Emotion, Aging, and Health [1 ed.] 1433821621, 9781433821622

Table of contents :
Contents
Contributors
Foreword
Acknowledgments
Introduction
Part I Neural and Cognitive Mechanisms
Chapter 1 Default Mode Network and Later-Life Emotion Regulation: Linking Functional Connectivity Patterns and Emotional Outcomes
Chapter 2 Age Differences in Use and Effectiveness of Positivity in Emotion Regulation: The Sample Case of Attention
Part II Regulatory Frameworks
Chapter 3 Resources for Emotion Regulation in Older Age: Linking Cognitive Resources With Cognitive Reappraisal
Chapter 4 Regulatory Flexibility and Its Role in Adaptation to Aversive Events Throughout the Lifespan
Part III
Motivational Perspectives
Chapter 5 Happy to Be Unhappy? Pro- and Contrahedonic Motivations From Adolescence to Old Age
Chapter 6 Emotional Aging in Different Cultures: Implications of Affect Valuation Theory
Part IV Health Implications
Chapter 7 Bridging the Dynamic Aspects of Personality and Emotion That Influence Health
Chapter 8 Positive Psychological Functioning: An Enduring Asset for Healthy Aging
Chapter 9 Emotional Experience and Health: What We Know, and Where to Go From Here
Part V Interventions
Chapter 10 The Humanization of Social Relations: Nourishment for Resilience in Midlife
Index
About the Editors

Citation preview

Emotion, Aging, and Health

BRONFENBRENNER SERIES ON THE ECOLOGY OF HUMAN DEVELOPMENT Chaos and Its Influence on Children’s Development: An Ecological Perspective Edited by Gary W. Evans and Theodore D. Wachs Research for the Public Good: Applying the Methods of Translational Research to Improve Human Health and Well-Being Edited by Elaine Wethington and Rachel E. Dunifon The Neuroscience of Risky Decision Making Edited by Valerie F. Reyna and Vivian Zayas Emotion, Aging, and Health Edited by Anthony D. Ong and Corinna E. Löckenhoff

Emotion, Aging, and Health Edited by

Anthony D. Ong and Corinna E. Löckenhoff

American Psychological Association • Washington, DC

Copyright © 2016 by the American Psychological Association. All rights reserved. Except as permitted under the United States Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, including, but not limited to, the process of scanning and digitization, or stored in a database or retrieval system, without the prior written permission of the publisher. Published by American Psychological Association 750 First Street, NE Washington, DC 20002 www.apa.org

To order APA Order Department P.O. Box 92984 Washington, DC 20090-2984 Tel: (800) 374-2721; Direct: (202) 336-5510 Fax: (202) 336-5502; TDD/TTY: (202) 336-6123 Online: www.apa.org/pubs/books E-mail: [email protected]

In the U.K., Europe, Africa, and the Middle East, copies may be ordered from American Psychological Association 3 Henrietta Street Covent Garden, London WC2E 8LU England Typeset in Goudy by Circle Graphics, Inc., Columbia, MD Printer: Bang Printing, Brainerd, MN Cover Designer: Mercury Publishing Services, Inc., Rockville, MD The opinions and statements published are the responsibility of the authors, and such opinions and statements do not necessarily represent the policies of the American Psychological Association. Library of Congress Cataloging-in-Publication Data Emotion, aging, and health / Anthony D. Ong and Corinna E. Löckenhoff. pages cm. — (Bronfenbrenner series on the ecology of human development) Includes bibliographical references and index. ISBN 978-1-4338-2162-2 — ISBN 1-4338-2162-1 1. Emotions in old age. 2. Aging— Psychological aspects. 3. Older people—Mental health. 4. Developmental psychology. I. Ong, Anthony D., editor. II. Löckenhoff, Corinna E., editor. BF724.85.E56E46 2015 155.67'124—dc23 2015033114 British Library Cataloguing-in-Publication Data A CIP record is available from the British Library. Printed in the United States of America First Edition http://dx.doi.org/10.1037/14857-000

This series is dedicated to the personal memories and lasting theoretical insights of our friend, colleague, and mentor, Urie Bronfenbrenner. His thinking about human development has profoundly influenced so many students and colleagues in multiple areas of enquiry. We hope this series will provide another vehicle through which Urie’s ideas on the bioecology of human development can continue to flourish.

CONTENTS

Contributors.................................................................................................   ix Foreword......................................................................................................   xi Karl Pillemer Acknowledgments......................................................................................   xv Introduction.................................................................................................. 3 Anthony D. Ong and Corinna E. Löckenhoff I.  Neural and Cognitive Mechanisms........................................................ 7 Chapter 1. Default Mode Network and Later-Life Emotion Regulation: Linking Functional Connectivity Patterns and Emotional Outcomes............. 9 Bruna Martins and Mara Mather Chapter 2. Age Differences in Use and Effectiveness of Positivity in Emotion Regulation: The Sample Case of Attention....................................... 31 Kimberly M. Livingstone and Derek M. Isaacowitz vii

II.  Regulatory Frameworks...................................................................... 49 Chapter 3. Resources for Emotion Regulation in Older Age: Linking Cognitive Resources With Cognitive Reappraisal............................................ 51 Heather L. Urry Chapter 4. Regulatory Flexibility and Its Role in Adaptation to Aversive Events Throughout the Lifespan................. 71 Charles L. Burton and George A. Bonanno III.  Motivational Perspectives.................................................................. 95 Chapter 5. Happy to Be Unhappy? Pro- and Contrahedonic Motivations From Adolescence to Old Age................... 97 Michaela Riediger and Gloria Luong Chapter 6. Emotional Aging in Different Cultures: Implications of Affect Valuation Theory...................... 119 Jeanne L. Tsai and Tamara Sims IV.  Health Implications.......................................................................... 145 Chapter 7. Bridging the Dynamic Aspects of Personality and Emotion That Influence Health............................. 147 Emily D. Bastarache and Daniel K. Mroczek Chapter 8. Positive Psychological Functioning: An Enduring Asset for Healthy Aging......................... 163 Laura D. Kubzansky and Julia K. Boehm Chapter 9. Emotional Experience and Health: What We Know, and Where to Go From Here............ 185 Susan T. Charles, Kate A. Leger, and Emily J. Urban V. Interventions...................................................................................... 205 Chapter 10. The Humanization of Social Relations: Nourishment for Resilience in Midlife......................... 207 Alex J. Zautra, Frank J. Infurna, Eva K. Zautra, Carmen Écija Gallardo, and Lilian Velasco Index......................................................................................................... 229 About the Editors..................................................................................... 237 viii       contents

CONTRIBUTORS

Emily D. Bastarache, BS, Department of Psychology, Weinberg College of Arts and Sciences, Northwestern University, Evanston, IL Julia K. Boehm, PhD, Department of Psychology, Chapman University, Orange, CA George A. Bonanno, PhD, Department of Counseling and Clinical Psychology, Teachers College, Columbia University, New York, NY Charles L. Burton, MS, MPhil, Department of Counseling and Clinical Psychology, Teachers College, Columbia University, New York, NY Susan T. Charles, PhD, Department of Psychology and Social Behavior, University of California, Irvine Carmen Écija Gallardo, PhD, Department of Psychology, Universidad Rey Juan Carlos, Madrid, Spain Frank J. Infurna, PhD, Department of Psychology, Arizona State University, Tempe Derek M. Isaacowitz, PhD, Department of Psychology, Northeastern University, Boston, MA Laura D. Kubzansky, PhD, MPH, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA

ix

Kate A. Leger, BS, Department of Psychology and Social Behavior, University of California, Irvine Kimberly M. Livingstone, PhD, Department of Psychology, Northeastern University, Boston, MA Corinna E. Löckenhoff, PhD, Department of Human Development, College of Human Ecology, Cornell University, Ithaca, NY Gloria Luong, PhD, Department of Human Development and Family Studies, Colorado State University, Fort Collins Bruna Martins, MA, Department of Psychology, University of Southern California, Los Angeles Mara Mather, PhD, Davis School of Gerontology and Department of Psychology, University of Southern California, Los Angeles Daniel K. Mroczek, PhD, Department of Psychology, Weinberg College of Arts and Sciences, Northwestern University, Evanston, IL, and Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL Anthony D. Ong, PhD, Department of Human Development, College of Human Ecology, Cornell University, Ithaca, NY Karl Pillemer, PhD, Department of Human Development, College of Human Ecology, Cornell University, Ithaca, NY Michaela Riediger, PhD, Department of Education and Psychology, Free University, and Max Planck Institute for Human Development, Berlin, Germany Tamara Sims, PhD, Department of Psychology, Stanford University, Stanford, CA Jeanne L. Tsai, PhD, Department of Psychology, Stanford University, Stanford, CA Emily J. Urban, BS, Department of Psychology and Social Behavior, University of California, Irvine Heather L. Urry, PhD, Department of Psychology, Tufts University, Medford, MA Lilian Velasco, PhD, Department of Psychology, Universidad Rey Juan Carlos, Madrid, Spain Alex J. Zautra, PhD, Department of Psychology, Arizona State University, Tempe Eva K. Zautra, MBA, Social Intelligence Institute, Phoenix, AZ

