The Oxford Handbook of Mood Disorders [Hardcover ed.] 0199973962, 9780199973965

Citation preview

 

The Oxford Handbook of Mood Disorders

 

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

editor-​in-​chief Peter E. Nathan 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

Editor in Chief

PSYCHOLOGY

peter e. nathan

The Oxford Handbook of Mood Disorders Edited by

Robert J. DeRubeis Daniel R. Strunk

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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 2017 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: DeRubeis, Robert J., editor. | Strunk, Daniel R., editor. Title: The Oxford handbook of mood disorders / edited by Robert J. DeRubeis and Daniel R. Strunk. Other titles: Handbook of mood disorders Description: Oxford ; New York : Oxford University Press, [2017] | Series: Oxford library of psychology series | Includes bibliographical references and index. Identifiers: LCCN 2017002688 (print) | LCCN 2017005222 (ebook) | ISBN 9780199973965 (hardcover) | ISBN 9780199973972 (updf ) | ISBN 9780190671754 (epub) Subjects: LCSH: Affective disorders—Handbooks, manuals, etc. Classification: LCC RC537 .O97 2017 (print) | LCC RC537 (ebook) | DDC 616.85/27—dc23 LC record available at https://lccn.loc.gov/2017002688 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

Oxford Library of Psychology  vii About the Editors  ix Contributors xi Contents xvii Chapters 1–498 Index 499

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O X F O R D L I B R A R Y O F   P S YC H O L O G Y

The Oxford Library of Psychology, a landmark series of handbooks, is published by Oxford University Press, one of the world’s oldest and most highly respected publishers, with a tradition of publishing significant books in psychology. The ambitious goal of the Oxford Library of Psychology is nothing less than to span a vibrant, wide-​ranging field and, in so doing, to fill a clear market need. Encompassing a comprehensive set of handbooks, organized hierarchically, the Library incorporates volumes at different levels, each designed to meet a distinct need. At one level is a set of handbooks designed broadly to survey the major subfields of psychology; at another are numerous handbooks that cover important current focal research and scholarly areas of psychology in depth and detail. Planned as a reflection of the dynamism of psychology, the Library will grow and expand as psychology itself develops, thereby highlighting significant new research that will have an impact on the field. Adding to its accessibility and ease of use, the Library will be published in print and, later on, electronically. The Library surveys psychology’s principal subfields with a set of handbooks that capture the current status and future prospects of those major subdisciplines. This initial set includes handbooks of social and personality psychology, clinical psychology, counseling psychology, school psychology, educational psychology, industrial and organizational psychology, cognitive psychology, cognitive neuroscience, methods and measurements, history, neuropsychology, personality assessment, developmental psychology, and more. Each handbook undertakes to review one of psychology’s major subdisciplines with breadth, comprehensiveness, and exemplary scholarship. In addition to these broadly conceived volumes, the Library also includes a large number of handbooks designed to explore in depth more specialized areas of scholarship and research, such as stress, health and coping, anxiety and related disorders, cognitive development, or child and adolescent assessment. In contrast to the broad coverage of the subfield handbooks, each of these latter volumes focuses on an especially productive, more highly focused line of scholarship and research. Whether at the broadest or most specific level, however, all of the Library handbooks offer synthetic coverage that reviews and evaluates the relevant past and present research and anticipates research in the future. Each handbook in the Library includes introductory and concluding chapters written by its editor to provide a roadmap to the handbook’s table of contents and to offer informed anticipations of significant future developments in that field. An undertaking of this scope calls for handbook editors and chapter authors who are established scholars in the areas about which they write. Many of the vii

 

nation’s and world’s most productive and best-​respected psychologists have agreed to edit Library handbooks or write authoritative chapters in their areas of expertise. For whom has the Oxford Library of Psychology been written? Because of its breadth, depth, and accessibility, the Library serves a diverse audience, including graduate students in psychology and their faculty mentors, scholars, researchers, and practitioners in psychology and related fields. Each will find in the Library the information they seek on the subfield or focal area of psychology in which they work or are interested. Befitting its commitment to accessibility, each handbook includes a comprehensive index, as well as extensive references to help guide research. Because the Library was designed from its inception as an online as well as a print resource, its structure and contents will be readily and rationally searchable online. Furthermore, once the Library is released online, the handbooks will be regularly and thoroughly updated. In summary, the Oxford Library of Psychology will grow organically to provide a thoroughly informed perspective on the field of psychology, one that reflects both psychology’s dynamism and its increasing interdisciplinarity. Once it is published electronically, the Library is also destined to become a uniquely valuable interactive tool, with extended search and browsing capabilities. As you begin to consult this handbook, we sincerely hope you will share our enthusiasm for the more than 500-​year tradition of Oxford University Press for excellence, innovation, and quality, as exemplified by the Oxford Library of Psychology. Peter E. Nathan Editor-​in-​Chief Oxford Library of Psychology

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Oxford Library of Psychology

 

A B O U T T H E   E D I TO R S

Robert J. DeRubeis Since receiving his PhD in Clinical Psychology at the University of Minnesota in 1983, Rob DeRubeis has been on the faculty in Psychology at the University of Pennsylvania, where he has served as director of Penn’s doctoral training program in clinical psychology, department chair, and associate dean for social sciences. He is the Samuel H. Preston Term Professor in the Social Sciences and Professor of Psychology. He has authored or co-authored over 100 articles and book chapters, with a focus on the processes that cause and maintain disorders of mood, as well as the treatments and treatment procedures that reduce and prevent the return of mood symptoms. His lab is currently developing and testing methods for application in mental health precision medicine. Dr. DeRubeis has received the Senior Distinguished Career Award from the Society for Psychotherapy Research and the Association for Psychological Science’s James McKeen Cattell Award for a lifetime of outstanding contributions to the area of applied psychological research.

Daniel R. Strunk Dan Strunk is Associate Professor of Psychology at The Ohio State University. He obtained his Ph.D. from the University of Pennsylvania in 2004. After completing a post-doctoral fellowship at Vanderbilt University, he joined the faculty at The Ohio State University in 2006 and was promoted to Associate Professor in 2011. Dr. Strunk has authored 35 articles and several book chapters. His work has helped to document and better characterize the pessimistic biases among those with depression. A major focus of his work has been to clarify the processes by which cognitive therapy achieves its effects. This work has highlighted the importance of therapists’ efforts to elicit cognitive change and clients’ efforts to apply the techniques of cognitive therapy on their own. His publications have appeared in, among others, the Journal of Consulting and Clinical Psychology, Behavior Therapy, Behaviour Research and Therapy, and Psychological Medicine.

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CO N T R I B U TO R S

Lyn Y. Abramson Professor Department of Psychology University of Wisconsin–​Madison Madison, Wisconsin, United States Abby D. Adler Research Associate Department of Psychiatry University of Pennsylvania Philadelphia, Pennsylvania, United States Lauren B. Alloy Professor Department of Psychology Temple University Philadelphia, Pennsylvania, United States Jay D. Amsterdam Emeritus Professor Department of Psychiatry University of Pennsylvania Philadelphia, Pennsylvania, United States Paul W. Andrews Assistant Professor of Evolutionary Psychology Department of Psychology, Neuroscience and Behaviour McMaster University Hamilton, Ontario, Canada Joaquin A. Anguera Adjunct Assistant Professor Departments of Psychiatry, Neurology & Physiology University of California, San Francisco San Francisco, California, United States Patricia A. Arean Professor Department of Psychiatry and Behavioral Sciences University of Washington Seattle, Washington, United States

Jacques P. Barber Professor and Dean Gordon F. Derner School of Psychology Adelphi University Garden City, New York, United States Isabelle E. Bauer Instructor Department of Psychiatry and Behavioral Sciences University of Texas Health Science Center at Houston Houston, Texas, United States Wade Berrettini Professor of Psychiatry Department of Psychiatry University of Pennsylvania Philadelphia, Pennsylvania, United States Sarah R. Black Postdoctoral Researcher Department of Psychiatry and Behavioral Health The Ohio State University Columbus, Ohio, United States Claudi L. H. Bockting Professor Department of Clinical Psychology Utrecht University Utrecht, The Netherlands Steven M. Brunwasser Research Instructor Department of Medicine Vanderbilt University Medical Center Nashville, Tennessee, United States Jennifer S. Cheavens Associate Professor Department of Psychology The Ohio State University Columbus, Ohio, United States

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Yulia E. Chentsova-​Dutton Associate Professor Department of Psychology Georgetown University Washington, D.C., United States Carol Chu Graduate Student, Clinical Psychology Department of Psychology Florida State University Tallahassee, Florida, United States Anahi Collado Psychologist Alvord, Baker, and Associates Rockville, Maryland, United States Michael J. Constantino Professor Department of Psychology University of Massachusetts Amherst Amherst, Massachusetts, United States Philip J. Cowen Professor of Psychopharmacology Department of Psychiatry University of Oxford Oxford, United Kingdom Pim Cuijpers Professor of Clinical Psychology Department of Clinical Psychology VU University Amsterdam, The Netherlands Lori F. Cummins Graduate Student, Clinical Psychology Department of Psychology University of Notre Dame Notre Dame, Indiana, United States Catherine D’Avanzato Psychologist Rhode Island Hospital Providence, Rhode Island, United States Robert J. DeRubeis Professor Department of Psychology University of Pennsylvania Philadelphia, Pennsylvania, United States Sona Dimidjian Associate Professor Department of Psychology and Neuroscience University of Colorado at Boulder Boulder, Colorado, United States xii Contributors

Zachary Durisko Postdoctoral Researcher Department of Psychology, Neuroscience and Behaviour McMaster University Hamilton, Ontario, Canada Audrey A. File Graduate Student, Clinical Psychology Department of Psychology University of Tennessee, Knoxville Knoxville, Tennessee, United States Nicholas R. Forand Assistant Professor Department of Psychiatry Hofstra Northwell School of Medicine Hempstead, New York, United States Jay C. Fournier Assistant Professor Department of Psychiatry University of Pittsburgh Pittsburgh, Pennsylvania, United States Ellen W. Freeman Research Professor Department of Obstetrics/​Gynecology University of Pennsylvania Philadelphia, Pennsylvania, United States Mary A. Fristad Professor Department of Psychiatry and Behavioral Health The Ohio State University Columbus, Ohio, United States Judy Garber Professor Department of Psychology and Human Development Vanderbilt University Nashville, Tennessee, United States Mark S. George Professor Department of Psychiatry and Behavioral Sciences Medical University of South Carolina Charleston, South Carolina, United States

 

Anda Gershon Instructor Department of Psychiatry and Behavioral Sciences—​Child and Adolescent Psychiatry Stanford University Stanford, California, United States Suzanne R. Gird Graduate Student, Clinical Psychology Psychology Department Wichita State University Wichita, Kansas, United States Benjamin L. Hankin Professor Department of Psychology University of Denver Denver, Colorado, United States Catherine J. Harmer Professor of Cognitive Neuroscience Department of Psychiatry University of Oxford Oxford, United Kingdom Mark L. Hatzenbuehler Associate Professor Department of Sociomedical Sciences Columbia University New York, New York, United States Steven D. Hollon Professor Department of Psychology Vanderbilt University Nashville, Tennessee, United States Derek R. Hopko Professor Department of Psychology University of Tennessee, Knoxville Knoxville, Tennessee, United States Allan V. Horwitz Professor Department of Sociology Rutgers University New Brunswick, New Jersey, United States Sam Hubley Assistant Professor Department of Family Medicine University of Colorado Denver, Colorado, United States

Marcus J. H. Huibers Professor of Clinical Psychology and Experimental Psychotherapy Department of Clinical Psychology VU University Amsterdam, The Netherlands Sheri L. Johnson Professor Department of Psychology University of California, Berkeley Berkeley, California, United States Thomas E. Joiner, Jr. Distinguished Professor Department of Psychology Florida State University Tallahassee, Florida, United States Suzanne E. Kerns Seattle Neuropsychiatric Treatment Center Seattle, Washington, United States Gabriela Kattan Khazanov Graduate Student, Clinical Psychology Department of Psychology University of Pennsylvania Philadelphia, Pennsylvania, United States Annet M. Kleiboer Assistant Professor Department of Clinical Psychology VU University Amsterdam, The Netherlands Daniel N. Klein Distinguished Professor Department of Psychology Stony Brook University Stony Brook, New York, United States Sophie A. Lazarus Postdoctoral Fellow Department of Psychiatry University of Pittsburgh Pittsburgh, Pennsylvania, United States Carl W. Lejuez Professor Department of Psychology University of Kansas Lawrence, Kansas, United States Eric Lenze Professor Department of Psychiatry Washington University in St. Louis Saint Louis, Missouri, United States Contributors

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Falk W. Lohoff Lasker Clinical Research Scholar Section on Clinical Genomics and Experimental Therapeutics National Institute on Alcohol Abuse and Alcoholism (NIAAA) Bethesda, Maryland, United States Lorenzo Lorenzo-​Luaces Doctoral Candidate, Clinical Psychology Department of Psychology University of Pennsylvania Philadelphia, Pennsylvania, United States Laura MacPherson Graduate Student, Clinical Psychology Department of Psychology University of Maryland College Park, Maryland, United States Jennifer E. McCabe-​Beane Doctoral Candidate, Clinical Psychology Department of Psychological and Brain Sciences University of Iowa Iowa City, Iowa, United States Crystal C. McIndoo Graduate Student, Clinical Psychology Department of Psychology University of Tennessee, Knoxville Knoxville, Tennessee, United States Katie A. McLaughlin Associate Professor Department of Psychology University of Washington Seattle, Washington, United States Kaja J. McMaster Doctoral Candidate, Clinical Psychology Department of Psychology University of California, Berkeley Berkeley, California, United States Matthew S. Michaels Graduate Student, Clinical Psychology Department of Psychology Florida State University Tallahassee, Florida, United States Scott M. Monroe Professor Department of Psychology University of Notre Dame Notre Dame, Indiana, United States xiv Contributors

Brianne M. Newman Associate Professor Department of Psychiatry and Behavioral Neuroscience Saint Louis University School of Medicine Saint Louis, Missouri, United States Elizabeth A. Nick Graduate Student, Clinical Psychology Department of Psychology and Human Development Vanderbilt University Nashville, Tennessee, United States Michael W. O’Hara Professor Department of Psychological and Brain Sciences University of Iowa Iowa City, Iowa, United States Alberta E. Pos Associate Professor Department of Psychology York University Toronto, Ontario, Canada Abigail Pringle Department of Psychiatry University of Oxford Warneford Hospital Oxford, United Kingdom Noreen A. Reilly-​Harrington Assistant Professor of Psychology Department of Psychiatry Harvard Medical School Boston, Massachusetts, United States David A. Richards Professor of Mental Health Services Research Department of Psychology University of Exeter Exeter, United Kingdom Kelly J. Rohan Professor Department of Psychological Science The University of Vermont Burlington, Vermont, United States Jonathan P. Roiser Professor Institute of Cognitive Neuroscience University College London London, United Kingdom

 

Jennifer N. Rough Graduate Student, Clinical Psychology Department of Psychological Science The University of Vermont Burlington, Vermont, United States Ayelet Meron Ruscio Associate Professor Department of Psychology University of Pennsylvania Philadelphia, Pennsylvania, United States Janusz K. Rybakowski Professor Department of Adult Psychiatry Poznan University of Medical Sciences Poznan, Poland Andrew G. Ryder Associate Professor Department of Psychology Concordia University Montreal, Quebec, Canada Barbara J. Sahakian Professor Department of Psychiatry University of Cambridge Cambridge, United Kingdom Rachel H. Salk Graduate Student, Clinical Psychology Department of Psychology University of Wisconsin–​Madison Madison, Wisconsin, United States Katherine E. Sasso Doctoral Candidate, Clinical Psychology Department of Psychology The Ohio State University Columbus, Ohio, United States Yvette I. Sheline Professor Department of Psychiatry University of Pennsylvania Philadelphia, Pennsylvania, United States Richard C. Shelton Professor Department of Psychiatry and Behavioral Neurobiology University of Alabama at Birmingham Birmingham, Alabama, United States

E. Baron Short Associate Professor Department of Psychiatry and Behavioral Sciences Medical University of South Carolina Charleston, South Carolina, United States Jair C. Soares Professor Department of Psychiatry and Behavioral Sciences University of Texas Health Science Center at Houston Houston, Texas, United States Jonathan P. Stange Postdoctoral Fellow Department of Psychiatry University of Illinois at Chicago Chicago, Illinois, United States Daniel R. Strunk Associate Professor Department of Psychology The Ohio State University Columbus, Ohio, United States Tony Z. Tang Visiting Scholar Department of Psychology University of Pennsylvania Philadelphia, Pennsylvania, United States Jerome C. Wakefield Professor, Silver School of Social Work Professor, Department of Psychiatry, School of Medicine New York University New York, New York, United States Jeanne Watson Professor Applied Psychology and Human Development University of Toronto Toronto, Canada Mark A. Whisman Professor Department of Psychology and Neuroscience University of Colorado Boulder Boulder, Colorado, United States

Contributors

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Robert D. Zettle Professor Psychology Department Wichita State University Wichita, Kansas, United States Yue Zhao Doctoral Candidate, Clinical Psychology Department of Psychology Concordia University Montreal, Quebec, Canada Sigal Zilcha-​Mano Assistant Professor Department of Psychology University of Haifa Haifa, Israel

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Mark Zimmerman Professor of Psychiatry and Human Behavior Department of Psychiatry and Human Behavior Brown Medical School Providence, Rhode Island, United States

 

CONTENTS

Part I 

• Overview

1. Introduction  3 Daniel R. Strunk and Robert J. DeRubeis

Part II 

• Phenomenology,

and Assessment

Classification, Epidemiology,

2. History of Depression  11 Allan V. Horwitz, Jerome C. Wakefield, and Lorenzo Lorenzo-​Luaces 3. The Evolution of Depressive Phenotypes  24 Paul W. Andrews and Zachary Durisko 4. Phenomenology and Course of Mood Disorders  37 Daniel R. Strunk and Katherine E. Sasso 5. Sex, Sexual Orientation, and Depression  49 Mark L. Hatzenbuehler and Katie A. McLaughlin 6. Suicide  60 Matthew S. Michaels, Carol Chu, and Thomas E. Joiner, Jr. 7. Disordered Mood in Cultural-​Historical Context  71 Andrew G. Ryder, Yue Zhao, and Yulia E. Chentsova-​Dutton 8. Uncomplicated Depression as Normal Sadness: Rethinking the Boundary Between Normal and Disordered Depression  83 Jerome C. Wakefield, Allan V. Horwitz, and Lorenzo Lorenzo-​Luaces 9. The Diagnosis and Assessment of Mood Disorders  95 Catherine D’Avanzato and Mark Zimmerman

Part III 

• 

Etiological, Vulnerability, and Risk Factors

10. Genetics of Bipolar and Unipolar Disorders  111 Wade Berrettini and Falk W. Lohoff 11. Environmental Risk and Protection in Unipolar Depression  120 Scott M. Monroe and Lori F. Cummins 12. Environmental Risk and Protective Factors in Bipolar Disorder  132 Sheri L. Johnson, Anda Gershon, and Kaja J. McMaster 13. Cognitive Vulnerability and Unipolar Depression  142 Lauren B. Alloy, Rachel H. Salk, Jonathan P. Stange, and Lyn Y. Abramson 14. Personality and Depression  154 Jay C. Fournier and Tony Z. Tang xvii

 

Part IV 

• 

Interpersonal and Intra-​individual Processes

15. Interpersonal Perspectives on Depression  167 Mark A. Whisman 16. Information Processing in Mood Disorders  179 Jonathan P. Roiser and Barbara J. Sahakian 17. Neuroendocrine and Neurochemical Processes in Depression  190 Philip J. Cowen 18. Neuropsychological Mechanisms of Depression and Treatment  201 Abigail Pringle and Catherine J. Harmer 19. Neural Structure and Organization of Mood Pathology  214 Brianne M. Newman, Isabelle E. Bauer, Jair C. Soares, and Yvette I. Sheline

Part V 

• 

Subtypes and Subpopulations

20. Persistent Depressive Disorder  227 Daniel N. Klein and Sarah R. Black 21. Premenstrual Dysphoric Disorder  238 Ellen W. Freeman 22. Seasonal Affective Disorder  254 Kelly J. Rohan and Jennifer N. Rough 23. Postpartum Mood Disorders  266 Jennifer E. McCabe-​Beane and Michael W. O’Hara 24. Depression During Childhood and Adolescence  276 Benjamin L. Hankin 25. Bipolar Disorder During Childhood and Adolescence  287 Mary A. Fristad and Elizabeth A. Nick 26. Mood Disorders in Late Life  299 Patricia A. Arean, Eric Lenze, and Joaquin A. Anguera

Part VI 

• 

Common Comorbidities

27. Anxiety and Depression  313 Ayelet Meron Ruscio and Gabriela Kattan Khazanov 28. Personality Disorders and Disorders of Mood  325 Jennifer S. Cheavens and Sophie A. Lazarus 29. Substance Use Disorders and Disorders of Mood  336 Anahi Collado, Laura MacPherson, and Carl W. Lejuez 30. Depressive Syndromes and Medical Comorbidities  348 Derek R. Hopko, Crystal C. McIndoo, and Audrey A. File

Part VII 

• 

Prevention and Treatment of Mood Disorders

31. Prevention of Depression  363 Steven M. Brunwasser and Judy Garber 32. Pharmacological Interventions for Depression  374 Richard C. Shelton

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33. Pharmacotherapy of Bipolar Disorder  385 Jay D. Amsterdam and Janusz K. Rybakowski 34. Brain Stimulation Treatments for Depression  398 Mark S. George, E. Baron Short, and Suzanne E. Kerns 35. Cognitive Therapy of Depression  411 Daniel R. Strunk, Abby D. Adler, and Steven D. Hollon 36. Behavior Therapy of Depression  423 Sam Hubley and Sona Dimidjian 37. Acceptance and Mindfulness-Based Interventions  435 Robert D. Zettle and Suzanne R. Gird 38. Psychodynamic and Interpersonal Psychotherapies  447 Jacques P. Barber, Sigal Zilcha-​Mano, and Michael J. Constantino 39. Humanistic and Experiential Perspectives  459 Jeanne Watson and Alberta E. Pos 40. Self-​Directed Approaches to the Treatment of Depression  469 Pim Cuijpers and Annet M. Kleiboer 41. Toward a Rational Model of Depression Treatment  478 Nicholas R. Forand, David A. Richards, Marcus J. H. Huibers, and Claudi L. H. Bockting 42. Psychosocial Approaches to the Treatment and Prevention of Bipolar Disorder  490 Noreen A. Reilly-​Harrington Index  499

Contents

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PART 

Overview

I

 

 

CH A PT E R

1

Introduction

Daniel R. Strunk and Robert J. DeRubeis

Abstract This volume provides what we believe to be the most comprehensive treatment of the range of mood disorders to date. In this introductory chapter, we present the organization and overarching themes of the volume. The volume’s coverage of mood disorders includes historical, cross-​cultural, developmental, neuroscientific, etiological, and therapeutic issues. Following this introduction (Section I), Section II provides coverage of the phenomenology, classification, and assessment of mood disorders. A key theme of the section, the heterogeneity of mood disorders, is then carried through the volume. Section III addresses key etiologic, vulnerability and risk factors. Section IV covers key interpersonal and intra-​personal factors, with several chapters focusing on neurobiological features. Section V examines variants of mood disorders as well as key sub-​populations. Section VI addresses common comorbidities. Finally, Section VII surveys the wide array of commonly used and evidence-​based treatment and prevention approaches. Key Words:  mood disorders, depression, bipolar disorder, etiology, treatment

Introduction

Mood disorders are common, sometimes debilitating, mental health conditions with considerable societal costs. These disorders include unipolar depression, bipolar disorder, and several variants of these disorders. In industrialized nations, depression alone ranks among the leading causes of disability. Bipolar disorder, while less common, is associated with even more marked impairments. Given the scope of the problem presented by mood disorders, it is understandable that there has been a wealth of research into the causes, consequences, and treatments for these disorders. Although we still have much to learn, the existing body of research on mood disorders is vast and ever-​growing. With this handbook, we provide comprehensive and detailed coverage of historical and modern developments in the characterization, understanding, and treatment of mood disorders. We believe

it is the most comprehensive volume ever published in this area. The chapters have been written by the world’s leading experts in their respective areas. We believe it will serve as an excellent in-​depth introduction to the mood disorders. For established researchers and clinicians, it will serve to round out their existing knowledge with comprehensive, up-​ to-​date coverage. Following this introduction (Section I), the handbook is organized into six sections. Section II:  Phenomenology, Classification, Epidemiology, and Assessment includes eight chapters. One of the themes of the book that comes through clearly in this section is the tremendous heterogeneity evident in the mood disorders. Chapter 2 traces the history of various approaches to conceptualizing the heterogeneity of depressive conditions. The authors highlight the surprisingly strong influence of the Feighner criteria, arguing that, although they had been presented as

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tentative and were based on rather limited empirical evidence, they became the basis of the criteria for depression presented in The Diagnostic and Statistical Manual of Mental Disorders III (DSM-​III) and carried forward to today. Chapter 3 considers depression from an evolutionary perspective, with the authors arguing that depression can be understood in the context of three phenotypes: sickness behavior, starvation depression, and melancholia. In Chapter 4, the authors provide an overview of the DSM-​5 approach to capturing the heterogeneity of mood disorders, and they highlight some of the differences between DSM-​IV and DSM-​5. One of the controversies they consider concerns the degree to which evidence of low levels of manic symptoms is important for a valid system of classification of mood disorders. Chapter 5 considers mood disorders across sexes and across people of different sexual orientations. The authors offer careful consideration of the various factors that are thought to give rise to differences in the experiences of mood disorders across these groups. In Chapter  6, the authors discuss suicide, a tragic outcome for which those with mood disorders are at an increased risk. In reviewing the risk factors for suicide, the authors make the case that the acquired capability to enact lethal self-​injury is an important, though overlooked, risk factor. In Chapter 7, the authors consider the importance of cultural contexts in the mood disorders. One of the differences the authors highlight is the presence, degree, and type of stigma regarding psychological disorders, and how this can be important to appreciate, both for assessment and for treatment. In Chapter 8, the authors develop the thesis that the disproportionality of one’s depressive symptoms in relation to environmental stresses is key to understanding the heterogeneity among those with mood disorders. The authors review a program of research suggesting that disproportionate or complicated depression differs in important ways from depression that can be understood as a normal reaction to environmental stress. Chapter  9, the final chapter in this section, covers the diagnosis and assessment of mood disorders. The authors argue that, despite substantial evidence that the use of standardized assessment measures increases diagnostic accuracy, they remain little-​utilized in most clinical settings. Across the chapters in this section, the considerable range of severity of depression is striking. These chapters provide a strong foundation, from a variety of perspectives, to understand the sources of heterogeneity, as well implications for mental health research and practice. 4 Introduction

In Section III:  Etiologic, Vulnerability, and Risk Factors, five chapters provide coverage of what is known regarding relevant genetic, environmental, cognitive, and premorbid personality factors. In Chapter  10, the authors review evidence regarding the role of genetics in the mood disorders. They provide an estimate of heritability in the range of 65–​80% for bipolar disorders and of approximately 40% for unipolar disorders. In c­hapters  11 and 12, the authors consider the role of environmental factors in depression and bipolar disorders, respectively. In the chapter on depression, the authors suggest there may be differences in the predictors of future episodes of depression, depending on the prior number of episodes already experienced by an individual. In Chapter  12, the authors review evidence regarding the role of the quality of one’s social interactions in the prediction of the onset and course of bipolar disorders. In Chapter 13, the authors describe the theory and evidence regarding the role of cognitive vulnerability in the development of depression. They provide an overview of findings from their own compelling prospective study showing that participants with high cognitive vulnerability are at greater risk for a first onset of depression than are those low in cognitive vulnerability. In Chapter 14, the authors consider the relation of personality to mood disorders, focusing especially on the dimensions of neuroticism and extraversion. They highlight an intriguing finding from a randomized trial comparing a serotonin reuptake inhibitor and a placebo. In that trial, the medication produced large changes in neuroticism not observed in the placebo condition. In fact, the difference observed in neuroticism was larger than that observed in depressive symptoms, leading the authors to consider the possibility that antidepressants might be better named “personality normalizers.” The chapters in this section make it clear that a complex combination of genetic and environmental risk factors is important in understanding the development of mood disorders. In Section IV: Interpersonal and Intra-​individual Processes, five chapters cover interpersonal and several intra-​individual factors implicated in the mood disorders. These intra-​ individual factors include individual differences in information processing as well as neurochemical and neuroendocrine processes. In Chapter 15, the importance of interpersonal characteristics and the quality of interpersonal relationships are reviewed. Consistent with this view, we learn that improving interpersonal relationships was identified as the most common treatment

 

goal among clients hospitalized for depression. Chapter 16 covers findings from research on information processing in the mood disorders. The authors distinguish “cold” (emotionally independent) and “hot” (emotionally dependent) cognition, arguing for their neuropsychological model, which can be used to understand recent psychopharmacological findings. Chapter  17 reviews neuroendocrine and neurochemical theories of depression, including the still-​dominant monoamine theories, as well as several more recent developments. In Chapter 18, the authors argue for a cognitive neuropsychological model of antidepressant treatment, in which the efficacy of antidepressants can be understood through their impact on neurocognitive factors. In the final chapter of this section, Chapter 19, the authors draw on neuro-​imaging studies to consider structural and functional factors that provide clues about the neural mechanisms of depression. In Section V:  Subtypes and Sub-​ populations, seven chapters cover variants of mood disorders. In Chapter  20, on persistent or chronic forms of depression, we learn about the recent introduction of “persistent depressive disorder” to the DSM, which subsumed the previous categories of “dysthymia” and “chronic forms of major depressive disorder.” In a detailed review of the etiology of chronic depression, the authors highlight key risk factors, most prominently the experience of maltreatment and adversity during childhood. Chapter  21 examines depressive disorders in which depressive symptoms and associated functional impairment occur in relation to menstrual cycles. The authors argue that the use of daily diaries in the assessment of the timing of symptoms across at least two menstrual cycles is a key to facilitating accurate diagnoses. Chapter 22 reviews winter seasonal affective disorder, defined by the experience of recurrent depressive episodes in winter months. The chapter highlights the importance of photoperiod as a key environmental risk factor in this disorder, but the authors also suggest that a more complex integrative approach to understanding risk for first and subsequent episodes of this disorder is needed. In Chapter 23, postpartum mood disorders are examined, including both postpartum depression and the less well-​ studied postpartum bipolar disorder. One intriguing possibility raised by the authors is that women with postpartum bipolar disorder may often be misdiagnosed with postpartum depression, a problem that might be partly accounted for by women with postpartum bipolar disorder tending to experience depressive as opposed to manic episodes in the postpartum period.

