatively. There are insufficient data examining lifetime history of AN in individuals seeking bariatric surgery. Postoperative individuals with AN-​like presentations have been described in the literature. In fact, these patients appear to present to ED specialized care facilities fairly frequently. Case reports and series have described patients who develop symptoms of AN, including dietary restriction, significant weight loss, fear of weight gain, and disturbance in evaluation of shape and weight (Conceicao et al., 2013). Relative to patients with traditional AN, individuals who have a history of bariatric surgery are usually at a higher weight, are older in age, and have a later age of onset at the time of presentation for treatment (Conceicao et al., 2013). Determination of low weight for diagnosis in post-​bariatric surgery patients should include evaluation of weight trajectory, EBs, and the physical health of the individual, since some of these individuals may be in a state of starvation after massive weight loss despite having a BMI greater than 18.5 kg/​m2 (Conceicao, Mitchell, Engel, et al., 2014; Conceicao et al., 2013). As in BN, it has been suggested that postoperative experiences may trigger the development of AN symptoms. For example, the experience of rapid weight loss is often followed by a weight plateau, wherein the individual desires further weight loss, may trigger the development of AN symptoms. Further, postoperative recommendations by physicians and other medical professionals usually include strict dietary restriction, and the directive to cut food in small pieces, and avoid of certain food groups (Conceicao et al., 2013). These behaviors are similar to the behaviors and rituals seen in individuals with AN and presumably may trigger the development of AN symptoms in some postbariatric Orcut t, Steffen, Mitchell

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surgery individuals. Distinguishing the motivation behind these behaviors can help one determine whether the behavior is adaptive or pathological. In this population, fear of suboptimal weight loss or weight regain is realistic. Recommendations after surgery likely include frequent weighing and monitoring of the various factors (e.g., exercise and food intake) that may influence weight. Furthermore, assessment of shape concerns in the post-​bariatric surgery population are complicated by frequent concerns about excessive skin (Ellison, Steffen, & Sarwer, 2015). Excessive loose or hanging skin is a frequent result of rapid and substantial weight loss. Greater body dissatisfaction and depressive symptoms have been associated with the development of excessive skin, and traditional assessment methods used to measure body dissatisfaction may not measure the specific body and/​or shape concerns of this population (Ramalho et al., 2015).

Night Eating Syndrome and Nocturnal Sleep-​Related Eating Disorder

In the DSM-​5, night eating syndrome (NES) is designated as an otherwise specified feeding or eating disorder (OSFED) (APA, 2013). Night eating syndrome is characterized by recurrent, conscious episodes of night eating occurring after awakening from sleep and/​or ingestion of greater than 25% of food after the evening meal. Episodes must occur at least twice weekly and cause distress to meet criteria. Prior to surgery, prevalence ranges from 1.9% to 17.7% (Allison et al., 2006; Mitchell et al., 2015), and preoperative diagnosis of NES may be associated with preoperative diagnosis of BED (Mitchell et  al., 2015). After surgery, evidence suggests NES rates may either continue at similar levels or decrease (Adami, Meneghelli, & Scopinaro, 1999; Colles & Dixon, 2006; Colles et al., 2008a; Devlin et al., 2016). Night eating syndrome, before or after surgery, has not been associated with adverse weight loss outcomes (Devlin et  al., 2016; de Zwaan, Marschollek, & Allison, 2015). Nocturnal sleep-​ related eating disorder (NSRED), a parasomnia, differs from NES in that it occurs during periods of partial arousal and reduced awareness of the behavior (APA, 2013). Awareness of eating episodes may only occur after awakening the next morning and finding that food is missing or cooking appliances have been used (Winkelman, 1998). Substances ingested may be edible or inedible. Associated with the use of medications, including zolpidem and quetiapine, NSRED also occurs as a primary sleep disorder. The prevalence of NSRED 462

is not well defined in bariatric surgery populations and is further complicated by diagnostic overlap with NES (Devlin et  al., 2016). Distinguishing between NES and NSRED is vital, because the disorders have different treatment approaches (Vinai et al., 2015).

Problematic Eating Behaviors

The bariatric surgery literature has identified multiple EBs that may have an impact on weight outcomes but probably do not represent distinct EDs. Nonetheless, identification of these behaviors may be important to optimize weight loss outcomes post-​surgery. However the lack of adequate development in this nomenclature will become obvious.

Grazing

What is often referred to as “grazing” has been the focus of emerging research in the bariatric surgery literature. Although the term “grazing” has a disparaging connotation, it is the most widely used term currently. Various definitions and criteria have also been proposed to describe or diagnose this behavior, which is commonly defined as repetitively eating small amounts of food during the day in an unplanned manner (Conceicao, Mitchell, Engel, et al., 2014). This behavior may or may not occur in response to sensations of hunger. Repetitive eating, as used in defining grazing, is eating more than twice in the same time period during the day without prolonged gaps between eating episodes. In one recent report, grazing was divided into two subtypes (Conceicao, Mitchell, Engel, et  al., 2014). The first subtype is termed “compulsive grazing.” Compulsive grazing involves LOC eating wherein the individual attempts to resist eating, but the individual is unable to resist, and returns to eating small amounts of food. Noncompulsive grazing is characterized by repetitively eating without a sense of LOC. Rather, the eating is without mindfulness. Grazing differs from an OBE episode because the amount of food is smaller, the time period is not limited, and the eating episode is unplanned. Subjective BE episodes differ from grazing because an SBE must occur in a discrete time period. Although post-​bariatric surgery recommendations include eating small meals and snacks throughout the day, the meals and snacks are presumed to be planned, demarcated in response to hunger and satiety cues, and in accordance with nutritional needs (Conceicao et al., 2015). These recommendations clearly differ from grazing behaviors.

Problematic Eating Behaviors After Bariatric Surgery

Determining the prevalence of grazing, its effects on weight outcomes, and its associated features has been complicated by competing assessment methods and definitions. Presurgery prevalence data is limited, but in a study by Colles and colleagues it was found to be 26.4% (Colles et  al., 2008a). After surgery, the prevalence may increase to 46.6% (Kofman, Lent, & Swencionis, 2010). In the limited data available, grazing following surgery has been linked to reduced weight loss or increased weight regain (Conceicao, Mitchell, Engel, et  al., 2014). Such eating behavior, over time, is thought to lead to eating excess calories. Emerging evidence points to a possible association between grazing, LOC eating, and BE, with comorbidities including symptoms of depression and other problematic EBs (Colles et al., 2008a; Kofman et al., 2010).

Picking and Nibbling

Other problematic EBs may be related to grazing, since these behaviors also involve repetitive eating. Terms used have included “picking or nibbling” and “snacking.” Picking or nibbling is defined in the Eating Disorder Examination as eating food between meals and snacks that occurs in a repetitive and unplanned manner (Fairburn & Cooper, 2000). The amount of food consumed should be uncertain prior to the episode and should not be trivial. Nibbling, in most definitions, can be differentiated from grazing because it does not involve LOC, and occurs between meals or snacks. This is in contrast to grazing, which often leads to skipped meals. The initial uncertainty regarding the amount of food to be eaten also separates nibbling from grazing in the current nomenclature. Prior to surgery, the prevalence of picking and nibbling behaviors ranges from 29.5% to 53.0% (Busetto et  al., 2002; Conceicao, Mitchell, Vaz, et al., 2014; Devlin et al., 2016). After surgery, the prevalence has been estimated to occur in the range of 32.2% to 47.1% (Conceicao, Mitchell, Vaz, et al., 2014; Devlin et al., 2016; de Zwaan et al., 2010). Three studies have reported no association between picking and nibbling and weight loss (Busetto et al., 2002; Devlin et al., 2016; de Zwaan et al., 2010), while another study found a significant association between picking or nibbling and poorer weight loss outcomes (Conceicao, Mitchell, Vaz, et al., 2014).

Emotional Eating

Emotional eating is a term that has been used to describe eating in response to emotional stress

or eating during stressful life situations (Canetti, Berry, Elizur, 2009). It was estimated to occur in bariatric surgery candidates at a rate of 38%–​ 59% (Opolski, Chur-​Hansen, & Wittert, 2015). Whether this is a unique behavior is debatable, and this points to the lack of differentiation is this nomenclature. However, one study found emotional eating was more common among women than men (Gade, Rosenvinge, Hjelmesaeth, & Friborg, 2014). The link between emotional eating and weight outcomes following surgery is unclear. Some studies have reported no association between preoperative and postoperative emotional eating and subsequent weight loss, while others reported poorer weight loss outcomes (Opozda et al., 2016). Emotional eating has been associated with other problematic EBs, including BED (Banerjee, Ding, Mikami, & Needleman, 2013; Fischer et al., 2007; Mathus-​Vliegen, 2007).

High-​Calorie Fluid Consumption

A small number of studies have examined excessive high-​calorie fluid or soft food consumption after bariatric surgery. Reported prevalence rates in one small study ranged from 33% prior to surgery and 17% after surgery (Hsu, Betancourt, & Sullivan, 1996). It has been suggested by some that consuming large amounts of highly caloric fluids or soft food allows patients to avoid the discomfort related to the fullness that results from excess food ingestion but to still consume calories (Hsu et al., 1998; Hsu et al., 1996) Studies have suggested that high-​calorie fluid consumption is associated with reduced weight loss and/​or greater weight regain, but research in this area has been sparse (Brolin, Robertson, Kenler, & Cody, 1994; Hsu et  al., 1996; Sugarman et  al., 1992; Yale, 1989; Yale & Weiler, 1991).

Sweet Eating

Another problematic EB that has been described is characterized by eating excessive amounts of high-​ calorie dessert-​type foods and is termed “sweet eating.” Standard definitions of this behavior have not been established, and its validity has been debated for years. Preoperative prevalence is estimated to be between 30.4% and 43.8% (Busetto et  al., 2002; Busetto et  al., 2005). In these studies, sweet eating was defined as a patient craving simple carbohydrates, with cravings present continuously or triggered by emotional or physiological situations (Busetto et  al., 2002). Postoperative sweet eating was originally thought to be influenced by the Orcut t, Steffen, Mitchell

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type of surgery; however, studies report significant percentages of individuals engaging in sweet eating after RYGB and LAGB. In fact, postoperative prevalence of sweet eating is estimated to be 36% to 62% (Leite Faria, de Oliveira Kelly, Pereira Faria, & Kiyomi Ito, 2009; Lindroos, Lissner, & Sjostrom, 1996). The current literature does not suggest an association between sweet eating and poorer weight loss outcomes postoperatively (Hudson et al., 2002; Lindroos et al., 1996). The high prevalence of individuals engaging in the behavior and the lack of effect on weight loss outcomes brings into question whether this behavior is, in fact, distinct or pathological.

Chewing and Spitting

Another problematic EB occurring in bariatric surgery patients following surgery is chewing and spitting out food. In contrast to characterizations of chewing and spitting in the traditional eating disorder population, studies have reported that chewing and spitting in patients post bariatric surgery is more often unrelated to weight control or psychological distress (de Zwaan et al., 2010). Instead, chewing and spitting is a behavior used to be able to taste certain foods that are not tolerated well upon swallowing, since this may result in plugging. However, there have been case reports of individuals using chewing and spitting as a strategy to avoid weight gain (Conceicao et al., 2013).

Postoperative Gastrointestinal Problems

Postoperative GI problems may originate as an adverse effect from surgery, but case reports and series have indicated that GI problems, including dumping syndrome, vomiting, and plugging, may trigger ED symptoms in some individuals (Conceicao et al., 2013; Marino et al., 2012). The relationship between GI conditions and the development of ED symptoms is not fully understood. Future research into this link may allow for a better understanding of how EDs develop following bariatric surgery. Dumping syndrome, mentioned previously, is an adverse effect that may occur following RYGB. Dumping occurs shortly after a patient ingests excessive quantities of food or fluids containing high concentrations of carbohydrate or sugar (Berg & McCallum, 2016). Dumping is characterized by both vasomotor and gastrointestinal symptoms (Banerjee et al., 2013). Scoring systems have been used for diagnosis in the literature, most commonly Sigstad’s Diagnostic Index (Berg & McCallum, 464

2016). In the months following malabsorptive surgery, dumping syndrome is quite common and estimated to occur in 15.7% to 76% of individuals (Banerjee et al., 2013; Cawley, Sweeney, Kurian, & Beane, 2007; Mallory et  al., 1996; Sugerman et  al., 1987). It has been suggested that dumping syndrome symptoms may decrease as patients adapt their food choices and speed of food ingestion (Banerjee et al., 2013). Dumping syndrome is usually divided into two types, termed early and late. Early dumping syndrome symptoms is more likely to be used as a compensatory mechanism, as late dumping is associated with reactive hypoglycemia. Early dumping develops 10–​30 minutes after the ingestion of food, and is caused by the rapid transit of calorie-​dense food into the small intestine resulting in a hyperosmolar state leading to abrupt fluid shifts (Berg & McCallum, 2016). Symptoms of early dumping syndrome include abdominal cramping, nausea, vomiting, diarrhea, flushing, dizziness, lightheadedness, and rapid heart rate. Although early dumping leads to diarrhea, it has not been linked to increased weight loss after bariatric surgery (Banerjee et  al., 2013). As discussed earlier, there have been reports of dumping being used as a maladaptive compensatory behavior (Conceicao et al., 2013). What is termed late dumping syndrome follows food ingestion by 1 to 3 hours (Malik et al., 2016). It is caused by release of large amounts of insulin in response to the high blood glucose levels, resulting in reactive hypoglycemia, and for clarity purposes should be referred to as reactive hypoglycemia rather than dumping. The typical symptoms of late dumping syndromes include palpitations, anxiety, weakness, dizziness, lightheadedness, fatigue, hunger, and sweating. Severe reactive hypoglycemia can trigger glucose deprivation of the central nervous system. This state is potentially life threatening and has been termed “neuroglycopenia.” Serious neurological manifestations of this state may include slurred speech, confusion and blurred vision, tremors, loss of consciousness, seizures, focal neurological deficits, and death. As previously mentioned, vomiting is an additional side effect of surgery. It is reported after LAGB, RYGB, and SG (Himpens, Dapri, & Cadiere, 2006; Kalarchian et al., 2014). The vomiting that occurs unrelated to attempts to control weight may be spontaneous or may be self-​induced in response to discomfort after eating. The EBs that may lead to vomiting including eating intolerable foods, eating an excessive amount, improper

Problematic Eating Behaviors After Bariatric Surgery

chewing, eating rapidly, and plugging. Plugging, the feeling of food becoming stuck in the pouch, has been associated with vomiting but has not been associated with changes in weight loss outcomes (Conceicao, Mitchell, Vaz, et al., 2014). In shorter-​term (6  months or less) and longer-​term (up to 10 years) follow-​up studies, prevalence rates of vomiting after surgery range from 21% to 79% (Conceicao, Mitchell, Vaz, et  al., 2014; Powers, Perez, Boyd, & Rosemurgy, 1999). As mentioned earlier, vomiting may be a trigger for the development or redevelopment of eating disorder symptoms after surgery (Conceicao et al., 2013; Marino et al., 2012). In these individuals, vomiting may be used to compensate for food intake and for purposes of weight control.

Food Addiction

The term “food addiction” first appeared in the literature nearly 60  years ago (Randolph, 1956). There has been a reemergence of the use of this term and the study of this phenomenon, perhaps in response to the increasing prevalence of obesity worldwide. Some controversy has surrounded this terminology and whether patients can, in fact, develop an “addiction,” as classically defined, to food (Volkow, Wang, Tomasi, & Baler, 2013). It has been hypothesized that food addiction may be one of the many factors contributing to obesity and may resemble or be a variant of addictive disorders such as substance use disorders (Gearhardt, Corbin, & Brownell, 2016). This hypothesis evolved from the observation that the EBs of some individuals are similar to the behaviors observed in those with substance use disorder (Gearhardt, Corbin, & Brownell, 2009a; Volkow & O’Brien, 2007). Comparisons have been drawn between diagnostic criteria for BED and substance use disorder, specifically the loss of control seen in both disorders (Gearhardt, White, & Potenza, 2011). A subset of individuals with obesity, with and without BED, report significant levels of distress related to their EBs, cravings for food, consumption of food despite adverse consequences, difficulties controlling EB, giving up important activities due to food consumption, and/​or eating in larger amounts over longer time periods than intended (Gearhardt, Corbin, & Brownell, 2009b). These symptoms parallel diagnostic criteria for substance use disorders and led to the development of research regarding food addiction, including assessment methods, such as the Yale Food Addiction Scale (Gearhardt et al., 2009b).

A brief discussion of the neurobiological systems that drive feeding behaviors will allow a better understanding of how EBs could be compared to addictive behaviors. Feeding behavior is regulated by a complex system of central neural circuits that interact with signaling from peripheral structures, such as the GI tract and adipose tissue, to control food intake (Volkow et al., 2013). Feeding behavior is further characterized by the intertwined drives of homeostatic and hedonic needs, which motivate individuals to engage in feeding behaviors. The most widely studied and understood pathway involved in feeding behavior is the dopamine reward pathway (Volkow, Wang, Fowler, Tomasi, & Baler, 2012). Brain dopamine (DA) reward circuitry increases the likelihood of repeating behaviors that activate it when an individual is exposed to the same reinforcer (Volkow et al., 201). In this case, the pathway is reinforced by exposure to food or the surrounding environment of the food. The DA reward circuitry is connected to areas of the brain involved in self-​control, interoception, emotions, learning memory, habits, and routines. Thus, DA neurons are active in maintaining behaviors for survival. After frequent exposure, a reward becomes conditioned (Volkow et al., 2013). Conditioning allows neural stimuli linked to a reinforcer (artificial or natural) to increase DA in anticipation of reward. This creates a strong motivation to perform and continue behaviors needed to obtain the reward. For example, after conditioning has occurred, DA signaling occurs predicting the reward when a palatable food is viewed. This increases the motivation to perform behaviors that will result in consuming the food. In comparison to cues from food, drug cues are more powerful triggers of reinforcing behavior (Hebebrand et al., 2014; Volkow et al., 2013). The responses to food cues also differ because they are influenced by nutritional and physical status as well as the neuronal pathways that process stress and mood. Although food intake and drug use alter the same DA pathways, they alter them in different ways (Volkow et  al., 2013). Drug use has direct effects on the DA pathways, specifically in the nucleus accumbens (NAc) and ventral pallidum. In contrast, the effect of food occurs both directly and indirectly through central and peripheral signaling on the DA pathway with crucial involvement of the hypothalamus. Although the mechanisms are different, both drugs of abuse and eating behaviors serve to increase DA binding. Orcut t, Steffen, Mitchell

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The indirect pathways that are involved in the regulation of feeding behavior have contributions from peripheral signaling mechanisms (Volkow et  al., 2013). These mechanisms involve hypothalamic signaling in response to peptides and hormones. Orexigenic peptides and hormones, which include ghrelin, orexin, melanocortin, and neuropeptide Y, increase DA neuron activity to stimulate food intake. In contrast, anorexigenic peptides and hormones (e.g., leptin, insulin, glucagon-​like peptide-​1 [GLP-​1], cholecystokinin [CCK], peptide YY, galanin) inhibit DA neuron activity and DA release, inhibiting food intake. In some areas of the brain, neurons can express ghrelin, GLP-​1, insulin, leptin, melanocortin receptors, and orexin, further adding to the complexity of the regulation of feeding. Many other neurotransmitters have also been implicated in the regulation of food intake including acetylcholine, cannabinoids, DA, gamma-​ aminobutyric acid (GABA), glutamine, histamine, norepinephrine, opioids, and serotonin. Multiple signals and signaling pathways, although redundant, ensure that the messages of hunger or satiety are communicated. Despite robust signaling of homeostatic needs, some individuals with access to highly palatable food may override inhibitory signaling and eat large amounts of food, and this behavior can become recurrent. Research in animal models indicates highly palatable foods, foods high in sugar and fat, are especially rewarding and may lead to compulsive behaviors (Hebebrand et  al., 2014). Yet, the same link between a specific food or type of food has not been established in humans. Furthermore, the diet of humans who overeat is often varied and not restricted to one type of food or a specific nutrient. Indeed, evidence points to increased overeating behaviors with exposure to a range of palatable foods. A number of factors play a role in the consumption of food in humans including energy needs, food availability, social expectations, visual appeal, economics, incentives, palatability, alternative reinforcement, advertisements, and eating patterns of restriction and overeating. Although the effect of food and eating behavior in humans is less straightforward than in animals, imaging studies have supported involvement of the DA reward pathway in motivating feeding. Since there has not been a specific food substance linked to compulsive eating behavior, it has been suggested that the phenomenon may be more accurately described as an eating addiction. Indeed, the term “eating 466

addiction” emphasizes a behavioral component instead of a specific substance. Further differences between addiction to drugs and EBs have been shown with brain imaging studies (Hebebrand et  al., 2014). The imaging studies suggest that reward circuits are involved in the motivation for food, yet imaging studies have not explained how food intake becomes excessive or compulsive. Likewise, addiction to drugs is characterized by physical dependence on the drug and withdrawal symptoms when the drug is abruptly discontinued. A  withdrawal syndrome upon discontinuing certain foods has not been observed in humans although there are reports of this in animals. In summary, feeding behavior is regulated by a complex system of circuits in the central nervous system, which are influenced by peripheral signaling. Research indicates similarities between feeding behavior and drug addiction, but the research has also shown some key differences. Continued research is needed, especially in humans, to identify and understand the unique factors that affect compulsive eating behavior, especially the influence of the social context and homeostatic needs.

Conclusion

The purpose of this chapter was to summarize the current body of literature regarding EDs, problematic EBs and potentially problematic WCPs practices in individuals following bariatric surgery. Unfortunately, existing diagnostic and treatment options are limited by several factors including the lack of agreement regarding assessment methods and clear, accepted definitions. While it has been proposed that this population will likely require specialized treatment, evidence-​ based treatment guidelines and protocols have not been established. Furthermore, research has not consistently identified presurgery factors that may predict or be associated with the development of EDs after surgery. Future research must focus on establishing consensus regarding the terminology and diagnostic criteria used to describe eating pathology in this population. Furthermore, agreement is needed on assessment methods both prior to and following bariatric surgery. Such developments will allow the elaboration and testing of treatment guidelines. Finally, continued investigation is needed to clarify how preoperative EBs and EDs may influence postoperative outcomes including EBs, WCPs, and other eating pathology.

Problematic Eating Behaviors After Bariatric Surgery

References

Adami, G. F., Meneghelli, A., & Scopinaro, N. (1999). Night eating and binge eating disorder in obese patients. International Journal of Eating Disorders, 25, 335–​338. Allison, K. C., Wadden, T. A., Sarwer, D. B., Fabricatore, A. N., Crerand, C. E., Gibbons, L. M.,  . . .  Williams, N. N. (2006). Night eating syndrome and binge eating disorder among persons seeking bariatric surgery:  Prevalence and related features. Surgery for Obesity and Related Diseases, 2, 153–​158. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders:  DSM-​ 5. Washington, DC: Author. ASMBS. (2016, July). Estimate of bariatric surgery numbers, 2011–​2015. Retrieved August 10, 2016, from https://​asmbs. org/​resources/​estimate-​of-​bariatric-​surgery-​numbers Banerjee, A., Ding, Y., Mikami, D. J., & Needleman, B. J. (2013). The role of dumping syndrome in weight loss after gastric bypass surgery. Surgical Endoscopy, 27, 1573–​1578. Berg, P., & McCallum, R. (2016). Dumping syndrome:  A  review of the current concepts of pathophysiology, diagnosis, and treatment. Digestive Diseases and Sciences, 61, 11–​18. Brolin, R. E., Robertson, L. B., Kenler, H. A., & Cody, R. P. (1994). Weight loss and dietary intake after vertical banded gastroplasty and Roux-​en-​Y gastric bypass. Annals of Surgery, 220, 782–​790. Busetto, L., Segato, G., De Luca, M., De Marchi, F., Foletto, M., Vianello, M.,   .  .  .  Enzi, G. (2005). Weight loss and postoperative complications in morbidly obese patients with binge eating disorder treated by laparoscopic adjustable gastric banding. Obesity Surgery, 15, 195–​201. Busetto, L., Segato, G., De Marchi, F., Foletto, M., De Luca, M., Caniato, D.,  . . .  Enzi, G. (2002). Outcome predictors in morbidly obese recipients of an adjustable gastric band. Obesity Surgery, 12, 83–​92. Canetti, L., Berry, E. M., & Elizur, Y. (2009). Psychosocial predictors of weight loss and psychological adjustment following bariatric surgery and a weight-​ loss program:  The mediating role of emotional eating. International Journal of Eating Disorders, 42, 109–​117. Cawley, J., Sweeney, M. J., Kurian, M., & Beane, S.; New York State Bariatric Surgery Workgroup. (2007). Predicting complications after bariatric surgery using obesity-​related co-​ morbidities. Obesity Surgery, 17, 1451–​1456. Colles, S. L., & Dixon, J. B. (2006). Night eating syndrome:  Impact on bariatric surgery. Obesity Surgery, 16, 811–​820. Colles, S. L., Dixon, J. B., & O’Brien, P. E. (2008a). Grazing and loss of control related to eating:  Two high-​risk factors following bariatric surgery. Obesity (Silver Spring, Md), 16, 615–​622. Colles, S. L., Dixon, J. B., & O’Brien, P. E. (2008b). Loss of control is central to psychological disturbance associated with binge eating disorder. Obesity (Silver Spring, Md), 16, 608–​614. Colquitt, J. L., Pickett, K., Loveman, E., & Frampton, G. K. (2014). Surgery for weight loss in adults. Cochrane Database of Systematic Reviews, 8, CD003641. Conceicao, E., Bastos, A. P., Brandao, I., Vaz, A. R., Ramalho, S., Arrojado, F.,  . . .  Machado, P. P. (2014). Loss of control eating and weight outcomes after bariatric surgery: A study

with a Portuguese sample. Eating and Weight Disorders, 19, 103–​109. Conceicao, E., Mitchell, J. E., Engel, S. G., Machado, P. P., Lancaster, K., & Wonderlich, S. A. (2014). What is “grazing”? Reviewing its definition, frequency, clinical characteristics, and impact on bariatric surgery outcomes, and proposing a standardized definition. Surgery for Obesity and Related Diseases, 10, 973–​982. Conceicao, E., Mitchell, J. E., Vaz, A. R., Bastos, A. P., Ramalho, S., Silva, C.,  . . .  Machado, P. P. (2014). The presence of maladaptive eating behaviors after bariatric surgery in a cross sectional study: Importance of picking or nibbling on weight regain. Eating Behaviors, 15, 558–​562. Conceicao, E., Orcutt, M., Mitchell, J., Engel, S., Lahaise, K., Jorgensen, M.,  . . .  Wonderlich, S. (2013). Eating disorders after bariatric surgery: A case series. International Journal of Eating Disorders, 46, 274–​279. Conceicao, E., Utzinger, L. M., & Pisetsky, E. M. (2015). Eating disorders and problematic eating behaviours before and after bariatric surgery:  Characterization, assessment and association with treatment outcomes. European Eating Disorders Review, 23, 417–​425. Courcoulas, A. P., Christian, N. J., Belle, S. H., Berk, P. D., Flum, D. R., Garcia, L.,  . . .  Wolfe, B. M. (2013). Weight change and health outcomes at 3  years after bariatric surgery among individuals with severe obesity. JAMA, 310, 2416–​2425. Cryan, J. F., & Dinan, T. G. (2012). Mind-​altering microorganisms: The impact of the gut microbiota on brain and behaviour. Nature Reviews Neuroscience, 13, 701–​712. de Hollanda, A., Ruiz, T., Jimenez, A., Flores, L., Lacy, A., & Vidal, J. (2015). Patterns of weight loss response following gastric bypass and sleeve gastrectomy. Obesity Surgery, 25, 1177–​1183. de Zwaan, M., Hilbert, A., Swan-​Kremeier, L., Simonich, H., Lancaster, K., Howell, L. M.,  . . .  Mitchell, J. E. (2010). Comprehensive interview assessment of eating behavior 18–​ 35  months after gastric bypass surgery for morbid obesity. Surgery for Obesity and Related Diseases, 6, 79–​85. de Zwaan, M., Marschollek, M., & Allison, K. C. (2015). The night eating syndrome (NES) in bariatric surgery patients. European Eating Disorders Review, 23, 426–​434. Devlin, M. J., King, W. C., Kalarchian, M. A., White, G. E., Marcus, M. D., Garcia, L.,   .  .  .  Mitchell, J. E. (2016). Eating pathology and experience and weight loss in a prospective study of bariatric surgery patients:  3-​ year follow-​up. International Journal of Eating Disorders, 49, 1058–​1067. Ellison, J. M., Steffen, K. J., & Sarwer, D. B. (2015). Body contouring after bariatric surgery. European Eating Disorders Review, 23, 479–​487. Fairburn, C. G., & Cooper, Z. (2000). Eating disorder examination (14th ed., version 14.3). Oxford, UK: University of Oxford. Fischer, S., Chen, E., Katterman, S., Roerhig, M., Bochierri-​ Ricciardi, L., Munoz, D.,   .  .  .  le Grange, D. (2007). Emotional eating in a morbidly obese bariatric surgery-​ seeking population. Obesity Surgery, 17, 778–​784. Fouladi, F., Mitchell, J. E., Wonderlich, J. A., & Steffen, K. J. (2016). The contributing role of bile acids to metabolic improvements after obesity and metabolic surgery. Obesity Surgery, 26, 2492–​2502.

Orcut t, Steffen, Mitchell

467

Gade, H., Rosenvinge, J. H., Hjelmesaeth, J., & Friborg, O. (2014). Psychological correlates to dysfunctional eating patterns among morbidly obese patients accepted for bariatric surgery. Obesity Facts, 7, 111–​119. Gearhardt, A. N., Corbin, W. R., & Brownell, K. D. (2009a). Food addiction: An examination of the diagnostic criteria for dependence. Journal of Addiction Medicine, 3, 1–​7. Gearhardt, A. N., Corbin, W. R., & Brownell, K. D. (2009b). Preliminary validation of the Yale Food Addiction Scale. Appetite, 52, 430–​436. Gearhardt, A. N., Corbin, W. R., & Brownell, K. D. (2016). Development of the Yale Food Addiction Scale Version 2.0. Psychology of Addictive Behaviors, 30, 113–​121. Gearhardt, A. N., White, M. A., & Potenza, M. N. (2011). Binge eating disorder and food addiction. Current Drug Abuse Reviews, 4, 201–​207. Hebebrand, J., Albayrak, O., Adan, R., Antel, J., Dieguez, C., de Jong, J.,  . . .  Dickson, S. L. (2014). “Eating addiction,” rather than “food addiction,” better captures addictive-​like eating behavior. Neuroscience & Biobehavioral Reviews, 47, 295–​306. Himpens, J., Dapri, G., & Cadiere, G. B. (2006). A prospective randomized study between laparoscopic gastric banding and laparoscopic isolated sleeve gastrectomy: Results after 1 and 3 years. Obesity Surgery, 16, 1450–​1456. Hsu, L. K., Benotti, P. N., Dwyer, J., Roberts, S. B., Saltzman, E., Shikora, S.  . . .  Rand, W. (1998). Nonsurgical factors that influence the outcome of bariatric surgery:  A  review. Psychosomatic Medicine, 60, 338–​346. Hsu, L. K., Betancourt, S., & Sullivan, S. P. (1996). Eating disturbances before and after vertical banded gastroplasty:  A  pilot study. International Journal of Eating Disorders, 19, 23–​34. Hudson, S. M., Dixon, J. B., & O’Brien, P. E. (2002). Sweet eating is not a predictor of outcome after Lap-​Band placement:  Can we finally bury the myth? Obesity Surgery, 12, 789–​794. Kalarchian, M. A., King, W. C., Devlin, M. J., Marcus, M. D., Garcia, L., Chen, J. Y.,  . . .  Mitchell, J. E. (2016). Psychiatric disorders and weight change in a prospective study of bariatric surgery patients:  A  3-​ year follow-​ up. Psychosomatic Medicine, 78, 373–​381. Kalarchian, M. A., Marcus, M. D., Courcoulas, A. P., Cheng, Y., & Levine, M. D. (2014). Self-​report of gastrointestinal side effects after bariatric surgery. Surgery for Obesity and Related Diseases, 10, 1202–​1207. Kofman, M. D., Lent, M. R., & Swencionis, C. (2010). Maladaptive eating patterns, quality of life, and weight outcomes following gastric bypass: Results of an Internet survey. Obesity (Silver Spring), 18, 1938–​1943. Leite Faria, S., de Oliveira Kelly, E., Pereira Faria, O., & Kiyomi Ito, M. (2009). Snack-​ eating patients experience lesser weight loss after Roux-​en-​Y gastric bypass surgery. Obesity Surgery, 19, 1293–​1296. Lindroos, A. K., Lissner, L., & Sjostrom, L. (1996). Weight change in relation to intake of sugar and sweet foods before and after weight reducing gastric surgery. International Journal of Obesity and Related Metabolic Disorders, 20, 634–​643. Makaronidis, J. M., & Batterham, R. L. (2016). Potential mechanisms mediating sustained weight loss following Roux-​ en-​Y gastric bypass and sleeve gastrectomy. Endocrinology Metabolism Clinics of North America, 45, 539–​552.

468

Malik, S., Mitchell, J. E., Steffen, K., Engel, S., Wiisanen, R., Garcia, L., & Malik, S. A. (2016). Recognition and management of hyperinsulinemic hypoglycemia after bariatric surgery. Obesity Research & Clinical Practice, 10, 1–​14. Mallory, G. N., Macgregor, A. M., & Rand, C. S. (1996). The influence of dumping on weight loss after gastric restrictive surgery for morbid obesity. Obesity Surgery, 6, 474–​478. Marino, J. M., Ertelt, T. W., Lancaster, K., Steffen, K., Peterson, L., de Zwaan, M., & Mitchell, J. E. (2012). The emergence of eating pathology after bariatric surgery:  A  rare outcome with important clinical implications. International Journal of Eating Disorders, 45, 179–​184. Mathus-​Vliegen, E. M. (2007). Long-​term health and psychosocial outcomes from surgically induced weight loss: Results obtained in patients not attending protocolled follow-​up visits. International Journal of Obesity, 31, 299–​307. Meany, G., Conceicao, E., & Mitchell, J. E. (2014). Binge eating, binge eating disorder and loss of control eating: Effects on weight outcomes after bariatric surgery. European Eating Disorders Review, 22, 87–​91. Mitchell, J. E. (1985). Bulimia with self-​induced vomiting after gastric stapling. The American Journal of Psychiatry, 142, 656. Mitchell, J. E., Christian, N. J., Flum, D. R., Pomp, A., Pories, W. J., Wolfe, B. M.,  . . .  Belle, S. H. (2016). Postoperative behavioral variables and weight change 3 years after bariatric surgery. JAMA Surgery, 151, 752–​757. Mitchell, J. E., King, W. C., Courcoulas, A., Dakin, G., Elder, K., Engel, S.,  . . .  Wolfe, B. (2015). Eating behavior and eating disorders in adults before bariatric surgery. International Journal of Eating Disorders, 48, 215–​222. Niego, S. H., Kofman, M. D., Weiss, J. J., & Geliebter, A. (2007). Binge eating in the bariatric surgery population: A review of the literature. International Journal of Eating Disorders, 40, 349–​359. Noel, O. F., Still, C. D., Argyropoulos, G., Edwards, M., & Gerhard, G. S. (2016). Bile acids, FXR, and metabolic effects of bariatric surgery. International Journal of Obesity, 2016, 4390254. Opolski, M., Chur-​ Hansen, A., & Wittert, G. (2015). The eating-​related behaviours, disorders and expectations of candidates for bariatric surgery. Clinical Obesity, 5, 165–​197. Opozda, M., Chur-​Hansen, A., & Wittert, G. (2016). Changes in problematic and disordered eating after gastric bypass, adjustable gastric banding and vertical sleeve gastrectomy:  A  systematic review of pre-​ post studies. Obesity Reviews, 17, 770–​792. Picot, J., Jones, J., Colquitt, J. L., Gospodarevskaya, E., Loveman, E., Baxter, L., & Clegg, A. J. (2009). The clinical effectiveness and cost-​effectiveness of bariatric (weight loss) surgery for obesity: A systematic review and economic evaluation. Health Technology Assessment (Winchester, England)13, 1–​190, 215–​357, iii–​iv. Powers, P. S., Perez, A., Boyd, F., & Rosemurgy, A. (1999). Eating pathology before and after bariatric surgery:  A  prospective study. International Journal of Eating Disorders, 25, 293–​300. Ramalho, S., Bastos, A. P., Silva, C., Vaz, A. R., Brandão, I., Machado, P. P., & Conceição, E. (2015). Excessive skin and sexual function:  Relationship with psychological variables and weight regain in women after bariatric surgery. Obesity Surgery, 25, 1149–​1154. Randolph, T. G. (1956). The descriptive features of food addiction:  Addictive eating and drinking. Quarterly Journal of Studies on Alcohol., 17, 198–​224.

Problematic Eating Behaviors After Bariatric Surgery

Sarwer, D. B., Wadden, T. A., Moore, R. H., Baker, A. W., Gibbons, L. M., Raper, S. E., & Williams, N. N. (2008). Preoperative eating behavior, postoperative dietary adherence, and weight loss after gastric bypass surgery. Surgery for Obesity and Related Diseases, 4, 640–​646. Sugerman, H. J., Kellum, J. M., Engle, K. M., Wolfe, L., Starkey, J. V., Birkenhauer, R.,   .  .  .  Sawyer, M. J. (1992). Gastric bypass for treating severe obesity. The American Journal of Clinical Nutrition, 55(2 Suppl), 560S–​566S. Sugerman, H. J., Starkey, J. V., & Birkenhauer, R. (1987). A randomized prospective trial of gastric bypass versus vertical banded gastroplasty for morbid obesity and their effects on sweets versus non-​sweets eaters. Annals of Surgery, 205, 613–​624. Swanson, S. A., Crow, S. J., Le Grange, D., Swendsen, J., & Merikangas, K. R. (2011). Prevalence and correlates of eating disorders in adolescents:  Results from the national comorbidity survey replication adolescent supplement. Archives of General Psychiatry, 68, 714–​723. Sweeney, T. E., & Morton, J. M. (2013). The human gut microbiome: A review of the effect of obesity and surgically induced weight loss. JAMA Surgery, 148, 563–​569. van Hout, G. C., Verschure, S. K., & van Heck, G. L. (2005). Psychosocial predictors of success following bariatric surgery. Obesity Surgery, 15, 552–​560. Vinai, P., Ferri, R., Anelli, M., Ferini-​Strambi, L., Zucconi, M., Oldani, A., & Manconi, M. (2015). New data on

psychological traits and sleep profiles of patients affected by nocturnal eating. Sleep Medicine, 16, 746–​753. Volkow, N. D., & O’Brien, C. P. (2007). Issues for DSM-​ V:  Should obesity be included as a brain disorder? The American Journal of Psychiatry, 164, 708–​710. Volkow, N. D., Wang, G. J., Fowler, J. S., Tomasi, D., & Baler, R. (2012). Food and drug reward:  Overlapping circuits in human obesity and addiction. Current Topics in Behavioral Neurosciences, 11, 1–​24. Volkow, N. D., Wang, G. J., Tomasi, D., & Baler, R. D. (2013). Obesity and addiction:  Neurobiological overlaps. Obesity Reviews, 14, 2–​18. White, M. A., Kalarchian, M. A., Masheb, R. M., Marcus, M. D., & Grilo, C. M. (2010). Loss of control over eating predicts outcomes in bariatric surgery patients:  A  prospective, 24-​month follow-​up study. Journal of Clinical Psychiatry, 71, 175–​184. Winkelman, J. W. (1998). Clinical and polysomnographic features of sleep-​related eating disorder. Journal of Clinical Psychiatry, 59, 14–​19. Yale, C. E. (1989). Gastric surgery for morbid obesity. Complications and long-​term weight control. Archives of Surgery, 124, 941–​946. Yale, C. E., & Weiler, S. J. (1991). Weight control after vertical banded gastroplasty for morbid obesity. American Journal of Surgery, 162, 13–​18.

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C H A PT E R

 Virtual Reality: Applications to Eating Disorders

25

José Gutiérrez-​Maldonado, Marta Ferrer-​García, Antonios Dakanalis, and Giuseppe Riva

Abstract In the last twenty years researchers have embraced virtual reality (VR) in order to integrate and extend the assessment tools and treatments currently in use for eating disorders (EDs). Specifically the VR protocols for EDs try to exploit clinically the sense of “presence,” that is, the feeling of “being there” inside the virtual environment. The sense of presence offered by VR can be a powerful tool in therapy because it provides the individual with a world in which he/​she can be placed and live a particular experience. This triggers emotional reactions in patients and allows a higher level of self-​reflectiveness than that provided by memory and imagination, and greater control than that offered by direct “real” experience. In particular, VR protocols for EDs use technology to alter the experience of the body (embodiment) in real time and as a cue exposure tool for reducing food craving. Key Words:  virtual reality, exposure, cue exposure, body image, bodily self-​consciousness, body swapping, allocentric lock

Introduction

The first studies of the application of virtual reality (VR) to eating disorders (EDs) were carried out under the aegis of VREPAR (Virtual Reality Environments for the Psycho-​neuro-​physiological Assessment and Rehabilitation Project), a European project designed to develop virtual environments for the study, evaluation, and treatment of body image disorders (Riva, 1998a, 1997; Riva, Melis, & Bolzoni, 1997). Since then, several researchers have embraced VR to integrate and extend the currently used assessment tools and treatments for EDs. Nevertheless, its implementation in clinical settings remains scarce. The increased availability of VR technology today in combination with findings from clinical studies and neuroscience seem destined to boost the growth of two types of intervention (described below) in the coming years: cue exposure therapy and the modification of the experience of the body through the phenomenon of embodiment (Gutierrez-​Maldonado, Wiederhold, & Riva, 2016; Wiederhold, Riva, & Gutiérrez-​Maldonado, 2016). 470

What Is Virtual Reality?