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FOREWORD Karl Pillemer

For at least 2000 years, human beings have considered the following question: What promotes health and happiness in old age? Over the centuries, philosophers, scientists, and politicians have discussed and debated the conditions needed to improve the prospects of people in the last third of life. But never has this topic held the urgency that it does today. When I began studying gerontology 35 years ago, population aging was presented as a looming specter that would haunt future times. Those times have arrived (or will shortly), as the world’s population over the age of 65 has doubled since 1980 and for the first time individuals in that age category outnumber children under the age of 5. We are thus in the midst of one of the most profound demographic shifts in human history. This phenomenon is, of course, an extraordinary achievement, testifying to improved living conditions and medical advances over the past century. But it also raises significant challenges for both individuals and societies, given that longevity often brings with it a burden of chronic disease and greatly increased risk of cognitive impairment. For humanitarian and for economic reasons, promoting health, delaying disability, and increasing meaningful social roles among older people are high priorities around

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the globe. The evidence base on which to develop both policies and inter­ ventions, however, is still underdeveloped. For this reason, this book is a timely and appropriate fourth volume in the American Psychological Association Bronfenbrenner Series on the Ecology of Human Development. Prior books in the series have dealt with the role of chaos in the lives of developing children, risky decision-making, and the promise of translational research models. Bronfenbrenner’s ecological perspective resonates in all of these volumes, which explore developmental issues not only from an individual perspective, but also in light of cultural, social, and economic factors. The importance of policies and social programs as key components in promoting optimal human development is emphasized throughout this series. The present volume reflects another key element of Bronfenbrenner’s pioneering work: an emphasis on time. Bronfenbrenner’s concept of the chronosystem highlights the importance of both historical events and individual transitions as key influences in development extending into adulthood and later life. Like the previous volumes, this book represents a major advance in our understanding of how to promote optimal human development, this time focusing on physical and psychological well-being in old age. Highlighting the intersections among emotions, health, and aging, the authors contribute to basic knowledge about development and successful adaptation in later life. As Susan T. Charles, Kate A. Leger, and Emily J. Urban put it in Chapter 9: “By understanding the strategies through which older adults capitalize on their limited resources, we can better understand the context of health across adulthood” (p. 198). Further, the chapters move beyond topics of pure scientific interest to inquiry about pathways to interventions that lead to successful aging. It is impossible for a reader to engage with this book and come away unconvinced of the importance of the study of emotion in the field of aging and life course development. The contributions range from efforts to understand the role of age-related neural and cognitive changes in emotion, to the nature and dynamics of emotion regulation, to cultural factors influencing affective experience, to the interaction of social connectedness and emotion. The growing theoretical and methodological sophistication in this field of study is showcased in the chapters, where attention is paid to such critical issues as personality, response to stressful events, and the role of positive emotions in promoting well-being. The powerful effects of various aspects of emotion on health are also demonstrated. It is commonplace to decry a perceived conflict between basic science and applied research. Although the two realms have been more closely aligned in psychology than in some other fields, there is still a considerable

xii       foreword

disconnect. This volume highlights the many ways that scientific discovery and practical use of findings can be brought together to solve human problems. And Urie Bronfenbrenner would be smiling as he read it. As a translational researcher before the name existed, he would embrace the themes of development and plasticity in later life, the importance given to social and cultural factors in understanding emotions, and the commitment to applying these scientific insights to creating an optimal world in which to grow old.

foreword

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ACKNOWLEDGMENTS

This volume, more than most, reflects the energies not of the editors but of the many who were involved in its creation. We are grateful to John Eckenrode, who was the first to graciously listen to our ideas about this book and then urged us to follow through with them. Special thanks go to Christopher Kelaher and Linda Malnasi McCarter at the American Psychological Association and to members of the Bronfenbrenner Steering Committee (Steve Ceci, Gary Evans, Daniel Lichter, Karl Pillemer, Valerie Reyna, and Elaine Wethington) for their patience, tact, and invaluable assistance throughout the editorial process. We owe a great intellectual debt to our teachers—John L. Horn and Laura Carstensen—quintessential developmental psychologists who, long before it was in vogue, combined psychological theory with the rigors of empirical research to ask the kinds of intuitive questions of aging and adult development that would later reveal remarkable foresight. Their commit­ ment to clarity and depth as well as truth and passion has given us the standard toward which we aspire. We are also grateful to the battalion of investigators whose imaginative sweep of ideas have shaped our thinking over the years: Paul Baltes, Lisa Barrett, C. S. Bergeman, Steve Boker, George Bonanno,

xv

Paul T. Costa, Jr., James Gross, Alice Isen, Robert McCrae, John Nesselroade, Karl Pillemer, Carol Ryff, Andrew Steptoe, Bert Uchino, Elaine Wethington, Steve Zarit, and Alex Zautra. The original impetus for this volume occurred during the fourth Biennial Urie Bronfenbrenner Conference Series at Cornell University in Ithaca, New York, on October 3–4, 2013. The event served as a springboard for the present focused volume. We thank Carrie Chalmers for invaluable help in organizing this conference and acknowledge financial support from the Cornell University Institute for the Social Sciences, the Scientific Research Network on Decision Neuroscience and Aging (R24-AG039350), the Cornell University Department of Human Development, The Constance and Carl Ferris Charitable Foundation, and Mrs. Liese Bronfenbrenner. At the institutional level, we are grateful to Cornell University for generously providing the intellectual climate and institutional support needed to undertake and complete this work. Finally, we wish to thank our friends and family whose encouragement made this work possible. Most of all, we thank the authors whose work is featured herein. We have learned much from them. We hope you do as well.

xvi       acknowledgments

Emotion, Aging, and Health

INTRODUCTION ANTHONY D. ONG AND CORINNA E. LöCKENHOFF

The chapters presented herein explore advances in the fields of aging and affective science and their application to promote positive health and well-being in adulthood and later life. A major aim of the volume is to bring together a set of chapters—written by recognized leaders in the field—that describe promising scientific agendas at the intersection of aging, emotion, and health. These agendas are currently creating significant interdisciplinary breakthroughs and are likely to yield major advances over the next several years. Topics include neural and cognitive mechanisms behind age-related shifts in affective experience and processing, emotion regulation strategies that serve to offset age-related declines in mental and physical functioning, the role of culture and motivation in shaping emotional experience across the lifespan, and the factors defining boundary conditions between human illness and human flourishing in old age. More broadly, this volume builds on the commitment of Urie Bronfenbrenner—a founder of Head Start and longtime faculty member in the Department of Human Development at Cornell University—to translate http://dx.doi.org/10.1037/14857-001 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

3

basic social scientific research into programs and policies to improve health and enhance quality of life. The volume editors thus seek to initiate a dialogue between basic and applied researchers—and ultimately with readers—on how to best understand the reciprocal relations between aging and emotion, and how to translate this understanding into interventions to promote mental and physical health across the life span. The volume is particularly timely given recent paradigm shifts in the fields of affective science (e.g., Davidson, Scherer, & Goldsmith, 2003; Lewis, Haviland-Jones, & Barrett, 2010; Panksepp, 2004) and positive aging (e.g., Qualls & Abeles, 2000; Reich, Zautra, & Hall, 2010; Schaie & Willis, 2011). Although much valuable and promising research has already been conducted within each of these fields, communication across fields has been less than optimal. The volume attempts to redress this imbalance by integrating findings from specialized lines of inquiry that use diverse methodologies. It will serve as a scaffold for the planning and implementation of emerging research initiatives. We organized the present book around five unifying themes. Within each theme are chapters that cover methodology and application. However, readers should bear in mind that the themes are interrelated and that individual chapters commonly address more than one theme. 77

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Part I is an overview of the neural and cognitive mechanisms of age-related changes in brain function and emotion–cognition interactions. Part II focuses on regulatory frameworks for evaluating emotional functioning in old age and their applications for understanding flexibility and adaptation to highly aversive life events. Part III concentrates on the role of motivational and cultural factors in age-related differences in affective experience and their implications for mental health and decision-making. Part IV presents approaches for investigating the health implications of positive and negative affective traits in later life. Part V focuses on interventions designed to facilitate positive health and resilience in older adults.