In ­chapters 24 through 26, mood disorders are considered from a lifespan perspective. Chapter 24 covers depression in childhood and adolescence. The authors argue that adolescent girls face greater stresses than boys and that this difference is important in understanding sex differences in depression, which first emerge in adolescence. Chapter 25 considers bipolar disorder during these developmental periods. A  controversy over the diagnosis of bipolar disorder in children is laid out, with a review of the evidence regarding differences in the symptom presentation between youth and adults (e.g., greater rates of psychosis and hypersexuality in adults) as well as a consideration of the degree to which available evidence indicates that these diagnoses persist into adulthood. Chapter 26 considers mood disorders in late life, an increasingly common presentation, given the growing population of older adults. For example, the authors describe vascular depression, an important subtype of depression marked in part by poor cognitive control, which may account for as many as 50% of older adult depression cases. This form of depression appears to respond poorly to selective serotonin reuptake inhibitors (SSRIs), but it responds favorably to behavioral interventions. Across the chapters in this section, there is attention to the classification of variants of mood disorders seen across the lifespan and in specific sub-​populations. In addition, the chapters provide a detailed account of our current understanding of the etiology of these mood disorder presentations, with comments on treatment considerations as appropriate. In Section VI: Common Comorbidities, four chapters address diagnostic and etiological questions related to mood disorders comorbid with anxiety disorders, personality disorders, substance use disorders, and medical conditions. Chapter 27 examines comorbid anxiety and depression, considering the patterns of comorbidity observed and how these patterns can be understood. The authors argue that the field must move beyond describing rates of comorbidity to testing competing causal models capable of accounting for the comorbidity observed. We also learn that certain patterns of comorbidity are associated with greater help seeking, such as those with panic disorder and depression being especially likely to seek treatment. Chapter 28 considers the comorbidity of mood disorders and personality disorders, which is common among those with persistent or recurrent forms of mood disorders. An argument is made for careful training and assessment as the keys to differentiating mood and personality disorders. Strunk, DeRubeis

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In Chapter 29, comorbidity of mood disorders and substance use disorders is considered, with attention to competing models that seek to account for the patterns of comorbidity that are observed. Consistent with the possibility that depression and substance use disorder may co-​ occur because of shared causes, we learn that impulsivity predicts future onsets of each disorder. In Chapter 30, the complex relations between depression and medical conditions such as cancer, cardiovascular disease, multiple sclerosis, and HIV/​AIDS are considered. Although depression has been found to predict cardiac mortality after myocardial infarction, the large Enhancing Recovery in Coronary Heart Disease Patients trial failed to find that depression interventions improved survival times. Across the chapters in this section, authors consider various causal models that could give rise to the patterns of comorbidity observed, and the degree to which each model is consistent with available evidence. The final and largest section of the book, Section VII:  Prevention and Treatment of Mood Disorders, includes twelve chapters that, collectively, represent the wide array of common and evidence-​based treatment and prevention approaches. Chapter 31, on the prevention of depression, highlights the efforts to evaluate prevention programs in various populations. As we learn in the chapter, a meta-​ analytic estimate of the prevention effect suggests that one case of depression is prevented for every 17–​22 people provided a preventive intervention. The next three chapters cover pharmacological and other somatic treatments for depression and bipolar disorders. Chapter  32 reviews pharmacological treatment of depression, with careful consideration of what is known regarding the mechanisms by which these treatments achieve their effects. In addressing the controversy over whether antidepressants increase the risk of suicide, the author suggests that a short-​term increase in suicidal ideation and self-​injury, which appears to result with at least some of the antidepressant medications, must be weighed against longer-​term reductions in risk of suicide. Chapter  33 examines pharmacological treatment of bipolar disorder, considering the use of mood stabilizing and “antidepressant” drugs with various presentations of bipolar disorders. The authors discuss the evidence regarding the risk of a medication-​induced manic episode when treating those with major depressive episodes and evidence of bipolar disorder. Though practice guidelines suggest that antidepressant drugs should be used only in combination with a mood stabilizer, the 6 Introduction

authors argue that antidepressant monotherapy is a safe and effective treatment for bipolar II disorder. Chapter  34 reviews brain-​ stimulation treatments for depression (e.g., electroconvulsive therapy and repetitive transcranial magnetic stimulation), treatments generally reserved for those who have not benefited from other treatment approaches. While effective, the mechanisms of treatments such as electroconvulsive therapy have remained elusive. The authors argue that stimulation methods that do not invoke seizures are less effective than those that do, but they suggest that there are other factors, in addition to the induction of seizures, that account for therapeutic response. Across c­hapters  35 through 39, the authors review influential psychosocial approaches to treating depression: cognitive therapy (CT; Chapter 35), behavior therapy (BT; Chapter  36), acceptance-​ based interventions (including acceptance and commitment therapy and mindfulness-​based cognitive therapy; Chapter  37), interpersonal and psychodynamic therapies (Chapter  38), and humanistic and experiential therapies (Chapter  39). In Chapter  35, we learn that cognitive therapy is an efficacious treatment with enduring effects. The authors describe a debate within the field regarding the interpretation of findings relevant to questions of the mechanisms by which cognitive therapy achieves its effects. They go on to argue that the evidence is consistent with the proposition that CT works through cognitive change, as its developers hypothesized. In Chapter 36, the authors trace the historical roots of behavioral therapies, highlighting the influence of Ferster in the 1970s, who argued that avoidance plays a central role in depression. Also discussed is a proposal, yet to be tested, that BTs can be provided by individuals with less extensive training than is necessary with other psychological treatments. In Chapter  37, acceptance and mindfulness-​based interventions are reviewed. We learn that although-​ mindfulness based cognitive therapy appears to reduce relapse among those with a history of three or more depressive episodes, important questions about its mechanisms remain. In Chapter 38, the authors review one of the most extensively tested treatments for depression, interpersonal therapy. While the developers do not appear to expect strong, enduring effects from this treatment, they have developed maintenance treatment intended to facilitate positive outcomes in the long term. Interestingly, one trial failed to find differences in outcome among weekly, bi-​weekly, or monthly versions of IPT, suggesting that the

 

intensity of maintenance treatment may not be an important determinant of long-​term outcomes. In the final chapter, on psychotherapeutic approaches to treating depression (Chapter  39), the authors review humanistic and experiential therapies. In their discussion of experiential psychotherapy, an argument is made that greater emotional processing has been linked to better therapeutic outcomes in this approach—​a relationship not observed with other forms of treatment. Across these chapters, the authors provide an overview of the therapeutic approaches and a review of the evidence relevant to evaluating the therapeutic benefits of these approaches. Chapter 40 surveys self-​ directed treatment approaches such as internet-​ delivered therapy, a potentially cost-​ effective form of treatment. A key observation that argues for the importance of these approaches in the future is that many people with depression do not seek treatment and prefer to address problems associated with mood disturbance themselves. The authors summarize data indicating that personal support provided by

a coach or therapist enhances the effects of these treatments. Chapter 41 provides a discussion of efforts to develop a coherent, comprehensive, rational model of care for those with mood difficulties. An important challenge of developing such a systematic approach is how to select the best treatment for each individual patient. The authors discuss promising new developments involving the use of multiple predictors to optimize treatment selection. In Chapter 42, psychosocial treatments for bipolar disorder are reviewed. While investigators have focused mostly on testing these treatments as an adjunct to medication, the author highlights a provocative finding of comparable benefit for a mood stabilizer and a psychosocial treatment (i.e., interpersonal social rhythm therapy) among those with bipolar II. Throughout all of the chapters in the Handbook, authors consider future directions to provide readers with a sense of priority research areas and possible advances in our understanding in coming years. We hope you find the handbook informative, comprehensive, and thought provoking.

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PART

Phenomenology, Classification, Epidemiology, and Assessment

II

 

 

CH A PT E R

2

History of Depression

Allan V. Horwitz, Jerome C. Wakefield, and Lorenzo Lorenzo-​Luaces

Abstract The symptoms that define depressive conditions have been recognized for millennia of medical history. The earliest Hippocratic writings not only define depression in similar ways as current works but also use context to differentiate ordinary sadness from depressive disorder. Sadness was understood as a natural reaction to loss; symptoms indicated a disorder only if they were not attributable to an identifiable trigger or if they displayed disproportionate intensity or duration to their triggers. The first serious approaches to subcategorize different types of depressive disorders developed in the seventeenth century. Despite agreement that a melancholic or psychotic form of depression existed, researchers debated the categorization of neurotic or nonpsychotic depressions until 1980 when the DSM-​ III introduced major depression as a unitary category. The DSM’s diagnostic system was historically anomalous because its diagnoses did not consider the context in which symptoms arose. The only exception within the DSM, for uncomplicated symptoms that follow bereavement, was removed from the DSM-​5 in 2013 so that depressive diagnoses now thoroughly conflate adaptive responses to loss with pathological depressions. Key Words:  depression, Hippocrates, DSM-​III, diagnosis, melancholia, melancholy, Emil Kraepelin, Sigmund Freud, major depressive disorder, symptoms

Depression, unlike many conditions in the current psychiatric canon, has a lengthy and readily identifiable history. Indeed, it is perhaps the most easily recognizable psychological disorder throughout history; similar symptomatic descriptions occur over a 2,500-​year span, representing what historian Stanley Jackson (1986, p. ix) calls a “remarkable consistency.” From the earliest medical texts in ancient Greece to the present Diagnostic and Statistical Manual of Mental Disorders (DSM), deep sadness and its variants—​ hopelessness, sorrow, dejection, despondency, emptiness, despair, discouragement—​ have been mentioned as core features of depression. Related symptoms have included aversion to food, sleeplessness, fatigue, irritability, restlessness, fear of death, repetitive focus on a few negative ideas, lack of pleasure or interest in usual activities, and social detachment.

Yet from the advent of psychiatry until the introduction of the DSM-​III in 1980, traditional psychiatry recognized that even intense sadness with its associated “symptoms” can be a normal emotional reaction to life circumstances, and took a contextual approach to the diagnosis of depressive disorder. Its various definitions did not focus on symptoms alone but emphasized that, to be considered as disorders, depressive reactions must be of disproportionate duration or severity to the situation in which they emerged. Whether a condition was diagnosed as disordered depended not just on the symptoms, which might be similar in normal sadness and in pathological depression. It was also not entirely defined by the condition’s severity, for normal sadness can be severe and disordered sadness can be moderate. Instead, the distinction between sadness and depressive disorder depended on the 11

 

degree to which the symptoms were an understandable response to circumstances. This chapter elaborates the history of this contextual approach to depression providing the background for how the definition of depression in the DSM-​III (1980) overturned thousands of years of thinking, replacing the more nuanced contextual approach with relatively precise and communicable symptomatic criteria that largely ignored the complexities of context, with detrimental side effects for psychiatric diagnosis. Worse, the DSM-​5 (American Psychiatric Association, 2013) for the most part eliminated the slim remainder of the contextual tradition—​the bereavement exclusion—​so that the current psychiatric diagnosis of major depression is entirely symptom based. Indeed, the most recent DSMs represent a significant regression from the earliest efforts to define depressive disorder and separate it from normal sadness. Although a symptom-​ based definition of depression might prove to be relatively reliable, this reliability comes at the expense of discriminant validity in distinguishing depressive disorders from normal sadness reactions.

The Classical Tradition

Writing in the fifth century bc, Hippocrates (460–​377 bc) and the school of Hippocratic physicians that formed around him provided the first known description of melancholia (the Greek name for pathological states of depression), stated succinctly in Hippocrates’s Aphorisms:  “Fear or sadness that last a long time mean melancholia” (Hippocrates, 1923–​1931, Vol. IV, p. 185). In addition to fear and sadness, the Hippocratic writings mentioned as symptoms of melancholia “aversion to food, despondency, sleeplessness, irritability, restlessness” (Hippocrates, 1923–​1931, Vol. I, p. 263). This description is remarkably similar to the current definition found in the DSM-​5 (American Psychiatric Association, 2013). Unlike DSM-​5, however, the Hippocratics did not view depression as a free-​standing condition but linked it with other conditions, especially anxiety (“fear”) and delusions. On the basis of the latter feature, melancholia was often characterized as “delirium without a fever.” A combination of anxious concerns and nameless fears, depressive symptoms such as blackness of mood and suicidal impulses, and paranoid tendencies such as sullen suspiciousness characterized melancholic conditions. Similarly, Galen (131–​201 ad) indicated that although “each (melancholic) patient acts quite differently than the others, all of them exhibit fear or despondency” (Radden, 2000, p. 10). He went on to 12

History of Depression

note: “Therefore, it seems correct that Hippocrates classified all their symptoms into two groups:  fear and despondency” (Jackson, 1986, p. 42). Although the Hippocratics agreed with contemporary accounts on the symptoms of melancholia, the Hippocratic definition in Aphorisms also specified the contextual constraint that the symptoms had to last an unusually long time to constitute melancholia. This indicates that it is not depressive symptoms alone but symptoms of unexpected duration that indicate disorder. This insistence that the sadness or fear must be prolonged is a first attempt to capture the notion that disproportion to circumstances is an essential aspect of depressive disorder. Hippocratic writings rarely focused on distinct external causes of melancholic disorders. Rather, their foundational principle was that health is a state of equilibrium within the body and that disease is due to a disturbance of this balance (Porter, 1997, pp. 55–​62). The Greeks viewed mental diseases, like disease in general, in terms of four basic humors: blood, phlegm, yellow bile, and black bile. Each humor possessed two of four properties: hot, cold, moist, or dry. When the humors were in balance with each other, a healthy state resulted. Diseases, both mental and physical, stemmed from too much or too little of one of these humors, a notion that would recur when theories of neurochemical imbalance were developed at the end of the twentieth century. For the Greeks, melancholia was connected to an excess of black bile. Yet mental disturbances that resulted from an excess of black bile were not localized but disrupted a holistic relationship between individuals and their surroundings. A variety of factors, including diet, lifestyles, living conditions, and atmospheric elements, could lead to humoral imbalances. Traditional diagnostic treatises followed Hippocrates in distinguishing depression as a disorder from a nondisordered type of deep sadness or fear that could have many of the same symptoms but was instead a normal, proportionate reaction to serious losses. For example, Aristotle (384–​322 bce), or perhaps one of his followers, distinguished normal states of sadness from pathological disease states, stating that in depression black bile is “cold beyond due measure” so “it produces groundless despondency” (Jackson, 1986, p. 32). Here, “beyond due measure” refers to responses that are disproportionate to their circumstances, so the resulting sadness is “groundless.” In contrast, sadness stemming from losses such as the death of intimates, reversals in fortune, disappointments in attaining valued life goals,

 

and romantic disappointments could be proportionate to their contexts and, therefore, not disordered. Given that the symptoms of normal sadness and depressive illness could be the same, ancient physicians understood that differential diagnosis required careful exploration that went beyond the symptoms to the context of the symptoms. For example, Greek physician Aretaeus of Cappadocia (ca. 150–​ 200 ad) explicitly separated melancholic patients who “are dull or stern, dejected or unreasonably torpid, without any manifest cause” from those who experience “mere anger and grief, and sad dejection of mind” (Jackson, 1986, pp.  39, 40). To illustrate the distinction, Aretaeus recounted his own version of the diagnostic triumph famous in ancient times of Erasistratus (304–​250 bc), physician to King Seleucus of Syria, in which Erasistratus discovered through shrewd observation that the king’s son, Antiochus, was not suffering from melancholia as his symptoms suggested, but was instead suffering from unrequited (and unexpressible) love—​for his father’s young wife! As Aretaeus tells it: A story is told, that a certain person, incurably affected, fell in love with a girl; and when the physician could bring him no relief, love cured him. But I think that he was originally in love, and that he was dejected and spiritless from being unsuccessful with the girl, and appeared to the common people to be melancholic. He then did not know that it was love; but when he imparted the love to the girl, he ceased from his dejection, and dispelled his passion and sorrow; and with joy he awoke from his lowness of spirits, and he became restored to understanding, love being his physician. ( Jackson, 1986, p. 40)

Similarly, during the same period, Galen draws this distinction in his case histories. For example, Galen describes a case in which he is unsure whether the problem lies in normal despair over some loss that is being hidden from the physician or the development of a depressive medical disorder: I was called in to see a woman who was stated to be sleepless at night and to lie tossing about from one position into another. Finding she had no fever, I made a detailed inquiry into everything that had happened to her, especially considering such factors as we know to cause insomnia. But she either answered little or nothing at all, as if to show that it was useless to question her. Finally, she turned away, hiding herself completely by throwing the bedclothes over her whole body, and laying her head on another

small pillow, as if desiring sleep. After leaving I came to the conclusion that she was suffering from one of two things: either from a melancholy dependent on black bile, or else trouble about something she was unwilling to confess. I therefore deferred till the next day a closer investigation of this. (Galen, 1929, p. 213)

In addition, early diagnosticians acknowledged that variations in temperament predispose some people to more readily or intensely experience sadness or fear. However, these variations were thought to be within a normal range of reasonably proportionate responses that did not represent a disorder. Depressive disorders thus differed from normal reactions, according to tradition, because they either arose in the absence of situations that would normally produce sadness or were of disproportionate magnitude or duration relative to their provoking causes. Such conditions indicated that something was wrong in the individual, not in the environment.

The Anatomy of Melancholy

Subsequent to early Greek and Roman medicine almost no new developments in medical thinking about melancholy occurred until the end of the eighteenth century. Robert Burton’s The Anatomy of Melancholy. published in 1621, illustrates the persistence of the classical tradition. It is the most renowned of all classical discussions of melancholy and perhaps of any volume ever written about depression. Burton described three major components of depression—​mood, cognition, and physical symptoms—​that are still viewed as the distinguishing features of the condition. However, he insisted that melancholic symptoms are not in themselves sufficient evidence of disorder. According to Burton, only symptoms that are without cause provide evidence of disorder. As he explained in this codicil to his definition: “without a cause is lastly inserted, to specify it from all other ordinary passions of Fear and Sorrow.” And, he noted, “signs in the mind” of melancholia included “Sorrow … without any evident cause; grieving still, but why they cannot tell.” Burton emphasized that a propensity to melancholy was present in all men, and was a normal and ubiquitous aspect of the human condition: Melancholy … is either in disposition or habit. In disposition, it is that transitory melancholy which goes and comes upon every small occasion of sorrow, need, sickness, trouble, fear, grief, passion, or perturbation of the mind, any manner of care,

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discontent, or thought, which causeth anguish, dullness, heaviness, and vexation of spirit… . And from these melancholy dispositions, no man living is free, no Stoic, none so wise, none so happy, none so patient, so generous, so godly, so divine, that can vindicate himself; so well composed, but more or less, some time or other, he feels the smart of it. Melancholy, in this sense is the character of mortality. (Burton, 1621/​2001, pp. 143–​144 )

In contrast to normal melancholy that arises naturally after people have suffered losses and disappointments and that is part of the “character of mortality,” Burton held that melancholic afflictions are “contrary to nature.” This latter condition, the disorder of melancholy, he defined as “a kind of dotage without a fever, having for his ordinary companions fear and sadness, without any apparent occasion” (Burton, 1621/​2001, pp. 169–​170). Burton was sensitive to the wide individual variation in the nature of loss responses. He believed that a quite broad range of temperamental reactions to loss was nondisordered as long as the reactions did not become chronic or self-​perpetuating. He noted: “For that which is but a flea-​biting to one, causeth insufferable torment to another, & which one by his singular moderation, & well composed carriage can happily overcome, a second is no whit able to sustaine” (Burton, 1621/​2001, p. 132). It is only when such normal reactions to specific events become established as an ongoing condition independent of events that Burton sees disorder: (I)t falleth out oftentimes that these Dispositions become Habits, and … make a disease. Even as one Distillation, not yet growne to custome, makes a cough; but continuall and inveterate causeth a consumption of the lungs: so doe these our Melancholy provocations… . This Melancholy of which we are to treat, … a Chronicke or continuate disease, setled humor … not errant but fixed, … growne to an habit, it will hardly be removed. (Burton, 1621/​2001, pp. 145–​146 )

In addition to noting normal variation in temperament, Burton was an astute observer of the extremes to which normal reactions to loss could go. He noted that the most intense painful losses included separation from friends and bereavement following loss of a loved one (“in this Labyrinth of accidental causes [of melancholy] … loss and death of friends may challenge first place” Burton, 1621/​ 14

History of Depression

2001, pp. 357–​358) and compellingly described the extremes that nondisordered grief can reach: If parting of friends, absence alone, can work such violent effects, what shall death do, when they must eternally be separated, never in this world to meet again? This is so grievous a torment for the time, that it takes away their appetite, desire of life, extinguisheth all delights, it causeth deep sighs and groans, tears, exclamations, … howling, roaring, many bitter pangs, and by frequent mediation extends so far sometimes, they think they see their dead friends continually in their eyes, … Still, still, still, that good father, that good son, that good wife, that dear friend runs in their minds; a single thought fills all their mind all year long, … They that are most staid and patient are so furiously carried headlong by the passion of sorrow in this case, that brave discreet men otherwise oftentimes forget themselves, and weep like children many months together. (Burton, 1621/​2001, pp. 358–​359)

Burton’s magisterial work remains the most comprehensive description of depression ever compiled. Yet his rambling and disjointed style, not to mention the inconsistencies and lack of systemization that plagued his work, meant that his vast compendium was not a useful foundation for the more scientific studies of depression that would emerge in later centuries. It remained for future diagnosticians to build on Burton’s work and to disentangle melancholia from other conditions. Burton’s work is clearly situated within the Hippocratic tradition. In effect, medical commentators throughout the eighteenth century relied primarily on Greek physicians, especially Galen, as authorities on depression and other mental illnesses (Simon, 1980). Likewise, the association of sadness and fear under the general melancholic umbrella persisted for centuries. The humoral theory of disease also endured in medical understandings and treatments of melancholy until the end of the seventeenth century and, sometimes, beyond then. Humoral thought was foundational not only in the culture of physicians but also in the medical lore of common people and the lay healers. Diseases resulted from imbalances between the various humors:  treatments aimed to correct such imbalances and restore the body to appropriate equilibrium. Hippocratic preferences for altering lifestyles continued to prevail over more intensive medical interventions. Fresh air, exercise, good sleeping, eating, and elimination habits, and control

 

of the passions remained prominent treatments for melancholy. Such treatments were typically intertwined with religious, magical, and folkloric methods (Shorter, 1992).

From the Seventeenth through the Nineteenth Centuries

A radical change in the Western intellectual tradition occurred in the seventeenth century as the inductive, empirical, and observational methods of Bacon and Newton overturned the more deductive, intuitive, and relational nature of Hippocratic methods. Notions of disease specificity also began to emerge, particularly in the work of English physician Thomas Sydenham (1624–​ 1689). Sydenham proposed that each disease had natural forms with uniform presentations in different individuals, an idea distinct from holistic Hippocratic thought. After thousands of years of dominance by Hippocratic views of humoral imbalance, a new system arose that was based on disturbances of the brain and the nervous system (Porter, 1997). Gradually, the capacious category of melancholia that spanned from the Hippocratics through Burton began to split into more specific manifestations. Depressive conditions were divided into two major types (Shorter, 2013). The first conditions were marked by deep mental anguish, hopelessness, complete joylessness, stupor, and suicidal thoughts and/​or actions. These were likely to be chronic and recurrent and require the attention of specialized healers (then called “alienists”) who treated insane conditions. In addition to this serious melancholia, a new category of “nervous disorders” began to emerge that viewed the nervous system as the source of health and illness, emphasizing the importance of nerves, fibers, and organs. Accordingly, the causes of nervous conditions were found in physiology, particularly brain lesions. Depressive symptoms were viewed as one component of a syndrome of “nervous disease,” “nervous illness,” “neurosis,” or, later, “neurasthenia” that referred to nonpsychotic conditions related to problems of the nervous system. The depressive component of such states was not seen as distinct from the variety of heterogeneous anxious and physiological symptoms that comprised this diagnosis. Nervous disorders encompassed anxiety, fatigue, somatic preoccupations, and obsessions (Shorter, 2013). Because these conditions were related to an organic system, they were not seen as mental problems. Nervous disorders fell under the domain of general physicians, neurologists, and spa doctors (Micale, 2008).

Melancholic and neurotic depressions were not two different points of the same continuum of severity. Instead, “There are two different kinds of depression, as different as tuberculosis and mumps; it makes no sense to lump both of them together under the general term ‘depression’ ” (Shorter, 2013, p. 80). By the nineteenth century these conditions were sharply distinguished by their symptoms, causes, and treatments. While alienists and psychiatrists treated melancholic patients, often within inpatient settings, nervous patients remained in the community under the purview of general physicians or specialized nerve doctors. The two leading diagnosticians of the late nineteenth century took sharply different approaches to depression. German psychiatrist Emil Kraepelin (1856–​1926), who spent his entire career practicing in mental asylums, focused on the melancholic type of depression. He linked depression with mania under the general umbrella of manic-​ depressive conditions, sharply distinguishing it from his second psychotic state of dementia praecox (schizophrenia). Manic depression and dementia praecox were homogeneous and distinct entities that presumably had entirely different causes, prognoses, and outcomes (Kraepelin, 1921). Early in his writings on classification and diagnosis, Kraepelin (1903) described melancholia as a separate disorder unrelated to manic-​depressive psychosis. Subsequently, however, he was impressed by the fact that in some cases that initially looked like melancholia, eventually—​often after long periods of time—​there developed a manic episode. He was also persuaded by a study by Dreyfus (1907) that the nature of melancholia and of the depressive pole of manic-​depressive illness is in fact qualitatively indistinguishable, and thus likely represent the same underling etiology. Kraepelin thus eventually combined all depressive and manic-​ depressive mood disorders into one category that, although encompassing a variety of clinical presentations, had as its hypothesized source the same underlying pathophysiology: “Manic depressive insanity as it is to be described in this section, includes on the one hand the whole domain of so called periodic and circular insanity, on the other hand … the greater part of the morbid states termed melancholia … . In the course of the years I have become more and more convinced that all the above-​mentioned states only represent manifestations of a single morbid process” (Kraepelin, 1921/​1976, pp.  1–​2). However, with the subsequent development of treatments specific to bipolar versus unipolar illness, all the unipolar

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forms were united under the DSM’s major depressive disorder. Kraepelin’s approach to psychiatric diagnosis is generally credited as the inspiration for the DSM system, so it is of interest that, unlike the DSM but like most of his predecessors, Kraepelin believed in the necessity of taking context into account when diagnosing depressive disorder in order to differentiate it from normal intense sadness:  “Morbid emotions are distinguished from healthy emotions chiefly through the lack of a sufficient cause, as well as by their intensity and persistence … . Again, morbid emotions sometimes attach themselves to some certain external occasions, but they do not vanish with the cause like normal feelings, and they acquire a certain independence” (Kraepelin, 1915, p. 68). Kraepelin, like Aretaeus, offered case illustrations of the danger of false positives and emphasized the need to consider context—​including history—​ to discriminate disorder from nondisorder: Several times patients have been brought to me, whose deep dejection, poverty of expression, and anxious tension tempt to the assumption of a circular [pathological] depression, while it came out afterwards, that they were cases of moodiness, which had for their cause serious delinquencies and threatened legal proceedings. As the slighter depressions of manic depressive insanity, as far as we are able to make a survey, may wholly resemble the well founded moodiness of health, with the essential difference that they arise without occasion, it will sometimes not be possible straightway to arrive at a correct interpretation without knowledge of the previous history in cases of the kind mentioned. (Kraepelin, 1917, pp. 199–​200)

In contrast to Kraepelin, who was generally concerned with the conditions of severe, hospitalized patients, the second towering figure of the time, Sigmund Freud (1856–​1939), had little concern with psychotic conditions. Instead, Freud was centrally involved with nervous conditions found in community practices. Yet Freud gave short shrift to depression, giving anxiety pride of place in his pantheon of neurotic symptoms. Freud’s sole major essay on depression, “Mourning and Melancholia,” focused on the distinction between the normality of grief and the disorder of melancholia: Although grief involves grave departures from the normal attitude to life, it never occurs to us to regard it as a morbid condition and hand the mourner

16

History of Depression

over to medical treatment. We rest assured that after a lapse of time it will be overcome, and we look upon any interference with it as inadvisable or even harmful. (Freud, 1917/​1957)

Freud emphasized that symptoms associated with mourning are intense and are “grave departures from the normal,” in the sense that grief is greatly different from usual functioning. Nevertheless, grief is not a “morbid” condition; that is, it is not a medical disorder that represents the breakdown of a biologically normal response and in fact does not require medical treatment. Medical intervention, he suggested, could actually harm the grieving person by interfering with this natural process. By the early decades of the twentieth century, then, depression was sharply split into melancholic conditions marked by serious symptoms that were linked to psychoses and neurotic depression that was one of the psychoneuroses. Whereas melancholic depression was thought to be due to some as yet unknown brain dysfunction, nonmelancholic conditions were seen as products of various psychosocial adversities, especially the loss of a love object. The former usually required some form of inpatient treatment while the latter could be handled within outpatient settings.

Between Kraepelin and Freud and the DSM-​III

Freud, along with American psychiatrist Adolf Meyer, was the major influence on the DSM-​I (1952) and DSM-​II (1968), the two manuals that preceded the DSM-​III. Depression, however, bore a more Kraepelinian stamp. Much in Kraepelinian style, the DSM-​I grouped affective disorders that were characterized by severe mood disturbances consistent with melancholia as one of the three major categories of psychotic disorders (the two others were schizophrenic and paranoid reactions) (American Psychiatric Association, 1952, p.  12). Persons receiving this diagnosis showed “evidence of gross misinterpretation of reality, including, at times, delusions and hallucinations” (American Psychiatric Association, 1952, p.  25). In contrast, these earlier manuals conceived of neurotic depression as an epiphenomenon of an underlying anxiety condition. The very first sentence of the DSM-​I classification of psychoneurotic disorders stated:  “The chief characteristic of these disorders is ‘anxiety’ which may be directly felt and expressed or which may be unconsciously and automatically controlled

 

by the utilization of various psychological defense mechanisms (depression, conversion, displacement, etc.)” (American Psychiatric Association, 1952, p. 31). Psychoneurotic depression was thus understood as a psychological defense against anxiety. The DSM-​II also grouped psychotic depression with states of mania, much in Kraepelinian fashion. It defined the category of major affective disorders as follows:  “This group of psychoses is characterized by a single disorder of mood, either extreme depression or elation …” (American Psychiatric Association, 1968, p. 35). It continued to submerge depressive neurosis within the broader category of anxiety conditions, stating that “Anxiety is the chief characteristic of the neuroses” (American Psychiatric Association, 1968, p. 39). In contrast to the prominence these manuals accorded psychotic forms of depression, they viewed psychoneurotic depression as one type of defense mechanism against anxiety. During the 1950s and much of the 1960s, nonpsychotic forms of depression were largely submerged into the broader conception of psychoneuroses. Although psychotic forms of depression were central to psychiatric theory, research, and practice before 1980, in the study of neurotic depression, numerous and often competing diagnostic systems existed and none had preeminence over the others (Grob & Horwitz, 2010). Most researchers agreed with the DSM-​I and DSM-​II that melancholic (or psychotic) depression—​a particularly serious state marked by vegetative symptoms, delusions, and hallucinations—​was a distinct type of disorder (e.g., Kiloh & Garside, 1963; Klein, 1974; Mendels & Cochrane, 1968; Paykel, 1971). Although researchers concurred that a separable, psychotic form of depression existed, they could not reach a consensus about the nature of nonpsychotic types of depression. Researchers argued over whether these depressions were continuous or discontinuous with psychotic forms, on the one hand, or with normality, on the other. They disputed how many forms neurotic conditions took and even whether they had any distinct forms at all. Diagnosticians who argued for discrete types could not agree on how many types existed. Some concluded that in addition to a melancholic, psychotic type, depression had only a single neurotic type (Kiloh & Garside, 1963). Others suggested that three or more distinct, neurotic states of depression existed (Hamilton & White, 1959; Paykel, 1971; Raskin & Crook, 1976). Various classifications of depression embraced from a single to as many as nine or more separate categories

(Kendell, 1976). Still others conceived of neurotic depression as more closely resembling a personality or temperament type than a disease condition (Eysenck, 1970). Nor was it known whether some milder forms of depression were early indicators of eventual psychotic forms. In addition, little consensus existed about the particular symptoms that were essential to definitions of nonpsychotic forms of depression and more disputes abounded over whether depression should be classified according to its symptoms, etiology, or response to treatments. In 1976 the prominent psychiatric diagnostician R.  E. Kendell published an article whose title accurately conveyed the situation at the time: “The Classification of Depressions: A Review of Contemporary Confusion.” Kendell outlined 12 major systems of classification, most of which had little to do with the others. He concluded (1976, p. 25) that “there is no consensus of opinion about how depressions should be classified, or any body of agreed findings capable of providing the framework of a consensus.” In 1979, just a year before the publication of the DSM-​III, psychiatrists Nancy Andreasen and George Winokur (1979) likewise noted the presence of “a hodgepodge of competing and overlapping systems” in research about depression. Similar to the other major diagnoses in psychiatry at the time, opinions regarding the classification of depression at the end of the 1970s featured an extraordinarily broad range of unresolved conflicts on how best to measure this condition. Yet in 1980, responding to this period of confused debate characterized by the highly unsettled state of empirical findings and lack of definitive theory about the nature of nonpsychotic depression, psychiatry would nonetheless adopt a definitive set of symptomatic criteria for depression that has remained stable until the present.

Sources of the DSM-​III

One of the 12 classifications of depression that Kendell reviewed in his 1976 article was “The St. Louis Classification” developed by a group of psychiatrists at Washington University (Horwitz, 2011). During the era in which psychodynamic perspectives dominated the psychiatric profession, the Washington University Department of Psychiatry was an outpost of traditional medically minded thinking. Led by Samuel Guze and Eli Robins, this group’s primary concern was to develop a reliable system of diagnosis that could differentiate the etiology, prognosis, and drug responses of various conditions. They developed operational criteria for

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14 disorders, known as the “Feighner criteria” after the psychiatric resident who was the first author of the article that described them (Feighner, Robins, Guze, Woodruff, Winokur, & Munoz, 1972). The Feighner criteria for depression required fulfillment of three conditions. First, patients must have a dysphoric mood marked by symptoms such as being depressed, sad, or hopeless. Second, the criteria required five additional symptoms from a list including loss of appetite, sleep difficulty, loss of energy, agitation, loss of interest in usual activities, guilt feelings, slow thinking, and recurrent suicidal thoughts. Finally, the condition must have lasted at least 1 month and not be due to another psychiatric or medical illness (which were classified as “secondary affective disorders”). Patients whose symptoms arose from preexisting mental or physical illnesses would receive a diagnosis of a secondary affective disorder. What was the basis for the Feighner criteria of depression? In contrast to the widespread belief that a strong empirical research base underlay the diagnostic criteria leading to the DSM-​III (e.g., Kendler, 1990; Sabshin, 1990), in fact, the evidence supporting its classification of depression was very limited. Only one of the five publications cited in the footnotes to the article provided empirical substantiation for the depression criteria (another citation refers to unpublished research by Robins and Guze). This was a study by psychiatrist Walter Cassidy and several colleagues that reported findings from a quantitative study of 100 patients called “manic-​depressive” and 50 medically sick controls (Cassidy, Flanagan, Spellman, & Cohen, 1957). The criteria of Cassidy et al. (1957) for depression required that patients “(a) had made at least one statement of mood change, including any of the following:  blue, worried, discouraged, and 16 equivalent expressions and (b)  had any 6 of the 10 of the following special symptoms: slow thinking, poor appetite, constipation, insomnia, feels tired, loss of concentration, suicidal ideas, weight loss, decreased sex interest, and wringing hands, pacing, over-​talkativeness, or press of complaints” (Cassidy et  al., 1957, p.  1535). Feighner himself noted that he “relied a lot on an article by Cassidy” (Kendler, Muñoz, & Murphy, 2010, p.  136) and his eponymous criteria made only four relatively small changes to these conditions, dropping constipation, adding feelings of self-​reproach or guilt, expanding insomnia to encompass sleep difficulties, and combining weight loss with anorexia into one item (Kendler et  al., 2010). In addition, the 18

History of Depression

Cassidy diagnostic criteria did not mention any necessary duration of symptoms, perhaps because all patients in their study were hospitalized and most had symptoms that endured for more than 6  months. The Feighner criteria added the stipulation that the symptoms must last for at least 1 month, a far shorter duration than that typifying the Cassidy hospitalized sample. Several aspects of the Cassidy criteria are noteworthy. First, all of the patients in the sample were “considered sick enough to require hospital observations, and in most cases the patients were admitted for electroconvulsive treatment” (Cassidy et  al., 1957, p.  1535). The diagnosis was thus grounded in melancholic symptoms that characterized state hospital patients, which could differ substantially from psychoneurotic depression found in outpatient settings or acute psychiatric wards, not to mention untreated community populations. In addition, Cassidy et  al. (1957, p. 1542) recognized the inexact nature of their criteria, stating that “The question immediately arises as to whether all these patients did, in fact, have manic-​depressive disease. At present, one cannot go beyond saying that the patients had a psychiatric illness… .” In particular, the Cassidy group noted the unresolved relationship of manic-​ depressive disease to patients with melancholia, manic-​depressive psychoses, anxiety, alcoholism, and manic-​ depressive personality types. They clearly believed that their diagnostic criteria were highly exploratory and far from the last word on depressive diagnoses and their relationship to criteria for other diagnoses. Likewise, the Feighner group presented their criteria as a tentative first step that awaited future validation and noted that they were “not intended as final for any illness” (Feighner et al., 1972, p. 57). Similarly, Kendell (1976, p. 25) did not place any special priority on the Feighner measurement of depression, noting that “no evidence has been offered to suggest that it is anything more than a convenient strategy.” Yet just 4 years after Kendell made this assessment, the Feighner classification of depression became almost the sole basis for the DSM-​III diagnosis. Indeed, by 1989, the article in which the Feighner criteria first appeared was the single most cited article in the history of psychiatry (Feighner, 1989). In a remarkably short period of time the process of diagnosing depressive disorder was transformed from a contentious battle among many competing systems to the unchallenged dominance of a single classification, the DSM-​III

 

diagnosis of Major Depression. How did this hegemony come about?