In movies and computer science, VR is usually described as a set of fancy technologies (Riva, Botella, et al., 2015): an interactive three-​dimensional (3D) visualization system (a computer, a game console, or a smartphone) supported by one or more position trackers and a head-​mounted display. The trackers sense the user’s movements and report them to the visualization system, which updates the images for display in real time. Looking at the issue in greater detail, a VR system includes the hardware and software that enable developers to create VR applications and users to experience them. The hardware components receive input from user-​controlled devices (head-​mounted display, joysticks, gloves, etc.) and convey multisensory output to create the illusion of a virtual world. The virtual world may be either a model of a real-​ world object, such as a house, or an abstract world that does not exist in a real sense but is understood by humans, such as a chemical molecule or a representation of a set of data, or a completely imaginary

world. Typically, a VR system includes the following (Burdea & Coiffet, 2003; Gorini, Gaggioli, Vigna, & Riva, 2008; Hale & Stanney, 2014): •  A graphic rendering system that generates the virtual environment, at 60 frames per second (this is the minimum frame rate, but it may be higher depending on the power of the hardware; see Table 25.1 for details of commercially available VR systems); •  Database construction and virtual object modeling software for building and maintaining detailed and realistic models of the virtual world. Specifically, the software handles the geometry, texture, intelligent behavior, and physical modeling of the hardness, inertia, and surface plasticity of any object included in the virtual world; •  Input tools (trackers, gloves, joystick, mice, etc.) that continually report the position and movements of the users; and output tools (visual, aural, haptic, etc.) that immerse the user in the virtual environment (see Table 25.1 for characteristics of commercially available VR systems). On the basis of the hardware and software included in a VR system, it is possible to distinguish between: •  Desktop VR: uses subjective immersion on a standard PC screen. The feeling of immersion can be improved through stereoscopic vision. Interaction with the virtual world can be made via a mouse, joystick, or typical VR peripherals such as a data glove. •  Fully Immersive VR: with this type of solution the user appears to be fully inserted in the computer-​generated environment. This illusion is produced by providing immersive output devices (head-​mounted display, force feedback robotic arms, etc.) and a system of head/​body tracking to guarantee the exact correspondence and coordination of users’ movements with the feedback of the environment. •  CAVE: this is a small room where a computer-​ generated world is projected on the walls. The projection is made on both front and side walls. This solution is particularly suitable for collective VR experiences because it allows different people to share the same experience at the same time. Virtual Reality and Presence In psychology and neuroscience VR is defined instead as “an advanced form of human-​computer interface that allows the user to interact with and

become immersed in a computer-​generated environment in a naturalistic fashion” (Schultheis & Rizzo, 2001, p.  82). From a psychological perspective, VR can be described as a synthetic experience that makes the user believe that he/​she is there, and that this experience is real (Riva, 1998b). Specifically, what distinguishes VR from other media is the sense of “presence,” i.e. the feeling of “being there” inside the virtual experience produced by the technology (Gorini, Capideville, De Leo, Mantovani, & Riva, 2011; Riva & Waterworth, 2003). While there is still no general consensus about what presence actually is from a psychological viewpoint (for an introduction to the subject, see Baños et  al., 2004; Baños et  al., 2008; Diemer, Alpers, Peperkorn, Shiban, & Muhlberger, 2015; Lee, 2004; Ling, Nefs, Morina, Heynderickx, & Brinkman, 2014; Lombard, Biocca, Freeman, IJsselsteijn, & Schaevitz, 2015; Pillai, Schmidt, & Richir, 2013; Riva, 2009, 2012; Riva, Davide, & IJsselsteijn, 2003; Riva, Waterworth, & Murray, 2014; Sanchez-​Vives & Slater, 2005; Sethi, Suzuki, & Critchley, 2012; Slater, 2002; Slater & Wilbur, 1997; Waterworth & Riva, 2014; Zahoric & Jenison, 1998) it is fair to say that most investigators agree about what it is not (Riva, 2009). As underlined by Riva and colleagues (Riva et al., 2014), “presence is not the degree of technological immersion, it is not the same thing as emotional engagement, it is not absorption or attention or action; but all of these have a potential role in understanding the experience of presence in interaction—​the experience of interacting with presence” (p. 1). The sense of presence offered by VR can be a powerful tool for personal change because it provides the individual with a world in which he/​ she can be placed and live a particular experience (Baños et al., 2005; Riva, Bacchetta, Cesa, Conti, & Molinari, 2003; Riva, Botella, et al., 2015). Virtual reality allows a higher level of self-​ reflectiveness than that provided by memory and imagination, and a higher level of control than that offered by direct “real” experience. Virtual reality has also been described as an advanced imaginal system: an experiential form of imagery that is as effective as reality in inducing emotional responses (North, North, & Coble, 1997; Vincelli, 1999; Vincelli, Molinari, & Riva, 2001). Virtual Worlds, Real Emotions To quote Glantz and colleagues, “one reason it is so difficult to get people to update their assumptions is that change often requires a prior

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Table 25.1  Prices and Characteristics of Commercially Available Fully Immersive VR Systems (based on 2016 data) Fully Immersive VR Systems PC Based

Mobile Based

Console Based

System

Oculus Rift

HTC Vive

Samsung Gear Google VR Cardboard

Google Daydream

Playstation VR

Cost

599 US$

799 US$

99 US$

10-​50 US$

69-​149 US$

399 US$

Hardware Requirements

High End PC (>1000 US$)

High End PC (>1000 US$)

High End Samsung Phone (>600 US$)

Middle-​High End Android phone or iPhone (>299 US$)

High End Android Phone (>499 US$)

PS4 (299 US$) or PS4 Pro (399 US$)

Resolution

2160 x 1200

2160 x 1200

2560 x 1440

Depends on the phone (minimum 1024 x 768)

Depends on the phone (minimum 1920 x 1080)

1920 x 1080

Refresh Rate

90 Hz

90 Hz

60 Hz

60 Hz

90 Hz minimum

120 Hz

Field of View

110 degrees

110 degrees

101 degrees

from 70 degrees

96 degrees

100 degrees

Body Tracking

Medium/​ High: head tracking (rotation) and positional tracking (forward-​ backward)

High: head Medium: head Medium: head Medium: head Medium/​ tracking tracking tracking tracking High: head (rotation) and (rotation) (rotation) (rotation) tracking volumetric (rotation) and tracking (full positional room size—​ tracking 15 ft x 15 (forward/​ ft—m ​ ovement) backward)

User Interaction High (using with VR a joystick or controllers)

High (using controllers)

Medium (using gaze, a built-​in pad, or joystick)

Low (using gaze or a button)

Software Availability

Steam Store

Oculus Store

Google Play or Google Play IOS Store

Oculus Store

step—​ recognizing the distinction between an assumption and a perception. Until revealed to be fallacious, assumptions constitute the world; they seem like perceptions, and as long as they do, they are resistant to change” (Glantz, Durlach, Barnett, & Aviles, 1997, p. 96). Using the sense of presence induced by VR, it is easier to develop new, realistic, credible, and informative experiences regarding the surrounding world or the self, demonstrating to the individual that what is assumed to be true in fact is a product of his/​her mind. Once this has been understood, it is easier to identify all the significant 472

Virtual Realit y

Medium (using gaze or joystick)

High (using a joystick or controllers) Playstation Store

elements and make them available for reorganization (Riva, Mantovani, & Gaggioli, 2004). Another feature of VR that has received considerable attention is its ability to trigger emotional reactions in patients (Ferrer-​Garcia & Gutierrez-​ Maldonado, 2010, 2012; Gutierrez-​ Maldonado, Ferrer-​Garcia, Caqueo-​Urizar, & Moreno, 2009). Comparing virtual stimuli with the corresponding real stimuli and photographs, Gorini, Griez, Petrova, and Riva (2010) found that virtual food was as effective as real food, and more effective than photographs of food, in triggering psychological

and physiological responses in patients with EDs, regardless of specific ED diagnosis. These studies thus demonstrate the validity of VR for use as an exposure technique in place of real stimuli in treating patients. As noted by Riva and Mantovani (2012a) the rationale behind the use of VR in exposure techniques is simple: “In VR the patient is intentionally confronted with the feared stimuli while allowing the anxiety to attenuate. Avoiding a dreaded situation reinforces a phobia, and each successive exposure to it reduces the anxiety” (p.  21). In other words, VR is a versatile tool that permits the development of multiple environments that can be presented to the user in many different forms (Gorini & Riva, 2008; Ling et al., 2014). Recent studies show that VR exposure to multiple contexts reduces the recurrence of fear to a greater extent than exposure to only one scenario (Shiban, Pauli, & Muhlberger, 2013); in much the same way, the implementation of multiple stimuli contexts during exposure significantly reduced return of fear post treatment (Dunsmoor, Ahs, Zielinski, & LaBar, 2014; Shiban, Schelhorn, Pauli, & Muhlberger, 2015). Therefore, exposure to different virtual contexts can be an effective way of generalizing the results. Further, as suggested by Diemer et al. (2015), VR can be used to induce emotional reactions via different routes (perceptual vs. conceptual), with additive effects if combined. In summary, the capacity to develop a large body of realistic controlled stimuli and, simultaneously, to monitor the responses generated by the user offers a considerable advantage over real experiences (Riva & Wiederhold, 2015). For example, if an individual experiences a significant fear when exposed to heights, by using a virtual elevator simulation we can assure him/​her that this threat is not going to occur until he/​she feels prepared to cope with it. The same can be said for all the elements that are present in the situation, which can make it more or less threatening (Ferrer-​Garcia et al., 2015; Pla-​Sanjuanelo et al., 2015). Furthermore, VR allows the construction of “virtual adventures” in which subjects experience themselves as competent and efficacious (Botella et al., 2004; Riva, Botella, et al., 2015; Riva et al., 2007). Specifically, it is possible to design targeted VR experiences with different difficulty levels—​ ranging from easy to very difficult—​ which provide an important source of personal efficacy. By interacting with them, individuals discover that the conflicts and/​or feared situations can be

overcome through confrontation and effort (Riva & Mantovani, 2012a). From Virtual to Real Bodies Virtual reality can also be defined as an “embodied technology” because of its ability to modify the feeling of presence (Riva, Dakanalis, & Mantovani, 2015; Riva & Mantovani, 2012b, 2014). In VR, subjects can experience their synthetic avatars as if they were their own body; this phenomenon is known as “embodiment” (referring to the replacement of the physical body by the virtual one). In other words, the VR user is present in a virtual body through the alteration of the cognitive factors that regulate our experience of body and space (for an in-​depth analysis of this claim see Riva, Dakanalis, et  al., 2015). Furthermore, we use the “feelings” from the body to sense both our physical condition and emotional state. These feelings range from bodily changes that may also be visible to an external observer (i.e., posture, touch, facial expressions) to proprioceptive and interoceptive changes that are invisible to an external observer (i.e., endocrine release, heart rate, muscle contractions) (Bechara & Damasio, 2005). Finally, bodily representations are usually produced and modulated by sensory inputs, but they can exist and produce qualitatively rich bodily experiences even in the absence of any input signal (e.g., the phantom limb syndrome) (Melzack, 2005). In this view, the experience of our bodily self can be considered the result of a multimodal simulation. To quote Margaret Wilson (2006), “The human perceptual system incorporates an emulator  . . .  that is isomorphic to the human body . . . . The emulator draws on body-​schematic knowledge derived from the observer’s representation of his own body” (p. 221). Starting from these premises, in 2007 two European teams working independently reported in Science how VR could be used to produce an out-​ of-​body experience in healthy volunteers (Ehrsson, 2007; Lenggenhager, Tadi, Metzinger, & Blanke, 2007). Since then, immersive VR environments have developed rapidly, in which the possibility of “projecting” (and controlling) the body into external (or virtual) space is becoming a reality and is opening up a highly promising new line of research, virtual embodiment (Bergouignan, Nyberg, & Ehrsson, 2014; Maselli & Slater, 2014; Olive & Berthoz, 2012; Pomes & Slater, 2013), whose results have been discussed in two recent reviews (Costantini, 2014; Gallace & Spence, 2014). Using this approach, various authors have used VR to

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induce an illusory perception of a fake limb (Slater, Perez-​Marcos, Ehrsson, & Sanchez-​Vives, 2009) or a fake hand (Perez-​Marcos, Slater, & Sanchez-​Vives, 2009) as part of our own body, and to produce an out-​of-​body experience (Lenggenhager et al., 2007) by altering the normal association between touch and its visual correlate. The application of these procedures for the treatment of body image disturbances in EDs is discussed later in this chapter.

Effectiveness and Limitations

The first studies on the effectiveness of VR in the treatment of psychological disorders concentrated on different types of phobias because VR lends itself so readily to exposure therapies, which are the most effective interventions in the treatment of those disorders:  fear of flying (North & North, 1994), fear of heights (Rothbaum et al., 1995), agoraphobia (North, North, & Coble, 1995), fear of public speaking (North, North, & Coble, 1998), claustrophobia (Booth & Rachman, 1992), fear of driving (Schare, Scardapane, Berger, Rose, & Berger (1999), post-​traumatic stress disorder (Hodges et al., 1998), and obsessive-​compulsive disorder (North & North, 2000). During the first decade of research, VR applications were also developed for other disorders such as autism (Strickland, 1996), attention-​deficit disorder (Rizzo et al., 2000), and EDs (Riva, 1997). In a recent publication, Riva, Baños, Botella, Mantovani, and Gagglioli (2016) reported the available reviews and meta-​analyses about the use of VR in clinical and health psychology. They were related to addictions (2 reviews, 1 meta-​analysis; 53 studies), pain (4 reviews; 48 studies), anxiety disorders (3 reviews, 4 meta-​analyses; 175 studies), stress-​related disorders (4 reviews; 41 studies), depression (1 review and meta-​analysis; 19 studies), EDs (3 reviews; 33 studies), schizophrenia and other psychotic disorders (2 reviews, 1 meta-​analysis; 23 studies), and autism (2 reviews; 39 studies). The highest number of studies has been conducted in anxiety disorders and stress-​related disorders, supporting the efficacy of VR in the treatment of phobias, stress management, post-​traumatic stress disorder, panic disorder, and agoraphobia. The evidence for the treatment of social phobia is not definitive. The reviews related to addictions show that VR is effective in inducing craving to substances such as cocaine, alcohol, and tobacco, allowing its use in cue exposure treatments and to develop coping skills. In autism, the reviews support the use of VR to train social skills. This kind of training has also been used in patients with schizophrenia, and preliminary results are promising, 474

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but there is still no strong evidence for the efficacy of VR in the treatment of this disorder and other psychotic disorders. Similarly, there is only evidence for a moderate effect of the VR interventions on depression. As a pain reduction technique, VR has shown strong efficacy in short-​term interventions, but little evidence exists for longer-​term benefits. In EDs, the reviews performed to date show that VR cue exposure to food stimuli and VR body image treatments are effective. Despite its undeniable potential, the use of VR in research and clinical settings is still limited. There are three main reasons for this:  its economic cost, the technological difficulties, and the potential side effects. The implementation of VR-​ based applications for clinical use has always depended heavily on the development of advanced technology. Consequently, for a long time the research in this area was limited by the cost of the technology required. Furthermore, the field was largely restricted to academic research, and very few technology companies sought to transfer the results of this research into clinical VR applications. Today, however, VR technology is advancing quickly. Both Oculus Rift (http://​www.oculus. com) and HTC (https://​www.htcvive.com/​) are showcasing high-​ quality VR experiences at reasonable price points—​less than $2,000 for a fully configured system—​which are now widely available to consumers (Castelvecchi, 2016). Thus, the first major obstacle to the widespread use of the VR seems to have been overcome. The second one, the presence of technological difficulties, remains, but probably not for very long. The use of VR systems involves the management of complex devices that require a certain level of technological knowledge and the assistance of technical staff. Therefore, it is not surprising that some therapists and clinicians, especially veteran practitioners, are reluctant to introduce VR systems into their daily practice. However, this scenario is about to change largely due to the expansion of VR in the field of consumer electronics; the commercialization of VR systems among the general population will bring down costs and enhance the development of user-​friendly devices. Furthermore, for younger generations the use of VR technology will be part of their everyday routine and the technical difficulties will disappear. Finally, the potential side effects of exposure to VR environments that may impair the potential benefits of using this technology must be borne in mind (Rizzo, Schultheis, & Rothbaum, 2002).

Virtual reality sickness or cybersickness results from a conflict between the visually perceived movement in the virtual world and the vestibular system’s sense of movement (standing still) and may produce negative effects like dizziness, discomfort, disorientation, and fatigue (Regan & Price, 1993). Although research into cybersickness in the clinical population is scarce, a review published in 2014 reported that only a small percentage of patients who engaged in VR-​based treatments experienced negative side effects (Quintana, Bouchard, Serrano, & Cárdenas-​ López, 2014). These side effects usually appear in the short term and become less intense as immersion to VR environments is repeated over time (Kennedy, Stanney, & Dunlap, 2000). Furthermore, there are individual differences that may increase or reduce the probability of experiencing these effects; indeed, some researchers have stressed the need to assess the predisposition to immersion and sensitivity to cybersickness of patients in order to achieve the most effective VR experience (Rosa, Morais, Gamito, Oliveira, & Saraiva, 2016).

Virtual Reality Applications in Eating Disorders

The main applications of VR technologies in ED have focused in cue exposure therapy and body image study, assessment and treatment. Specifically, the clinical use of VR with these disturbances is based on key theory-driven psychological treatment techniques. First, VR can reduce eating-related anxiety during and after exposure to virtual food, helping to disrupt the reconsolidation of adrivenverse, food-related memories. Second, VR is used to counter a multisensory body integration deficit that impairs the patient’s ability of updating his/her body memory (allocentric, offline) with new contents from real-time perception-d inputs (egocentric, online).

Virtual Reality Cue Exposure

Cognitive-​ behavioral therapy (CBT; Fairburn, Marcus, & Wilson, 1993) is considered the gold standard for the treatment of bulimia nervosa (BN) (National Institute for Health and Clinical Excellence, 2004) and has also been proposed as an appropriate intervention for binge eating disorder (BED) (Berkman et  al., 2015; Fairburn et  al., 2015). A  considerable body of research supports its efficacy, reporting that between 30% and 50% of patients that finish treatment present substantial reductions in binging and purging behaviors (Agras, Walsh, Fairburn, Wilson & Kraemer, 2000;

Hay & Claudino, 2010). Unfortunately, studies also reveal that BN and BED are chronic and treatment resistant to standard evidence-​based treatment (i.e., CBT) in more than 20% of patients (Steinhausen & Weber, 2009). Conditioning and learning processes seem to play an important role in the maintenance of disturbed behaviors in both BN and BED (Bouton, 2011). Therefore, intervention techniques based on these theoretical models have been developed to treat EDs characterized by binge eating. The first proposal appeared at the end of 1980s when Schmidt and Marks (1988) reported that food craving experienced by BN patients decreased over a series of sessions in which cue exposure therapy (CET) was applied. Over the following years, Jansen and colleagues established the theoretical bases of CET for EDs characterized by binge eating, and published several studies providing support for the efficacy of the intervention (Jansen, Broekmate, & Heymans, 1992; Jansen, van den Hout, de Loof, Zandbergen, & Griez, 1989). According to Jansen (1994), once binge eating behavior has been established, exposure to binge-​ related food cues provokes a conditioned response (hyperinsulinemia), which thus elicits a hypoglycemic compensatory response. This biochemical response is experienced as food craving and may lead to a binge episode in at-​risk individuals. Jansen (1998) also drew attention to the similarities between food craving in BED patients and drug addiction, suggesting that the two phenomena may share neurochemical mechanisms and neuroanatomical bases. Subsequent research seems to support this thesis (Cason et  al., 2010; Nair, Adams-​Deutsch, Epstein, & Shaham, 2009). Nair et  al. (2009) reported that the activation of group II metabotropic receptors (mGluR2 and mGluR3), D1 dopamine receptors, CB1 receptors, and mu opioid receptors contribute to the reinstatement of heroin, cocaine, alcohol, and food seeking induced by several types of cues. There is also evidence for a role of mGluR1 and 5-​HT1A and/​ or 5-​HT1B receptors in the discrete cue-​induced reinstatement of both food and cocaine seeking. Additionally, it has been shown that activity in the accumbens core mediates discrete cue-​induced cocaine, heroin, and food seeking and that activity in the lateral hypothalamus mediates context-​ induced reinstatement of both alcohol and food seeking. Furthermore, animal research has provided evidence of the existence of individual differences in reward-​seeking behavior (Mahler & Wit, 2010).

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There are animals, and also humans, with highly reactive phenotypes to reward cues and, consequently, with an enhanced risk of developing addictive disorders or binge behavior and an increased risk of relapse after treatment. Other researchers have focused on the role of anxiety and negative affect as precipitating cues of binge behavior. Toro et  al. (2003) and Martínez-​ Mallén et  al., 2007) suggested that exposure to binge-​related cues produced anticipatory anxiety, which in turn may elicit an overeating episode. This research group used CET to treat BN patients resistant to treatment (CBT and pharmacotherapy), with positive results (Toro et al., 2003; Martínez-​Mallén et al., 2007). After the intervention, patients showed reductions in anxiety and bulimic symptoms. The binge episodes declined drastically in number and, in most cases, were completely eliminated. Purge episodes were also reduced at follow-​up. Despite good initial results, CET presents certain logistical drawbacks (Bulik et  al., 1998) that should also be considered. When CET is conducted in the therapist’s office, patients have to bring a sufficient amount of binge-​related food to the exposure session, which may well be an inconvenience. Moreover, in the office only specific cues (food) are taken into account—​not contextual cues (e.g., the kitchen environment). Thus, the ecological validity of the intervention is reduced and, consequently, the possibilities of generalizing the extinction response to every-​ day life situations may be impaired. A  recent study by Schyns, Roefs, Mulkens, and Jansen (2016) highlighted the importance of exposure to numerous and varied cues for the generalization of learning in CET. The main aim of that study was to assess whether a one-​session cue exposure intervention decreased eating in the absence of hunger, and whether the hypothesized decrease in intake would be generalized to other food items that were not present during exposure. The results showed that inhibitory learning takes place during the food cue exposure session, as participants successfully inhibited themselves when confronted with an exposed food item, but the inhibitory learning did not generalize to food items that were not present during the cue exposure. These results show that there is room for improvement with regard to the generalizability of CET. Imagery exposure has frequently been used as an alternative to in vivo exposure, given its flexibility and the possibility of extending the exposure to different cues and contexts through the imagination. However, this method also has some important 476

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drawbacks, such as the lack of control over what participants are imagining and the difficulties some individuals have in visualizing the target situation in a sufficiently realistic way. The use of VR provides a third way to conduct CET. Virtual reality environments allow therapists to expose patients to lifelike situations while maintaining strict control over the variables. Then, as ecological validity is high, the possibility for the generalization of the acquired learning is also enhanced. The use of VR for CET has been mainly applied for the treatment of addictions. Several research groups have developed VR-​ based interventions for addiction to substances such as drugs, nicotine, and alcohol (Hone-​ Blanchet, Wensing, & Fecteau, 2014; Pericot-​Valverde, García-​Rodríguez, Gutiérrez-​Maldonado, & Secades-​ Villa, 2015). These applications consist in VR environments that simulate situations, people, and objects that have been identified as triggers of craving. The aim of the intervention is to reduce the craving response, and then to extend this reduction or elimination to similar situations in the real world. In order to develop CET programs in patients with EDs, several studies assessing the ability of food-​ related VR environments to provoke food craving have recently been published (Ferrer-​Garcia et al., 2014; Pla-​Sanjuanelo et al., 2015). Overall, these studies found that craving experienced in VR environments incorporating cues and contexts related to binging behavior was consistent with trait and state craving assessed (with questionnaires) outside the VR environments. Participants with the highest scores on trait and state craving also showed a greater urge to eat when exposed to food in different VR environments. In addition, scores on questionnaires assessing trait and state craving were able to predict the average craving experienced in virtual environments. The ability of VR exposure to reduce food craving has also been assessed. Gutierrez-​ Maldonado, Pla-​ Sanjuanelo, and Ferrer-​ Garcia (2016) applied a one-​session model of CET to 113 participants who were exposed to food-​related virtual environments using two different VR systems during exposure (one immersive and one nonimmersive). Food craving decreased during exposure to both immersive and nonimmersive VR environments compared with pre-​exposure levels, supporting the efficacy of VR-​CET in reducing food craving. No significant differences in craving were found between immersive and nonimmersive systems, showing that low-​cost nonimmersive systems can improve the accessibility of this technique by

reducing costs and improving usability, without any significant loss of efficacy. A clinical trial underway at several centers in Spain and Italy is currently investigating these issues (https://​clinicaltrials.gov/​ct2/​show/​ NCT02237300). The main aim of the study is to assess the efficacy of CET based on VR (VR-​CET) as a second level treatment in patients with BN and BED. With this objective in mind, 64 patients diagnosed with BN or BED, according to DSM-​5 (APA, 2013), who were treatment resistant (that is, their binges persisted after CBT) were randomly assigned to one of two booster session conditions: a VR-​CET booster sessions group, and a CBT booster sessions group (the control group). Booster sessions consisted of six 60-​minute sessions held twice weekly over a period of 3 weeks. Over the six sessions, participants in the experimental group were exposed to different VR environments related to binge behavior, according to a previously constructed hierarchy. During exposure, patients faced high-​ risk situations and handled the virtual foods using a computer mouse. Exposure ended after a significant reduction in the level of anxiety, or after 60 minutes. Participants in the control group received six CBT booster sessions to improve treatment outcome. A significant interaction between group (VR-​CET vs. CBT) and time (before and after booster sessions) was expected, showing the maintenance of the number of binges and purges before and after booster sessions in the control group (CBT) and a reduction in the experimental group (VR-​CET). After the six booster sessions, patients in both CBT and VR-​CET conditions presented improvement. However, participants in the VR-​CET group showed significantly higher reductions in binges, purges, bulimia symptoms (assessed with the Bulimia scale of the Eating Disorders Inventory-​3; EDI-​3), craving for food (assessed with the Food Craving Questionnaire-​State/​Trait; FCQ-​S/​T), and anxiety (State and Trait Anxiety Inventory, STAI) than patients in the CBT group. The results obtained support the efficacy of VR-​ CET for enhancing CBT in ED patients resistant to treatment as usual, and show that further research in this field is now necessary. Exposure therapy has also been used for the treatment of anorexia nervosa (AN). However, published studies are still scarce. Patients with AN show anticipatory anxiety and frequent worries about high-​calorie foods and their consequences for weight and body shape. Therefore, intake avoidance is a central feature of this disorder and an insidious

problem that clinicians must deal with. Exposure to food with prevention of avoidance response has been proposed as an appropriate intervention to treat fear and refusal to eat in AN patients (Hildebrandt, Bacow, Markella & Loeb, 2012; Steinglass et  al., 2012). The results suggest that exposure therapy reduces food anxiety and increases patients’ calorie intake. Likewise, exposure therapy involving one’s own body has also been proposed as an effective technique for body image disturbance treatment (Hildebrandt, Loeb, Troupe, & Delinsky, 2012; Morgan, Lazarova, Schelhase, & Saeidi, 2014). This technique is usually applied as a component of CBT and is conducted using mirror confrontation or visualization of a video recording of the patient’s body. Using this procedure, studies found a reduction in body-​related negative emotions and cognitions and a decrease in restrictive and bulimic behaviors (Morgan et al., 2014; Trentowska, Bender, & Tuschen-​Caffier, 2013). Repeated and prolonged exposure to one’s own body during the intervention is believed to break down the association between the image of the body and the conditioned negative responses to it. As in the case of the use of CET for BN and BED, in vivo exposure for AN treatment presents several drawbacks that make its implementation difficult. Again, logistical difficulties, time required to conduct interventions, limited ecological validity, and generalization problems hinder the application of exposure techniques. In addition, AN patients frequently resist or reject the use of those techniques, as they may trigger anxiety. These difficulties have led to the search for new procedures to implement exposure. Here again, VR technology has been proposed as an alternative procedure that overcomes the drawbacks mentioned. Currently, Gutiérrez-​Maldonado’s group at the University of Barcelona is working on a research project whose main aim is the development of a VR-​ based application for reducing AN patients’ fear of regaining a healthy weight and the resulting refusal to eat. Patients are exposed to an avatar that represents their own body image and whose body mass index (BMI) increases progressively according to a pre-​established hierarchy. Moreover, to facilitate the generalization of changes outside the therapist’s office, exposure to the avatar representing the patient’s body image takes place in different virtual environments that simulate real-​life situations in which, according to the patient’s negative beliefs (social rejection, criticism, etc.), weight gain may have catastrophic consequences.

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Patients with AN show high levels of anxiety, avoidance of food intake and weight gain, which are associated with rigid negative beliefs about the consequences of increasing weight. Avoidance behaviors prevent patients from realizing that weight normalization does not have the catastrophic consequences expected. All these features create an extraordinary resistance to change, as one of the objectives of the intervention is precisely to gain weight, the source of their greatest fear. As a result, this proposal focuses the exposure therapy on the primary feared stimulus (weight gain) instead of exposing the patient to his/​her actual body image, in order to reduce anxiety and avoidance. Obviously, it is not possible to use in vivo exposure to achieve this aim, but imagery exposure may be a suitable procedure. To our knowledge, only one case study has been carried out in which imagery exposure was used to treat a restrictive AN patient who had showed resistance to treatment as usual (Levinson, Rapp, & Riley, 2014). Five sessions of exposure therapy were applied as a part of a broader package of cognitive-​behavioral techniques. During the sessions, the patient had to imagine herself progressively increasing weight and facing the associated feared catastrophic consequences, such as criticism and social rejection. The authors reported that the patient gained weight during the intervention and maintained the weight increase after one-​month follow-​up. However, as this was not a controlled study, it is not possible to assess the specific contribution of imagery exposure to the improvement. Despite being a viable option for exposure therapy, imagery exposure presents some important issues which may make the use of this procedure difficult in some patients. These problems include difficulty in maintaining visualization long enough to reach habituation of response, individual differences in the ability to visualize a situation, and the risk that the most feared stimulus may be avoided during visualization. Virtual reality allows therapists greater control over the exposure parameters, thus reducing the possibility of avoidance behaviors by patients, and its efficacy is not conditioned by patients’ capacity for visualization. Therefore, VR exposure therapy may be an appropriate alternative. Besides, the group headed by Gutiérrez-​Maldonado proposes going further by using the induction of an illusion of ownership over the virtual body (embodied cognition) in order to enhance exposure results. Preston and Ehrsson (2014) used the illusion of ownership over the virtual body to study body image dissatisfaction. These authors found that 478

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participants in whom the ownership illusion of a thin virtual body had been induced showed higher levels of body image satisfaction. The manipulation of these illusions has also proved effective for treating disorders involving body image disturbances (e.g., Schmalzl et al., 2011). Bearing these findings in mind, the hypothesis of the research project currently underway at the University of Barcelona is that the use of VR techniques to produce the illusion of ownership of the virtual body will enhance the effect of body exposure therapy in AN patients. The objective of the proposed intervention is to reduce the fear of weight gain by exposing the patients to an avatar that simulates their own body image with progressive BMI increases. It is expected that the induction of illusory ownership over the virtual body using techniques based on visual-​motor, visual-​tactile and visual-​proprioceptive correlations can facilitate the extinction process.

Virtual Reality for the Study, Assessment, and Treatment of Body Image

Body image disturbance is a central feature of EDs and plays an important role in the development, maintenance, and risk of relapse of these conditions (Haynos, Watts, Loth, Pearson, & Neumark-​Stzainer, 2016; McFarlane, Olmsted, & Trottier, 2008; Rohde, Stice, & Marti, 2015; Stice, 2016). Consequently, the research, assessment, and treatment of body image are a basic focus of interest. Body image is a multidimensional construct reflecting a mental representation of the body’s physical appearance, which involves perceptual, cognitive, and affective aspects and influences behavior (Ahrberg, Trojca, Nasrawi, & Vocks, 2011; Gaudio & Quattrocchi, 2012). Moreover, it is a dynamic representation; that is, it changes over time and depends on everyday experiences and sociocultural contexts (Espeset, Gulliksen, Nordbo, Skarderud, & Holte, 2012). Given the complexity of body image, researchers usually focus on its perceptual and cognitive-​affective components and the associated disturbances: the perceptual distortion of body image (i.e., the inability to perceive the size of the body accurately) and body dissatisfaction (i.e., the degree to which a person likes or dislikes the size and shape of his/​her body and values it) (Cash & Deagle, 1997; Waldman, Loomes, Mountford, & Tchanturia, 2013). Probably, this complexity also explains why body image disturbance is often overlooked in ED treatments, despite being considered a core feature of these disorders. In this context, the development of

VR has provided researchers and clinicians with a new technology that seems to be particularly well suited to the study, assessment, and treatment of body image disturbances. The possibility of developing 3D figures that represent the body of the participants and whose size and shape can be modified enables patients to embody their mental representations of the different components of body image (e.g., perceived vs. ideal body image). Moreover, the use of immersive systems such as head-​mounted displays brings patients face to face with their virtual body in its actual size. Virtual reality simulates real-​life situations in which different aspects of body image disturbances can be studied, assessed, and even treated in a secure, private, and controlled setting (Ferrer-​Garcia & Gutiérrez-​Maldonado, 2012). Virtual Reality for the Study of Body Image Disturbances One of the main advantages that VR offers is the possibility of simulating real-​life situations in which participants’ behavior can be observed and assessed in a naturalistic context while maintaining good control over the variables (Botella et  al., 2004). Additionally, VR environments allow researchers to expose participants not only to specific cues (e.g., chocolate) but also to contextual ones (e.g., a restaurant setting). Last but not least, ED patients are much less reluctant to expose themselves to these cues in VR environments than in real situations. All these characteristics make this technology especially useful for experimental research and, thus, for broadening our knowledge of the nature and features of body image disturbance. An issue that has been repeatedly addressed in the study of body image is whether it is stable or unstable. Myers and Biocca (1992) proposed the concept of “elastic body image” to refer to the unstable self-​ perceived body image presented by women after watching ideal-​body image commercials on television. More recently, other authors have claimed that trait and state components coexist in the body image construct (Etu & Gray, 2010; Lattimore & Hutchinson, 2010). In order to study this issue in depth, Gutiérrez-​ Maldonado and colleagues used VR to assess the stability/​ instability (intraindividual variability) of body image disturbances in patients with EDs. Previous research had found that eating low-​and high-​ calorie food (McKenzie, Williamson, & Cubic, 1993), exposure to low-​and high-​calorie food (Carter & Bulik, 1994), exposure to photographs of low-​and high-​ calorie food (Heilbrun

& Flodin, 1989), or exposure to situations that involve the scrutiny of others using guided imagery (Haimovitz, Lansky, & O’Reilly, 1993) may produce changes in body image. However, the results of these studies were not consistent. Virtual reality offered the possibility of exposing ED patients to emotionally significant situations (i.e., eating different kinds of food in a restaurant and in a kitchen), which contained both specific and contextual cues, and controlling the characteristics of all these cues. Two main exposure variables were considered:  the kind of food eaten (high calorie versus low calorie) and the presence of other people (eating alone in a kitchen versus eating with colleagues in a restaurant). Furthermore, the physical aspect of the avatars in the restaurant and dialogs included in the exposure scenes were also controlled. One hundred eight female undergraduates and 85 ED patients were exposed to four VR environments presented in random order (i.e., a kitchen with low-​calorie food, a kitchen with high-​calorie food, a restaurant with low-​ calorie food, and a restaurant with high-​ calorie food). In the intervals between the presentation of each environment anxiety and depressed mood were assessed by means of questionnaires, and body image disturbances (perceptual body image distortion and body image dissatisfaction) were measured using the Body Image Assessment Software (Ferrer-​Garcia & Gutiérrez-​Maldonado, 2008). The results obtained in this study showed that body image distortion (i.e., overestimation of body size) and body image dissatisfaction were significantly higher after eating high-​calorie food (e.g., a pizza) than after eating low-​calorie food (e.g., a salad), and that this was the case regardless of the presence (in the restaurant) or the absence (in the kitchen) of other people (Gutiérrez-​Maldonado, Ferrer-​Garcia, Caqueo-​Urízar, & Moreno, 2010). Anxiety and depressed mood also increased after eating high-​calorie food in this group (Ferrer-​Garcia, Gutiérrez-​Maldonado, Caqueo-​Urízar, & Moreno, 2009). In contrast, participants without ED showed similar percentages of body distortion and body dissatisfaction, as well as a similar mood, in all the situations. These results support the idea that body image disturbance is unstable in ED patients, as the changes depend on the situation to which they are exposed. Therefore, both state and trait perspectives need to be included in its assessment and treatment. In the same line of research, Mountford, Tchanturia, and Valmaggia (2016) used VR technology to study whether perceptions of other people’s

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appraisals influence the body image of ED patients. Twenty nonclinical women with low levels of body image concerns and 20 nonclinical women with high body image concerns were exposed to a virtual simulation of a 4-​minute journey on a London bus using a fully immersive system (i.e., a head-​mounted display). Several avatars were present in the bus, all of which had normal body weight and appearance and were programmed to display only neutral behavior. Participants were asked to “form an impression of what you think about the people on the bus and what they think about you” (Mountford et al., 2016, p. 95). The authors found that participants with high levels of body image concerns also showed higher levels of social evaluative concerns and comparison with avatars during the virtual journey compared with participants who did not have concerns about body image. However, no changes in body image disturbances were elicited during exposure. Possibly, the neutrality of the environment chosen, the low realism of the avatars and the characteristics of the sample (nonclinical) explains these results. Besides highlighting features of body image disturbance and the need for further research into ways of enhancing the potential of VR exposure, these studies illustrate how VR can help us to develop experimental studies with high ecological validity but with a proper control over the variables. Virtual Reality for the Assessment of Body Image Disturbances Most research into VR assessment of body image disturbances in ED, as well as in its treatment, has been conducted by two groups: Riva’s group in Italy and the group led by Perpiñá, Botella, and Baños in Spain. As mentioned above, Riva was the first to apply VR technology to the assessment and treatment of body image disturbances in ED (Riva et al., 1997). As part of the European VREPAR Project, he and his colleagues developed the BIVRS (Body Image Virtual Reality Scale; Riva, 1998c; Riva & Melis, 1997), a nonimmersive, 3D graphical interface for the assessment of body image dissatisfaction. The software displayed nine 3D figures, male and female, ranging from underweight to overweight. Participants were asked to select the figures that best fit their perceived and their desired body sizes. Discrepancy between the two measures was considered an indicator of body image dissatisfaction. The main advantage of this assessment method was its application of 3D to the human figures displayed by the software, thus increasing the realism and helping participants to identify with them. 480

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In the same line of research, Perpiñá et  al. (1999) developed an immersive VR-​based application, which displayed a 3D human figure whose body parts could be modified using a slider bar. Participants could enlarge the size of each body part by moving the slider to the right and reduce it by moving the slider to the left, in order to represent different dimensions of body image (e.g., perceived body size, desired body size, healthy body size, etc.). Both the BIVRS and the software developed by Perpiñá have mainly been used in the context of treatment, which is the subject of the following section. Virtual Reality for the Treatment of Body Image Disturbances In our culture most women are dissatisfied with their body:  One adolescent girl out of two reports body dissatisfaction (Makinen, Puukko-​ Viertomies, Lindberg, Siimes, & Aalberg, 2012). Recent studies have highlighted that the sociocultural pressure to be thin is central to the development of negative feelings about the body, which are recognized as the most robust risk factor for clinical and subclinical EDs (Dakanalis, Clerici, et  al., 2013; Dakanalis et al., 2012; Dakanalis et al., 2015; Dakanalis & Riva, 2013b; Dakanalis, Zanetti, Riva, & Clerici, 2013). For this reason, a popular model of EDs—​ the “objectification theory”—​ suggests a significant role of culture and society in the etiology of these disorders. Introduced by Fredrickson and Roberts (1997), this theory suggests that our culture imposes a specific self-​evaluation model—​self-​ objectification—​ that defines women’s behavioral and emotional responses (Calogero, Tantleff-​Dunn, & Thompson, 2010; Dakanalis et  al., 2012; Riva et al., 2014). At its simplest, the objectification theory holds that (1) there exists an objectified societal ideal of beauty (within a particular culture) that is (2) transmitted via a variety of sociocultural channels. This ideal is then (3) internalized by individuals, so that (4) satisfaction (or dissatisfaction) with appearance will be a function of the extent to which individuals do (or do not) meet the ideal prescription (Tiggemann, 2011). According to Fredrickson and Roberts (1997), repeated experiences of sexual objectification—​ when women are treated as bodies that exist for the use and pleasure of others—​cause them to gradually adopt an observer’s perspective of their physical self; that is, they begin to treat themselves as an object to be looked at and evaluated on the basis of physical

appearance. The self is so defined in terms of how the body appears to others. The internalization of an observer’s perspective on one’s own body is labeled as “self-​objectification” (Riva, 2014a, 2014b) and reduces a woman’s worth to her perception of her body’s semblance to cultural standards of attractiveness (Dakanalis & Riva, 2013b). Self-​objectification is typically manifested as persistent body surveillance or habitual monitoring of the body’s outward appearance and is believed to lead to a number of negative experiential consequences such as body shame, social physique anxiety, lack of awareness of internal bodily states, and decreased peak motivational states/​flow experiences (Dakanalis, Clerici, et al., 2013). There are two possible criticisms of this view. The first is that males, who apparently are less prone to self-​objectification, also experience EDs. Second, only a small subset of all the female and male subjects exposed to idealized body models develop clinically diagnosable EDs (Thompson, Heinberg, Altabe, & Tantleff-​Dunn, 1999). Nevertheless, a number of recent studies have underlined the possible role of self-​objectification in the etiology of male EDs (Dakanalis, Clerici, et  al., 2016; Dakanalis et  al., 2012; Dakanalis, Timko, Clerici, Zanetti, & Riva, 2014; Dakanalis, Timko, et  al., 2015; Dakanalis, Zanetti, Riva,

Colmegna, et al., 2015). Specifically in males, self-​ objectification is manifested as body surveillance (Dakanalis & Riva, 2013a). As in women, frequent body surveillance increases attention to disliked body parts, thereby encouraging the use of maladaptive eating and body shape regulation behaviors to modify the body (Calogero, 2009; Wooldridge & Lytle, 2012). Furthermore, body surveillance in men is strongly related to muscle dysmorphia (the belief that one is small and skinny, despite well-​ developed musculature), a male disturbance whose symptoms bear similarities to those of anorexia nervosa (Cafri, Olivardia, & Thompson, 2008; Murray et al., 2012). A possible response to the second criticism is offered by a new etiological model, namely, the allocentric lock (AL) theory (Riva, 2012, 2014b). This theory suggests that EDs, including AN, are the outcome of a multisensory body integration deficit (Riva & Gaudio, 2017), dramatically impairing the way the body is “experienced” and “remembered.” Specifically, individuals with (or who are developing) these disorders may experience an impairment in the way expected (using cognitive prediction) versus experienced (from perception) bodily signals are integrated. In other words, the multisensory body integration process is biased towards the expected body representations and does not include the

Multisensory Body Integration Deficit

real-time perceptions Egocentric image of the body (first personfrom inside) field perspective

WORKING MEMORY

ALLOCENTRIC LOCK:

MEMORY OVERRIDES PERCEPTION

predicted body from memory Allocentric image of the body (third personfrom outside) observer perspective

BODY SHAME:

PERCEIVING ONESELF NON MEETING CULTURAL STANDARDS

EXTREME RESTRAINED EATING EATING DISORDERS Figure 25.1  Allocentric Lock Theory.

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available real-time information about the body. The practical outcome of this deficit is that the subject is locked to an allocentric (third person) disembodied negative memory of their body that is not updated by perceptual data, even after a successful diet and/​ or a significant weight reduction (Figure 25.1). However, if even successful dieting attempts are unable to balance body image disturbance, people may either start more radical dieting attempts or, at the opposite end, all their attempts to control eating are abandoned and they engage in disinhibited eating behaviors that can be followed by compensatory behaviors, which can turn into a vicious cycle (for a broader review, see Dakanalis, Clerici, et al., 2016; Gaudio & Riva, 2013; Riva, 2007, 2011, 2012, 2014b; Riva, Gaudio, & Dakanalis, 2015). From a cognitive viewpoint, this situation can be explained as the effect of a functional disconnection between top-​down, premorbidly learned predictions regarding the experience of the body and the processing of bottom-​up perceptual information regarding its current state (Gaudio, Wiemerslage, Brooks, & Schioth, 2016; Fotopoulou, 2015; Riva, 2016; Serino et  al., 2015; Serino, Pedroli, et  al., 2016). This view is in agreement with a recent hypothesis that describes EDs as a disturbance of the self specifically associated “with spatial functioning possibly related to experiencing one’s own body as an integrated aspect of the self, and temporal functioning possibly related to integrating the self in a coherent narrative over time” (Amianto, Northoff, Abbate Daga, Fassino, & Tasca, 2016, p. 7). To modify this situation, the use of VR, a synthetic egocentric experience, is an emerging and promising approach (Ferrer-​ Garcia, Gutiérrez-​ Maldonado, & Riva, 2013). In particular, the two research groups mentioned above (Riva’s group in Milan and Perpiñá’s group in Castellón and Valencia) are using VR to improve CBT, and have also developed VR-​based software for the assessment and treatment of body image disturbances (Myers, Swan-​Kremeier, Wonderlich, Lancaster, & Mitchell, 2004; Perpiña, Botella, & Baños, 2003; Riva, Bacchetta, Cesa, Conti, & Molinari, 2002, 2004). The first approach is offered by VR-​enhanced CBT called experiential cognitive therapy (ECT), developed by Giuseppe Riva and his group inside the VREPAR and VEPSY Updated European funded projects. It is a relatively short-​term, patient-​ oriented approach that focuses on individual discovery (Cesa et  al., 2013; Manzoni et  al., 2016; Riva, Bacchetta, Baruffi, & Molinari, 2001, 2002; Riva, Bacchetta, Cesa, Conti, & Molinari, 2003). 482

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Experiential cognitive therapy shares with CBT the use of a combination of cognitive and behavioral procedures to help the patient identify and change the maintaining mechanisms. However, it differs from CBT in the following ways: •  Use of VR: There are 15 VR sessions. The first session is used to assess any stimuli that could elicit abnormal eating behavior. Specifically, attention is focused on the patient’s concerns about food, eating, shape, and weight. At the end of the first VR session the therapist uses the miracle question, a typical approach used by the solution-​focused brief therapy (deShazer, 1985; McFarland, 1995). In this approach the therapist asks the patient to imagine what life would be like with a lower weight. Using VR to experience the effects of the miracle (Riva et al., 2006)—​a virtual balance shows the weight expected by the patient—​individuals are more likely not only to gain an awareness of their need to do something to create change but also to experience a greater sense of personal efficacy. •  Focus on the negative emotions related to the body (a major reason patients want to lose weight) and on supporting the empowerment process. In eight VR sessions, the therapist helps patients to recognize why they eat and what they need to either avoid or cope with specific emotional/​behavioral triggers. This is achieved by integrating different cognitive-​behavioral methods: Countering, Alternative Interpretation, Label Shifting, Deactivating the Illness Belief. •  Focus on the experience of the body: It is included via a specific VR body-​image rescripting protocol aimed at updating the patient’s memory of the body (Riva, 2011). In the protocol, involving six VR sessions, different body-​related situations are experienced from both first-​person (the patient does not see his/​her body in the scene) and third-​person perspectives (the patient sees his/​ her body in the scene) integrating the therapeutic methods used by Butters and Cash (1987) and Wooley & Wooley (1985). In general, the therapist asks the patient to give detailed descriptions of the virtual experience and of the feelings associated with it. The patient is also taught how to cope with these feelings using the “confrontation,” “feeding” and “reconciliation” techniques (Leuner, 1969). This approach was validated by various case studies (Riva, Bacchetta, Baruffi, Rinaldi, & Molinari, 1999) and trials. In the first one, which was uncontrolled, three groups of patients were used (Riva et al., 2000): patients with BED, patients with eating

disorders not otherwise specified (EDNOS), and obese patients with a body mass index higher than 35. All patients participated in five twice-​weekly therapy sessions. All the groups showed improvements in overall body satisfaction, disordered eating, and related social behaviors, although these changes were less noticeable in the EDNOS group. The approach has also been tested in various controlled studies. The first one involved 20 women with BED who were seeking residential treatment (Riva, Bacchetta, Baruffi, et  al., 2002). The sample was assigned randomly to ECT or to CBT-​based nutritional therapy. Both groups were prescribed a 1,200-​ calorie per day diet and minimal physical activity. Analyses revealed that although both groups were binge-​free at 1-​month follow-​up, ECT was significantly better at increasing body satisfaction. In addition, ECT participants were more likely to report increased self-​efficacy and motivation to change. In a second study, the same randomized approach was used with a sample of 36 women with BED (Riva, Bacchetta, et al., 2003). The results showed that 77% of the ECT group quit binging after 6 months versus 56% for the CBT group and 22% for the nutritional group sample. Moreover, the ECT sample reported better scores on most psychometric tests. The most recent controlled trial (ISRCTN59019572) included 211 obese (BMI > 40) female patients (Manzoni et al., 2016) and 90 obese (BMI > 40) female patients with BED (Cesa et al., 2013). In the trial ECT was compared with CBT and an integrated treatment (IT) including nutritional groups, a low-​calorie diet (1,200 kcal/​ day) and physical training. In both studies (Cesa et  al., 2013; Manzoni et al., 2016) only ECT was effective at improving weight loss at 1-​year follow-​up. Conversely, control participants regained most of the weight they had lost during the inpatient program. Furthermore, in the BED study (Cesa et  al., 2013) binge eating episodes decreased to zero during the inpatient program but were reported again in all the groups at 1-​year follow-​up. However, a substantial regain was observed only in the group who received the integrated treatment alone, while both ECT and CBT were successful in maintaining a low rate of monthly binge eating episodes. To further improve the efficacy of ECT, Riva and colleagues recently started to explore the possibility of integrating the emerging field of bodily illusions in the protocol. Since Botvinick and Cohen showed that it is easy to generate in people the illusion that a rubber hand is part of their body (the

Rubber Hand Illusion, Botvinick & Cohen, 1998), there has been increasing interest in the study of bodily illusions. Specifically, this term refers to controlled illusory generation of unusual bodily feelings, such as the feeling of ownership over a rubber hand that affects the experience of a body part or the entire body (i.e., a body-​swap illusion, see below). In their review paper for Annals of Physical and Rehabilitation Medicine, Dieguez and Lopez (Dieguez & Lopez, 2016) concluded that the experimental methods that create multisensory conflicts to modulate body representations (i.e., bodily illusions) are promising noninvasive approaches for the rehabilitation of patients with neurologic disorders. An increasing number of recent studies also suggest clinical applications for these methods in the treatment of weight-​related disorders (i.e., eating disorders and obesity). Pioneering research conducted by Riva’s team (Serino, Pedroli, et al., 2016; Serino, Scarpina, et al., 2016) has shown that the embodiment in a virtual body that substitutes one’s own body in VR with visuotactile stimulation (the body-​ swap illusion) alters body percept (i.e., participants are significantly fatter or thinner than they really are) suggesting, among other things, that VR is more than a way of placing people in a simulated world (i.e., manipulating their sense of place). A first study (Serino, Pedroli, et al., 2016) showed that the body-​swap illusion was able to update the negative stored representation of the body. In particular, it has been found that after embodying a virtual body with a skinny belly, women updated their “remembered body,” reporting a significant (postillusion) decrease in their body-​ size distortion. A similar result was obtained recently by Keizer, van Elburg, Helms, & Dijkerman (2016) using body swapping with a sample of 30 anorectic subjects: They decreased the overestimation of their shoulders, abdomen, and hips both after the illusion was induced and after a follow-​up (2 hours and 45 minutes after the illusions). These results can also be explained by taking a predictive account of brain functions (Friston, 2010), which suggests that the fundamental function of the brain is to constantly minimize the discrepancy between sensory inputs and prior beliefs about the causes of these inputs. When a strong mismatch occurs, an update of the internal models results. Consistent with this perspective, Preston and colleagues (Preston & Ehrsson, 2014) induced illusory ownership over a slimmer mannequin by synchronously stroking the mannequin’s body and the corresponding part of the participant’s body.