We hope that this volume will be of interest to applied researchers and scholars across disciplinary boundaries within the social and behavioral sciences (anthropology, sociology, psychology, applied philosophy) and across subdisciplinary boundaries within psychology and other fields (clinical, cognitive, developmental, personality, and social psychology, as well as gerontology and geriatrics). The book can work as a stand-alone text for instructors teaching graduate seminars on aging and emotion, and it can serve as a reference for applied and basic researchers interested in a broad 4       ong and löckenhoff

but selective survey of investigators working at the interface of emotion, aging, and health. REFERENCES Davidson, R. J., Scherer, K. R., & Goldsmith, H. (Eds.). (2003). Handbook of affective sciences. London, England: Oxford University Press. Lewis, M., Haviland-Jones, J. M., & Barrett, L. F. (Eds.). (2010). Handbook of emotions. New York, NY: Guilford Press. Panksepp, J. (Ed.). (2004). Affective neuroscience: The foundations of human and animal emotions. New York, NY: Oxford University Press. Qualls, S. H., & Abeles, N. (Eds.). (2000). Psychology and the aging revolution: How we adapt to longer life. Washington, DC: American Psychological Association. Reich, J. W., Zautra, A. J., & Hall, J. S. (Eds.). (2010). Handbook of adult resilience. New York, NY: The Guilford Press. Schaie, K. W., & Willis, S. L. (Eds.). (2011). Handbook of the psychology of aging (7th ed.). London, England: Academic Press.

introduction     

5

I Neural and Cognitive Mechanisms

1 DEFAULT MODE NETWORK AND LATER-LIFE EMOTION REGULATION: LINKING FUNCTIONAL CONNECTIVITY PATTERNS AND EMOTIONAL OUTCOMES BRUNA MARTINS AND MARA MATHER

Aging is marked by cognitive declines across modalities. Sensory processing becomes noisier, memories tougher to access, and complex tasks increasingly difficult to perform accurately (Goh, 2011; Li & Lindenberger, 2002). Lateral areas of the prefrontal cortex (PFC) involved in salience and executive processing lose volume with age (Cabeza, 2002; Fjell et al., 2009; Raz et al., 2005). In addition, older people show difficulty maintaining and manipulating information (Goh, An, & Resnick, 2012; Park & Reuter-Lorenz, 2009) and selectively inhibiting distractions (Lustig, Hasher, & Zacks, 2007) compared with younger adults. However, despite structural declines in lateral brain regions, overall emotional experience tends to be less negative for older than younger adults. Selfreported well-being is lowest in midlife and increases after age 50 (Jeste et al., 2013), and older adults report less negative affect in daily life than do younger people (Stone, Schwartz, Broderick, & Deaton, 2010). Negative affect does We thank Margy Gatz, Brittany Ko, and Jan Florjanczyk for their helpful comments on this manuscript. This work was supported by the National Science Foundation [DGE-0937362] and by the National Institutes on Health [RO1AG025340]. http://dx.doi.org/10.1037/14857-002 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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tend to increase in the last decade of life before the terminal year (Schilling, Wahl, & Wiegering, 2013); however, when physical functioning is accounted for, negative affect is lower in late life than in midlife, even among those over age 85 (Windsor, Burns, & Byles, 2013). In this chapter, we focus on emotion regulation processes in healthy aging. Although we do not discuss physical health and its impact on emotion regulation, we caution that this remains an important area for future consideration. Older adults show improvements relative to younger people in well-being, as well as in outcomes related to the regulation of emotions. Mood disorders indicating emotional dysregulation such as depression (Blazer, 2003; Piazza & Charles, 2006) and anxiety (Fiske, Wetherell, & Gatz, 2009) decrease in prevalence with age (Kessler et al., 2005). Subclinical mood symptoms such as ruminative thinking also tend to decrease across the lifespan (Sütterlin, Paap, Babic, Kübler, & Vögele, 2012). Thus, healthy older adults appear to manage their emotional well-being better than do younger adults. A possible mechanism for this difference may involve changes in emotion regulation brain networks. Successful emotion regulation is associated with activity in lateral executive regions, as well as medial regions in younger adults (Buhle et al., 2014; Frank et al., 2014). While lateral brain structures and functions tend to decline with age, medial brain structures involved in self-related processing remain relatively intact in later life (Fjell et al., 2009; Gutchess, Kensinger, Yoon & Schacter, 2007; Lalanne, Grolleau, & Piolino, 2010). These wellmaintained medial areas of the PFC may help sustain emotion regulation function in late life despite declines in lateral PFC. In this chapter, we discuss the functional connectivity of medial selfrelated brain circuits and suggest how this network connectivity may support emotion regulation in older adults. First, we provide background on emotional outcomes and self-related processing in later life. Next, we introduce the brain circuits contributing to emotion regulation and review age-related changes within these networks. Then we report connectivity changes in a network known as the default mode network (DMN)—a set of medial regions involved in internally directed or self-generated thought (Andrews-Hanna, Smallwood, & Spreng, 2014). We then compare DMN functional connectivity with attention and executive networks in older adults to connectivity in two different populations: (a) people with depression, a disorder marked by increased self-focus and negative functional outcomes; and (b) mindfulness practitioners trained to be aware of self-related processes, who generally show positive functional outcomes. On the basis of this review, we propose a model of how self-related processing and increased connectivity of the DMN with other networks may promote positive emotional outcomes in both healthy aging and mindfulness experts. Throughout the chapter, we graphically describe each component of the model in Figure 1.1, one pathway at a time. 10       martins and mather

Self-Related Meaning Medial DMN

A C1

Emoonal Processing

C2

Amygdala

B1

B2

Situaonal Meaning

A enonal Control

Lateral Execuve Network

Medial Salience Network

Negave

Posive

Increase aenon towards assessing situaonal and self-related meaning

Figure 1.1.  A model of brain network integration in emotion regulation in aging. (A) Default mode network (DMN) is more functionally connected to the amygdala for older adults; (B1) Lateral executive network–amygdala connectivity demonstrates no significant age differences; (B2) Medial salience network–amygdala connectivity is enhanced for older adults compared to younger adults; (C) Older adults and mindfulness experts show increased connectivity between DMN–executive and DMN– salience networks. Integration of situational and self-related processing in emotion regulation may drive positive outcomes in both populations. Note that the C-paths are weakened for depressed individuals.

POSITIVE EMOTION AND SELF-RELATED PROCESSING ARE PRIORITIZED IN LATER LIFE Older adults show a preference to ignore negative and attend to positive information relative to younger adults, indicating a positivity effect (Mather & Carstensen, 2005). For instance, older adults more quickly detected items appearing in the same location as a previously seen positive image than a previously seen negative image, while younger adults did not show this difference by valence (Mather & Carstensen, 2003). Similarly, older adults preferred to default mode network and later-life emotion regulation     