The DSM-​III

DSM-​III formulated depression in a radically new way relative to the previous 2500  years of medical diagnosis. Its definition of major depressive disorder (MDD) required either a dysphoric mood or loss of interest or pleasure in usual activities. In addition, at least four of the following symptoms must be present nearly every day for a period of at least 2 weeks: (1) poor appetite or significant change in weight; (2)  insomnia or hypersomnia; (3)  psychomotor agitation or retardation; (4)  decreased sexual drive; (5) fatigue or loss of energy; (6) feelings of worthlessness, self-​reproach, or excessive or inappropriate guilt; (7) diminished ability to think or concentrate or indecisiveness; and (8) recurrent thoughts of death or suicidal ideation or suicide attempt (American Psychiatric Association, 1980, p. 213). These criteria almost completely mirrored the Feighner criteria, which themselves closely resembled the original Cassidy diagnosis. The only major changes the DSM-​III made to the Feighner criteria were to, first, exempt from diagnosis anyone who meets these symptom criteria if their symptoms are due to bereavement after the death of a loved one that lasts no more than 2  months and are not of extreme severity (American Psychiatric Association, 1980, p. 214). The earlier criteria, in contrast, contained no exceptions other than for symptoms that arose from a preexisting mental or physical condition. Second, the DSM-​III lowered the necessary duration of symptoms from 1  month to 2 weeks and the necessary number of symptoms from six to five. Finally, the DSM-​III abandoned the differentiation that Kendell had considered at the core of the Feighner criteria: “The most important feature of this classification is the distinction it draws between primary and secondary affective disorders” (Kendell, 1976, p. 23). Departing from diagnostic conceptions about depression over the previous 250 years, the DSM-​ III unified depressive conditions into a single category. In contrast to the sharp split of depression into psychotic and psychoneurotic forms in the DSM-​I and DSM-​II, MDD embraced both unipolar psychotic and psychoneurotic forms of depression. Melancholic depression—​ the central depressive condition before the DSM-​III—​became a subtype of MDD (American Psychiatric Association, 1980, p.  215). Meeting criteria for the subtype required

lack of pleasure or emotionally reactivity, as well as three symptoms from a list including either distinct quality of mood, symptoms of greater severity in the morning, early-​ morning awakening, marked psychomotor retardation, weight loss, or excessive guilt. There is an understanding that the melancholic subtype had some correspondence to the classical conceptualization of depression (Parker, 2000). However, people could qualify for a diagnosis of melancholy only if they already meet the criteria for MDD. Moreover, the current definition that emphasizes the presence of specific symptoms departs from the contextual tradition. The submersion of melancholia into the broader MDD category ensured its fall into obscurity (McPherson & Armstrong, 2006; Zimmerman & Spitzer, 1989). Likewise, the category of “Dysthymic Disorder (or Neurotic Depression),” which was inserted into the manual to mollify psychoanalysts, never gained traction as a well-​established disorder (Bayer & Spitzer, 1985; McPherson & Armstrong, 2006). Indeed, because this diagnosis required a 2-​year duration, it was inherently applicable only to persons with the most longstanding types of mood disorder. Major depression was the sole depressive diagnosis of any importance. The MDD diagnosis that emerged in the DSM-​ III was in many ways a major achievement. It succeeded in establishing a single standard of measurement that has been almost universally adopted in psychiatric research on depression (McPherson & Armstrong, 2006). It thus facilitated communication and understanding among the research community and provided diagnostic criteria that clinicians and researchers from a variety of theoretical persuasions could use. In addition, it realized the major aim of Spitzer and his colleagues to create a reliable way of measuring depression. Although the MDD diagnosis was a major accomplishment for research-​oriented psychiatrists, it also entailed serious deficiencies. The emphasis on creating measurable and reliable diagnoses came at the expense of establishing validity. The DSM-​III itself defined a valid mental disorder as a “behavioral, psychological, or biological” dysfunction in the individual, which the DSM-​IV later specified “must not be merely an expectable and culturally sanctioned response to a particular event, for example, the death of a loved one” (American Psychiatric Association, 1994, p. xxi). In line with this definition, the MDD criteria excluded bereaved people from diagnoses unless they have particularly longstanding or severe symptoms (e.g., including

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marked psychomotor retardation or morbid feelings of worthlessness). They did not, however, exclude people whose symptoms arose from other life events such as the dissolution of a romantic relationship, loss of a valued job, or failure to achieve a long-​ desired goal, thus suggesting that these responses are not “expectable” or “culturally sanctioned.” This reasoning was contrary to the centuries-​long understanding that such people do not have individual dysfunctions but are responding naturally to undesirable losses in their lives (Horwitz & Wakefield, 2007). The failure to allow exclusions other than bereavement enhanced the reliability of the MDD diagnosis because clinicians and researchers might disagree on whether depressive symptoms represent appropriate contextual responses. However, as the diagnostic tradition from the Hippocratics through Freud emphasized, the use of symptoms, without regard to the context in which they develop and are maintained, combines nondisordered people whose symptoms result from some loss with those people whose symptoms either are inexplicable or are disproportionate to their social context. Likewise, the diagnosis encompasses conditions that are as brief as 2 weeks as well as those that persist for long periods of time. They also treat severe symptoms such as suicide attempts or feelings of worthlessness as comparable to common symptoms such as insomnia and fatigue. The result is that the MDD diagnosis encompassed an extraordinarily heterogeneous range of conditions under a single label. In effect, it ignored the pre-​ DSM-​III consensus that melancholic depressions were distinct from psychoneurotic ones. The many issues that the varied classifications of depression could not resolve before the publication of the DSM-​III suddenly disappeared. Questions over how many distinct types of depression existed, the relationship between psychotic and neurotic forms of depression, and whether depression was best measured by dimensions or categories were all settled by fiat. Although the Feighner group framed their criteria as a tentative first step toward the eventual establishment of a reliable and valid classification scheme, the DSM-​III adopted these criteria with few changes. Moreover, save for the removal of the bereavement exclusion in DSM-​5, which moved even further away from the classical contextual approach, the MDD criteria remained almost intact in subsequent manuals, the DSM-​III-​ R, DSM-​IV, and DSM-​IV-​TR (American Psychiatric Association, 1987, 1994, 2000). The wholesale, and 20

History of Depression

largely arbitrary, adoption of one among a number of competing ways of defining depression perhaps accounts for why—​more than 30  years after its promulgation—​research on depression has yet to yield any major breakthroughs in the understanding of the etiology, prognosis, or treatment of this condition (Blazer, 2005; Frances, 2013; Horwitz & Wakefield, 2007; Shorter, 2013).

The Consequences of the DSM-​III Diagnosis of Major Depression

The MDD category in the DSM-​III encompassed all of the heterogeneous categories of endogenous, exogenous, neurotic, and even psychotic forms of depression that existed before 1980. MDD captured both amorphous and short-​lived reactions to psychosocial problems as well as serious and chronic conditions that in the past had been associated with melancholic depression. This heterogeneous quality of the MDD diagnosis is especially consequential when the diagnosis is used outside of hospital settings. An underlying assumption behind the use of the Feighner criteria as the foundation of the MDD diagnosis is that measures developed in hospitalized populations of severely impaired patients could be applied to all depressive conditions. Yet within hospitalized populations the symptoms that appeared in the diagnostic criteria can be assumed to be severe and, usually, long-​lasting. Yet MDD is used not just in inpatient institutions but in all settings that require diagnoses, including general medical practice and private mental health practices and clinics. It is also the diagnosis used in epidemiological investigations among untreated community populations, in research studies, and in treatment outcome assessment. The DSM-​III diagnosis of major depression in effect became the arbiter of what depression was in clinical and clinical research settings, community studies, and the culture at large. The significance of the MDD criteria changed when they were applied to outpatient populations and, especially, to community populations in which their application can result in many false-​positive diagnoses (Wakefield, Schmitz, First, & Horwitz, 2007). In these settings, low mood, poor appetite, insomnia, fatigue, lack of concentration, and the like are typically common responses to ubiquitous stressful experiences such as the loss of valued relationships, jobs, or goals that, as noted, even the DSM definition of mental disorder did not categorize as valid disorders. Indeed, Robert Spitzer, the

 

head of the DSM-​III task force, acknowledges that in regard to MDD: “the DSM is not consistent even in applying its own definition of mental disorder to the diagnostic criteria sets for specific disorders” (Horwitz & Wakefield 2007, p.  viii). When diagnoses require just 2-​week duration they can include many short-​lived responses to stressors. Moreover, the lack of exclusion criteria other than bereavement virtually ensured that the criteria could not separate natural symptoms of sadness from dysfunctional depressive disorders. Because the MDD diagnosis that emerged in the DSM-​III encompassed symptoms that typified very severe and enduring symptoms as well as those that were short-​lived and common signs of distress such as sadness, fatigue, sleep and appetite difficulties, or lack of concentration, it is no surprise that following the publication of the DSM-​III depression became by far the most common diagnosis in outpatient mental health treatment. Indeed, by the beginning of the twenty-​first century Major Depression constituted a full 38% of all diagnoses in outpatient settings out of the hundreds of possibilities (Olfson et al., 2002). Major Depression also became the major target of a new class of drugs, the selective serotonin reuptake inhibitors, which came on the market in the late 1980s. Because the DSM-​III depression criteria could encompass such a wide variety of everyday psychosocial problems, it made the most marketing sense to call them “antidepressants.” In fact, these capacious drugs were, and are still, used to treat an enormous variety of conditions including not only depression but also anxiety, obsessions, alcohol abuse, eating disorders, and a host of undifferentiated symptoms. The label “antidepressant” reinforced the popularity of the depression diagnosis because if some condition was treated with an antidepressant it must be depression. The overwhelming marketing success of the MDD diagnosis came at the cost of hindering scientific research. It left unresolved whether melancholic depression—​the central depressive condition before the DSM-​III—​is a distinct condition or simply the most severe type of major depression (Taylor & Fink, 2006). The melding of serious melancholic conditions with transient stress-​related sadness creates a roadblock in the way of finding a condition with a distinct etiology, prognosis, and treatment. It also thwarts progress in finding the possible biological roots of depression by combining distinct states that might represent brain dysfunctions with natural products of psychosocial stressors.

Pre-​DSM-​III controversies over whether depression is best viewed as a categorical or dimensional condition likewise remain unresolved. In addition, the question of how to distinguish depressive disorders from depressive personality types is unsettled. Whereas the DSM-​III generated consensus about the operational definition of depression, questions about whether depression is continuous or categorical, how many categories it has, what its relationship to melancholic conditions is, and how it can be distinguished from normal sadness seem no closer to resolution now than they were when the DSM-​III arose.

Conclusions

What is striking from this brief overview of conceptualizations of depressive disorder from Hippocrates to the DSM-​III is, first, the remarkable consistency of the symptoms that are mentioned—​ by and large the same kinds of symptoms that current diagnostic manuals emphasize. And, second, there is a remarkably solid and well-​elaborated tradition of distinguishing disorder from normal emotion via various versions of the “with cause” versus “without cause” criterion that goes back to ancient times. Because stressful life events can precede serious and long-​standing depressions, “disproportionate to cause” seems to characterize dysfunctional conditions better than the traditional term “without cause.” The entire 2,500-​year record indicates an understanding that pathological depression is an exaggerated form of a normal human emotional response. Thus, diagnosticians understood that the first step in understanding a patient’s condition must be to use the relation of symptoms to their triggering causes to distinguish the normal from the disordered. The power, consistency, and rationale of the “disproportionate” medical understanding of depressive disorder form the backdrop for our own era’s radical departures in diagnostic approach. Finally, the historical tradition preceding the DSM-​III sharply distinguished severe states of melancholic depression from less disabling psychoneurotic depression, which it often associated with cooccurring symptoms of anxiety. In the urgent quest for reliability, the adoption of the current depression criteria for the most part inadvertently rejected the previous 2,500  years of clinical diagnostic tradition that explored the context and meaning of symptoms in deciding whether someone is suffering from intense normal sadness or a depressive disorder. The DSM-​III criteria, which persist into the present, also blurred

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the traditional distinction between melancholic and neurotic depression, calling both forms “Major Depression.” The unwitting result of this effort, especially as psychiatry turned from the serious conditions of inpatients to the far more heterogeneous conditions of outpatients and community members, was to be a massive pathologization of normal sadness. Ironically, this can be argued to have made depressive diagnosis less, rather than more, scientifically valid. The sole remnant of the “disproportionate to cause” tradition was the bereavement exclusion that remained in DSM IV-​ TR. The removal of this criterion from the diagnostic criteria in DSM-​5 indicates that far from making diagnostic progress, the recent history of the mood disorders shows significant regression in understanding the most basic of all distinctions—​ the difference between normal sadness and depressive disorder.

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CH A PT E R

3

The Evolution of Depressive Phenotypes

Paul W. Andrews and Zachary Durisko

Abstract Depression is a heterogeneous collection of phenotypes sharing partially overlapping genes, neurobiology, and symptoms. This chapter applies an evolutionary perspective to the distinct etiologies and functions of three reliably identified depressive phenotypes: sickness behavior, starvation depression, and melancholia (i.e., depression with melancholic features). Infection and food shortage are evolutionarily ancient problems, and so sickness behavior and starvation depression probably evolved first. Melancholia probably evolved more recently and shows signs of an evolutionary design for a cognitive function. More specifically, evidence suggests that melancholia is an adaptation for promoting analytical reasoning, and probably evolved as an adaptive response to complex problems involving resource management or conflicts with close social partners. These depressive phenotypes, although distinct, are functionally similar, which explains the overlapping genetics, neurobiology, and symptomatology. In all three, depressive symptoms help the body coordinate the reallocation of limited energy resources in response to persistent threats. Key Words:  adaptation, analysis, depression, energy allocation, evolution, melancholia, sickness behavior, starvation, suicide, trade-​offs

Introduction

Depressive disorders, as they are currently diagnosed, encompass a suite of behavioral syndromes defined by sad mood and anhedonia that are otherwise heterogeneous in symptom and cause (Akiskal, 2008). Different depressive disorders are distinguished by the presence or absence of other behavioral symptoms. There are many diagnostic categories, and not all of them are reliable, so it is not clear that they all “carve nature at its joints.” Moreover, many etiological pathways can lead to clusters of depressive symptoms, including some not typically classified as psychiatric disorder (Durisko, Mulsant, & Andrews, 2015). In this chapter, we focus on the evolution of three reliably identified depressive phenotypes with overlapping symptoms: sickness behavior, starvation depression, and melancholic depression. The symptoms of each are listed in Table 3.1. 24

Sickness behavior is induced following the onset of a challenge to the immune system and is thought to promote recovery. Starvation depression is caused by a persistent lack of food and is thought to promote survival during periods of energy shortage. Of clinically diagnosed episodes of major depression, melancholia is the most reliably diagnosed and most common subtype, often accounting for 50% or more of episodes in community or patient samples (Angst, Gamma, Benazzi, Ajdacic, & Rössler, 2007; Xiang et  al., 2012). Some episodes of melancholic depression used to be termed endogenous to refer to the lack of an obvious environmental trigger. However, these causes are sometimes underreported due to their severe, personal, or embarrassing nature (Leff, Roatch, & Bunney, 1970; Mundt, Reck, Backenstrass, Kronmüller, & Fiedler, 2000). In

 

Table 3.1.  The Symptomatic Similarity between Sickness Behavior, Starvation Depression, Melancholia, and Inescapable Shock Symptoms

Sickness Behavior

Starvation

Melancholia

Inescapable Shock (Rats)

Anhedonia

↑3,11

↑9

↑21

↑22

Weight

↓3,11

↓9

↓21

↓22

Sexual behavior

↓3,11

↓9

↓21

↓22

HPA axis activity

↑3

↑20

↑21

↑22

Altered focus of attention

Yes10

Yes9

Yes1

Yes12,14

Complex information processing

No3,11

?

Yes1

Yes12,14

Sleep duration

↑7

—​13

↓21

↓16

REM sleep

↓11

↓13

↑21

↑16

Slow wave sleep

↑11

↑13

↓21

↓16

Passive coping

Yes3

?

Yes15

Yes22

Motor activity

↓3,11

↑6

↓21

↓8

Body temperature

↑3,11

↓18

↑19

↑4

Preference for carbohydrate over protein

↑3

↓17

↑2

↑5

Andrews and Thomson (2009); 2 Christensen and Brooks (2006); 3 Dantzer (2001); 4 Deak et al. (1997); 5 Dess (1992); 6 Exner et al. (2000); Hart (1988); 8 Jackson et al. (1978); 9 Keys et al. (1950); 10 Kramer et al. (2002); 11 Larson and Dunn (2001); 12 Lee and Maier (1988); 13 MacFadyen et al. (1973); 14 Minor et al. (1984); 15 Neumann et al. (2011); 16 O’Malley et al. (2013); 17 Overmann (1976); 18 Rising et al. (1992); 19 Rausch et al. (2003); 20 Schwartz and Seeley (1997); 21 Taylor and Fink (2008); 22 Vollmayr and Henn (2003). “?” indicates data are not available. “—​” indicates no significant change in the symptom. Symptoms shaded in gray are shared across phenotypes. 1 7

fact, melancholia is highly associated with adverse events and life stressors (Taylor & Fink, 2008). Although melancholia is not a separate diagnostic category in the Diagnostic and Statistical Manual for Mental Disorders (DSM), a recent post for The New  Yorker revealed that the writers of the latest edition did not create a separate category because its reliability would have drawn attention to the subjectivity and imprecision associated with other DSM categories (Greenberg, 2013). The multiple pathways for producing depressive syndromes probably require multiple evolutionary explanations. There are many such hypotheses (Durisko et al., 2015; Hagen, 2011), although most have not been rigorously tested and many are undoubtedly incorrect. This chapter focuses on hypotheses that offer insights into the symptomatic similarity between sickness, starvation, and melancholic depressions. We first define relevant evolutionary concepts.

Adaptation and Disorder

An important evolutionary insight into mood disorders is that some may not really be “disorders” at all. The current DSM acknowledges the inability to “completely separate normal and pathological symptom expressions” in its diagnostic system (APA, 2013, p.  21). In this volume, Jerome Wakefield argues that all unambiguous cases of disorder involve an adaptation that is not performing its evolved function, and we adopt this definition in this chapter. An adaptation is a trait that has been modified by natural selection over evolutionary time for a unique gene-​ propagating effect (Andrews, Gangestad, & Matthews, 2002). That gene-​propagating effect is then called the function of the trait. Like man-​made machinery, adaptations can break down abruptly or gradually decline in function, and these events can be termed malfunctions or dysfunctions. The vertebrate eye is a classic example of an evolved adaptation, yet it is susceptible to many known malfunctions (or Andrews, Durisko

25

 

disorders). Under this evolutionary definition of disorder, a properly functioning adaptation cannot be disordered. As we show in this chapter, all the purportedly pathological symptoms of depression, including anhedonia, reduced sexual function and appetite, altered cognition, and suicidal behavior, can be produced by properly functioning adaptations. This makes it difficult to distinguish true instances of disorder and “normal” responses to stressors by such criteria. Importantly, the claim that many serious episodes of depression may be adaptive does not imply that they should not be treated. Childbirth is also a normal adaptation with an evolutionarily ancient history, but it often requires medical intervention because it can be dangerous in humans. Nevertheless, it is a cardinal rule of medicine that appropriate treatment depends on an accurate understanding of etiology. Determining an appropriate treatment for depression depends on determining whether it is a properly functioning adaptation or a malfunctioning adaptation. How do we recognize adaptations and determine whether they are functioning properly? This cannot be done reliably by measuring the reproductive success associated with the trait in the modern environment (Andrews et al., 2002). Claims about adaptations are historical and refer to the ancestral selection pressures that shaped the trait in question. Reproductive success associated with an adaptation may be different in modern and ancestral environments. Adaptations associated with lower reproductive success in modern environments exist because they conferred an advantage in ancestral environments. Our preference for sugar was undoubtedly adaptive in ancestral environments where refined carbohydrates were not freely available. Although this preference can cause disorders and reduce reproductive success in modern environments (diabetes, heart disease, etc.), the preference is not itself a disorder. Rather, it is an adaptation that was forged in ancestral environments, and it is still operating as it evolved to operate even though the environment has changed. The only reliable method for identifying adaptations is to decompose all the working parts of a trait and figure out how they interact together. This process has been called “reverse engineering” (Andrews et al., 2002; Tooby & Cosmides, 2000). Biological organisms are highly organized, well-​ coordinated assemblages of matter, and evolution 26

by natural selection is the only known natural process that can generate nonrandom biological organization or coordination. If a trait exhibits a highly nonrandom organization or coordination for promoting a particular effect, so that the only plausible explanation is that natural selection shaped the trait for the effect, then the trait is an adaptation and the promoted effect is its function. Thousands of years of reverse engineering research, for instance, has revealed that the eye is composed of multiple highly organized structures (retina, lens, pupil, iris, etc.). These components operate together in a highly nonrandom, coordinated fashion to promote vision. The only plausible scientific account for this design is that natural selection shaped the eye over evolutionary time to promote vision. During the reverse engineering process, researchers develop a conceptual “blueprint” of the structure and operation of the adaptation. This blueprint also provides a natural understanding of the ways in which the adaptation can malfunction and cause disorder. For instance, the conceptual blueprint of the eye allows us to understand many specific disorders (e.g., hardening of the lens, detachment of the retina from the choroid, increased intraocular pressure due to degradation of the trabecular meshwork).

Depressive Adaptations

Depressive syndromes are almost certainly not a hodgepodge of symptoms without causal ordering. Evolutionary theory suggests that they can be usefully organized around the emotion of sadness (Figure 3.1). Emotions are ancient adaptations that evolved to coordinate body systems to promote adaptive responses to problems in the environment (Tooby & Cosmides, 1990). The behavioral outputs of emotions are not fixed, so the evolved function of emotions must lie upstream, at the level of information processing, where the body can assess the situation and make decisions about how best to respond. Thus, emotions such as sadness are thought to be an integral part of the causal pathway by which the body produces adaptive responses to the environment. They are reliably triggered by specific situations in the environment, and they coordinate various systems of the body to promote an information-​processing function. Because depressive phenotypes are really clusters of symptoms, of which sadness is one, some symptoms may be part of the triggering process, whereas others are part of

The Evolution of Depressive Phenot ypes

 

Reproduction

Cognition

Situational Trigger

Sadness

Immune function

Decisionmaking process

Growth

Maintenance

Figure 3.1.  Hypothetical schematic of the causal structure of depressive adaptations.

the subsequent coordination process. We discuss sickness behavior and starvation depression in terms of this general causal model.

Sickness Behavior

Infection is a problem facing all organisms (Fuhrman, 1999), and sick organisms exhibit an adaptive depressive phenotype that is evolutionarily ancient (Dantzer, 2001; Hart, 1988). Sickness behavior is present across mammals (Hart, 1988), and aspects can even be found in insects (Chambers & Schneider, 2012). Obviously, eliminating a pathogen from the body requires a response from the immune system. This response is not fixed, but rather is tailored to the pathogen, so pathogen-​specific information must be processed to create the appropriate response. Generating an appropriate immune response requires massive amounts of energy, so the body reallocates energy to immune function while downregulating other energetically expensive processes, including growth, reproduction, and physical activity (Lochmiller & Deerenberg, 2000) (Figure  3.2). General cognitive functioning declines during infection, because attention is drawn to painful sensations (Kaplan, Trevino, Johnson, & Levy, 2003; Kramer et  al., 2002), which promotes lethargy and rest. Depressive symptoms play a role in coordinating these trade-​ offs (Dantzer, 2001; Hart, 1988). Lethargy and anhedonia reduce energy spent on normally rewarding activities such as sex and play. Appetite also decreases, which may seem puzzling given the

energetic demands of the immune system. But organisms must often expend considerable energy to acquire food and may be better off conserving energy (Hart, 1988). Moreover, the consumption of foods high in iron (e.g., animal protein) can promote pathogen replication (Hart, 1988), whereas the immune system preferentially runs on carbohydrates (Wolowczuk et al., 2008). Thus, although appetite and overall caloric intake are reduced during infection, the proportion of carbohydrates in the diet increases and the proportion of protein decreases (Dantzer, 2001).

Starvation Depression

Starvation is also a problem that all organisms face, and it can trigger an adaptive depressive phenotype (Keys, Brozek, & Henschel, 1950). To outlast food shortages, the body must monitor systems crucial to maintenance and carefully triage the allocation of energy stored in tissues (adipose tissue, muscle) to maintenance functions (McCue, 2012; Prentice, 2005) (Figure 3.2). The brain in particular is preserved, and other tissues are sacrificed (Ruiz-​Núñez, Pruimboom, Dijck-​ Brouwer, & Muskiet, 2013). Growth, reproduction, and immune function are downregulated to reduce metabolism (Prentice, 2005; Prentice & Keneba, 2007). The symptoms of depression triggered during starvation coordinate these trade-​offs (Engel & Schmale, 1972). For instance, many hedonic activities (e.g., sex, social interaction) are energetically expensive, so interest in such activities is reduced. Andrews, Durisko

27

 

100 90

Energy Allocation (%)

80 70 60

Reproduction Maintenance Growth Physical Activity Cognition Immune System

50 40 30 20 10 0 Normal Baseline

Sickness Behavior

Starvation

Melancholic Depression

Figure 3.2.  Hypothetical energy allocation during sickness, starvation, and depression, relative to normal baseline.

A Generalized Hypothesis

Sickness behavior and starvation depression share a functional similarity. In both, depressive symptoms help coordinate energetic trade-​offs in response to persistent threats—​infection and starvation. In sickness behavior, immune function gets prioritized access to resources while growth and reproduction are reduced. In starvation, maintenance functions get prioritized access to resources while growth, reproduction, and immune function are reduced. This suggests that natural selection may favor the evolution of depressive phenotypes in response to any persistent threat in which the body must make sustained trade-​offs in the allocation of limited resources. This generalized resource allocation hypothesis suggests that any specific hypothesis for depression that is structured around resource allocation logic warrants greater attention and should be rigorously tested. In the next section, we focus in detail on one hypothesis for melancholic depression.

The Evolution of Melancholic Depression

The symptoms of sickness behavior and melancholic depression are strikingly similar (Table 3.1), and they share common genes and neurobiology (Dantzer, O’Connor, Freund, Johnson, & Kelly, 2008; Raison & Miller, 2013). This similarity has spurred hypotheses characterizing depression as a disorder of the immune response (Dantzer et  al., 2008) or as an adaptive response to social stressors that predict the risk of infection (Raison & Miller, 28

2013). However, these hypotheses are inconsistent with the fact that sickness behavior and melancholia have key symptomatic differences. Cognition is generally impaired during sickness, and more time is spent in slow wave sleep (Dantzer, 2001; Larson & Dunn, 2001). In contrast, melancholic depression is associated with an increase in rapid eye movement (REM) sleep (Taylor & Fink, 2008) and rumination (Nelson & Mazure, 1985). Rumination is a cognitive symptom referring to intrusive, distraction-​resistant thoughts focused on the circumstances surrounding the episode (Andrews & Thomson, 2009). We can now draw powerful inferences about the origin and function of melancholia. Although sickness, starvation, and melancholic depressions are all expressed in humans, the cognitive nature of melancholia suggests that it evolved more recently (Figure 3.3). The neurobiology they share in common likely first evolved to promote sickness behavior or starvation depression. Later, it was coopted and modified to promote melancholia. The evidence of cooption lies in the overlapping symptoms, genes, and neurobiology. The evidence of modification comes from the symptomatic differences, which must involve distinct neurobiology. Even though melancholia probably evolved more recently, it may not be unique to humans since the inescapable shock model of depression is symptomatically similar (Table 3.1). The unique symptoms of melancholia suggest that the modification is attributable to natural selection for a cognitive function. That is,

The Evolution of Depressive Phenot ypes

 

Animalia

Porifera (sponges) Cnidaria (jellyfish)

Arthropoda (fruit fly) Rodentia (mouse) Melancholia

Starvation depression Sickness behavior

Nematoda (C. elegans)

Homo (humans)

Figure 3.3.  Tentative phylogeny of starvation depression, sickness behavior, and melancholia.

the neurological mechanisms that produce melancholic symptoms may be an adaptation for enhanced cognition that evolved as an extension of the energy reallocation machinery of sickness behavior. First, ruminative thinking involves an analytical processing style in which complex problems are broken into smaller, more manageable components, which are then studied sequentially (Andrews & Thomson, 2009). Analysis is a highly useful approach to solving complex problems, such as in science, mathematics, and many areas of modern life. Second, rumination is resistant to distraction (Andrews & Thomson, 2009). To keep track of the components, analysis requires working memory (WM), a memory system in which information is kept active because it is useful for ongoing processing. As WM load increases, tasks become more vulnerable to interruption because it is easier for task-​ irrelevant stimuli to displace relevant information (Kane & Engle, 2002). The distraction-​resistant nature of rumination may promote analysis by reducing the vulnerability to interruption (Andrews & Thomson, 2009). Third, the increase in REM sleep also points to a cognitive function, since REM sleep helps consolidate hippocampal memory representations that encode complex information (Rasch & Born, 2013). Each symptom, by itself, probably reflects nontrivial neurological modification. The confluence of them together suggests that melancholia exhibits highly nonrandom biological organization for the sustained processing of complex information. The fact that evolution by natural selection is the only known source of highly nonrandom biological organization suggests that there is an adaptation for producing melancholic symptoms in response to complex stressors, assisting in the processing and resolution of those stressors. To

be clear, the claim is that the adaptation is in the neurological machinery for producing melancholic symptoms, not in the symptoms itself, as those could also be produced by a malfunction in that machinery. Prior research has proposed that depression evolved as a response to complex problems in which the symptoms help promote uninterrupted analysis (Andrews & Thomson, 2009). This analytical rumination hypothesis (ARH) was explicitly framed in resource allocation logic. Specifically, the ARH is based on the fact that WM resources are limited, which makes cognitive processes, including analysis, increasingly vulnerable to interruption as WM load increases. Under the ARH, the problem that triggered the depressive episode is complex and important to resolve, so it should get prioritized access to WM resources. To do this, other processes that could draw WM resources away from the triggering problem must be inhibited, and depressive symptoms help coordinate this trade-​ off. For instance, anhedonia reduces interest in normally pleasurable activities that would otherwise draw attention away from the triggering problem. Thus, the ARH can be framed in terms of the generalized resource allocation hypothesis wherein the limited resource is WM. As described below, rumination is likely to be energetically expensive as well. We now turn to several testable implications of the ARH.

Analytical Processing is Promoted Throughout the Continuum of Melancholic Symptoms

The analytical processing style could exist throughout the continuum of symptom severity for melancholia (Andrews & Thomson, 2009). There is, in fact, substantial evidence for this prediction. An analytical rumination style called “reflective pondering” has been found in both subclinical and clinical samples (Joormann, Dkane, & Gotlib, 2006; Treynor, Gonzalez, & Nolen-​Hoeksema, 2003). In our own work, we have developed a new instrument specifically for assessing analytical rumination, and it shows positive correlations with depressive symptoms in cross-​sectional studies of both clinical and subclinical samples (Barbic, Durisko, & Andrews, 2014; Durisko et al., unpublished). If depression focuses attention on analyzing the triggering problem, then fewer cognitive resources should be available for other things. Moreover, this effect should be present across the range of depressive symptomology. Consistent with this, depressed Andrews, Durisko

29

 

patients often perform worse than nondepressed controls on abstract cognitive tasks in the laboratory (Austin, Mitchell, & Goodwin, 2001). That the performance decrements are due to an altered focus of attention, rather than impaired cognition, is well supported. In clinical and subclinical samples, the performance decrements can be eliminated by simple attentional interventions such as thinking about a black umbrella for a few minutes (reviewed in Andrews & Thomson, 2009). In short, focused analysis of the triggering problem appears to explain performance decrements on abstract analytical tasks. People with depression are more likely to show performance enhancements on laboratory tasks similar to the problems in their lives (Andrews & Thomson, 2009). As we discuss below, depressed people often face problems in their lives that involve cost–​benefit trade-​offs. Consequently, they seem to reliably outperform nondepressed controls on laboratory tasks that involve making a decision based on an optimization or a cost–​benefit analysis (Table 3.2). This enhanced performance has been found across the range of depressive symptomology, including people with severe symptoms (Keller, Lipkus, & Rimer, 2002; Overall & Hammond, 2013) and patients hospitalized for depression (von Helversen, Wilke, Johnson, Schmid, & Klapp, 2011).