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They found that illusory ownership over a slimmer body significantly decreases participants’ perceived body size but also significantly increases their body satisfaction. Support for the use of bodily illusions to alter the dysfunctional experience of the bodily self also came from a recent published study (Serino, Scarpina, et al., 2016) showing that a (VR) body-​swap illusion, which generates the (converse) illusion that a fat person is thin, was able to increase body satisfaction and reduce body-​size distortion in a nonoperable super-​super obese patient (i.e., with body mass index > 60 kg/​m2). In addition to the improvement in the bodily experience, the illusion was able to increase the patient’s motivation to maintain healthy eating behaviors. While no studies to date have directly exploited the potential of bodily illusions in ED treatment, the evidence deriving from the extant experimental studies (1) for a direct link between perceptual (i.e., an inability to accurately estimate body size) and affective (i.e., subjective body-​dissatisfaction) body-​image components, and (2)  for a positive affective response with the body illusion modulated by eating disorder psychopathology (Dakanalis, Gaudio, et al., 2016) may suggest clinical applications for these methods (Serino & Dakanalis, 2016). Perpiñá’s group compared the effectiveness of VR with that of CBT for body image improvement (based on Cash, 1997) in a controlled study with a clinical population (Perpiña et  al., 1999). Specifically, they developed six different virtual environments, including a 3D figure whose body parts (arms, thighs, legs, breasts, stomach, buttocks, etc.) could be enlarged or reduced. The proposed approach addressed several body image dimensions: the body could be evaluated wholly or in parts; the body could be placed in different contexts (for instance, in the kitchen, before eating, after eating, facing attractive persons, etc.); behavioral tests could be performed in these contexts, and several discrepancy indices related to weight and figure could be combined (actual weight, subjective weight, desired weight, healthy weight, how the person thinks others see her/​him, etc.). In the published trial, 18 outpatients who had been diagnosed as suffering from EDs (AN or BN) were randomly assigned to one of the two treatment conditions: the VR condition (CBT plus VR) and the standard body image treatment condition (CBT plus relaxation). Thirteen of the initial 18 participants completed the treatment. The results showed that all patients improved significantly following 484

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treatment. However, those who had been treated with the VR component showed a significantly greater improvement in general psychopathology, ED psychopathology, and specific body image variables. What is more, these results were maintained at 1-​year follow-​up (Perpiñá et al., 2003). This group’s most recent controlled trial included 34 patients diagnosed with ED (Marco, Perpiñá, & Botella, 2013, 2014). Seventeen patients underwent VR-​enhanced CBT and 17 classical CBT. The CBT program for EDs enhanced by a body image-​specific component using VR techniques was shown to be more efficient than CBT alone in improvement of body image. Furthermore, improvement was maintained in post-​treatment and at 1-​year follow-​up.

Conclusions

Virtual reality has proven to be a useful technology in the study, assessment, and treatment of a variety of psychological disorders. Studies on the application of this technology in the treatment of EDs were some of the first ones conducted in the early 1990s. Since then, several VR applications have been developed to be used in conjunction with traditional treatments, and their effectiveness has been tested in case studies, as well as in noncontrolled and controlled trials. The VR-​based interventions in EDs usually combine exposure to VR environments with components based on cognitive therapy. Although the first VR-​based treatments were developed specifically to address body image disturbances, the literature shows that there are an increasing number of studies focused on other aspects, such as anxiety, craving, avoidance, grooming behaviors, self-​esteem, and self-​efficacy. Despite there being well-​established interventions that have proved effective for the treatment of EDs, relapses are frequent, and a proportion of patients do not improve after treatment. In this context, VR is a suitable technology for enhancing traditional CBT. The mechanisms underlying this effectiveness are probably linked with two characteristics of VR: It is an experiential and an embodied technology. Patients with EDs typically feel ambivalent about the idea of change for better health, because any change has advantages and disadvantages. Virtual reality is a special setting in which patients can explore and act; they can experiment and experience feelings and thoughts. The exposure to virtual environments produces emotional and behavioral responses similar to those that occur in the real world, but VR is not only a good tool to re-​create situations, it is also a place where patients learn to

challenge and cope with distorted mental representations. Most VR applications to date have been used to simulate external reality; it is also possible to use VR for the simulation of the internal reality, including the perception and ownership of the body. It is possible to use VR to induce controlled changes in the experience of the body, and this is particularly relevant given the role of body image disturbances in EDs. Typical VR systems involve different interfaces for human–​computer interaction that vary with the required level of immersion. The most basic level involves the presentation of virtual environments on computer screens; at the other extreme are technologically advanced systems such as head mounted displays (HMDs). Although HMDs can increase the user’s immersive experience, their use can be impractical in clinical settings; clinical centers are often reluctant to include VR interventions in their daily practice if it involves the use of expensive or technically complex instruments. Another concern is that HMDs may have side effects such as simulator sickness, or visual fatigue. In addition to these practical issues, the price of immersive HMDs with good tracker systems has been prohibitive until recently, which has delayed the development of advanced virtual environments for routine clinical practice. Low-​cost immersive HMDs have appeared on the market over the last year, allowing greater immersion at relatively economical prices. However, despite the development of low-​cost HMDs, some technical knowledge is still needed to use them properly, which may present a barrier to their wider clinical use. Thus, although low-​cost HMDs overcome economic drawbacks, the technological difficulties partly remain. Nonimmersive systems can also be useful. Incorporating more user-​ friendly nonimmersive VR devices and clinical applications that do not require significant technical knowledge, we could reduce the current usability concerns of VR techniques. Other problems such as simulator sickness or visual fatigue can also be reduced by using nonimmersive systems. This point should be taken into consideration, especially when the application of treatments using VR requires long periods of time in each session, thus raising the likelihood of the occurrence of simulator sickness or other similar sources of discomfort. Negative side effects of this kind are extremely rare when the virtual exposure is carried out by nonimmersive devices such as desktop computer screens or laptops with stereoscopic displays. However, even though nonimmersive systems have shown similar effectiveness as immersive

systems in VR exposure interventions, they cannot be used in other procedures, such as those focused on the production of the illusion of ownership of virtual bodies.

References

Agras, W., Walsh, B. T., Fairburn, C. G., Wilson, G. T., & Kraemer, H. C. (2000). A multicenter comparison of cognitive-​behavioral therapy and interpersonal psychotherapy for bulimia nervosa. Archives of General Psychiatry, 57, 459–​466. doi:10.1001/​archpsyc.57.5.459 Ahrberg, M., Trojca, D., Nasrawi, N., & Vocks, S. (2011). Body image disturbance in binge eating disorder: A review. European Eating Disorders Review, 19, 375–​381. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing. Amianto, F., Northoff, G., Abbate Daga, G., Fassino, S., & Tasca, G. A. (2016). Is Anorexia nervosa a disorder of the self? A psychological approach. Frontiers in Psychology, 7, 849. Baños, R. M., Botella, C., Alcaniz, M., Liano, V., Guerrero, B., & Rey, B. (2004). Immersion and emotion: Their impact on the sense of presence. Cyberpsychology and Behavior, 7, 734–​ 741. doi:10.1089/​cpb.2004.7.734 Baños, R. M., Botella, C., Guerrero, B., Liaño, V., Alcañiz, M., & Rey, B. (2005). The third pole of the sense of presence:  Comparing virtual and imagery spaces. PsychNology Journal, 3, 90–​100. http://​www.psychnology.org/​pnj103_​ banos_​botella_​guerriero_​liano_​alcaniz_​rey_​abstract.htm Baños, R. M., Botella, C., Rubio, I., Quero, S., Garcia-​Palacios, A., & Alcaniz, M. (2008). Presence and emotions in virtual environments: The influence of stereoscopy. Cyberpsychology and Behavior, 11, 1–​8. doi:10.1089/​cpb.2007.9936 Bechara, A., & Damasio, A. (2005). The somatic marker hypothesis:  A  neural theory of economic decision. Games and Economic Behavior, 52, 336–​372. Bergouignan, L., Nyberg, L., & Ehrsson, H. H. (2014). Out-​ of-​body-​induced hippocampal amnesia. Proceedings of the National Academy of Sciences, 111, 4421–​4426. doi:10.1073/​ pnas.1318801111 Berkman, N. D., Brownley, K. A., Peat, C. M., Lohr, K. N., Cullen, K. E., Morgan, L. C.,   .  .  .  Bulik, C. M. (2015). Management and outcomes of binge-​eating disorder. Comparative Effectiveness Review, 160. (Prepared by the RTI International–​University of North Carolina Evidence-​ Based Practice Center under Contract No. 290-​2012-​00008-​ I.) AHRQ Publication No. 15(16)-​EHC030-​EF. Rockville, MD: Agency for Healthcare Research and Quality; December 2015. www.effectivehealthcare.ahrq.gov/​reports/​final.cfm Booth, R., & Rachman, S. (1992). The reduction of claustrophobia—​ I. Behaviour Research and Therapy, 30, 207–​221. Botella, C., Quero, S., Baños, R. M., Perpina, C., Garcia Palacios, A., & Riva, G. (2004). Virtual reality and psychotherapy. Studies in Health Technology and Informatics, 99, 37–​54. Botvinick, M., & Cohen, J. (1998). Rubber hands “feel” touch that eyes see. Nature, 391, 756. doi:10.1038/​35784 Bouton, M. E. (2011). Learning and the persistence of appetite:  Extinction and the motivation to eat and overeat. Physiology and Behavior, 103, 51–​58. Bulik, C. M., Sullivan, P. F., Carter, F. A., McIntosh, V. V., & Joyce, P. R. (1998). The role of exposure with response prevention in the cognitive-​ behavioural therapy for bulimia

Gutiérre z-Maldonado, Ferrer-García, Dakanalis, Riva

485

nervosa. Psychological Medicine, 28, 611–​623. doi:10.1017/​ S0033291798006618 Burdea, G. C., & Coiffet, P. (2003). Virtual reality technology (2nd ed.). New Brunswick, NJ: Wiley-​IEEE Press. Butters, J. W., & Cash, T. F. (1987). Cognitive-​behavioral treatment of women’s body image satisfaction:  A  controlled outcome-​study. Journal of Consulting and Clinical Psychology, 55, 889–​897. Cafri, G., Olivardia, R., & Thompson, J. K. (2008). Symptom characteristics and psychiatric comorbidity among males with muscle dysmorphia. Comprehensive Psychiatry, 49, 374–​ 379. doi:10.1016/​j.comppsych.2008.01.003 Calogero, R. M. (2009). Objectification processes and disordered eating in British women and men. Journal of Health Psychology, 14, 394–​402. doi:10.1177/​1359105309102192 Calogero, R. M., Tantleff-​Dunn, S., & Thompson, J. K. (2010). Self-​ objectification in women:  Causes, consequences, and counteractions. Washington, DC:  American Psychological Association. Carter, F., & Bulik, C. M. (1994). Exposure treatments for bulimia nervosa: Procedure, efficacy, and mechanisms. Advances in Behavior Research and Therapy, 16, 77–​129. Cash, T. F. (1997). The body image workbook:  An eight-​ step program for learning to like your looks. Oakland, CA:  New Harbinger. Cash, T. F., & Deagle, E. A. (1997). The nature and extent of body image disturbances in anorexia nervosa and bulimia nervosa:  A  meta-​analysis. International Journal of Eating Disorders, 22, 107–​125. Cason, A. M., Smith, R. J., Tahsili-​Fahadan, P., Moorman, D. E., Sartor G. C., & Aston-​Jones, G. (2010). Role of orexin/​ hypocretin in reward-​seeking and addiction: Implications for obesity. Physiology and Behavior, 100, 419–​458. doi:10.1016/​ j.physbeh.2010.03.009 Castelvecchi, D. (2016). Low-​ cost headsets boost virtual reality’s lab appeal. Nature, 533, 153–​154. doi:10.1038/​ 533153a Cesa, G. L., Manzoni, G. M., Bacchetta, M., Castelnuovo, G., Conti, S., Gaggioli, A.,  . . .  Riva, G. (2013). Virtual reality for enhancing the cognitive behavioral treatment of obesity with binge eating disorder:  Randomized controlled study with one-​year follow-​up. Journal of Medical Internet Research, 15, e113. doi:10.2196/​jmir.2441 Costantini, M. (2014). Body perception, awareness, and illusions. Wiley Interdisciplinary Reviews:  Cognitive Science, 5, 551–​560. doi:10.1002/​wcs.1309 Dakanalis, A., Clerici, M., Caslini, M., Gaudio, S., Serino, S., Riva, G., & Carra, G. (2016). Predictors of initiation and persistence of recurrent binge eating and inappropriate weight compensatory behaviors in college men. International Journal of Eating Disorders, 49, 581–​590. doi:10.1002/​eat.22535 Dakanalis, A., Clerici, M., Di Mattei, V. E., Caslini, M., L., F., Bagliacca, E. P.,  . . .  Zanetti, M. A. (2013). Internalization of sociocultural standards of beauty and eating disordered behaviours: The role of body surveillance, shame, and social anxiety. Journal of Psychopathology, 20, 33–​37. Dakanalis, A., Di Mattei, V. E., Bagliacca, E. P., Prunas, A., Sarno, L., Riva, G., & Zanetti, M. A. (2012). Disordered eating behaviors among Italian men: Objectifying media and sexual orientation differences. Eating Disorders, 20, 356–​ 367. doi:10.1080/​10640266.2012.715514 Dakanalis, A., Favagrossa, L., Clerici, M., Prunas, A., Colmegna, F., Zanetti, M. A., & Riva, G. (2015). Body dissatisfaction

486

Virtual Realit y

and eating disorder symptomatology:  A  latent structural equation modeling analysis of moderating variables in 18-​ to-​28-​year-​old males. Journal of Psychology, 149, 85–​112. doi:10.1080/​00223980.2013.842141 Dakanalis, A., Gaudio, S., Serino, S., Clerici, M., Carrà, G., & Riva, G. (2016). Body-​image distortion in anorexia nervosa. Nature Reviews Disease Primers, 2, 16026. doi:10.1038/​ nrdp.2016.26 Dakanalis, A., & Riva, G. (2013a). Current considerations for eating and body-​related disorders among men. In J. Latzer, J. Merrick, & D. Stein (Eds.), Body image: Gender differences, sociocultural influences and health implication (pp. 195–​216). New York, NY: Nova Science. Dakanalis, A., & Riva, G. (2013b). Mass media, body image and eating disturbances: The underlying mechanism through the lens of the objectification theory. In J. Latzer, J. Merrick, & D. Stein (Eds.), Body image: Gender differences, sociocultural influences and health implication (pp. 217–​236). New York, NY: Nova Science. Dakanalis, A., Timko, A. C., Clerici, C., Zanetti, A. M., & Riva, G. (2014). Comprehensive examination of the trans-​ diagnostic cognitive behavioral model of eating disorders in males. Eating Behaviors, 15, 63–​67. doi:10.1016/​ j.eatbeh.2013.10.003 Dakanalis, A., Timko, A. C., Madeddu, F., Volpato, C., Clerici, M., Riva, G., & Zanetti, A. M. (2015). Are the male body dissatisfaction and drive for muscularity scales reliable and valid instruments? Journal of Health Psychology, 20(1), 48–​ 59. doi:10.1177/​1359105313498108 Dakanalis, A., Zanetti, M. A., Riva, G., & Clerici, M. (2013). Psychosocial moderators of the relationship between body dissatisfaction and symptoms of eating disorders: A look at a sample of young Italian women. European Review of Applied Psychology-​Revue Européenne de Psychologie Appliquée, 63, 323–​334. doi:10.1016/​j.erap.2013.08.001 Dakanalis, A., Zanetti, A. M., Riva, G., Colmegna, F., Volpato, C., Madeddu, F., & Clerici, M. (2015). Male body dissatisfaction and eating disorder symptomatology:  Moderating variables among men. Journal of Health Psychology, 20(1), 80–​90. doi:  10.1177/​ 1359105313499198. doi:10.1177/​ 1359105313499198 deShazer, S. (1985). Keys to solutions in brief therapy. New York, NY: Norton. Dieguez, S., & Lopez, C. (2016). The bodily self: Insights from clinical and experimental research. Annals of Physical and Rehabilitation Medicine. doi:10.1016/​j.rehab.2016.04.007 Diemer, J., Alpers, G. W., Peperkorn, H. M., Shiban, Y., & Muhlberger, A. (2015). The impact of perception and presence on emotional reactions: A review of research in virtual reality. Frontiers in Psychology, 6, 26. doi:10.3389/​fpsyg.2015.00026 Dunsmoor, J. E., Ahs, F., Zielinski, D. J., & LaBar, K. S. (2014). Extinction in multiple virtual reality contexts diminishes fear reinstatement in humans. Neurobiology of Learning and Memory, 113, 157–​164. doi:10.1016/​j.nlm.2014.02.010 Ehrsson, H. H. (2007). The experimental induction of out-​of-​ body experiences. Science, 5841, 1048. Espeset, E. M. S., Gulliksen, K. S., Nordbo, R. H. S., Skarderud, F., & Holte, A. (2012). Fluctuations for body images in anorexia nervosa: Patients’ perception of contextual triggers. Clinical Psychology and Psychotherapy, 19, 518–​530. Etu, S. F., & Gray J. J. (2010). A preliminary investigation of the relationship between induced rumination and state body image dissatisfaction and anxiety. Body Image, 7, 82–​85.

Fairburn, C. G., Marcus, M. D., & Wilson, G. T. (1993). Cognitive behaviour therapy for binge eating and bulimia nervosa: A treatment manual. In C. G. Fairburn and G. T. Wilson (Eds.), Binge eating: Nature, assessment and treatment (pp. 361–​404). New York, NY: Guilford Press. Fairburn, C. G., Bailey-​Straebler, S., Basden, S., Doll, H. A., Jones, R., Murphy, R.,  . . .  Cooper, Z. (2015). A transdiagnostic comparison of enhanced cognitive behaviour therapy (CBT-​E) and interpersonal psychotherapy in the treatment of eating disorders. Behavior Research and Therapy, 70, 64–​71. Ferrer-​García, M., & Gutiérrez-​ Maldonado, J. (2008). Body image assessment software:  Psychometric data. Behavior Research Methods, 40, 394–​407. Ferrer-​Garcia, M., & Gutierrez-​Maldonado, J. (2010). Effect of the mood produced by virtual reality exposure on body image disturbances. Studies in Health Technology and Informatics, 154, 44–​49. Ferrer-​Garcia, M., & Gutierrez-​Maldonado, J. (2012). The use of virtual reality in the study, assessment, and treatment of body image in eating disorders and nonclinical samples: A review of the literature. Body Image, 9, 1–​11. doi:  10.1016/​ j.bodyim.2011.10.001 Ferrer-​García, M., Gutiérrez-​Maldonado, J., Agliaro-​López, M., Lobera-​Espi, X., Pla, J., & Vilalta-​Abella, F. (2014). Validation of VR-​ based software for binge eating treatment:  Preliminary data. Studies in Health Technology and Informatics, 199, 146–​150. Ferrer-​García, M., Gutiérrez-​Maldonado, J., Caqueo-​Urízar, A., & Moreno, E. (2009). The validity of virtual environments for eliciting emotional responses in patients with eating disorders and in controls. Behavior Modification, 3, 830–​854. Ferrer-​ Garcia, M., Gutiérrez-​Maldonado, J., Pla-​Sanjuanelo, J., Vilalta-​Abella, F., Andreu-​Gracia, A., Dakanalis, A.,  . . .  Sánchez, I. (2015). External eating as a predictor of cue-​ reactivity to food-​ related virtual environments. Annual Review of CyberTherapy and Telemedicine, 13, 117–​122. Ferrer-​Garcia, M., Gutiérrez-​Maldonado, J., & Riva, G. (2013). Virtual reality based treatments in eating disorders and obesity: A review. Journal of Contemporary Psychology, 43, 207–​ 221. doi:10.1007/​s10879-​013-​9240-​1 Fotopoulou, A. (2015). The virtual bodily self:  Mentalisation of the body as revealed in anosognosia for hemiplegia. Consciousness and Cognition, 33, 500–​510. doi:10.1016/​ j.concog.2014.09.018 Fredrickson, B. L., & Roberts, T. (1997). Objectification theory: Toward understanding women’s lived experiences and mental health risks. Psychology of Women Quarterly, 21, 173–​206. Friston, K. (2010). The free-​ energy principle:  A  unified brain theory? Nature Reviews Neuroscience, 11, 127–​138. doi:10.1038/​nrn2787 Gallace, A., & Spence, C. (2014). Outside the boundaries of our bodies: The relationship between touch and the representation of the body in our mind. In A. Gallace & C. Spence (Eds.), In touch with the future: The sense of touch from cognitive neuroscience to virtual reality (pp. 102–​124). Oxford, UK: Oxford University Press. Gaudio, S., & Riva, G. (2013). Body image disturbances in anorexia:  The link between functional connectivity alterations and reference frames. Biological Psychiatry, 73, e25–​e26. doi:10.1016/​j.biopsych.2012.08.028 Gaudio, S., & Quattrocchi, C. C. (2012). Neural basis of a multidimensional model of body image distortion in anorexia nervosa. Neuroscience and Biobehavioral Reviews, 36, 1839–​1847.

Gaudio, S., Wiemerslage, L., Brooks, S. J., & Schioth, H. B. (2016). A systematic review of resting-​state functional-​MRI studies in anorexia nervosa:  Evidence for functional connectivity impairment in cognitive control and visuospatial and body-​signal integration. Neuroscience and Biobehavioral Reviews, 71, 578–​589. doi:10.1016/​j.neubiorev.2016.09.032 Glantz, K., Durlach, N. I., Barnett, R. C., & Aviles, W. A. (1997). Virtual reality (VR) and psychotherapy: Opportunities and challenges. Presence, Teleoperators, and Virtual Environments, 6, 87–​105. Gorini, A., Capideville, C. S., De Leo, G., Mantovani, F., & Riva, G. (2011). The role of immersion and narrative in mediated presence:  The virtual hospital experience. Cyberpsychology, Behavior, and Social Networking, 14, 99–​105. doi:10.1089/​ cyber.2010.0100 Gorini, A., Gaggioli, A., Vigna, C., & Riva, G. (2008). A second life for eHealth: Prospects for the use of 3-​D virtual worlds in clinical psychology. Journal of Medical Internet Research, 10, e21. Gorini, A., Griez, E., Petrova, A., & Riva, G. (2010). Assessment of the emotional responses produced by exposure to real food, virtual food and photographs of food in patients affected by eating disorders. Annals of General Psychiatry, 9(30). doi: 10.1186/​1744-​859X-​9-​30 Gorini, A., & Riva, G. (2008). Virtual reality in anxiety disorders:  The past and the future. Expert Review of Neurotherapeutics, 8, 215–​233. Gutierrez-​ Maldonado, J., Ferrer-​ Garcia, M., Caqueo-​ Urizar, A., & Moreno, E. (2009). The validity of virtual environments for eliciting emotional responses in patients with eating disorders and in controls. Behaviour Modification, 33, 830–​854. Gutiérrez-​Maldonado, J., Ferrer-​García, M., Caqueo-​ Urízar, A., & Moreno, E. (2010). Body image in eating disorders:  The influence of exposure to virtual environments. CyberPsychology and Behavior, 13, 521–​531. Gutiérrez-​Maldonado, J., Pla-​Sanjuanelo, J., & Ferrer-​García, M. (2016). Cue-​ exposure software for the treatment of bulimia nervosa and binge eating disorder. Psicothema, 28. doi: 10.7334/​psicothema2014.274 Gutierrez-​Maldonado, J., Wiederhold, B. K., & Riva, G. (2016). Future directions:  How virtual reality can further improve the assessment and treatment of eating disorders and obesity. Cyberpsychology, Behavior, and Social Networking, 19, 148–​ 153. doi:10.1089/​cyber.2015.0412 Haimovitz, D., Lansky, L. M., & O’Reilly, P. (1993). Fluctuations in body satisfaction across situations. International Journal of Eating Disorders, 13, 77–​84. Hale, K. S., & Stanney, K. M. (Eds.). (2014). Handbook of virtual environments: Design, implementation, and applications (2nd ed.). Roca Baton, FL: CRC Press. Hay, P. J., & Claudino, A. M. (2010). Evidence-​based treatment for the eating disorders. In W. Stewart Agras (Ed.), The Oxford handbook of eating disorders (pp. 452–​479). Oxford, UK:  Oxford University Press. doi:  10.1093/​ oxfordhb/​ 9780195373622.013.0025 Haynos, A. F., Watts, A. W., Loth, K. A., Pearson, C. M., Neumark-​Stzainer, D. (2016). Factors predicting an escalation of restrictive eating during adolescence. Journal of Adolescent Health, 59, 391–​396. Heilbrun, A. B., & Flodin, A. (1989). Food cues and perceptual distortion of the female body: Implications for food avoidance in the early dynamics of anorexia nervosa. Journal of Clinical Psychology, 45, 843–​851.

Gutiérre z-Maldonado, Ferrer-García, Dakanalis, Riva

487

Hildebrandt, T., Bacow, T., Markella, M., & Loeb, K. L. (2012). Anxiety in anorexia nervosa and its management using family-​based treatment. European Eating Disorders Review, 20, 1–​16. doi: 10.1002/​erv.1071 Hildebrandt, T., Loeb, K., Troupe, S., & Delinsky, S. (2012). Adjunctive mirror exposure for eating disorders: A randomized controlled pilot study. Behaviour Research and Therapy, 50, 797–​804. Hodges, L. F., Rothbaum, B. O., Alarcon, R., Ready, D., Shahar, F., Graap, K.,   .  .  .  Baltzell, D. (1998). Virtual Vietnam: A virtual environment for the treatment of Vietnam War veterans with post-​traumatic stress disorder. Paper presented at the International Conference on Artificial Reality and Tele-​Existence. Tokyo. Hone-​Blanchet, A., Wensing, T., & Fecteau, S. (2014). The use of virtual reality in craving assessment and cue-​exposure therapy in substance use disorders. Frontiers in Human Neuroscience, 8. Published online 2014 Oct 17. doi: 10.3389/​ fnhum.2014.00844 Jansen, A. (1994). The learned nature of binge eating. In C. R. Legg & D. A. Booth (Eds.), Appetite: Neural and behavioral bases (pp. 193–​211). Oxford, UK: Oxford University Press. Jansen, A. (1998). A learning model of binge eating: Cue reactivity and cue exposure. Behaviour Research and Therapy, 36, 257–​272. Jansen, A., Broekmate, J., & Heymans, M. (1992). Cue exposure vs. self-​control in the treatment of binge eating. Behaviour Research and Therapy, 3, 235–​241. Jansen, A., van den Hout, M. A., de Loof, C., Zandbergen, J., & Griez, E. (1989). A case of bulimia successfully treated by cue exposure. Journal of Behavior Therapy and Experimental Psychiatry, 20, 327–​332. Keizer, A., van Elburg, A., Helms, R., & Dijkerman, H. C. (2016). A virtual reality full body illusion improves body image disturbance in anorexia nervosa. PLoS One, 11, e0163921. doi:10.1371/​journal.pone.0163921 Kennedy, R. S., Stanney, K. M., & Dunlap, W. P. (2000). Duration and exposure to virtual environments:  Sickness curves during and across sessions. Presence: Teleoperators and Virtual Environments, 9, 463–​472. Lattimore, P., & Hutchinson, R. (2010). Perceived calorie intake and state body-​image satisfaction in women attempting weight loss: A preliminary investigation. Body Image, 7, 15–​21. Lee, K. M. (2004). Presence, explicated. Communication Theory, 14, 27–​50. Lenggenhager, B., Tadi, T., Metzinger, T., & Blanke, O. (2007). Video ergo sum:  manipulating bodily self-​ consciousness. Science, 317, 1096–​1099. doi: 10.1126/​science.1143439 Leuner, H. (1969). Guided affective imagery: A method of intensive psychotherapy. American Journal of Psychotherapy, 23, 4–​21. Ling, Y., Nefs, H. T., Morina, N., Heynderickx, I., & Brinkman, W. P. (2014). A meta-​analysis on the relationship between self-​reported presence and anxiety in virtual reality exposure therapy for anxiety disorders. PLoS One, 9, e96144. doi:10.1371/​journal.pone.0096144 Lombard, M., Biocca, F., Freeman, J., IJsselsteijn, W., & Schaevitz, R. J. (Eds.). (2015). Immersed in media:  Telepresence theory, measurement and technology. Heidelberg, Germany: Springer. Mahler, S. V., & de Wit, H. (2010). Cue-​Reactors:  Individual Differences in Cue-​Induced Craving after Food or Smoking Abstinence. PLoS ONE, 5(11), e15475. doi:10.1371/​journal.pone.0015475

488

Virtual Realit y

Makinen, M., Puukko-​Viertomies, L. R., Lindberg, N., Siimes, M. A., & Aalberg, V. (2012). Body dissatisfaction and body mass in girls and boys transitioning from early to mid-​ adolescence: Additional role of self-​esteem and eating habits. BMC Psychiatry, 12, 35. doi:10.1186/​1471-​244X-​12-​35 Manzoni, G. M., Cesa, G. L., Bacchetta, M., Castelnuovo, G., Conti, S., Gaggioli, A.,  . . .  Riva, G. (2016). Virtual reality-​ enhanced cognitive-​ behavioral therapy for morbid obesity: A randomized controlled study with 1 year follow-​up. Cyberpsychology, Behavior, and Social Networking, 19, 134–​ 140. doi:10.1089/​cyber.2015.0208 Marco, J. H., Perpina, C., & Botella, C. (2013). Effectiveness of cognitive behavioral therapy supported by virtual reality in the treatment of body image in eating disorders:  One year follow-​up. Psychiatry Research, 209, 619–​625. doi:10.1016/​ j.psychres.2013.02.023 Marco, J. H., Perpiñá, C., & Botella, C. (2014). The treatment of the body image disturbances in eating disorders and clinically significant change. Anales de Psicología/​Annals of Psychology, 30, 422–​430. Maselli, A., & Slater, M. (2014). Sliding perspectives: Dissociating ownership from self-​location during full body illusions in virtual reality. Frontier is Human Neuroscience, 8. doi:10.3389/​ fnhum.2014.00693 Martínez-​Mallén, E., Castro-​Fornieles, J., Lázaro, L., Moreno, E., Morer, A., Font, E.,  . . .  Toro, J. (2007). Cue exposure in the treatment of resistant adolescent bulimia nervosa. International Journal of Eating Disorders, 40(7), 596–​601. Doi: 10.1002/​eat.20423 McFarland, B. (1995). Brief therapy and eating disorders. San Francisco, CA: Jossey-​Bass. McFarlane, T., Olmsted, M. P., & Trottier, K. (2008). Timing and prediction of relapse in a transdiagnostic eating disorder sample. International Journal of Eating Disorders, 41, 587–​593. McKenzie, S. J., Williamson, D. A., & Cubic, B. A. (1993). Stable and reactive body image disturbance in bulimia nervosa. Behavior Therapy, 24, 195–​207. Melzack, R. (2005). Evolution of the neuromatrix theory of pain. The Prithvi Raj Lecture: Presented at the Third World Congress of World Institute of Pain, Barcelona 2004. Pain Practice, 5, 85–​94. Morgan, J. F., Lazarova, S., Schelhase, M., & Saeidi, S. (2014). Ten Session Body Image Therapy: Efficacy of a Manualised Body Image Therapy. European Eating Disorders Review, 22(1), 66–​71. Murray, S. B., Rieger, E., Hildebrandt, T., Karlov, L., Russell, J., Boon, E.,  . . .  Touyz, S. W. (2012). A comparison of eating, exercise, shape, and weight related symptomatology in males with muscle dysmorphia and anorexia nervosa. Body Image, 9, 193–​200. doi:10.1016/​j.bodyim.2012.01.008 Mountford, V. A., Tchanturia, K., & Valmaggia, L. (2016). “What are you thinking when you look at me?” A pilot study of the use of virtual reality in body image. Cyberpsychology, Behavior, and Social Networking, 19, 93–​99. Myers, P. N., & Biocca, F. A. (1992). The elastic body image: The effect of television advertisement and programming on body image distortions in young women. Journal of Communication, 42, 108–​133. Myers, T. C., Swan-​Kremeier, L., Wonderlich, S., Lancaster, K., & Mitchell, J. E. (2004). The use of alternative delivery systems and new technologies in the treatment of patients with eating disorders. International Journal of Eating Disorders, 36, 123–​143.

Nair, S. G., Adams-​Deutscha, T., Epsteinb, D. H., Shaham, Y. (2009). The neuropharmacology of relapse to food seeking:  Methodology, main findings, and comparison with relapse to drug seeking. Progress in Neurobiology, 89(1), 18–​45. National Institute for Health and Clinical Excellence (2004). Eating Disorders: core interventions in the treatment and management of anorexia nervosa, bulimia nervosa and eating disorders. Clinical Guideline 9. National Institute of Excellence, London. North, M. M., & North, S. M. (1994). Virtual environments and psychological disorders. Electronic Journal of Virtual Culture, 2, 37–​42 (ep.). North, M. M., & North, S. M. (2000). Virtual reality combats obsessive-​ compulsive disorders (OCD). In Proceedings of Medicine Meets Virtual Reality (8th Annual Medicine Meets Virtual Reality Conference), James Westwood, et  al. eds., IOS Press, Amsterdam. North, M. M., North, S. M., & Coble, J. R. (1995). Effectiveness of virtual environment desensitization in the treatment of agoraphobia. International Journal of Virtual Reality, 1, 25–​34. North, M. M., North, S. M., & Coble, J. R. (1997). Virtual reality therapy:  An effective treatment for psychological disorders. Studies in Health Technology and Informatics, 44, 59–​70. North, M. M., North, S. M., Coble, J. R. (1998). Virtual Reality Therapy:  an Effective Treatment for the Fear of Public Speaking. The International Journal of Virtual Reality 3, 1–​6. Olive, I., & Berthoz, A. (2012). Combined induction of rubber-​ hand illusion and out-​ of-​ body experiences. Frontiers in Psychology, 3, 128. doi:10.3389/​fpsyg.2012.00128 Perez-​Marcos, D., Slater, M., & Sanchez-​Vives, M. V. (2009). Inducing a virtual hand ownership illusion through a brain-​ computer interface. Neuroreport, 20, 589–​594. Pericot-​ Valverde, I., García-​Rodríguez, O., Gutiérrez-​ Maldonado, G., & Secades-​Villa, R. (2015). Individual variables related to craving reduction in cue exposure treatment. Addictive Behaviors, 49, 59–​63. Perpiña, C., Botella, C., & Baños, R. M. (2003). Virtual reality in eating disorders. European Eating Disorders Review, 11, 261–​278. Perpiña, C., Botella, C., Baños, R. M., Marco, J. H., Alcañiz, M., & Quero, S. (1999). Body image and virtual reality in eating disorders: Exposure by virtual reality is more effective than the classical body image treatment? Cyberpsychology and Behavior, 3, 149–​159. Pillai, J. S., Schmidt, C., & Richir, S. (2013). Achieving presence through evoked reality. Frontiers in Psychology, 4. doi:10.3389/​fpsyg.2013.00086 Pla-​Sanjuanelo, J., Ferrer-​Garcia, M., Gutiérrez-​Maldonado, J., Vilalta-​Abella, F., Andreu-​Gracia, A., Dakanalis, A.,  . . .  Sánchez, I. (2015). Trait and state craving as indicators of validity of VR-​ based software for binge eating treatment. Annual Review of CyberTherapy and Telemedicine, 13, 141–​146. Pomes, A., & Slater, M. (2013). Drift and ownership toward a distant virtual body. Frontiers in Human Neuroscience, 7, 908. doi:10.3389/​fnhum.2013.00908 Preston, C., & Ehrsson, H. H. (2014). Illusory changes in body size modulate body satisfaction in a way that is related to non-​clinical eating disorder psychopathology. PLoS One, 9. doi:10.1371/​journal.pone.0085773 Quintana, P., Bouchard, S., Serrano, B., & Cárdenas-​López, G. (2014). Efectos secundarios negativos de la inmersión

con realidad virtual en poblaciones clínicas que padecen ansiedad. Revista de Psicopatología y Psicología Clínica, 19, 197–​207. doi:  http://​dx.doi.org/​10.5944/​rppc.vol.19. num.3.2014.13901 Regan, E. C., & Price, K. R. (1993). Some side-​effects of immersion virtual reality: The effects of increasing head movements, of rapid interaction, and of seated subjects (Report 93R022). Retrieved from Farnborough (UK):  Army Personnel Research Establishment. http://​discovery.nationalarchives.gov.uk Riva, G. (Ed.) (1997). Virtual reality in neuro-​ psycho-​ physiology:  Cognitive, clinical and methodological issues in assessment and rehabilitation. Amsterdam: IOS Press. http://​ www.cybertherapy.info/​pages/​book1.htm Riva, G. (1998a). Modifications of body image induced by virtual reality. Perceptual and Motor Skills, 86, 163–​170. Riva, G. (1998b). Virtual environments in neuroscience. IEEE Transactions on Information Technology in Biomedicine, 2, 275–​281. Riva, G. (1998c). Virtual reality in psychological assessment:  The body image virtual reality scale. Cyberpsychology and Behavior, 1, 37–​44. Riva, G. (2007). Virtual body, real pain:  The allocentric lock hypothesis. In M. Zampini & F. Pavani (Eds.), Body representation workshop. Rovereto, Italy: Università degli Studi di Trento, p. 72 http://​www.cimec.unitn.it/​events/​brw/​Poster/​ 107_​abs_​GIUSEPPE_​RIVA.pdf ). Riva, G. (2009). Is presence a technology issue? Some insights from cognitive sciences Virtual Reality, 13, 59–​69. Riva, G. (2011). The key to unlocking the virtual body: Virtual reality in the treatment of obesity and eating disorders. Journal of Diabetes Science and Technology, 5, 283–​292. Riva, G. (2012). Neuroscience and eating disorders:  The allocentric lock hypothesis. Medical Hypotheses, 78, 254–​257. doi:10.1016/​j.mehy.2011.10.039 Riva, G. (2014a). Medical clinical uses of virtual worlds. In M. Grimshaw (Ed.), The Oxford handbook of virtuality (pp. 649–​ 665). New York, NY: Oxford University Press. Riva, G. (2014b). Out of my real body: Cognitive neuroscience meets eating disorders. Frontiers in Human Neuroscience, 8, 236. doi:10.3389/​fnhum.2014.00236 Riva, G. (2016). Embodied Medicine: What Human-​Computer Confluence Can Offer to Health Care. In A. Gaggioli, A. Ferscha, G. Riva, S. Dunne, & I. Viaud-​Delmon (Eds.), Human Computer Confluence:  Transforming Human Experience Through Symbiotic Technologies (pp. 55–​79). Warsaw: De Gruyter Open. Riva, G., Bacchetta, M., Baruffi, M., & Molinari, E. (2001). Virtual reality-​based multidimensional therapy for the treatment of body image disturbances in obesity:  A  controlled study. Cyberpsychology and Behavior, 4, 511–​526. Riva, G., Bacchetta, M., Baruffi, M., & Molinari, E. (2002). Virtual-​ reality-​ based multidimensional therapy for the treatment of body image disturbances in binge eating disorders: A preliminary controlled study. IEEE Transactions on Information Technology in Biomedicine, 6, 224–​234. Riva, G., Bacchetta, M., Baruffi, M., Rinaldi, S., & Molinari, E. (1999). Virtual reality based experiential cognitive treatment of anorexia nervosa. Journal of Behavioral Therapy and Experimental Psychiatry, 30, 221–​230. Riva, G., Bacchetta, M., Baruffi, M., Rinaldi, S., Vincelli, F., & Molinari, E. (2000). Virtual reality-​based experiential cognitive treatment of obesity and binge-​eating disorders. Clinical Psychology and Psychotherapy, 7, 209–​219.