11

look at happy faces and away from angry faces; in contrast, younger adults demonstrated a gaze bias for fear-provoking faces (Isaacowitz, Wadlinger, Goren, & Wilson, 2006). Thus, older adults tend to disengage from negative information. Older adults also appear to regulate their emotions during unavoidable interactions with negative stimuli more than do younger adults. In one study, younger and older adults either naturally viewed disgusting videos of surgical operations or were told to increase or decrease their emotional reactions during the films (Kunzmann, Kupperbusch, & Levenson, 2005). Younger adults showed no difference between the control condition (i.e., natural film viewing) and the increasing emotion condition, whereas older adults showed no difference between the control condition and the decreasing emotion condition. This suggests a tendency for older adults to focus away from negative content and for younger adults to amplify their negative emotions under natural viewing conditions. In another experiment, older and younger adults listened to audiotapes of strangers making offensive comments about them, and older people made fewer and less negative comments regarding the tapes than younger adults (Charles & Carstensen, 2008). Another study found that older adults reported no increase in negative arousal prior to monetary losses, while younger participants did (Nielsen, Knutson, & Carstensen, 2008). These studies suggest that older adults tend to naturally diminish negative affect once it is induced, even without instructions to do so. One explanation for this age-related optimization of positive emotions is that older adults focus more on emotional outcomes and regulation of affect than do younger adults. Socioemotional selectivity theory argues that as perceived lifespan decreases, older adults tend to maximize positive affective experiences in the present moment, which in turn should support psychological and emotional well-being across the lifespan (Carstensen, Isaacowitz, & Charles, 1999; Charles & Carstensen, 2008; Lang & Carstensen, 2002). Greater focus on emotional well-being and maintenance of affect in later life may lead to differences in how new information is processed in relation to one’s personal goals and self-relevance. In one study, older and younger adults were shown negative film clips of injustice situations and asked to either passively view, suppress their emotional reactions, or positively refocus their attention to a pleasant memory unrelated to the video (Phillips, Henry, Hosie, & Milne, 2008). Older adults reported lower levels of negative emotion after utilizing self-relevant distraction rather than an emotional suppression strategy, while younger adults showed no difference between conditions. Thus, it appears that for older adults, using self-relevant positive information as a distraction improves affect more than does suppressing emotions. Older adults show a preserved capacity for processing the self-relevance of information, and thus boost later memory for that information (Gutchess 12       martins and mather

et al., 2007; Leshikar, Park, & Gutchess, 2014; Symons & Johnson, 1997). Older adults engage self-referential medial prefrontal cortical regions (MPFC) more during the encoding of positive information than negative, and this activity is predictive of later memory for the encoded information (Gutchess, Kensinger, & Schacter, 2007; Leclerc & Kensinger, 2008). In contrast, younger adults show greater MPFC activity during encoding of negative stimuli, and better memory for these negative items that are processed in relation to the self. Thus, selfreferent information is not always better remembered but is selectively encoded based on valence. These findings suggest that older adults tend to selectively process positive information more self-referentially, whereas younger adults selectively process negative stimuli in relationship to the self through medial activation. Medial brain structures that process self-relevance decline across the lifespan at a slower rate than lateral central executive regions (Fjell et al., 2009) and may help boost positive associations in memory. We posit that by selectively increasing the self-relevance of positive but not negative emotional situations, older adults can increase well-being (Figure 1.1, Path A). Before discussing the functional connectivity of the self-related circuits, we review how functional connectivity can be used as a method for assessing networks. AGE-RELATED CHANGES IN FUNCTIONAL CONNECTIVITY OF EMOTION REGULATION CIRCUITS Functional Connectivity Methods for Quantifying Network Circuitry While traditional functional magnetic resonance imaging methods identify regions activated in the brain by specific tasks, functional connectivity methods identify synchronization among regions in the brain in their spontaneous fluctuations in activity. Correlated temporal patterns among different regions identify networks (Friston, Frith, Liddle, & Frackowiak, 1993). Different networks associated with different functions, such as visuospatial processing or executive processing, can be identified from patterns of brain activity even while people are at rest (Laird et al., 2011; Mennes et al., 2010; Smith et al., 2009). In this chapter, we focus on three canonical networks in the brain: (a) a medial DMN, which includes regions in MPFC and posterior cingulate cortex and is more active during rest than during cognitive task performance; (b) a lateral executive network with key regions in dorsolateral PFC and posterior parietal cortex, activated during effortful goal-directed working memory tasks; and (c) a primarily medial salience network active in attentional control, including areas in the anterior insula, anterior cingulate cortex, and ventro­ lateral PFC (Fox, Corbetta, Snyder, Vincent, & Raichle, 2006; Greicius, Krasnow, Reiss, & Menon, 2003; Raichle et al., 2001). Throughout the chapter, we aim to default mode network and later-life emotion regulation     

13

investigate the coupling between these three networks, as well as the functional connectivity within each. The anatomical representation of each network is provided in Figure 1.2. In Figure 1.1, we suggest how these three networks may function together to support emotion regulation processing in aging, and we review evidence from depressed patients and mindfulness practitioners that also supports this proposed mechanism. Activity in a brain region known as the amygdala is associated with fear learning and emotional responding (LeDoux, 2003), and in Figure 1.1 we review how connectivity of the amygdala with these networks of interest may influence emotion regulation. Functional connectivity can be assessed both across regions of the same network (intranetwork connectivity) as well as between different networks (internetwork connectivity). For instance, recent evidence supports that the executive network coactivates with other networks depending on the task goals at hand; for instance, it is coactive with the DMN during an autobiographical task that requires thinking about one’s self, but not during an attentionally demanding planning task that does not rely on self-processing 1. Default Mode Network

Z= + 26 mm

2. Central Executive Network

Z= + 56 mm

X= +/- 42 mm

X =+ 4 mm

3. Salience Network

Z= + 20 mm

X= +/- 38 mm

Figure 1.2.  Regions of the default mode, executive, and salience networks. (1) Key regions of default mode network (DMN) include the medial prefrontal cortex (MPFC) and posterior cingulate cortex. (2) Executive network whose key regions include the dorsolateral prefrontal cortex and posterior parietal cortex. (3) Regions of the salience network including the ventrolateral prefrontal cortex, anterior insula, and anterior cingulate cortex (highlighted in grey box). Data from Shirer et al. (2012).

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(Spreng, Stevens, Chamberlain, Gilmore, & Schacter, 2010). In the following sections, we review changes within the DMN, as well as internetwork changes between the DMN and the executive/salience networks in healthy older adults, depressed patients, and mindfulness practitioners. Default Mode Network and Self-Related Processing The DMN activates during unstructured cognitive processing, including daydreaming about self-relevant agendas at rest (Buckner, Andrews-Hanna, & Schacter, 2008; Mason et al., 2007). It comprises primarily medial structures, including the MPFC, the posterior cingulate cortex/precuneus, the inferior parietal lobule, and the hippocampus (Raichle et al., 2001; see Figure 1.2, Section 1, for DMN regions). During attention-demanding cognitive tasks, DMN activity decreases and activity in the salience network increases (Shulman et al., 1997; Figure 1.2, Section 3). Most cognitive tasks also yield anticorrelations between the DMN and the executive network, with the exception of tasks in which self-related processing promotes goal-directed task performance (Spreng et al., 2010). However, among older adults, DMN activity decreases less as cognitive task difficulty increases (Persson, Lustig, Nelson, & Reuter-Lorenz, 2007; Sambataro et al., 2010). A recent study indicated that these age differences in DMN activity carry over to emotion regulation (Martins, Ponzio, Velasco, Kaplan, & Mather, 2015). In this study, the posterior component of the DMN was activated during use of both self-reflective distraction and reappraisal emotion regulation strategies in older adults. In contrast, among younger adults, the posterior DMN activated only during self-reflective distraction. This suggests that the DMN is involved in a broader range of contexts in emotion regulation and self-reflective processing for older people (Martins et al., 2015; see also Spreng & Schacter, 2012; Figure 1.1, Path A). Older Adults Show Greater Amygdala Connectivity With DMN and Other Networks During Uninstructed Emotion Regulation Emotion regulation success is often quantified in terms of downregulation of activity in the amygdala, which can be modulated by different emotion regulation processes (Ochsner, Silvers, & Buhle, 2012). One of the most effective emotion regulation strategies, cognitive reappraisal, involves trying to “see the silver lining” in a negative situation (Gross, 2002). During reappraisal use, the MPFC and the DMN promote self-reflective processes that determine the personal meaning of stimuli and monitor one’s emotional state (Ochsner et al., 2012; Figure 1.1, Path A). Activity in regions of the salience network directs attention toward the assessment of emotional and default mode network and later-life emotion regulation     