Depression Is Triggered by Complex Problems

The ARH predicts that depression is triggered by complex problems for which sustained, uninterrupted analysis is an adaptive response. We discuss two complex problems with evolutionary relevance. First, a social dilemma is a conflict with a close partner (mate, family member, friend) with whom it is important to maintain cooperative relations (Andrews & Thomson, 2009). Social dilemmas are complex problems because they are difficult to resolve in one’s favor without risking the erosion of the cooperative bond. Social dilemmas are a stronger predictor of depressive symptoms than simple interpersonal conflict (Gautam, Saito, Houde, & Kai, 2011; Pagel, Erdly, & Becker, 1987). Second, resource management dilemmas, in which people have too little time, money, or other resources to meet demands, are complex because a cost–​benefit analysis must be performed to determine how scarce resources should be allocated. Resource management dilemmas are positively associated with depressive symptoms (Roxburgh, 2004). 30

Table 3.2.  Depressed Mood Enhances Performance on Tasks Involving Cost–​Benefit Analysis Effect

Level of Depression

Reference

Experimentally induced

Hertel et al. (2000)

Sensitivity to Subclinical costs and benefits (BDI > 10) of social options Subclinical (BDI-​SF > 5)

Accurate risk assessment

Optimal choices

Hokanson et al. (1980) Pietromonaco and Rook (1987)

Major depression Keller et al. (CES-​D ≥ 16) (2002) Major depression Smoski et al. (HAM-​D > 13) (2008) Experimentally induced

Au et al. (2003)

Major depression von Helversen (hospitalized) et al. (2011)

Salary after graduating college

Subclinical (Likert scale)

Iyengar et al. (2006)

Awareness of impairment in brain injury and schizophrenia

Subclinical (various)

Fleminger et al. (2003)

Assessment of romantic partner’s commitment

Subclinical (CES-​D)

Overall and Hammond (2013)

BDI, Beck Depression Inventory; BDI-​SF, Beck Depression Inventory-​Short Form; CES-​D, Center for Epidemiologic Studies-​Depression; HAM-​D, Hamilton Rating Depression Scale.

Bereavement is a specific type of stressor that might seem paradoxical under the ARH because analysis cannot bring back the dead. However, analysis might prevent other deaths in the future. Due to the fitness consequences, parents may be particularly likely to analyze the circumstances of a child’s death to assess if they could have done anything differently. They may grieve a lost child for years, particularly if they had negative interactions with the child immediately before the child’s death (Thieleman & Cacciatore, 2014). Bereavement may also be depressogenic if it causes resource management dilemmas, such as financial stress or household management difficulties

The Evolution of Depressive Phenot ypes

 

(Liu & Chen, 2006; Umberson, Wortman, & Kessler, 1992).

Analytical Rumination Helps People Solve, Manage, or Cope with the Triggering Problem

It is widely thought that depressive cognition is maladaptive, but the evidence for this is not strong (reviewed in Andrews & Thomson, 2009). Depression is associated with increased pessimism, but this may be an honest assessment that one faces complex problems that are difficult to solve. Moreover, such an assessment may be an important psychological state that triggers sadness and analytical rumination. People with depression also show increased attention to negative information, but such information could be useful when trying to understand and solve such problems. Finally, it is commonly argued that depressed people have poor social problem-​solving skills. Of course, the most important metric for assessing this is the ability to achieve social goals that are relevant to the depressed person’s episode. However, research in this area tends to focus on proxy variables that researchers assume are associated with effective social problem solving (empathy, voice tone, cooperativeness). One area of research that might be taken as evidence against effective problem solving proposes that depression alters the brain, increases the depressogenic impact of minor stressors, and eventually disassociates episodes from stressors. This kindling hypothesis is widely thought to have substantial empirical support (e.g., Monroe & Harkness, 2005), and it suggests that depression cannot solve problems when they occur in the absence of problems. For instance, among people currently experiencing a bout of depression, people with greater histories of depression report fewer precipitating stressors. Although consistent with the kindling hypothesis, it is also consistent with the alternative that people with greater histories of depression have a stable genetic sensitivity to stressors. One study attempted to rule out this alternative using a longitudinal within-​person design (Kendler, Thornton, & Gardner, 2000). Using Cox proportional hazards analysis, the authors reported a significant interaction between the number of prior episodes of depression and exposure to a stressor on the risk of a new episode of depression. But its value was less than 1, which could suggest that a history of depression, rather than sensitizing the brain, protects against new episodes of depression. Finally, kindling studies rarely ensure that participants are

unmedicated, which is problematic because antidepressant medications (ADMs) can produce a pattern similar to kindling (Andrews, Kornstein, Halberstadt, Gardner, & Neale, 2011). ADMs disturb monoamine neurotransmitter levels, and the brain’s homeostatic mechanisms attempt to restore equilibrium. When ADMs are discontinued, these homeostatic forces can cause relapses that are unassociated with stressors. The most crucial issue for the ARH is whether depressive rumination helps people solve or cope with the problem that triggered the episode (Andrews & Thomson, 2009). The current evidence does not allow conclusive determination because most studies evaluate depressive cognition using laboratory tasks rather than the triggering problem. One relevant experiment explored the effects of mood in a simulated market (Au, Chan, Wang, & Vertinsky, 2003). Participants were finance or economics students with knowledge of, or experience with, simulated or real financial trading. On each round participants were provided with historically accurate charts about the daily closing prices of currencies in the past 3 years and with news items that described influential market factors, the market movement, and comments from leading practitioners and economists from prominent investment banks. Careful analysis of this information would allow participants to make good predictions about the relative movement of Deutsche marks and Swiss francs. Performance was assessed by whether participants decided to buy or sell the correct currency on that round (accuracy) and by how much money the participants gained or lost (profit), which in turn depended on accuracy and the amount invested. Mood was manipulated by providing participants with false feedback on the first round. In the positive mood induction, participants received a high profit for their decision, regardless of what they actually did. In the sad mood induction, participants took a substantial loss. In the neutral mood induction, participants broke even. Participants who had sad mood induced by false negative feedback on the first round made more accurate decisions on subsequent rounds than those in the positive and neutral conditions. This interesting study suggests that sadness may help promote analysis of the triggering problem. Factor analyses of rumination scales show two different subtypes: one focused on the past (“brooding”) and another associated with increased analysis (“reflective pondering”) (Joormann et al., 2006; Treynor et  al., 2003). In longitudinal studies, Andrews, Durisko

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brooding is associated with higher depressive symptoms over time, and it is commonly thought to be maladaptive. However, reflective pondering is associated with lower symptoms over time and may reflect a positive effect of analysis on problem solving (Joormann et  al., 2006; Treynor et  al., 2003). Similarly, interventions that naturally encourage rumination (e.g., journal writing about your strongest thoughts and feelings related to the episode) tend to shorten the duration of clinical episodes (Krpan et al., 2013). Therapies that foster analysis of problems also reduce symptoms. Rumination-​ Focused Cognitive–​Behavioral Therapy helps promote the reflective (analytical) style of rumination through the use of functional analytic techniques (Watkins et  al., 2007). Similarly, Concreteness Training involves the depressed person imagining personally relevant emotional events, focusing on the unique details of the event, and attempting to understand why the event occurred (Watkins, Baeyens, & Read, 2009).

growth and reproduction. For instance, hippocampal neurogenesis is downregulated, which may contribute to a decline in hippocampal volume during depression (Arnone et  al., 2012). Although many researchers consider this pathological, many organisms show plasticity in neurogenesis in response to environmental demands (Gross, 2000). For instance, the attenuation of synapse strength in the hippocampus (a phenomenon called long-​term depression) is important in WM tasks (Laroche, Davis, & Jay, 2000). Long-​term depression is associated with a loss of dendritic spines in hippocampal neurons (Zhou, Homma, & Poo, 2004), which may contribute to the shrinkage in this region. Moreover, the shrinkage appears to be reversible, since depressed patients who remit without medication have normal hippocampal volumes (Arnone et al., 2012). Thus, neurogenesis may be temporarily downregulated because it is expensive and interferes with WM processes.

Analytical Rumination Is Energetically Expensive

Again, our analysis suggests that any hypothesis for depression based in resource allocation logic warrants closer scrutiny. For instance, depression may have evolved to inhibit effort that is likely to be wasted because circumstances are unpropitious (Nesse, 2000). Another hypothesis proposes that depression can have negative effects on close social partners who otherwise benefit from the relationship (e.g., mates, kin, allies). The withdrawal of those benefits during  depression could motivate social partners to help depressed individuals resolve their problems. Thus, depression could have evolved to divert energy, time, effort, or other valuable resources from close social partners to motivate them to provide help (Hagen, 2003; Watson & Andrews, 2002). This hypothesis provides a possible explanation for the link between depression and suicidal behavior and deliberate self-​harm. Although suicidal behavior is commonly considered to be evidence of mental disorder, there are clear examples of adaptation for suicide in nature (Andrews & Thomson, 2010). One type of suicidal behavior has the social goal of seeking or leveraging help from others (Stengel & Cook, 1958). Such suicide attempts are sometimes thought to be “bluffs,” but the risk of death must be great enough to influence social partners (Andrews, 2006). Thus, some suicide attempts could be a desperate gamble in which a nontrivial risk of death is incurred to leverage help from social partners. Overall, the gamble can be favored by natural

Rodents exposed to inescapable shock show an increase in glycolytic pathways to generate adenosine triphosphate (ATP), the primary molecule used to fuel biological processes (Mallei et al., 2011; Uehara, Sumiyoshi, Itoh, & Kurachi, 2007). Glycolysis generates less ATP per glucose molecule than oxidative phosphorylation, but it produces ATP at a faster rate (Pfeiffer, Schuster, & Bonhoeffer, 2001), so glycolysis is an indicator of metabolic activity (Shulman, Hyder, & Rothman, 2001). Moreover, glycolysis does not use oxygen, and in the brain it occurs in astrocytes that rely on stored glucose rather than blood-​ borne glucose. Consequently, neuronal activity and blood flow can be decoupled in regions relying heavily on glycolysis (Shulman et al., 2001), such as the prefrontal cortex (Vaishnavi et al., 2010). In fact, the correlation between regional activity and blood flow, normally positive in nondepressed people, becomes negative in many brain regions of patients with unmedicated depression (Dunn et al., 2005). This evidence suggests that depressive cognition is so energetically expensive it can be supported only by glycolysis.

Other Energetically Expensive Processes Are Downregulated

Further evidence that depression is energetically expensive comes from the fact that other energetically expensive activities are downregulated, such as 32

Other Depressive Adaptations?

The Evolution of Depressive Phenot ypes

 

selection if the social rewards are great enough, but some people may die from the attempt. Depression and suicidal behavior may therefore be part of the same tactical dimension for leveraging help from others. Natural selection can also favor extremely deadly suicide attempts that the attempter has little chance of surviving. The circumstances favoring the evolution of such attempts require the individual to have little chance of future reproduction, and close genetic relatives must have reduced fitness by caring for the individual (e.g., the individual has chronic health problems). Some empirical support for this burdensomeness-​to-​kin hypothesis has been found in humans (deCatanzaro, 1995). Both types of suicidal behavior may require analysis of the individual’s situation (e.g., the likely risks and benefits of making a suicide attempt, and the effects of the attempt on kin), which may also contribute to the association with depression (Andrews & Thomson, 2010). Indeed, adolescents appear to engage in a cost–​ benefit analysis before making a suicide attempt during conflict with their parents (Andrews, 2006).

Conclusions

Sickness behavior, starvation depression, and melancholia share partially overlapping symptoms, neurobiology, and genes. The common neurobiology probably originated to coordinate a response to either infection or starvation, whereas melancholia involved the subsequent cooption and modification of this machinery. These three syndromes share a functional similarity:  coordinating trade-​offs in limited resources in response to persistent threats (starvation, infection, complex problems such as social or resource management dilemmas). The energy reallocation that occurs in melancholia may often be the output of a properly functioning adaptation. First, melancholia is often triggered by complex problems that (like starvation and infection) are so persistent they likely require a sustained reallocation of energy. Second, by directing energy toward promoting analysis of those problems, the cognitive effects of melancholia show an ecological correspondence to the situational causes. The correspondence suggests that the analytical processing style might help depressed people solve the problems that triggered their episodes. Some evidence supports this prediction, though it should be researched in greater detail. Third, by upregulating cognition and downregulating growth and reproduction, melancholia appears to coordinate

various biological systems in the body in a nonrandom fashion to promote uninterrupted analysis. Given the evidentiary demands of demonstrating adaptation, this prediction should also be tested more rigorously. The distraction-​ resistant nature of rumination is particularly worthy of further study because it is thought to promote unproductive, repetitive, circular thinking. However, distraction resistance may have evolved to promote problem solving by adaptively reducing the vulnerability of analysis to interruption (Andrews & Thomson, 2009). The ARH predicts that many of the behavioral and cognitive symptoms of depression—​anhedonia, social withdrawal, lethargy, sleeping and eating less, difficulty concentrating—​ act in a highly nonrandom, coordinated fashion to facilitate analytical rumination by promoting distraction resistance (Andrews & Thomson, 2009). Evolutionary theory offers hope for a better understanding of the etiology of depressive phenotypes, including some currently classified as clinical disorders. This, in turn, could lead to more effective treatments. Future research will need to test whether this framework can improve clinical practice in mental health.

References

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CH A PT E R

4

Phenomenology and Course of Mood Disorders

Daniel R. Strunk and Katherine E. Sasso

Abstract In this chapter, we provide an overview of the phenomenology of the mood disorders, including attention to both symptoms and functional impairment. Our overview emphasizes the heterogeneity among those with these disorders, as well as the most influential approaches to describing this variability across and within bipolar and depressive disorders. We discuss the degree of overlap between bipolar and depressive disorders, paying special attention to the clinical significance of low levels of manic symptoms. We also review several influential symptom-​based specifiers, including those that refer to melancholic, atypical, anxious, and psychotic features. Having considered variability in the symptoms of these disorders, we then consider the course of these disorders. We survey the remarkable variability in course as well as current approaches to characterizing these differences. We conclude with a discussion of future directions. Key Words:  phenomenology, course, bipolar disorders, depression, subtypes, persistent, recurrent

The mood disorders involve experiences of abnormal negative or positive moods, but the features of these disorders are not limited to aspects of mood. In the depressive disorders, “non-​mood” symptoms include reduced interest and pleasure, changes in weight, sleep dysregulation, psychomotor agitation or retardation, loss of energy, feelings of worthlessness, difficulty concentrating, and thoughts of—​ including preoccupation with—​ death. In the bipolar disorders, characteristics include grandiosity, reduced need for sleep, flight of ideas, distractibility, increased goal-​ directed activity, as well as engaging in behaviors with the potential for painful consequences (e.g., spending sprees, sexual indiscretions). In their most severe forms, mood disorders can lead to dramatic, long-​ term functional impairments that wreak havoc on the lives of those affected. Although clinically significant distress or impairment is required for the

diagnosis of any of the mood disorders, these disorders show tremendous variation in the severity of the impairment. There is also great variation in the specific symptoms of those who experience mood disorders—​ across distinct disorders, but also even among those meeting criteria for the same disorder. Another important form of variability is in the course of the mood disorders, with some people experiencing a single discrete episode, whereas others experience a chronic or recurrent course. In this chapter, we provide an overview of the phenomenology of mood disorders, emphasizing the tremendous heterogeneity that characterizes these disorders. We review current diagnostic criteria for the mood disorders, evidence of the functional impairment associated with these disorders, current approaches to subtyping these disorders, and what is known about the course of these disorders.

37

 

Depressive and Bipolar Disorders: Current Diagnostic Categories

The Diagnostic and Statistical Manual of Mental Disorders–​5th Edition (DSM-​5; American Psychiatric Association [APA], 2013), the dominant diagnostic system for psychopathology in the United States, divides the mood disorders into two groups:  the depressive disorders and bipolar and related disorders. The depressive disorders include: major depressive disorder (MDD), disruptive mood dysregulation disorder, persistent depressive disorder, and premenstrual dysphoric disorder (DSM-​5; APA, 2013). Bipolar diagnoses include bipolar I disorder, bipolar II disorder, and cyclothymic disorder (DSM-​5; APA, 2013). In this chapter, our coverage of the depressive disorders is focused primarily on MDD and its recurrent forms, which are now classified as persistent depressive disorder. For the bipolar disorders, we focus on bipolar I disorder and, to a lesser extent, bipolar II disorder. MDD is the most common of the mood disorders, as well as the most common of all psychological disorders overall. In order to receive a diagnosis of MDD, an individual must meet criteria for a major depressive episode (MDE), which requires the following over a period of at least two weeks: 1. Experiencing at least five of nine depressive symptoms, with at least one of the symptoms being either depressed mood or loss of interest or pleasure; 2. Impairment of normal functioning; and 3. The symptoms not being attributable to the effects of a substance, another medical condition, or another disorder. If one has experienced manic symptoms (such as a manic or hypomanic episode), then a diagnosis of one of the bipolar disorders is indicated. These criteria have remained relatively unchanged since DSM-​ III, with the exception of changes to the bereavement exclusion (as discussed in Chapter 2). To provide an indication of how common MDD is, we consider analyses of the National Comorbidity Survey Replication (NCS-​ R), which examined DSM-​IV diagnoses as assessed through clinical interviews in a representative national sample of 9,282 adults in the United States. Estimates from that study suggest a 12-​month prevalence of 7% and a lifetime prevalence of 16% (Kessler et  al., 2003; Kessler et  al., 2014; see also Bromet et  al., 2011). Point prevalence estimates suggest 2–​ 4% of the population meets criteria for MDD at any one time (Kessler & Bromet, 2013). As is true for the NCS-​R, 38

estimates of the prevalence of MDD over time largely come from large-​scale epidemiological studies, which have tended to rely on retrospective reports. Lifetime prevalence estimates reflect the prevalence up until the time of the study. Of course, some participants who have not experienced a mood disorder may go on to experience one later in life. Actuarial methods for estimating the projected total lifetime risk in the NCS-​R for those who have not yet lived through the risk period have provided a projected lifetime prevalence rate of 23% (Kessler et  al., 2005). Although this estimate may seem high, even it may be too low. Repeated assessments with comprehensive review of past periods are likely to yield more accurate information than one-​ time retrospective reports. In a longitudinal study that followed participants from childhood, the cumulative incidence of depression through age 30 was 51% (Rohde, Lewinsohn, Klein, Seeley, & Gau, 2013; see also Moffitt et al., 2010). Such estimates suggest that the experience of MDD may be so common that mental health professionals may need to reconsider how they define the disorder (as discussed in Chapter 8). Turning to the bipolar disorders, a diagnosis of bipolar I  disorder requires at least one manic episode, with such an episode being defined by the following core features: 1. For at least one week (unless hospitalization is required), display of a continually abnormal, inflated, unrestrained, or irritable mood, in addition to continuous heightened energy or activity for most of every day; and 2. At least three of the following symptoms (four if the previous criterion was satisfied only through irritable mood): grandiosity or inflated self-​esteem, reduced need for sleep, increased talkativeness or pressured speech, flight of ideas, being very easily distracted, increased activity or agitated movements, and risky behaviors with the potential for harmful consequences (e.g., excessive spending, risky sexual behaviors). These episodes may take on different forms for different individuals, but are all characterized by dramatic shifts in mood. For some, mood is elevated, giving them the feeling they are invincible, while for others, these shifts result in extreme irritability and agitation. Such mood shifts are accompanied by changes in cognition and self-​ perception, which are also reflected in behavioral changes, such as excessive energy, pressured speech, or engaging in high-​risk activities. In clinical samples, about half of those with bipolar I  disorder

Phenomenology and Course of Mood Disorders

 

experience psychotic features such as hallucinations or delusions (Judd et  al., 2002). Although a diagnosis of bipolar I disorder does not require having experienced an MDE, more than 90% of those who experience a manic episode later experience recurrent depressive episodes (Fiedorowicz et  al., 2011). Recent prevalence estimates drawn from the NCS-​R study suggest that for bipolar I  disorder, 12-​ month prevalence is 0.6%, with a retrospectively assessed lifetime prevalence of 1.0% (Merikangas et al., 2007). Whereas bipolar I disorder requires the experience of a manic episode but not an MDE, bipolar II disorder requires the experience of an MDE as well as a hypomanic episode. Hypomanic episodes share features with manic episodes, but are defined by fewer symptoms, a shorter duration (but at least four days), and a change in functioning without that change being large enough to constitute marked impairment. These episodes cannot include psychotic features or require hospitalization. For bipolar II disorder, 12-​month prevalence was been estimated at 0.8% in the NCS-​R, with a lifetime prevalence estimate of 1.1% (Merikangas et al., 2007). When considering bipolar I or II disorder, the projected total lifetime risk from the NCS-​R study was estimated to be 5.1% (Kessler et al., 2005). Symptoms of mania that are insufficient to warrant a diagnosis of bipolar I  or bipolar II disorders can be captured by other diagnoses, including cyclothymic disorder. Cyclothymic disorder is defined by a period of at least two years marked by periods of both hypomanic symptoms and depressive symptoms, with these symptoms being present for at least half this time, and no symptom-​free period lasting two months or more. Recent estimates of clinically significant bipolar spectrum symptoms including cyclothymic disorder as well as bipolar I and II suggest a 12-​month prevalence estimate of 1.4%, with a lifetime prevalence of 2.4% (Merikangas et al., 2007).

Functional Impairment

By definition, mood disorders involve clinically significant distress or impairment in important areas of functioning; however, the nature of these impairments and the full scope of their impact on the lives of those with these disorders is something that researchers have been slower to appreciate, perhaps in part because such impairments are somewhat difficult to measure. Since 1990, a group of researchers has been reporting on a large effort to compare the total cost of various conditions and diseases (i.e., the “global burden of disease”

approach), which they have achieved by providing estimates of disability-​adjusted life years (DALYs). DALYs reflect the combination of years of life lost due to premature death (as in the case of suicide or heart disease) and years lost to disability, with these values being determined by both the magnitude of the disability involved and the number of years with the disability. Due in no small part to its high prevalence, MDD has featured prominently in the list of leading causes of DALYs. According to the estimates made in 2010, MDD was the fourth-​ ranked cause of disability in the Western Europe, the fifth-​ranked cause in high-​income portions of North America, and the eleventh leading cause of DALYs internationally (Murray et al., 2013). Mood disorders are associated with difficulties in a variety of domains. Both depressive and bipolar disorders have been associated with poor marital outcomes (i.e., lower likelihood of marriage, poor relationship functioning) as well as poorer quality of interpersonal relationships with friends and family (Coryell et  al., 1993; Hunt, Eisenberg, & Kilbourne, 2010; Judd, Schettler, Solomon, et  al., 2008). MDD has been found to increase one’s risk for premature termination of education and teen childbearing (Kessler & Bromet, 2013). Those who meet criteria for MDD tend to be seen as less desirable social partners and rated as less competent in social skills. Mothers and fathers with depression exhibit more negative parenting behaviors than parents who do not have depression. Those who experience depression are also thought to exhibit characteristics that increase their risk for certain kinds of negative life events (for a review of these findings on interpersonal factors, see Chapter 15). Together, these impairments begin to suggest the potential scope of the functional difficulties associated with the mood disorders. Recent findings have also suggested that mood disorders have a large impact on work performance. Those with depression have an increased rate of unemployment, more absences from work, and lower productivity when working than non-​ depressed individuals (Bender & Farvolden, 2008; see review by Lerner & Henke, 2008). In an examination that considered both the costs of absenteeism and “presenteeism” (i.e., reduced productivity at work) using data from the NCS-​R study, researchers found that 1.1% of workers met criteria for bipolar I or bipolar II disorders in the past 12 months, and 6.4% of workers met criteria for MDD in that period. Those who met criteria for a bipolar disorder experienced a combined average of 65.5 days of work lost. Among Strunk, Sasso

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those with MDD, they had experienced 27.2 lost workdays. On this basis, the investigators estimated annual costs to the U.S. labor force of $14.1 billion for bipolar I and II disorders and $36.6 billion for MDD (Kessler et al., 2006). Such estimates suggest that the impact of mood disorders includes serious costs in lost productivity. Research also suggests that mood disorders may contribute to poor health (for more on this, see Chapter 30). MDD is associated with a variety of chronic physical disorders, including cancer, cardiovascular disease, diabetes, chronic respiratory disorders, and chronic pain conditions (Kessler & Bromet, 2013). While evidence that depression plays a causal role in these conditions is not well established, it is likely to complicate the course of these conditions. Depression has been associated with conditions that could lead to compromised health, including smoking and drinking, being overweight, poorer compliance with treatment regimens, and impaired immune functioning. Among the medically ill, depressive disorders predict increased morbidity and mortality (Benton, Staab, & Evans, 2007; Katon, 2003). Bipolar disorders are also associated with increased incidence of medical conditions (e.g., metabolic syndrome and migraine), as well as increased healthcare costs. Thus, there is considerable evidence that the mood disorders are associated with functional impairments in interpersonal and occupational functioning as well as poorer physical health.

Mood Disorders as a Heterogeneous Group

There is substantial heterogeneity in the experience of those who meet criteria for a mood disorder. Even among a group of individuals who all meet criteria for MDD, the symptoms can vary substantially from one person to the next. In addition, discriminating between depressive and bipolar disorders is not always simple, particularly when someone presents with a current MDE and has a history of only some hypomanic symptoms. Beyond the distinction between bipolar and depressive disorders, it is also important to note that those with MDD often experience symptoms that overlap with other disorders. Comorbidity is common among people with depression and bipolar disorders, with anxiety disorders and substance use disorders being particularly common (see Chapters 27 and 29). The presence of comorbidity has raised important questions about whether such comorbidity reflects problems in diagnostic validity, the role of common risk factors, or a causal relationship between disorders. 40

While parsing the heterogeneity reflected among the mood disorders has received considerable attention, key questions about the best ways to conceptualize this variability remain. We now review recent efforts to parse the observed heterogeneity in the mood disorders.

Parsing the Heterogeneity in Mood Disorders Bipolar and MDD: Evidence for Overlap and Distinction

Although the distinction between depressive and bipolar disorders has largely stood the test of time, research from a variety of disciplines suggests MDD and bipolar disorder may not be so easily distinguished (Smith & Craddock, 2011). Recent evidence indicates that a subset of individuals experiencing depressive episodes who are diagnosed with a depressive disorder nonetheless possess subthreshold bipolar symptoms, which may offer a valuable clue to better understanding the heterogeneity present among those affected. Manic-​like symptoms that occur at a level below the diagnostic threshold for hypomania are common among some patients who experience recurrent episodes of presumed unipolar depression (Angst et  al., 2010; Angst et  al., 2011; Merikangas et  al., 2008; Smith & Craddock, 2011; Zimmermann et al., 2009). The presence of subthreshold bipolar symptoms in patients with an MDD diagnosis has been associated with a significantly increased family history of mania, more morbid course of illness, poorer psychosocial functioning, younger age of disorder-​onset, worse quality of life, and higher rates of nicotine and cannabis dependence and alcohol use disorders (Angst et al., 2010; Angst et al., 2011; Merikangas et al., 2008; Zimmermann et al., 2009). Thus, depressive symptoms among those with subthreshold bipolar symptoms may be etiologically distinct from other experiences of depression. Evidence showing that sub-​syndromal manic symptoms occur frequently during depressive episodes in those with bipolar disorder also provides an important clue for understanding the heterogeneity observed among this group. Sub-​ syndromal manic symptoms have been found to occur in the majority (67–​ 76%) of bipolar patients experiencing depressive episodes (Goldberg et  al., 2009; Judd et  al., 2012). The manic symptoms most commonly observed include distractibility, racing thoughts, and psychomotor agitation (Goldberg et  al., 2009). Patients with a bipolar disorder whose depressive

Phenomenology and Course of Mood Disorders

 

episodes are characterized by sub-​ syndromal manic symptoms are significantly more likely than those without these symptoms to have an earlier onset age, to meet criteria for bipolar I  subtype, and to exhibit heightened suicidal behavior (Goldberg et  al., 2009; Judd et  al., 2012). Compared to DSM-​ IV-​ TR (DSM-​ IV Text Revision), DSM-​5 allows for greater opportunity to specify the experience of manic symptoms that may accompany depressive symptoms. The “with mixed features” specifier, new for DSM-​5, can be applied to episodes of mania or hypomania when depressive features are present, and to MDEs when features of mania or hypomania are present, even if they are sub-​syndromal (APA, 2013). Future research is needed to determine if the inclusion of this specifier will facilitate clinical predictions and treatment planning. While this suggests greater overlap in between recurrent MDD and bipolar disorder than is often recognized, the symptoms of MDEs among those with MDD and those with bipolar disorder do exhibit subtle, yet important, differences (Smith & Craddock, 2011). MDEs among those with bipolar disorder are characterized by higher rates of psychomotor retardation, more psychotic features, greater difficulty thinking, more early morning awakening, hypersomnia, and more morning worsening of mood compared with those observed in MDD (Forty et  al., 2008; Mitchell et al., 2011).

Parsing Heterogeneity: Defining Subtypes and Specifiers

The observed heterogeneity of symptom presentation in depression has stimulated numerous efforts to identify meaningful subtypes of depression. We review four of the DSM-​5 specifiers that can be applied to any given MDE and have been suggested as indicating meaningful subtypes of mood disorder. Specifiers of depressive episodes provide the promise of providing more specific information on the etiology and treatment response likely for a given type of depression. However, consensus on the models best suited to identify these specifiers or subtypes is considerably lacking. In their review, Harald and Gordon (2012) provided an overview of the most recognized depression subtypes and subtype models, and they reviewed the empirical evidence that can speak to distinctions among those subtypes. They identified fifteen subtype models, which could be divided into five major categories: (1) symptom-​ based subtypes; (2)  etiologically based subtypes;

(3) time of onset–​based subtypes; (4) female depression as a gender-​based subtype, and; (5) treatment-​ resistant depression as a treatment-​response-​based subtype. We focus on the symptom-​based subtypes (i.e., melancholic, atypical, anxious, and psychotic) because they have received the most attention in empirical investigations. We now turn our attention to each of these subtypes and the available research evidence that addresses their utility and validity.

Influential Subtypes: Symptom-​Based

Melancholic features. In the DSM-​ 5, the “melancholic features” specifier is used to denote depressive episodes for which: (A) the most severe period is characterized by either a complete loss of pleasure in almost all activities, or a marked lack of reactivity to usually pleasurable stimuli; and (B) three or more of the following are present: (1) a distinct quality of depressed mood characterized by profound despair; (2) morning worsening of mood; (3) early morning wakening; (4) marked psychomotor agitation or retardation; (5) significant weight loss or anorexia; and (6) excessive or inappropriate guilt. Melancholic depression is related to several similar concepts (i.e., “endogenous,” “endogenomorphic,” “autonomous,” “vital,” and “typical” depression; Leventhal & Rehm, 2005; Parker et al., 2010). Depression with melancholic features may be the most common subtype, often accounting for 50% or more of episodes in community or patient samples (Angst, Gamma, Benazzi, Ajdacic, & Rössler, 2007). Although the DSM-​5 does not delineate melancholia as a distinct depressive disorder, there is some evidence to suggest that melancholic depression may reflect a distinct form of severe depression (Leventhal & Rehm, 2005; Parker et al., 2010; Shorter, 2007). Melancholic depression has been associated with several biological changes and clinical features beyond those captured by the DSM-​5 specifier. Perhaps most notably, those with melancholic depression, as well as those with psychotic features, have been found to show nonsuppression of cortisol on the dexamethasone suppression test (i.e., an abnormal response indicative of hypercortisolism; Carroll, 1984). Melancholic depression has also been associated with reduced libido and impaired working memory and concentration, as well as sleep disturbances involving reduced rapid eye movement (REM) latency, increased REM time, and reduced deep sleep (Armitage, 2007; Parker et  al., 2010; Taylor & Fink, 2006, 2008). Those with this form of depression have also been found Strunk, Sasso

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to exhibit increased sensitivity to minor stressors, lower likelihood of personality disorder and parasuicidal behaviors, and higher likelihood of actual suicide (Coryell, 2007; Harkness & Monroe, 2006; Leventhal & Rehm, 2005). Atypical depression. The “atypical” specifier is appropriate when an MDE is characterized by:  (1)  mood reactivity (i.e., mood brightens in response to actual or potential positive events); and (2)  two of the following symptoms are present: weight gain or increased appetite, hypersomnia, leaden paralysis in arms or legs, or a long-​standing pattern of interpersonal rejection sensitivity, not limited to mood episodes (APA, 2013). Atypical depression occurs in an estimated 15–​ 50% of all depressed patients (Thase, 2007) and is particularly common among women (Halbreich & Kahn, 2007). A long history of research has been devoted to the study of atypical depression, and a recent latent class analysis is consistent with its representing a specific subtype of depression (Pae, Tharwani, Marks, Masand, & Patkar, 2009; Sullivan, Prescott, & Kendler, 2002). Despite this, atypical depression remains a somewhat controversial subtype, with the validity of the main mood-​reactivity criterion often questioned (Harald & Gordon, 2012; Pae et al., 2009). Some have suggested that neurovegetative symptoms should take diagnostic priority, and others have raised concerns regarding the overlap between atypical depression and personality disorders (Pae et al., 2009). Atypical depression has been associated with both hypercortisolemia and abnormally decreased HPA-​ axis (hypothalamic–​ pituitary–​ adrenal axis) functioning (Posternak, 2003; Thase, 2009). Differences in brain laterality, such as abnormally increased right hemispheric processing, also serve to distinguish atypical depression from melancholia and other depressive conditions (Thase, 2009). To date, only rejection sensitivity has been identified as a core psychosocial correlate of atypical depression (Harald & Gordon, 2012; Pae et al., 2009). Anxious depression. Anxious distress has been recognized as a predominant feature of MDD in both primary care and psychiatric health settings (Fava et  al., 2004; Fava et  al., 2008). In DSM-​5, the “with anxious distress” specifier was added. It is applied if at least two of the following are present during the majority of days:  feeling tense, feeling unusually restless, having difficulty concentrating due to worry, fearing that something awful may happen, or feeling that one may lose control of 42

himself/​herself (APA, 2013). Severity level within this specifier is also noted, with four levels ranging from mild to severe. Anxious depression has been associated with older age, unemployment status, lower education levels, more severe depression, and increased suicide risk (Fava et al., 2004). Psychotic depression. The “psychotic features” specifier can be applied if the patient who is experiencing an MDE also reports delusions or hallucinations (APA, 2013). Additionally, the following symptoms have been found to be more pronounced in psychotic, relative to non-​ psychotic, depression:  excessive guilt/​ worthlessness, severe psychomotor disturbance, and cognitive symptoms (i.e., deficits in attention, psychomotor speed, executive functioning, and memory; see review by Harald & Gordon, 2012). Due to the similarities in symptoms, some have proposed that psychotic depression be considered as a subtype of melancholic depression (Taylor & Fink, 2008).