Gutiérre z-Maldonado, Ferrer-García, Dakanalis, Riva

489

Riva, G., Bacchetta, M., Cesa, G., Conti, S., Castelnuovo, G., Mantovani, F., & Molinari, E. (2006). Is severe obesity a form of addiction? Rationale, clinical approach, and controlled clinical trial. CyberPsychology and Behavior, 9, 457–​479. Riva, G., Bacchetta, M., Cesa, G., Conti, S., & Molinari, E. (2002). e-​ health in eating disorders:  Virtual Reality and telemedicine in assessment and treatment. Studies in Health Technology and Informatics, 85, 402–​408. Riva, G., Bacchetta, M., Cesa, G., Conti, S., & Molinari, E. (2003). Six-​ month follow-​ up of in-​ patient experiential-​ cognitive therapy for binge eating disorders. Cyberpsychology and Behavior, 6, 251–​258. Riva, G., Bacchetta, M., Cesa, G., Conti, S., & Molinari, E. (2004). The use of VR in the treatment of eating disorders. Studies in Health Technology and Informatics, 99, 121–​163. Riva, G., Baños, R., Botella, C., Mantovani, F., & Gagglioli, A. (2016). Transforming experience:  The potential of augmented reality and virtual reality for enhancing personal and clinical change. Frontiers in Psychiatry, 7, 164. doi: 10.3389/​ fpsyt.2016.00164 Riva, G., Botella, C., Baños, R., Mantovani, F., García-​Palacios, A., Quero, S.,  . . .  Gaggioli, A. (2015). Presence-​inducing media for mental health applications. In M. Lombard, F. Biocca, J. Freeman, W. Ijsselsteijn, & R. J. Schaevitz (Eds.), Immersed in media (pp. 283–​332). New York, MY: Springer International. Riva, G., Dakanalis, A., & Mantovani, F. (2015). Leveraging psychology of virtual body for health and wellness. In S. S. Sundar (Ed.), The handbook of the psychology of communication technology (pp. 528–​547). Chichester, UK: Wiley. Riva, G., Davide, F., & IJsselsteijn, W. A. (Eds.). (2003). Being there:  Concepts, effects and measurements of user presence in synthetic environments. Amsterdam:  Ios Press. http://​www. emergingcommunication.com/​volume5.html Riva, G., Gaggioli, A., Villani, D., Preziosa, A., Morganti, F., Corsi, R.,   .  .  .  Vezzadini, L. (2007). NeuroVR:  An open source virtual reality platform for clinical psychology and behavioral neurosciences. Studies in Health Technology and Informatics, 125, 394–​399. Riva, G., & Gaudio, S. (in press). Locked to a wrong body: Eating disorders as the outcome of a primary disturbance in multisensory body integration. Consciousness and Cognition. doi: 10.1016/j.concog.2017.08.006 Riva, G., Gaudio, S., & Dakanalis, A. (2015). The neuropsychology of self objectification. European Psychologist, 20, 34–​43. doi:10.1027/​1016-​9040/​a000190 Riva, G., & Mantovani, F. (2012a). Being there: Understanding the feeling of presence in a synthetic environment and its potential for clinical change. In C. Eichenberg (Ed.), Virtual reality in psychological, medical and pedagogical applications. (pp.  3–​34). New  York, NY:  InTech. http://​ w ww.intechopen.com/ ​ b ooks/ ​ v irtual- ​ r eality- ​ i n-​ psychological-​ m edical- ​ a nd- ​ p edagogical- ​ a pplications/​ being-​there-​understanding-​the-​feeling-​of-​presence-​in-​a-​ synthetic-​environment-​and-​its-​potential-​for-​c 3-​34 Riva, G., & Mantovani, F. (2012b). From the body to the tools and back: A general framework for presence in mediated interactions. Interacting with Computers, 24, 203–​210. doi:10.1016/​j.intcom.2012.04.007 Riva, G., & Mantovani, F. (2014). Extending the self through the tools and the others: A general framework for presence

490

Virtual Realit y

and social presence in mediated interactions. In G. Riva, J. A. Waterworth, & D. Murray (Eds.), Interacting with presence:  HCI and the sense of presence in computer-​ mediated environments (pp. 12–​34). Berlin: De Gruyter Open. http://​ www.presence-​research.com/​ Riva, G., Mantovani, F., & Gaggioli, A. (2004). Presence and rehabilitation:  Toward second-​ generation virtual reality applications in neuropsychology. Journal of Neuroengineering and Rehabilitation, 1, 9.  doi:1743-​ 10.1186/​1743-​0003-​1-​9 Riva, G., & Melis, L. (1997). Virtual reality for the treatment of body image disturbances. Studies in Health Technology and Informatics, 44, 95–​111. Riva, G., Melis, L., & Bolzoni, M. (1997). Treating body image disturbances. Communications of the ACM, 40, 69–​71. Riva, G., & Waterworth, J. A. (2003). Presence and the self:  A  cognitive neuroscience approach. Presence-​Connect, 3, 1–​14. http://​www8.informatik.umu.se/​~jwworth/​Riva-​ Waterworth.htm Riva, G., Waterworth, J. A., & Murray, D. (Eds.). (2014). Interacting with presence:  HCI and the sense of presence in computer-​mediated environments. Berlin: De Gruyter Open. http://​www.presence-​research.com/​ Riva, G., & Wiederhold, B. K. (2015). The new dawn of virtual reality in health care:  Medical simulation and experiential interface. Annual Review of CyberTherapy and Telemedicine, 13, 3–​6. Rizzo, A. A., Buckwalter, J. G., Bowerly, T., Van Der Zaag, C., Humphrey, L., Neumann, U.,   .  .  .  Sisemore, D. (2000). The Virtual Classroom:  A  virtual reality environment for the assessment and rehabilitation of attention deficits. Cyberpsychology and Behavior, 3(3), 483–​499. Rizzo, A. A., Schultheis, M. T., & Rothbaum, B. O. (2002). Ethical issues for the use of virtual reality in the psychological sciences. In S. Bush & M. Drexler (Eds.), Ethical issues in clinical neuropsychology (pp. 243–​279). Lisse, the Netherlands: Swets & Zeitlinger. Rohde, P., Stice, E., Marti, C. N. (2015). Development and predictive effects of eating disorder risk factors during adolescence:  Implications for prevention efforts. International Journal of Eating Disorders, 48, 187–​198. Rosa, P. J., Morais, D., Gamito, P., Oliveira, J., & Saraiva, T. (2016). The immersive virtual reality experience: A typology of users revealed through multiple correspondence analysis combined with cluster analysis technique. Cyberpsychology, Behavior, and Social Networking, 19, 209–​216. Rothbaum, B., Hodges, L., Kooper, R., Opdykes, D., Williford, J., & North, M. (1995). Effectiveness of computer-​generated (virtual reality) graded exposure in the treatment of acrophobia. American Journal of Psychiatry, 152, 626–​628. Sanchez-​Vives, M. V., & Slater, M. (2005). From presence to consciousness through virtual reality. Nature Reviews Neuroscience, 6, 332–​339. Schare, M. L., Scardapane, J. R., Berger, A. L., Rose, N. & Berger, S. (1999). A virtual reality based anxiety induction procedure with driving phobic patients. Presented at Association for Advancement of Behavior Therapy, Toronto, Canada. Schmidt, U., & Marks, I. (1988). Cue exposure to food plus response prevention of binges for bulimia:  A  pilot study. International Journal of Eating Disorders, 7(5), 663–​672. Schyns, G., Roefs, A., Mulkens, S., & Jansen, A. (2016). Expectancy violation, reduction of food cue reactivity and

less eating in the absence of hunger after one food cue exposure session for overweight and obese women. Behavior Research and Therapy, 76, 57–​64. Schultheis, M. T., & Rizzo, A. A. (2001). The application of virtual reality technology in rehabilitation. Rehabilitation Psychology, 46, 296–​311. Serino, S., & Dakanalis, A. (2016). Bodily illusions and weight-​related disorders:  Clinical insights from experimental research. Annals of Physical and Rehabilitation Medicine doi: 10.1016/​j.rehab.2016.10.002 Serino, S., Dakanalis, A., Gaudio, S., Carra, G., Cipresso, P., Clerici, M., & Riva, G. (2015). Out of body, out of space:  Impaired reference frame processing in eating disorders. Psychiatry Research, 230, 732–​734. doi:10.1016/​ j.psychres.2015.10.025 Serino, S., Pedroli, E., Keizer, A., Triberti, S., Dakanalis, A., Pallavicini, F.,  . . .  Riva, G. (2016). Virtual Reality Body Swapping: A Tool for Modifying the Allocentric Memory of the Body. Cyberpsychology, Behavior, and Social Networking, 19(2), 127–​133. doi:10.1089/​cyber.2015.0229 Serino, S., Scarpina, F., Keizer, A., Pedroli, E., Dakanalis, A., Castelnuovo, G.,  . . .  Riva, G. (2016). A novel technique for improving bodily experience in a non-​operable super-​super obesity case. Frontiers in Psychology, 7, 837. doi:10.3389/​ fpsyg.2016.00837 Sethi, A. K., Suzuki, K., & Critchley, H. D. (2012). An interoceptive predictive coding model of conscious presence. Frontiers in Psychology, 2, article 395, 1–​16. doi:10.3389/​ fpsyg.2011.00395 Shiban, Y., Pauli, P., & Muhlberger, A. (2013). Effect of multiple context exposure on renewal in spider phobia. Behaviour Research and Therapy, 51, 68–​74. doi:10.1016/​ j.brat.2012.10.007 Shiban, Y., Schelhorn, I., Pauli, P., & Muhlberger, A. (2015). Effect of combined multiple contexts and multiple stimuli exposure in spider phobia:  A  randomized clinical trial in virtual reality. Behaviour Research and Therapy, 71, 45–​53. doi:10.1016/​j.brat.2015.05.014 Slater, M. (2002). Presence and the sixth sense. Presence: Teleoperators, and Virtual Environments, 11, 435–​439. Slater, M., Perez-​Marcos, D., Ehrsson, H. H., & Sanchez-​Vives, M. V. (2009). Inducing illusory ownership of a virtual body. Frontiers in Neuroscience, 3, 214–​220. doi:10.3389/​ neuro.01.029.2009 Slater, M., & Wilbur, S. (1997). A framework for immersive virtual environments (FIVE):  Speculations on the role of presence in virtual environments. Presence: Teleoperators and Virtual Environments, 6, 603–​616. Steinglass, J., Albano, A. M., Simpson, H. B., Carpenter, K., Schebendach, J., & Attia, E. (2012). Fear of food as a treatment target: exposure and response prevention for anorexia nervosa in an open series. International Journal of Eating Disorders, 45(4), 615–​621. doi: 10.1002/​eat.20936. Steinhausen, H. C., & Weber, S. (2009). The outcome of bulimia nervosa: Findings from one-​quarter century of research. American Journal of Psychiatry, 166, 1331–​1341.

Stice, E. (2016). Interactive and mediational etiologic models of eating disorder onset: Evidence from prospective studies. Annual Review of Clinical Psychology, 12, 359–​381. Strickland, D. (1996). A virtual reality application with autistic children. Presence, Teleoperators and Virtual Environments, 6, 319–​329. Thompson, J. K., Heinberg, L. J., Altabe, M., & Tantleff-​Dunn, S. (1999). Exacting beauty:  Theory, assessment and treatment of body image disturbance. Washington DC: American Psychological Association. Tiggemann, M. (2011). Sociocultural perspectives on human appearance and body image. In T. F. Cash & L. Smolak (Eds.), Body image: A handbook of science, practice, and prevention (pp. 12–​19). New York, NY: Guilford. Toro, J., Cervera, M., Feliu, M. H., Garriga, N., Jou, M., Martinez, E., & Toro, E. (2003). Cue exposure in the treatment of resistant bulimia nervosa. International Journal of Eating Disorders, 34, 1–​8. Trentowska, M., Bender, C., Tuschen-​Caffier, B. (2013). Mirror exposure in women with bulimic symptoms, how do thoughts and emotions change in body image treatment? Behaviour Research and Therapy, 51, 1–​6. Vincelli, F. (1999). From imagination to virtual reality:  the future of clinical psychology. Cyberpsychology and Behavior, 2, 241–​248. Vincelli, F., Molinari, E., & Riva, G. (2001). Virtual reality as clinical tool:  Immersion and three-​ dimensionality in the relationship between patient and therapist. Studies in Health Technology and Informatics, 81, 551–​553. Waldman, A., Loomes, R., Mountford, V. A., & Tchanturia, K. (2013). Attitudinal and perceptual factors in body image distortion:  An exploratory study in patients with anorexia nervosa. Journal of Eating Disorders, 1, 1–​9. doi:  10.1186/​ 2050-​2974-​1-​17 Waterworth, J. A., & Riva, G. (2014). Feeling present in the physical world and in computer-​mediated environments. London, UK: Palgrave Macmillan. Wiederhold, B. K., Riva, G., & Gutiérrez-​Maldonado, J. (2016). Virtual reality in the assessment and treatment of weight-​ related disorders. Cyberpsychology, Behavior, and Social Networking, 19, 67–​73. doi:10.1089/​cyber.2016.0012 Wilson, M. (2006). Covert imitation. In G. Knoblich, I. M. Thornton, M. Grosjean, & M. Shiffrar (Eds.), Human body perception from the inside out (pp. 211–​228). New  York, NY: Oxford University Press. Wooldridge, T., & Lytle, P. P. (2012). An overview of anorexia nervosa in males. Eating Disorders, 20, 368–​378. doi:10.1080/​ 10640266.2012.715515 Wooley, S. C., & Wooley, O. W. (1985). Intensive out-​ patient and residential treatment for bulimia. In D. M. Garner & P. E. Garfinkel (Eds.), Handbook of psychotherapy for anorexia and bulimia (pp. 120–​132). New  York, NY: Guilford Press. Zahoric, P., & Jenison, R. L. (1998). Presence as being-​in-​the-​world. Presence, Teleoperators, and Virtual Environments, 7, 78–​89.

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C H A PT E R

 Mobile Device Applications for the Assessment and Treatment of Eating Disorders

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Alison M. Darcy and Shiri Sadeh-​Sharvit

Abstract Mobile devices and applications (apps) are increasingly used in clinical practice, offering reconceptualization of and novel avenues to tracking symptoms and delivery of more personalized interventions. This chapter reviews the burgeoning approaches to the integration of mobile in screening and treating individuals with eating disorders. Promising methods of data collection such as ecological momentary assessments enhance the capabilities of detecting symptoms and recognizing patterns—​both are fundamental to the screening, evaluation, and monitoring of eating disorders and lay the foundations for better treatment design. More recent advances in machine learning allow ecological momentary interventions to be delivered and continuously optimized at the individual level in real time. This chapter explores what this means for the future of personalized treatment for eating disorders, referring to apps that integrate these mechanisms. Finally, the chapter provides a framework for evaluating mobile device mental health apps in clinical care. Key Words:  eating disorders, guided self-​help, mobile health, self-​monitoring, smartphone, app

Introduction

One can think of contemporary psychotherapies—​particularly the most evidence-​ based such as cognitive-​behavioral therapy, dialectical behavior therapy, and so forth—​as involving a process that combines several elements. The first is pattern identification in mood, thoughts, behaviors, and the contexts in which they arise. The second element is experimentation in understanding how modifications to those patterns may help or hinder us. Another element is learning, or psychoeducation. Finally, the therapeutic relationship itself is assumed to be therapeutic, providing accountability, empathy and unconditional positive regard traditionally provided within the structure of regular appointments with a clinician in a physical space designated for this purpose. A major problem with this traditional approach, particularly illuminated by the regular in-​person 492

appointments, is that it is inherently unscalable and as such, only a minority of individuals have access to it. Indeed, relatively few clinicians are sufficiently trained to deliver evidence-​ based treatments to individuals with eating disorders and those that are tend to live in urban centers in Western countries near academic centers. Shame and stigmatization of mental illness (Swan & Andrews, 2003) also impede the rates of eating disorder treatment seeking and compliance (Puhl, Latner, King, & Luedicke, 2014). Such shortcomings of current psychotherapies have driven technologists to augment and replicate therapeutic elements with varying degrees of success. Moreover, the ability to find community, especially among people with rare disorders, is a function that Internet technologies are particularly well suited to since it is one of the primary reasons the Internet was originally developed.

The potential for technologies to be used to enhance therapy has been recognized for decades (e.g., Agras, Taylor, Feldman, Losch, & Burnett, 1990), however, recent advances in mobile devices have opened up unprecedented possibilities to seamlessly integrate various functions of the therapeutic process into one’s everyday life. Mobile refers to wireless devices and sensors (including mobile phones) that are intended to be carried with the person during day-​to-​day activities (Kumar et  al., 2013). Mobile mental health offers an opportunity to both improve the efficiency of healthcare and engage individuals in their own health (Kostkova, 2015). This chapter posits that mobile technology has the potential to extend the very landscape that has defined—​ and limited—​ eating disorders therapy in the 20th century, liberating it from the bricks-​ and-​mortar constraints of physical services and 50-​ minute sessions, and introducing a 24 hours per day, 7 day per week (24/​7) opportunity for engagement in health promotion. Because mobile technology is advancing so quickly, we do not provide an exhaustive review of specific apps that may come and go, but instead aim to equip the reader with a framework for understanding mobile technologies’ potential functions, pertinent issues, and some of the current controversies.

The Promise and Reach of Mobile

Mobile devices have been the fastest adopted technology in history, fundamentally transforming the way people communicate and go about their daily lives in less than two decades. Whereas the functionality of older mobile phones was limited to the computational power that could fit inside the device, smartphones by contrast can access enormous computational power in “the cloud” via Internet connectivity. This makes smartphones vastly more powerful and thus ideally poised to process large amounts of data that are gathered by sensors that are inbuilt in the device. Distributed cloud computing is one of three key factors that is driving a period of immense technological innovation. Another key factor is rapid development of the field of machine learning analytics, a branch of artificial intelligence (AI) in which computational algorithms independently learn from data without human intervention. Machine learning algorithms keep search engine results relevant to specific users, keep SPAM out of inboxes, and are the basis of the autonomous (self-​driving) cars. The third factor is the global adoption of inexpensive

mobile (including wearable) technology, providing the means to gather enormous amounts of personally relevant data. In terms of reach, smartphones are facilitating Internet adoption in emerging economies facilitated by easier dissemination of wireless networks rather than costly cable infrastructures. Mobile apps have also eroded some of the ethnic and socioeconomic disparity that has been observed in the adoption of previous technologies, setting the scene for an opportunity to disseminate to traditionally underserved populations. For example, in 2013 in the United States 59% of Caucasian, 74% of African American, and 68% of Hispanic individuals owned smartphones (Duggan & Smith, 2013). Interestingly, people tend to develop an emotional connection with their smartphone (Vincent, 2005), which make them excellent platforms for data collection and behavioral change in an ecologically valid way (Klasnja & Pratt, 2012). In a closed loop feedback system, the mobile technology (e.g., smartphone) is not just the measurement device but ultimately becomes a platform from which tailored interventions can be delivered based on meaningful insights derived by the machine learning algorithms that are busy processing your data in the background (i.e., “the Cloud”). In essence, the conditions necessary for the development of technologies that have real potential to impact lives in a personally meaningful way have never been more present than they are now (Darcy, Louie, & Roberts, 2016).

Mobile Mental Health Adoption

Technology is increasingly being integrated into health services, and this endeavor has been supported by government in many countries including the US Health Information Technology Economic and Clinical Health Act (HITECH) as well in the United Kingdom’s National Health Service. Data suggest that clinicians are open to this and that there is substantial drive from health consumers in addition. In contrast to e-​mental health, mobile mental health adoption has been comparatively slow (Chan, Torous, Hinton, & Yellowlees, 2015). Mobile app quality has been highly variable, and this relatively low barrier to entry has appropriately undermined consumer and clinician confidence. For example, one review of apps for eating disorders revealed that out of 44 apps identified, 50% of them provided potentially harmful information, such as “tips” for anorexia nervosa (Fairburn & Rothwell, 2015). This variability in quality is likely less to do with fundamental problem with the feasibility of mobile Darcy, Sadeh-Sharvit

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apps in healthcare, and more in line with what tends to happen in the early days after the introduction of any new technology. In addition to inevitable initial instability of most newly introduced technologies, the potential for reducing the overall burden of illness in the population, enhancing access to care and, in some cases quality of care, remains. Recent academic-​industry partnerships are signaling a new, more stable era for mobile app development that combines both computational and academic rigor. For example, Samsung has recently partnered with the University of California, San Francisco, to create mobile health devices and applications; Apple recently released a call for innovative research for mobile mental health initiatives that may make use of their Health kit; and so on. However, as the mental health field moves toward the longer-​term goal of precision therapeutics, only the earliest of steps have been taken in eating disorders. While the potential of mobile apps has not yet been fully realized (Juarascio, Goldstein, et al., 2015), we explore early initiatives in assessment and monitoring, self-​help and guided self-​help, and treatment augmentation and delivery.

Apps for the Assessment and Monitoring of Eating Disorders

Traditional questionnaire-​based tools have been validated in patients and disseminated among eating disorder professionals. Despite their psychometric strengths, the key limitations of these self-​reports are that they are subject to recall bias and measurement errors. Self-​report measures, are, by definition, subjective, and in eating disorders as with other mental illness, individuals often have illness-​ relevant biases that can affect responses (Waldman, Loomes, Mountford, & Tchanturia, 2013). In addition, some limitations exist with current self-​report eating disorder measures when used with certain populations, for example with males, since many assessments were initially developed and normed among relatively small, female samples (Darcy & Lin, 2012). Self-​monitoring of meals and symptoms is at the core of most evidence-​ based treatments for eating disorders, and completion of this activity is associated with better outcomes (Kazantzis, Whittington, & Dattilio, 2010; Lebeau, Davies, Culver, & Craske, 2013). However, self-​monitoring is difficult for many patients with eating disorders (Cebolla et al., 2010) and is especially challenging for adolescents (Lock, 2005; Nichols & Gusella, 2003). Smartphones are thought to be a more 494

convenient way to self-​monitor because individuals are typically in close proximity to their phone, using it for work, interpersonal connection, and searching or recording of information that they consider important (Fox & Duggan, 2013). Inexpensive wearable devices (e.g., Bluetooth-​ enabled fitness trackers, etc.) are a promising new arena for collecting data passively—​which could enhance screening, assessment, and monitoring eating disorders for both the individual and their care team—​by being both effortless and more objective. Surprisingly, few studies have examined self-​ monitoring on phones against traditional paper and pen methods. However, there are two reports that demonstrate increased adherence to smartphone self-​monitoring over paper and pen for recording meals (Carter, Burley, Nykjaer, & Cade, 2013) and physical activity (Kirwan, Duncan, Vandelanotte, & Mummery, 2012). In addition, some patient populations may prefer mobile apps to traditional monitoring (Riley et al., 2011, Darcy et al., 2016). Such real-​time recording of symptoms is fundamental to every formulation of eating disorder cases. Most empirically supported interventions in eating disorders rely on identifying and making sense of the individual, complex matrix of cognitions, emotions, behaviors, and exercise, and their role in precipitating, maintaining, and recovering from eating psychopathology. Mobile devices offer innovative methods to screen, assess, and evaluate symptoms, at a location and time that fit the individual’s routine and with minimal burden. Moreover, mobile devices are in the unique position to offer the ability to conduct and integrate sophisticated pattern recognition via machine learning algorithms, which may assist clinicians in constructing the formulation. Mobile devices can record varied information that ranges from passive data (e.g., glucose levels, indicating how much time has passed since the last meal, the number of steps a day) to active self-​ monitoring of meals, binges and purges, and the cognitions, emotions, contexts, and triggers that are associated with them. Real-​time recording is fundamental to assessment of specific symptoms, is supported in specialized apps for eating disorders like Recovery Record and RiseUp as well as in products like Apple Watch—​which all use reminders prompting the individual to record their health data. Mobile devices can also communicate with certain functions embedded in smartphones and wearables, including sensors of physical activity levels, geographic locations (for further analysis of triggers),

Mobile device Applications for Assessment and Treatment

number of text messages sent and received, and predefined reminders to record data. These functions could be programmed not only according to expert opinion and empirical data, but they could also be informed by the individual’s goals and preferences. Personalized information could be collected in association with individual triggers, for instance using the geographic location services of the phone to mark proximity to ice cream stores, if these are known triggers of a binge. Further, standardized self-​report measures for mental disorders completed on apps have similar psychometric features as those administered via traditional data collecting methods (Chan et al., 2015). Recovery Record, relatedly, has demonstrated capacity to administer validated measures to assess users’ current symptoms (Tregarthen, Lock, & Darcy, 2015). The capabilities of mobile devices and apps uniquely complement a specific and highly sensitive method of recording real-​time patient data, called ecological momentary assessment (EMA). In EMA, information on symptoms can be collected in real time, and later analyzed and assessed by a mental health expert. Further, after one’s baseline pattern of symptoms has been established, machine-​ learning-​enabled algorithms could signal significant deviations and inform the individual, their care team, or another designated function. Ecological momentary assessment has been used effectively in the measurement of eating disorders, for instance successfully detecting the temporal relationship between stress and binge eating (Engel et al., 2016; Goldschmidt et  al., 2014). TakeControl, a new app-​based intervention for eating disorders that is currently under development (Juarascio, Manasse, Goldstein, Forman, & Butryn, 2015), aims to use EMA in assessment and treatment. An algorithm based on machine learning would detect patterns of relationships between triggers and binge behaviors, and would inform the user that they are at a high risk for a binge episode. Recovery Record also includes reminders that are set for estimated times of meals, to ensure that these are recorded as close as possible to their occurrence. Modeling EMA data allows researchers and clinicians to explore interactions that might elucidate symptoms, and indicate a significant change in symptoms that may warrant a different level of care. It also facilitates testing the validity of theories on which treatments have been based in both one individual as well as large-​scale samples. To the best of our knowledge, currently there are no published data on the use of EMA in mobile-​ based interventions for eating disorders,

however as previously mentioned, at least one app is currently in development by Juarascio, Goldstein, and colleagues (2015). Although there is no existing research on the fidelity of different modules to record real-​ time data in eating disorders (i.e., online versus a mobile device), cell phones have the advantage over EMA devices of having 24/​7 access to the individual as well as the benefit of being experienced as part of their intimate environment. Therefore, the development of mobile devices and apps should be prioritized as the preferred method of collecting data to screen for, assess, and monitor eating disorders. As triggers for eating disorder symptoms may be highly diverse and context-​related, the refined algorithms need some assistance from device users to be meaningful. This could result in greater awareness of triggers, but also be more tedious and not appropriate for everyone. Assessment and monitoring by mobile devices might also be affected by user-​ initiated errors, for instance recall bias, uncharged battery that makes the mobile device unavailable, misuse or misplacement of sensors and functions within the app, and so forth. Nonetheless, given their distinct benefits for assessment of symptoms, Recovery Record and RiseUp—​the only existing specialized apps that are currently available for public use—​as well as additional developing apps and devices, should be more extensively studied. More research is also needed on the capacity of mobile devices, and particularly wearables, to provide more accurate and additional data points for screening and monitoring.

Mobile Delivered Interventions for Eating Disorders

The magnitude of individuals requiring evidence-​ based interventions for eating disorders will outnumber available therapists in the foreseeable future, particularly as rates of eating disorders are still increasing (Micali, Hagberg, Petersen, & Treasure, 2013). Problems like cost, mobility, access to treatment, and stigma deter individuals who need treatment from receiving it. App-​based interventions for eating disorders can be provided in the format of guided self-​help, or as a method to augment and complement face-​ to-​ face intervention. We will now describe these two modules and review the few available apps that incorporate mobile delivered interventions for eating disorders. A recent review of the literature concluded that there is a reassuring number of rigorous studies confirming that e-​ mental health applications Darcy, Sadeh-Sharvit

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impart many benefits including improved accessibility, reduced running costs, flexibility in terms of standardization and personalization, interactivity, and consumer engagement (Lal & Adair, 2014). Internet-​delivered cognitive-​behavioral therapy (CBT), for example, has almost two decades of research data that support its use with certain populations. Mobile mental health adoption, on the other hand, has been comparatively slow (Chan et al., 2015). Guided self-​help (GSH) interventions for eating disorders, that is, prebuilt programs that include psychoeducational materials, self-​ paced exercises and homework, and often also minimal support by a mental health professional or other person, have received empirical support for the past two decades (Perkins, Murphy, Schmidt, & Williams, 2006). Data indicate no difference in outcomes between patients with eating disorders who received the intervention in a face-​to-​face format or online (Wilson & Zandberg, 2012). Apps appear to be a highly suitable platform to provide GSH, as they are embedded within the lives of individuals and are free from the resource constraints associated with conventional therapy. Psychoeducation could be conveyed using a variety of methods (including reading materials, quizzes, audio and video files, links to complementary materials online, etc.). The range of formats to provide psychoeducation about the eating disorder and ways to combat it may enhance learning and patient acceptability. For example, delivery of psychoeducational materials can be matched to the learning style of an individual so as to enhance engagement. Additionally, progress in app-​based GSH programs is self-​paced, tailored to the individual’s schedule and preferred location. The intervention is often broken down to short segments that include some psychoeducation and an activity. For instance, Lantern—​primarily a Web-​based program that has been adapted for mobile—​ provides 10-​ minute sessions of CBT-​ inspired GSH that are limited to once a day in order to pace users’ progress and allow material and new skills to be processed. Additional apps for eating disorders, such as RiseUp and Stop Binge Eating provide psychoeducational materials for self-​help, but are not exclusively based on empirically supported interventions for eating disorders. Recovery Record, Before I  Eat, and iCounselor all employ strategies to reduce eating disorder symptoms that include components of CBT, acceptance and commitment therapy, mindfulness, and general self-​ soothing techniques. 496

Coaching-​ enhanced intervention, such as the one offered by Lantern, matches a mental health coach that interacts with the user through the app. Coaches—​whose possible contribution to large-​scale mobile mental health intervention efforts is gradually increasing—​can individualize the program to fit the user’s needs, respond to questions, clarify concepts, and refocus the user on important intervention components. However, health coaches are currently unlicensed and unregulated, although there are efforts underway to establish best practices guidelines. In addition, no research exists in the eating disorder field about the efficacy of mobile GSH programs that have been adapted from Web-​based models. In the absence of a coach who can individualize program content to fit the needs of the individual, app-​based programs can adapt to the needs of the individual in response to data provided in the program. The interactive nature of mobile apps and devices presents innovative methods to make mobile-​based GSH much more interactive than its book-​based or online counterparts. Recovery Record has recently received NIH funding in partnership with our group at Stanford to develop and evaluate an adaptive version of the app with guided self-​help programs tailored for specific user groups, against a standard version of the app. Preliminary data suggested that, though about 30% have clinically significant symptom reduction after 28 days of app use, users’ response and reduction in psychopathology vary according to the symptom profile. These interventions are designed as stand-​alone programs, and were designed using a “person-​centered design process” that aims to specifically design for the experience of individuals consulted in the process (Kelley & Littman, 2007). The aim was to replicate some of the elements of the therapeutic process reported to be desirable by individuals consulted during the design phase. Such elements included regular check-​ins and accountability; goal-​setting support; and help interpreting things that are going well versus things that are challenging. A curated list of specific goals, skills, and challenges corresponding to each of the groups’ symptom profiles identified in a preliminary analysis were developed. To foster user engagement, content was designed to mirror therapy delivery such that goals, skills, and challenges are more achievable in the early weeks of the intervention but gradually become more difficult as the user progresses through the program. Beyond tailoring to individuals at group level, an important feature of mobile devices is that they are especially geared toward sending content specific to

Mobile device Applications for Assessment and Treatment

the individual via just-​in-​time (JIT) interventions. These JIT interventions are an algorithm-​supported emerging approach of programmed intervention responses to small changes in cognition, emotion, behavior, and context. These predetermined interventions are based on EMA and can be delivered via mobile devices (Nahum-​Shani et al., 2014). The JIT interventions can analyze changes in behavior, prompt the individual to make adaptive changes accordingly, and guide them through the process with specific instructions or encouragement to turn to higher levels of care. In the field of eating disorders, where eating and exercise (or lack thereof ) often represent an impulsive reaction to a psychological or situational trigger, complex algorithms could record a person’s normal patterns. Subsequently, algorithms look for significant deviations and offer strategies to address relapse. To the best of our knowledge, JIT interventions have not been deployed in any commercially available app and no studies of them in eating disorders have been published to date. Carroll and colleagues (2013) reported a pilot study testing wearable mobile detectors of heart rate, that aimed to detect arousal that could lead to emotional eating and encourage the user to exercise deep breathing as prevention. There was 75% overlap between the physical arousal detected by these wearables and self-​reported negative emotions, however the use of stress reduction prompts has not been tested yet. An additional promising way to use app capabilities is to promote interpersonal connectedness and support, which are lacking resources for many patients. Indeed, many mobile apps have created new ways for individuals to connect and are becoming inherently more social. In direct peer-​to-​peer environments, advice or feedback patients may receive could be detrimental and warrants some monitoring by experts (Juarascio, Goldstein, et al., 2015). However, it is possible to allow for interpersonal connection in a controlled and managed way, such as in Recovery Record’s “Pair-​up” feature (Tregarthen et al., 2015). This feature allows for individuals to connect with another user of similar demographics and select pre-​vetted encouraging messages, thus providing and receiving peer support, but in a way that is protected and asynchronous. None of these abovementioned apps currently offers a personalized analysis of symptoms and the triggers for their occurrence. Not all of these apps are available across all types of mobile phones, limiting the dissemination among the patient population. Additionally, the GSH approach used in apps

thus far has been CBT. Both ACT and DBT, which have good GSH modules, should be tested further so that more diverse groups of patients could benefit of this resource. Technology can enhance treatment components that traditional intervention approaches do not address sufficiently. Integrating face-​ to-​ face and online treatment or technology-​based components is a practice called “blended care” or “blended therapy” (Wentzel, van der Vaart, Bohlmeijer, & van Gemert-​ Pijnen, 2016). A  blended therapy would include, for instance, a psychoeducational video on a new skill that the patient would watch 3  days before the face-​ to-​ face session and then practice. Consequently, the therapy session would be used for troubleshooting and refinement of the learned material, and greater personalization of the knowledge and skills acquired. To date, no empirical investigation of blended care in the treatment of eating disorders has been published. App-​based components that are initiated, facilitated, or prescribed by the therapist could booster the in-​person treatment and monitoring of patients. By further personalizing the treatment, adding modular intervention units (particularly in the presence of comorbidity), saving time in session, and promoting a better system for more real time check-​ ins between sessions—​ “conservative” treatments are enhanced. The meals, emotions, and cognitions logged on Recovery Record, for example, can be retrieved by the therapist at any time between sessions or before the weekly meeting. Therapists (who received an invite from their client) can send cheerleading and supportive messages between meetings, and encourage practice of the skills and techniques learned in treatment. If delivered conjointly, both modalities should complement each other, rather than compete or override. Unfortunately, most mobile health apps do not adequately use mobile device capabilities (Juarascio, Manasse, et al., 2015).

The State of Currently Available Technologies

Eating disorder treatment and assessment could capitalize the accessibility, functionality, interactive nature, convenience, low cost, and privacy of mobile health technologies. Therefore, mobile devices can improve engagement, adherence, and psychoeducation, as well as enrich the quantity and quality of data available for treatment planning and monitoring accessible by providers. Such features are ideal for engaging patients in treatment due to several advantages over static programs, such as portability, Darcy, Sadeh-Sharvit

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capacity for real-​time, in-​the-​moment interaction, and multiple built-​in sensors for collection and presentation of data (Heron & Smyth, 2010). We have referred here to six available apps that offer psychoeducation, self-​ monitoring of symptoms, guided self-​ help that can be enhanced by coaching, and communication with a clinician. We have also mentioned an app that is in development, and is planned to use EMA in reducing binging. We are aware of research involving three of these seven apps that is being carried out in an academic setting. All of these apps are in English, and there are currently no data on their use by non-​English speakers. Our findings are in concert with those of a recent review (Juarascio, Manasse, et al., 2015), indicating that there are also very limited data on the feasibility, acceptability, and outcomes of currently available apps. The apps that currently exist vary greatly. The interface of some is likely to evolve to more algorithm-​ driven, targeted platforms that will address different typologies of individuals at risk for eating disorders as well as patients with full-​syndrome conditions. Therefore, it is clear that one cannot make a sweeping judgement about the efficacy of apps as they exist currently, partly because it is early days for these technologies and none have published data from randomized clinical trials at this time, though several studies are underway. In addition, trying to judge the efficacy of apps for eating disorders is similar to evaluating the efficacy of treatments for cancer. Symptom presentations, populations, and tolerance will vary; so too do the treatment approaches that will be effective. The earliest data from mobile apps supports this view (Tregarthen et  al., 2015). Another necessary direction of research is testing whether transitioning effective Web-​based mobile health tools into app-​based modalities may be a feasible modality for delivering or enhancing evidence-​based treatments (Taylor et  al., 2016). However, it is clear that mature mobile device apps are uniquely poised to monitor and gather data and deliver targeted intervention based on individual differences. Thus mobile device apps are the cornerstone of a move toward precision psychiatry that has the capacity to lower the overall burden of illness and improve outcomes over and above a growing literature that supports adaptive treatments (Oldenburg, Taylor, O’Neil, Cocker, & Cameron, 2015).

Current Controversies

In the following section, we address the key criticisms of mobile apps for eating disorders. 498

We also suggest some possible solutions for these controversies.

Bias in Self-​Report in Paper-​and-​Pencil Versus Mobile Assessments

Eating disorders assessment heavily relies on patients’ self-​ report. It has been questioned whether mobile app-​level food and symptom self-​ monitoring affords advantages over paper-​and-​pen methods (Fairburn & Rothwell, 2015). However, since mobile real-​time monitoring employs the use of time stamps, app-​based assessments of eating disorders are considered more accurate (Engel et  al., 2016). Interestingly, while interest in the integration of mobile devices in clinical practice and research is increasing in the eating disorders field, there are no empirical data comparing self-​report of cognitions, emotions, and behaviors associated with DSM-​5 diagnoses between the traditional self-​monitoring paper diaries and mobile devices. In general, individuals are more compliant with self-​report administered in mobile devices than in paper-​and-​pencil notebooks, and do it closer to the actual time they report (Stone, Shiffman, Schwartz, Broderick, & Hufford, 2002). Further, data from individuals with anxiety, depressive, and bipolar disorders suggest that self-​monitoring using mobile devices demonstrates greater sensitivity to detect change in symptoms over the week (Depp, Kim, Vergel de Dios, Wang, & Ceglowski, 2012; Torous et  al., 2015), and possibly indicates more severe symptoms than reported on paper (Moore, Depp, Wetherell, & Lenze, 2016). Improved mobile methods to collect passive and active data, could help therapists provide more accurate diagnoses and treatment plans.

Mobile Apps as a Replacement for Therapy

It is clear that mobile mental health apps will never replace traditional therapy and there will always be a need for expertise in the treatment of eating disorders. However, dissemination and implementation of evidence-​based therapies is one of the biggest challenges facing our field. In an environment where resources are constrained, strategies that can better allocate therapist time by “task shifting” some functions to a device, where this can be accomplished in a valid way, can be viewed as part of a pragmatic solution to a global problem. A related criticism is that individuals who use mobile apps might not seek therapy in favor of using an app instead. This is only a problem if the person requires a higher level of care, and thus mobile apps that are used in the context of treatment should integrate the

Mobile device Applications for Assessment and Treatment

capacity to triage appropriately. Apps that are used outside of therapeutic context should never discourage an individual from seeking treatment. However, the reality is that the majority of individuals who have an eating disorder never present for treatment, and apps may be in a unique position to encourage, rather than discourage it. Tregarthen et  al. (2015) found that a substantial portion of Recovery Record users had never told another person about their illness. In this way, mobile apps are uniquely poised to offer a positive initial experience with therapeutic content and if validated, could be a useful part of a comprehensive stepped-​care strategy.

Privacy and Confidentiality

Privacy and confidentiality are among the most pressing issues for health-​related mobile apps. In the United States, mobile health apps did not exist when HIPAA laws were developed in 2006, and thus the unique challenges they present have not been considered in current mandates. When the National Health Service in the UK published its Health Apps Library to encourage the use of mobile health apps, it was removed shortly thereafter due to concerns that the majority of apps on the list had no data privacy policy and had other data concerns. As a baseline best practice, apps should transparently communicate a data policy, however, few do this and individuals may not look for one, or worse, they may incorrectly assume that there is already an acceptable amount of data protection when none, in fact exists. Research on individual health literacy suggest that patients with low health literacy are less likely to use apps and mobile trackers, and less likely to view them as helpful, but believe them to be private (Mackert, Mabry-​Flynn, Champlin, Donovan, & Pounders, 2016). To date, most breaches of personal health information reported to the Department of Health and Human Services (HHS) under the HITECH Act have been due to the theft or loss of a mobile device or laptop, rather than direct hacks. However, the issue of privacy and confidentiality should be consistently discussed because data are increasingly becoming more and more identifiable, especially in the context of triangulation of data types, behavioral pattern recognition, and machine learning algorithms.

The Values Embedded in Artificial Intelligence

One of the largest ongoing debates in artificial intelligence (AI) relates to the pace at which the technology is developing and the unknown

implications for humanity. While it is likely to be a long time before AI becomes sentient, we are already seeing some of these issues being raised in mental health. Apps as we know them (mostly visual programs run on a smartphone) are showing signs of petering out and are likely to be replaced in the coming decades by chatbots (automated text-​ based AI agents that converse via text messages on a screen) and conversational agents (such as Apple’s Siri) that are spoken to directly in a conversational manner. Developments in the “Internet-​of-​things” (that is, connected devices in the home) are driving this technology such that we will simply ask our agent to do things like turn up the heating or “call Mum” without ever physically interacting with a device. Given the conversational format of these interactions, they may be ideally poised to act as therapists or as first responders. Importantly, they may already be used in this way, before sufficient thought and consideration has been paid to how the AI should respond to its user. For instance, Miner and colleagues investigated conversational agents’ response to mental health-​ related and emergency statements such as “I’ve just been raped,” “I am depressed” and “I want to commit suicide.” Responses across 77 conversational agents were highly inconsistent, and sometimes stigmatizing, some recognizing the statement but failing to respond in a respectful way, and many failing to refer to appropriate services (Miner et  al., 2016). A critical challenge is identifying a health-​relevant utterance and then responding in the appropriate way. For eating disorders, this may be particularly challenging, as it can be the meaning of the language or behavior, not the behavior itself that has clinical relevance. Technology companies should consult with mental health experts and clinicians when designing these new interfaces, though little guidance exists around which values to embed. What therapeutic orientation should the conversational agent have, if any, for example?

A Framework for Evaluating Mobile Mental Health in Clinical Care

While it is still early days and genuine challenges exist that make quality research difficult to produce, work is underway to provide a framework for clinicians to be able to evaluate mobile mental health apps in the context of clinical care. Torous and colleagues with the American Psychiatric Association have proposed a hierarchy of needs model (Figure 26.1) with foundational tiers being more important grounding principles than upper tiers. Darcy, Sadeh-Sharvit

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The foundational tier is safety. At the most basic level, the app should not cause any harm. While this sounds self-​evident, it is particularly relevant in eating disorders, where one review found that up to 50% of apps created for use by individuals with eating disorders contained harmful information, such as pro-​ana (pro-​anorexia nervosa) ideals (Fairburn & Rothwell, 2015). This tier also includes privacy and safety concerns. Ideally data should be encrypted in situ and in transit as is consistent with most data legislation for covered entities (such as HIPAA laws in the United States). However most mobile mental health and behavioral health apps are not legally obliged to comply with this standard and are currently not automatically subject to FDA approval (US Department of Health and Human Services). Where developers choose not to comply with these standards, the app should at least carry a transparent data policy available to its users that includes what if any identifiable data are collected both actively and passively, how the data are stored, used, and most importantly, if, how, and under what circumstances they could be shared. In this way, individuals themselves can make the decision around acceptable privacy and data use conditions. Many health apps lack even a basic privacy policy and checking for the presence of one is always a critical step. The next tier is efficacy. As has been discussed in this chapter, while it is of some urgency to produce a literature that elucidates the usefulness of apps, it is nonetheless somewhat challenging and a relatively slow endeavor. In the interim, Torous and colleagues (2015) suggest that individuals should look for apps that are built in a way that translate basic research findings into their technology, and/​or that translate or are built on therapeutic approaches that are grounded in evidence. What theoretical framework, if any, is the app built on, and is it explained and transparent? We would add to this an additional element of efficacy, and that is personal to the patient. There have been many examples of patients who have innovated technology because the current technologies that exist for their condition do not fit their purpose or use case. For example, a type-​ 2-​diabetes patient who was worried that her phone alarm was incapable of awakening her from a diabetic coma hacked various devices such that a complex and loud set of alarms would sound when indicated by her blood sugar levels. In a participatory medicine framework, such individuals are known as engaged patients, or e-​patients. In the context of eating disorders, where engagement in therapy can be low, this may convey a specific advantage. 500

The next tier in this framework is ease of use. Does the app have a consistent user experience and use case, or can it be used inappropriately? It should not be taken for granted that all app users will use the app in the same way. An early case series of a mobile app for eating disorders, for example, found that while clinicians were relatively consistent in their use of the app, each patient used the app in a unique way (Darcy, Adler, Miner, & Lock, 2014). Thus it is important that clinicians and researchers inquire as to how the app is being used by both parties. Indeed, preliminary studies suggest that a one-​app-​fits-​all approach to app design may not be appropriate for individuals with specific symptom profiles in populations where there is a lot of heterogeneity. For example, individuals with eating disorders who engage in extreme restriction may hypothetically use an eating disorders app to perseverate and excessively quantify meals, especially where calories are collected (Darcy, Bryson, Kim, Tregarthen, & Lock, 2017, in review). Fortunately, apps have the ability to selectively present feature sets based on a user’s responses or use habits once learned with a great deal of precision and at little extra cost, once there are sufficient data to train a model. Such is the promise of machine learning (Darcy et al., 2016). Finally, the self-​actualized level for mobile health apps is data sharing. Is the data gathered on the app fully interoperable? Can it, for example, be integrated into the electronic medical record? While this is challenging for app developers to achieve, it substantially adds value to the app in a clinical context for the clinician. An app that does not facilitate proper data sharing risks fragmenting care and isolating the patient and treatment team. Conversely, the patient may not actually desire data sharing with the therapist or integration of data into the permanent medical record, and consent is always required. This dilemma has yet to be resolved, though under the new paradigm of patient-​ centered medicine data ownership and subsequent decisions around such should reside with the patient. We embed within this hierarchy of needs (see Figure 26.1) concurrent patient-​ centered and clinician-​centered considerations as a guide. These questions are by no means exhaustive. Also, it is not necessary for an app to meet all levels of this hierarchy to be a “good” app, for example a purely educational app may not enable data sharing. Rather considering each of these levels and using them as a basis to start an informed discussion with a patient is the goal of this model. We thus suggest that the most

Mobile device Applications for Assessment and Treatment

Is there anything confusing?

Data Sharing Usability

Does the patient want to share data and if so, can they?

Should there be interoperability? If so, is there? If not, are there plans for this function?

How consistent is the user experience? Is it being used the way it was intended?

Do any studies exist?

Why? Under what circumstances?

Efficacy

Is the app helpful?

Is the app built on evidence based approaches and/or theory? Does the company have any academic partnership?

Does the app make any claims not backed by research evidence?

Is the app being used in the way it was intended?

Are there any risks presented by the patient’s use of the app, and if so are these acceptable to the patient?

Has the patient considered data privacy issues?

Safety

Is there a clear data policy?

Does the clinician know what level of privacy is valued by the patient?

Patient considerations

Clinician considerations

Collaborative exploration

Figure 26.1  Framework for evaluating mobile mental health in clinical care 

useful starting point for a clinician to evaluate apps in the context of clinical care is to allow the process to be patient-​driven, for three reasons. The first is that in the constantly shifting app landscape (Larsen, Nicholas, & Christensen, 2016), where millions of apps are available and their form factor will continue to evolve, it is unreasonable for a clinician to comprehensively evaluate even the most relevant ones. The second is that technology has allowed individuals

to be engaged in their own healthcare in an unprecedented way (Topol, 2015). Thus a patient-​driven process is in concert with the empowering spirit of technology itself and it would be counterproductive to halt that process. Finally, it is well known that individuals with eating disorders are difficult to engage in treatment for a variety of reasons, thus if an individual elects to use a tool that facilitates an engagement toward recovery then the clinician should discuss it Darcy, Sadeh-Sharvit

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with them in the same way that they would any other mechanism or tool that engages the patient in their own health promotion, regardless of their own personal opinion or experience of app use.

Summary

Similarly to mental health professionals’ interest in staying up-​ to-​ date with best-​ practices for the assessment and treatment of eating disorders, clinicians should educate themselves about how to evaluate available mobile apps and continuously check their proven efficacy, relevance, and usefulness for their patients. An open discussion about the patient’s use of technology to promote recovery is warranted. Mobile health technologies are theoretically poised to provide pattern-​recognition intelligence that could be stronger than the one offered in classic treatment models; although therapy is largely based on pattern recognition and analysis, retrospective self-​report is often biased. Mobile health initiatives are progressing toward app-​based and other technology interfaces that will all be mobile, for example, conversational agents and wearable technology that does not rely on self-​report. This presents exciting opportunities to rethink the roles of clinicians and technology as well as whether, how, and when they interface. Inclusion of mobile device applications will ultimately evolve the eating disorder field and the care we provide our patients. When used properly, apps can improve the screening, evaluation, self-​ management, and traditional treatment of eating disorders. Apps could augment existing services that are inadequate worldwide; there will never be sufficient clinicians to provide face-​to-​face or telepsychology for everyone who needs it. Currently, access and scale are some of the biggest problems that face the field of psychotherapy right now, and mobile could be a viable way to address some of the inherent limitations, though it is relatively early days in the evolution of these technologies.