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situational meaning (Figure 1.2, Section 3), and lateral executive network regions alter and update meaning in working memory during reappraisal processing (Figure 1.2, Section 2). Both younger and older adults demonstrate strong functional connectivity between the anterior DMN and the amygdala (Figure 1.1, Path A), as well as connectivity between lateral executive network regions and the amygdala when instructed to reappraise (Urry et al., 2006; Winecoff, Labar, Madden, Cabeza, & Huettel, 2011; Figure 1.1, Path B1). However, when processing negative stimuli in the absence of explicit emotional regulation instructions, older adults show greater functional connectivity between the anterior cin­gulate cortex (hub of the salience network; Figure 1.2, Section 3) and the amygdala than do younger adults (St. Jacques, Dolcos, & Cabeza, 2010; Figure 1.1, Path B2). In another study, older adults who recalled more positive faces from a set of positive, negative, and neutral video clips showed stronger resting MPFC–amygdala functional connectivity than did those who recalled more negative faces, but this effect was not found in younger adults (Sakaki, Nga, & Mather, 2013). This tighter coupling between MPFC and the amygdala in older adults was also found to predict the strength of bias in memory toward recalling positive items (Sakaki et al., 2013). It thus appears that older adults show stronger spontaneous functional connectivity between medial structures and the amygdala than do younger adults when processing emotional stimuli (Figure 1.1, Paths A and B2). In the next section, we investigate age-related changes in connectivity both within the DMN and between the DMN and the salience and executive networks (Figure 1.1, C paths). DMN FUNCTIONAL CONNECTIVITY AND EMOTION REGULATION Functional Connectivity Decreases Within the DMN for Older Adults Within the DMN, functional connectivity decreases with age (AndrewsHanna et al., 2007; Batouli, Boroomand, Fakhri, Sikaroodi, & Oghabian, 2009; Bluhm et al., 2008; Damoiseaux et al., 2008; Grady, Grigg, & Ng, 2012). In particular, connectivity between anterior and posterior DMN regions is weaker among older than younger adults during both resting state (Bluhm et al., 2008; Damoiseaux et al., 2008) and cognitive task performance (Sambataro et al., 2010). Older adults also demonstrate weaker functional connectivity within the DMN during performance of a self-reflective processing task (Grady et al., 2012). These studies demonstrate a decline of functional connectivity within the DMN with age, both at rest and during cognitive and self-related task performance. 16       martins and mather

Increased Connectivity Between DMN and Other Networks in Later Life While DMN internal functional connectivity decreases with age, DMN connectivity with the salience and executive networks increases (Figure 1.1, B paths). Resting state connectivity of the DMN, salience, executive, visual, and somatomotor networks, and other networks reveal less segregation with increasing age (20–89 years; see Chan, Park, Savalia, Petersen, & Wig, 2014). This indicates that younger adults show greater differentiation between networks and that age leads to greater cohesion between networks. Internetwork connectivity was also assessed during task performance of an autobiographical planning task and a visuospatial task, and the relationships between the functional connectivity of the DMN, executive, and salience networks were assessed in younger and older adults (Spreng & Schacter, 2012). Older adults showed greater coupling between the DMN and the executive network for both visuospatial and autobiographical planning tasks. On the other hand, younger adults showed coupling between the DMN and the executive network for the autobiographical task, and between the salience and executive network for the visuospatial task (which requires attentional control). These findings suggest that the functional connectivity of the DMN to other networks increases in later life (Figure 1.1, C paths). However, whether these enhanced connections indicate facilitation of self-related processing in cognitive contexts remains speculative. Therefore, we draw from two other populations— depressed patients and mindfulness practitioners—and examine how changes in functional connectivity relate to differing emotional outcomes. Default Mode Connectivity Increases With Rumination in Depression Perseveration on negative self-related thoughts, or rumination, is among one of the cardinal symptoms of depression (Nolen-Hoeksema, 1991). Patients with major depressive disorder (MDD) attend more to and better remember negative than positive stimuli (Williams et al., 1996). Individuals with depression are faster to detect a dot in the same spatial location as a preceding negative face than following a neutral one (Joormann & Gotlib, 2007), indicating a negativity bias in spatial attention. In addition, depressed individuals show greater MPFC activity during tasks promoting negative self-focus than controls, and this activation correlates with rumination scores (Nejad, Fossati, & Lemogne, 2013). Resting state functional connectivity within the DMN is increased for depressed patients relative to controls (Berman et al., 2011) and is predictive of depressive episode duration (Greicius et al., 2007). Depression is also associated with decreased connectivity between the DMN and the salience and executive networks. Anand et al. (2005) reported decreased connectivity between the MPFC and the amygdala for individuals default mode network and later-life emotion regulation     

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with MDD relative to healthy controls, both at rest and when viewing emotional images. Furthermore, greater dominance of DMN over executive network activity at rest correlates positively with maladaptive depressive rumination scores and correlates negatively with a measure of adaptive selfrelated reflection (Hamilton et al., 2011). In summary, depressed individuals show greater DMN intranetwork connectivity, and decreased internetwork connectivity between the DMN and other networks during both rest and task performance (weakened C paths in Figure 1.1). We next contrast these DMN connectivity patterns to those of mindfulness practitioners, who, like older adults, demonstrate positive functional outcomes. Intranetwork and Internetwork Default Mode Connectivity is Enhanced for Mindfulness Practitioners A central aim of mindfulness practice is to observe the present moment, and increase awareness of both self and situation, without judgment or attempts to change the status quo (Hayes, Strosahl, & Wilson, 1999; KabatZinn, 2003). Mindfulness practice is associated with increases in well-being and can decrease stress (see the review by Rubia, 2009). For instance, mindfulness practice leads to decreased self-reported negative affect and to fewer ruminative and depressive symptoms (Chambers, Gullone, & Allen, 2009). Additionally, mindfulness meditators are better able to disengage from negative images, similar to what is seen among older adults (Ortner, Kilner, & Zelazo, 2007). Meditators with extensive mindfulness experience show increased functional connectivity within the DMN. Meditation experts with more than 120 months of experience showed greater functional connectivity within the DMN than did novices both at rest and during meditation (Brewer et al., 2011). In addition, self-reported mindfulness in daily life is positively associated with resting state connectivity strength within the DMN (Prakash, De Leon, Klatt, Malarkey, & Patterson, 2013). In terms of internetwork connectivity, relative to novices, experienced mindfulness meditators1 show increased DMN connectivity to executive network regions in the dorsolateral PFC both at rest and during meditation (Brewer et al., 2011; Farb et al., 2007; see Figure 1.1, Path C1), and increased posterior DMN functional connectivity to the anterior

It is important to note that mindfulness experience differed across the studies reviewed here, and the operational definition of a “mindfulness expert” is heterogeneous. Mindfulness experience included participants in mindfulness training studies who trained for 2 months according to a manualized mindfulness based stress reduction (MBSR) protocol relative to control participants, mindfulness practitioners with over 120 months meditation practice (Concentration, Loving-Kindness, and Choiceless Awareness meditation) who were selected as a special population, and one study reviewed utilized self-reported daily mindfulness scores as a continuous variable in their analyses. 1

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cingulate cortex of the salience network (Figure 1.1, Path C2). These findings suggest that functional connectivity of the DMN with regions outside of the network also increase with mindfulness practice. INTEGRATING SITUATION AND SELF: EMOTION REGULATION IN AGING, DEPRESSION, AND MINDFULNESS PRACTICE Based on the literature on aging, depressed individuals, and mindfulness practitioners reviewed above, we now discuss the consistent relationships between functional connectivity of the DMN, executive, and salience networks across these three populations. Older Adults Show Greater Corticolimbic Functional Connectivity During Uninstructed Reappraisal Increased connectivity between brain regions involved in processing self and situation may promote older adults’ strategies in natural emotion regulation settings. Connectivity between medial and limbic structures tends to be stronger for older than younger adults when viewing emotional stimuli without explicit emotion regulation instructions (Sakaki et al., 2013; St. Jacques et al., 2010). Older adults show spontaneous enhancement of these DMN-amygdala and salience network–amygdala circuits relative to younger adults, even without reminders or supporting cues. In our model of emotion regulation in aging, we propose that these networks regulate the amygdala by updating self-related meaning of reappraisals (see Ochsner et al., 2012; Figure 1.1, Path A). However, connectivity of executive regions and the amygdala during cued emotion regulation is similar across the lifespan (Winecoff et al., 2011; Figure 1.1, Path B1). Thus, it seems that younger adults are equally capable of regulating their emotions but are less likely to do so when not reminded. This motivational account fits the notion that older adults more readily recruit cognitive control mechanisms to regulate their emotions (Knight et al., 2007; Kryla-Lighthall & Mather, 2009; Mather & Carstensen, 2005; Mather & Knight, 2005) and maps well onto previous behavioral findings in which younger adults’ memory biases resemble those of older adults when in an emotion-focus condition (Kennedy, Mather, & Carstensen, 2004; Mather & Johnson, 2000). Older adults also appear to have stronger functional connectivity of the salience network and DMN with the amygdala than do younger adults (Sakaki et al., 2013; St. Jacques et al., 2010; Figure 1.1, Path B2). Given the role of regions in the salience network and DMN in utilization of reappraisal strategies (Ochsner et al., 2012), stronger connectivity between these networks and the amygdala may facilitate emotion regulation strategy use. Enhancement of default mode network and later-life emotion regulation     