Course of Mood Disorders

As with the symptomatology of these disorders, the course of the mood disorders also shows considerable variability. For bipolar I disorder, the average age of onset of the first mood episode has been estimated from the NCS-​R to be 18 years of age, with the interquartile range (i.e., the range from the 25th to the 75th percentile) extending from 12 to 21 years old. For bipolar II disorder, the mean age of onset was 20 years old in the NCS-​R, with an interquartile range from 12–​24 (Merikangas et al., 2007). According to the estimate from the World Mental Health (WMH) Survey Initiative, the median age of onset for MDD is 23 in the United States, with estimates from other high-​ income countries suggesting a somewhat later age. Across all countries included in the WMH survey, the median age of onset for any mood disorder ranged from 25–​45, with the range from the 25th to the 75th percentile extending from age 17–​65 (Kessler et al., 2007). Thus, whereas bipolar disorders tend to develop by early adulthood, the risk of a first onset of MDD appears to extend later into life. A first onset of depression later in life is not uncommon. Moreover, because of the large baby boom generation entering this period of their life and the need to consider special factors in older age (e.g., vascular depression; see Chapter 26 for a more extensive discussion), depression in older age is likely to be an increasingly prevalent clinical problem.

Phenomenology and Course of Mood Disorders

 

Course of Bipolar Disorders

Depending on its course, an initial MDE could ultimately be diagnosed as MDD or as a bipolar disorder. Among those with an initial depressive episode, roughly 12% will go on to develop bipolar II disorder, and 7% go on to develop bipolar I disorder (Fiedorowicz et al., 2011). Among those diagnosed with MDD, subthreshold hypomanic symptoms, psychosis, and familial history of bipolar disorder predict progression to a bipolar disorder. Thus, continual monitoring for possible progression to bipolar disorder is important (Fiedorowicz et al., 2011; Zimmermann et al., 2009). Epidemiological estimates suggest that approximately one in five individuals who have experienced a manic episode have no lifetime history of MDEs (Kessler, Rubinow, Holmes, Abelson, & Zhao, 1997); however, the majority of these individuals will go on to develop MDEs at some point in their lives (APA, 2013; Solomon et  al., 2003). When the onset of manic symptoms does not occur until mid-​or late-​ life, the DSM-​5 suggests considering the role of medical conditions, or substance use or withdrawal (APA, 2013). Course has often been suggested as crucial to making diagnostic distinctions between bipolar disorders and other conditions (e.g., schizoaffective disorder; Youngstrom & Perez Algorta, 2014). A  more episodic course with good functioning between episodes would typically be taken as consistent with bipolar disorder. The course of the disorder is to a large degree indicated by the duration and frequency of episodes. It is important to recognize that the duration criteria for depressive, manic, and hypomanic episodes do not have strong empirical justification. Instead, the criteria are based on committee consensus. The issue seems all the more important when one recognizes that episodes may not correctly capture all of the symptoms relevant to the course of the disorder. Research suggests that inter-​episode symptoms are common in bipolar disorder. In a 20-​year prospective study, sub-​ syndromal symptoms were present about half of the time (Judd et al., 2003). Sub-​syndromal manic symptoms during bipolar depressive episodes have also been shown to predict significantly more severe and longer lasting depressive episodes (Judd et al., 2012). Thus, while the current definitions of episodes have moved the field forward, some evidence suggests that they may not fully capture all the relevant symptoms. The dominant view of bipolar disorders has been that these disorders follow a course marked by

progressive worsening, with each episode increasing both the risk for future episodes and resistance to treatment, including treatments that previously had been successful (Scott et al., 2006; Youngstrom & Perez Algorta, 2014). Compared to depressive disorders, those with bipolar disorders tend to experience a greater number of episodes, with the depressive episodes tending to be briefer, but no less intense (Johnson, Cuellar, & Miller, 2008). Whether such a course reflects the inherent progression of the disorder or unintended long-​term effects of pharmacotherapy is less clear, as the available evidence comes largely from clinical samples in which those with a poor course might be overrepresented (Reichart & Nolen, 2004). Regardless, the course of bipolar disorders is not independent of environmental influence. The risk of an episode of these disorders is related to environmental factors such as social support, family environment, exposure to traumatic events, and other major life events. (For a more detailed discussion, see Chapter 12.) Thus, progressive worsening, even if the norm, may not be entirely unalterable. In addition, the view of bipolar disorders as characterized by progressive worsening has not gone unchallenged. Among the more provocative suggestions has been that for some, the experience of mania may be an indicator of a developmental difficulty with emotion regulation rather than the emergence of what will prove to be a lifelong condition. Consistent with such a possibility, evidence from two large surveys indicated that the rate of mania among 18–​24-​year-​olds dropped from 6% to 3% when they were followed up at ages 25–​29 (Cicero, Epler, & Sher, 2009). In the NCS-​R study, those who met criteria for bipolar I  disorder reported an average of 78 lifetime episodes, with ten years altogether spent in an episode. Among those who met criteria for bipolar II disorder, they reported an average of 64 lifetime episodes, with 12  years spent in an episode. In a recent longitudinal study of patients with bipolar I  disorder, the median duration of episodes were:  15 weeks for depression, seven weeks for mania, and three weeks for hypomania (Solomon et al., 2010). Other evidence suggests that among those with bipolar I disorder, those with the disorder spend about 32% of their time in a depressive episode, 2% in a manic episode, 7% in a hypomanic episode, and 6% either cycling or in a mixed stated (Judd et al., 2002). Thus, these results suggest that the lives of those with bipolar disorders are very strongly affected by their repeated experiences with the disorder. Strunk, Sasso

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Among those with bipolar disorder, several factors are useful in predicting the course of the disorder. Residual symptoms following the resolution of an episode have been identified as a particularly strong predictor of risk for another episode of the disorder (Judd, Schettler, Akiskal, et  al., 2008). However, more frequent episodes have also been shown to be associated with a poorer course. The most common way to identify these patients is with the rapid cycling specifier. While a number of the specifiers for MDD can be applied to bipolar disorders as well, rapid cycling is unique to bipolar disorders and merits special consideration. Rapid cycling refers to the experience of four or more distinct mood episodes in the previous 12 months, where the transition from one episode to the next involves either moving to the opposite polarity or a period of two months or more between episodes. This specifier characterizes about 16% of those who meet criteria for bipolar I  (Kupka, Luckenbaugh, Post, Leverich, & Nolen, 2003). Several characteristics have been associated with rapid cycling in the bipolar disorders, including child abuse, early age of onset, and a history of drug abuse (Kupka et al., 2005). Those with rapid cycling tend to have greater symptom severity of both depressive and manic episodes and are at higher risk of serious suicide attempts (Coryell et al., 2003).

Course of Depressive Disorders

In describing the course of depression, it is important to consider both the persistence of the disorder and the frequency of recurrence. As was true for bipolar disorder, interpreting evidence about the course of depression is complicated by the use of treatments that may affect the course of the disorder, both positively and negatively. In prospective studies conducted to examine the course of major depression, some participants were treated for their disorder, but none of the treatments were provided by the investigators. In these studies, estimates of episode duration have been about 20–​30 weeks (Klein & Allmann, 2014). One such estimate comes from the Collaborative Depression Study (Keller et  al., 2013), which involved following a large clinical sample for 30 years. In that study, after two years, 20% of patients who initially met criteria for an MDE continued to meet criteria. After five years, 12% still met criteria. After ten years, 8% still had ongoing MDEs. In prospective study of dysthymic disorder, 26% did not recover over a ten-​year follow-​up period. Thus, depressive episodes tend to resolve in about five to six months on average, 44

though a subset of those who experience depressive disorders appear to have a much more persistent course. With regard to risk of recurrence, different authors have emphasized the view of depression as either a highly recurrent disorder or a disorder that can be characterized by a single episode without subsequent recurrence (Monroe & Harkness, 2011). In patient samples, the rate of recurrence is quite high. In the Collaborative Depression Study, the rate of recurrence was 40% at five-​year follow-​up, but rose to 91% at the 30-​year follow-​up. However, in community samples, the estimated rate of recurrence is much lower. In a review comparing the recurrence rates observed, after 15  years, in specialized mental healthcare settings as compared to the general population, rates obtained in specialized settings (85%) were much higher than those observed in the general population (35%; Hardeveld, Spijker, De Graaf, Nolen, & Beekman, 2010). Overall, Monroe and Harkness have suggested that the true recurrence rate in the general population is likely to be 40–​50%. Thus, for 40% or more of those who experience an MDE, their experience with depression proves to be an acute, time-​limited condition; they do not go on to experience additional episodes. Nonetheless, many do experience additional episodes. With each new episode, the risk of additional episodes increases, and the time until the next episode is reduced. Altogether, the available evidence suggests that depression is an acute and time-​limited disorder for some and a recurrent disorder for others. In characterizing the course of depression, a number of key terms have been suggested (see Frank et  al., 1991). Thus far, we have primarily emphasized the onset of first episodes as well as the experience of later episodes (i.e., recurrence). Remission occurs when an episode has ended. When an episode ends following a treatment for depression, the term “response” is used. Once a response is sustained for an extended period, an individual can be said to have experienced recovery. Finally, an important conceptual distinction has been made between “relapse” and “recurrence.” Whereas recurrence involves the onset of a new episode, relapse is used to refer to the return of symptoms a short period after one had shown a response. When one experiences a relapse, the symptoms of the current episode are thought to have returned, rather than the symptoms of a new, independent episode having emerged. As a practical matter, the distinctions among these

Phenomenology and Course of Mood Disorders

 

states are made simply on the basis of the severity of symptoms across time. Clear and consistent operational definitions of the course of depression are important for improving our understanding of how depression manifests across the lifespan. To date, efforts to predict the course of the depressive disorders have highlighted several important factors. In predicting the persistence of depression, variables including exposure to childhood adversity, personality characteristics such as high neuroticism and low extraversion, as well as exposure to chronic stress have each been found to predict chronic (vs. non-​chronic) forms of depression. In predicting recurrence, a family history of depression, personality characteristics such as neuroticism, and exposure to major negative life events have been identified as important predictors (Klein & Allmann, 2014). While evidence suggests that stressful life events are more powerful predictors of initial, relative to subsequent episodes of MDD, it is unclear to what extent this pattern is attributable to the experience of episodes increasing one’s vulnerability to future episodes vs. the presence of multiple episodes revealing preexisting vulnerabilities (for a more detailed discussion, see Chapter 11). In addition, both residual symptoms and the number of prior episodes have been identified as predictors of risk for relapse or recurrence (Hardeveld et al., 2010; Richards, 2011). An alternative, less frequently used approach to understanding the course of depression is to classify depressive disorders based on their overall course. Using latent class growth analysis, researchers have begun to distinguish different patterns of course that capture and organize the variability observed in these disorders (see Rhebergen et al., 2012).

Future Directions

The great heterogeneity present among those who experience mood disorders, along with what has been understood about these disorders, suggests a number of directions for future research. One direction is to examine further the significance of low levels of manic symptoms among those diagnosed with depressive disorders. Second, as the National Institute of Mental Health is currently promoting the use of the Research Domain Criteria to encourage researchers to integrate behavioral with neurobiological research, such an integration might promote improvements in the classification and the prediction of course in mood disorders. Third, research should be

aimed at a better understanding of symptoms of depression and mania in their social context. For example, researchers could profitably focus on efforts to distinguish symptoms and episodes that reflect a normal reaction versus an abnormal reaction to stressful life events and circumstances (as discussed in chapters 2 and 8). Such contextual information is not well represented in current symptom-​based approaches to identifying subtypes of depression. Finally, a better understanding of the course of depression will require more information from long-​term prospective designs in which participants are followed through their first as well as any subsequent experiences of depression. Existing evidence suggests that factors that predict the initial onset of a disorder may not be the same as those that predict the subsequent course of the disorder. Approaches that seek to understand risk for mood disorders as a function of one’s personal history as well as history of mood episodes will prove useful in this regard. The mood disorders are an enormously heterogeneous class of disorders. While it is difficult to predict which approaches to understanding this heterogeneity will prove most useful, the task of working to understand this variability so that we can correspondingly advance our understanding of the etiology and treatment of these disorders is critical.

References

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Hardeveld, F., Spijker, J., De Graaf, R., Nolen, W. A., & Beekman, A. T. F. (2010). Prevalence and predictors of recurrence of major depressive disorder in the adult population. Acta Psychiatrica Scandinavica, 122, 184–​191. doi:10.1111/​ j.1600-​0447.2009.01519.x Harkness, K. L., & Monroe, S. M. (2006). Severe melancholic depression is more vulnerable than non-​melancholic depression to minor precipitating life events. Journal of Affective Disorders, 91, 257–​263. doi:10.1016/​j.jad.2005.12.009 Hunt, J., Eisenberg, D., & Kilbourne, A. (2010). Consequences of receipt of a psychiatric diagnosis for completion of college. Psychiatric Services, 61, 399–​404. Johnson, S. L., Cuellar, A. K., & Miller, C. (2008). Bipolar and unipolar depression: A comparison of clinical phenomenology, biological vulnerability, and psychosocial predictors. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of depression (2nd ed., pp. 142–​162). New York, NY: Guilford Press. Judd, L. L., Akiskal, H. S., Schettler, P. J., Coryell, W., Maser, J., Rice, J. A., … Keller, M. B. (2003). The comparative clinical phenotype and long term longitudinal episode course of bipolar I  and II:  A  clinical spectrum or distinct disorders? Journal of Affective Disorders, 73, 19–​ 32. doi:10.1016/​ S0165-​0327(02)00324-​5 Judd, L. L., Akiskal, H. S., Schettler, P. J., Endicott, J., Maser, J., Solomon, D. A., … Keller, M. B. (2002). The long-​term natural history of the weekly symptomatic status of bipolar I  disorder. Archives of General Psychiatry, 59, 530–​537. doi:10.1001/​archpsyc.59.6.530 Judd, L. L., Schettler, P. J., Akiskal, H., Coryell, W., Fawcett, J., Fiedorowicz, J. G., … Keller, M. B. (2012). Prevalence and clinical significance of subsyndromal manic symptoms, including irritability and psychomotor agitation, during bipolar major depressive episodes. Journal of Affective Disorders, 138, 440–​448. doi:10.1016/​j.jad.2011.12.046 Judd, L. L., Schettler, P. J., Akiskal, H. S., Coryell, W., Leon, A. C., Maser, J. D., & Solomon, D. A. (2008). Residual symptom recovery from major affective episodes in bipolar disorders and rapid episode relapse/​ recurrence. Archives of General Psychiatry, 65, 386–​394. doi:10.1001/​ archpsyc.65.4.386 Judd, L. L., Schettler, P. J., Solomon, D. A., Maser, J. D., Coryell, W., Endicott, J., & Akiskal, H. S. (2008). Psychosocial disability and work role function compared across the long-​ term course of bipolar I, bipolar II and unipolar major depressive disorders. Journal of Affective Disorders, 108, 49–​ 58. doi:10.1016/​j.jad.2007.06.014 Katon, W. J. (2003). Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biological Psychiatry, 54, 216–​226. doi:10.1016/​S0006-​3223(03)00273-​7 Keller, M. B., Boland, R. Leon, A., Solomon, D., Enicott, & Li, C. (2013). Clinical course and outcome of unipolar major depression. In M. B. Keller, W. H. Coryell, J. Endicott, J. D. Maser, & P. J. Schettler (Eds.), Clinical guide to depression and bipolar disorder (pp. 155–​173). Washington, DC: American Psychiatric Press. Kessler, R. C., Akiskal, H. S., Ames, M., Birnbaum, H., Greenberg, P., Jin, R., … Wang, P. S. (2006). Prevalence and effects of mood disorders on work performance in a nationally representative sample of US workers. American Journal of Psychiatry, 163, 1561–​1568. Kessler, R. C., Amminger, G. P., Aguilar-​Gaxiola, S., Alonso, J., Lee, S., & Ustun, T. B. (2007). Age of onset of mental

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disorders: A review of recent literature. Current Opinion in Psychiatry, 20, 359–​364. Kessler, R. C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K. R., … Wang, P. S. (2003). The epidemiology of major depressive disorder: Results from the National Comorbidity Survey Replication (NCS-​R). Journal of the American Medical Association, 289, 3095–​3105. doi:10.1001/​ jama.289.23.3095 Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-​ of-​onset distributions of DSM-​IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 593–​602. doi:10.1001/​archpsyc.62.6.593 Kessler, R. C., & Bromet, E. J. (2013). The epidemiology of depression across cultures. Annual Review of Public Health, 34, 119–​138. doi:10.1146/​annurev-​publhealth-​031912-​114409 Kessler, R. C., De Jonge, P., Shahly, V., Van Loo, H. M., Wang, P. S. E., & Wilcox, M. A. (2014). Epidemiology of depression. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of depression (3rd ed., pp. 7–​24). New York, NY: Guilford. Kessler, R. C., Rubinow, D. R., Holmes, C., Abelson, J. M., & Zhao, S. (1997). The epidemiology of DSM-​III-​R bipolar I  disorder in a general population survey. Psychological Medicine, 27, 1079–​1089. Klein, D. N., & Allmann, A. E. (2014). Course of depression:  Persistence and recurrence. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of depression (3rd ed., pp. 64–​ 83). New York, NY: Guilford. Kupka, R. W., Luckenbaugh, D. A., Post, R. M., Leverich, G. S., & Nolen, W. A. (2003). Rapid and non-​rapid cycling bipolar disorder: A meta-​analysis of clinical studies. Journal of Clinical Psychiatry, 64, 1483–​1494. Kupka, R. W., Luckenbaugh, D. A., Post, R. M., Suppes, T., Altshuler, L. L., Keck, P. E. Jr., … McElroy, S. L. (2005). Comparison of rapid-​cycling and non-​rapid-​cycling bipolar disorder based on prospective mood ratings in 539 outpatients. American Journal of Psychiatry, 162, 1273–​1280. doi:10.1176/​appi.ajp.162.7.1273 Lerner, D., & Henke, R. M. (2008). What does research tell us about depression, job performance, and work productivity? Journal of Occupational and Environmental Medicine, 50, 401–​410. doi:10.1097/​JOM.0b013e31816bae50 Leventhal, A. M., & Rehm, L. P. (2005). The empirical status of melancholia: Implications for psychology. Clinical Psychology Review, 25, 25–​44. doi:10.1016/​j.cpr.2004.09.001 Merikangas, K. R., Akiskal, H. S., Angst, J., Greenberg, P. E., Hirschfeld, R. M., Petukhova, M., & Kessler, R. C. (2007). Lifetime and 12-​ month prevalence of bipolar spectrum disorder in the National Comorbidity Survey Replication. Archives of General Psychiatry, 64, 543–​552. doi:10.1001/​ archpsyc.64.5.543 Merikangas, K. R., Herrell, R., Swendsen, J., Rössler, W., Ajdacic-​Gross, V., & Angst, J. (2008). Specificity of bipolar spectrum conditions in the comorbidity of mood and substance use disorders: Results from the Zurich cohort study. Archives of General Psychiatry, 65, 47–​ 52. doi:10.1001/​ archgenpsychiatry.2007.18 Mitchell, P. B., Frankland, A., Hadzi-​ Pavlovic, D., Roberts, G., Corry, J., Wright, A., … Breakspear, M. (2011). Comparison of depressive episodes in bipolar disorder and in major depressive disorder within bipolar disorder pedigrees. The British Journal of Psychiatry, 199, 303–​309. doi:10.1192/​ bjp.bp.110.088823

Moffitt, T. E., Caspi, A., Taylor, A., Kokaua, J., Milne, B. J., Polanczyk, G., & Poulton, R. (2010). How common are common mental disorders? Evidence that lifetime prevalence rates are doubled by prospective versus retrospective ascertainment. Psychological Medicine, 40, 899–​909. doi:10.1017/​ S0033291709991036 Monroe, S. M., & Harkness, K. L. (2011). Recurrence in major depression: A conceptual analysis. Psychological Review, 118, 655–​674. doi:10.1037/​a0025190 Murray, C. J., Vos, T., Lozano, R., Naghavi, M., Flaxman, A. D., Michaud, C., … Aboyans, V. (2013). Disability-​ adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–​2010: A systematic analysis for the Global Burden of Disease Study 2010. The Lancet, 380, 2197–​2223. doi:10.1016/​S0140-​6736(12)61689-​4 Pae, P. C.-​U., Tharwani, H., Marks, D. M., Masand, P. S., & Patkar, A. A. (2009). Atypical depression. CNS Drugs, 23, 1023–​1037. doi:10.2165/​11310990-​000000000-​00000 Parker, G., Fink, M., Shorter, E., Taylor, M. A., Akiskal, H., Berrios, G., … Swartz, C. (2010). Issues for DSM-​ 5:  Whither melancholia? The case for its classification as a distinct mood disorder. American Journal of Psychiatry, 167, 745–​747. doi:10.1176/​appi.ajp.2010.09101525 Posternak, M. A. (2003). Biological markers of atypical depression. Harvard Review of Psychiatry, 11, 1–​7. doi:10.1080/​ 10673220303941 Reichart, C. G., & Nolen, W. A. (2004). Earlier onset of bipolar disorder in children by antidepressants or stimulants? An hypothesis. Journal of Affective Disorders, 78, 81–​84. doi:10.1016/​S0165-​0327(02)00180-​5 Rhebergen, D., Lamers, F., Spijker, J., De Graaf, R., Beekman, A. T.  F., & Penninx, B. W.  J. H. (2012). Course trajectories of unipolar depressive disorders identified by latent class growth analysis. Psychological Medicine, 42, 1383–​1396. doi:10.1017/​S0033291711002509 Richards, D. (2011). Prevalence and clinical course of depression:  A  review. Clinical Psychology Review, 31, 1117–​1125. doi:10.1016/​j.cpr.2011.07.004 Rohde, P., Lewinsohn, P. M., Klein, D. N., Seeley, J. R., & Gau, J. M. (2013). Key characteristics of major depressive disorder occurring in childhood, adolescence, emerging adulthood, and adulthood. Clinical Psychological Science, 1, 41–​53. doi:10.1177/​2167702612457599 Scott, J. A. N., Paykel, E., Morriss, R., Bentall, R., Kinderman, P., Johnson, T., … Hayhurst, H. (2006). Cognitive–​behavioural therapy for severe and recurrent bipolar disorders. The British Journal of Psychiatry, 188, 313–​320. doi:10.1192/​bjp.188.4.313 Shorter, E. (2007). The doctrine of the two depressions in historical perspective. Acta Psychiatrica Scandinavica, 115, 5–​13. doi:10.1111/​j.1600-​0447.2007.00957.x Smith, D. J., & Craddock, N. (2011). Unipolar and bipolar depression:  Different or the same? The British Journal of Psychiatry, 199, 272–​274. doi:10.1192/​bjp.bp.111.092726 Solomon, D. A., Leon, A. C., Coryell, W. H., Endicott, J., Li, C., Fiedorowicz, J. G., … Keller, M. B. (2010). Longitudinal course of bipolar I  disorder:  Duration of mood episodes. Archives of General Psychiatry, 67, 339–​347. doi:10.1001/​ archgenpsychiatry.2010.15 Solomon, D. A., Leon, A. C., Endicott, J., Coryell, W. H., Mueller, T. I., Posternak, M. A., & Keller, M. B. (2003). Unipolar mania over the course of a 20-​year follow-​up study. American Journal of Psychiatry, 160, 2049–​2051. doi:10.1176/​ appi.ajp.160.11.2049

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CH A PT E R

5

Sex, Sexual Orientation, and Depression

Mark L. Hatzenbuehler and Katie A. McLaughlin

Abstract Females and lesbian, gay, and bisexual (LGB) populations are twice as likely to develop depression as males and heterosexuals, respectively. This chapter reviews the descriptive epidemiology of sex and sexual orientation differences in depression, and discusses explanations for these group differences, including neurobiological (e.g., differences in limbic system reactivity), individual (e.g., cognitive and affective processes), and interpersonal processes (e.g., victimization experiences), as well as structural influences (e.g., state-​level policies that differentially target gays and lesbians for social exclusion). The chapter summarizes common vulnerabilities to depression in females and sexual minorities and offers several directions for future research, including the need for multimethod, multilevel approaches that can increase our understanding of the emergence and persistence of differences in depression based on sex and sexual orientation. Key Words:  sex differences, sexual orientation, group differences, cognitive/​affective processes, neurobiological processes, interpersonal processes, structural influences

According to the World Health Organization (2008), depression is the leading cause of disability among any disease or illness. Depression is not uniformly distributed in the general population, however. Females (Nolen-​Hoeksema & Hilt, 2009) and sexual minorities1 (Meyer, 2003) are twice as likely to suffer from depression as males and heterosexuals, respectively. In this chapter, we describe the epidemiology of differences in depression based on sex and sexual orientation, with a focus on differences in lifetime prevalence, age of onset, and persistence/​ chronicity. We also review explanations for these differences. We take a “cells-​to-​society” approach, describing factors that range from neurobiological influences (e.g., hormones, differences in limbic system reactivity) to structural influences (e.g., state-​level policies that differentially target gays and lesbians for social exclusion). We conclude by summarizing common vulnerabilities to depression in females and sexual minorities and offer directions for future research.

Epidemiology of Major Depression by Sex and Sexual Orientation

A number of epidemiological studies of depression have been conducted in large, representative samples of the United States and other countries, including the National Comorbidity Survey (NCS) and Replication (NCS-​ R), the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), and the World Mental Health (WMH) Surveys. In this section, we review evidence concerning differences in depression based on sex and sexual orientation in three domains:  (1)  the lifetime prevalence of depression; (2) the age of onset/​developmental trends of depression; (3)  and the persistence/​ chronicity of depression.

Lifetime Prevalence

One of the most consistent findings in the psychiatric epidemiological literature is the 2:1 sex difference in the lifetime prevalence of depression; 49

 

women are diagnosed with depression at twice the rate of men in adulthood (Kessler et  al., 2003). Although the lifetime prevalence of depression varies cross-​culturally, women exhibit higher rates of depression compared to men across cultures as well as across sociodemographic groups within cultures (Weissman et al., 1996). Epidemiological studies in the United States suggest that major depression will affect one out of four women and one out of eight men in their lifetimes. For example, the NCS-​R reported a lifetime prevalence of major depressive disorder as 21.3% for women and 12.7% for men (Kessler et al., 2003). The NESARC reported slightly lower, but similar lifetime prevalence rates:  17.1% for women and 9.0% for men (Hasin, Goodwin, Stinson, & Grant, 2005). Although the 2:1 sex difference in depression has remained constant over many years, the lifetime prevalence of major depression has increased in both men and women in more recent cohorts (Kessler et al., 2003). Recent epidemiological research has also indicated that sexual minorities are at increased risk for psychiatric morbidity across a wide spectrum of outcomes, including major depression (for a meta-​ analysis, see King et al., 2008). These disparities in depression appear to be most pronounced among gay men, who have been found across numerous studies to have a higher lifetime prevalence of DSM-​diagnosed major depression (Cochran & Mays, 2000; Cochran, Mays, & Sullivan, 2003; Gilman, Cochran, Mays, Ostrow, & Kessler, 2001) than heterosexual men. Although some studies have shown higher rates of depression in sexual minority women compared to heterosexual women (e.g., Gilman et al., 2001), others have shown no statistically significant group differences (e.g., Cochran et al., 2003), which may in part be due to low statistical power given the small sample sizes of sexual minorities in most population-​based studies.

Age of Onset/​Developmental Trends

The prevalence of major depression varies markedly across the life-​ course. A  meta-​ analysis of depression in youth reported that the prevalence of depression is only 2.8% in children under the age of 13 years and increases to 5.6% in adolescents aged 13–​18  years (Costello, Erkanli, & Angold, 2006). By adulthood, the lifetime prevalence of depression is 16.2% with 6.6% of adults experiencing a major depressive episode in a given 1-​year period (Kessler et al., 2003). The incidence of depression remains relatively low until about 11  years of age 50

and rises most dramatically between ages 15 and 18 years (Hankin et al., 1998; Kessler et al., 2003). Although the prevalence of childhood depression is similar for boys and girls, females are more likely than males to develop depression beginning at age 13 years (Hankin et al., 1998; Nolen-​Hoeksema & Girgus, 1994). The risk for depression then remains elevated among females relative to males throughout adolescence and adulthood (Kessler et  al., 2003; Kim-​Cohen et  al., 2003). By age 18  years, the 2:1 sex difference is apparent; it remains stable throughout adulthood (Eaton et al., 1997). (For a further discussion of the emergence of sex differences in depression during adolescence, see Hilt & Nolen-​Hoeksema, 2009.) In recent studies using nationally representative or community-​based samples, sexual minority adolescents have been found to be at elevated risk for depressive symptoms and major depression compared to their heterosexual peers (e.g., Hatzenbuehler, McLaughlin, & Nolen-​Hoeksema, 2008; Russell & Joyner, 2001). Depressive symptoms may also emerge earlier in the life-​ course among sexual minorities relative to heterosexuals. For instance, two studies from general population samples have shown that sexual minority men had an earlier age of onset of major depression than heterosexual men (Cochran & Mays, 2000; Gilman et al., 2001).

Persistence/​Chronicity

Sex differences in major depression episodes could reflect the fact that women are more likely to experience first onsets, longer depressive episodes, a greater risk of recurrence of depression, or all of these. Data from several studies of adults (e.g., Kessler, McGonagle, Swartz, Blazer, & Nelson, 1993) and children or adolescents (e.g., Hankin et al., 1998), however, indicate that the sex difference in depression is explained by a greater proportion of first onsets in girls and women compared to boys and men, and not to longer durations or greater recurrence. As previously mentioned, sexual minorities are already at higher risk for depression than their heterosexual peers during adolescence. In turn, adolescents who have experienced a major depressive episode are at a pronounced risk for recurrent problems with depression and for relapse in adulthood (e.g., Lewinsohn, Rhode, Klein, & Seeley, 1999). Using data from the National Health and Nutrition Examination Survey-​III (NHANES III), Cochran and Mays (2000) found that sexual minority men

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experienced greater recurrent depression than heterosexual men. Moreover, data from the NCS indicated that sexual minorities had numerically elevated odds (ORs  =  1.6 for men and 3.1 for women) for persistence of major depression relative to heterosexuals, although the differences did not reach statistical significance. Thus, the extent to which sexual minorities are at elevated risk for disorder severity, including persistence, warrants greater attention in future research.

Explanations of Group Differences in Depression

Many different explanations of these group differences in depression have been proposed. In this section, we adopt a multilevel approach to examining potential explanations for these differences, reviewing evidence for risk factors for depression, including biological (e.g., hormones, differences in limbic system reactivity), cognitive/​affective (e.g., rumination), interpersonal (e.g., rejection sensitivity, victimization/​ abuse), and structural (e.g., social conditions and institutional policies) levels. Although a comprehensive review of each of these potential explanatory factors is beyond the scope of this chapter, we refer the reader to more comprehensive reviews of the literature on depression in women and men (Hyde, Mezulis, & Abramson, 2008; Nolen-​ Hoeksema & Hilt, 2009) and on mental health in sexual minorities and heterosexuals (Hatzenbuehler, 2009; Meyer, 2003) for more thorough discussions of different explanations.