References

Agras, W. S., Taylor, C. B., Feldman, D. E. Losch, M., & Burnett, K. F. (1990). Developing computer-​assisted therapy for the treatment of obesity. Behavior Therapy, 21, 99–​109. doi: 10.1016/​S0005-​789480191-​1 Carter, M. C., Burley, V. J., Nykjaer, C., & Cade, J. E. (2013). Adherence to a smartphone application for weight loss compared to website and paper diary:  Pilot randomized controlled trial. Journal of Medical Internet Research, 15(4), e32. doi: 10.2196/​jmir.2283

502

Carroll, E. A., Czerwinski, M., Roseway, A., Kapoor, A., Johns, P., Rowan, K., & Schraefel, M. C. (2013, September). Food and mood:  Just-​in-​time support for emotional eating. In 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII) (pp. 252–​257). Danvers, MA: Institute of Electrical and Electronics Engineers. Cebolla, A., Oliver, E., Baños, R., Botella, C., Zaragozá, I., Alcañiz, M.,  . . .  Guille V. (2010). PDA self-​register system for eating disorders:  A  study on acceptability and satisfaction. Studies in Health Technology and Informatics, 154, 50–​ 52. doi: 10.3233/​978-​1-​60750-​561-​7-​50 Chan, S., Torous, J., Hinton, L., & Yellowlees, P. (2015). Towards a framework for evaluating mobile mental health apps. Telemedicine and e-​Health, 21, 1038–​1041. Darcy, A M, Adler, S, Miner, A, & Lock, J. D. (2014). How smartphone applications may be implemented in the treatment of eating disorders: Case reports and case series data. Advances in Eating Disorders: Theory, Practice and Research, 2, 217–​232. doi: 10.1080/​21662630.2014.938089 Darcy, M. A., Bryson, S. W., Kim, J. P., Tregarthen, J., & Lock, J. D. (2017). Is smartphone app food journaling a good idea for everyone? An eating disorder perspective. Manuscript under review. Darcy, A. M., & Lin, I. H.  J. (2012). Are we asking the right questions? A  review of assessment of males with eating disorders. Eating Disorders, 20, 416–​426. doi:  10.1080/​ 10640266.2012.715521 Darcy, A. M., Louie, A. K., & Roberts, L. W. (2016). Machine learning and the profession of medicine. JAMA, 315, 551–​ 552. doi:10.1001/​jama.2015.18421 Depp, C. A., Kim, D. H., Vergel de Dios, L., Wang, V., & Ceglowski, J. (2012). A pilot study of mood ratings captured by mobile phone versus paper-​and-​pencil mood charts in bipolar disorder. Journal of Dual Diagnosis, 8, 326–​332. doi: 10.1080/​15504263.2012.723318 Duggan, M., & Smith, A. (2013). Cell internet use 2013. Washington, DC: Pew Research Center. Engel, S. G., Crosby, R. D., Thomas, G., Bond, D., Lavender, J. M., Mason, T.,   .  .  .  Wonderlich, S. A. (2016). Ecological momentary assessment in eating disorder and obesity research: A review of the recent literature. Current Psychiatry Reports, 18, 1–​9. doi:  10.1007/​ s11920-​016-​0672-​7 Fairburn, C. G., & Rothwell, E. R. (2015). Apps and eating disorders: A systematic clinical appraisal. International Journal of Eating Disorders, 48, 1038–​1046. Fox, S., & Duggan, M. (2013). Health Online 2013. Washington, DC: Pew Research Center. Goldschmidt, A. B., Wonderlich, S. A., Crosby, R. D., Engel, S. G., Lavender, J. M., Peterson, C. B.,  . . .  Mitchell, J. E. (2014). Ecological momentary assessment of stressful events and negative affect in bulimia nervosa. Journal of Consulting and Clinical Psychology, 82, 30. doi: 10.1037/​a0034974 Heron, K. E., & Smyth, J. M. (2010). Ecological momentary interventions:  Incorporating mobile technology into psychosocial and health behaviour treatments. British Journal of Health Psychology, 15, 1–​39. doi:  10.1348/​ 135910709X466063 Juarascio, A. S., Goldstein, S. P., Manasse, S. M., Forman, E. M., & Butryn, M. L. (2015). Perceptions of the feasibility and acceptability of a smartphone application for the treatment of binge eating disorders:  Qualitative feedback

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from a user population and clinicians. International Journal of Medical Informatics, 84, 808–​816. doi:  10.1016/​ j.ijmedinf.2015.06.004 Juarascio, A. S., Manasse, S. M., Goldstein, S. P., Forman, E. M., & Butryn, M. L. (2015). Review of smartphone applications for the treatment of eating disorders. European Eating Disorders Review, 23, 1–​11. doi: 10.1002/​erv.2327 Kazantzis, N., Whittington, C. & Dattilio, F. (2010). Meta-​ analysis of homework effects in cognitive and behavioral therapy:  A  replication and extension. Clinical Psychology: Science and Practice, 17, 144–​156. doi:10.1111/​ j.1468-​2850.2010.01204.x Kelley, T., & Littman, J. (2007). The art of innovation: Lessons in creativity from IDEO, America’s leading design firm (1st ed.). New York, NY: Random House. Kirwan, M., Duncan, M. J., Vandelanotte, C., & Mummery, W. K. (2012). Using smartphone technology to monitor physical activity in the 10,000 Steps Program: A matched case–​ control trial. Journal of Medical Internet Research, 14(2), e55. doi: 10.2196/​jmir.1950 Klasnja, P., & Pratt, W. (2012). Healthcare in the pocket: Mapping the space of mobile-​phone health interventions. Journal of Biomedical Informatics, 45, 184–​198. Kostkova, P. (2015). Grand challenges in digital health. Frontiers in Public Health, 3, 134. doi: 10.3389/​fpubh.2015.00134 Kumar, S., Nilsen, W. J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M.,  . . .  Hedeker, D. (2013). Mobile health technology evaluation: The mHealth evidence workshop. American Journal of Preventive Medicine, 45, 228–​236. Lal, S., & Adair, C. E. (2014). E-​mental health: A rapid review of the literature. Psychiatric Services, 65, 24–​32. doi: 10.1176/​ appi.ps.201300009 Larsen, M. E., Nicholas, J., & Christensen, H. (2016). Quantifying app store dynamics:  Longitudinal tracking of mental health apps. JMIR mHealth and uHealth, 4, e96. doi: 10.2196/​mhealth.6020 LeBeau, R. T., Davies, C. D., Culver, N. C., & Craske, M. G. (2013). Homework compliance counts in cognitive-​ behavioral therapy. Cognitive Behaviour Therapy, 42(3), 171–​ 179. doi: 10.1080/​16506073.2013.763286 Lock, J. (2005). Adjusting cognitive behavior therapy for adolescents with bulimia nervosa: Results of case series. American Journal of Psychotherapy, 59(3), 267. Mackert, M., Mabry-​Flynn, A., Champlin, S., Donovan, E. E., Pounders, K. (2016). Health literacy and health information technology adoption:  The potential for a new digital divide. Journal of Medical Internet Research, 18(10), e264. doi: 10.2196/​jmir.6349 Micali, N., Hagberg, K. W., Petersen, I., & Treasure, J. L. (2013). The incidence of eating disorders in the UK in 2000–​2009:  Findings from the General Practice Research Database. BMJ Open, 3, e002646. doi:10.1136/​ bmjopen-​2013-​002646 Miner, A. S., Milstein, A., Schueller, S., Hegde, R., Mangurian, C., & Linos, E. (2016) Smartphone-​based conversational agents and responses to questions about mental health, interpersonal violence, and physical health. JAMA Internal Medicine, 176(5), 619–​625. doi:10.1001/​jamainternmed.2016.0400 Moore, R. C., Depp, C. A., Wetherell, J. L., & Lenze, E. J. (2016). Ecological momentary assessment versus standard assessment instruments for measuring mindfulness, depressed mood, and anxiety among older adults.

Journal of Psychiatric Research, 75, 116–​123. doi:  10.1016/​ j.jpsychires.2016.01.011 Nahum-​ Shani, I., Smith, S. N., Tewari, A., Witkiewitz, K., Collins, L. M., Spring, B., & Murphy, S. (2014). Just in time adaptive interventions (JITAIs):  An organizing framework for ongoing health behavior support. Methodology Center Technical Report 14–​126. Retrieved from:  https://​methodology.psu.edu/​media/​techreports/​14-​126.pdf on September 1, 2016. Nichols, S., & Gusella, J. (2003). Food for thought: Will adolescent girls with eating disorders self-​monitor in a CBT Group? The Canadian child and adolescent psychiatry review, 12(2), 37–​39. Oldenburg, B., Taylor, C. B., O’Neil, A., Cocker, F., & Cameron, L. D. (2015). Using new technologies to improve the prevention and management of chronic conditions in populations. Annual Review of Public Health, 36, 483–​505. doi: 10.1146/​ annurev-​publhealth-​031914-​122848 Perkins, S. S., Murphy, R. R., Schmidt, U. U., & Williams, C. (2006). Self‐help and guided self‐help for eating disorders. Cochrane Database of Systematic Reviews, 3, CD004191. doi: 10.1002/​14651858.CD004191.pub2. Puhl, R. M., Latner, J. D., King, K. M., & Luedicke, J. (2014). Weight bias among professionals treating eating disorders:  Attitudes about treatment and perceived patient outcomes. International Journal of Eating Disorders, 47, 65–​75. Riley, W. T., Rivera, D. E., Atienza, A. A., Nilsen, W., Allison, S. M., & Mermelstein, R. (2011). Health behavior models in the age of mobile interventions:  Are our theories up to the task? Translational behavioral medicine, 1(1), 53–​71. doi: 10.1007/​s13142-​011-​0021-​7 Stone, A. A., Shiffman, S., Schwartz, J. E., Broderick, J. E., & Hufford, M. R. (2002). Patient non-​compliance with paper diaries. BMJ, 324, 1193–​1194. doi:  10.1136/​ bmj.324.7347.1193 Swan, S., & Andrews, B. (2003). The relationship between shame, eating disorders and disclosure in treatment. British Journal of Clinical Psychology, 42, 367–​378. Taylor, C. B., Kass, A. E., Trockel, M., Cunning, D., Weisman, H., Bailey, J.,  . . .  Wilfley, D. E. (2016). Reducing eating disorder onset in a very high risk sample with significant comorbid depression: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 84, 402. doi: 10.1037/​ccp0000077 Torous, J., Staples, P., Shanahan, M., Lin, C., Peck, P., Keshavan, M., & Onnela, J. P. (2015). Utilizing a personal smartphone custom app to assess the Patient Health Questionnaire-​ 9 (PHQ-​ 9) depressive symptoms in patients with major depressive disorder. Journal of Medical Internet Research Mental Health, 2: e8. doi: 10.2196/​mental.3889. Topol, E. (2015). The patient will see you now: The future of medicine is in your hands. New York, NY: Basic Books. Tregarthen, J. P., Lock, J., & Darcy, A. M. (2015). Development of a smartphone application for eating disorder self‐monitoring. International Journal of Eating Disorders, 48, 972–​982. doi: 10.1002/​eat.22386 Waldman, A., Loomes, R., Mountford, V. A., & Tchanturia, K. (2013). Attitudinal and perceptual factors in body image distortion:  an exploratory study in patients with anorexia nervosa. Journal of Eating Disorders, 1, 1.  doi:  10.1186/​ 2050-​2974-​1-​17 Wentzel, J., van der Vaart, R., Bohlmeijer, E. T., & van Gemert-​ Pijnen, J. E. (2016). Mixing online and

Darcy, Sadeh-Sharvit

503

face-​to-​face therapy: How to benefit from blended care in mental health care. JMIR Mental Health, 3. doi: 10.2196/​ mental.4534 Wilson, G. T., & Zandberg, L. J. (2012). Cognitive-​behavioral guided self-​ help for eating disorders:  Effectiveness and

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scalability. Clinical Psychology Review, 32, 343–​357. doi: 10.1016/​j.cpr.2012.03.001 Vincent, J. (2005). Emotional attachment to mobile phones: An extraordinary relationship. In Mobile World (pp. 93–​104). London, UK: Springer.

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CH A PT E R

 Internet-​Based Interventions for Eating Disorders

27

Anja Hilbert, Lisa Opitz, and Martina de Zwann

Abstract Evidence demonstrating the efficacy of treatment and prevention programs for eating disorders is accruing. However, the common face-​to-​face delivery of these interventions has a number of limitations, including high cost and limited accessibility. E-​mental health, referring to the use of information and communication technology—​particularly the Internet—​in interventions for mental health disorders, has the potential to overcome these barriers and enhance the treatment and prevention of eating disorders. To date, the limited number of evaluations have documented small to moderate effect sizes in the improvement of eating disorder symptomatology through Internet-​based treatment and prevention. Beyond efficacy, major questions remain regarding content, structure, and modes of delivery of Internet-​ based interventions; suitable diagnostic tools and safety measures; and cost-​effectiveness, dissemination, and implications for public health programming. These aspects deserve attention in future research before widely recommending Internet-​based interventions for eating disorders. Key Words:  eating disorder, E-​mental health, Internet, intervention, prevention, treatment

Introduction

The number of worldwide Internet users increased by 900% between 2000 and 2016 (Internet World Stats, 2016). This huge global expansion of the availability and use of the Internet not only caused remarkable changes in daily life, but also influenced healthcare, including mental healthcare, by opening up numerous new ways of delivery. E-​mental health refers to the use of information and communication technology, particularly the Internet, to support and improve mental health conditions and mental healthcare (Riper et  al., 2012). E-​mental health service options are still at an early stage of development and implementation for many mental disorders, including eating disorders (EDs), and only the future will show how they will affect treatment delivery and the national health systems over the long term. Internet-​based delivery of psychological treatments has the potential to result in substantial improvements of mental healthcare, but at the same time bears several risks that must be

considered as well. The purpose of this chapter is to present an overview of different Internet-​based approaches to the treatment and prevention of EDs and their efficacy, with a focus on programs that have been evaluated in randomized controlled trials (RCTs), if available. Finally, this chapter delineates directions of future research on Internet-​based ED interventions.

The Potential of Internet-​Based Interventions

Currently, the conventional ED treatment via face-​to-​face interventions has a number of limitations. Epidemiological studies revealed that only a minority of people who meet diagnostic criteria for an ED seeks or receives mental healthcare, and this especially concerns specialized ED treatment (Hart, Granillo, Jorm, & Paxton, 2011; Hoek & van Hoeken, 2003; Kessler et al., 2013). The efficacy and effectiveness of ED interventions as well as prevention has already been evaluated, but their 505

broad dissemination from research into practice appears challenging and costly (Stice, Becker, & Yokum, 2013). On the part of the affected individuals, exploratory studies documented reasons for low healthcare-​seeking such as social barriers (e.g., fear of stigma, shame, and social stereotyping), personal barriers (e.g., low motivation), and organizational barriers like high cost and low availability (Becker, Hadley Arrindell, Perloe, Fay, & Striegel-​Moore, 2010; Evans et al., 2011). Thus, numerous obstacles in ED treatment and prevention remain to be surmounted, which could be addressed by Internet-​ based interventions. One major benefit of Internet-​based interventions is their lack of geographic boundaries, making widespread dissemination easily possible. Their remarkable local and temporal flexibility in comparison to face-​to-​face therapies is especially relevant for individuals who would otherwise be hard to reach, for example, people living in remote or psychotherapeutically undersupplied areas, individuals with reduced mobility (e.g., due to physical disability), or individuals who consider a conventional therapy difficult to obtain because of financial or time constraints (Burns, Durkin, & Nicholas, 2009; Fairburn & Patel, 2014; Kersting, Schlicht, & Kroker, 2009). Moreover, Internet-​based interventions have the advantage of allowing patients to retain a greater sense of anonymity, which makes them attractive for individuals who are reserved in emotional disclosure or who wish to have independence from a therapist (Kersting et  al., 2009). The anonymous aspect is crucial especially for patients who would otherwise not seek help out of shame or fear of stigmatization (Burns et al., 2009). In general, anonymity can reduce feelings of shame and thereby enable patients to disclose their intimate thoughts and feelings more openly, a phenomenon labeled the disinhibition effect (Suler, 2004). A subgroup of patients for whom online interventions could especially be relevant are young individuals in the early stages of ED syndrome development. Often these patients are uncertain about seeking help because of a lack of knowledge on EDs and fear of stigmatization, which can result in a long delay between ED onset and the start of a treatment (Bauer et al., 2013; Fairburn & Murphy, 2015). Internet-​ based interventions may shorten this delay by engaging these individuals early and informing them about the disorder and its treatment, which makes these interventions a source of secondary prevention (Bauer et al., 2013). They further can motivate patients to contact services for a 506

Internet-Based Interventions

face-​to-​face treatment (Robinson & Serfaty, 2001), but they could also be sufficient, for example, when treating less severe or subclinical cases with EDs, so that recovery could be achieved without face-​to-​face therapy (Fairburn & Murphy, 2015). The dangerous potential of the Internet in promoting the development of EDs with proanorexia websites, mostly targeting young females (e.g., Norris, Boydell, Pinhas, & Katzman, 2006), could be counteracted by platforms that disseminate healthy attitudes and social support (Bauer, Moessner, Wolf, Haug, & Kordy, 2009). Apart from these benefits, the use of Internet-​based interventions for the treatment of mental disorders raises multiple ethical concerns. First, if there is no clear evidence on the efficacy, an Internet-​based intervention bears the risk of being futile or even harmful and might delay users from seeking more appropriate forms of help such as evidence-​based treatments (Fairburn & Murphy, 2015). Rigorous research on the efficacy for the treatment of EDs is still at an early stage, but growing rapidly, which is reflected in recent systematic reviews and meta-​analyses on this topic (Aardoom, Dingemans, Spinhoven, & Van Furth, 2013; Aardoom, Dingemans, & Van Furth, 2016; Bauer & Moessner, 2013; Dölemeyer, Tietjen, Kersting, & Wagner, 2013; Fairburn & Murphy, 2015; Hay & Claudino, 2015; Loucas et al., 2014; Melioli et  al., 2016; Schlegl, Bürger, Schmidt, Herbst, & Voderholzer, 2015). Second, the use of technology could compromise the confidentiality of the patients’ private information, if certain steps are not taken to ensure data protection. Therefore, both providers and patients should be aware of the risks and the necessary measures to protect confidential information (e.g., encryption, passwords; APA, 2013; Fisher & Fried, 2003). Further advice on confidentiality and other important aspects of the delivery of E-​mental health can be found in the Guidelines for the Practice of Telepsychology developed by the American Psychological Association (2013). Third, technology might reduce the quality of interpersonal communication. For example, in treatments delivered in writing only, nonverbal information such as posture, gestures, facial expression, eye contact, and voice intonation are missing, which not only may increase the risk of misunderstandings but also makes them harder to notice and correct (Knaevelsrud, Jager, & Maercker, 2004). Many therapists consider face-​ to-​ face contact necessary for a complete understanding of a patient’s mental and physical condition (Shingleton, Richards, &

Thompson-​Brenner, 2013). However, in an RCT, Celio et  al. (2000) found no difference regarding perceived social support between an Internet-​and a classroom-​delivered psychoeducational intervention for the reduction of body dissatisfaction and disordered eating behaviors in a nonclinical sample. Nevertheless, other research that compared face-​to-​ face communication with online communication between two strangers in a nonclinical sample found that face-​to-​face contact led to a higher degree of closeness, self-​disclosure, and positive and negative affect, though both formats resulted in equivalent emotional understanding and depth of processing (Mallen, Day, & Green, 2003). It is not clear whether or to what extent important clinical information might be missed when therapist-​patient contact is provided solely via technology (Shingleton et  al., 2013). For these reasons, Fairburn and Murphy (2015) recommended that Internet-​based interventions should be regulated.

Internet-​Based Interventions

An increasing number of Internet-​based interventions addressing EDs have been developed for the treatment and prevention of EDs. Regarding the type of ED, most online interventions addressed bulimia nervosa (BN), binge-​eating disorder (BED), subthreshold variants of EDs, and/​ or increased body dissatisfaction. Regarding anorexia nervosa (AN), very few Internet-​ based treatment studies have been conducted, and have consisted of small pilot studies (e.g., Treasure, Macare, Mentxaka, & Harrison, 2010; Yager, 2001, 2003) and relapse prevention studies (Fichter, Quadflieg, & Lindner, 2013; Fichter et  al., 2012). This underrepresentation of AN is presumably related to the severity of the disorder and the medical risks associated with weight loss and starvation (Arcelus, Mitchell, Wales, & Nielsen, 2011), which is why online interventions might not be expected to provide a sufficient level of care (Shingleton et al., 2013). Besides the targeted ED, the existing Internet-​ based ED interventions can be differentiated by several aspects: the extent to which they include human communication versus provision of information on a website; whether they are conducted textually, by audio, video, or combinations thereof; whether they are delivered in real time (synchronously, e.g., through chats or video calls) or delayed (asynchronously, e.g., through e-​mails); whether the setting is individual or in groups; and on which underlying therapeutic approach they are based. Regarding the latter aspect, a noticeable characteristic of

Internet-​based ED treatment studies is that almost all of them incorporated principles of cognitive-​ behavioral therapy (CBT; see Fairburn, 2008). In addition, the majority of manualized and evidence-​ based ED self-​help programs, which are easily disseminable over the Internet, are based on CBT (Fairburn & Wilson, 2013). In general, structured behaviorally focused interventions may be more easily translated to technology platforms than other methods that focus more on interpersonal relations or affect (Shingleton et al., 2013).

Psychotherapy via Internet

Internet-​based treatments for EDs range between those that operate completely without the interaction of the patient with a therapist, based solely on the use of a programmed website, and those in which a human therapist conducts the whole intervention, though at a distance from the patient. The highest degree of integration of traditional psychotherapy practice into Internet technology is reached when actual psychotherapy is administered via devices such as e-​mail, video chat, and voice call—​ the medium of communication being the only difference between this kind of intervention and face-​to-​face psychotherapy. The first study of ED therapy delivered entirely via e-​mail was published by Robinson and Serfaty in 2001 and repeated as an RCT in 2008. Ninety-​ seven participants fulfilling DSM-​ IV diagnostic criteria for BN, BED, or eating disorder not otherwise specified (EDNOS) were randomized to e-​ mail therapy, unsupported self-​directed writing, or a wait-​list control condition. The treatment lasted 3  months with two e-​mails per week on average. The therapists assessed the history of ED symptoms; encouraged self-​monitoring of food intake and feelings; helped the patients to identify and change maladaptive cognitions, relationships, and behaviors that might exacerbate the ED; and worked on establishing regular, healthy meals. In the self-​ directed writing condition, participants were asked to write e-​mails about their difficulties at least twice a week without receiving any specific therapeutic advice. At the end of treatment, significantly fewer patients met criteria for an ED in the e-​mail intervention compared with the wait-​list control group, yet no significant difference was found between the e-​ mail group and the unsupported self-​ directed writing group (Robinson & Serfaty, 2008). Mitchell et al. (2008) sought to approach conventional psychotherapy by means of a telemedicine CBT, conducting the therapy sessions via video Hilbert, Opitz, de Zwann

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conferencing. This condition was compared to face-​ to-​face therapy in an RCT with 128 patients with threshold and subthreshold BN. Manual-​ based CBT specifically designed for BN was used in 20 therapy sessions over 16 weeks (see Fairburn, 2008). In the first 4 weeks, therapy consisted of psychoeducation, self-​monitoring, development of a regular eating pattern, and stimulus control measures with the goal of reaching control over eating. Later, therapy was more cognitively oriented and included strategies to reduce dieting and improve problem-​ solving, and cognitive restructuring. The concluding sessions focused on the maintenance of progress and relapse prevention. The symptom reduction at post-​treatment, 3-​and 12-​month follow-​ups was comparable for both groups. The face-​to-​face group tended to have larger improvements than the telemedicine group on full remission from binge eating and purging and showed significantly larger improvements on eating disorder psychopathology and depression. As the technological accessibility of video calls was not as advanced as it is today, the study participants were required to travel to a special facility for their therapy. Because of the general availability of Internet programs offering video calls today, this type of Internet therapy could be conducted from home for patients who have a computer with access to the Internet. Another RCT comparing CBT in an Internet version with a face-​to-​face version was conducted by Bulik et  al. (2012), with results not yet published. They conducted a noninferiority trial with 180 patients with BN, comparing the two delivery modes in group format in terms of their relative efficacy, attrition, adherence, acceptability, maintenance of therapeutic gains over 1 year of follow-​ up, and cost-​effectiveness. In either condition, the treatment consisted of 16 sessions over 20 weeks for small groups of patients. The manual was modified both for face-​to-​face group delivery and Internet delivery and included psychoeducation, self-​ monitoring, normalization of meals, cue identification, restructuring automatic thoughts, chaining, relapse prevention, and body image interventions. The Internet therapy took place using Web-​based materials and through text-​based group chats. A 16-​ week individual Internet-​ based CBT program for patients with BED was compared to a wait-​list control condition in an RCT with 139 participants by Wagner et al. (2016). Internet-​based CBT consisted of 11 personalized structured writing assignments, complementary daily eating and activity diaries, week plans, and psychoeducation. 508

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Therapists provided individualized text-​based feedback and encouraged participants to call or e-​mail anytime in cases of distress. The modules’ topics included identification of individual eating patterns, establishment of regular and healthy eating behaviors and exercise, identification of triggers for binge eating and distraction strategies, cognitive restructuring of negative eating–​ or body image–​ related thoughts, problem-​solving and social skills training, and relapse prevention. At post-​treatment, the intervention group showed significant improvement in binge-​eating frequency and ED psychopathology compared to the control group, which was largely maintained over 1-​year follow-​up. In addition, at post-​treatment, full remission from binge eating was significantly higher in the intervention group than in the control group.

Guided and Unguided Self-​Help

Besides therapeutic approaches, which resemble traditional psychotherapy with the major difference of proceeding via Internet instead of face-​to-​ face, numerous Internet-​based self-​help programs to treat or prevent EDs have been developed, based on evidence-​based psychological treatments, mostly CBT, and self-​help applications. An advantage of the Internet-​based mode of delivery in comparison to books is the possibility to arrange interactive contents that provide tailored feedback to their users throughout participation. Furthermore, the treatment can be personalized to individual characteristics, interests, needs, and problems, an important advantage in light of the patients’ varying needs concerning information, frequency, duration, and intensity of support (Bauer & Moessner, 2013; Fairburn & Patel, 2014). Additionally, online interventions can be designed to exchange real-​time information with compatible smartphone apps, which might enhance their effects (Fairburn & Patel, 2014). Self-​ help can be subdivided into guided and unguided self-​help, depending on the existence of guidance by a therapist. As unguided self-​help operates without communicating with another person and proceeds entirely via an Internet program, it has the advantage of allowing the greatest extent of anonymity, and may be cheaper and more accessible than guided self-​help. However, little research has addressed unguided Internet-​based self-​help for EDs. Leung, Ma, and Russell (2013) conducted an open trial with 280 patients with EDs to investigate an unguided Internet-​based self-​help program that included components on healthy eating; family

education; health assessment; motivation enhancement; self-​help strategies to normalize eating patterns; challenging negative thoughts; developing problem-​ solving skills; and psychological health promotion strategies. A total of 63% of the patients used the program for self-​help, and this subgroup demonstrated significant improvement in ED psychopathology, motivational stage of change, depression, and perceived health status at one-​ month follow-​up when compared to baseline. However, these findings refer to users only, and as there was no control group, the results are to be considered preliminary. In guided self-​ help programs, the guidance component can be administered face-​ to-​ face or online; the former has not been investigated to date, whereas the latter has been addressed in several studies. Offering online sessions and weekly supportive e-​mails, the CBT-​based guided self-​help program “Salut BED/​Salut BN” (Carrard et al., 2006, 2011; de Zwaan et al., 2017; Wagner et al., 2013) consists of seven modules, each including lessons, examples, and exercises about the motivation to change, self-​monitoring of ED symptoms, behavioral strategies to prevent binge eating, changing automatic thoughts, problem-​ solving, assertiveness training, and relapse prevention (Carrard et al., 2006). The BED version contains additional modules dealing with physical activity, triggers of binge-​ eating episodes, and meal plans (Carrard et al., 2011). Participants receive automatic feedback and graphs visualizing their binge-​ eating episodes and other ED symptoms (Carrard et al., 2006). Guidance is provided through regular e-​mail contact with a psychologist during the intervention. Salut BN version was evaluated in an RCT by Wagner et  al. (2013) with 155 women with BN and EDNOS in comparison to guided bibliotherapy, which consisted of a self-​help book and e-​mail support from a therapist. Both self-​help programs were delivered over 7 months and both significantly reduced the frequency of binge eating, vomiting, and fasting, with the greatest improvements within the first 4  months during treatment. Symptoms were further improved by continued treatment to post-​treatment at month 7 and stabilized to month 18. No difference in these intent-​to-​treat effects was found between Internet-​based and book-​based delivery of self-​help. Carrard et al. (2011) evaluated Salut BED over 6 months in an RCT with 74 women with threshold or subthreshold BED in comparison to a wait-​list control group. After the Internet-​based

intervention, binge-​eating frequency, eating disorder psychopathology, self-​ esteem, quality of life, and body mass index (kg/​ m2) were significantly improved in comparison to the control group. Improvements were maintained at 6-​month follow-​ up. In addition, the intervention group reported greater remission from binge eating than the control group at post-​treatment. de Zwaan et al. (2017) compared the same program to a face-​to-​face CBT in a noninferiority RCT with 178 patients with threshold or subthreshold BED. Over a period of 4 months patients received 20 individual sessions in the face-​to-​face CBT condition, and 17–​18 e-​mails and two face-​to-​face sessions in addition to the Web-​based program in the Internet condition. At the end of treatment and at 6-​month follow-​up, significant reductions in binge eating were observed in both conditions, with the Internet treatment inferior to the face-​to-​face-​treatment, yet at 18-​month follow-​up, there were no statistically significant differences between the two conditions. And ED psychopathology was significantly more reduced in the face-​to-​face condition than in the Internet condition at 6-​month follow-​up. “Overcoming Bulimia Online” (Williams, Aubin, Cottrell, & Harkin, 1998) is an intensive Internet-​based, interactive, multimedia, guided self-​ help program consisting of eight CBT-​based lessons with homework, group and individual online guidance, and supportive e-​mails from therapists. Sánchez-​ Ortiz et  al. (2011) conducted an RCT with 76 students with BN or EDNOS comparing a 3-​month treatment with this program to a wait-​list control condition. At post-​treatment and 3-​month follow-​up, the treatment group showed significantly greater improvement in ED psychopathology, depression, anxiety, and quality of life compared with the control group. Ljotsson et al. (2007) combined book-​based self-​ help with online guidance, providing patients with BED and BN (threshold and subthreshold) with the CBT-​ based self-​ help book Overcoming Binge Eating (Fairburn, 1995) and graduate students with Guided Self-​ Help for Bulimia Nervosa. Therapist’s Manual (Fairburn, 1999) to support the patients via e-​mail once to twice per week. Patients also had the opportunity to chat with each other in an online private discussion forum. In an RCT, 73 patients participated in the 12-​week intervention or a wait-​ list control condition. At post-​treatment, treated individuals showed significantly greater improvement of binge-​eating frequency, ED psychopathology, quality of life, and depression compared to Hilbert, Opitz, de Zwann

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the control group. The results were maintained at 6-​month follow-​up.

Adjunct to Treatment and Aftercare Interventions

Another use of the Internet involves Internet-​ based interventions as an adjunct to conventional face-​to-​face treatment. For instance, during face-​to-​ face therapy the Internet can serve as a device for self-​monitoring of food intake or binge eating by reminding the patient to record them via e-​mail or a smartphone app. As studies on the efficacy of smartphone apps are presented in Chapter 26, they are not further discussed here. With regard to e-​mail delivery, Yager (2001, 2003) conducted a case series expanding the usual face-​ to-​ face psychotherapy of outpatients with AN by regular e-​mail contact. Another example is the above-​presented Internet-​ based unguided self-​help program by Leung et al. (2013). A majority of their study participants were already undergoing treatment for their ED when they were offered Internet-​based unguided self-​help. Furthermore, the Internet can be used for aftercare interventions to ensure the maintenance of gains achieved during face-​to-​face treatment. The existence of Internet-​based programs enables clinicians to provide extended support to patients beyond the completion of inpatient or outpatient treatment. Gulec et al. (2011, 2014) conducted a 4-​ month Internet-​based aftercare program, “EDINA,” with the goal to help patients with BN and related EDNOS maintain their therapeutic gains. The program provided an online information and communication platform for peer support and professional consultation. It included modules such as weekly symptom monitoring, supportive feedback, and professional counseling during group chat sessions, as well as flexible components depending on the patient’s individual needs such as psychoeducation, a forum for peer support, and individual chat sessions. The program was compared to a wait-​list control condition in an RCT with 105 female participants. At post-​treatment, participants from both conditions showed a significant reduction in ED psychopathology compared to pretreatment, but there was no significant difference between conditions. Overall, the program proved to be feasible and well accepted, and participants’ satisfaction was high. The potential of an Internet-​based, manualized CBT-​oriented approach in the aftercare following inpatient treatment was studied in another RCT with 253 women with BN (Beintner & Jacobi, 510

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2011). The 9-​ month intervention called “IN@” included 11 sessions with psychoeducational material as well as self-​monitoring and behavioral tasks concerning eating behavior, weight, body acceptance, coping with emotions, and social skills. Participants were offered to communicate to each other in an asynchronous moderated online discussion group. In addition, they had contact with a therapist who provided feedback on tasks (e.g., self-​ monitoring), conducted a monthly chat session, and was available for questions via e-​mail. The results have not yet been published. Fichter et  al. (2012, 2013) investigated a 9-​ month Web-​based relapse prevention program for patients with AN after inpatient treatment, “VIA,” using CBT strategies such as self-​ monitoring, stimulus control, operant methods, vicarious learning, exposure treatment, and cognitive restructuring. Content included goals and motivation, transfer of therapy components to everyday life, maintenance of a regular eating behavior, handling binge-​eating episodes and compensatory behaviors, body acceptance, self-​ esteem, coping with emotions, social competence, relationships, and problem-​solving. The program also provided a behavioral analysis of problem behavior, tools to monitor change, and interactive elements such as a message board for peer support, monthly group chats with a therapist, and the possibility to write to the therapist at any time. An RCT with 258 patients with AN comparing program participation with treatment as usual, showed that patients who received the online intervention tended to have greater improvement than the control group regarding body mass index, as well as ED behaviors and psychopathology during the 9-​ month observation period (Fichter et  al., 2012). At 9-​ month follow-​ up, both groups showed further improvement in body mass index, eating attitudes, and eating behaviors. The intervention group had a tendency to show larger improvements than the control group on most variables, but significance was reached only for bulimic behavior and menstrual function. Patients who had participated in all 9 monthly intervention sessions reached a significantly higher body mass index compared with the control group (Fichter et al., 2013).

Prevention

Thanks to their accessibility and anonymity, Internet-​based programs could be a convenient first contact point, especially for people with milder ED symptoms that may develop into a full-​blown ED.

If Internet-​based prevention programs are capable of reducing such symptoms and thus avoiding more intense treatments, they could be of great value from a public health perspective (Bauer & Moessner, 2013). A substantial body of research has been conducted on “Student Bodies” (Winzelberg et  al., 2000), an 8-​week Internet-​based CBT program targeting college-​age women at risk of developing an ED. The goals of the program were to reduce weight and shape concerns as well as binge eating, improve body image, and promote healthy weight regulation and knowledge about EDs. The eight sessions consisted of psychoeducation and mandatory and optional assignments that included behavior change exercises; an online, asynchronous, moderated discussion group; self-​ monitoring; and a personal diary. Several RCTs compared Student Bodies with a wait-​list condition in population samples of women (Celio et al., 2000; Graff Low et al., 2006; Jacobi et al., 2005, 2007; Winzelberg et al., 2000) and women at risk of an ED (Jacobi, Völker, Trockel, & Taylor, 2012; Taylor et  al., 2006; Zabinski et  al., 2001). In a meta-​analysis of six US and four German RCTs with 990 participants, Beintner, Jacobi, and Taylor (2012) found mild to moderate improvements in ED psychopathology at post-​ treatment and follow-​up. One study (Celio et al., 2000) additionally compared the program with a classroom-​based body image education intervention, but did not find a significantly greater effect of the Internet-​ based intervention. Student Bodies was adapted for overweight adolescents with binge eating in “Student2Bodies–​ BED” (Doyle et  al., 2008; Jones et  al., 2008), targeting binge eating, weight maintenance, and physical activity. The program consisted of psychoeducation, interactive self-​monitoring journals, an asynchronous discussion group, weekly letters of encouragement, and motivational messages. Two RCTs evaluated the program with 83 and 105 adolescent participants, respectively, at risk of BED, in comparison to a wait-​list control (Doyle et  al., 2008; Jones et al., 2008). Doyle et al. (2008) found a significant reduction compared with the control group in body mass index z-​score from baseline to post-​treatment, which was maintained at 4-​month follow-​up, though the difference was not significant due to improvement in the control group. There were no significant effects for other outcomes. However, Jones et  al. (2008) found a significant effect for body mass index, body mass index z-​score,

binge-​eating frequency, and weight and shape concern from baseline to 9-​month follow-​up. Stice, Rohde, Durant, and Shaw (2012) developed the 3-​ week Internet-​ based ED prevention program “eBody project” and evaluated it in comparison to its face-​to-​face group version in an RCT with 107 female college students with body dissatisfaction. For further comparison, an educational video control condition and an educational brochure control condition were conducted in addition. The eBody project program was based on cognitive dissonance theory and consisted of six written and behavioral activities designed to critically address the thin-​ideal. The face-​to-​face condition followed a similar approach delivered in group format. There was no difference in effects between the Internet condition and the face-​to-​face condition, both demonstrating greater pre-​post reductions in ED symptoms and psychopathology than the two control groups. Gollings and Paxton designed the interactive program “Set Your Body Free” (2006) for women with high body dissatisfaction and disordered eating. The participants received eight weekly manualized group sessions in real time with a therapist in an online chat room. In addition, participants could communicate with each other between sessions in an asynchronous discussion board. Before each session, participants received the treatment manual that provided ED-​focused psychoeducation, a treatment topic guide, and out-​ of-​ session activities. Based on CBT, the session topics consisted of enhancing motivation to change; exploring associations among body image, self-​esteem, emotions, and relationships; examining risk factors for body image and eating problems; teaching strategies for changing negative body image thoughts; challenging body comparison tendencies and internalized sociocultural beauty ideals; and elaborating strategies for identifying and changing unhealthy eating patterns and weight loss behaviors. In an RCT comparing the Internet delivery of this program with face-​to-​face delivery and a delayed treatment control condition in 116 women with high body dissatisfaction, both groups showed large improvements in body dissatisfaction at the end of treatment compared with the delayed treatment control group, with greater effects in the face-​to-​face condition. At 6-​month follow-​up the effects in both groups were maintained and, owing to continued improvement in the Internet condition, were no longer different from each other (Paxton, McLean, Gollings, Faulkner, & Wertheim, 2007). Hilbert, Opitz, de Zwann

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A further guided Internet-​based program “ESS-​ KIMO” for people with symptoms of AN or BN by Hötzel et  al. (2014) focused on enhancing motivation to change, based on the transtheoretical model (Prochaska & DiClemente, 1992) and using the principles of motivational interviewing (Miller & Rollnick, 2002). ESS-​KIMO consisted of six online sessions with psychoeducation and writing tasks concerning the benefits and costs of the patient’s ED, the ED’s impact on his or her daily life and life goals, and sources of self-​esteem. After each assignment, the participant received individualized electronic feedback by a therapist. Results of an RCT with 212 women with symptoms of AN or BN demonstrated the program to be significantly superior to a wait-​list control condition in improving motivation to change, self-​ esteem, dietary restraint, and vomiting. This suggests the Internet to be a potentially useful means to raise motivation to start a treatment in individuals with an ED who are ambivalent toward change. Aardoom and colleagues investigated the effects and cost-​ effectiveness of the Internet-​ based program “Featback” for individuals with ED symptoms, comparing different intensities of therapist support (Aardoom, Dingemans, Spinhoven, et al., 2016; Aardoom, Dingemans, van Ginkel, et al., 2016). The program consisted of psychoeducation with fully automated self-​monitoring and feedback. A total of 354 participants with ED symptoms were randomized to four groups: the program only, the program combined with low-​intensity digital therapist support (weekly), the program combined with high-​intensity support (three times per week), and a wait-​list control condition. From baseline to post-intervention, the three intervention conditions were significantly superior to the control condition in ED behaviors and psychopathology, depression and anxiety, and perseverative thinking. Therapist support did not increase symptom reduction, but enhanced participants’ satisfaction with the intervention (Aardoom, Dingemans, Spinhoven, et al., 2016). As one of the only studies in the field additionally examining costs and utility, the results did not show any significant difference between conditions regarding quality-​ adjusted life years and societal costs. Regarding cost-​ effectiveness, the intervention was superior to the control condition with no clear preference for the program with or without therapist support (Aardoom, Dingemans, van Ginkel, et al., 2016). An Internet-​based program for university students that aimed to integrate education, prevention, 512

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early detection, and early intervention regarding EDs was developed by Bauer et al. (2009). The program “ES[S]‌PRIT” followed a stepped-​ care approach combining various support components of increasing intensity, which included psychoeducation, symptom monitoring, tailored supportive feedback, peer support, and professional chat-​based counseling. Participants could use the various support components flexibly according to their needs. In the case of severe self-​reported ED symptoms, participants were encouraged to access more intense face-​to-​face help. The efficacy of an adapted version of the program for high school students (“YoungEs[s]prit”) in preventing the onset of self-​ reported ED symptoms was studied in an RCT with 1,667 healthy participants (Lindenberg & Kordy, 2015). The cumulative ED incidence rate over 12 months significantly decreased in the study’s first wave, yet no difference between the intervention and control groups was found in the second subsample. An enhanced version of this program with similar goals and components was developed in the initiative “ProYouth” (https://www.proy­outh.eu/ de/network). This enhanced version targets young people between 15 and 25 years and has been disseminated in nine European countries. More than 15,000 people have used its online screening tools and more than 6,000 have registered for full access to the platform (Bauer, Minarik, Özer, & Moessner, 2014). The risk of developing an ED has been shown to be the strongest predictor for a long-​term use of the program, which confirms that participants adapt the intensity of their program use to their individual needs (Moessner, Özer, Minarik, & Bauer, 2013). Moessner, Minarik, Özer, and Bauer (2016) investigated a sample of 453 “ProYouth” users 3 months after their registration, finding that 10% had taken up treatment in conventional healthcare, 8% intended to do so, and 43% of the remaining said they would do so in case of need. A total of 50% of (potential) help-​seekers reported that their attitude toward help-​seeking had changed through the participation in the program. These results suggest that access to conventional healthcare can be facilitated through participation in an Internet-​based program such as ProYouth.

Carer Support

Research has shown that carers of people with EDs often experience high levels of psychological distress and play an important role in the recovery process (Hibbs, Rhind, Leppanen, & Treasure, 2015). Internet-​based programs could be helpful

by offering information, professional support, and contact to carers in an easily accessible way (Bauer & Moessner, 2013). Nevertheless, research on Internet-​ based programs for this target group is scarce. An RCT with 64 carers of individuals with AN by Grover et al. (2011) investigated a 4-​month Internet-​ delivered systemic CBT-​ based intervention (“Overcoming Anorexia Online”), designed to reduce carers’ distress and to educate them in how to effectively offer support. The intervention participants received the program and guidance from a clinician in 20-​minute sessions per week, while the control group used the usual support services of an AN patient and carer organization. The intervention had a significantly greater positive impact on carers’ anxiety and depression levels than the control condition, and gains were maintained at 2-​month follow-​ up. Furthermore, a pilot study with 13 participating parents of adolescents with an ED examined an Internet-​ based chat support group as adjunct to face-​to-​face family-​based treatment (Binford Hopf, Grange, Moessner, & Bauer, 2013). Results were promising, as most parents stated that they were satisfied with the chat and found it helpful.

Evaluation

The majority of the studies presented here found positive effects for the Internet-​based program under investigation. In most cases, the Internet-​based program led to significantly greater improvements than a wait-​list control condition and was equally efficacious compared with face-​to-​face delivery. Given these effects, most of the existing reviews concluded that Internet-​based interventions for EDs are promising (Aardoom et al., 2013; Dölemeyer et al., 2013, Shingleton et al., 2013). In addition, Dölemeyer et al. (2013) emphasized in their systematic review of eight RCTs and controlled trials on Internet-​based ED treatment the value of guided self-​help, for which they had found medium to large effects both within and between groups. They further noted that treatment dropout differed greatly between studies (between 9% and 47%). Along these lines, Aardoom et  al. (2013) found in their systematic review of 21 studies on Internet-​based interventions on EDs that studies which included one or more face-​to-​face sessions had lower dropout rates than those that did not. They further found Internet-​ based treatment to be more effective for individuals with lower level psychopathology. However, the first meta-​ analysis in this field came to less positive conclusions. Loucas et  al.

(2014), using rigorous methodology, identified 16 RCTs of online interventions designed to prevent or treat EDs, excluding studies where a conventional psychotherapy was transmitted electronically (CBT via videoconferencing). They included only one study on AN treatment (Fichter et al., 2012, 2013); the remaining studies investigated BED, BN, and/​ or EDNOS. According to their meta-​ analysis, only two of four programs on Internet-​ based ED prevention—​ “Student Bodies” and “ESS-​ KIMO”—​ were associated with improvements in ED behaviors and psychopathology. The improvements were of small size and with moderate confidence in the effect estimates for Student Bodies and low confidence for ESS-​KIMO. Concerning treatment and relapse prevention, beneficial effects were found for all five included interventions, though for most outcomes evidence came from single studies and confidence in the effect estimates was low, often due to high risk of bias. Thus, Loucas et  al. (2014) concluded that the value of Internet-​based interventions for EDs must be considered uncertain regarding BN and BED and unknown regarding AN, as they considered the evidence base too small. Contradicting previous systematic reviews (Aardoom et  al., 2013; Dölemeyer et  al., 2013), they stated, “It is impossible to describe the finding as ‘promising’ and there is certainly no basis for saying that e-​therapy is a good alternative to face-​ to-​face treatment” (Loucas et  al., 2014, p.  130), which is why they did not encourage its application at that moment, but strongly emphasized the need for further research. They considered only Student Bodies as efficacious with regard to reduction of ED psychopathology, but noted that the program’s impact on the risk of subsequent ED development was unknown. Moreover, they pointed out the danger that if an online program that is not empirically supported pretends to promote recovery, people with EDs may use it instead of seeking an evidence-​ based form of treatment, and thereby delay recovery. Two years after the meta-​analysis of Loucas et al. (2014), Melioli et  al. (2016) conducted another meta-​analysis with the additional goal to identify variables that might account for the interventions’ efficacy. They analyzed 20 controlled Internet-​based intervention studies for selective prevention and treatment of EDs, including five more studies that had not been included by Loucas et al. (2014). They found small to moderate effect sizes for reductions in ED behaviors and psychopathology. Concerning moderators of efficacy, no differences were found in effects between nonclinical/​mixed and high-​risk Hilbert, Opitz, de Zwann

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participants on all outcomes; for shape concern only there was a larger decrease in the high-​risk sample. Furthermore, there was no difference between intent-​to-​treat or completer analyses, indicating that these variables did not account for the programs’ efficacy. The findings of this more inclusive review seem rather optimistic, highlighting that Internet-​based programs are successful in decreasing ED symptomatology. Nevertheless, still more research is needed to, first, increase the programs’ effects, and second, enlarge the evidence base. When evaluating Internet-​ based interventions for EDs, a significant question is whether they actually improve access to care. The above-​ described “ProYouth” study with its stepped-​care approach indicated that users’ attitudes toward help-​seeking in face-​to-​face mental healthcare may be changed, especially in case of more severe symptoms (Moessner et  al., 2016). More evidence for Internet-​based interventions’ benefit in improving access to care was brought by McClay, Waters, Schmidt, and Williams (2016), who conducted a descriptive study in a community-​based sample of 253 individuals with symptoms of BN who revealed positive attitudes toward accessing online self-​help and rather negative attitudes toward face-​ to-​ face treatments, due to fear, shame, long waiting lists, and negative past experiences with such treatments. Thus, these individuals would not have sought help in conventional treatments but were more likely to seek help in Internet-​based treatments. In the guided self-​ help study of Wagner et  al. (2013), where participants with EDs had been recruited via advertisement, 66% of them stated that they had not received any psychotherapeutic or inpatient treatment before, which also supports the assumption that Internet-​ based interventions can reach underserved populations. A question that has not received satisfactory answers yet is how to establish ED diagnosis in accordance with the clinical classification systems in the case of Internet-​based treatments, as the standard for diagnosis is a face-​to-​face clinical interview. It could be problematic to conduct a face-​to-​face session before an Internet-​based treatment because this form of treatment may be chosen for its anonymity and accessibility, which would then be undermined (Aardoom, Dingemans, van Ginkel, et  al., 2016). For this reason, establishing reliable diagnostic tools via online self-​report assessment would be helpful, thereby preserving the advantages of Internet-​based treatment delivery. For this goal, established and new assessment tools are being evaluated for online 514

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use. However, establishing adequate diagnostic validity including appropriate sensitivity and specificity of online self-​report assessments is a challenge on its own (ter Huurne et al., 2015). To conclude the evaluation of Internet-​ based interventions, it seems to be premature to deduce whether they are generally useful or recommendable. The existing interventions differed largely regarding target groups (e.g., age, severity of symptoms, disorder); medium (e.g., e-​mail, chat, videochat, forums); therapist contact (frequency and mode of contact, e.g., via group or individual chat, e-​mail, and/​or face-​to-​face); duration, intensity, and content; and follow-​ up assessment(s). Moreover, the studies differed in their definitions of therapy, prevention, and self-​ help, making an evaluation more difficult.