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medial emotion regulation circuits may provide additional regulation routes to down-regulate the amygdala and compensate for gray matter loss in lateral executive network regions (Cabeza, 2002; Fjell et al., 2009; Raz et al., 2005). Increased DMN Internetwork Connectivity May Represent Greater Self-Reflection in Aging Changes in connectivity of networks involved in self-related processing, attentional control, and executive control of emotion may support improved emotion regulation in later life. Relating the self to the situation could represent a possible compensatory mechanism in aging, involving two stages. As previously mentioned, like younger adults, older adults may initially engage salience network–amygdala circuits to increase attention directed toward a stimulus and executive network–amygdala circuits to maximize the positivity of situational meaning (i.e., reappraising a sad situation as only being temporary). In a second stage of processing, older people may use enhanced DMN–executive network and DMN–salience network connections to increase awareness of the associations between positive interpretations and the self (and to dissociate negative interpretations from the self). Increased synchrony between the DMN and lateral executive network regions may result from the integration of self-related processing in more contexts in later life (Martins et al., 2015; Spreng & Schacter, 2012; Figure 1.1, C paths). An age-related increase in associating positive situations to the self and decreasing self-involvement in unalterable negative situations may be one route leading to age by valence interactions in emotional memory (Glisky & Marquine, 2009; Gutchess, Kensinger, & Schacter, 2007; Gutchess, Kensinger, Yoon, et al., 2007; Kensinger & Leclerc, 2009). In addition, internetwork connectivity between the DMN and the salience and executive networks is also enhanced with mindfulness expertise. Given that both older adults and mindfulness experts show high levels of wellbeing and stronger functional connectivity across networks, a connection may exist between network connectivity and outcomes (Figure 1.1, C paths). It is possible that mindfulness experts also assess the self and situation closely, but accept rather than change these situations. It is not surprising that mindfulness and awareness of situational and self-related appraisals have been suggested as a first step in enacting reappraisal strategies (Garland, Gaylord, & Fredrickson, 2011). Regions overlapping with the DMN show activation during self-reflection, regardless of whether self-related processing is conscious or implicit (Rameson, Satpute, & Lieberman, 2010). However, the connection between situational context and positive emotions in older adults remains unknown, and clarifying the role of awareness of these contextual links is an important direction for future research. Furthermore, while the three populations investigated in this chapter demonstrate a consistent pattern in DMN 20       martins and mather

internetwork functional connectivity, differences between these special populations are multifactorial and could represent other variables unexplored in our review. Differing functional mechanisms may manifest in similar network patterns that differ in terms of their etiology. Future research should investigate direct relationships between outcomes in these populations and DMN networking in order to better clarify the mechanisms outlined here. In contrast, depressed individuals failed to show enhanced connectivity between the DMN and other networks. We suggest that decreased internetwork connectivity further reduces the ability of self-processing to alter negative situations and/or the ability of situational appraisals to alter negative thoughts. Depression is associated with a decreased ability to assess situations, feelings, and emotions from a distanced perspective (Sheppard & Teasdale, 2000). Decreased DMN–executive network and DMN–salience network interactions may lead to processing the self separately from emotion regulation goals. Processing of negative situations separately from emotional selfassessment may also decrease feelings of self-efficacy and maintain feelings of hopelessness (Maier & Seligman, 1976). Intranetwork Connectivity Cannot Predict Emotion Regulation Outcomes The stronger connectivity found within the DMN for depressed patients and mindfulness practitioners was strikingly different from the decreased connectivity found within the DMN in aging populations. Ruminative symptoms correlate with increased internal connectivity of the DMN in depressed patients (Berman et al., 2011), and in parallel, with level of mindfulness meditation practice both in daily life and in the laboratory (Brewer et al., 2011; Prakash et al., 2013). Thus, stronger internal DMN connectivity is not in itself diagnostic of well-being; it tracks negative emotional outcomes for depressed patients and positive emotional outcomes in mindfulness expertise. This suggests that decreased DMN connectivity in older adult populations is unlikely in itself to impair emotion regulation. However, more research is needed to uncover which characteristics of these populations are consistently associated with DMN internal connectivity. SUMMARY Emotional resilience in later life poses an age-related enigma. Lateral executive structures decline, and yet older adults show improvements in emotional outcomes. Emotion regulation goals that shift with age and rely on brain regions that decline relatively little through the lifespan such as the default mode network and later-life emotion regulation     

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MPFC, help explain this puzzle (Mather, 2012). The DMN shows enhanced connectivity with the executive and salience network regions for both older adults and mindfulness experts, but not for depressed individuals. In contrast, the internal connectivity of the DMN increases for both depressed patients and mindfulness practitioners, but decreases in older adults. This shows that there is no consistent relationship between favorable emotional outcomes and DMN intranetwork connectivity. This remains an area to be investigated in future research. We propose an emotion regulation mechanism in which the functional connectivity between the DMN and lateral executive/medial salience networks may represent the integration of successful reappraisal outcomes and self-related meaning. Taking stock of situational and self-related feelings and emotions is the first step toward emotion regulation (Garland et al., 2011). In the case of older adults, internetwork connectivity may link positive reappraisals to the self. REFERENCES Anand, A., Li, Y., Wang, Y., Wu, J., Gao, S., Bukhari, L., . . . Lowe, M. J. (2005). Activity and connectivity of brain mood regulating circuit in depression: A functional magnetic resonance study. Biological Psychiatry, 57, 1079–1088. http://dx.doi.org/10.1016/j.biopsych.2005.02.021 Andrews-Hanna, J. R., Smallwood, J., & Spreng, R. N. (2014). The default network and self-generated thought: Component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences, 1316, 29–52. http:// dx.doi.org/10.1111/nyas.12360 Andrews-Hanna, J. R., Snyder, A. Z., Vincent, J. L., Lustig, C., Head, D., Raichle, M. E., & Buckner, R. L. (2007). Disruption of large-scale brain systems in advanced aging. Neuron, 56, 924–935. http://dx.doi.org/10.1016/j.neuron. 2007.10.038 Batouli, A. H., Boroomand, A., Fakhri, M., Sikaroodi, H., & Oghabian, M. A. (2009). The effect of aging on resting-state brain function: An fMRI study. Iranian Journal of Radiology, 6, 153–158. Berman, M. G., Peltier, S., Nee, D. E., Kross, E., Deldin, P. J., & Jonides, J. (2011). Depression, rumination and the default network. Social Cognitive and Affective Neuroscience, 6, 548–555. http://dx.doi.org/10.1093/scan/nsq080 Blazer, D. G. (2003). Depression in late life: Review and commentary. The Journals of Gerontology: Series A. Biological Sciences and Medical Sciences, 58(3), M249–265. http://dx.doi.org/10.1093/gerona/58.3.M249 Bluhm, R. L., Osuch, E. A., Lanius, R. A., Boksman, K., Neufeld, R. W. J., Théberge, J., & Williamson, P. (2008). Default mode network connectivity: Effects of age,