Neurobiological Explanations

A variety of neurobiological factors might underlie sex differences in the emergence of depression during adolescence. Early pubertal onset has been associated with an elevated risk for adolescent depression among females in multiple studies (Graber et  al., 2007; Graber, Nichols, & Brooks-​ Gunn, 2010). Determining whether the biological factors that lead to early pubertal onset play a role in explaining the sex difference in depression incidence during adolescence represents an important goal for future research. Moreover, although the consistently documented association between early pubertal timing and depression risk in females might reflect underlying neurobiological vulnerability, the pathways linking pubertal onset and depression also involve a variety of psychosocial factors. For example, poor-​quality family, peer, and romantic relationships are both a predictor and consequence of early pubertal onset. Stressors in the family

environment, such as low-​quality family interactions or father absence, are thought to contribute to early pubertal onset; conversely, early maturing girls have lower-​ quality relationships with family and peers and are at a higher risk for physical and verbal abuse from romantic partners (Graber et al., 2010). The combination of early pubertal timing and subsequent stressful life events, particularly peer stressors, is associated with an elevated risk for depression (Conley & Rudolph, 2009; Ge, Conger, & Elder, 2001). The relationship between early puberty and depression in females may also be mediated by self-​ esteem and body dissatisfaction (Negriff & Susman, 2011; Stice, Presnell, & Bearman, 2001). Adolescence is characterized by marked increases in physiological reactivity to stress, both in the hypothalamic–​ pituitary–​ adrenal (HPA) axis and in the autonomic nervous system (Stroud et  al., 2009). This increase in stress reactivity occurs to a greater degree for female adolescents as compared to males (Stroud, Papandonatos, Williamson, & Dahl, 2004). Stressful life events, particularly chronic stressors occurring in interpersonal domains, can lead to dysregulation in physiological stress response systems (Gunnar & Quevedo, 2007). Evidence suggests that female adolescents experience higher levels of interpersonal stressors than males, particularly in peer and family domains (Rudolph & Hammen, 1999). As these systems become more attuned to the social environment in adolescence, interpersonal stressors might be particularly likely to alter stress response system functioning in females, elevating the risk for major depression. Dysregulated cortisol regulation has been observed in depressed youths, with the most commonly reported pattern involving elevated evening cortisol levels (Goodyer, Park, & Herbert, 2001; Lopez-​Duran, Kovacs, & George, 2009). The degree to which this dysregulation is a precursor to or consequence of depression itself remains unclear, although in a prospective study elevated cortisol-​to-​dehydroepiandrosterone (DHEA) ratio (a measure of anabolic balance) predicted major depression onset in a high-​risk adolescent sample (Goodyer, Herbert, & Tamplin, 2003). By adulthood, few neurobiological factors have been identified that might contribute to sex differences in the risk for major depression. Women exhibit greater limbic system reactivity to stress as compared to men, who exhibit greater activation in regions of the prefrontal cortex following stressors (Wang et  al., 2007). Sex differences in serotonin synthesis in the brain have also been documented (Nishizawa et al., 1997), but their role in underlying Hatzenbuehler, McLaughlin

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differences in depression is unknown. Finally, it has been suggested that genetic vulnerabilities to depression operate differently for males and females, such that certain genetic polymorphisms are associated with depression among females but not among males (Eley et al., 2004), although evidence for such differences is inconsistent across studies. Taken together, evidence for neurobiological factors underlying sex differences in depression is stronger during adolescence than adulthood. Just as biological explanations of sex differences have focused on putatively immutable characteristics between men and women, so too have biological explanations of sexual orientation addressed differences between heterosexual and sexual minority populations (for a history of these arguments, see Fausto-​Sterling, 2000). Researchers have used multiple methods to pursue these putative biological differences, such as electroencephalography (EEG) and assessments of circulating androgen levels (for a comprehensive review, see Mustanski, Chivers, & Bailey, 1999). For instance, several studies have reported that gay men exhibit female-​ typical patterns in EEGs during spatial and verbal tasks (e.g., Wegesin 1998). Similarly, some studies of finger length ratio (e.g., Williams et al., 2000) have reported that the right hand 2D(index finger):4D(ring finger) ratio for lesbians is not significantly different from that of heterosexual men (but is significantly smaller than heterosexual women). However, these results have not always been consistent (Mustanski et al., 1999). Furthermore, in cases in which group differences have been found, researchers have rarely considered how and whether these differences may contribute to sexual orientation disparities in depression. There are some notable exceptions, including recent studies exploring sexual orientation differences in HPA axis reactivity (e.g., Juster, Smith, Ouellet, Sindi, & Lupien, 2013; Hatzenbuehler & McLaughlin, 2014), which represents an important area for future study on neurobiological risk factors that may explain group differences in depression based on sexual orientation.

Cognitive and Affective Explanations Rumination

Rumination is defined as the tendency to think passively and brood about negative thoughts and feelings in a repetitive manner (Nolen-​Hoeksema, 1991). Individual differences in people’s tendency to ruminate are associated with a risk for major depression, such that higher levels of rumination predict the onset, persistence, and 52

severity of major depressive episodes (for a review, see Nolen-​ Hoeksema, Wisco, & Lybomirsky, 2008). Consistent evidence indicates that beginning in adolescence females engage in rumination significantly more than males (Hankin, 2008), and this sex difference in rumination has been shown to account statistically for the sex difference in depression in multiple studies (e.g., Nolen-​ Hoeksema, Larson, & Grayson, 1999). There are many possible reasons for why females have a greater tendency to ruminate than males. One is that girls are socialized to use emotion-​focused coping strategies, whereas boys are socialized to cope in a more direct manner (e.g., problem solving). There is some evidence for this in observational work with child–​ parent interactions (e.g., Adams, Kuebli, Boyle, & Fivush, 1995). Another possibility is that females are more likely to experience environmental stressors that promote rumination. Indeed, conceptualizations of the sex difference in depression have often noted that women are more likely than men to experience the kinds of uncontrollable interpersonal stressors that might be especially likely to lead to rumination (e.g., sexual abuse, harassment at work) (Nolen-​Hoeksema, 2001; Nolen-​ Hoeksema et al., 1999). It is also possible that sex differences in rumination are not the result of environmental experiences, but rather reflect innate differences in processing style or a propensity for self-​reflection. Research has also indicated that rumination is an important mechanism explaining sexual orientation disparities in depressive symptoms. In a longitudinal study of adolescents, Hatzenbuehler, McLaughlin, and Nolen-​Hoeksema (2008) found that sexual minority youth were more likely than their heterosexual peers to ruminate, and group differences in rumination accounted for the higher levels of depressive symptoms among sexual minority youth. Furthermore, a daily diary study found that sexual minority young adults were more likely to ruminate on days in which stigma-​related stressors (e.g., perceived discrimination) occurred; in turn, rumination statistically accounted for the relationship between these stigma-​related stressors and psychological distress (Hatzenbuehler, Nolen-​ Hoeksema, & Dovidio, 2009).

Negative Attributional Style and Hopelessness

Negative attribution style—​ defined as the tendency to attribute negative events to stable

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and global causes, to assume that negative events invariably lead to negative consequences, and to assume that negative events reflect internal deficits or failings (see Chapter 13)—​is a cognitive factor that may contribute to the sex differences in depression (Hyde et al., 2008). Negative attributional style is strongly associated with depressive symptoms and interacts with stressful life events to predict increases in depression over time (e.g., Alloy et al., 2000). There is some evidence that adolescent girls are more likely to have a negative attributional style than boys (Hankin & Abramson, 2002). Furthermore, the relationship between a negative attributional style and depressive symptoms is stronger for adolescent girls than for boys (Gladstone, Kaslow, Seeley, & Lewinsohn, 1997), which may contribute to sex differences in depression. The degree to which cognitive vulnerability predicts depressive symptoms following interpersonal stressors, specifically peer rejection experiences, has also been found to be stronger among adolescent females as compared to males (Prinstein & Aikins, 2004). The degree to which sex differences in the associations of negative attributional style and depression persist into adulthood is unknown. In addition to rumination and negative attributional style, Hyde and colleagues (2008) suggested that women’s greater tendency to attend to their bodies and to have lower body esteem as compared to men may represent an important cognitive factor in risk for female depression. Sex differences in body image and satisfaction that emerge during adolescence may therefore play a role in explaining sex differences in depression. Although there is no research on negative attribution style as it relates to sexual orientation differences in depression, there is some research on hopelessness, a related construct. Hopelessness is defined as the belief that negative events will occur (or, conversely, that desired events will not occur) and that there is nothing the individual can do to change the situation (Abramson, Metalsky, & Alloy, 1989). Hopelessness is a potent risk factor for the onset of major depression that may contribute specifically to sexual orientation differences in depression. Studies have indicated that sexual minority adolescents are more likely to feel hopeless than their heterosexual peers (e.g., Russell & Joyner, 2001); group differences in hopelessness predicted higher rates of depressive symptoms among sexual minority adolescents relative to their heterosexual peers (Safren & Heimberg, 1999).

Interpersonal Factors

Interpersonal theories of depression highlight a variety of social behaviors that contribute to and maintain depressive symptoms, including excessive reassurance seeking, negative feedback seeking, and basing your self-​worth on the opinions of others (see Chapter  51; Joiner & Coyne, 1999). In this section, we review several interpersonal factors that may contribute to differences in depression based on sex and sexual orientation. We focus in particular on those factors that are common across women and sexual minorities, including rejection sensitivity and interpersonal stressors. This necessarily selective approach will not address factors that have not yet been adequately studied with one or both groups (e.g., interpersonal orientation; Feingold, 1994).

Interpersonal Stressors

Exposure to stress is common in the lives of depressed people (Hammen, 2005). Although there is a great debate about the operationalization and measurement of stress, even studies that focused only on “independent” or fateful events that could not have been due to the individual’s depression or other characteristics have shown a link between stressful life events and an elevated risk of experiencing depression (see Hammen, 2005; Monroe, 2008). Both the differences in depression between women and men, and between sexual minorities and heterosexuals, have been attributed in part to differences in exposure to stressors. Below, we discuss interpersonal stressors that may contribute to sex and sexual orientation differences in depression, with a particular focus on victimization and violence. Females are more likely to be exposed to multiple forms of interpersonal violence than males, including rape, sexual assault, and stalking (Kessler, Sonnega, Bromet, Hughes, & Nelson, 1995; Tolin & Foa, 2006). Having been the victim of rape more than doubles your chances of developing depression (Burnam et al., 1988), and it is estimated that 10–​15% of women have been victims of rape during their lifetime (Kessler et al., 1995). In addition to rape, other types of interpersonal victimization, such as intimate partner violence and sexual abuse, also confer a risk for developing depression (Weiss, Longhurst, &Mazure, 1999). Although boys and men are also victims of childhood maltreatment, females are more likely to experience sexual abuse than males (Finkelhor, Hotaling, Lewis, & Smith, 1990), and this may partially explain the higher rates of depression in women. For example, one review Hatzenbuehler, McLaughlin

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estimated that about one-​third of the sex difference in adult depression could be attributed to the higher rates of childhood sexual abuse in girls (Cutler & Nolen-​Hoeksema, 1991). Other work suggests that exposure to other forms of victimization, such as intimate partner violence, might also contribute to sex differences in depression (Campbell, 2002). Sexual minorities are also disproportionately exposed to victimization and violence relative to heterosexuals. Balsam, Rothblum, and Beauchaine (2005) found that LGB individuals experienced more forms of victimization over the life course than their heterosexual siblings. In particular, LGB participants reported more childhood psychological and physical abuse by parents and caretakers, more childhood sexual abuse, more partner psychological and physical abuse in adulthood, and more sexual assault experiences in adulthood than their heterosexual siblings. Previous studies also suggest that disproportionate exposure to physical and sexual abuse is associated with elevations in depressive symptoms among sexual minorities as compared to heterosexuals (McLaughlin, Hatzenbuehler, Xuan, & Conron, 2012). LGB adolescents are also more likely than their heterosexual peers to be victims of peer violence (e.g., Russell, Seif, & Truong, 2001). Studies with representative samples of youth have demonstrated that these group differences in peer victimization partially account for the association between sexual orientation and risk of suicide (Russell & Joyner, 2001). It is important that future researchers determine whether peer victimization can account for disparities in depressive symptoms based on sexual orientation.

Rejection Sensitivity

Rejection sensitivity is defined as the tendency to “anxiously expect, readily perceive, and overreact to rejection” (Downey, Freitas, Michaelis, & Khouri, 1998, p.  545), and is associated with depression, particularly in the context of interpersonal stressors and relationship loss. For example, rejection sensitivity is associated prospectively with increases in depression among women who experienced a partner-​initiated break-​up, but not among those who initiated a break-​up or experienced noninterpersonal stressors (Ayduk, Downey, & Kim, 2001). In a daily diary study, the romantic partners of women high in rejection sensitivity were more likely to experience relationship dissatisfaction when conflict arose; these rejection-​ sensitive women also considered their partners to be more withdrawn 54

(Downey et al., 1998). This finding was not true of romantic partners of men high on rejection sensitivity, which suggests that the fulfillment of women’s rejection expectations may have a greater impact on their interpersonal relationships than is the case for men. This study did not examine depression, but points to a potential mechanism that may contribute to higher rates of depression in women. This research on rejection sensitivity in interpersonal contexts has been extended to examine sensitivity to status-​based rejection. For example, expectations of rejection based on race impairs the functioning of African-​American students across a variety of domains, including affiliation and trust within institutional settings (Mendoza-​ Denton, Downey, Purdie, Davis, & Pietrzak, 2002). At least one study has linked high levels of rejection sensitivity to depressive symptoms among sexual minority men (Hatzenbuehler, Nolen-​Hoeksema, & Erickson, 2008).

Structural Explanations Social Conditions and Institutional Policies/​Practices

There is a body of literature that considers gendered social structure and interactions as factors that can explain sex differences in mental disorders, including depression (e.g., Lennon, 1995; Simon, 1995). One focus of this line of work has been on chronic strain related to gender roles. Evidence from multiple epidemiological studies indicates that the benefits of marriage are greater for males than for females, and that females experience greater stress related to marriage than males (Bebbington, 1998). Women report more chronic strain related to the family, finances, parenting, and workload inequalities within marriages than men (Nolen-​Hoeksema et  al., 1999). These chronic strains partially explained the sex differences in depression in multiple studies (e.g., Nolen-​ Hoeksema et al., 1999). Similarly, Rosenfield (1989) documented that sex differences in depressive symptoms were no longer observed when familial demands between men and women were equal (i.e., sex differences in depressive symptoms are reduced to nonsignificance), indicating that demands are a mediator of the relationship between sex and depressive symptoms. Women are also more likely to be single parents than men, and the prevalence of depression has been found to be particularly high among unmarried women raising young children and in the postpartum period for women without a cohabiting partner (Brown & Moran,

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1997; Hobfoll, Ritter, Lavin, Hulsizer, & Cameron, 1995). In addition to chronic strains related to gender roles, research has also focused on ways in which women’s lower social status may contribute to sex differences in depression. For instance, a cross-​national comparison of psychiatric disorders in 15 countries from the WMH surveys showed a significant narrowing of sex differences in major depression resulting from changes in gender ideology, including women’s labor force experience, education levels, median age of marriage, and contraception use (Seedat et al., 2009). Within the United States, state-​level policies related to reproductive rights have also been linked to the prevalence of major depression among women; specifically, the odds of depression are lower among women living in states with legal and policy protections of women’s reproductive health rights than among women in states without these protections (McLaughlin, Xuan, Subramanian, & Koenen, 2011). This association could reflect either the fact that women in these states are denied access to services they need or that these policies reflect a climate that is hostile to women’s rights. Social/​ structural factors are also related to depression among sexual minorities. Several studies have documented that social policies that differentially target gays and lesbians for social exclusion are strongly related to mental health outcomes in LGB populations (for a review, see Hatzenbuehler, 2010). In one study, Hatzenbuehler, Keyes, and Hasin (2009) coded states for the presence or absence of policies that confer protection to gays and lesbians—​ namely, hate crime statutes and employment nondiscrimination policies that include sexual orientation as a protected class. This policy information was linked to individual-​level data on mental health and sexual orientation from a nationally representative survey of U.S. adults. The prevalence of psychiatric disorders was significantly higher among LGB adults living in states with policies that did not confer protection to gays and lesbians, compared to LGB individuals living in states with protective policies. For instance, sexual orientation disparities in dysthymia were not evident in states with protective policies; however, LGB adults who lived in states with no protective policies were nearly 2.5 times more likely to have dysthymia than were heterosexuals in those same states. In a follow-​up study, Hatzenbuehler, McLaughlin, Keyes, and Hasin (2010) used longitudinal data to evaluate the impact of social policies on LGB mental health. During 2004, 16 states passed constitutional

amendments banning same-​ sex marriage. These events occurred between two waves of data collection in a nationally representative, prospective study of U.S. adults. Respondents were first interviewed in 2001 and then the same respondents were reinterviewed in 2005 following the passage of the same-​sex marriage bans. This provided a natural experiment that provided researchers with the opportunity to examine changes in the prevalence of psychiatric disorders among LGB respondents who were assessed before and after the same-​sex marriage bans were passed. Of relevance to the current chapter, LGB adults who lived in states that passed same-​sex marriage bans experienced a 35% increase in major depression between the two waves (Hatzenbuehler et al., 2010). In contrast, LGB respondents in states without these bans experienced a 14% decrease in major depression during the study period. Furthermore, rates of depression among heterosexuals were largely unchanged during this period, providing evidence for the specificity of these policies to LGB populations.

Future Directions and Conclusions

Although depression is a debilitating disorder, its consequences are disproportionately experienced by certain segments of the population, including women and sexual minorities. Beginning in mid-​ adolescence and continuing throughout the rest of the life-​course, females are more likely than males to develop major depression, with elevated risk observed specifically for first onsets of depression but not for episode persistence. Similarly, members of sexual minority groups are at an increased risk for depression compared to heterosexuals, and this disparity begins in adolescence. We highlighted correlates and determinants of group differences in depression related to sex and sexual orientation. In particular, research has identified numerous biological, intrapersonal (i.e., cognitive/​ affective), interpersonal, and social/​ structural factors that may contribute to sex and sexual orientation disparities in the lifetime prevalence of major depression. Although this literature has provided significant insights, there is a dearth of research that examines the ways in which these multilevel factors operate together to increase the vulnerability to depression among women and sexual minorities. This lack of multilevel research may be due to the fact that depression researchers tend to focus on risk factors in isolation from their respective disciplines. Psychologists, for instance, tend to focus on neurobiological and intrapersonal factors, whereas medical sociologists and social Hatzenbuehler, McLaughlin

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epidemiologists typically focus on social-​structural factors. Progress in understanding the determinants of disparities in depression based on sex and sexual orientation will be advanced by developing and testing theoretical models that span the entire range of neurobiological, cognitive/​affective, interpersonal, and social/​structural factors that contribute to these disparities. To address these gaps in the literature, we believe that the field would benefit from increased interdisciplinary research that applies a cells-​to-​society approach to investigating sex and sexual orientation differences in major depression. It is likely that social-​structural factors give rise to intrapersonal and interpersonal factors that in turn contribute to depression. For instance, intrapersonal factors, such as rumination, may mediate the relationship between social-​ structural factors (e.g., repressive policies) and depression. Furthermore, it is possible that risk factors across levels interact synergistically to create elevations in depression. For example, gays and lesbians with greater rejection sensitivity are likely to be at a heightened risk for depression if they reside in areas with more negative social policies surrounding homosexuality. Examining these cross-​level interactions raises new opportunities for interdisciplinary research on disparities in major depression. Such research will not only contribute to a more comprehensive understanding of the etiology of sex and sexual orientation differences in depression, but will also lead to the development of more effective preventive interventions that target the multilevel influences of depression.

Acknowledgments

This chapter was supposed to be written by Dr.  Susan Nolen-​ Hoeksema, who invited us to write the chapter with her. We are deeply saddened that Susan passed away before we could begin working on the chapter. Although Susan was not able to take part in writing the chapter, her seminal ideas and scholarship on these topics inspired much of the content that is reviewed. In addition to being an outstanding scholar and leader in the field, Susan was an inspiring, generous, and insightful mentor and collaborator. We miss her terribly.

Note

1. We will use the commonly accepted term “sexual minority” to refer to lesbian, gay, and bisexual (LGB) individuals in recognition of the various ways that sexual orientation has been operationalized in the existing literature (e.g., sexual identity, sexual behavior, sexual attraction). The term “LGB”

56

is used in those instances in which specific studies have used measures of self-​identification.

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adults with mental disorder:  Developmental follow-​ back of a prospective-​ longitudinal cohort. Archives of General Psychiatry, 60(7), 709–​717. King, M., Semlyen, J., Tai, S. S., Killaspy, H., Osborn, D., Popelyuk, D., … Nazareth, I. A. (2008). Systematic review of mental disorder, suicide, and deliberate self harm in lesbian, gay and bisexual people. BMC Psychiatry, 8(1), 70. Lennon, M. C. (1995). Work conditions as explanations for the relations between socioeconomic status, gender, and psychological disorders. Epidemiologic Reviews, 17, 120–​127. Lewinsohn, P. M., Rhode. P., Klein, D. N., & Seeley, J. R. (1999). Natural course of adolescent major depressive disorder: I. Continuity into young adulthood. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 56–​63. Lopez-​ Duran, N., Kovacs, M., & George, C. J. (2009). Hypothalamic-​ pituitary-​ adrenal axis dysfunction in depressed children and adolescents:  A  meta-​ analysis. Psychoneuroendocrinology, 34, 1272–​1283. McLaughlin, K. A., Hatzenbuehler, M. L., Xuan, Z., & Conron, K. J. (2012). Disproportionate exposure to early-​life adversity and sexual orientation disparities in psychiatric morbidity. Child Abuse and Neglect, 36, 645–​655. McLaughlin, K. A., Xuan, Z., Subramanian, S. V., & Koenen, K. C. (2011). State-​level women’s status and psychiatric disorders among U.S. women. Social Psychiatry and Psychiatric Epidemiology, 46, 1161–​1171. Mendoza-​ Denton, R., Downey, G., Purdie, V., Davis, A., & Pietrzak, J. (2002). Sensitivity to status-​ based rejection:  Implications for African-​ American students’ college experience. Journal of Personality and Social Psychology, 83, 896–​918. 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. Monroe, S. M. (2008). Modern approaches to conceptualizing and measuring human life stress. Annual Review of Clinical Psychology, 4, 33–​52. Mustanski, B. S., Chivers, M. L., & Bailey, J. M. (1999). A critical review of recent biological research on human sexual orientation. Annual Review of Sex Research, 13, 89–​104. Negriff, S., & Susman, E. J. (2011). Pubertal timing, depression, and externalizing problems: A framework, review, and examination of gender differences. Journal of Research on Adolescence, 21, 717–​746. Nishizawa, S., Benkelfat, C., Young, S. N., Leyton, M., Mzengeza, S., de Montigny, C., Blier, P., & Dikisic, M. (1997). Differences between males and females in rates of serotonin synthesis in human brain. Proceedings of the National Academy of Sciences, 94, 5308–​5313. Nolen-​Hoeksema, S. (1991). Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology, 100, 569–​582. Nolen-​Hoeksema, S. (2001). Gender differences in depression. Current Directions in Psychological Science, 10(5), 173–​176. Nolen-​Hoeksema, S., & Girgus, J. S. (1994). The emergence of gender differences in depression during adolescence. Psychological Bulletin, 115(3), 424–​443. Nolen-​Hoeksema, S., & Hilt, L. M. (2009). Gender differences in depression. In C. Hammen & I. Gotlib (Eds.), Handbook of depression (pp. 386–​404). New York, NY: Guilford.

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CH A PT E R

6

Suicide

Matthew S. Michaels, Carol Chu, and Thomas E. Joiner, Jr.

Abstract Suicide represents a growing public issue that involves great emotional cost and loss of life. This chapter provides an academic overview of the topic of suicide. Methods of classification and definitional issues are discussed. Epidemiological trends in rates of suicide and suicide attempts are well established and are reported. The phenomenology of suicidal behavior represents an under-studied area and there is discussion of the few studies that exist and possibilities for future investigations in this area. Next, the etiology of suicide in the context of current suicide theory, including the interpersonal theory of suicide, is discussed. This essay concludes with a practical discussion of clinical risk assessment for suicidal behavior and future recommendations for research. Key Words:  suicide, suicidal behavior, suicide attempts, suicide theory, interpersonal theory of suicide

Introducing Suicide

On a cold November morning in 1981, the body of actress Natalie Wood was discovered in the seawater near Santa Catalina Island, California. She had previously attempted suicide by overdosing in 1966 and had repeatedly practiced for a drowning scene on the set of Splendor in the Grass, but her husband reported that she was not suicidal (Finstad, 2001). The coroner ruled her death an accident, but it was reclassified years later as “Cause of death unknown” in light of evidence that she may have been assaulted (Finstad, 2001). This example illustrates the difficulties in classifying causes of death in general, and classification is particularly difficult for suicides. We will begin by defining key constructs and classification issues. Despite classification difficulties, roughly 38,000 deaths per year are classified as suicides in the United States, making it the tenth leading cause of death (Murphy, Xu, & Kochanek, 2013). Worldwide, approximately one million people die by suicide per year. Across countries, it is estimated 60

that suicides are underreported due to a variety of factors, including misclassification and declining autopsy rates (Sainsbury & Jenkins, 1982; Tøllefsen, Hem, & Ekeberg, 2012). These statistics illustrate the major impact that suicide has on society and its importance as a public health issue, but they do not describe the emotional cost for those who lose a loved one to suicide and for those who contemplate or attempt suicide. The clinical course (i.e., development and progression) of suicidal behavior is little understood, but it appears to be an emerging area of research. Common correlates of suicide are understood much better, with a good deal of empirical epidemiological research supporting that understanding. Theories of suicide offer insight into the etiology of the behavior. Clinically, there are many viable options for the assessment of suicide.

Classification and Definitions

To begin, it is important to address two key issues:  (1)  classifying when a death was a suicide, and (2) defining suicide.

 

Classification

Deaths are classified into four broad causal categories: natural causes, homicide, suicide, and accident. The ambiguities in the boundaries among these categories are the crux of the problem. As in the example of Natalie Wood, one might conjecture the possibility that her death was due to suicide based on her background, which included her near-​death by drowning as a young girl, subsequent acting in a drowning scene, and a prior suicide attempt, though the evidence does not support suicide in her case. The other three categories are more likely, but her death still defies clear classification because the primary cause of death could have been hypothermia (natural causes), injuries sustained from an assault (homicide), or accidental drowning (with other possibilities being secondary). The degree to which intent is apparent can clarify the boundary between suicide and accident, which is commonly the most difficult distinction to make. Another issue is whether actual death occurs—​should “suicide” be an umbrella term that includes attempted suicide? If so, does it matter whether actual injury occurred? These issues are the subject of ongoing efforts in the field (as described by Van Orden et al., 2010) to refine current definitions, and these definitions are likely to continually evolve, although it should be noted that standardization could benefit communication and understanding regarding the discourse on suicide.

Definitions

Many researchers in the field of suicidology have sought to devise a nomenclature, or a set of clearly defined and commonly understood terms, for suicide-​related phenomena, with the goal of improving clarity and precision when communicating about suicide in research and clinical contexts. One of the first sets of nomenclature, which was widely used in clinics and research, was created by Aaron Beck, who was the first to make the distinction between suicidal ideation, attempts, and completed suicide (Ellis, 2006). Although Beck’s work for the National Institute of Mental Health is still widely adopted in suicidology, the emergence of a variety of new terms and concepts in suicide-​related phenomena has necessitated the development of more precise and comprehensive nomenclatures. More recently, O’Carroll and colleagues (1996) devised a set of suicidological nomenclature, which has since been revised by Silverman and colleagues (2007) to increase the feasibility of its use in clinical

contexts. Completed suicide is defined in terms of three components:  (1)  death as a result of injury that is both (2)  self-​inflicted and (3)  intentional. Based on this definition of suicide, O’Carroll and colleagues, and later Silverman and colleagues, created an outline to clarify suicide-​related terminology in terms of outcome and intent to die from suicide (see Silverman et  al., 2007 for an elaboration on the terms). This nomenclature defines suicide attempts as self-​ harming behavior involving intent for death, regardless of the result, and defines suicide-​related behavior as self-​ injurious behavior with the intention to kill oneself and desire to use this to attain another goal (Silverman et al., 2007). The field of suicidology not only focuses on the study of suicide but also seeks to understand suicide-​ related thoughts and behaviors, such as suicidal ideation and attempts. The majority of researchers and clinicians distinguish suicidal behavior from non-​ suicidal self-​ injury (e.g., cutting or burning oneself ), which is defined as self-​harming behaviors without the intention of dying (e.g., Nock & Kessler, 2006).

Epidemiology

Suicide is a leading cause of death across populations all over the world. In 2013, the World Health Organization (WHO) ranked suicide as one of the 20 leading causes of death (WHO, 2013). Roughly 800,000 people die by suicide each year, which amounts to one death every 40 seconds. Furthermore, it is estimated that 8–​ 16  million individuals make non-​fatal suicide attempts across the world each year (WHO, 2013). For 53% of those who died by suicide, it was their first suicide attempt (Simon et  al. 2002), but the remaining 47% had a history of previous suicide attempts. Such a history of suicide attempts substantially elevates one’s risk of death by suicide (Van Orden et al., 2008). Despite generally high rates of suicide-​ related behaviors worldwide, there are nevertheless patterns in suicide rates, which contribute to our understanding of risk for suicide. Rates of mortality associated with suicide vary across regions, countries, and other environmental factors, as well as individual factors, such as age, gender, and genetics (Harris & Barraclough, 1997). As of 2011, some of the highest rates of suicide, ranging from 40 to more than 60 deaths per 100,000 (WHO, 2013), are found in two of the Baltic nations of Europe (i.e., Lithuania, Latvia), countries of the former Soviet Bloc (e.g., Hungary, Kazakhstan) and several Asian nations (e.g., Sri Michaels, Chu, Joiner

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Lanka, South Korea; WHO, 2013). Latin American nations boast some of the lowest rates of suicide in the world (WHO, 2013); however, it should be noted that the incidence of suicide may be subject to over-​reporting and under-​reporting internationally, nationally, or regionally due to ambiguity in information, social stigma, and inconsistent standards (Sainsbury & Jenkins, 1982; Tøllefsen et al., 2012). Relatedly, within the United States, there are significant differences in suicide-​related behaviors among individuals of different ethnic and racial backgrounds (e.g., Gutierrez, Rodriguez, & Garcia, 2001). It has been posited that this may be due to factors such as acculturative and social stress, as well as socioeconomic status and sense of belonging (Gutierrez et al., 2001). Aside from ethnicity, other forms of culture, such as military culture, may also influence rates of suicidal behavior. In the past, rates of suicide in the U.S. military were lower than the civilian rate (i.e., 10.3–​11.3 per 100,000). However, in 2005, rates sharply increased, and, despite latest reports showing a welcome decrease, since 2009, the military suicide rate, which is approximately 18 per 100,000, has surpassed that of the general population (Kessler et al., 2013; LeardMann et al., 2013; WHO, 2013). War is likely to increase specific risk factors related to suicide among veterans, including acquired capability and post-​traumatic stress disorder (PTSD), but, to the authors’ knowledge, no specific studies have demonstrated definitively why the spike in rates of suicide has occurred. Recent studies have shown that major risk factors for military suicides are similar to risk factors in the general population, such as being of the male gender, and the presence of mental health disorders, substance abuse, and interpersonal or financial difficulties. Factors associated with deployment to war zones and combat were not found to be major contributors to risk (e.g., LeardMann et al., 2013). Suicide rates tend to increase with aging in many populations, across both genders (WHO, 2013). Suicide remains one of the ten leading causes of death among individuals aged 10–​64 years (WHO, 2013). In the United States, the rate of suicide in elderly Caucasian males increases precipitously, with rates peaking at 62 deaths by suicide per 100,000 (Conwell, Duberstein, & Caine, 2002) compared to the national average of 11.3 suicides per 100,000 people in the general population (Centers for Disease Control [CDC], 2013). Research has suggested that suicide later in life is highly correlated with social isolation (e.g., Conwell, 1994), physical illness (e.g., Quan et al., 2002), and mental 62 Suicide

illnesses—​ particularly major depression, which presents in 80% of individuals over the age of 74 who die by suicide (e.g., Conwell et  al., 1996). More recently, studies testing the traditional view of aging and suicide have reported that many countries do not show this trend, with some studies demonstrating that rates were highest in younger individuals (e.g., Shah, 2007). Despite shifts in the trend between aging and suicide, there remains evidence that elderly individuals are more likely to die among those who attempt suicide (Conwell, Duberstein, & Caine, 2002). Across different places and age groups, gender is consistently associated with differences in mortality rates (Hawton, 2000). Also referred to as “the gender paradox,” this gender gap in suicide is a striking pattern of generally higher prevalence rates of completed suicide in males than in females, while the opposite is true for suicide attempts, which see higher rates in females than in males (Canetto & Sakinofsky, 1998). Presently, China is the only country in the world where rates of suicide in females are equal to, or higher than, those of males, and suicide rates for both sexes and all age groups are three times higher in rural than in urban areas (Hawton, 2000; Phillips, Li, & Zhang, 2002). In the United States, gender differences also exist in the nature of suicide-​related behaviors, with males commonly employing violent methods of suicide and self-​harm, such as guns or asphyxiation, while less violent methods, such as drugs or carbon monoxide poisoning, tend to be used by females (Denning, Conwell, King, & Cox, 2000; Hawton, 2000). However, this trend appears to vary across cultures—​for example, one study conducted in South India reported that both men and women were likely to attempt suicide by using poison, albeit different types of poison, and self-​immolation was more common among women (Sudhir Kumar, Mohan, Ranjith, & Chandrasekaran, 2006). Relatedly, studies of sexuality have found higher rates of suicidal behavior in sexual-​minority individuals than in their heterosexual counterparts (e.g., Meyer, 2003). Studies consistently indicate that those who identify as homosexuals and bisexuals are approximately two times more likely to report suicidal ideation (King et  al., 2008), even when accounting for gender, age, and race (Silenzio et al., 2007). Results from one meta-​analysis found that rates of suicide attempts for sexual-​minority participants were between 20% and 42% (Remafedi, 1999). According to Meyer’s (2003) minority stress

 

model, environmental stressors such as experiences of harassment, discrimination, and prejudice create a hostile social environment that exacerbates risk for mental disorders, which are associated with an elevated risk for suicidal behavior. Mental disorders have been consistently associated with suicide across studies (e.g., Harris & Barraclough, 1997). Most individuals who die by suicide (i.e., 95%; Cavanagh, Carson, Sharpe, & Lawrie, 2003) suffer from mental disorders. Some have argued that all individuals who die by suicide could have been diagnosed with a mental disorder (e.g., Joiner, 2010). This position stretches beyond the current nomenclature to reconceptualize suicidal behavior as a primary form of psychopathology, rather than merely a consequence of another form of psychopathology such as depression, and this thinking is in line with current recommendations for revisions in the nomenclature (e.g., Oquendo et al., 2008). Even with the present nomenclature, mental disorders are one of the strongest predictors of attempted suicide (Harris & Barraclough, 1997), with comorbid diagnoses of two or more mental disorders conferring even greater risk (e.g., Nock et al., 2009). Specifically, the five mental disorders most robustly associated with suicide, in alphabetical order, are anorexia, bipolar disorder, borderline personality disorder, major depressive disorder, and schizophrenia (Joiner, Michaels, Chu, & Buchman-​ Schmitt, 2013). Individuals who suffer from at least one of these five disorders have suicide rates roughly 50 times higher than the general population (Harris & Barraclough, 1997). It is important to emphasize that, whereas these five mental disorders confer the highest risk, other mental disorders elevate risk as well. Anorexia nervosa (AN) is known as the most lethal of mental disorders. Although medical complications are the primary cause of death in anorexia, suicide was found to be the second most common cause of death, with approximately 27%–​32% of deaths occurring as a result of suicide (Franko & Keel, 2006). Deaths by suicide among those with AN are approximately 58 times more frequent than in the general population (Herzog et  al., 2000; Pompili, Mancinelli, Girardi, Ruberto, & Tatarelli, 2004). Furthermore, in one study evaluating case reports of suicide decedents with anorexia, death by suicide in anorexic individuals was not found to be the result of compromised physical health, which would lead to a decreased ability to be rescued following their attempt (Holm-​Denoma et al., 2008). Rather, death was the result of the commission of

a highly lethal attempt that would have taken the life of individuals with or without anorexia (Holm-​ Denoma et  al., 2008), indicating that anorexic individuals’ susceptibility to death by suicide is not explained by nutritional deficiencies. Although risk factors associated with suicidality (e.g., impulsivity, depressed mood) were not controlled, the authors suggest that these variables are unlikely to be the primary explanation for the high rates of suicide completion among anorexics—​there are high rates of these risk factors among those with other disorders conferring risk for suicide (e.g., impulsivity in bulimia nervosa). Longitudinal studies following a sample of individuals with anorexia nervosa until their death would be informative. In addition to high rates of suicide completion, rates of suicide attempts among individuals with anorexia are also high, ranging from 10%–​20% across studies (Franko & Keel, 2006). Bipolar disorder is also strongly related to suicidal behavior, with 20%–​56% of individuals with this disorder having a history of suicide attempts, and between 10% and 15% of individuals ultimately dying by suicide (Goodwin & Jamison, 1990; Harris & Barraclough, 1997; Hawton, Sutton, Haw, Sinclair, & Harriss, 2005b). Early onset of bipolar disorder, in addition to the severity of episodes and comorbidity, increase the risk for suicide attempts (Hawton et al., 2005b). Aside from general risk factors for suicide, bipolar-​disorder–​specific risk factors also exist, such as the early stages of the disease (i.e., first 7–​12  years; Tsai, Kuo, Chen, & Lee, 2002), and early onset of the disorder, family history of suicide, or a history of multiple attempts (see Gonda et al., 2012, for review). It is estimated that there is a 15-​fold increase in risk for suicide in individuals with bipolar disorder (Harris & Barraclough, 1997; Van Orden et al., 2010). Individuals with borderline personality disorder have been found to have very high rates of suicide-​ related behaviors (81%; Zanarini et al., 2003), with rates of completed suicide ranging from 4%–​5% up to 10% (American Psychiatric Association, 2001; Van Orden et al., 2010). Of the many symptoms of this disorder, emotional instability has been found to be most highly correlated with suicide (Yen et al., 2004). Major depressive disorder is consistently associated with suicide, and estimates of case fatalities are between 2% and 6%, depending on the type of population (i.e., outpatients versus inpatients; Bostwick & Pankratz. 2000). In adults, the early stages of the disorder representing a high-​risk period Michaels, Chu, Joiner

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for attempted suicide, even after controlling for the duration of the depression and its severity (Malone, Haas, Sweeney, & Mann, 1995). In adolescents, half of those who die by suicide meet diagnostic requirements for a current major depressive disorder at time of death (Marttunen, Aro, Henriksson, & Lonnqvist, 1991). Schizophrenia carries a lifetime prevalence of approximately 2%–​ 6% (Palmer, Pankratz, & Bostwick, 2005). In a meta-​analysis of risk factors in individuals with schizophrenia, specific risk factors included agitation, previous depressive episodes, and previous suicide attempts (Hawton, Sutton, Haw, Sinclair, & Deeks, 2005a).