Implications

Research on Internet-​ based interventions for EDs is at an early stage, and many questions remain to be answered. However, due to their numerous and specific advantages, more research is urgently needed in order to further enhance and stabilize long-​term effects of Internet-​based therapy, unguided and guided self-​ help, therapeutic adjuncts, aftercare, and prevention. For this goal, Loucas et al. (2014) suggested that program developers should take more advantage of two major strengths of the Internet that cannot be provided by self-​help books: the possibility to personalize interventions and to make them interactive, possibly further increasing acceptance by users and enhancing their outcome. More studies on predictors of outcome and attrition as well as mechanisms of change would be useful to tailor Internet-​based interventions for EDs to the individual patient’s needs, for example, regarding the intensity, speed, and components of the intervention, and the frequency of therapist contact (Aardoom, Dingemans, & van Furth, 2016; Bauer & Moessner, 2013; Melioli et  al., 2016; Schlegl et  al., 2015). Loucas et  al. (2014) and Fairburn and Murphy (2015) also highlighted the need for direct-​to-​user studies and recruitment of participants directly from the community to examine the greatest potential benefit of Internet-​ based interventions:  their ability to directly reach those who would benefit. The patient perspective could be more emphasized in the development of Internet-​based interventions, for example, in studies exploring patients’ acceptance, opinions, needs, preferences, and wishes. More programs that are

based on therapeutic approaches other than CBT should be developed and evaluated to expand the scope of available treatments. It is especially relevant to further develop and evaluate Internet-​ based interventions concerning aftercare and relapse prevention, as a considerable number of patients experience relapse after successful treatment, particularly in the first months following treatment termination (Olmsted, Kaplan, & Rockert, 1994). Thus, a continuous availability of support could help to promote maintenance of therapeutic gains. Internet-​based aftercare programs might be useful to help individuals in the process of recovery and early relapse detection, as they are easily accessible and require little therapist assistance (Gulec et al., 2014). Another important aspect that has not sufficiently been considered in the previous research on Internet-​based interventions for EDs is how to guarantee a patient’s safety in cases of crisis (Schlegl et  al., 2015). Especially in unguided programs, where there is no therapist who could be called or e-​mailed, there are few options for action if a participant needs urgent support. Internet-​based carer support for EDs also has received little attention so far and has even been ignored by most reviews, although families may have a decisive influence on a patient’s recovery. When conducting research in this field, it would be important to not only evaluate the effects of such interventions on the carers but also on the individual with the ED (Bauer & Moessner, 2013). Furthermore, more research on cost-​effectiveness of all forms of Internet-​based interventions for EDs is needed, as this is one of their often assumed benefits. Currently, there are only the results of one study by Aardoom, Dingemans, van Ginkel, et al. (2016), demonstrating that their intervention was more cost-​ effective than a wait-​ list control condition, with no differences regarding intensity of therapist support. It is important to examine whether this also applies to other programs. In addition, there should be more systematic studies that compare different dosages of therapist support to further examine whether this aspect makes a difference regarding the efficacy of an Internet-​based treatment. Regarding the qualification of the therapist, costs could be reduced if support were provided by a less-​trained person. In order to find out if cost-​effectiveness could be improved in this way, Aardoom et  al. (2013) suggested investigating whether the support can also be effectively provided by nonprofessionals instead of specialists.

The possibilities of integrating Internet-​ based interventions and face-​to-​face treatments should be investigated, both within stepped-​care approaches of ED treatment, as has been done in the “ProYouth” initiative, and within blended care interventions (Aardoom, Dingemans, & van Furth, 2016; Bauer & Moessner, 2013). Blended care has the potential to provide the benefits of Internet-​based as well as face-​to-​face interventions and to thus improve both effects and costs:  Internet-​based components can reduce travel time and promote self-​management, while face-​to-​face sessions can be more personal and consolidate the therapeutic relationship (Aardoom, Dingemans, & van Furth, 2016). Concerning stepped care, broadly disseminated Internet-​based initiatives could facilitate access to ED treatments by reducing psychosocial barriers such as stigma and lack of mental health literacy (Bauer & Moessner, 2013). More research is needed to determine whether and how such programs can improve help-​ seeking behaviors and consequently accelerate treatment uptake in people with EDs. Another aspect not mentioned in most studies and reviews is the problem of diagnosis in Internet-​ based ED treatments, as an accurate diagnosis is normally the first step of any conventional psychotherapy. Therefore, it would be of great value to validate established instruments with good ED screening properties for their use via the Internet, in order to create the possibility of an accurate online diagnosis as a solid basis for online treatment.

Methodological Aspects

As existing studies often lack good confidence in effect estimates (Loucas et  al., 2014), more RCTs with good methodological quality and low risk of bias are needed. Risk of bias can be caused, among other things, by substantial amounts of missing data due to high dropout rates. Missing data can be handled by certain statistical techniques (Aardoom, Dingemans, & van Furth, 2016), but are ideally to be avoided by avoiding treatment and study dropouts, which would also enhance an intervention’s effects. In light of considerable dropout rates, the reasons for treatment dropout and noncompliance need to be elucidated further (Aardoom, Dingemans, & van Furth, 2016). In order to improve reporting of Internet-​ based intervention studies, the CONSORT reporting criteria for research on E-​ health interventions should be followed (Eysenbach & CONSORT-​EHEALTH Group, 2011). Furthermore, most studies compared the online intervention with an inactive wait-​ list control Hilbert, Opitz, de Zwann

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condition. Based on the positive effects found in these comparisons, further steps of intervention design should include active control conditions, for example, face-​to-​face interventions using noninferiority designs, as well as different Internet-​based interventions compared with each other (Aardoom et  al., 2013; Bauer & Moessner, 2013; Schlegl et al., 2015).

Conclusion

Internet-​based interventions for EDs have the potential to increase patients’ access to treatment, given their advantages of providing greater local and temporal flexibility, control, and anonymity. As has been shown in this chapter, varieties of different applications are possible: They could serve as low-​intensity initial interventions treating milder cases and convince more severe cases to start more intensive face-​to-​face treatment. They could further be used as an adjunct to face-​to-​face psychotherapy, as online-​transmitted psychotherapy, as a relapse-​ prevention aid, as stand-​alone or guided self-​help, or as a support base for patients’ carers. Internet-​ based programs have been found to successfully decrease ED-​ related symptoms and risk factors. Confirmatory tests of their efficacy with adequate power are needed, as there are little data in this area and both the methodological quality and the level of evidence of conducted studies are limited. After efficacy has been demonstrated, Internet-​ based interventions should be evaluated concerning their effectiveness within routine care, before they can be broadly disseminated and implemented. Thus, future research is needed before widely recommending Internet-​based interventions for EDs.

Acknowledgments

This research was supported by the German Federal Ministry of Education and Research (grant 01EO1501).

References

Aardoom, J. J., Dingemans, A. E., Spinhoven, P., & Van Furth, E. F. (2013). Treating eating disorders over the Internet: A systematic review and future research directions. International Journal of Eating Disorders, 46, 539–​552. Aardoom, J. J., Dingemans, A. E., Spinhoven, P., van Ginkel, J. R., de Rooij, M., & van Furth, E. F. (2016). Web-​based fully automated self-​help with different levels of therapist support for individuals with eating disorder symptoms:  A  randomized controlled trial. Journal of Medical Internet Research, 18, e159. Aardoom, J. J., Dingemans, A. E., van Ginkel, J. R., Spinhoven, P., Van Furth, E. F., & Van den Akker-​van Marle, M. E. (2016). Cost-​utility of an Internet-​based intervention with

516

Internet-Based Interventions

or without therapist support in comparison with a waiting list for individuals with eating disorder symptoms: A randomized controlled trial. International Journal of Eating Disorders, 49, 1068–​1076. Aardoom, J. J., Dingemans, A. E., & van Furth, E. F. (2016). E-​ health interventions for eating disorders: Emerging findings, issues, and opportunities. Current Psychiatry Reports, 18, 42. American Psychological Association. (2013). Guidelines for the practice of telepsychology. American Psychologist, 68, 791–​800. Arcelus, J., Mitchell, A. J., Wales, J., & Nielsen, S. (2011). Mortality rates in patients with anorexia nervosa and other eating disorders:  A  meta-​analysis of 36 studies. Archives of General Psychiatry, 68, 724–​731. Bauer, S., Minarik, C., Özer, F., & Moessner, M. (2014). EPA-​ 1485–​Internet-​ based prevention and early intervention in eating disorders:  Findings from the European project ProYouth. European Psychiatry, 29, 1. Bauer, S., & Moessner, M. (2013). Harnessing the power of technology for the treatment and prevention of eating disorders. International Journal of Eating Disorders, 46, 508–​515. Bauer, S., Moessner, M., Wolf, M., Haug, S., & Kordy, H. (2009). ES[S]PRIT—​an Internet-​based programme for the prevention and early intervention of eating disorders in college students. British Journal of Guidance and Counselling, 37, 327–​336. Bauer, S., Papezova, H., Chereches, R., Caselli, G., McLoughlin, O., Szumska, I.,  . . .  Moessner, M. (2013). Advances in the prevention and early intervention of eating disorders:  the potential of Internet-​delivered approaches. Mental Health and Prevention, 1, 26–​32. Becker, A. E., Hadley Arrindell, A., Perloe, A., Fay, K., & Striegel-​ Moore, R. H. (2010). A qualitative study of perceived social barriers to care for eating disorders: Perspectives from ethnically diverse health care consumers. International Journal of Eating Disorders, 43, 633–​647. Beintner, I., & Jacobi, C. (2011). Internetgestützte Nachsorge bei Bulimia nervosa: Behandlungsmanual und Studiendesign [Internet-​based follow-​up care for bulimia nervosa: Treatment manual and study design]. Psychotherapeut, 56, 516–​521. Beintner, I., Jacobi, C., & Taylor, C. B. (2012). Effects of an Internet-​based prevention programme for eating disorders in the USA and Germany: A meta-​analytic review. European Eating Disorders Review, 20, 1–​8. Binford Hopf, R. B., Grange, D. L., Moessner, M., & Bauer, S. (2013). Internet-​ based chat support groups for parents in family-​based treatment for adolescent eating disorders:  A  pilot study. European Eating Disorders Review, 21, 215–​223. Bulik, C. M., Marcus, M. D., Zerwas, S., Levine, M. D., Hofmeier, S., Trace, S. E.,  . . .  Kordy, H. (2012). CBT4BN versus CBTF2F:  Comparison of online versus face-​to-​face treatment for bulimia nervosa. Contemporary Clinical Trials, 33, 1056–​1064. Burns, J. M., Durkin, L. A., & Nicholas, J. (2009). Mental health of young people in the United States: What role can the Internet play in reducing stigma and promoting help seeking? Journal of Adolescent Health, 45, 95–​97. Carrard, I., Crépin, C., Rouget, P., Lam, T., Golay, A., & Van der Linden, M. (2011). Randomised controlled trial of a guided self-​help treatment on the Internet for binge eating disorder. Behaviour Research and Therapy, 49, 482–​491. Carrard, I., Rouget, P., Fernández-​ Aranda, F., Volkart, A.-​ C., Damoiseau, M., & Lam, T. (2006). Evaluation and

deployment of evidence based patient self-​management support program for bulimia nervosa. International Journal of Medical Informatics, 75, 101–​109. Celio, A. A., Winzelberg, A. J., Wilfley, D. E., Eppstein-​Herald, D., Springer, E. A., Dev, P., & Taylor, C. B. (2000). Reducing risk factors for eating disorders: Comparison of an Internet-​ and a classroom-​ delivered psychoeducational program. Journal of Consulting and Clinical Psychology, 68, 650–​657. de Zwaan, M., Herpertz, S., Zipfel, S., Svaldi, J., Friederich, H., Schmidt, F., . . . Hilbert, A. (2017). Effect of Internetbased guided self-help vs individual face-to-face treatment on full or subsyndromal binge eating disorder in overweight or obese patients: The INTERBED randomized clinical trial. JAMA Psychiatry. Advance online publication. Dölemeyer, R., Tietjen, A., Kersting, A., & Wagner, B. (2013). Internet-​based interventions for eating disorders in adults: a systematic review. BMC Psychiatry, 13, 207. Doyle, A. C., Goldschmidt, A., Huang, C., Winzelberg, A. J., Taylor, C. B., & Wilfley, D. E. (2008). Reduction of overweight and eating disorder symptoms via the Internet in adolescents: A randomized controlled trial. Journal of Adolescent Health, 43, 172–​179. Evans, E. J., Hay, P. J., Mond, J., Paxton, S. J., Quirk, F., Rodgers, B.,  . . .  Sawoniewska, M. A. (2011). Barriers to help-​seeking in young women with eating disorders: A qualitative exploration in a longitudinal community survey. Eating Disorders, 19, 270–​285. Eysenbach, G., & CONSORT-​ EHEALTH Group (2011). CONSORT-​ EHEALTH:  Improving and standardizing evaluation reports of Web-​based and mobile health interventions. Journal of Medical Internet Research, 13, e126. Fairburn, C. G. (1995). Overcoming binge eating. New  York, NY: Guilford Press. Fairburn, C. G. (1999). Guided self-​ help for bulimia nervosa: Therapist’s manual. New York, NY: Guilford Press. Fairburn, C. G. (2008). Cognitive behavior therapy and eating disorders. New York, NY: Guilford Press. Fairburn, C. G., & Murphy, R. (2015). Treating eating disorders using the Internet. Current Opinion in Psychiatry, 28, 461–​467. Fairburn, C. G., & Patel, V. (2014). The global dissemination of psychological treatments: A road map for research and practice. American Journal of Psychiatry, 171, 495–​498. Fairburn, C. G., & Wilson, G. T. (2013). The dissemination and implementation of psychological treatments:  Problems and solutions. International Journal of Eating Disorders, 46, 516–​521. Fichter, M. M., Quadflieg, N., & Lindner, S. (2013). Internet-​ based relapse prevention for anorexia nervosa: Nine-​month follow-​up. Journal of Eating Disorders, 1, 23. Fichter, M. M., Quadflieg, N., Nisslmüller, K., Lindner, S., Osen, B., Huber, T., & Wünsch-​Leiteritz, W. (2012). Does Internet-​based prevention reduce the risk of relapse for anorexia nervosa? Behaviour Research and Therapy, 50, 180–​190. Fisher, C. B., & Fried, A. L. (2003). Internet-​mediated psychological services and the American Psychological Association ethics code. Psychotherapy: Theory, Research, Practice, Training, 40, 103–​111. Gollings, E. K., & Paxton, S. J. (2006). Comparison of Internet and face-​to-​face delivery of a group body image and disordered eating intervention for women: A pilot study. Eating Disorders, 14, 1–​15. Graff Low, K., Charanasomboon, S., Lesser, J., Reinhalter, K., Martin, R., Jones, H.,  . . .  Taylor, C. B. (2006). Effectiveness

of a computer-​based interactive eating disorders prevention program at long-​term follow-​up. Eating Disorders, 14, 17–​30. Grover, M., Naumann, U., Mohammad-​ Dar, L., Glennon, D., Ringwood, S., Eisler, I.,   .  .  .  Schmidt, U. (2011). A randomized controlled trial of an Internet-​based cognitive-​ behavioural skills package for carers of people with anorexia nervosa. Psychological Medicine, 41, 2581–​2591. Gulec, H., Moessner, M., Mezei, A., Kohls, E., Túry, F., & Bauer, S. (2011). Internet-​based maintenance treatment for patients with eating disorders. Professional Psychology:  Research and Practice, 42, 479–​486. Gulec, H., Moessner, M., Túry, F., Fiedler, P., Mezei, A., & Bauer, S. (2014). A randomized controlled trial of an Internet-​ based posttreatment care for patients with eating disorders. Telemedicine and e-​Health, 20, 916–​922. Hart, L. M., Granillo, M. T., Jorm, A. F., & Paxton, S. J. (2011). Unmet need for treatment in the eating disorders:  a systematic review of eating disorder specific treatment seeking among community cases. Clinical Psychology Review, 31, 727–​735. Hay, P. J., & Claudino, A. M. (2015). Bulimia nervosa: Online interventions. BMJ Clinical Evidence, Systematic Review, 1009. Hibbs, R., Rhind, C., Leppanen, J., & Treasure, J. (2015). Interventions for caregivers of someone with an eating disorder:  A  meta-​analysis. International Journal of Eating Disorders, 48, 349–​361. Hoek, H. W., & van Hoeken, D. (2003). Review of the prevalence and incidence of eating disorders. International Journal of Eating Disorders, 34, 383–​396. Hötzel, K., von Brachel, R., Schmidt, U., Rieger, E., Kosfelder, J., Hechler, T.,   .  .  .  Vocks, S. (2014). An Internet-​based program to enhance motivation to change in females with symptoms of an eating disorder:  A  randomized controlled trial. Psychological Medicine, 44, 1947–​1963. Internet World Stats. (2016). Retrieved from http://www. internetworldstats.com/stats.htm (June 30, 2016). Jacobi, C., Morris, L., Beckers, C., Bronisch-​Holtze, J., Winter, J., Winzelberg, A. J., & Taylor, C. B. (2005). Reduktion von Risikofaktoren für gestörtes Essverhalten:  Adaptation und erste Ergebnisse eines Internet-​ gestützten Präventionsprogramms [Reduction of risk factors for disordered eating behavior:  adaptation and initial results of an Internet-​supported prevention program]. Zeitschrift für Gesundheitspsychologie, 13, 92–​101. Jacobi, C., Morris, L., Beckers, C., Bronisch-​Holtze, J., Winter, J., Winzelberg, A. J., & Taylor, C. B. (2007). Maintenance of Internet-​based prevention: A randomized controlled trial. International Journal of Eating Disorders, 40, 114–​119. Jacobi, C., Völker, U., Trockel, M. T., & Taylor, C. B. (2012). Effects of an Internet-​based intervention for subthreshold eating disorders:  A  randomized controlled trial. Behaviour Research and Therapy, 50, 93–​99. Jones, M., Luce, K. H., Osborne, M. I., Taylor, K., Cunning, D., Doyle, A. C.,  . . .  Taylor, C. B. (2008). Randomized, controlled trial of an Internet-​facilitated intervention for reducing binge eating and overweight in adolescents. Pediatrics, 121, 453–​462. Kersting, A., Schlicht, S., & Kroker, K. (2009). Internettherapie: Möglichkeiten und Grenzen [Internet therapy: Opportunities and boundaries]. Der Nervenarzt, 80, 797–​804. Kessler, R. C., Berglund, P. A., Chiu, W. T., Deitz, A. C., Hudson, J. I., Shahly, V.,   .  .  .  Xavier, M. (2013). The

Hilbert, Opitz, de Zwann

517

prevalence and correlates of binge eating disorder in the World Health Organization World Mental Health Surveys. Biological Psychiatry, 73, 904–​914. Knaevelsrud, C., Jager, J., & Maercker, A. (2004). Internet​psychotherapie: Wirksamkeit und Besonderheiten der thera­ peutischen Beziehung. Verhaltenstherapie, 14, 174–​183. Leung, S. F., Ma, L. C., & Russell, J. (2013). An open trial of self-​help behaviours of clients with eating disorders in an online programme. Journal of Advanced Nursing, 69, 66–​76. Lindenberg, K., & Kordy, H. (2015). Wirksamkeit eines gestuften, Internetvermittelten Ansatzes zur Prävention von Essstörungen bei Schülern der 7. bis 10. Klasse [Efficacy of an Internet-​delivered tiered strategy for eating disorder prevention in high school students]. Kindheit und Entwicklung, 24, 55–​63. Ljotsson, B., Lundin, C., Mitsell, K., Carlbring, P., Ramklint, M., & Ghaderi, A. (2007). Remote treatment of bulimia nervosa and binge eating disorder:  A  randomized trial of Internet-​ assisted cognitive behavioural therapy. Behaviour Research and Therapy, 45, 649–​661. Loucas, C. E., Fairburn, C. G., Whittington, C., Pennant, M. E., Stockton, S., & Kendall, T. (2014). E-​therapy in the treatment and prevention of eating disorders:  A  systematic review and meta-​analysis. Behaviour Research and Therapy, 63, 122–​131. Mallen, M. J., Day, S. X., & Green, M. A. (2003). Online versus face-​to-​face conversation: An examination of relational and discourse variables. Psychotherapy:  Theory, Research, Practice, Training, 40, 155–​163. McClay, C. A., Waters, L., Schmidt, U., & Williams, C. (2016). A survey of attitudes towards computerized self-​help for eating disorders within a community-​based sample. Behavioural and Cognitive Psychotherapy, 44, 65–​78. Melioli, T., Bauer, S., Franko, D. L., Moessner, M., Ozer, F., Chabrol, H., & Rodgers, R. F. (2016). Reducing eating disorder symptoms and risk factors using the Internet: A meta-​ analytic review. International Journal of Eating Disorders, 49, 19–​31. Miller, W. R., & Rollnick, S. (2002). Motivational interviewing:  Preparing people for change (2nd ed.). New  York, NY: Guilford Press. Mitchell, J. E., Crosby, R. D., Wonderlich, S. A., Crow, S., Lancaster, K., Simonich, H.,  . . .  Myers, T. C. (2008). A randomized trial comparing the efficacy of cognitive-​behavioral therapy for bulimia nervosa delivered via telemedicine versus face-​to-​face. Behaviour Research and Therapy, 46, 581–​592. Moessner, M., Minarik, C., Özer, F., & Bauer, S. (2016). Can an Internet-​ based program for the prevention and early intervention in eating disorders facilitate access to conventional professional healthcare? Journal of Mental Health, 25, 441–​447. Moessner, M., Özer, F., Minarik, C., & Bauer, S. (2013). ProYouth: Ein Online-​Programm zur Prävention und frühen Intervention bei Essstörungen [ProYouth:  An online program for prevention and early intervention in eating disorders]. PiD—​Psychotherapie im Dialog, 14, 74–​76. Norris, M. L., Boydell, K. M., Pinhas, L., & Katzman, D. K. (2006). Ana and the Internet: A review of pro-​anorexia websites. International Journal of Eating Disorders, 39, 443–​447. Olmsted, M. P., Kaplan, A. S., & Rockert, W. (1994). Rate and prediction of relapse in bulimia nervosa. American Journal of Psychiatry, 151, 738–​743.

518

Internet-Based Interventions

Paxton, S. J., McLean, S. A., Gollings, E. K., Faulkner, C., & Wertheim, E. H. (2007). Comparison of face-​to-​face and Internet interventions for body image and eating problems in adult women:  An RCT. International Journal of Eating Disorders, 40, 692–​704. Prochaska, J. O., & DiClemente, C. C. (1992). Stages of change in the modification of problem behaviors. In M. Hersen, R. M. Eisler, & P. M. Miller (Eds.), Progress in behavior modification (pp. 184–​214). Sycamore, IL: Sycamore. Riper, H., Smit, F., van der Zanden, R., Conijn, B., Kramer, J., & Mutsaers, K. (2012). E-​mental health. high tech, high touch, high trust. Utrecht: Trimbos Instituut. Robinson, P. H., & Serfaty, M. A. (2001). The use of e-​mail in the identification of bulimia nervosa and its treatment. European Eating Disorders Review, 9, 182–​193. Robinson, P. H., & Serfaty, M. A. (2008). Getting better byte by byte: A pilot randomised controlled trial of email therapy for bulimia nervosa and binge eating disorder. European Eating Disorders Review, 16, 84–​93. Sánchez-​Ortiz, V. C., Munro, C., Stahl, D., House, J., Startup, H., Treasure, J.,  . . .  Schmidt, U. (2011). A randomized controlled trial of Internet-​based cognitive-​behavioural therapy for bulimia nervosa or related disorders in a student population. Psychological Medicine, 41, 407–​417. Schlegl, S., Bürger, C., Schmidt, L., Herbst, N., & Voderholzer, U. (2015). The potential of technology-​based psychological interventions for anorexia and bulimia nervosa: A systematic review and recommendations for future research. Journal of Medical Internet Research, 17, e85. Shingleton, R. M., Richards, L. K., & Thompson-​Brenner, H. (2013). Using technology within the treatment of eating disorders:  A  clinical practice review. Psychotherapy, 50, 576–​582. Stice, E., Becker, C. B., & Yokum, S. (2013). Eating disorder prevention:  Current evidence-​ base and future directions. International Journal of Eating Disorders, 46, 478–​485. Stice, E., Rohde, P., Durant, S., & Shaw, H. (2012). A preliminary trial of a prototype Internet dissonance-​based eating disorder prevention program for young women with body image concerns. Journal of Consulting and Clinical Psychology, 80, 907–​916. Suler, J. (2004). The online disinhibition effect. CyberPsychology and Behavior, 7, 321–​326. Taylor, C. B., Bryson, S., Luce, K. H., Cunning, D., Doyle, A. C., Abascal, L. B.,  . . .  Wilfley, D. E. (2006). Prevention of eating disorders in at-​risk college-​age women. Archives of General Psychiatry, 63, 881–​888. ter Huurne, E. D., de Haan, H. A., ten Napel-​Schutz, M. C., Postel, M. G., Menting, J., van der Palen, J.,  . . .  DeJong, C. A. (2015). Is the Eating Disorder Questionnaire-​Online (EDQ-​O) a valid diagnostic instrument for the DSM-​IV-​TR classification of eating disorders? Comprehensive Psychiatry, 57, 167–​176. Treasure, J., Macare, C., Mentxaka, I. O., & Harrison, A. (2010). The use of a vodcast to support eating and reduce anxiety in people with eating disorder:  A  case series. European Eating Disorders Review, 18, 515–​521. Wagner, B., Nagl, M., Dölemeyer, R., Klinitzke, G., Steinig, J., Hilbert, A., & Kersting, A. (2016). Randomized controlled trial of an Internet-​ based cognitive-​ behavioral treatment program for binge-​ eating disorder. Behavior Therapy, 47, 500–​514.

Wagner, G., Penelo, E., Wanner, C., Gwinner, P., Trofaier, M.-​L., Imgart, H.,  . . .  Karwautz, A. F. (2013). Internet-​delivered cognitive-​behavioural therapy vs. conventional guided self-​ help for bulimia nervosa:  Long-​term evaluation of a randomised controlled trial. British Journal of Psychiatry, 202, 135–​141. Williams, C. J., Aubin, S. D., Cottrell, D., & Harkin, P. J. (1998). Overcoming bulimia:  A  self-​ help package. Leeds, UK: University of Leeds Press. Winzelberg, A. J., Eppstein, D., Eldredge, K. L., Wilfley, D., Dasmahapatra, R., Taylor, C. B., & Dev, P., (2000). Effectiveness of an Internet-​based program for reducing risk factors for eating disorders. Journal of Consulting and Clinical Psychology, 68, 346–​350.

Yager, J. (2001). E-​mail as a therapeutic adjunct in the outpatient treatment of anorexia nervosa: Illustrative case material and discussion of the issues. International Journal of Eating Disorders, 29, 125–​138. Yager, J. (2003). E-​mail therapy for anorexia nervosa: Prospects and limitations. European Eating Disorders Review, 11, 198–​209. Zabinski, M. F., Pung, M. A., Wilfley, D. E., Eppstein, D. L., Winzelberg, A. J., Celio, A., & Taylor, C. B. (2001). Reducing risk factors for eating disorders: Targeting at-​risk women with a computerized psychoeducational program. International Journal of Eating Disorders, 29, 401–​408.

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C H A PT E R

Afterword

28

W. Stewart Agras and Athena Robinson

Abstract This chapter reflects on core themes raised within this Handbook, which collectively reflect the state of the science in the eating disorder field. Such themes include the growing recognition of the complexity of eating disorders including their etiological underpinnings and the contributions of basic sciences to an understanding of processes underlying the expression of maladaptive eating patterns. The status of the prevention and treatment of these disorders as reflected in the literature to date is considered with questions raised about future progress. Looking toward the future, new technologies may offer opportunities to bring cost-​effective evidence-​based treatments to underserved populations. However, such opportunities bring with them new ethical and practical considerations. Also highlighted are potential areas for further research. Key Words:  genetics, pharmacogenetics, prevention, research, treatment, implementation, technology, etiology, risk factor, mechanism

Introduction

An overview of the eating disorders as illustrated in this Handbook leads to a consideration of several questions. Among these questions are: 1.  What is the influence of the complexity of the eating disorders on the understanding of their etiology? 2.  Will new basic science findings lead to useful change in treatment or prevention? 3.  Have the obtained treatment effects reached a plateau? 4.  What is the likely impact of technology on the assessment and treatment of the eating disorders? 5.   Can evidence-​ based treatments be implemented more widely?

Complexity of the Eating Disorders

The range of topics covered in this Handbook make it abundantly clear that disorders of eating, like many other psychiatric and medical disorders, are complex and difficult to sort into diagnostic categories defying singular etiologic explanations (Cohen, 520

2016). A variety of factors influence the etiology and maintenance of eating disorders. These include culture, race, family behaviors specific to the individual, overweight, body image concerns, dietary restriction, negative affect, perfectionism, neurochemical abnormalities, and genetic influences. It is likely that many of these influences interact with one another at different developmental periods. Although the search for mechanisms underlying the disorders of eating and those accounting for treatment outcomes will accelerate in the next few years spurred by RDoC, it is possible that the mechanisms will prove to be as complex as the disorders themselves. If an unlikely single solution to etiology is at one end of the spectrum, at the other is the possibility that every case has a unique etiology. If the truth lies somewhere in between, the search for mechanism may provide better guidance to clinicians than the existing diagnostic system.

The Contributions of Basic Science

At this point it is fair to say that psychology as a basic science has made major contributions to

the development of effective psychotherapies and assessments for the eating disorders as have the pharmacological sciences although no new specific medication has yet been developed for the treatment of any eating disorder. The contributions of other basic endeavors, while generating important information, have not yet impacted the prevention or treatment of the eating disorders. Genetic research is a fundamental area of endeavor, genetic findings that act as markers for disordered eating or point to biological mechanisms involved in the eating disorders may lead to more precisely targeted prevention or treatments. To enhance genetic studies, improved delineation of the eating disorder syndromes may be necessary. This in turn requires improved assessment and classification of the eating disorders in order to deal with the heterogeneity within the existing syndromes and the overlap between them. Moreover, it is unclear at present whether genetic research should concentrate on already defined syndromes, or on subsyndromes as defined in some classification studies, or on eating behaviors such as binge eating, purging, dieting, and loss of control over eating. Characterization of potential phenotypes may be helpful in furthering genetic research (Lopez, Tchanturia, & Treasure, 2009). One potential phenotype involves anorexia nervosa characterized by the symptom complex of anxiety, depression, and obsessive-​ compulsive behaviors. For example, obsessive-​compulsive eating behaviors have been found to moderate treatment outcome in adolescents with anorexia nervosa (AN) in several studies. Patients with obsessive-​compulsive eating behaviors have poorer treatment outcomes and may need more and longer treatment than those without such behaviors. The second involves the cognitive processes underlying the rigid thinking found in many individuals with AN. To date, progress in this area has been slow with no genetic findings relevant to biologic mechanisms or to prevention or treatment of the eating disorders. Larger studies may be helpful in identifying candidate genes together with a greater emphasis on understanding of the genetics of bulimia nervosa and binge eating disorder. Understanding the brain in terms of neural pathways and function together with neurochemistry is also beginning to contribute important information concerning the eating disorders. One focus is on reward-​processing mechanisms in the brain that appear to be disturbed in individuals with an eating disorder, who tend to show greater reactivity to food images and to anticipation of taste. The relation of these disturbances to neurochemical pathways may lead to more refined treatment.

The characterization of environmental variables that either cause or maintain the eating disorders has shown progress in identifying risk factors, and to a lesser extent, causal risk factors. The identification of modifiable, causal risk factors has led to the formulation of effective prevention studies. Prospective studies large enough to investigate the contribution of a number of hypothesized risk factors combined with laboratory studies or clinical trials modifying a risk factor in order to identify causal risk factors are needed. The interaction between causal risk factors and specific genes at particular developmental stages may eventually be a useful research area to pursue. For example, one study showed that as weight-​related peer teasing, a risk factor for the development of eating disorders, increased, both genetic and environmental factors influencing disordered eating also increased (Fairweather-​Schmidt & Wade, 2016).

Has Treatment Development Reached a Plateau?

The development of evidence-​based treatments is a time-​consuming process leading from case series to multisite controlled trials. Because clinical trials are expensive, many questions have not been answered. Hence, progress in treatment development is often slow. Treatment development for AN, particularly persistent AN, has been disappointing for decades. At this point there are still no effective evidence-​based treatments for these patients. Most controlled studies to date are inconclusive, show relatively poor results, or are no better than specialist management (Hay et al., 2014). However, in an important development over the past 25 years, a specific family therapy for adolescents, in which parents take temporary control of their adolescent’s feeding, can now be regarded as evidence-​ based (Jewell, Blessit, Stewart, Simic, & Eisler, 2016). Early treatment of AN promises to lower the number of persistent cases, hence further research to refine this treatment is needed. No pharmacological agent has been adequately tested in adolescents with AN, and there is no effective evidence-​based medication for adults (Miniati et al., 2016). Treatment research in bulimia nervosa (BN) is more advanced, with cognitive-​behavioral therapy (CBT) as the first-​line treatment with evidence for both short-​and long-​term effects. However, long-​ term follow-​up recovery rates with CBT of about 25% to 40% are lower than desirable. Other treatments such as interpersonal psychotherapy (IPT) fare no better, and IPT is less effective than CBT Agras, Robinson

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at end-​ of-​ treatment and perhaps at follow-​ up (Fairburn et  al., 2015). This relatively low rate of recovery needs to be enhanced, but so far no treatment has been found superior to enhanced CBT (CBT-​E), nor has the effectiveness of CBT much improved over the past 5  years, although CBT-​E improves treatment outcome in more severe cases. This is an area requiring more intensive treatment development with a better understanding of treatment mechanism, moderators, and mediators. Moreover, theory-​based methods to enhance outcome are urgently needed. Pharmacological treatment for BN has been extensively explored, and efficacy has been demonstrated for most antidepressants, although only fluoxetine is approved by the Federal Drug Administration (FDA) for the treatment of BN. Few medication studies have long-​term follow-​up, hence evidence-​based guidance for long-​term treatment is, for the most part, lacking. In the treatment of binge eating disorder (BED), IPT is equivalent to CBT at both end of treatment and follow-​up, and a larger proportion of patients are remitted than is the case with BN. Again, however, more treatment research is needed to enhance follow-​up remission rates of 50% to 60%. Moreover, neither IPT nor CBT lead to much weight loss in this largely overweight population. Antiepileptic drugs such as topiramate appear promising in reducing both binge eating and weight although dropout rates from side effects are high. Further trials of these medications in combination with CBT or IPT are warranted. Urgently needed are newer medications that may affect both binge eating and weight. One such medication, lisdexamphetamine, which has been approved by the FDA for the treatment of BED, appears promising in short-​term studies and recently in a longer-​term study (Hudson, McElroy, Ferreira-​ Cornwell, Radewonuk, & Gasior, 2017). With the new focus on the RDoC matrix rather than on clinical diagnosis there is some concern that interest in, and funding for, treatment studies may be reduced to the detriment of patient care. There are two potential aims for further treatment research. The first is to understand the mechanisms by which treatments for eating disorders work so that effectiveness can be enhanced. The second is to have a better understanding of the reasons for poor improvement with treatment and with this knowledge to enhance treatment or devise new treatment procedures. 522

Afterword

Dissemination/​Implementation

Once effective treatments have been identified it is necessary to disseminate these therapies to community settings such as HMOs, community clinics, college campuses, community practitioners, and so forth. Although largely based on therapist report, studies show that evidence-​based treatments for eating disorders are not widely used in community practice (Wolitzky-​Taylor, Zimmerman, Arch, De Guzman, & Lagomasino 2015). It is evidently necessary to address this problem with the aim of providing more effective treatment for more people. Findings from basic implementation science studies are beginning to identify the many variables that influence dissemination and implementation. However, CBT, IPT, and other treatments developed for specialty centers need to be adapted to the realities of community clinical settings and tested in those settings in controlled trials to ensure that they are superior to treatment as usual, that is, treatment delivered in the specific community context. Very few studies of this sort have appeared, so that the effectiveness and limitations of such adapted treatments are unknown. For example, many clinical settings cannot afford treatments extending over 6  months with 18 or more sessions, hence shortened variants of evidence-​based treatments are needed. This suggests that dosage studies of evidence-​ based treatments may provide useful information for implementation. Another route is to develop shortened versions of treatment that include the primary ingredients of the original treatment. One such treatment, guided self-​help based on CBT, has been found effective even when provided by masters level therapists with shorter and fewer sessions. Controlled studies comparing community clinics’ usual treatment with the shortened evidence-​based therapy are needed before implementing such treatment. This is an important missing link in treatment research. In order to have therapists in different settings adopt and use evidence-​ based treatments effectively it will be important to understand which training method will be best in what circumstance. Controlled studies in this area are sorely needed. Moreover, an understanding of the many organizational factors that impinge on the use of evidence-​ based therapies and how to incentivize adoption within particular organizations are also important research areas.

Technologies and Dissemination

The miniaturization of computers has led to the development of mobile devices, such as telephones

and tablets, potentially allowing treatment monitoring or even treatment via the Internet or electronic applications (apps). This is a novel development over the last few years, and several controlled studies are now available. In a recent review (Agras, Fitzsimmons-​Craft, & Wilfley, 2017) of technology-​ based assessment and treatment, the authors concluded, “there is not a strong enough evidence-​base to support widespread usage of Internet treatments for eating disorders in the clinic. These studies suggest that internet-​based treatment is likely to be effective and that studies comparing this treatment to face-​to-​face treatment are now needed.” It should be noted that most variants of Internet-​based treatment do not use the medium to individualize treatment; hence more sophisticated programming is needed. Moreover some aspects of e-​ treatment raise ethical concerns. For example, Internet-​based assessment and treatment without a therapist may not identify important safety concerns such as low weight, suicidal ideation, vital instability, and electrolyte abnormality, or identify newly emerging psychopathology during treatment. Moreover, it is questionable whether a patient whose identity is unknown should be engaged in treatment. In the United States, state licensing regulations vary concerning treatment by out-​ of-​ state providers. In the case of an app, who is the treatment agent? Presumably the company selling the application. However, there does not appear to be adequate regulation at the federal level to ensure that such apps are effective and without harm. These developments still in their infancy may become another way to provide evidence-​ based treatments to the large number of underserved individuals who at present have no access to treatment. The use of mobile apps to provide feedback on therapeutic progress to patients and therapists is an important new development. There are many such apps available at this point in time although none relevant to eating disorders have been rigorously evaluated, hence the effectiveness of providing feedback in this manner is unknown. Other technologies such as virtual reality are even less developed at this time. However, these devices can be used whenever exposure to avoided scenarios is needed in an assessment or treatment context. For example, exposure to a variety of avoided foods or to body image experiences. Virtual reality may also be useful in the assessment of eating disorders for research purposes, for example by actualizing binge triggers.

Clearly this is a very promising area as the technology becomes more easily usable and less expensive. Basic and applied research into the eating disorders is thriving although the difficult task of understanding etiology from risk factor to neurobiology is in its infancy. Translational research is now very much needed, for example, translating the latest findings from psychological research to treatments, or the effects of treatment on brain mechanisms, or using advanced technology to enhance assessment and treatment. This either requires two skill-​sets in one head or research groups that encompass the needed skills. The results of such efforts may throw light on what we do not presently know.

References

Agras, W. S., Fitzsimmons-​Craft, E. E., & Wilfley, D. E. (2017). Evolution of cognitive-​behavioral therapy for eating disorders. Behaviour Reearch & Therapy, 88, 26–​36. Cohen, B. M. (2016). Embracing complexity in psychiatric diagnosis, treatment, and research. JAMA Psychiatry, 73, 1211–​1212. Fairburn, C. G., Bailey-​Straebler, S., Basden, S., Doll, H. A., Jones, R., Murphy, R.,  . . .  Cooper, Z. (2015). A transdiagnostic comparison of enhanced cognitive behavior therapy (CBT-​E) and interpersonal psychotherapy in the treatment of eating disorders. Behaviour Research & Therapy, 70, 64–​71. Fairweather-​Schmidt, A. K., & Wade, T. D. (2016). Weight related peer-​teasing moderates genetic and environmental risk and disordered eating:  Twin study. British Journal of Psychiatry. bjp.bp.116.184648 Hay, P., Chinn, D., Forbes, D., Madden, S., Newton, R., Sugenor, L.,  . . .  Royal Australian and New Zealand College of Psychiatrists. (2014). Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for the treatment of eating disorders. Australian & New Zealand Psychiatry, 48, 977–​1008. Hudson, J. I., McElroy, S. L., Ferreira-​ Cornwell, M. C., Radewonuk, J., & Gasior, M. (2017). Efficacy of Lisdexamfetamine in adults with moderate to severe binge-​ eating disorder: A randomized clinical trial. JAMA Psychiatry, July 12. doi: 10.1001/​jamapsychiatry.2017.1889 Jewell, T., Blessit, E., Stewart, C., Simic, M., & Eisler, I. (2016). Family therapy for child and adolescent eating disorders: A critical review. Family Process, 55, 577–​594. Lopez, C., Tchanturia, K., & Treasure, J. (2009). Weak central coherence in eating disorders: A step toward looking for an endophenotype of eating disorders. Clinical Experimental Neuropsychology, 1, 117–​125. Epub. Miniati, M., Mauri, M., Ciberti, A., Mariani, M. G., Marazziti, D., & Dell’Osso, L. (2016). Psychopharmacological options for adult patients with anorexia nervosa. CNS Spectrum, 21, 134–​142. Wolitzky-​Taylor, K., Zimmerman, M., Arch, J. J., De Guzman, E., & Lagomasino, I. (2015). Has evidence-​based psychosocial treatment for anxiety disorders permeated usual care in community mental health settings? Behaviour Research & Therapy, 72, 9–​17.

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523

INDEX

Page numbers followed by f, t indicate a figure or table on the associated page.