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Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., . . . Beckmann, C. F. (2009). Correspondence of the brain’s functional architecture during activation and rest. PNAS Proceedings of the National Academy of Sciences of the United States of America, 106, 13040–13045. http://dx.doi.org/10.1073/ pnas.0905267106 Spreng, R. N., & Schacter, D. L. (2012). Default network modulation and largescale network interactivity in healthy young and old adults. Cerebral Cortex, 22, 2610–2621. http://dx.doi.org/10.1093/cercor/bhr339 Spreng, R. N., Stevens, W. D., Chamberlain, J. P., Gilmore, A. W., & Schacter, D. L. (2010). Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition. NeuroImage, 53, 303–317. http://dx.doi. org/10.1016/j.neuroimage.2010.06.016 St. Jacques, P., Dolcos, F., & Cabeza, R. (2010). Effects of aging on functional connectivity of the amygdala during negative evaluation: A network analysis of fMRI data. Neurobiology of Aging, 31, 315–327. http://dx.doi.org/10.1016/ j.neurobiolaging.2008.03.012 Stone, A. A., Schwartz, J. E., Broderick, J. E., & Deaton, A. (2010). A snapshot of the age distribution of psychological well-being in the United States. PNAS Proceedings of the National Academy of Sciences of the United States of America, 107, 9985–9990. http://dx.doi.org/10.1073/pnas.1003744107 Sütterlin, S., Paap, M. C., Babic, S., Kübler, A., & Vögele, C. (2012). Rumination and age: Some things get better. Journal of Aging Research, 2012, 1. http://dx.doi. org/10.1155/2012/267327 Symons, C. S., & Johnson, B. T. (1997). The self-reference effect in memory: A meta-analysis. Psychological Bulletin, 121, 371–394. http://dx.doi.org/10.1037/ 0033-2909.121.3.371 Urry, H. L., van Reekum, C. M., Johnstone, T., Kalin, N. H., Thurow, M. E., Schaefer, H. S., . . . Davidson, R. J. (2006). Amygdala and ventromedial prefrontal cortex are inversely coupled during regulation of negative affect and predict the diurnal pattern of cortisol secretion among older adults. The Journal of Neuroscience, 26, 4415–4425. http://dx.doi.org/10.1523/JNEUROSCI.3215-05.2006 Williams, J. M., Ellis, N. C., Tyers, C., Healy, H., Rose, G., & MacLeod, A. K. (1996). The specificity of autobiographical memory and imageability of the future. Memory & Cognition, 24, 116–125. http://dx.doi.org/10.3758/BF03197278 Windsor, T. D., Burns, R. A., & Byles, J. E. (2013). Age, physical functioning, and affect in midlife and older adulthood. The Journals of Gerontology: Series B. Psychological Sciences and Social Sciences, 68, 395–399. http://dx.doi.org/10.1093/geronb/gbs088 Winecoff, A., Labar, K. S., Madden, D. J., Cabeza, R., & Huettel, S. A. (2011). Cognitive and neural contributors to emotion regulation in aging. Social Cognitive and Affective Neuroscience, 6, 165–176. http://dx.doi.org/10.1093/scan/nsq030

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2 AGE DIFFERENCES IN USE AND EFFECTIVENESS OF POSITIVITY IN EMOTION REGULATION: THE SAMPLE CASE OF ATTENTION KIMBERLY M. LIVINGSTONE AND DEREK M. ISAACOWITZ

How does emotion regulation vary across the lifespan? A typical review of research on age differences in emotion regulation might proceed strategy by strategy and describe research on whether or not there are age differences in each of these strategies. However, researchers have recently acknowledged that examining individual differences in emotion regulation involves addressing two distinct questions: Are there differences in the use of strategies, and are there differences in the effectiveness of those strategies (Bolger & Zuckerman, 1995; Isaacowitz & Blanchard-Fields, 2012; McRae, 2013)? The distinction between use and effectiveness of regulatory strategies has been previously addressed in the domain of personality and coping (Bolger & Zuckerman, 1995). In this framework, individual differences can influence experience in two ways. First, they can affect whether and how a person is exposed to a stressful situation; in this differential exposure model, the relationship between a personality trait and stress is mediated by the number and intensity of stressors a person encounters. Second, individual http://dx.doi.org/10.1037/14857-003 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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differences can affect how a person reacts to stressful situations; in the differential reactivity model, personality moderates the effects of stressful events on experienced stress. This can occur in two broad ways: by influencing the choice of strategies a person uses, as well as by influencing the effectiveness of those strategies. Applying this framework to the domain of aging and emotion would suggest that age influences emotional experience by influencing the situations older adults expose themselves to, as well as how they react to emotion-eliciting situations. Moreover, age influences the choice of emotion regulation strategies people use and how effective those strategies are. Though there is likely some overlap between the emotion regulation strategies people use and what tends to work for them, people often choose strategies that are not useful and ignore strategies that would benefit them (e.g., Aldao, 2013; Isaacowitz & Blanchard-Fields, 2012). The strategies preferred in young adulthood may lose favor with age, and new ones may be developed. Moreover, this is likely influenced by age-related cognitive, physical, and social changes that enhance or diminish the effectiveness of strategies (Charles, 2010; Urry & Gross, 2010). Thus far, the use and effectiveness of emotion regulation strategies have generally been examined separately, using different methodologies and time frames (McRae, 2013). In this chapter, we examine why and how age influences the use and effectiveness of emotion regulation strategies. For example, which motivational and cognitive processes underlie age differences? As people age, shifts in goals and priorities (Carstensen, Isaacowitz, & Charles, 1999), as well as changes in cognitive and physical processes (Charles, 2010; Urry & Gross, 2010), are thought to have profound influences on emotions and the ways in which people go about regulating them. We first review prominent theories of aging and emotion. In the emotional aging domain, socioemotional selectivity theory (SST) describes how emotional and other goals shift over the life course, providing one answer to why emotional experience and emotion regulation change with age (Carstensen, 1995; Carstensen et al., 1999). In the emotion regulation domain, the process model describes strategies people can use to modify their emotions (Gross, 1998; Gross & Thompson, 2007). Two related theories—the selection, optimization, and compensation in the emotion regulation (SOC–ER) model (Urry & Gross, 2010) and the strength and vulnerability integration (SAVI) model (Charles, 2010)—address how emotional experience and emotion regulation change with age. We then explore possible integration between motivational and strategy-based models, examining the case of attentional deployment, an emotion regulation strategy proposed by the process model that shows age-related changes consistent with SST. The research findings on age differences in attentional deployment also highlight the importance of distinguishing 32       livingstone and isaacowitz

between use and effectiveness. Finally, we explore applications of this theoretical overlap to other strategies and propose ways of extending this research in future directions. THEORETICAL FRAMEWORKS OF AGING AND EMOTION REGULATION Aging and Emotion Regulation Goals One reason emotion regulation is thought to change over the lifespan is that the emotion regulation goals people hold shift with advancing age. Emotion regulation can be used for prohedonic goals (e.g., reducing anxiety in a stressful situation, savoring joy during a happy event), or for instrumental goals that might involve contrahedonic regulation for the purpose of longerterm gains (e.g., maintaining anger in a confrontation in order to more strongly assert oneself; Tamir, 2009; see also Chapter 5, this volume). SST suggests that goals become more prohedonic with age: As people age, they perceive time as less open-ended and so become more oriented toward the present than the future (Carstensen et al., 1999). As a result, their priorities shift from knowledge acquisition goals to emotion regulation goals. Specifically, the theory states that older adults are more concerned with maintaining and enhancing positive emotion, and avoiding and minimizing negative emotion (Carstensen et al., 1999). In contrast, younger adults often have nonhedonic or contra­ hedonic instrumental goals that can involve confronting negative information or experiences in order to gain long-term benefits (e.g., Riediger, Schmeidek, Wagner, & Lindenberger, 2009). In other words, according to SST, the emotion regulation goals of older adults are more likely to be prohedonic. In contrast, although younger adults do want to be happy and feel good, they are more willing to expose themselves to potentially negative situations for the sake of long-term gains like accumulating knowledge, forming new relationships, and competing to get ahead. In turn, changing goals lead to shifts in cognitive processing that are thought to manifest in age-related positivity effects, defined as preferential processing of positive relative to negative stimuli in older adults compared with younger adults (Carstensen & Mikels, 2005). Age-related positivity effects have been demonstrated in both attention (with older adults paying more attention to positive and less attention to negative stimuli, compared with younger adults) and memory (with older adults remembering more positive and less negative stimuli, compared with younger adults; see Reed, Chan, & Mikels, 2014). For example, positivity effects have been found in working memory (Mikels, Larkin, Reuter-Lorenz, & Carstensen, 2005), memory for emotional age differences in use and effectiveness of positivity     