Phenomenology

The course of suicidal behavior is not nearly so well studied as some other psychological syndromes, such as schizophrenia (conceptualizations of which have included prodromal, active, and residual phases). Psychologists as early as Kraepelin in 1896 described prodromal disturbances as occurring prior to overt psychotic symptoms (as described by Klosterkötter, Schultze-​ Lutter, & Ruhrmann, 2008). Current conceptualizations of suicidal behavior do not follow such a classification system, and there is insufficient evidence for the existence of distinct “phases” of suicidal behavior across individuals. However, some trends emerge, and there are consistencies in clusters of symptoms for those at imminent risk of suicide. Peer-​reviewed studies in this area are rare, which represents an excellent opportunity for future direction in suicide research. In one of the few examples of such studies, Busch, Fawcett, and Jacobs (2003) conducted an analysis of charts from 76 patients who died by suicide while under hospital care or immediately following discharge. This study identified several imminent risk factors for suicide, including severe anxiety and/​or extreme agitation (Busch et al., 2003). Beyond the lack of studies, other issues in this area include the lack of scientific approach. The “psychological autopsy” procedure is a method used to determine the underlying factors in ambiguous deaths that involves interviewing family members and individuals with whom the decedents had interactions closely prior to their deaths (Didi Hirsch Mental Health Services, 2011). Although such qualitative data can shed light on the experiential aspects of suicide, the approach to analyzing data gathered in this manner should be scientific. While some authors describe single cases (e.g., Shneidman, 1993), Robins (1981) conducted 64 Suicide

psychological autopsies of 134 suicide decedents and discussed aggregate patterns across the case studies on the basis of interviews with informants, such as family members, other relatives, friends, and other acquaintances. Robins (1981) described several important symptoms exhibited by the decedents prior to their death, including weight loss (60%), nervousness (59%), insomnia (58%), weekly to daily alcohol consumption (53%), and sadness (46%). Other characteristics included unemployment (25%), feelings of burdensomeness (21%), and feelings of worthlessness or being no good (22%). These qualitative features are also conceptualized in non-​phenomenological work as part of the interpersonal theory of suicide (e.g., believing that one’s death is more beneficial than one’s life; Van Orden et  al., 2010). This theory is described in greater detail later.

Etiology

The interpersonal theory of suicide (ITS) was developed in response to a relative lack of theoretical explanations of suicidal behavior in comparison to existing theoretical understanding of other psychopathologies, with the aim of inviting serious scientific inquiry, including attempts to falsify the central tenets of the theory (Van Orden et  al., 2010). Prior to the development of this theory, there was a paucity of integrative models that addressed factors both within the individual and between individuals and environments (e.g., Prinstein, 2008). Three key etiological constructs are posited in the ITS, which have been thoroughly tested empirically. These proximal risk factors include thwarted belongingness, perceived burdensomeness, and acquired capability, which are discussed more in depth later (Van Orden et  al., 2010; Joiner, 2005). The ITS is a relatively new theory of suicide, and to understand its context, it is useful to discuss a history of psychological theories of suicide. An early approach to understanding suicide scientifically was Dublin and Bunzel’s (1933) analysis. They studied data from the Metropolitan Life Insurance Company, using rigorous statistical methodology. Although their approach was atheoretical, they discussed a number of important trends. Notably, these authors were among the first to describe the gender effect of men completing suicide more frequently than women, but women attempting suicide more frequently

 

than men (as cited by Joiner, Michaels, Chu, & Buchman-​Schmitt, 2013).

Biological Explanations for Suicide

Behavioral genetic studies suggest that genetics may contribute to a diathesis for suicide-​ related behaviors (e.g., Joiner et  al., 2002; Mann et  al., 2000); however, consensus about which genetic components are contributing factors is lacking (Joiner, Michaels, Chu, & Buchman-​ Schmitt, 2013). To date, a major focus of suicide-​related genetic studies has been on the serotonin transporter gene polymorphism (5-​HTTLPR, which is the gene coding for the serotonin transporter; Mann et  al., 2000). Some have suggested that 5-​HTTLPR may be more specifically relevant to violent and multiple suicide attempts as opposed to those exhibiting general suicide-​related behaviors (Bondy et al., 2006). However, findings from a meta-​analysis conducted by Lin and Tsai (2004) failed to show a direct relationship between the polymorphism and suicidal behavior. In general, the available evidence to support causal claims for biological explanations of suicide is inconclusive.

Cognitive Behavioral Theories of Suicide

With regard to the cognitive-​ behavioral approach, Aaron Beck led much of the seminal work relating cognition to suicidal risk. This work is built on the strong association between depression and suicide, which is well-​established (e.g., Malone et  al., 1995; Marttunen et  al., 1991). Beck reasoned that serious suicidal intent is not so much related to depression itself as it is related to negative expectations, which are an aspect of depression (Beck, Weissman, Lester, & Trexler, 1974). Thus, the “association between suicidal intent and depression is an artifact resulting from a joint attachment to a third variable, namely hopelessness” (Beck et al., 1974). To put it another way, the presence of hopelessness in many depressed patients accounts for the relationship between depression and suicide. Conceptually, Shneidman (1993) described “psycheache” as psychological pain leading to suicide with cognitive overtones. However, this conceptual framework has yet to be thoroughly tested empirically.

Suicide-​Specific Theories

As mentioned above, the ITS posits that three constructs (thwarted belongingness, perceived burdensomeness, and acquired capability for suicide) are proximally related to both serious suicide

attempts and death by suicide (Van Orden et  al., 2010; Joiner, 2005). These constructs were initially posited in Joiner (2005), in which acquired capability involves an individual’s overcoming the natural self-​preservation instinct and thereby having the ability to enact lethal self-​injury. However, capability alone is not enough, because “there are many people who, through an array of provocative experiences, have become fearless, pain-​ tolerant, and knowledgeable about dangerous behaviors, and yet who have no desire to hurt themselves” (p. 47). It is only when capability interacts with desire that an individual can enact a serious or lethal suicide attempt. The desire for suicide is conceptualized as consisting of the interaction between thwarted belongingness and perceived burdensomeness. The former involves the thwarting of the need for affiliation, which is a “superordinate need” according to Henry Murray (as cited by Joiner, 2005), an expert on human needs. The latter, burdensomeness, involves individuals’ believing themselves to negatively affect others because they perceive themselves to be ineffective. These perceptions may be inaccurate, but they believe that their perceived ineffectiveness or incompetence is stable and not temporary, and probably experience shame because of these feelings, to the point where their death becomes a realistic way for them to reduce the perceived burden on others. Subsequently, Van Orden and colleagues (2010) revised the theory through a more nuanced delineation of its three primary constructs. Thwarted belongingness was conceptualized as the subjective experience of being alone, consisting of both feeling disconnected from others and the absence of reciprocal care relationships. Perceived burdensomeness is conceptualized as the subjective feeling that “I am a burden,” and consists of the belief that one is more of a liability than an asset to others, as well as feelings of self-​hatred. Dimensions of acquired capability that are also included are a reduced fear of death and elevated physical pain tolerance. The main aims of the ITS are to provide a generative scientific framework and a lens through which other factors can be investigated. For example, “disgust” is a novel factor with regard to suicide, but it may hold some promise and can be examined within this theoretical framework. Another aim is to predict future suicidal behavior through the identification of proximal risk factors (Van Orden et al., 2010). As mentioned in Robins (1981), self-​ disgust has been found to be present in individuals in the Michaels, Chu, Joiner

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final months before they died by suicide. Recently, researchers have conceptualized the potential role that disgust with life may play in severe suicidal ideation and behavior (Chu, Buchman-​ Schmitt, Michaels, Ribeiro, & Joiner, 2013). Specifically, disgust with life is conceptualized as encompassing self-​disgust as well as disgust with others or with the world. Disgust with life may (at least partially) motivate withdrawal from life—​including social withdrawal and withdrawal from normal physiological activities (e.g., eating, sex, even drinking alcohol). These behaviors have been observed in individuals fairly shortly preceding their death (Robins, 1981), and this conceptualization represents an alternative explanation to the previously hypothesized mechanism, in which these behaviors are believed to be driven by over-​arousal. The relationship between disgust with self and suicidal behavior may be mediated by perceived burdensomeness and the relationship between disgust with others/​the world, and suicidal behavior may be mediated by thwarted belongingness. If it were instead demonstrated that the disgust predictors mediated either the relationship between perceived burdensomeness and suicide, or thwarted belongingness and suicide, then such evidence would falsify the claim that the ITS variables are proximally related to suicide. Alternative theoretical models of suicidal behavior include O’Connor’s (2011) Integrated Motivational-​Volitional (IMV) Model of Suicidal Behaviour, a tripartite model that maps relationships between background factors and events to the development of suicidal ideation/​intent, which is in turn linked to the development of actual suicidal behavior. The model is based on the Theory of Planned Behavior, which states that a person’s behavior is predicted directly by their behavioral intentions, which are in turn predicted by attitudes, social norms, and perceptions about behavioral inhibition (O’Connor, 2011). This model is of particular interest when examined in comparison to the ITS. The IMV model includes the constructs of thwarted belongingness and perceived burdensomeness as motivational moderators and acquired capability as a volitional moderator. The ITS states that these constructs are directly and proximally necessary for suicidal behavior, and that the relationships between all other factors and suicide are fully mediated by these three constructs. The IMV model states that thwarted belongingness and perceived burdensomeness merely moderate the relationship between entrapment and suicidal ideation/​ intent (and are thus 66 Suicide

not “necessary,” in the logical sense of the word). Likewise, acquired capability merely moderates the relationship between suicidal ideation/​intent and suicidal behavior (and is likewise not necessary). Thus, the crux of the difference between these two theories is the role of thwarted belongingness, perceived burdensomeness, and acquired capability. Specifically, the ITS framework states that the three constructs are directly related to suicidal behavior, and the IMV model implies that the three constructs are indirectly related to suicidal behavior. These theoretical distinctions have yet to be tested empirically, however.

Other Theoretical Perspectives

Menninger’s (1938) speculations in Man Against Himself may be of interest for their historical value. He describes suicide as resulting from aggression turned inward, reflecting his psychodynamic background, but he digresses into speculations about associations between suicide and factors such as masturbation and nail-​biting, which were never tested empirically. Similarly, Freud (1922) contemplated the apparent contrasts between self-​ preservation and the inevitable death of every organism, leading him to posit the existence of “death instincts” as a foil to sexual “life instincts.” A reflection on the popularity of these ideas makes one realize how a scientific approach to the understanding of suicide has progressed. Several modern applications of psychodynamic perspectives have been conducted. One such application was an empirical study designed to determine whether psychiatric inpatients hospitalized for a suicide attempt could be distinguished from matched control psychiatric inpatients on the basis of four psychodynamic factors: self-​directed aggression, object loss, ego functioning disturbance, and pathological object relations (Kaslow et al., 1998). Support was found for the object-​relations hypothesis, and partial support was found for the object-​ loss hypothesis, but the other two hypotheses were not supported.

Assessment Clinical Practice

Suicide risk assessments provide crucial benefits both for managing suicidal behavior and for providing treatment benefits. Cukrowicz, Wingate, Driscoll, and Joiner (2004) have recommended the following best practices, among others, with regard to the standard of care for the treatment of suicide in a clinical setting: the use of empirically supported

 

risk assessments and flowchart-​style decision trees (e.g., Joiner, Walker, Rudd, & Jobes, 1999), which aid clinicians in making decisions about patients’ risk level and the appropriate actions, as well as being mindful of their legal responsibilities. Furthermore, assessments should focus on factors that are most predictive of completed suicide. Following these guidelines increases safety for suicidal patients and provides the secondary benefit of reducing legal liability. One empirically supported approach to suicide management is the Collaborative Assessment and Management of Suicidality (CAMS; Jobes & Drozd, 2004). The CAMS approach to suicidality is focused on the development of a robust therapeutic alliance between the therapist and client, which serves as the channel for delivering necessary clinical interventions. The CAMS approach is based on the use of the Suicidal Status Form (SSF), which comprises a comprehensive risk assessment and documentation, the development of a treatment plan, and ongoing monitoring and documentation of risk. The CAMS approach emphasizes empathy with the suicidal client (Jobes, 2011) and as such, it posits that this assessment process allows the client and therapist to work together to manage the client’s suicidal behavior. Moreover, this process is purported to have a therapeutic effect, and thus, CAMS functions as a treatment. To date, the use of CAMS and the SSF has been supported by a variety of correlational studies and one randomized control trial (Jobes, 2012), which showed that CAMS, compared to enhanced treatment as usual, had more robust effects on suicidality at the end of treatment and at follow-​up (Comtois et al., 2011). Joiner and colleagues (1999) describe one method for standardizing suicide risk assessment practices by use of a risk assessment tree. The decision tree described by Joiner and colleagues (1999) includes an assessment of suicide attempt history, and considers whether the individual endorsed any resolved and detailed plans for suicide, preparations for suicide (e.g., buying a gun, writing a suicide note), suicidal desire, and ideation or thoughts about suicide. Other factors are also assessed, such as significant negative life events, hopelessness, impulsivity, and presence of psychopathology. Although protective factors are discussed in this article, they are viewed as less reliable predictors that may not influence the accuracy of risk assessment. Other warning signs, such as agitation, insomnia, nightmares, and social withdrawal, may be considered in

determining suicide risk. After these various items are assessed, the individual is designated at either “low,” “moderate,” “severe,” or “extreme” risk for suicide. On the basis of this suicide risk designation, clinicians may follow Joiner and colleagues’ (1999) recommendations for appropriate actions that ensure the safety of the at-​risk individual. A person in the “low” risk category has either no identifiable suicide-​related symptoms, has multiple suicide attempts with no other risk factors, or has one suicide attempt or fewer with limited suicidal ideation and limited or no resolved plans and preparation, as well as no or few additional risk factors. A person with “moderate” risk has either multiple previous attempts with any other notable finding, one attempt or less with at least moderate resolved plans and preparation, and one attempt or fewer with at least moderate suicidal desire and ideation and two additional risk factors. “Severe” risk is designated if an individual has multiple attempts with two additional notable risk factors or (at most) one attempt, at least moderate symptoms of resolved plans and preparation, and at least one other significant risk factor. “Extreme” risk is designated for individuals with multiple attempts who have severe resolved plans and preparation or individuals with at most one attempt but at least two additional significant risk factors.

Legal Concerns

Lastly, when conducting suicide risk assessments, it is recommended that clinicians consider their legal responsibilities. In the United States, state law dictates these responsibilities, with the majority of states mandating “a duty to warn” and a minority of states granting “permission to warn” (Herbert, 2002). Beyond this distinction, there is still a good deal of variation in legal requirements. “No-​suicide” contracts are often used, but they have been found to have little practical benefit and do not protect from liability, because a fair percentage of those who die by suicide have signed such contracts. Specifically, Busch and colleagues (2003) have found that 28% of those who died by suicide had a no-​suicide contract in effect.

Future Directions

Though scientific understanding of suicide has advanced beyond early speculative psychodynamic frameworks, suicidology remains a relatively new interdisciplinary field. Key areas for growth include increased awareness regarding a Michaels, Chu, Joiner

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standardized terminology, advances in research methodology, increased phenomenological understanding, and dissemination of assessment best practices. Consistent use of established nomenclatures of terms related to suicide is likely to lead to increased validity and generalizability of findings across research and clinical settings. Future research focusing on advancing methodology in psychological autopsies would also be beneficial. Disadvantages of psychological autopsy studies to date have included a lack of internal reliability given the common use of single-​item interview questions, as well as inconsistent measurement across studies. Given that this technique relies on detailed case history of decedents, achieved ecological validity may be much greater compared to studies involving suicide as an outcome variable through the use of measures that only approximate death by suicide, such as current suicidal ideation. Development of psychometrically validated measures for use in psychological autopsies would maintain the validity advantages of this approach, while mitigating current disadvantages. For researchers desiring a qualitative approach, evaluation of open-​ended clinical interviews by multiple raters and high inter-​rater reliability among blind raters could lend greater rigor to future research examining phenomenological descriptions of suicide. Finally, the use of empirically supported frameworks for risk assessment has been shown to improve outcomes for patients. It is unclear, however, whether dissemination of these best practices has resulted in their widespread usage, which could be clarified if new research is conducted on training standards and policies across accredited sites. Though a psychological approach to suicidality has been adopted throughout this chapter, there is a recognized need for interdisciplinary cooperation between fields ranging from sociology to medicine in the prevention and treatment of this leading behavioral cause of death.

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Disordered Mood in Cultural-​Historical Context

Andrew G. Ryder, Yue Zhao, and Yulia E. Chentsova-​Dutton

Abstract The research literature on mood disorders is dominated by Western concepts. Historical changes and cultural variations are the focus of this chapter. We begin with a historical overview, then turn to the contemporary literature on cultural variations in mood disorders, focusing on: (1) etiological beliefs, (2) risk and resilience, (3) incidence and prevalence, and (4) symptoms. We propose an approach to understanding cultural variations in psychopathology based on a core idea from cultural psychology: the mutual constitution of culture, mind, and brain. Then, we describe some of the ways symptoms of disordered mood can be understood as emerging from looping processes in the culture-mind-brain system. For future research, we emphasize the importance of integrative studies across culture-, mind-, and brain-levels. Then we consider the possibility that historical changes in descriptions of disordered mood might include culturally shaped transformations in normal and abnormal experience. Key Words:  culture, history, depression, mania, psychopathology, mood

Mood disorders disrupt lives worldwide, posing grave threats to productivity, relationships, and well-​ being. Depression in particular is projected to become one of the top two contributors to the global burden of disease by 2030 (Lopez & Mathers, 2006). Mania, while less common, wreaks considerable havoc, often in tandem with depression. Given the personal and social costs of these disorders, there is an urgent need to better understand their etiology, presentation, course, and outcome, along with the best options for treatment. Yet, the overwhelming majority of studies on depression and mania, as with psychopathology more generally, rely on “Western” models of conceptualizing, assessing, and treating these disorders. Even when some of these studies are conducted elsewhere, there is usually an assumption that Western-​based criteria reflect universal phenomena. Cross-​national research is thus most often conducted with the limited aim of evaluating people who meet these criteria in different cultural contexts. In this view, mood disorders are like other medical conditions that have a clear etiology

and pathology leading to a specific set of symptoms. Available evidence suggests otherwise. In this chapter, we argue that mood disorders are profoundly shaped by their cultural and historical context. We begin with a brief history of mood disorders before turning to contemporary research on (1) etiological beliefs, (2) stress and vulnerability, (3) incidence and prevalence, and (4) symptom presentation. As this literature includes many more studies of depression than mania, and many more studies conducted in North American or Chinese samples compared with the rest of the world, our review is weighted accordingly. We note also that, while these bodies of research inform us about how mood disorders vary across cultural contexts, relatively little is understood about how culture shapes these disorders. Indeed, throughout our review we are hampered by the lack of a coherent view of “culture” in many of these studies. Moreover, there is a paucity of theoretical and empirical work integrating the cultural level of analysis with those of mind and brain. We 71

 

are left with an isolated set of cultural facts about the mood disorders rather than an integrated perspective. In the second half of this chapter, we begin outlining what such a perspective might look like in light of emerging ideas on the mutual constitution of culture, mind, and brain (Kitayama & Uskul, 2011; Ryder, Ban, & Chentsova-​Dutton, 2011). We conclude by briefly considering two directions for future research. For the first, we call for more studies explicitly designed to study interactions across culture-​, mind-​, and brain-​levels of analysis. For the second, we return to the historical review of the mood disorders and propose that historical era, like cultural context, might actually shape how these disorders are experienced and expressed by people suffering from them.

A Brief History

Descriptions of various dejected and excited states can be found in Western literature, dating back to its written origins (Jackson, 1985). The concept of melancholia, for example, can be traced to the writings of Hippocrates, who described symptoms that include despondency, loss of appetite, insomnia, irritability, and restlessness. Indeed, the term itself comes from Hippocrates’ humoral theory of illness, with melancholia denoting an excess of “black bile” (Ancient Greek melan-​ = black, kholē = bile); excited mania, meanwhile, was attributed to an excess of “yellow bile.” Aretaeus of Cappadocia, in the second century ce, described how some people tend to oscillate between excited and melancholic states (Akiskal, 1996). Whereas melancholia described a psychological state with a biological cause, acedia described a superficially similar state with a very different etiology. The term was originally used to describe the sense of isolation and spiritual despair experienced by some ascetic monks, and included experiences such as sad mood, low spirits, anguish, loss of energy, fatigue, carelessness, sloth, and negligence. These “symptoms” were seen as the consequences of succumbing to the demon of acedia—​the “noonday demon”—​sent to test the devoted monk (Wenzel, 1960). Over time, as various schemes of deadly sins were described and preached against, acedia became associated with these universal dangers (Jackson, 1985). While still understanding acedia as a sin, the scholastics of the 1200s increasingly described it as a disorder of emotional life, sometimes even in humoral terms. Notably, texts that considered natural causes also tended to describe acedia less as a vice, reducing its stigma (Wenzel, 1960). 72

By the 1500s, acedia had been absorbed by the humoral theory, losing its distinct etiology but retaining some of its moral force (Kleinman, 1986). Meanwhile, melancholia became an increasingly broad term, so that by the early 1800s, it included most mental illnesses that involved few delusions as opposed to many. This trend towards generality started to reverse with “faculty psychology,” a nineteenth-​century philosophical attempt to break down psychological functioning into irreducible “faculties.” The faculty of “affectivity” captured the domain of mood and emotion; disorders in this faculty were referred to as affective disorders. The concept of melancholy thus shifted from a very broad category to a specific form of disordered mood. Borrowing a then-​popular word in cardiovascular medicine for reduced function, this new disorder was named depression (Berrios, 1996). The classical idea that depressed and excited mood states might be linked had lain dormant for almost two millennia, but was picked up again in the mid–​nineteenth century. In the 1820s and 1830s, Esquirol, with his students and colleagues, began to follow the course of mental illness over time rather than relying on cross-​sectional descriptions (Akiskal, 1996). By the time of Kraepelin’s (1921) landmark division of schizophrenia and manic-​depressive illness, both “mania” and “depression” clearly defined serious, potentially debilitating, problems. What, then, of the milder forms of depression, more in the tradition of acedia? While European psychiatrists were linking mania and depression, American neurologists were describing various syndromes attributed to functional exhaustion of the nervous system, or neurasthenia (Shorter, 1992). Beard (1869) described this as a nervous syndrome comprising more than 50 symptoms, including “general malaise, debility of all the functions, poor appetite, abiding weakness in the back and spine, fugitive neurological pains, hysteria, insomnia, hypochondriasis, disinclination for consecutive mental labor, severe and weakening attacks of sick headache, and other analogous symptoms …” (p. 12). “Nervous exhaustion” was most commonly described among educated people in the middle and upper social classes, particularly “mental workers” who were dealing with the stressful consequences of rapid modernization (Liu, 1989). By the dawn of the twentieth century, neurasthenia was well known both professionally and popularly throughout the industrialized West. The twentieth century also brought psychoanalysis. While the early analysts classified neurasthenia

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as an “actual neurosis”—​that is, as caused by a physical problem of the nervous system—​the spread of psychoanalytic practice was accompanied by the spread of its conceptual domain. As it became increasingly difficult to diagnose neurasthenic symptoms in the absence of a putative intrapsychic conflict, the category fell into disuse (Chatel & Peele, 1970). Ironically, now that psychiatry has all but abandoned this archaic term, other branches of medicine are confronting relatively “new” problems characterized by prolonged fatigue. Abbey and Garfinkel (1991), for example, found a high degree of overlap between chronic fatigue syndrome and the original descriptions of neurasthenia by Beard. Curiously, as the neurasthenia diagnosis was all but disappearing in North America and Western Europe, it was being introduced, studied, and increasingly adopted in East Asia. Between the founding of the Republic of China in 1912 and the Communist Revolution of 1949, Chinese physicians used the American concept of neurasthenia, regarding it as an anxiety reaction (Liu, 1989). After the revolution, the chief scientific influence on China shifted to the Soviet Union—​but there, too, neurasthenia had become popular in no small part due to the integration of Beard’s (1869) original work into Pavlovian psychology. After China’s break with the Soviet Union in the 1960s, Chinese physicians took a renewed interest in the indigenous literature on traditional Chinese medicine (TCM), noting several similar, popularly known, and non-​ stigmatizing diagnostic equivalents to neurasthenia in the TCM system (Lee, 1999). While these equivalents have an ancient pedigree within TCM, constructs resembling depression emerged much more recently and never became as important as in the West (Tseng, 1974). In many ways, Chinese neurasthenia appears to be following the trajectory of its Western counterpart. In the 1980s, neurasthenia rates were extremely high, although the label may have been assigned in many cases to help patients and families avoid stigma (Lee, 1999). Over the past few decades, however, there has been a steady shift towards the use of the “depression” label, and perhaps even a shift towards a symptom-​presentation pattern that more closely resembles that of Western depression. This intriguing possibility—​that the historical era can actually shape symptom presentation and not merely how syndromes are described—​will be taken up in the final section of this chapter. First, let us consider some contemporary evidence pertaining to cultural group variations in depression and mania.

Cultural Group Variations

Research on mood disorders is based almost exclusively on one of two widely used classification systems—​The Diagnostic and Statistical Manual of Mental Disorders (DSM-​ 5; American Psychiatric Association, 2013) or the International Classification of Diseases (ICD-​10; World Health Organization, 2008). Both systems define pathological disturbances of mood as central to mood disorders. As described in Chapter 2 of this volume, this family of diagnoses can be broadly subdivided into the unipolar mood disorders, such as major depressive disorder (MDD) and the bipolar mood disorders, such as bipolar I disorder (BD). Indeed, “depression” can be used to describe a mood state, a symptom, a constellation of symptoms, a discrete episode, a chronic condition, a trait-​like dimension, or a categorical diagnosis. In addition to this ambiguity, the term “depression” carries with it a set of cultural assumptions. For that reason alone, a straightforward comparison across different cultural groups based on a formal diagnostic system is problematic. Even a diagnostic category that appears to work well enough in a given cultural context does not necessarily carry the same meaning, or describe the same kind of people, as it does in another cultural context. Diagnostic manuals are themselves cultural products. The centrality of depressed mood and anhedonia to MDD in a given context, for example, cannot emerge as a finding from research using a diagnostic system that already requires one or both of these symptoms. Indeed, while in this chapter and elsewhere we retain terms like “depression” and “bipolar disorder” when reporting results from studies grounded in these systems, we nevertheless prefer when possible to use broader and less explicitly culture-​ bound terms such as “serious distress” or “disordered mood” (Ryder & Chentsova-​Dutton, 2015). The available research evidence bolsters our concern about the uncritical use of Western labels—​ and Western ideas more generally—​to describe mood disorders across cultural contexts. It is to this evidence that we now turn.

Etiological Beliefs

The criteria for mood disorders in the DSM and ICD reflect Western beliefs and values that emphasize the Cartesian distinction between mind and body (Ryder et al., 2008; Ryder & Chentsova-​ Dutton, 2012). Indeed, most of the scientific and clinical literature on mood disorders has been generated in contexts with strong cultural links to Ryder, Zhao, Chentsova-Dut ton

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Western Europe, particularly the United States. Many of the basic assumptions of these contexts are, however, idiosyncratic from a global perspective. Researchers have exhaustively documented the emphasis in the industrialized West on the uniqueness and autonomy of the self; in this view, healthy functioning is grounded in a positive self-​ image, personal values and achievements, and open expression of one’s emotions (Kirmayer, 2007). In such contexts, mental disorders are often “psychologized,” understood as problems of the mind (Ban, Kashima, & Haslam, 2012). Far more common globally are cultural contexts that promote interdependence through relationships and social networks, although there is considerable heterogeneity in the ways this is done. In East Asian cultural settings, for example, healthy functioning tends to be characterized by self-​criticism, avoidance of interpersonal conflicts, and inhibition of emotional expression depending on relational needs, all with the aim of preserving group harmony (Heine, Lehman, Markus, & Kitayama, 1999; Markus & Kitayama, 1991, 2010). Mental disorders are more likely to be flagged if they disrupt this harmony, and then “moralized,” understood as a moral violation or failure of some kind (Ban et al., 2012). The consequence may be increased stigma for certain kinds of symptoms, and a tendency to avoid discussion of these symptoms: for example, stigma was associated with psychological symptoms but not somatic symptoms in a sample of female Turkish migrants in Germany (Montesinos et al., 2012). In many cases, more than one model of serious distress may be available in a given cultural context, with use of these models depending on the situation. Pritzker (2007), for example, observed that depressed Chinese people often shift in their use of bodily metaphors, locating depression sometimes in the heart and sometimes in the brain, each with different implications. Modernization and Westernization processes in many societies can introduce people to new models of depression, but these models often end up coexisting with—​rather than replacing—​ traditional models. Privileging some expressions and ignoring others can lead researchers and clinicians to miss important heterogeneity within a particular cultural context. This diversity of beliefs, both within and across cultural contexts, also has consequences for the dividing line between normal and abnormal:  at what point is serious distress pathologized? In some cultural contexts, serious distress is understood as a troubling but otherwise normal part of the human 74

experience. In Good’s (1977) classic ethnography conducted in Iran, serious distress was seen as the consequence of living a moral life in a fallen world. People in Eastern European cultural contexts tend to report lower levels of positive emotions compared to other Europeans, but they do not pathologize this tendency unless the symptoms are severe (Jurcik, Chentsova-​Dutton, Solopieva-​Jurcikova, & Ryder, 2013). Similarly, compared to their peers in the United States, older Russians are less likely to view depression as an illness and more likely to consider it a normal part of aging (Turvey et al., 2012). Similar conclusions have been drawn by researchers studying older Hmong and Cambodian samples (Lee et al., 2010). Cultural variations in etiological beliefs about serious distress can shape understandings about who is potentially vulnerable, as well as the kinds of stressors that might be especially troublesome. These beliefs, as we shall see, might even act directly to shape risk for serious distress in particular cultural contexts.