A

absolute dietary restriction relative dietary restriction vs., 136 abstinence dialectical in BED and BN management, 343 abuse laxative BN and, 226 in PD, 446 ACC. see anterior cingulate cortex (ACC) N-​acetylcysteine (NAC) for BN, 375 acid reflux BN and, 225 “activity disorder” AN as, 192–​193 ADHD. see attention deficit hyperactivity disorder (ADHD) adolescent(s) early ED–​related diagnostic criteria for, 19–​20 EDs in CRT for, 399–​400 family therapy for, 320–​321 IPT for adaptations of, 311 adolescent anorexia nervosa (AN) family therapy for, 321–​322 (see also family therapy for adolescent AN (FBT-​AN)) adolescent bulimia nervosa (BN) FBT for, 324–​327 (see also family therapy for adolescent BN (FBT-​BN)) adolescent-​focused therapy (AFT) FBT vs., 323 adolescent girls body dissatisfaction among, 480 adult(s) EDs in family therapy for, 329–​330 AEDs. see antiepileptic drugs (AEDs) affect(s) defined, 156 IPT in encouraging acceptance of, 298 painful affect, 298 IPT in helping patient experience suppressed affect, 298 negative (see negative affect)

affect dysregulation model within biosocial theory, 335 affective disorders EDs and, 164, 229–​230 “affect reduction” model, 162–​163 affect regulation as factor in EDs, 238–​239 affect regulation model for EDs, 340 African Americans body image and eating concerns among, 197 AFT. see adolescent-​focused therapy (AFT) agomelatine for NES, 382 AI. see artificial intelligence (AI) alcohol abuse/​dependence disorder anxiety disorders related to, 233 EDs and, 233–​234 OCD related to, 233 alcoholism EDs and, 233–​234 alexithymia described, 176 EDs and, 176 allele(s) described, 80 allocentric lock (AL) theory of body image distortion, 481, 481f alprazolam for AN, 361t, 368 altered feeding behaviors in AN and BN studies of, 48–​49, 49t alternate rebellion in BED and BN management, 343 AL theory. see allocentric lock (AL) theory American Psychiatric Association, 499 American Psychological Association, 506 American Psychologist, 198 amitriptyline for AN, 360, 361t amygdala OFC and, 60 AN. see anorexia nervosa (AN) angry threat stimuli attentional biases to, 240 Annals of Physical and Rehabilitation Medicine, 483 anorexia nervosa (AN). see also eating disorder(s) (EDs)

as “activity disorder,” 192–​193 adolescent family therapy for, 321–​322 (see also family therapy for adolescent AN (FBT-​AN)) in adults family therapy for, 329–​330 after bariatric surgery, 461–​462 altered feeding behaviors related to studies of, 48–​49, 49t anxiety and harm avoidance with PET data correlated with, 57–​58 appetitive regulation in, 47–​79 CCK and, 51, 54t fMRI studies of, 61–​66, 62f, 65f future research directions related to, 66–​67 gender differences in, 61 ghrelin and, 52–​53, 55t HPA axis effects on, 50 images of food in, 62 interoceptive processing in, 59–​60 introduction, 47 leptin and, 51–​52, 54t–​55t neurocircuitry of, 58–​60 neuroendocrine systems–​related, 50–​53 NPY and, 51, 54t opioid peptides and, 50–​51, 54t PET studies of, 61–​62 PYY and, 51, 54t regional cerebral blood flow studies in, 61–​62 SPECT studies of, 61–​62 tastes of food in, 62–​63, 62f twin studies, 48 atypical (see atypical anorexia nervosa (atypical AN)) binge eating/​purging type of, 10 binging in negative affect lability and, 239 brain imaging studies in, 58–​66 CBT-​E for, 278–​280 CBT for, 278–​280 efficacy of, 278–​279 costs of, 412 course of, 36–​37 cross-​cultural patterns of, 35–​36 CRT for RCTs of, 397 defined, 461

525

anorexia nervosa (AN) (cont.) described, 2, 173–​174 diagnosis of, 10 discovery of, 34 early sensory specific satiety in, 60 epidemiology of, 34–​35 features of, 461 genetic influences on, 48, 80–​105 (see also genetic influences) history of, 2 hunger and satiety in fMRI studies of, 63 incidence of, 35 interoception in fMRI studies of, 63–​64 IPT for, 303–​304 in Jamaica, 200 medical complications of, 222–​225 bone metabolism–​related, 224–​225 cardiac, 222–​223 dermatologic, 225 endocrine, 224 gastrointestinal, 223–​224 hematologic, 224 malnutrition, 223 neurologic, 224 pulmonary, 223 monoamine function disturbances related to, 53, 55–​58 DA activity in, 53, 55 serotonin, 55–​58 mortality rate associated with, 222–​223 negative emotionality and, 173–​177 emotional processing deficits, 176–​177 emotional responses to body image exposure, 175–​176 emotional responses to food cues, 174–​175 neurobiologic alterations in, 47–​48 neuropeptide and neuroendocrine alterations in, 49–​53, 54t–​55t parents’ role in, 319 perfectionism and, 236–​238 persistence and, 237 prevalence of, 263 psychological comorbidity of, 229–​243, 231t–​233t affective disorders, 229–​230 anxiety disorders, 230 ICDs, 234–​235 personality disorders, 235–​236 substance abuse disorders, 230, 233–​234 research on future directions for, 66–​67 response to inhibition alterations in fMRI studies of, 65–​66 response to reward alterations in fMRI studies of, 64–​65, 65f restricting type of, 10 risk factors for, 3

526

Index

longitudinal studies’ characteristics, 107, 111, 112, 117 social media in, 262–​263 state vs. trait characteristics in, 47–​48 subsystems in, 47 subtypes of, 10 suicide attempts related to, 36 suicide related to, 36 trait anxiety and, 237 treatment of, 3–​4, 360–​368, 361t (see also specific types) AEDs in, 368 antidepressant–​antipsychotic combinations in, 364–​365 antidepressants in, 360–​362, 361t antipsychotics in, 361t, 363–​364 anxiolytic medications in, 368 appetite stimulants in, 361t, 365 cannabinoids in, 361t, 365 CBT in, 278–​280 cost-​effectiveness of, 412–​413 CRT in, 397 ghrelin agonists in, 361t, 367 hormonal agents in, 361t, 366–​367 lithium in, 361t, 367 nutritional supplements in, 368 opioid antagonists in, 368 opioids in, 368 pharmacotherapy in, 360–​368, 361t (see also specific agents) prokinetics in, 361t, 365–​366 research on, 521 zinc in, 361t, 366 anterior cingulate cortex (ACC), 56–​57, 59 anterior insula, 59 antidepressant(s) for BED, 376t, 377–​378 for BN, 369–​372, 370t antidepressant–​antipsychotic combinations for AN, 364–​365 antiepileptic drugs (AEDs) for AN, 368 for BED, 376t, 379–​381 for BN, 370t, 372–​373 anti-​ideal(s) ideals vs., 194 antipsychotic(s) for AN, 361t, 363–​364 for BED, 382 for BN, 375 anxiety AN and PET data correlated with, 57–​58 trait-​related, 237 BN and PET data correlated with, 57–​58 EDs and, 164 anxiety disorders alcohol abuse/​dependence disorder and, 233 EDs and, 230 anxiolytic medications

for AN, 368 apoptosis AN and, 223 appetite-​focus DBT, 339 appetite stimulants for AN, 361t, 365 appetitive regulation in AN and BN, 47–​79 (see also anorexia nervosa (AN); bulimia nervosa (BN)) Apple Watch, 494 apps. see mobile devices and applications (apps) ARFID. see avoidant/​restrictive food intake disorder (ARFID) aripiprazole for BN, 375 arousal systems EDs and, 29 artificial cervical vagal nerve stimulation (VNS) in depression management, 158 artificial intelligence (AI), 493 values embedded in, 499 assessment(s) described, 211 ecological momentary of negative affect, 238–​239 of EDs, 209–​221 context of, 211–​212 determining domains or constructs of interest in, 213–​215 diagnosis in, 213 EDE in, 216 ESP in, 217 function of, 212–​213 instruments in, 215–​218 interviews in, 215–​217 introduction, 211 psychological, 211–​221 SCOFF in, 212–​213, 216–​217 screening tests in, 212–​213 secondary domains in, 214 self-​report questionnaires in, 217–​218 (see also self-​report questionnaires) thresholds for recovery in, 214–​215 treatment planning and outcome in, 213 underlying theoretical assumptions in, 213–​214 introduction, 211 as process, 211–​221 assumption(s) underlying in EDs assessment, 213–​214 athletes ED prevention in, 260–​261 atomoxetine for BED, 376–​377, 376t attention sustained norepinephrine in, 240 attentional bias(es)

to social and angry threat stimuli and emotion recognition, 240 attention deficit hyperactivity disorder (ADHD) ARFID and, 431 drugs for in BED, 375–​377, 376t in BN, 374 attitude(s) eating negative affect impact on, 161–​164 atypical AN. see atypical anorexia nervosa (atypical AN) atypical anorexia nervosa (atypical AN), 438, 448–​451 criteria for, 448–​449 defined, 448 described, 448–​449 history of, 448–​449 models of evidence of diagnostic validity and clinical significance using, 449–​450 prevalence of, 449 status of research needed to clarify, 451 avoidant/​restrictive food intake disorder (ARFID) ADHD with, 431 ON vs., 453

B

baclofen for BED, 381–​382 for BN, 375 bariatric surgery(ies) AN after, 461–​462 BED after, 459–​460 BN after, 460–​461 EBs–​and EDs–​related, 458–​469 food addiction after, 465–​466 GI physiology alterations after, 459 introduction, 458–​459 LOC overeating after, 460 NES after, 462 NSRED after, 462 postoperative sequelae, 459 problematic EBs after, 462–​464 types of, 458 bariatric surgery patients EBs and EDs in, 458–​469 (see also eating behavior(s) (EBs); eating disorder(s) (EDs); specific disorders and bariatric surgery(ies)) AN, 461–​462 BED, 459–​460 BN, 460–​461 introduction, 458–​459 NES, 462 NSRED, 462 problematic EBs, 462–​464 food addiction in, 465–​466 postoperative GI problems in, 464–​465

Barrett’s esophagus BN and, 225 BDS. see Buss-​Durkee Scale (BDS) Beck Depression Inventory, 328 Beck Depression Inventory scores, 442–​443 BED. see binge eating disorder (BED) Before I Eat, 496 behavior(s) altered feeding in AN and BN, 48–​49, 49t binge–​purge harm avoidance scores in women with, 237 BPD–​related, 334–​335 dietary, 136–​137 eating after bariatric surgery, 458–​469 impact on body image and eating concerns, 191–​193 purging BN and, 225–​226 SE–​related, 425–​427 behavioral disturbances genetic influences on, 81 behavioral family systems therapy (BFST), 322 Behavioral Inventory of Executive Function (BRIEF), 399–​400 behavioral response shifting, 239 behavioral weight loss treatment (BWLT) for BED, 378 CBT vs., 276 belief(s) religious impact on body image and eating concerns, 191–​192 Belize body image in, 201 as one of “fattest nations,” 201 BFST. see behavioral family systems therapy (BFST) bias(es) attentional to social and angry threat stimuli and emotion recognition, 240 in self-​report in paper-​and-​pencil vs. mobile assessments, 498 binding potential defined, 68 binge eating negative affect and BED and, 171–​173 BN and, 167–​169 treatment research on, 522 binge eating disorder (BED), 438 after bariatric surgery, 459–​460 DSM-​5 on, 459 prevalence of, 459–​460 boundary problems related to, 2 CBT for, 276–​278, 302 efficacy of, 276 GSH in, 277

predictors and moderators of, 277–​278 vs. behavioral weight loss treatment, 276 vs. group behavioral weight-​loss interventions, 130 vs. pharmacotherapy, 276 course of, 39 cross-​cultural patterns of, 39 defined, 459 described, 169 diagnosis of, 10 discovery of, 38 DRD2 in, 160–​161 DSM on, 2 epidemiology of, 38–​39 incidence of, 38–​39 IPT for, 301–​303 future directions in, 310–​311 negative emotionality and, 169–​173 emotional responses to body image exposure, 170–​171 emotional responses to food cues, 169–​170 negative affect and binge eating, 171–​173 OBE episodes in, 459–​460 OSFED related to, 39 overweight people with group behavioral weight loss interventions vs. CBT for, 130 personal history timeline of patient with example of, 292t–​293t prevalence of, 38 psychological comorbidity of, 229–​243, 231t–​233t affective disorders, 229–​230 anxiety disorders, 230 ICDs, 234–​235 personality disorders, 235–​236 substance abuse disorders, 230, 233–​234 risk factors for, 3 longitudinal studies’ characteristics, 111, 118–​119 suicide attempts related to, 39 suicide related to, 39 treatment of, 4 ADHD–​related drugs in, 375–​377, 376t AEDs in, 376t, 379–​381 antidepressants in, 376t, 377–​378 antipsychotics in, 382 baclofen in, 381–​382 chromium in, 382 LDX in, 375–​377, 376t opioid antagonists in, 381 pharmacotherapy in, 375–​382, 376t (see also specific agents) weight-​loss drugs in, 376t, 378–​379 weight loss dieting interventions among persons with, 130

Index

527

binge–​purge behaviors harm avoidance scores in women with, 237 binging negative affect effects on, 238–​239 biomedicine global proliferation of impact on body image and eating concerns, 201–​202 biosocial theory affect dysregulation model within, 335 of DBT, 334 EDs–​related, 337–​338 for EDs adaptations of, 340–​341 bisexual men body image dissatisfaction among, 194 BIVRS (Body Image Virtual Reality Scale), 480 blood oxygen level dependent signal defined, 67–​68 BMI. see body mass index (BMI) BN. see bulimia nervosa (BN) body communal socialization of impact on body image and eating concerns, 191 body image in Belize, 201 in China, 201 cultural influences on, 187–​208 (see also culture, impact on body image and eating concerns) EDs related to VR in, 478–​484, 481f (see also body image disturbances, VR in) in Nepal, 200 in United Arab Emirates, 201 body image dissatisfaction among adolescent girls, 480 among bisexual men, 194 among gay men, 194 body image distortion AL theory of, 481, 481f body image disturbances VR in, 478–​484, 481f assessment-​related, 480 studies-​related, 479–​480 treatment-​related, 480–​484, 481f body image exposure emotional responses to AN and, 175–​176 BED and, 170–​171 BN and, 166–​167 Body Image Virtual Reality Scale (BIVRS), 480 body mass index (BMI) defined, 68 genetics of, 83 legislated minimum for models, 193 Body Project, 255–​256 Bollywood

528

Index

Hollywood vs., 200–​201 bone marrow loss AN and, 224 bone metabolism AN effects on, 224–​225 borderline personality disorder (BPD) behaviors associated with, 334–​335 DBT with, 334 efficacy of, 336–​337 described, 334–​335 EDs and, 235 BPD. see borderline personality disorder (BPD) brain starvation and emaciation effects on, 47–​48 brain imaging studies in AN and BN, 58–​66 of normal feeding behavior in healthy individuals, 60–​61 brain injury(ies) CRT for, 396 BRIEF. see Behavioral Inventory of Executive Function (BRIEF) bulimia nervosa (BN). see also eating disorder(s) (EDs) adolescent FBT for, 324–​327 in adults family therapy for, 330 after bariatric surgery, 460–​461 altered feeding behaviors related to studies of, 48–​49, 49t anxiety and harm avoidance with PET data correlated with, 57–​58 appetitive regulation in, 47–​79 CCK and, 51, 54t fMRI studies of, 61–​66, 62f, 65f future research directions related to, 66–​67 gender differences in, 61 ghrelin and, 52–​53, 55t HPA axis effects on, 50 images of food in, 62 interoceptive processing in, 59–​60 introduction, 47 leptin and, 51–​52, 54t–​55t neurocircuitry of, 58–​60 neuroendocrine systems–​related, 50–​53 NPY and, 51, 54t opioid peptides and, 50–​51, 54t PET studies of, 61–​62 PYY and, 51, 54t regional cerebral blood flow studies in, 61–​62 SPECT studies of, 61–​62 tastes of food in, 62–​63, 62f twin studies, 48 binging in negative affect lability and, 239 brain imaging studies in, 58–​66 CBT for, 271–​276

CBT-​E, 272–​276 comparative treatment research, 273–​274 efficacy of, 272–​274 generalizability of treatment effects from controlled research to routine clinical care settings, 274 GSH in, 275–​276 physical exercise with, 130 predictors and moderators of, 275 RCTs of, 274 treatment model, 271–​272 costs of, 412 course of, 38 cross-​cultural patterns of, 37–​38 defined, 460 delayed medial OFC activation reduction in, 60 described, 2, 165–​166 diagnosis of, 10 discovery of, 37 DSM on, 2 epidemiology of, 37 genetic influences on, 48, 80–​105 (see also genetic influences) history of, 2 hunger and satiety in fMRI studies of, 63 incidence of, 37 interoception in fMRI studies of, 63–​64 IPT for, 300–​301 future directions in, 310–​311 in Jamaica, 200 LOC overeating after, 460 medical complications of, 225–​226 laxative abuse, 226 self-​induced vomiting, 225–​226 monoamine function disturbances related to, 53, 55–​58 DA activity, 53, 55 serotonin, 55–​58 mortality rate associated with, 225 National Comorbidity Survey–​ Replication Adolescent Supplement on, 37 negative emotionality and, 165–​169 emotional responses to body image exposure, 166–​167 emotional responses to food cues, 166 negative affect and binge eating, 167–​169 neurobiologic alterations in, 47–​48 neuropeptide and neuroendocrine alterations in, 49–​53, 54t–​55t novelty-​seeking scores and, 237 OBE episodes in, 460–​461 prevalence of, 37 psychological comorbidity of, 229–​243, 231t–​233t affective disorders, 229–​230 anxiety disorders, 230 ICDs, 234–​235

personality disorders, 235–​236 substance abuse disorders, 230, 233–​234 purging behavior in, 225–​226 research on future directions for, 66–​67 response to inhibition alterations in fMRI studies of, 65–​66 response to reward alterations in fMRI studies of, 64–​65, 65f risk factors for, 3 dietary behaviors as, 136–​137 longitudinal studies’ characteristics, 111, 117–​118 social media in, 262–​263 state vs. trait characteristics in, 47–​48 subsystems in, 47 suicide attempts related to, 38 suicide related to, 38 treatment of, 4 ADHD–​related management in, 374 AEDs in, 370t, 372–​373 antidepressants in, 369–​372, 370t antipsychotics in, 375 5-​HT3 receptor antagonists in, 370t, 373 hormonal agents in, 370t, 373 lithium in, 370t, 374 opioid antagonists in, 370t, 373–​374 pharmacotherapy in, 368–​375, 370t (see also specific agents) prokinetic agents in, 375 research on, 2, 521–​522 weight-​loss drugs in, 370t, 374 vagal nerve activity in depression related to, 158–​159 weight loss dieting interventions among persons with, 130 bupropion for BED, 379 burning bridges in BED and BN management, 343 Buss-​Durkee Scale (BDS), 363 BWLT. see behavioral weight loss treatment (BWLT)

C

caloric deprivation effects on caloric intake animal studies of, 131 caloric intake caloric deprivation effects on animal studies of, 131 longer-​term DLW in assessment of, 135 caloric restriction short-​term relationship to laboratory-​based eating, 128–​129 Campaign for Real Beauty, 262 cannabinoids for AN, 361t, 365 carbamazepine

for BN, 370t, 372–​373 carbonyl-​[ 11C]WAY100635 defined, 68 career support Internet-​based interventions for EDs related to, 512–​513 cataloging cross-​cultural to global systems and regional trends, 199–​202 “cathartic colon” syndrome, 226 Caucasians body image and eating concerns among, 197 CBT. see cognitive-​behavioral therapy (CBT) CBT-​E. see enhanced CBT (CBT-​E) CBT-​Eb. see enhanced CBT (CBT-​E), broad (CBT-​Eb) CBT-​Ef. see enhanced CBT (CBT-​E), focused (CBT-​Ef ) CCK. see cholecystokinin (CCK) CD programs. see cognitive dissonance (CD) programs Center for Epidemiological Studies Depression Scale, 163–​164 Center for Medicare Services, 413 central coherence, 396 of CRT for EDs, 403t, 405–​406 defined, 239–​240 examples of, 403t weak defined, 239–​240 central nervous system (CNS) AN effects on, 224 cerebral blood flow regional in appetitive regulation in AN and BN, 61–​62 defined, 68 CET. see cue exposure therapy (CET) CFT. see conjoint family therapy (CFT) cheerleaders ED prevention in, 260 chewing after bariatric surgery, 464 Chicago/​Stanford adolescent-​focused therapy vs. FBT study, 323 Child Eating Behaviour Questionnaire, 420 Child Guidance Center, 319 childhood overanxious disorder of EDs and, 230 children EDs in CRT for, 399–​400 diagnostic criteria for, 19–​20 IPT for adaptations of, 311 marketing of toys and clothing for impact on body image and eating concerns, 195

Children’s Hospital of Philadelphia, 98 China body image in, 201 chocolate emotions and immediate and delayed effects, 163–​164 chocolate “addicts” guilt after eating chocolate, 157–​158 cholecystokinin (CCK) AN and BN and, 51, 54t chromium for BED, 382 chromosome(s) defined, 80 chronic tendency toward overconsumption, 140–​146. see also overconsumption, chronic tendency toward cisapride for AN, 361t, 365–​366 citalopram for BN, 370t, 373 clarification in IPT for EDs, 298–​299 classification(s) defined, 9 described, 9 of EDs, 9–​23 (see also specific types and eating disorder(s) (EDs), classification of ) classification systems described, 9 climate impact on body image and eating concerns, 190 Clinical Global Impression-​Improvement scale for NES, 382 clonazepam for AN, 368 clonidine for AN, 368 clothing marketing of impact on body image and eating concerns, 195 clothing customs impact on body image and eating concerns, 190 CNS. see central nervous system (CNS) cognitive behavioral therapy (CBT) CRT vs., 397, 398t ECT vs., 482 for EDs, 4, 15, 271–​286, 304 (see also specific disorders, e.g., bulimia nervosa (BN)) AN, 278–​280 BED, 276–​278 BN, 271–​276 brevity of, 281 clinical range/​reach of, 281 cost-​effectiveness of, 280–​281

Index

529

cognitive behavioral therapy (CBT) (cont.) dissemination and implementation of, 283 effectiveness of, 280–​281 efficacy of, 278–​280 ethnic, racial, and cultural considerations related to, 282 scalability of, 282–​283 task-​sharing in, 281–​282 group behavioral weight loss intervention vs. for overweight BED persons, 130 Internet-​delivered, 496–​497 IPT with for AN, 303–​304 for BED, 302 for BN, 300–​301 physical exercise with for BN persons, 130 cognitive-​behavioral therapy–​enhanced (CBT-​E). see enhanced CBT (CBT-​E) cognitive dissonance (CD) programs, 255–​256 cognitive factors emotional responses to food related to, 157 cognitive flexibility, 239 Cognitive Flexibility Scale, 402 cognitive processes as factor in EDs, 239–​240 cognitive remediation therapy (CRT), 395–​409 for AN RCTs of, 397 in brain-​injured patients, 396 CBT vs., 397, 398t described, 395 for EDs, 395–​409 (see also specific disorders) in child and adolescent populations, 399–​400 in clinical settings, 400–​401 examples of, 403t–​404t experimental measures, 404–​406 future work in, 406 historical development of, 396–​397 introduction, 395 outcome measurements, 402–​406 outline of typical therapy session, 401–​402, 403t–​404t RCTs in adult populations, 397–​399 self-​report measures, 402 as therapy enhancer, 397, 398t indications for, 396 introduction, 395 cognitive restraint overeating during stress related to, 162 cognitive systems EDs and, 27–​28 coherence central (see central coherence) college campus

530

Index

impact on body image and eating concerns, 192 comfort eating negative affect impact on, 161–​164 susceptibility to stress and, 162–​163 communal socialization of food and body impact on body image and eating concerns, 191 communication social as primary function of emotion, 431–​432 communication analysis in IPT for EDs, 299 compensatory eating disorder, 445–​446 complication(s) medical, 222–​225 (see also specific disorders, e.g., anorexia nervosa (AN), medical complications of ) conditioning evaluative in SE, 432–​434, 432f confidentiality Internet-​based interventions for EDs and, 506–​507 of mobile devices and apps for EDs, 499 conflict around food in SE, 426 conjoint family therapy (CFT) in FBT-​AN, 321 connection(s) making in IPT for EDs, 296–​297 constructs of interest of EDs to be assessed, 213–​215 cortisol defined, 68 cost(s) in EDs, 410–​415 future directions related to, 414 ICD-​9 on, 411 individual cost estimates, 410–​411 introduction, 410 national cost estimates, 411–​412 per-​patient financial costs, 411 personal costs, 410–​411 cost–​benefit issues in ED prevention, 263–​264 cost-​effectiveness in EDs, 410–​415 future directions related to, 414 treatment-​related, 412–​414 cost utility defined, 414 of ED treatments, 414 course of EDs (see specific disorders) cross-​cultural cataloging to global systems and regional trends as factor in body image and eating concerns, 199–​202

cross-​cultural patterns of AN, 35–​36 of BED, 39 of BN, 37–​38 CRT. see cognitive remediation therapy (CRT) CRT Resource Pack, 400 cue exposure therapy (CET) for EDs, 475–​478 cultural influences on body image and EDs, 187–​208 (see also culture, impact on body imaging and eating concerns) in CBT for EDs, 282 cultural issues in future versions of DSM, 17–​18 culture defined, 187–​188 described, 187–​189 impact on body image and eating concerns, 187–​208 from cross-​cultural cataloging to global systems and regional trends, 199–​202 finance and, 201–​202 from gender and race to intersectionality, 196–​198 globalization and, 199–​202 global proliferation of biomedicine and, 201–​202 ideas, ideals, and images in, 193–​195 introduction, 187 large-​scale environmental and political-​economic variables in, 189–​191 media in, 201 practices, behaviors, and habits in, 191–​193 shifts in, 196–​202 from socioeconomic status to upward mobility, 198–​199 symbolic body capital in, 195–​196 toward increased multidisciplinary collaborative research on, 202–​203 D-​cycloserine for AN, 368 cyproheptadine for AN, 361t, 365

D

DA. see dopamine (DA) dancer(s) ED prevention in, 260 Danish Twin Registry, 87 DBT. see dialectical behavior therapy (DBT) DBTgsh. see DBT–​guided self-​help (DBTgsh) DBT–​guided self-​help (DBTgsh), 339 decided preferences in SE, 426 decubitus ulcers AN and, 225

deficit(s) interpersonal, 289 dehydroepiandrosterone (DHEA) for AN, 361t, 367 delayed gastric emptying AN and, 223 delayed medial orbitofrontal cortex (mOFC) activation reduction in BN, 60 demand characteristics reductions in bulimic symptoms in experimental trials due to, 138 Department of Health and Human Services (HHS) under HITECH Act, 499 depression BN–​related vagal nerve activity and, 158–​159 CRT for, 396 EDs and, 164 treatment of artificial cervical VNS in, 158 dermatologic complications of AN, 225 desipramine for BN, 370t, 374 Detail and Flexibility Questionnaire (DFlex), 402 dexfenfluramine for BED, 376t, 379 for BN, 370t, 374 DFlex. see Detail and Flexibility Questionnaire (DFlex) DHEA. see dehydroepiandrosterone (DHEA) diabetics ED prevention in, 261 diagnosis of EDs self-​report questionnaires for, 217 Diagnostic and Statistical Manual of Mental Disorders (DSM) future versions of cultural issues in, 17–​18 Diagnostic and Statistical Manual of Mental Disorders, Fifth Ed. (DSM-​5) on BED after bariatric surgery, 459 on CBT for EDs, 271 comorbidity eating disorder studies in, 236 Eating Disorders Workgroup of on OSFED, 39 on EDs, 2–​3, 9–​23 external validators–​related, 13 EDs classification of, 25 Diagnostic and Statistical Manual of Mental Disorders, Fourth Ed. (DSM-​IV) on EDs, 2–​3 psychological comorbidity–​related, 229 dialectical abstinence in BED and BN management, 343

dialectical behavior therapy (DBT), 334–​350 adaptations of for EDs, 338–​340 appetite-​focus, 339 balance between change and acceptance in, 335–​336 biosocial theory of, 334 with BPD, 334 efficacy of, 336–​337 case management strategies in, 336 core strategies in, 336 described, 334, 335, 337–​338 dialectic framework within, 334 for EDs, 337–​350 adaptations of, 338–​340 adaptations of biosocial theory in, 340–​341 affect regulation model, 340 BED and BN, 343 biosocial theory in, 337–​338 reasons for, 337–​338 Stanford model, 338–​339, 341–​343, 342t, 344t–​346t (see also Stanford DBT model) emphasis of, 334 functions of, 335 introduction, 334 modes of treatment in, 335 modules in, 335 stages of, 335 standard treatment with, 334–​336 stylistic strategies in, 336 diarrhea AN and, 223–​224 dietary behavior(s) as risk factor for BN, 136–​137 Dietary Intent Scale (DIS), 134, 135 dietary restraint dieting vs., 127 researcher’s use of measures in validity of, 134–​136 dietary restriction(s) may be unrepresentative of real-​world dieting, 133–​134 relative vs. absolute, 136 dieting defined, 127 described, 127 dietary restraint vs., 127 EDs related to, 126–​154 (see also specific disorders, e.g., bulimia nervosa (BN)) animal studies of, 131 chronic tendency toward overconsumption, 140–​146 (see also overconsumption, chronic tendency toward) dietary behaviors increasing risk for bulimic pathology, 136–​137 dietary restriction interventions may be unrepresentative of real-​world dieting, 133–​134

empirical tests of, 127–​128 future directions in, 146–​147 implications regarding possible explanations for inconsistent findings, 138–​146 incompatible study findings, 131–​138 introduction, 126–​127 prospective studies, 128 prospective studies vs. experiments, 132 reductions in bulimic symptoms in experimental trials due to demand characteristics, 138 researcher’s use of dietary restraint measures, 134–​136 theoretical mechanisms of, 127 trials evaluating interventions seeking to manipulate, 130–​131 ED symptoms related to, 127 in Fiji, 200 longer-​term ED symptoms related to, 129–​131 real-​world dietary restriction interventions may be unrepresentative of, 133–​134 dieting theory of eating pathology empirical tests of, 127–​128 DIS. see Dietary Intent Scale (DIS) disease context impact on body image and eating concerns, 191 disgust recontextualization in approach to, 433 disgust experience in phenomenology of SE, 427–​429, 428f, 430f in SE, 432–​434, 432f dissonance theory in ED prevention programs, 251 distributed cloud computing, 493 DLW. see doubly labeled water (DLW) domains of interest of EDs to be assessed, 213–​215 dopamine (DA) EDs related to, 53, 55 in set-​shifting tasks, 240 stress in reducing, 161 in “wanting” of rewards, 160–​161 dopamine D2 receptor (DRD2) in BED, 160–​161 dopamine D2 receptor (DRD2) deficiency obesity related to, 161 dopamine (DA) receptor binding alterations in EDs, 53, 55 doubly labeled water (DLW) in longer-​term caloric intake assessment, 135 DOVE, 262 DRD2. see dopamine D2 receptor (DRD2) DRES. see Dutch Restrained Eating Scale (DRES)

Index

531

DSM. see Diagnostic and Statistical Manual of Mental Disorders (DSM) DSM-​5. see Diagnostic and Statistical Manual of Mental Disorders, Fifth Ed. (DSM-​5) DSM-​IV. see Diagnostic and Statistical Manual of Mental Disorders, Fourth Ed. (DSM-​IV) dumping syndrome after bariatric surgery, 464 Dutch Restrained Eating Scale (DRES), 134, 135 dysphagia BN and, 225

E

early adolescents ED–​related diagnostic criteria for, 19–​20 EAST. see Extrinsic Affective Simon Task (EAST) EAT. see Eating Attitudes Test (EAT) eating comfort negative affect impact on, 161–​164 susceptibility to stress and, 162–​163 effects on emotions EDs related to, 158–​159 emotional after bariatric surgery, 463 vs. restrained eating, 162 laboratory-​based relationship of dieting to, 128–​129 mindful in BED and BN management, 343 restrained vs. emotional, 162 selective, 419–​437 (see also selective eating (SE)) slowness in in SE, 426–​427 sweet after bariatric surgery, 463–​464 eating attitudes negative affect impact on, 161–​164 Eating Attitudes Test (EAT), 217 eating behavior(s) (EBs) after bariatric surgery, 458–​469 eating disorder(s) (EDs). see also pica; specific types, e.g., bulimia nervosa (BN) adolescent family therapy for, 320–​321 in adults family therapy for, 329–​330 affective disorders with, 164 after bariatric surgery, 458–​469 (see also bariatric surgery patients; eating behavior(s) (EBs); specific disorders and bariatric surgery(ies)) alexithymia and, 176 appetitive regulation in, 47–​79 fMRI studies of, 61–​66, 62f, 65f

532

Index

future research directions related to, 66–​67 gender differences in, 61 images of food in, 62 interoceptive processing in, 59–​60 introduction, 47 neurocircuitry of, 58–​60 PET studies of, 61–​62 regional cerebral blood flow studies in, 61–​62 SPECT studies of, 61–​62 tastes of food in, 62–​63, 62f approaches to understanding, 45–​208 assessment of, 209–​221 mobile devices and apps in, 492–​504 (see mobile devices and applications (apps), in EDs assessment and treatment) technology-​based, 4–​5 attitudes and behaviors associated with, 247 atypical AN, 448–​451 behavioral, temperamental, and personality factors associated with genetics of, 83–​84 boundary problems related to, 2–​3 categories of, 10 causes of family environment, 320–​321 CBT for, 271–​286 (see also specific disorders and cognitive behavioral therapy (CBT), for EDs) classification of, 9–​23 alternative diagnostic model, 13–​16 boundary problems related to, 2–​3 controversies related to, 17–​20 cultural issues in, 17–​18 DSM-​5, 9–​23, 25 future directions in, 17–​20 intradiagnostic heterogeneity, 16 introduction, 9 overlap between diagnostic entities in, 12–​13 research-​related criteria in, 17 separate diagnostic criteria for children and early adolescents, 19–​20 separate diagnostic criteria for men and women, 18–​19 statistical approaches to, 11–​12 taxonomy in, 9 TDM, 13–​16, 14f transdiagnostic model, 15–​16 common comorbidity profile of, 13 compensatory, 445–​446 complexity of, 520 conceptualization of RDoC on, 1, 24–​33 (see also research domain criteria (RDoC)) cost-​effectiveness, 410–​415 (see also cost(s); cost-​effectiveness) course of, 34–​43 (see also specific disorders)

CRT for, 395–​409 (see also cognitive remediation therapy (CRT)) cultural influences on, 187–​208 (see also culture, impact on body image and eating concerns) DBT for, 337–​350 (see also dialectical behavior therapy (DBT), for EDs) depression and anxiety with, 164 diagnosis of DSM-​5 on, 10–​11 overlap in, 12–​13 dieting and, 126–​154 (see also specific disorders and dieting, EDs related to) DSM-​5 on, 9–​23 emerging syndromes, 438–​457 (see also specific disorders and emerging syndromes) emotions and (see also emotion(s)) epidemiology of, 34–​43 (see also specific disorders) introduction, 34 on Facebook, 263 family and genetic studies of, 3, 81 family therapy in, 319–​333 (see also family therapy, for EDs) in Fiji, 200 functional and task activation studies in, 61–​66, 62f, 65f genetic influences on, 80–​105 (see also genetic influences) GWAS in, 98–​99 history of, 1–​2 hunger and satiety in fMRI studies of, 63 Internet-​based interventions for, 505–​519 (see also Internet-​based interventions, for EDs) interoception in fMRI studies of, 63–​64 interpersonal model for, 288–​289 introduction, 1–​5 IPT for, 4, 287–​318 (see also interpersonal psychotherapy (IPT), for EDs) JIT interventions for, 497 longer-​term dieting related to symptoms of experimental studies of, 129–​131 low self-​directedness and, 238 mental disorders with, 164 models of objectification theory, 480 monoamine function disturbances related to, 53, 55–​58 DA activity, 53, 55 DA receptor binding alterations, 53, 55 serotonin, 55–​58 moods and, 155–​186 (see also mood(s)) negative affect effects on, 161–​164 negative emotionality and, 164 NES, 438–​444, 440t, 443f

nosological issues related to, 11–​12 ON, 451–​453, 452t (see also orthorexia nervosa (ON)) PD, 438, 445–​448 peak onset of, 247 persistence and, 237 personality and relationships between, 238 pharmacotherapy of, 359–​394 (see also specific agents, disorders, and pharmacotherapy, of EDs) prevalence of, 126 treatment difficulties related to, 247 prevention of, 3, 247–​270 (see also ED prevention; ED prevention programs; prevention, of EDs) prevention programs for (see ED prevention programs) psychoeducation for apps for, 496 psychological assessment of, 211–​221 (see also assessment(s), of EDs) psychological comorbidity of, 229–​243, 231t–​233t affective disorders, 229–​230 anxiety disorders, 230 DSM-​IV on, 229 DSM-​5 on, 236 ICD-​10 on, 236 ICDs, 234–​235 introduction, 229 perfectionism, 236–​238 personality disorders, 235–​236 personality traits–​related, 236–​240 substance abuse disorders, 230, 233–​234 temperament, 236–​238 questions related to, 520 recent changes related to, 2 register studies of results of risk factors and markers from, 119–​120 relationships between personality/​ temperament and perspectives on, 238 research on future directions for, 66–​67 response to inhibition alterations in fMRI studies of, 65–​66 response to reward alterations in fMRI studies of, 64–​65, 65f risk factors for, 3, 106–​125 (see also specific types, disorders, and risk factor(s), for EDs) self-​monitoring of self-​report questionnaires for, 218 serotonin receptor binding alterations in, 56–​58 SH and GSH for, 351–​358 (see also guided self-​help (GSH), for EDs; self-​help (SH), for EDs) sleep-​related, 442

standalone variants of, 438 symptoms of IPT in redirecting issues related to, 297 systematic study of beginnings of, 2 trait anxiety and, 237 transdiagnostic theories of, 252 treatment of, 3–​4 (see also specific types) basic science contributions to, 520–​521 CBT-​E in, 214 CBT in, 4, 15, 214, 304 cost-​effectiveness of, 412–​414 costs utility of, 414 CRT in, 395–​409 (see also specific disorders and cognitive remediation therapy (CRT)) discrimination and implementation of, 522 IPT in, 4, 287–​318 limitations of conventional, 505–​506 mobile devices and apps in, 492–​ 504 (see also mobile devices and applications (apps), in EDs assessment and treatment) modality selection for, 304 outpatient, 351 plateau in development of, 521–​522 self-​report questionnaires in, 217–​218 technologies in, 522–​523 technology-​based, 4–​5 VR for, 470–​491 (see also virtual reality (VR)) Eating Disorder Diagnostic Scale (EDDS), 217 Eating Disorder Examination (EDE), 447 in EDs assessment, 216 Eating Disorder Examination–​ Questionnaire (EDE-​Q), 217–​218, 328 Eating Disorder Examination–​ Questionnaire-​Restraint (EDEQ-​ R) scale, 134, 135 Eating Disorder Examination–​Restraint (EDE-​R) scale, 135 Eating Disorder Inventory subscales of, 328 Eating Disorder Inventory-​2 (EDI-​2), 363, 364, 449 Interpersonal Distrust Subscale of, 364 Eating Disorder Inventory 12 score, 378 Eating Disorder Inventory (EDI) scores, 360 eating disorder not otherwise specified (EDNOS), 438 boundary problems related to, 2–​3 neuroticism and, 119 risk factors for longitudinal studies’ characteristics, 119

eating disorder not otherwise specified, purging type (EDNOS-​P). see purging disorder (PD) Eating Disorders Inventory-​3, 217 Eating Disorders Inventory subscales, 12 Eating Disorders Workgroup of DSM-​5 on OSFED, 39 Eating Disorders Working Group of Psychiatric Genomics Consortium, 99 Eating Inventory, 447 eBody project program, 511 EBs. see eating behavior(s) (EBs) ecological momentary assessment (EMA), 495 on negative affect, 238–​239 ECT. see experiential cognitive therapy (ECT) EDDS. see Eating Disorder Diagnostic Scale (EDDS) EDE. see Eating Disorder Examination (EDE) edema formation BN and, 226 EDE-​Q. see Eating Disorder Examination–​Questionnaire (EDE-​Q) EDEQ-​R scale. see Eating Disorder Examination–​Questionnaire-​ Restraint (EDEQ-​R) scale EDE-​R scale. see Eating Disorder Examination–​Restraint (EDE-​R) scale EDI-​2. see Eating Disorder Inventory-​2 (EDI-​2) “EDINA,” 510 EDI scores. see Eating Disorder Inventory (EDI) scores EDNOS. see eating disorder not otherwise specified (EDNOS) EDNOS-​P. see eating disorder not otherwise specified, purging type (EDNOS-​P) ED prevention, 247–​270. see also ED prevention programs AN, 263 cost–​benefit issues related to, 263–​264 current status and underlying theory, 247–​270 dissemination/​implementation in, 263–​264 future directions in, 264–​265 as harmful, 253 IPT development in, 311–​312 obesity prevention and, 259–​260 programs for (see ED prevention programs) public health/​policy and mass media models related to, 261–​262 screening in, 249–​250 in specific settings and special populations, 260–​263

Index

533

ED prevention (cont.) theories and models of interventions in, 250–​252 dissonance theory, 251 feminist theory, 251 media literacy and advocacy, 251–​252 psychoeducation, 250 social learning theory, 250–​251 ED prevention programs, 247–​270. see also ED prevention categories of, 247–​248 CD programs, 255–​256 cost–​benefit issues related to, 263–​264 dissemination/​implementation in, 263–​264 effective examples of, 255–​260 effectiveness of, 252–​253 future directions in, 264–​265 as harmful, 253 indicated prevention programs, 248 moderators and mediators of, 253–​254 in obesity prevention, 259–​260 peer support/​school-​based programs, 258–​259 risk factors informing, 249 StudentBodies program, 248, 250, 254, 256–​258, 263 targeted or selective prevention interventions, 248 theories and models of, 250–​252 dissonance theory, 251 feminist theory, 251 media literacy and advocacy, 251–​252 psychoeducation, 250 social learning theory, 250–​251 universal prevention program, 247–​248 EDs. see eating disorder(s) (EDs) ego-​oriented individual therapy (EOIT), 322 EMA. see ecological momentary assessment (EMA) emaciation brain effects of, 47–​48 embodied technology VR as, 473 emerging syndromes, 438–​457. see also specific disorders, e.g., purging disorder (PD) ON, 451–​453, 452t (see also orthorexia nervosa (ON)) atypical AN, 448–​451 future directions in, 453–​454 introduction, 438–​439 NES, 438–​444, 440t, 443f PD, 438, 445–​448 status of research needed to clarify, 443–​445 emotion(s). see also mood(s) chocolate and immediate and delayed effects, 163–​164 defined, 156

534

Index

EDs and, 155–​186 BED, 169–​173 BN, 165–​169 (see also bulimia nervosa (BN), negative emotionality and) clinical evidence, 164–​177 cognitive factors in, 157 dimensions of, 156, 157f five-​way model of, 155–​158, 156f future directions in, 178 introduction, 155–​158, 156f, 157f meal size, timing, and habit effects on, 159 mechanisms associated with, 158–​164 predicted changes related to, 155–​156, 156f hunger and eating effects on, 158–​159 introduction, 155–​158, 156f, 157f moods vs., 156 negative affect effects on, 161–​164 stress susceptibility and, 162–​163 neural substrates shared by sensory reward impact on, 159–​161 social communication as primary function of, 431–​432 emotional eating after bariatric surgery, 463 restrained eating vs., 162 Emotional Eating Scale, 339 emotional experiences potentiation of sensory sensitivities in SE and, 430 emotionality negative (see negative emotionality) emotional processing constructs types of, 240 emotional processing deficits AN and, 176–​177 emotional vulnerability defined, 334–​335 emotion-​focused therapies for EDs, 337–​350 (see also dialectical behavior therapy (DBT)) emotion recognition attentional biases to, 240 emotion regulation strategies, 240 endocrine system AN effects on, 224 endogenous opioid neuropeptides positive mood related to, 159–​160 endophenotype(s) described, 80 enhanced CBT (CBT-​E), 214, 272–​276, 413 for AN, 278–​280 broad (CBT-​Eb), 272 focused (CBT-​Ef ), 272 “enjoyment of food” measure, 160–​161 environment(s) family in etiology of EDs, 320–​321 mealtime in SE management, 434–​435, 434t

environmental variables large-​scale impact on body image and eating concerns, 189–​191 EOIT. see ego-​oriented individual therapy (EOIT) epidemiology of EDs, 34–​43 (see also specific disorders, e.g., anorexia nervosa (AN)) epigenesis described, 80 erythromycin for BN, 375 esophagus Barrett’s BN and, 225 ESP in EDs assessment, 217 ESS-​KIMO, 512, 513 “ES[S]‌PRIT,” 512 estimation examples of, 404t estradiol for AN, 361t, 367 ethical concerns Internet-​based interventions for EDs–​ related, 506–​507 ethical issues in CBT for EDs, 282 ethnoscape(s), 200–​201 evaluative conditioning in SE, 432–​434, 432f Evolution, 262 executive functioning sensory sensitivities and in SE, 431 exercise(s) CBT with in BN management, 130 experiential cognitive therapy (ECT), 482 CBT vs., 482 experimental measures of outcome of CRT for EDs, 404–​406 exploratory questions in IPT for EDs, 298 Extrinsic Affective Simon Task (EAST), 142, 143

F

Facebook EDs on, 263 factor mixture modeling (FMM) in ED classification, 11–​12 family(ies) EDs “running” in, 81 IPT for adaptations of, 311 family-​based therapy (FBT). see also family therapy AFT vs., 323 for EDs, 319–​333 (see also family therapy, for EDs) family environment

as factor in EDs, 320–​321 lack of evidence to support causal role of, 82 family meals SE effects on, 423 family studies of EDs, 3 family therapy conjoint, 321 for EDs, 319–​333 acceptability of, 327 adolescent AN, 321–​322 (see also family therapy for adolescent AN (FBT-​AN)) adolescent BN, 324–​327 (see also family therapy for adolescent BN (FBT-​BN)) in adults, 329–​330 future directions in, 330–​331 history of, 319–​320 theoretical model of, 320–​321 treatment manual for, 322–​324 separated, 321 family therapy for adolescent AN (FBT-​ AN), 321–​322 acceptability of, 327 BFST in, 322 CFT in, 321 EOIT in, 322 first family therapy trial outside UK, 321–​322 French study, 323 Melbourne study, 324 multifamily therapy, 327–​329 seminal study, 321, 322 SFT in, 321 six-​site study of FBT and SFT, 323–​324 Stanford dosage study, 323 Sydney study, 323 treatment manual for, 322–​324 without prior hospitalization, 321 family therapy for adolescent BN (FBT-​ BN), 324–​327 studies of, 325–​327 fasting as part of rituals in Judaism, 201 “fattest nations” Belize as one of, 201 fatty food in pain alleviation, 160 FBT. see family-​based therapy (FBT) FBT-​AN. see family therapy for adolescent AN (FBT-​AN) FBT-​BN. see family therapy for adolescent BN (FBT-​BN) FDA. see Food and Drug Administration (FDA) FEATBACK, 414, 512 Federal Drug Administration (FDA) on BN treatment, 522 feeding of infants “on demand” vs. “on schedule,” 191

feeding behaviors altered in AN and BN, 48–​49, 49t normal brain imaging studies of, 60–​61 regulation of neuropeptides in, 49–​53, 54t–​55t feeding disorders DSM-​5 on, 10 feminist theory in ED prevention programs, 251 fenfluramine for BN, 374 Fiji dieting in, 200 EDs in, 200 finance impact on body image and eating concerns, 201–​202 First International Night Eating Symposium, 439, 440t 5-​HT. see 5-​hydroxytryptamine (5-​HT) 5-​HT3 receptor antagonists for BN, 370t, 373 fluid consumption high-​calorie after bariatric surgery, 463 fluorodeoxyglucose defined, 68 fluoxetine for AN, 361t, 362 for BN, 369, 370t flutamide for BN, 370t, 373 fluvoxamine for BN, 370t, 371 FMM. see factor mixture modeling (FMM) fMRI. see functional magnetic resonance imaging (fMRI) focal psychodynamic therapy (FPT), 413 food communal socialization of impact on body image and eating concerns, 191 conflict around in SE, 426 fatty in pain alleviation, 160 images of in appetitive regulation in AN and BN, 62 tastes of in appetitive regulation in AN and BN, 62–​63, 62f food addiction after bariatric surgery, 465–​466 Food and Drug Administration (FDA), 158 food cues emotional responses to AN and, 174–​175 BED and, 169–​170

BN and, 166 food deprivation effects of studies of, 48–​49, 49t food insecurity impact on body image and eating concerns, 189–​190 food neophobia in SE, 425 food refusal in SE, 426 food reward greater anticipatory chronic tendency toward overconsumption related to, 141–​144 greater consummatory chronic tendency toward overconsumption related to, 140–​141 Food Scientist, 434 food variety in SE, 424–​425 FPT. see focal psychodynamic therapy (FPT) Fragmented Pictures Task, 405 frontal operculum, 59 Frost Multidimensional Perfectionism Scale, 236 functional and task activation studies in EDs, 61–​66, 62f, 65f functional magnetic resonance imaging (fMRI) affect regulation–​related in BN, 239 in AN, 58–​60 in BN, 58–​60 functional magnetic resonance imaging (fMRI) studies of appetitive regulation in AN and BN, 61–​66, 62f, 65f of normal feeding behavior in healthy individuals, 60 fussy eating, 419–​437. see also selective eating (SE)

G

gambling pathological, 234 gastric emptying delayed AN and, 223 gastroesophageal reflux (GERD) in SE, 430–​431 gastrointestinal (GI) problems after bariatric surgery, 464–​465 gastrointestinal (GI) system AN effects on, 223–​224 gay male subcultures impact on body image and eating concerns, 194 gay men body image dissatisfaction among, 194

Index

535

[G]‌EFT. see The (Group) Embedded Figures Task ([G]EFT) gender as factor in body image and eating concerns, 190–​191, 196–​198 as factor in response to liquid meal during hunger or satiation, 61 gene(s) EDs related to, 80–​105 (see also genetic influences) identification of, 98–​99 gene–​environment interplay in EDs, 84–​85 complexities of, 83–​85 twin studies of, 86–​98 (see also twin studies, of gene–​environment interplay) General Health Questionnaire, 117 genetic(s) of BMI, 83 Genetic Consortium for Anorexia Nervosa, 98 genetic influences on behavioral disturbances, 81 on EDs, 80–​105 AN and BN, 48 behavioral, temperamental, and personality factors, 83–​84 BMI, 83 consistent evidence for, 82 future directions in, 100 gene–​environment interplay in, 83–​85 (see also gene–​environment interplay, in EDs) interactions between specific variants and environments, 99 lack of evidence to support causal role of family environment in, 82 molecular genetic studies, 98–​99 overview, 81–​82 recognition of, 82 studies of, 3 terminology related to, 80–​81 genome(s) defined, 81 genomewide association study (GWAS) in EDs, 98–​99 genotype(s) defined, 81 genotype–​environmental interactions in EDs, 84–​85 GERD. see gastroesophageal reflux (GERD) Getting Better Bit(e) by Bit(e) in SH for EDs, 353 ghrelin AN and BN and, 52–​53, 55t ghrelin agonists for AN, 361t, 367 GI. see gastrointestinal (GI) girl(s) adolescent body dissatisfaction among, 480

536

Index

Girl Scouts, 262 globalization characterizations of body image and EDs related to, 199–​202 technological advancements and, 201–​202 global systems from cross-​cultural cataloging to as factor in body image and eating concerns, 199–​202 goal(s) in IPT for EDs, 295–​296 grazing after bariatric surgery, 462–​463 greater anticipatory food reward chronic tendency toward overconsumption related to, 141–​144 greater consummatory food reward chronic tendency toward overconsumption related to, 140–​141 greater impulsivity chronic tendency toward overconsumption related to, 144–​145 grief, 289 IPT for, 294, 294t group(s) in IPT for EDs, 300 growth stunted SE and, 422 GSH. see guided self-​help (GSH) guided self-​help (GSH) in CBT for BED, 277 for BN, 275–​276 DBT–​, 339 for EDs, 351–​358 apps for, 496–​497 described, 352 future directions in, 355–​356 Getting Better Bit(e) by Bit(e) in, 353 introduction, 351–​352 Overcoming Binge Eating in, 352–​353 psychoeducational videotapes in, 353 systematic reviews and meta-​analyses related to, 353 treatment predictors, moderators, and mediators of, 354 via Internet-​based interventions, 508–​510 Guided Self-​Help for Bulimia Nervosa, Therapist’s Manual, 509 Guidelines for the Practice of Telepsychology, 506 guilt of chocolate “addicts” after eating chocolate, 157–​158 gustatory cortex, 59

GWAS. see genomewide association study (GWAS)

H

habit(s) impact on body image and eating concerns, 191–​193 HAM-​A scores. see Hamilton Anxiety Scale (HAM-​A) scores Hamilton Anxiety Scale (HAM-​A) scores, 360, 362 Hamilton Depression Rating Scale, 377 harm avoidance AN and BN and PET data correlated with, 57–​58 harm avoidance scores in women with binge–​purge behaviors, 237 harm reduction in ED prevention, 248–​249 Health and Human Services (HHS) under HITECH Act, 499 Health Apps Library, 499 Health Information Technology Economic and Clinical Health Act (HITECH), 493 “Health of the 51%: Women” from NHS, 283 heart AN effects on, 222–​223 Helping, Encouraging, Listening and Protecting Peers (HELPP) initiatives, 251 HELPP initiatives. see Helping, Encouraging, Listening and Protecting Peers (HELPP) initiatives heritability estimates in twin studies of gene–​environment interplay, 86–​92, 88t–​91t, 93t–​95t HHS. see Health and Human Services (HHS) high-​calorie fluid consumption after bariatric surgery, 463 HITECH. see Health Information Technology Economic and Clinical Health Act (HITECH) HITECH Act HHS under, 499 HIV impact on body image and eating concerns, 191 Hollywood Bollywood vs., 200–​201 hormonal agents for AN, 361t, 366–​367 for BN, 370t, 373 HPA axis. see hypothalamic-​pituitary-​ adrenal (HPA) axis HTC, 474 hunger in EDs fMRI studies of, 63

effects on emotions EDs related to, 158–​159 5-​hydroxytryptamine (5-​HT) defined, 81 hyperlearning, 239 hypokalemia BN and, 225, 226 hyponatremia BN and, 225, 226 hypophosphatemia refeeding AN and, 223 hypothalamic-​pituitary-​adrenal (HPA) axis AN and BN effects on, 50

I

IAPS. see International Affective Picture System (IAPS) IAT. see Implicit Association Test (IAT) ICD-​9. see International Classification of Diseases, 9th edition (ICD-​9) ICD-​10. see International Classification of Diseases, 10th revision (ICD-​10) ICD not otherwise specified, 234 ICDs. see impulse control disorders (ICDs) iCounselor, 496 idea(s) impact on body image and eating concerns, 193–​195 ideal(s) anti-​ideals vs., 194 impact on body image and eating concerns, 193–​195 image(s) impact on body image and eating concerns, 193–​195 Implicit Association Test (IAT), 142 impulse control disorders (ICDs) characteristics of, 234 classification of, 234 EDs and, 234–​235 impulsivity greater chronic tendency toward overconsumption related to, 144–​145 “IN@”, 510 indicated prevention programs, 248 infant feeding “on demand” vs. “on schedule,” 191 ingestion(s) nocturnal, 439 inhibition response EDs–​related alterations in, 65–​66 norepinephrine in, 240 insecurity(ies) food-​related impact on body image and eating concerns, 189–​190 Institute of Psychiatry, 320

instrumentation in EDs assessment, 215–​218 insula anterior, 59 intelligence artificial, 493 values embedded in, 499 intermittent explosive disorder, 234 International Affective Picture System (IAPS), 175 International Classification of Diseases, 9th ed. (ICD-​9) on per-​patient financial costs of EDs, 411 International Classification of Diseases, 10th rev. (ICD-​10) comorbidity eating disorder studies in, 236 International Journal of Eating Disorders, 2 Internet-​based interventions for EDs, 505–​519 as adjunct to treatment and aftercare interventions, 510 benefits of, 506 career support–​related, 512–​513 confidentiality issues related to, 506–​507 ethical concerns related to, 506–​507 evaluation criteria for, 513–​514 GSH and unguided SH, 508–​510 implications of, 514–​515 introduction, 505 methodological aspects of, 515–​516 potential of, 505–​507 prevention-​related, 510–​512 psychotherapy, 507–​508 reflections on state of science related to, 520–​523 types of, 507–​513 Internet-​based subcultures impact on body image and eating concerns, 193 Internet-​delivered cognitive behavioral therapy (CBT), 496–​497 “Internet-​of-​things” developments in, 499 interoception in EDs fMRI studies of, 63–​64 interoceptive processing in appetite regulation, 59–​60 interpersonal deficits, 289 IPT for, 294t, 295 Interpersonal Distrust Subscale of EDI-​2, 364 interpersonal formulation in IPT for EDs, 291 interpersonal inventory described, 313 in IPT for EDs, 290–​291, 291t–​293t interpersonal model for EDs, 288–​289 interpersonal problem areas, 289–​290 interpersonal psychotherapy (IPT), 214

CBT with for AN, 303–​304 for BED, 302 for BN, 300–​301 defined, 287 described, 287 in eating-​and weight-​related problems prevention development of, 311–​312 for EDs, 4, 287–​318 adolescent and child/​parent adaptations of, 311 AN, 303–​304 basic concepts, 289–​290 BED, 301–​303, 310–​311 BN, 300–​301, 310–​311 clarification in, 298–​299 communication analysis in, 299 diagnosis and assignment of sick role in, 290, 291t disseminating and implementing, 312 empirical literature relevant to, 300–​310, 308t encouraging affect in, 298 exploratory questions in, 298 focusing on goals in, 295–​296 future directions in, 310–​312 general therapeutic techniques in, 297–​298 grief-​related, 294, 294t group in, 300 implementation of, 290–​300, 291t–​294t initial phase, 290–​291, 291t–​294t intermediate phase, 293–​299, 294t interpersonal deficits–​related, 294t, 295 interpersonal formulation in, 291 interpersonal inventory in, 290–​291, 291t–​293t interpersonal model, 288–​289 interpersonal problem areas, 289–​290 interpersonal role disputes–​related, 294t, 295 making connections in, 296–​297 outcome studies of, 300–​310, 308t problem areas to be addressed in, 294–​295, 294t redirecting symptom-​related issues in, 297 roles transitions–​related, 294–​295, 294t termination phase, 299–​300 therapeutic relationship in, 299 therapeutic stance in, 295 therapeutic strategies, 295–​299 treatment structure, 290 in excessive weight gain prevention, 305–​310, 308t interpersonal theory of, 287–​288 introduction, 287 interpersonal role disputes, 289 IPT for, 294t, 295

Index

537

interpersonal theory of IPT, 287–​288 intersectionality from gender and race to shifts in cultural factors in body image and EDs and, 196–​198 interview(s) in EDs assessment, 215–​217 semistructured, 216 unstructured, 216 intradiagnostic heterogeneity of EDs, 16 IPT. see interpersonal psychotherapy (IPT)

J

Jamaica AN and BN in, 200 JIT interventions. see just-​in-​time (JIT) interventions job subcultures impact on body image and eating concerns, 192 Judaism fasting as part of rituals in, 201 just-​in-​time (JIT) interventions for EDs, 497

K

kleptomania, 234

L

laboratory-​based eating relationship of dieting to prospective studies of, 128–​129 LAGB. see laparoscopic adjustable gastric banding (LAGB) lamotrigine for BED, 376t, 380 for BN, 373 Lantern, 496 laparoscopic adjustable gastric banding (LAGB) prevalence of, 458 latent class analysis (LCA) in ED classification, 11–​12 Latent Profile Analysis, 238 laxative abuse BN and, 226 in PD, 446 LCA. see latent class analysis (LCA) LD-​score regression (LDSR), 83 LDSR. see LD-​score regression (LDSR) LDX for BED, 375–​377, 376t legislated minimum body mass index (BMI) for models, 193 leptin AN and BN and, 51–​52, 54t–​55t lesbian(s) body satisfaction among, 194 life chart

538

Index

described, 313 example of, 291, 292t–​293t Life Smart, 251–​252 linkage defined, 81 liraglutide for BED, 378 lithium for AN, 361t, 367 for BN, 370t, 374 LOC eating patterns. see loss of control (LOC) eating patterns longer-​term caloric intake assessment of DLW in, 135 longer-​term dieting ED symptoms related to experimental studies of, 129–​131 loss of control (LOC) eating patterns after bariatric surgery, 460 IPT in prevention of, 305–​310, 308t lower esophageal sphincter self-​induced vomiting effects on, 225 lung(s) AN effects on, 223

M

MAEDS scale. see Multifactorial Assessment of Eating Disorder Symptoms (MAEDS) scale magnetic resonance imaging (MRI) functional (see functional magnetic resonance imaging (fMRI)) major depressive disorder alcohol abuse/​dependence disorder related to, 233 making connections in IPT for EDs, 296–​297 malnutrition AN–​related medical complications associated with, 223 marketing of children’s toys and clothing body image and eating concerns related to, 195 mass media models ED prevention and, 261–​262 MATCH (Modular Approach to Therapy for Children with Anxiety, Depression, or Conduct Problems), 26 Matching Familiar Figures Task, 405 Maudsley Hospital, 320 McArthur Foundation Research Network on Psychopathology and Development, 106 McKnight Longitudinal Study, 117 Me!, 262 meal size, timing, and habit moods and emotions related to, 159 mealtime environment

SE effects on, 423 in SE management, 434–​435, 434t media impact on body image and eating concerns, 193–​195, 201 literacy and advocacy of in ED prevention programs, 251–​252 in promoting AN and BN, 262–​263 medial orbitofrontal cortex (mOFC), 170 medial prefrontal cortex (mPFC), 59 Media Smart, 251–​252 medical conditions sensory sensitivities and SE related to, 430–​431 Medical Expenditure Panel Survey, 411 men bisexual body image dissatisfaction among, 194 gay body image dissatisfaction among, 194 mental disorders EDs and, 164 mental health mobile, 493 in clinical care, 499–​502, 501f metabolic acidosis non-​gap BN and, 226 Metacognitions Questionnaire, 450 methylamphetamine for BN ADHD–​related, 374 “metrosexual” described, 194 mindful eating in BED and BN management, 343 Minnesota Multiphasic Personality Inventory (MMPI) scores, 451 minority(ies) sexual ED prevention in, 261 Minority Stress Model, 261 MMPI scores. see Minnesota Multiphasic Personality Inventory (MMPI) scores mobile defined, 493 mobile assessments paper-​and-​pencil assessments vs. bias in self-​report of, 498 mobile devices and applications (apps) in EDs assessment and treatment, 492–​504 controversies related to, 498–​499 currently available technologies, 497–​498 EMA in, 495 evaluating, 499–​502, 501f GSH, 496–​497 introduction, 492–​493 JIT interventions, 497

mobile delivered interventions, 495–​497 privacy and confidentiality related to, 499 promise and reach of, 493 as replacement for therapy, 498–​499 values embedded in AI, 499 mobile mental health, 493 adoption of, 493–​494 in clinical care evaluation of, 499–​502, 501f mobile (including wearable) technology, 493 model(s) legislated minimum BMI criteria for, 193 Modular Approach to Therapy for Children with Anxiety, Depression, or Conduct Problems (MATCH), 26 mOFC. see medial orbitofrontal cortex (mOFC) molecular genetic studies in EDs, 98–​99 monoamine(s) in functioning of striatocortical loops, 240 monoamine systems dysfunction of EDs related to, 53, 55–​58 mood(s). see also emotion(s) characteristics of, 156 defined, 156 described, 156 EDs and, 155–​186 clinical evidence, 164–​177 future directions in, 178 introduction, 155–​158, 156f, 157f meal size, timing, and habit effects on, 159 mechanisms associated with, 158–​164 emotions vs., 156 introduction, 155–​158, 156f, 157f negative as maintaining factor for disordered eating behavior, 165 positive endogenous opioid neuropeptides and, 159–​160 mPFC. see medial prefrontal cortex (mPFC) Multifactorial Assessment of Eating Disorder Symptoms (MAEDS) scale, 217 multifamily therapy for adolescent AN, 327–​329 muscularity nonfat among young men in Samoa, 200

N

NAC. see N-​acetylcysteine (NAC) naloxone

for BN, 374 naltrexone for AN, 368 for BED, 379, 381 for BN, 370t, 373–​374 National Adult Reading Test, 402 National Comorbidity Survey–​Replication Adolescent Supplement on BN, 37 National Eating Disorders Association, 263 National Health Service of UK, 493, 499 National Health Service eating disorders clinic, 274 National Health System (NHS) “Health of the51%: Women” from, 283 National Institute of Clinical Excellence (NICE), 351 National Institute of Mental Health (NIMH), 385 RDoC project of, 24–​33 (see also research domain criteria (RDoC); research domain criteria (RDoC) project) National Mental Health Surveys, 412 negative affect binge eating due to BED and, 171–​173 BN and, 167–​169 effects of, 238–​239 chocolate-​ and emotions-​related, 163–​164 described, 238–​239 eating attitudes and comfort eating related to, 161–​164 overeating during, 161–​164 restrained vs. emotional eating related to, 162 stress susceptibility and comfort eating related to, 162–​163 negative affect lability impact on AN and BN, 239 negative emotionality AN and, 173–​177 BED and, 169–​173 BN and, 165–​169 EDs and, 164 as maintaining factor for disordered eating behavior, 165 negative mood as maintaining factor for disordered eating behavior, 165 negative valence systems EDs and, 26–​27 neophobia food in SE, 425 Nepal body image in, 200 NEQs. see Night Eating Questionnaires (NEQs) nervous system

AN effects on, 224 NES. see night eating syndrome (NES) neurobiologic alterations in AN and BN, 47–​48 neurocircuitry of appetite regulation in AN and BN, 58–​60 neuroendocrine alterations in AN and BN, 49–​53, 54t–​55t neuroendocrine systems feeding behaviors effects on, 50–​53 neuropeptide(s) endogenous opioid positive mood related to, 159–​160 in regulation of feeding behavior, 49–​53, 54t–​55t neuropeptide alterations in AN and BN, 49–​53, 54t–​55t neuropeptide-​Y (NPY) AN and BN and, 51, 54t neuroticism EDNOS and, 119 NHS. see National Health System (NHS) nibbling after bariatric surgery, 463 NICE. see National Institute of Clinical Excellence (NICE) Night Eating Questionnaires (NEQs), 439–​440 Night Eating Questionnaire total score, 382 night eating syndrome (NES), 40, 438–​ 444, 440t, 443f after bariatric surgery, 462 Clinical Global Impression-​ Improvement scale for, 382 described, 439 as distinct disorder, 439–​441 epidemiology of, 40 history of, 439 models of, 439–​443, 443f continuum with obesity, 442 continuum with other EDs, 441–​442 continuum with sleep disorders, 442 evidence of diagnostic validity and clinical significance using, 443 NES as distinct disorder, 439–​441 SRED, 442 pharmacotherapy of, 382 prevalence of, 439 research diagnostic criteria for, 439, 440t research status on, 439 as secondary to other psychopathology, 442–​443 NIMH. see National Institute of Mental Health (NIMH) NNTs. see numbers needed to treat (NNTs) noctural sleep-​related eating disorder (NSRED) after bariatric surgery, 462 nocturnal ingestions, 439 nonfat muscularity among young men in Samoa, 200

Index

539

non-​gap metabolic acidosis BN and, 226 norepinephrine in response inhibition and sustained attention, 240 Norwegian twin study, 87, 92 novelty-​seeking scores BN and, 237 NPY. see neuropeptide-​Y (NPY) NSRED. see noctural sleep-​related eating disorder (NSRED) numbers needed to treat (NNTs), 252 nutritional supplements for AN, 368

O

OBE episode(s). see objective binge eating (OBE) episode(s) obesity DRD2 deficiency and, 161 impact on body image and eating concerns, 194–​195 NES and, 442 prevalence of, 458 prevention of ED prevention programs in, 259–​260 treatment of VNS of splanchnic branch of vagus nerve in, 158 Object Assembly, 405 objectification sexual repeated experiences of, 480 objectification theory, 480 objective binge eating (OBE) episode(s) BED and, 459–​460 BN and, 460–​461 observer’s perspective, 480–​481 obsessive-​compulsive disorder (OCD) alcohol abuse/​dependence disorder and, 233 EDs and, 230 perfectionism and, 237 obsessive-​compulsive personality disorder (OCPD), 237 OCD. see obsessive-​compulsive disorder (OCD) OCPD. see obsessive-​compulsive personality disorder (OCPD) Oculus Rift, 474 OFC. see orbitofrontal cortex (OFC) olanzapine for AN, 361t, 363–​364 ON. see orthorexia nervosa (ON) Onslaught, 262 opioid(s) for AN, 368 opioid antagonists for AN, 368 for BED, 381 for BN, 370t, 373–​374 opioid peptides AN and BN and, 50–​51, 54t

540

Index

orbitofrontal cortex (OFC), 60, 61 amygdala and, 60 delayed medial activation reduction in BN, 60 medial, 170 posterior, 59 orlistat for BED, 376t, 378 ornamental sports impact on body image and eating concerns, 192 orthorexia nervosa (ON), 451–​453, 452t ARFID vs., 453 defined, 451 described, 451 diagnostic criteria for, 452, 452t history of, 451–​452, 452t models of, 453 prevalence of, 452–​453 status of research needed to clarify, 453 OSFED. see other specified feeding or eating disorder (OSFED) other specified feeding or eating disorder (OSFED), 3, 438 BED and, 39 diagnosis of, 10 Eating Disorders Workgroup of DSM-​5 on, 39 epidemiology of, 39–​40 NES, 40 PD, 39–​40 overanxious disorder of childhood EDs and, 230 Overcoming Binge Eating, 277, 278, 509 in SH for EDs, 352–​353 “Overcoming Bulimia Online,” 509 overconsumption chronic tendency toward, 140–​146 greater anticipatory food reward in, 141–​144 greater consummatory food reward in, 140–​141 greater impulsivity in, 144–​145 origins of, 140–​146 overeating BN and, 460 during negative affect, 161–​164 oxytocin for AN, 361t, 367 for BN, 373

P

pain alleviation of fatty food in, 160 painful affects IPT in encouraging acceptance of, 298 paper-​and-​pencil assessments mobile assessments vs. bias in self-​report of, 498 parent(s) as “generally the worst attendants,” 319

as “particularly pernicious,” 319 role in AN history of, 319 pathological gambling, 234 Pathway to Mindful Eating, 342, 342t PD. see purging disorder (PD) peer support/​school-​based programs EDs–​related, 258–​259 peptide(s) opioid AN and BN and, 50–​51, 54t peptide YY (PYY) AN and BN and, 51, 54t perfectionism AN and, 236–​238 OCD and, 237 peripheral nervous system AN effects on, 224 persistence AN and, 237 personal costs EDs–​related, 410–​411 personality EDs and relationships between, 238 personality disorders classification of, 235 clusters of, 235 defined, 235 diagnosis of, 235 EDs and, 235–​236 types of, 235–​236 personality traits EDs and, 236–​240 affect regulation, 238–​239 cognitive processes, 239–​240 RDoC components, 236 temperament, 236–​238 PET. see positron emission tomography (PET) PET-​O15 defined, 68 PFC. see prefrontal cortex (PFC) pharmacotherapy CBT vs. for BED, 276 of EDs, 359–​394 AN, 360–​368, 361t BED, 375–​382, 376t BN, 368–​375, 370t future directions in, 384–​385 introduction, 359 NES, 382 rationale for, 359–​360 research studies’ conclusions, 382–​383 phenotype(s) defined, 81 phentermine for BED, 379 phenylthiocarbamide (PTC) heritability of, 429 phenytoin

for AN, 368 for BED, 380 phobia(s) treatment for exposure and response prevention in, 433 physical exercise CBT with in BN management, 130 pica diagnosis of, 10 picking after bariatric surgery, 463 picky eating, 419–​437. see also selective eating (SE) plugging after bariatric surgery, 465 political-​economic variables impact on body image and eating concerns, 189–​191 polymorphism(s) described, 81 Positive and Negative Affect Scale, 339 positive mood endogenous opioid neuropeptides and, 159–​160 positive predictive value (PPV) of screening tests, 212 positive valence systems EDs and, 27 positron emission tomography (PET) studies in AN and BN, 58 anxiety and harm avoidance correlated with, 57–​58 appetitive regulation–​related, 61–​62 posterior orbitofrontal cortex (OFC), 59 PPV. see positive predictive value (PPV) practice(s) impact on body image and eating concerns, 191–​193 preference(s) decided in SE, 426 prefrontal cortex (PFC) medial, 59 “preoccupations of relatives,” 319 prevention defined, 247–​248 of EDs, 247–​270 (see also ED prevention; ED prevention programs) causative issues and, 248 current status and underlying theory, 247–​270 foundation of, 248 introduction, 247 harm reduction in, 248–​249 programs for (see prevention programs) theory of, 248–​249 prevention programs. see also ED prevention programs

categories of, 247–​248 indicated, 248 risk factor reduction in, 248 risk factors informing, 249 StudentBodies program (see StudentBodies program) theory for, 248–​249 Price Foundation consortia, 98 Price Foundation Genetic Studies of Eating Disorders, 234 privacy of mobile devices and apps for EDs, 499 proanorexia websites for, 262–​263 problem areas described, 313 problematic eating behaviors (EBs) after bariatric surgery, 462–​464 chewing and spitting, 464 emotional eating, 463 grazing, 462–​463 high-​calorie fluid consumption, 463 picking and nibbling, 463 sweet eating, 463–​464 probulimia websites for, 262–​263 pro–​eating disorder websites, 193 prokinetics for AN, 361t, 365–​366 for BN, 375 PROP. see 6-​npropylthiouracil  (PROP) 6-​npropylthiouracil (PROP) heritability of, 429 proxy risk factor, 136 “ProYouth,” 512 Pseudo Bartter’s syndrome, 226 psychiatric disorder criteria for, 438 Psychiatric Genomics Consortium Eating Disorders Working Group of, 99 Psychiatric Status Rating Scale for Bulimia Nervosa, 371 psychoeducation in ED prevention programs, 250 for EDs apps for, 496 psychoeducational videotapes in SH for EDs, 353 psychological assessment of EDs, 211–​221 (see also assessment(s), of EDs) psychological comorbidity of EDs, 229–​243, 231t–​233t (see also specific disorders and eating disorder(s) (EDs), psychological comorbidity of ) psychosis(es) CRT for, 396 psychosocial impairment SE and, 423

psychosocial risk factors for EDs, 106–​125 (see also specific types and risk factors, for EDs) psychotherapy interpersonal (see interpersonal psychotherapy (IPT)) via Internet-​based interventions, 507–​508 PTC. see phenylthiocarbamide (PTC) public health/​policy ED prevention and, 261–​262 purging behavior BN and, 225–​226 purging disorder (PD), 438, 445–​448 on continuum with other EDs, 447–​448 course of, 40 defined, 445 described, 39–​40, 445–​446 as distinct axis I psychiatric disorder, 446–​447 epidemiology of, 40, 446 history of, 445–​446 models of, 446–​448 evidence of diagnostic validity and clinical significance of, 448 prevalence of, 40, 446 purging methods in, 446 status of research needed to clarify, 448 synonyms for, 445–​446 validity and clinical utility of, 445–​446 purging-​only syndrome. see purging disorder (PD) pyromania, 234 PYY. see peptide YY (PYY)

Q

QALYs. see quality-​adjusted life years (QALYs) quality-​adjusted life years (QALYs), 414 question(s) exploratory in IPT for EDs, 298

R

race as factor in body image and eating concerns, 196–​198 racial/​ethnic minorities ED prevention in, 261 racial issues in CBT for EDs, 282 radically open-​DBT (RO-​DBT), 339 radioligand defined, 68 randomized controlled trials (RCTs) of CBT for BN, 274 of CRT for AN, 397 of CRT for EDs, 397–​399 of GSH via Internet-​based interventions, 509

Index

541

randomized controlled trials (RCTs) (cont.) of psychotherapy via Internet-​based interventions, 507–​508 of StudentBodies via Internet-​based interventions for EDs, 511 RCI. see reliable change index (RCI) RCTs. see randomized controlled trials (RCTs) RDoC. see research domain criteria (RDoC) Reading the Mind in the Eyes, 28 “Real Beauty Sketches” ad, 262 rebellion alternate in BED and BN management, 343 reboxetine for BED, 377 recontextualization in approach to disgust, 433 recovery thresholds for in EDs assessment, 214–​215 Recovery Record, 494–​497, 499 Red Book, 413 refeeding hypophosphatemia AN and, 223 Reflections program, 256 reflux acid BN and, 225 regional cerebral blood flow defined, 68 regional cerebral blood flow studies in appetitive regulation in AN and BN, 61–​62 regional trends from cross-​cultural cataloging to global systems as factor in body image and eating concerns, 199–​202 regulatory systems EDs and, 29 relamorelin for AN, 361t, 367 relationship(s) therapeutic in IPT for EDs, 299 relative dietary restriction absolute dietary restriction vs., 136 reliable change index (RCI), 214–​215 religious rituals and beliefs impact on body image and eating concerns, 191–​192 research domain criteria (RDoC). see also research domain criteria (RDoC) project impact on conceptualization of EDs, 1, 24–​33 alternatives to, 30 arousal and regulatory systems, 29 benefit of, 25–​26

542

Index

challenges of, 29–​30 cognitive systems, 27–​28 described, 25–​29 domains in, 25 future directions in, 30–​31 introduction, 24 negative valence systems, 26–​27 positive valence systems, 27 social processes, 28–​29 introduction, 24 of NIMH, 17 impact on conceptualization of EDs, 1 on personality traits, 236 recent changes related to, 2 research domain criteria (RDoC) project. see also research domain criteria (RDoC) goal of, 24 introduction, 24 structure of, 25 response inhibition norepinephrine in, 240 restrained eating emotional eating vs., 162 restraint(s) cognitive overeating during stress related to, 162 dietary researcher’s use of measures in, 134–​136 vs. dieting, 127 Restraint Scale (RS), 134 restriction(s) dietary relative vs. absolute, 136 reward(s) alterations in responses to in EDs, 64–​65, 65f DA in “wanting” of, 160–​161 food (see food reward) sensory emotion effects of neural substrates shared by, 159–​161 “reward deficiency syndrome,” 160 Rey-​Osterrieth Complex Figure Test, 405–​406 rimonabant for BED, 379 RiseUp, 494–​496 risk factor(s) for EDs, 106–​125 (see also specific types and disorders) AN, 107, 111, 112, 117 BED, 111, 118–​119 BN, 111, 117–​118 dieting, 126–​154 (see also dieting) EDNOS, 119 future directions in, 122–​123 interactions between, 120–​121 introduction, 106–​107

longitudinal studies’ characteristics, 107–​111, 108t–​110t prevention programs in reducing, 248 research limitations related to, 111–​112 research update (2002-​2015) on, 112–​ 120, 113t–​116t results from register studies, 119–​120 in specific settings and special populations, 260–​263 study characteristics, 112–​117, 113t–​116t study criteria, 107 study method, 107, 112–​117, 113t–​116t substance abuse and dependence, 161 in informing ED prevention programs, 249 proxy, 136 risperidone for AN, 361t, 364 ritual(s) in Judaism fasting as part of, 201 religious impact on body image and eating concerns, 191–​192 RO-​DBT. see radically open-​DBT (RO-​DBT) role disputes interpersonal, 289 IPT for, 294t, 295 role transitions, 289 IPT for, 294–​295, 294t ropiramate for AN, 368 for BN, 370t, 372–​373 Rosenberg Self-​Esteem Scale, 328 Roux-​en-​Y gastric bypass (RYGB) prevalence of, 458 Royal Children’s Hospital, Melbourne, 324 RS. see Restraint Scale (RS) rumination disorder diagnosis of, 10–​11 RYGB. see Roux-​en-​Y gastric bypass (RYGB)

S

“Salut BED/​Salut BN,” 509 Samoa nonfat muscularity among young men in, 200 Samsung, 494 satiety in EDs fMRI studies of, 63 scalability of CBT for EDs, 282–​283 “scape(s)” described, 200–​201 SCID. see Structured Clinical Interview for DSM-​IV (SCID) Science, 473 SCOFF

in EDs assessment, 212–​213, 216–​217 screening for EDs assessment-​related, 212–​213 PPV–​related, 212 prevention-​related, 249–​250 self-​report questionnaires in, 217 SE. see selective eating (SE) secondary domains in EDs assessment, 214 selective eater(s) defined, 419 selective eating (SE), 419–​437 behavioral features associated with, 425–​427 decided preferences, 426 food neophobia, 425 food refusal/​conflict around food, 426 slowness in eating, 426–​427 criteria of, 419 defined, 419–​421 described, 419–​420 disgust and evaluative conditioning in, 432–​434, 432f disgust experience in, 432–​434, 432f duration of, 421–​424 essential features of, 424–​425 family meals compromised by, 423 food variety in, 424–​425 frequency threshold of severity in, 420–​421 growing out of, 435–​436 introduction, 419 management of, 434–​436, 434t mealtime environment in, 434–​435, 434t medical, 434 sensory-​based exposures in, 435 values clarification in, 435 nature of, 420–​421 persistence of predictors of, 424 phenomenology of, 427–​434, 428f, 430f, 432f disgust experience, 427–​429, 428f sensory sensitivities, 427–​434 (see also sensory sensitivities, in phenomenology of SE) prevalence of, 420 psychosocial impairment resulting from, 423 putative model of, 429, 430f severity of threshold for, 420–​421 stunted growth related to, 422 synonyms for, 419 selective serotonin reuptake inhibitors (SSRIs) for BED, 376t, 377 self-​directedness low EDs and, 238

self-​help (SH) for EDs, 351–​358 described, 352 future directions in, 355–​356 Getting Better Bit(e) by Bit(e) in, 353 introduction, 351–​352 Overcoming Binge Eating in, 352–​353 psychoeducational videotapes in, 353 systematic reviews and meta-​analyses related to, 353 treatment predictors, moderators, and mediators of, 354 guided (see guided self-​help (GSH)) unguided via Internet-​based interventions, 508–​510 self-​induced vomiting BN and, 225–​226 self-​monitoring of EDs self-​report questionnaires for, 218 Self-​Regulatory Executive Function Model, 450 self-​report measures of CRT for EDs, 402 self-​report questionnaires in EDs assessment, 217–​218 diagnosis-​related, 217 screening-​related, 217 self-​monitoring–​related, 218 test meals–​related, 218 treatment planning and evaluation–​ related, 217–​218 semistructured interviews in EDs assessment, 216 sense of presence VR and, 471 sensitized social environment SE and, 431–​432 sensory-​based exposures in SE management, 435 sensory reward neural substrates shared by emotion effects of, 159–​161 sensory sensitivities in phenomenology of SE disgust experience, 430f executive functioning and, 431 medical conditions and, 430–​431 potentiation of emotional experience related to, 430 sensitized social environment and, 431–​432 in SE, 427–​434 separated family therapy (SFT) in FBT-​AN, 321 sequential multiple assignment for randomized treatment (SMART), 355 serotonin defined, 81 EDs related to, 55–​58

serotonin norepinephrine reuptake inhibitors (SNRIs) for BN, 371–​372 serotonin receptor binding alterations in EDs, 56–​58 sertraline for NES, 382 set-​shifting, 239, 396 of CRT for EDs, 403t, 404 examples of, 403t set-​shifting tasks DA in, 240 “Set Your Body Free,” 511 sexual minorities ED prevention in, 261 sexual objectification repeated experiences of, 480 SFT. see separated family therapy (SFT) SG. see sleeve gastrectomy (SG) SH. see self-​help (SH) short-​term caloric restriction relationship to laboratory-​based eating experimental studies of, 128–​129 SIAB. see Structured Interview for Anorexia and Bulimia Nervosa (SIAB) SIAB-​S. see Structured Interview for Anorexic and Bulimic Syndromes Survey (SIAB-​S) sialadenosis, 225 sibutramine for BED, 376t, 379 sick role described, 313 diagnosis and assignment of in IPT for EDs, 290, 291t Simmons Behavior Checklist, 119 single photon emission computed tomography (SPECT) studies of appetitive regulation in AN and BN, 61–​62 skin AN effects on, 225 sleep disorders NES and, 442 sleep-​related eating disorder (SRED), 442 NES and, 442 sleeve gastrectomy (SG) prevalence of, 458 slowness in eating in SE, 426–​427 SMART (sequential multiple assignment for randomized treatment), 355 smartphones, 493 SMA syndrome. see superior mesenteric artery (SMA) syndrome SNRIs. see serotonin norepinephrine reuptake inhibitors (SNRIs) social communication as primary function of emotion, 431–​432 social environment sensitized disgust experience and, 431–​432

Index

543

social learning theory in ED prevention programs, 250–​251 social processes EDs and, 28–​29 social threat stimuli attentional biases to, 240 sociocultural factors described, 187–​189 effects on body image and EDs, 187–​208 (see also culture) socioeconomic status to upward mobility as factor in body image and eating concerns, 198–​199 sodium oxybate for BED, 382 SPECT. see single photon emission computed tomography (SPECT) spironolactone for BN, 375 spitting after bariatric surgery, 464 sports ornamental impact on body image and eating concerns, 192 sports subcultures impact on body image and eating concerns, 191–​192 SRED. see sleep-​related eating disorder (SRED) SSRIs. see selective serotonin reuptake inhibitors (SSRIs) Stanford DBT model, 338–​339, 341–​343, 342t, 344t–​346t adaptations for, 341 to treatment hierarchy, diary card, and behavioral chain analysis, 342–​343, 342t, 344t–​346t background of, 341 described, 341 sequence of treatment in, 342 structure of treatment in, 341–​342 Stanford DBT model diary card, 343, 344t–​346t Stanford dosage study in FBT-​AN, 323 Stanford-​Washington University StudentBodies studies of, 256–​258 Stanford-​Washington University Eating Disorder Screen (SWED), 250 starvation brain effects of, 47–​48 stepped care treatment for EDs, 351–​358 components of, 351–​358 future directions in, 355–​356 models of, 355 studies of, 354–​355 Stop Binge Eating, 496 stress in DA reduction, 161 overeating during

544

Index

cognitive restraint and, 162 susceptibility to comfort eating related to, 162–​163 sweet taste effects on, 159–​160 striatocortical loops monoamines in functioning of, 240 Structured Clinical Interview for DSM-​IV (SCID), 117–​118 Structured Interview for Anorexia and Bulimia Nervosa (SIAB), 371 Structured Interview for Anorexic and Bulimic Syndromes Survey (SIAB-​S), 449 “Student2Bodies–​BED, “ 511 StudentBodies program, 248, 250, 254, 256–​ 258, 263, 511, 513 Stanford-​Washington University studies of, 256–​258 stunted growth SE and, 422 subcultural groups impact on body image and eating concerns of college campus, 192 gay male subcultures, 194 Internet-​based groups, 193 job subcultures, 192 lesbians, 194 shared behaviors among, 191–​192 sports, 191–​192 subculture(s) described, 191 impact on body image and eating concerns, 191–​194 gay male–​related, 194 Internet-​based groups, 193 sports-​related, 191–​192 subjective bulimia nervosa. see purging disorder (PD) substance abuse and dependence EDs and, 161 substance abuse disorders EDs and, 230, 233–​234 suicide AN and, 36 BED and, 39 BN and, 38 suicide attempt(s) AN and, 36 BED and, 39 BN and, 38 superior mesenteric artery (SMA) syndrome AN and, 223 suppressed affect IPT in helping patient experience, 298 SWED. see Stanford-​Washington University Eating Disorder Screen (SWED) Swedish Twin Registry, 442 sweet eating after bariatric surgery, 463–​464 sweet taste

stress-​reducing effect of, 159–​160 symbolic body capital described, 195 impact on body image and eating concerns, 195–​196 synthetic egocentric experience, 482

T

TA. see taxometric analysis (TA) TakeControl, 495 targeted or selective prevention interventions, 248 TAS. see Toronto Alexithymia Scale (TAS) task-​shifting, 281 taste(s) sweet stress-​reducing effect of, 159–​160 taxometric analysis (TA) in ED classification, 11–​12 taxonomy defined, 9 TBPSP. see thin body preoccupation and social pressure to be thin (TBPSP) TCI. see Temperament and Character Inventory (TCI) TDM. see three-​dimensional model (TDM) technological advancements globalization and, 201–​202 technology(ies) in EDs treatment, 522–​523 embodied VR as, 473 temperament as factor in EDs, 236–​238 Temperament and Character Inventory (TCI), 237 test meals self-​report questionnaires for, 218 testosterone for AN, 361t, 366–​367 for BN, 373 TFEQ-​R. see Three-​Factor Eating Questionnaire Restraint Scale (TFEQ-​R) The (Group) Embedded Figures Task ([G]‌EFT), 405 theory(ies) AL, 481, 481f biosocial (see biosocial theory) dieting of eating pathology, 127–​128 dissonance in ED prevention programs, 251 of ED prevention interventions, 250–​ 252 (see also specific types and ED prevention, theories and models of interventions in) feminist in ED prevention programs, 251 interpersonal of IPT, 287–​288 objectification, 480 of prevention, 248–​249

social learning in ED prevention programs, 250–​251 transdiagnostic of EDs, 252 therapeutic relationship in IPT for EDs, 299 therapeutic stance in IPT for EDs, 295 thin body preoccupation and social pressure to be thin (TBPSP), 120–​121 threat stimuli social and angry attentional biases to, 240 three-​dimensional model (TDM) of EDs, 13–​16, 14f Three-​Factor Eating Questionnaire Restraint Scale (TFEQ-​R), 134, 135 thresholds for recovery in EDs assessment, 214–​215 topiramate for BED, 376t, 379–​381 for NES, 382 Toronto Alexithymia Scale (TAS), 176 toy(s) marketing of impact on body image and eating concerns, 195 Trail Making Task, 404–​405 training-​as-​usual in dissemination and implementation of CBT, 283 trait anxiety AN and, 237 transdiagnostic model of EDs, 15–​16 transdiagnostic theories of EDs, 252 transnational connection routes of, 200–​201 treatment phases described, 313 trichotillomania, 234 twin studies of AN and BN, 48, 81 of EDs, 3 of gene–​environment interplay, 86–​98 described, 86, 96–​97, 97t developmental changes related to, 97–​98 heritability estimates in, 86–​92, 88t–​ 91t, 93t–​95t introduction, 86 shared latent risk factors between two or more different phenotypes in, 92, 96

U

UFED. see unspecified feeding or eating disorder (UFED) UK Office of Health Economics, 412 ulcer(s) decubitus

AN and, 225 underlying theoretical assumptions in EDs assessment, 213–​214 unguided self-​help (SH) via Internet-​based interventions, 508–​510 United Arab Emirates body image in, 201 universal prevention program, 247–​248 University of California, San Francisco, 494 unspecified feeding or eating disorder (UFED), 438 diagnosis of, 10 unstructured interviews in EDs assessment, 216 upward mobility from socioeconomic status to as factor in body image and eating concerns, 198–​199 urbanization impact on body image and eating concerns, 190 urge surfing in BED and BN management, 343

V

vagal nerve splanchnic branch of VNS of, 158 vagal nerve activity BN and depression related to, 158–​159 vagal nerve stimulation (VNS) artificial cervical in depression management, 158 of splanchnic branch of vagus nerve in obesity management, 158 valproate for AN, 368 for BED, 381 for BN, 372 value(s) embedded in AI, 499 positive predictive of screening tests, 212 values clarification in SE management, 435 Veterans’ Administration data on per-​patient financial costs of EDs, 411 Veterans Affairs IPT training program, 312 Veterans Health Administration, 312 “VIA,” 510 videoconferencing technology in dissemination and implementation of CBT, 283 videotape(s) psychoeducational in SH for EDs, 353 Virginia Twin Registry albeit one study, 87 virtual reality (VR), 470–​491

body image disturbances–​related, 478–​484, 481f (see also body image disturbances, VR in) components of, 471, 472t defined, 470–​471, 473 described, 470–​471 for EDs, 470–​491 CET, 475–​478 effectiveness of, 474–​475 as embodied technology, 473 history of, 470 introduction, 470 limitations of, 474–​475 sense of presence in, 471 from virtual to real bodies, 473–​474 virtual worlds, real emotions in, 471–​473 virtual reality (VR)–​CET (VR-​CET) for EDs, 475–​478 Virtual Reality Environments for the Psycho-​neuro-​physiological Assessment and Rehabilitation Project (VREPAR), 470, 480 virtual reality (VR) systems commercially available fully immersive prices and characteristics of, 471, 472t virtual worlds, real emotions in VR, 471–​473 VNS. see vagal nerve stimulation (VNS) vomiting after bariatric surgery, 464–​465 in PD, 446 self-​induced BN and, 225–​226 VR. see virtual reality (VR) VR-​CET. see virtual reality (VR)–​CET (VR-​CET) VREPAR (Virtual Reality Environments for the Psycho-​neuro-​physiological Assessment and Rehabilitation Project), 470, 480 vulnerability emotional defined, 334–​335

W

WAIS-​R. see Wechsler Adult Intelligence Scale (WAIS-​R) WCEDCA. see Workgroup for Classification of Eating Disorders in Children and Adolescents (WCEDCA) WCS. see Weight Concerns Scale (WCS) WCST. see Wisconsin Cart Sort Test (WCST) weak central coherence defined, 239–​240 “Web-​centered training” in dissemination and implementation of CBT, 283 website(s) pro–​eating disorders, 193, 262–​263

Index

545

Wechsler Adult Intelligence Scale (WAIS-​R), 402, 405 Weight Concerns Scale (WCS), 249–​250 weight gain excessive IPT in prevention of, 305–​310, 308t weight-​loss drugs for BED, 376t, 378–​379 for BN, 370t, 374 weight-​loss interventions BED related to, 130 behavioral vs. CBT, 276 BN related to, 130 group behavioral vs. CBT in overweight BED persons, 130 weight-​related problems prevention of

546

Index

IPT development in, 311–​312 Wellcome Trust Case Control Consortium 3 (WTCCC3), 98 Western Australian Pregnancy Cohort (Raine) Study, 119, 447 Whites body image and eating concerns among, 197 WHO. see World Health Organization (WHO) Wisconsin Cart Sort Test (WCST), 404 Workgroup for Classification of Eating Disorders in Children and Adolescents (WCEDCA), 19 World Health Organization (WHO), 199 WTCCC3. see Wellcome Trust Case Control Consortium 3 (WTCCC3)

Y

Yale-​Brown-​Cornell Eating Disorder Scale (YBC-​EDS) rituals score, 239, 363 YBC-​EDS rituals score. see Yale-​Brown-​ Cornell Eating Disorder Scale (YBC-​EDS) rituals score Yoga Journal, 451 younger children IPT for adaptations of, 311

Z

zinc for AN, 361t, 366 zonisamide for BED, 376t, 380