Stress and Vulnerability

There has been a long-​standing interest in the interactional contributions of stress and vulnerability on risk for mood disorders. Certain vulnerability factors are potentially universal. For example, rumination, hopelessness, and reliance on maladaptive coping strategies are associated with increased depression in both Chinese and North American samples (Auerbach, Abela, Zhu, & Yao, 2010; Stewart et al., 2004). Nonetheless, there is evidence to support the cultural shaping of vulnerability and its sources. For example, emphasizing individualistic values may confer vulnerability to depression by broadening discrepancies between realistic outcomes and cultural ideals, in turn leading to negative self-​evaluation (Reynolds, Stewart, MacDonald, & Sischo, 2006). Submissive behaviors can exacerbate this vulnerability (O’Connor, Berry, Weiss, & Gilbert, 2002), perhaps attributable to the tendency in Western cultural contexts to emphasize self-​ assertion (Heine et al., 1999). There is emerging evidence that the high value placed on the pursuit of happiness, so central to American individualism, may actually confer vulnerability to mood disorders. For example, evidence from non-​clinical samples shows associations between happiness valuation and loneliness, unhappiness, and less response to a positive mood induction (Mauss, Tamir, Anderson, & Savino, 2011; Mauss et  al., 2012). Happiness valuation

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was also associated with more depressive symptoms in a remitted depressed group and was stronger in a remitted depressed group compared to a non-​ depressed group (Ford, Shallcroft, Mauss, Floerke, & Gruber, 2014). Moreover, happiness valuation was associated with a measure of BD risk, higher likelihood of past BD diagnosis, and worse prospective illness course for BD (Ford, Mauss, & Gruber, 2015). These findings may be context-​specific: in a four-​country study, happiness valuation was only associated with lower well-​ being in the United States (Ford et al., 2015). Culture also shapes both the likelihood and the assigned meaning of stressors. For example, interpersonal conflicts appear to be primary stressors for Western adolescents (Grant et  al., 2006), whereas poor academic performance has a stronger association with depression in Chinese than in American adolescents (Li & Zhang, 2008). Poor academic performance was found to be prospectively associated with depression in Chinese children, and to predict severe depression and suicidal ideation in Chinese adolescent samples (Chen, Rubin, & Li, 1995; Hesketh, Ding, & Jenkins, 2002). Auerbach, Eberhart, and Abela (2010) found that interpersonal stress interacted with low self-​ control to predict a later increase in depressive symptoms in Canadian but not Chinese adolescents. The authors propose that stressed Chinese adolescents with a reduced sense of control tend to act in ways that generate future stress. As culture shapes importance of primary control (Sastry & Ross, 1998), future studies should evaluate cultural mechanisms underlying these findings. Such mechanisms might help explain cross-​country group differences reported in epidemiological studies.

Incidence and Prevalence

Further evidence suggesting the importance of cultural context to mood disorders can be found in cross-​national projects by psychiatric epidemiologists. While these studies are limited by their tendency to assess mood disorders according to Western-​ derived criteria, country-​ level differences at least alert us to the possibility of intriguing cultural variations. Weissman and colleagues (1996) examined ten sites and found lifetime prevalence estimates ranging from 1.5% (Taiwan) to 19.0% (Lebanon). Studies by the International Consortium of Psychiatric Epidemiology also covered ten sites and found lifetime prevalence estimates ranging from 3.0% (Japan) to 16.0% (United States) (Andrade et al., 2003).

Researchers have generally found lower rates of depression in East Asia, relative to North America and Western Europe. For example, the Global Burden of Disease project reported a one-​year incidence rate for MDD in China of 2.3% (Murray & Lopez, 1996) compared with the 10.3% rate previously found in the United States (Kessler et  al., 1994). Across a number of studies, the one-​year incidence rate for MDD ranges from a low of about one in forty people in some countries (e.g., in East Asia) to a high of about one in twelve in others (e.g., in North America) (e.g., Demyttenaere et al., 2007; Kessler et al., 2009; Lin & von Korff, 2008; Ohayon & Hong, 2006; Vasiliadis, Lesage, Adair, Wang, & Kessler, 2007). Weissman and colleagues (1996) found that the lifetime prevalence of BD ranges from 0.3% (Taiwan) to 1.5% (New Zealand). In other words, a Western society had a rate five times higher than that of a Chinese society (the United States was three times higher than Taiwan), raising questions about the cultural shaping of BD similar to those about MDD (Hechtman, Raila, Chiao, & Gruber, 2013). A  Chinese epidemiological study found the 12-​month prevalence rate of BD to be 0.1% (Shen et al., 2006); in contrast, the U.S. National Comorbidity Survey Replication found a one-​year prevalence rate for BD of 2.6%. The reasons underlying this variation are unclear, and not necessarily related to “culture” as such. For example, Noaghiul and Hibbeln (2003) have shown an inverse relationship between bipolar rates and seafood consumption, suggesting a link with Omega 3 fatty acids. Other researchers have found evidence for higher rates of hypomanic traits, which are associated with increased risk for mood disorders, in at least some migrant samples (Carta et  al., 2012; Swinnen & Selten, 2007). Evidence of group difference is not necessarily evidence for cultural shaping, underscoring the need for studies specifically designed to unpack these effects.

Symptom Presentation

In contrast to syndrome-​focused epidemiological studies, research on symptom presentation has focused much more directly on cultural processes. There is now considerable anthropological and psychological evidence to support the idea that culture not only informs beliefs about serious distress, but also shapes the symptoms themselves. While the list of potential symptoms across cultural contexts is finite, it is also much longer than the collections presented in DSM or ICD; culture appears to play Ryder, Zhao, Chentsova-Dut ton

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a critical role in determining which symptoms are emphasized (Ryder & Chentsova-​Dutton, 2015). For example, Korean migrant women in the United States tend to emphasize emotional entrapment—​ the experience of having to hide one’s negative feelings about others without an outlet for expressing them (Bernstein, Lee, Park, & Jyoung, 2008). Distressed Puerto Ricans tend to focus on crying jags, sleeping difficulties, and even visions (Koss-​ Chioino, 1999), whereas distressed rural Nepalese tend to complain of numbness and tingling (Kohrt et al., 2005). One of the few cultural variations in the mood disorders that has received sustained research attention from multiple research teams over several decades centers on “Chinese somatization”—​the tendency, relative to Western norms, to de-​emphasize psychological symptoms of depression in favor of somatic symptoms (Ryder & Chentsova-​ Dutton, 2012). The first studies on this topic were published in the early 1980s and contrasted low rates of depression with high rates of neurasthenia. In a now-​classic study combining anthropological and psychiatric methods, Kleinman (1982) studied 100 consecutive neurasthenia patients and found that most of them could be diagnosed with a depressive disorder based on a structured interview. Nonetheless, he noted that the symptoms of many of these patients differed from a typical American presentation; chief presenting complaints included headaches (90% of cases), insomnia (78%), and various pains (49%), whereas depressed mood was not often a primary concern (9%). Although many papers in subsequent years would attempt to explain the Chinese tendency to emphasize somatic symptoms, to our knowledge, the first direct comparisons of Chinese and Western samples did not take place until almost two decades later. Several studies were conducted during this time to support Chinese somatization. They tended, however, to interpret Chinese findings in light of the standard Western clinical picture of depression as predominantly psychological (Ryder & Chentsova-​ Dutton, 2012). This bias became increasingly problematic in light of growing evidence that somatic symptoms are ubiquitous in depression, including in Western cultural contexts (Isaac, Janca, & Orley, 1996). An international multisite study confirmed that somatic symptoms are indeed found worldwide; at Western sites, predominantly somatic presentations accounted for between 45% (Paris, France) and 95% (Ankara, Turkey) of patients meeting criteria 76

for MDD, with a rate of 87% in Shanghai, China (Simon, von Korff, Piccinelli, Fullerton, & Ormel, 1999). The authors of this study argued that cross-​ site variation was best explained by the extent to which patients at each site had the opportunity to establish a personal relationship with their clinician, rather than by the cultural context per se. Yen, Robins, and Lin (2000) reported that Chinese patients seeking treatment at counseling centers and clinics emphasized somatic symptoms relative to Chinese students, but found no differences when comparing Chinese students with American students. These authors concluded that a somatic symptom emphasis might be attributable to the “sick role” played by Chinese patients. The story was different when clinical samples were directly compared cross-​ nationally on a symptom-​by-​symptom basis. Somatic chief complaints were much more common in depressed Malaysian Chinese outpatients compared with depressed Euro-​Australian outpatients. A self-​report measure also showed a greater emphasis on somatic symptoms in the Malaysian Chinese sample, along with an even more striking emphasis on psychological symptoms in the Euro-​ Australian sample (Parker, Cheah, & Roy, 2001). A  follow-​up study with Chinese-​ Australians in a primary care setting found that symptom presentation increasingly matched Euro-​Australian norms over time, consistent with the view that these patterns are attributable to the specific cultural context (Parker, Chan, Tully, & Eisenbruch, 2005). Ryder and colleagues (2008) replicated these findings in Chinese and Euro-​Canadian depressed outpatients using clinical and structured interviews along with questionnaires. Again, group differences were particularly striking for psychological symptoms. Findings from a small set of studies suggest there may be cultural variations in the clinical presentation of BD as well. Some of these studies evaluate the degree to which BD emphasizes mania versus depression. Unipolar mania with no depressive episodes has been observed both among the Chinese (Lee, 2001) and the Yoruba in Nigeria (Makanjuola, 1985). Similarly, BD patients of African origin were more likely than white Britons to show exclusively manic presentations (Kirov & Murray, 1999). In a study of BD patients in Israel, a predominance of manic episodes over depressive episodes was observed, in contrast to the pattern commonly observed in European patients. As with epidemiological findings, differences identified in particular countries are not necessarily due to culture as

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such: the authors propose that their Israeli findings may be due to the influence of temperature and exposure to sunshine (Osher, Yaroslavsky, el-​Rom, & Belmaker, 2000). There is also evidence of variability in mania symptoms. Among the Amish, high levels of persecutory delusions and grandiose themes, particularly with religious overtones, were observed in an interview-​based study (Egeland, Hostetter, & Eshleman, 1983). A  low occurrence of flight of ideas and a relatively high occurrence of persecutory and self-​blaming delusions were found among manic patients in eastern India (Sethi & Khanna, 1993). Afro-​Caribbeans were more likely to have had mood-​incongruent delusions and lower rates of suicidality compared to white Britons (Kirov & Murray, 1999). Unfortunately, most of these studies failed to test potential explanations for why these group differences were observed. In summary, there are clear indications of variability in clinical presentations in different cultural contexts. However, there is little empirical evidence pertaining to the reasons for these variations. Our consideration of the research literature on the cultural shaping of mood disorders has now brought us to the point where a deeper integration is needed. It is all too easy to present a set of disconnected findings from a range of cultural contexts without saying much about culture and how it actually shapes mood disorders. We thus turn now to a brief consideration of “culture,” and its deep interconnectedness with mind and brain, before considering some potential research directions that could emerge from this perspective.

Where Is “Culture” in Cultural Studies of Mood Disorders?

Although we are influenced by several disciplines concerned with the link between culture and mind, we emphasize a cultural psychology approach. Drawing from anthropology, cultural psychology has increasingly adopted a distinction between “culture” and “cultural group.” We rely on provisional cultural groups because they facilitate research design and communication, not because they have some kind of fixed essence. Far from fixed, culture is fluid, partial, hybrid, and contested. Work on distributed cognition demonstrates that cultural meanings do not have to be accessible to everyone equally, or at all (Sperber & Hirschfeld, 2004). Individual group members may fully or partially adhere to, flexibly adapt, or fully reject a given culturally normative practice. Culture cannot be reduced to mind, nor mind to culture—​rather, they

exist in a dynamic relationship of mutual constitution (Shweder, 1990). Similarly, we must resist a growing tendency in psychology and psychiatry to view mind and culture as reducible to the brain, as there are limits to the explanatory power of theories that invoke only brain processes. Recent developments in cognitive science characterize the mind as embedded in the local social world, and even the physical environment (Hutchins, 2011). In keeping with contemporary cultural psychology, we therefore propose that the brain is an integral part of any holistic systems view of human psychology (Kitayama & Uskul, 2011). The brain is vital to our perspective, not because it is a fixed entity from which all causal arrows proceed, but precisely because it is evolutionarily adapted and environmentally responsive, flexible and also constrained, all at once. Mutual constitution must be extended to include the brain, but not at the expense of the mind (Ryder & Chentsova-​Dutton, 2015).

The Mutual Constitution of Culture, Mind, and Brain

Treating culture-​mind-​brain as a single, multilevel system has implications that go beyond the traditional tripartite division provided by the biopsychosocial model. To begin with, we cannot easily compartmentalize even specific claims about a given disorder to a single level, and we must avoid the easy reduction of mood disturbance to the “lowest” level. Instead, events cascade through culture-​mind-​brain in all directions. Rapid socioeconomic change can lead to job loss and geographical dislocation, which in turn can stress family systems, making people feel miserable and influencing their cortisol levels—​ which itself has further consequences, for brain functioning, subjective experience, family dynamics, and so on. In previous work, we have proposed that one way of simplifying matters, while still attending to all levels of culture-​mind-​brain, is to adopt the concept of cultural scripts (Ryder & Chentsova-​Dutton, 2015). Normative cultural scripts can be understood as a set of interpretative guides that provide the backdrop against which symptoms are experienced. For example, depressed European Americans are less emotionally reactive—​and depressed Asian Americans are more emotionally reactive—​ than their non-​ depressed counterparts (Chentsova-​ Dutton et al., 2007). In one sense, these are opposing findings; in another, both findings show that depression is associated with emotional reactivity Ryder, Zhao, Chentsova-Dut ton

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that differs from relevant cultural norms. But this finding raises an important question: different with respect to which norms?

The Emergence of Emotional Symptoms in Culture-​Mind-​Brain

Certain experiences deviate sufficiently from local cultural norms that they are seen as abnormal, but nonetheless there are consensual understandings of how these experiences should be construed. Moreover, not only do these deviant cultural scripts help the sufferer make at least partial sense of his or her suffering, there is emerging evidence that they guide people to attend to particular experiences, and may even contribute to their emergence as problematic symptoms rather than transitory events. For example, a person concerned about a relapse into depression may scan their thoughts for self-​doubt, making these thoughts more likely to occur. Meanwhile, all kinds of other thoughts, emotions, sensations, and other potentially symptomatizable experiences fade into the background inasmuch as they do not fit available interpretive lenses (Kirmayer & Sartorius, 2007; Ryder & Chentsova-​Dutton, 2015). The attention-​directing effects of these scripts do not cease with the emergence of a symptom or set of symptoms. Rather, identification of a symptom can elicit further interpretations, which can trigger emotional responses, which themselves are accompanied by a set of potential somatic, cognitive, and behavioral consequences. Pathology emerges as the consequence of looping effects where the response to a particular experience further exacerbates it (Kirmayer & Sartorius, 2007). These short-​term loops are joined by longer-​term loops, which can serve to maintain and exacerbate the pathology. Indeed, looping may be central to why transient symptoms develop into more chronic syndromes (Ryder & Chentsova-​ Dutton, 2015). Symptoms that frequently get pulled into these kinds of chronic loops within a given cultural context are likely to be named, and identified as both important and problematic within that context—​and in Western contexts, perhaps granted status as a psychiatric category.

Rethinking Research on Mood Disorders

If we take the view that mood disturbances emerge and are maintained at least in part by looping effects spanning culture, mind, and brain, there are some implications that might change the way we do research. At a minimum, we hope these changes 78

will include a thoroughgoing engagement with the mechanisms underpinning cultural variation, with a move away from simply cataloguing and speculating on group differences. We thus conclude with a brief look at two promising research directions that could help push the field forward—​integrative research on culture-​mind-​brain and the psychological study of historical change. The premise that culture-​mind-​brain constitutes a single multilevel system can help inform recent work on the biological and cultural co-​construction of mood disorders. For example, vulnerability to depression is associated with sensitivity to environmental stressors, which in Western cultural contexts is associated with variations in one of the serotonin transporter genes (Caspi, Hariri, Holmes, Uher, & Moffitt, 2010). From a global perspective, however, populations with higher rates of this genetic sensitivity actually show lower rates of depression. Chiao and Blizinsky (2009) present evidence that people from ethnic groups with a higher likelihood of environmental sensitivity tend to inhabit cultural contexts that foster collective values, which may protect people in these groups from serious distress. In short, concern for the cultural should not be opposed to the many exciting developments in clinical neuroscience. Researchers should at least be aware of relevant research targeting all three levels; moreover, we suspect that truly transformative work will be highly integrative. For example, Kim and colleagues (2010) have demonstrated that engagement in emotional support-​seeking is best predicted by interactive effects between Korean and Euro-​American group membership (culture), subjective distress (mind), and oxytocin receptor polymorphism (impact on brain). Immordino-​ Yang, Yang, and Damasio (2014) present evidence that cultural group, specifically Chinese or Euro-​ American, is associated with the subjective intensity of emotional experience but not with cardiac reactivity. Moreover, intensity is associated with different regions of the anterior insula in the two groups, a finding with implications for the study of culture and somatic symptoms. Some recent work is also beginning to show the relevance of such a multilevel approach to bipolar disorder. Hechtman and colleagues (2013) draw on the emerging field of cultural neuroscience to present a transdiagnostic approach to positive emotion regulation, with implications for the study of manic and depressive states. They outline a research agenda for this work that involves evidence from five

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sources:  cultural context, behavior, neuroimaging, genetic polymorphisms, and psychophysiology. The result is both a framework through which one can understand the wide range of findings across levels of analysis pertaining to positive emotion regulation, and an agenda for future integrative research. An important consequence of this kind of complex, multilevel perspective is that it forces researchers to consider the possibility that cultural-​ ­ historical change might shape psychological phenomena in important ways. We began this chapter with a brief historical overview of disordered mood, emphasizing Western and Chinese perspectives. One straightforward way of reading such histories would be to see them as an ordered progression towards a better understanding of depression and bipolar disorder. There is some truth to this view: contemporary neuroscience surely has an advantage, both ontologically and pragmatically, over the classical Greek humoral theory. Yet historical shifts in the social meaning of these disorders, and the symptoms that are emphasized in particular eras, raise intriguing questions about whether the mood disorders themselves have changed over time (Shorter, 1992). There is evidence to suggest that rates of depression have increased in the United States (Hidaka, 2012), although it is difficult to disentangle shifts in diagnostic practices, how depression is discussed, and actual rates of serious distress (Murphy, Laird, Monson, Sobol, & Leighton, 2000). From 1991–​ 1992 to 2001–​ 2002, the prevalence of MDD among U.S.  adults increased from 3.3% to 7.1% (Compton, Conway, Stinson, & Grant, 2006). Similar shifts may be underway in China, affecting both depression rates and symptom presentation. In 1993, a mental health survey undertaken in seven regions of China reported surprising point-​prevalence estimates of 0.05% for any affective disorder (Zhang, Shen, & Li, 1998). A recent meta-​analysis based on 17 studies from 2001 to 2010 estimated a point prevalence rate of 1.6% (Gu et al., 2013). Similarly, the 0.1% rate of BD (Shen et  al., 2006), discussed earlier, might be smaller than rates in several other countries, but it is considerably higher than the rates of 0.003% to 0.009% reported between 1958 and 1979 (Lin, Kleinman, & Lin, 1981), and at least somewhat higher than the rates of 0.037% to 0.089% reported in the 1980s (Cheung, 1991). Given emerging evidence of increasing individualism and emotional expressivity in China as well

(e.g., Cai, Kwan, & Sedikides, 2012), we may be observing mental health consequences of striking—​ and rapid—​changes in Chinese society. Another possibility is a shift in willingness to acknowledge serious distress coupled with a shift in presentation towards the psychological symptoms emphasized by Western research tools and training models. These speculations, however, must be tempered by acknowledgment that methodological issues plague comparisons of studies conducted at different times (Guo, Tsang, Li, & Lee, 2011). Future research in this area should move beyond observation of base rate differences to studies designed to evaluate temporal shifts and unpack underlying cultural-​ historical mechanisms.

Concluding Remarks

There is a growing research literature on the cultural shaping of depression, accompanied by an increasing number of studies that move beyond description to explanation. Among the latter, studies conducted in East Asian, and especially Chinese, contexts tend to predominate. Increased attention to other cultural contexts would enhance the literature. As for the cultural shaping of BD, considerably fewer studies have been conducted, but there has been an increasing attention given in recent years to the potential role of the sociocultural environment. Unfortunately, much of this literature is limited by the uncritical adoption of Western-​derived diagnostic criteria, and by the tendency to catalogue group differences rather than unpack the mechanisms and processes of cultural variation. We propose that the best way to advance this work in the future is for researchers interested in culture–​mind links to engage directly with researchers focused on mind–​ brain links, in order to develop a truly integrative science of mood disorders.

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CH A PT E R

8

Uncomplicated Depression as Normal Sadness: Rethinking the Boundary Between Normal and Disordered Depression

Jerome C. Wakefield,  Allan V. Horwitz, and Lorenzo Lorenzo-​Luaces

Abstract About half of all individuals meet the criteria for DSM-​defined major depressive disorder (MDD) by the age of 30. These and other considerations suggest that MDD criteria are too inclusive and apply to individuals who are not ill but are experiencing normal sadness. This chapter reviews a research program that attempts to address this issue by examining “uncomplicated depression,” a subcategory of MDD that is hypothesized to consist of false positive diagnoses in which normal sadness is misdiagnosed as MDD. Data on uncomplicated depression suggest that many individuals who currently meet the DSM criteria for MDD are at no greater risk for subsequent depressive episodes, attempting suicide, or development of generalized anxiety disorder than members of the general population. These data suggest that uncomplicated depression is normal sadness, not major depression, and should not be diagnosed as disordered. They thus indicate that current DSM criteria for MDD are overly inclusive. Key Words:  depression, sadness, diagnosis, melancholia, DSM-​5, grief, bereavement, uncomplicated depression, harmful dysfunction

Major depressive disorder (MDD) is the condition most frequently treated by mental health professionals (Mojtabai & Olfson, 2008) and the second leading cause of disability among the world’s adults (World Health Organization [WHO], 2001). In addition, longitudinal studies of community populations suggest that around half of the population will experience at least one episode of this disorder by the age of 30 (Moffitt et al., 2010; Rohde, Lewinsohn, Klein, Seeley, & Gau, 2012). In this chapter, we propose that the extraordinarily high frequency of MDD results from the failure of the current psychiatric criteria to distinguish genuine cases of depressive disorder from normal sadness. The current definition of MDD in the fifth edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-​5; APA, 2013) requires the presence for a

minimum duration of two weeks of symptoms from at least five out of nine symptoms group. These are: depressed mood or sadness, diminished interest or pleasure in usual activities, sleep difficulties, changes in weight or eating, psychomotor retardation or agitation, fatigue, feelings of worthlessness or guilt, diminished ability to concentrate, and thoughts about death or suicidal ideation. These symptom-​ based criteria for MDD were originally formulated to distinguish depression from other medical disorders among clearly ill hospitalized populations for research purposes (Horwitz, Wakefield, & Lorenzo-​ Luaces, 2016; Kendler, Muñoz, & Murphy, 2014; Wakefield et al., 2010) and have never been adequately validated to distinguish normal from disordered sadness. Because an extremely heterogeneous range of conditions, from mild one-​episode cases to chronic or recurrent severe episodes, can meet these criteria (Lorenzo-​Luaces, 2015; Monroe & 83

 

Harkness, 2011, 2012; Zeiss & Lewinsohn, 2000), the current DSM-​defined diagnostic criteria may encompass many “false positive” misdiagnoses of normal sadness that result in inflated prevalence rates (Friedman, 2012; Parker, 2007). Establishing a valid diagnostic boundary separating MDD from normal sadness is challenging because normal reactions to stress exhibit many of the same symptoms as depressive disorders (Horwitz & Wakefield, 2007). Crystallizing the need for a scientific approach to this question, Maj (2011) challenged researchers to undertake the difficult task of answering the question “When does depression become a mental disorder?” In this chapter, we review a research program that attempts to address this question by examining “uncomplicated depression,” a proposed subcategory of DSM-​ defined MDD that probably captures a “false positives” subgroup that is best understood as normal sadness, not depressive disorder. The publication of DSM-​5 provides an additional reason for investigating the threshold for MDD. DSM-​5 added a note to the MDD criteria set that explicitly recognizes that some conditions satisfying the symptom criteria are in fact not depressive disorders but normal and understandable reactions to stressors: Responses to a significant loss (e.g., bereavement, financial ruin, losses from a natural disaster, a serious medical illness or disability) may include the feelings of intense sadness, rumination about the loss, insomnia, poor appetite, and weight loss noted in Criterion A, which may resemble a depressive episode. Although such symptoms may be understandable or considered appropriate to the loss, the presence of a major depressive episode in addition to the normal response to a significant loss should also be carefully considered. This decision inevitably requires the exercise of clinical judgement based on the individual’s history and the cultural norms for the expression of distress in the context of loss. (APA, 2013, p. 151)

This note leaves decisions about whether a loss-​ related condition that meets the criteria for MDD is in fact disordered or not disordered to each clinician. Given that the vast majority of major depressive episodes occur after a stressor, the lack of symptom-​based criteria for making this distinction throws the diagnosis of one of the DSM’s central categories into doubt, undermining the DSM’s primary rationale of providing reliable operationalized diagnostic criteria for research as well as clinical 84

diagnosis (Maj, 2010). Further understanding of this boundary issue is thus urgently needed.

Origins of Uncomplicated Depression

In an influential early study, Clayton, Desmarais, and Winokur (1968) conducted a longitudinal investigation of normal grief in a nonclinical population. They empirically established what physicians had observed since antiquity: grief after the death of a loved one routinely includes transient occurrences of many of the same symptoms that occur during pathological depression. They identified the depressive symptoms common in their sample of bereaved individuals and distinguished them from the symptoms that occurred frequently in a clearly disordered hospitalized sample with depressive disorder (Clayton, Herjanic, Murphy, & Woodruff, 1974). For example, in Clayton et al.’s normal sample, in the first weeks post-​loss, 87% of bereaved subjects reported depressed mood; 85%, sleep disturbance; 79%, crying; and about half reported diminished interest in usual activities like watching TV (42%), difficulty concentrating (47%), and lessened appetite (49%). Such episodes remitted on their own and did not cause the kind of marked impairment that frequently leads to psychiatric consultation and care (Clayton et  al., 1968; Clayton, Halikas, & Maurice, 1971). In contrast, psychotic ideation, self-​condemnation, suicidal ideation, and psychomotor retardation were rare in these cases of normal grief but more common in pathological cases (Clayton et  al., 1974). A  substantial percentage approaching half of the normal grief cases satisfied criteria for a DSM-​style symptom-​based definition of MDD at some point within the first year after the loss, even though presumably they generally were not disordered (Bornstein, Clayton, Halikas, Maurice, & Robins, 1973; Clayton et al., 1971). The architects of the DSM-​III responded to the work of Clayton and colleagues by integrating into the MDD criteria a “bereavement exclusion” (BE). This exclusion recognized that the symptoms of MDD overlap with those of grief, so that MDD is not diagnosed in cases of uncomplicated bereavement that are not prolonged or especially severe but would otherwise meet the MDD criteria (APA, 1980). However, the DSM-​III architects also appreciated another feature of the contextual tradition:  that bereavement can trigger a genuinely pathological depressive reaction (Parkes, 1964). In other words, bereavement can be “complicated” by a depressive disorder when it endures for an extended period of time (operationalized in DSM-​IV [APA,  1994] as

Uncompli cated Depression as Normal Sadness

 

two months) or when it features at least one especially serious symptom. Until its elimination from DSM-​5, the BE was the sole remnant within the diagnostic criteria of the long contextual tradition of diagnosing melancholic illness that existed both before the modern DSMs and in the DSMs prior to DSM-​5. Successive DSM revisions never considered extending the BE to other stressors, and the DSM-​5 eliminated the BE altogether. Wakefield and colleagues undertook a series of empirical investigations to test, not only whether bereavement constitutes a justifiable exception to the DSM’s symptom-​ based definition of MDD, but also whether a broader range of loss events (e.g., separation and divorce, unemployment, diagnosis of a life-​threatening illness) should also represent exceptions to the diagnosis. Based on Wakefield’s harmful dysfunction (HD) analysis of the concept of mental disorder (Wakefield, 1992a, 1992b, 2007) as applied to depression, they generalized the BE to other stressors to create the concept of uncomplicated depression. To distinguish uncomplicated (presumptively non-​ disordered) depression from complicated (presumptively disordered) depression, they relied on the same symptom criteria as the BE. For a DSM-​defined depressive episode to be considered uncomplicated, it had to include only general-​ distress type symptoms. It could not include any of the following six pathosuggestive symptoms or features:  (1)  psychotic ideation; (2)  psychomotor retardation; (3) morbid preoccupation with worthlessness; (4) suicidal ideation; (5) marked functional impairment; or (6) prolonged duration, operationalized as the depressive episode lasting longer than two months in DSM-​IV. (Although earlier DSMs had specified that the depression must start within a few months of the loss to be considered loss-​ related, there was no such specification in DSM-​IV, leaving the consideration of whether depression is bereavement-​ related to clinicians’ judgement). If an episode had any one or more of these pathosuggestive features, then it was considered complicated depression and was assumed to be disordered. This distinction between uncomplicated and complicated conditions is consistent with the history of medical thinking about depression (Horwitz & Wakefield, 2007) as well as with the thinking of lay individuals and mental health professionals who tend to consider sadness and moderate feelings of depression after losses or major stressors to be normal responses (Holzinger, Matschinger, Schomerus, Carta, & Angermeyer, 2011; Kim, Paulus, Nguyen, & Gonzalez, 2012). Note that the uncomplicated/​

complicated distinction is not the same as the reactive/​endogenous distinction that distinguishes conditions that are caused by stressors from those that have no external causes. The reactive/​endogenous distinction was not meant as an account of normal versus disordered depression, because many reactive depressions can be true disorders. Instead, the necessary distinction must separate normal from pathological reactive depressions.

Homogeneity of Uncomplicated Depression Across Stressors

An initial question in exploring uncomplicated depression was whether the uncomplicated/​complicated distinction is applicable and looks somewhat similar across different stressors or whether grief is a unique stressor. Wakefield, Schmitz, First, and Horwitz (2007) used data from the National Comorbidity Study (NCS; Kessler et al., 1994) to compare uncomplicated versus complicated MDD episodes after death of a loved one versus after other reported events that triggered depressive episodes. Consistent with their hypothesis, the bereavement-​ and other-​ triggered groups were comparable in terms of demographics, clinical history, percentage of individuals qualifying as “uncomplicated,” and symptom profiles. Most importantly, bereavement-​ triggered and other-​triggered depressions that were classified as uncomplicated were uniformly low in pathology-​ indicating validators and statistically indistinguishable from each other on eight out of the nine pathology validators. The only exception was a modest but statistically significant difference in those reporting that depression “interfered a lot” with their life: more individuals in the other loss–​ triggered group than in the bereavement-​triggered group (12.4% vs. 4.6%) reported this. In contrast, individuals with complicated-​loss responses to either kind of stressor were much higher than uncomplicated cases of either kind in terms of pathology validators, including: number of symptoms, likelihood of meeting criteria for melancholic depression, rates of suicide attempts, duration of symptoms, interference with life, prior episodes, and rates of mental health service utilization. These results supported the hypothesis of a homogeneous uncomplicated-​ depression category across triggering stressors that has a substantially more benign clinical profile than standard MDD does. Wakefield et al. (2007) interpreted this result as supporting the conclusion that uncomplicated depression in general is a non-​disordered response to loss and therefore that

Wakefield, Horwitz, Lorenzo-Luaces

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the BE should be expanded and applied to other stressors. A broadly similar study using a different sample (Kendler, Myers, & Zisook, 2008) also failed to find any evidence that bereavement-​triggered depression meaningfully differed from depression triggered by other stressors. However, these authors interpreted their finding to mean that the BE should be eliminated altogether rather than expanded. They reasoned that, because uncomplicated reactions to stressors other than grief are currently classified as disorders, there is no reason to single out bereavement as exceptional. Wakefield et  al. (2007) and Kendler et al. agreed that uncomplicated depressive reactions to death of a loved one and to other losses should be similarly classified. They differed, however, over whether uncomplicated depressive reactions should generally be considered disordered or non-​disordered. Wakefield and colleagues went on to pursue a research program to address this broader question about uncomplicated depression.

Concurrent Validity

Wakefield et al.’s analyses (2007) suggested that uncomplicated depressions are less pathological than complicated episodes are. This led the authors to argue, first, that the BE should be extended to other stressors and, second, that all uncomplicated depressions are non-​ disorders. However, critics pointed out that these findings were limited by the fact that many of the validators used to test the differences between uncomplicated and complicated depressions were confounded by the defining features of the uncomplicated/​complicated distinction itself (Kendler & Zisook, 2009). For example, by definition, NCS “uncomplicated” episodes required brief (10,000 persons). A statistical price must be paid for testing this large number of SNPs, so a statistical level of p = ~5 × 10−8 is the equivalent of p = 0.05 when searching the entire genome for association. The stringent statistical correction for multiple-​testing no doubt masks true signals from genes that confer only very modest risk of disease, although in theory this limitation could be overcome by larger sample sizes. The sample size required to achieve adequate power for expected effects sizes (odds ratios