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images (Charles, Mather, & Carstensen, 2003), and autobiographical memories (Kennedy, Mather, & Carstensen, 2004). A recent meta-analysis found that positivity effects in attention and memory are most robust when cognitive processing is unconstrained, which the authors interpreted as evidence that they are driven by top-down motivational processes (Reed et al., 2014). In other words, according to SST, positivity effects reflect the natural preferences of older adults and occur when they have the resources available to use them. In examining the question of whether positivity effects in attention constitute emotion regulation, Isaacowitz and Blanchard-Fields (2012) stated that researchers must establish (a) that age differences in preferences for positive over negative material exist, and (b) that these age differences lead to reliable age differences in affect and emotion. In their review, they show that research has frequently demonstrated that positivity effects exist (see also Reed et al., 2014), but it is not always the case that these age-related cognitive tendencies lead to reliable age differences in affect and emotion (Isaacowitz & Blanchard-Fields, 2012). As we describe below, positive gaze preferences (looking more at positive and less at negative stimuli) can reflect the emotion regulation strategy of attentional deployment. The questions posed by Isaacowitz and Blanchard-Fields (2012) can be extended to other emotion-related processes as well. Specifically, are there reliable age differences in the use of various emotion regulation strategies? Are there age differences in the effectiveness of emotion regulation strategies in producing desired affective states? Thus far, most research has examined these questions in a piecemeal way. In the following, we review the existing theory and research on age differences in the use and effectiveness of emotion regulation strategies. Then, we propose a way to integrate the motivational and strategy-based approaches. Specifically, we suggest that SST’s assertion that older adults prioritize positive over negative experiences, relative to younger adults, has implications for the means with which older adults attempt to influence their emotions (i.e., the strategies they choose, and what is effective for them). This would then allow us to form testable hypotheses linking the two theoretical approaches. Aging and Emotion Regulation Strategies The process model of emotion regulation (Gross, 1998; Gross & Thompson, 2007) is currently the most influential one generating research on emotion regulation in adulthood. According to the model, people use five broad families of strategies to manage their emotional experience, which vary by the stage of emotion they target. Situation selection and situation modification represent the earliest strategies in which people choose to avoid or enter a situation (selection) or directly change their situation (modification) before an emotion is even 34       livingstone and isaacowitz

elicited. Attentional deployment—shifting attention toward or away from possible emotion-eliciting stimuli—and cognitive change (e.g., reappraisal)—changing the way you think about the situation or experience—represent cognitive strategies by which a person can still intervene to change his or her emotions before the full-blown emotional response occurs. Attentional deployment is thought to occur earlier in the process than reappraisal and to require less engagement with the potentially emotion-eliciting stimuli (Sheppes et al., 2014). Response modulation occurs after the emotion has been elicited, and focuses on changing one’s behavioral or physiological response, for example, by hiding one’s facial expression of the emotion (expressive suppression). According to the process model, strategies that target earlier stages of the emotion generative process are more likely to be successful in influencing emotions (Gross, 1998). This may especially be the case for older adults because of age-related changes in cognitive and physical resources (Charles, 2010; Urry & Gross, 2010). Drawing on the process model of emotion regulation, the SOC–ER framework explores why strategy use and effectiveness might change as people age (Urry & Gross, 2010). SOC–ER proposes that to maintain successful emotion regulation, older individuals reduce the use of strategies that rely on resources that decline with age, and compensate by using other strategies that are more likely to be effective for them, thus adaptively using resource-matched regulation strategies to achieve positive emotional outcomes. For example, older adults may rely less on reappraisal, which requires active engagement with emotional stimuli as well as cognitive control and effort, and shift more toward situation selection, which allows them to avoid negative situations in the first place. Similarly, the SAVI model suggests that older adults can best manage their emotions by preventing them from occurring in the first place or by disengaging (Charles, 2010). According to SAVI, older adults have gained experience and knowledge about emotions and the situations that elicit them, which allows them to anticipate and avoid highly negative situations or create positive emotion-eliciting situations. On the other hand, they face declines in cognitive and physiological functioning, which makes downregulating from high-arousal situations more difficult. In response to these changing resources, they may change the frequency with which they use certain strategies, and they may have different degrees of success when implementing them. In sum, both models suggest the strategies that people prefer to use and those that are effective for them shift with age in predictable ways. One limitation of the emotion regulation literature to date is that the questions of use and effectiveness have generally been examined separately, typically using different methodologies (McRae, 2013). In theory, the two are also entwined: In the SOC–ER model, for example, Urry and Gross (2010) suggested that younger and older adults differ in using emotion regulation age differences in use and effectiveness of positivity     

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strategies “more frequently and/or successfully” (p. 355). They did not offer separate hypotheses, but were explicit in noting the distinction. Moving forward, it will be important to examine both questions systematically, using parallel methodology (see McRae, 2013). In the following, we explore a possible integration of motivational and strategy-based approaches that offers a way to develop testable hypotheses regarding age differences in emotion regulation use and effectiveness, and thus to test them in a systematic way. NEW THEORETICAL DEVELOPMENTS: MERGING POSITIVITY EFFECTS AND THE PROCESS MODEL SST (Carstensen et al., 1999) focuses on motivation, whereas the process model (Gross, 1998), SOC–ER (Urry & Gross, 2010), and SAVI (Charles, 2010) focus on means for emotion regulation. These approaches thus represent possibly complementary approaches to studying emotion regulation across the lifespan, together addressing the questions of what changes and why. In particular, we propose that the age-related changes in motivation suggested by SST influence the means of emotion regulation as outlined by the process model. Recent research stemming from the process model has demonstrated the importance of differentiating among strategies within a family of strategies. For example, one meta-analysis identified seven types of attentional deployment, four types of cognitive change, and four types of response modulation and found that effectiveness depends on the specific instructions—in other words, the type of attentional deployment, for example (Webb, Miles, & Sheeran, 2012). Therefore, it is important to examine the various “flavors” within each family of the process model. One particularly intriguing idea, which we focus on below, is that compared with younger adults, older adults favor positivity in emotion regulation, which helps them achieve the high level of well-being that is often seen in later life. SST (Carstensen et al., 1999) suggests that older adults are motivated to reduce negative emotion and maximize positive emotion, and the process model (Gross, 1998; Urry & Gross, 2010) suggests ways in which they can do this. If these models are compatible, we might expect positivity effects at all stages of emotion regulation, from situation selection to response modulation. Table 2.1 presents examples of possible positivity effects across the process model. Although most of this list presents potential hypotheses for future work to investigate, some evidence for positivity effects in process model strategies already exists: For example, some older adults choose to enter positive situations and avoid negative situations (Rovenpor, Skogsberg, & Isaacowitz, 2013); they direct their attention toward positive and away from negative stimuli (see Isaacowitz, 2012, for a review); and they 36       livingstone and isaacowitz

TABLE 2.1 Possible Positivity Effects in the Process Model of Emotion Regulation Stage of the process model

Positivity in emotion regulation

Situation selection

Seeking out and choosing positive situations, avoiding negative situations

Situation modification

Enhancing positive aspects of the situation, minimizing negative aspects

Attentional deployment

Directing attention toward posi­ tive stimuli, directing attention away from negative stimuli

Reappraisal

Positive reappraisal: focusing on the positive aspects of negative situations

Response modulation

Putting on a happy face even in negative situations; cultivating positive physio­ logical responses (e.g., via meditation)

Examples of other possible regulation strategies Seeking out negative situations or avoiding positive situa­ tions; seeking out neutral situations; seeking out famil­ iar situations, regardless of valence Taking no action to modify the situation; enhancing impor­ tant aspects of the situation regardless of valence Directing attention toward negative stimuli or away from positive stimuli; directing attention toward or away from emotionally salient material, regardless of valence Detached reappraisal: main­ taining an objective outlook; rumination: thinking about the negative aspects Suppressing the expression or experience of negative emo­ tion (maintaining a neutral expression); exaggerating expression or experience of negative emotion

may also focus on positive aspects of the situation rather than trying to reduce all emotion when reappraising (see Shiota & Levenson, 2009). Table 2.1 lists specific strategies within each family of the process model, comparing the forms representing positivity against alternative forms of emotion regulation would reveal the extent to which positivity in emotion regulation exists in older compared with younger adults. The particular forms of each strategy people employ are likely to depend on their goals and motives. Positivity is likely to be effective for those who wish to maximize positive and minimize negative emotion. SST suggests that older adults’ present-oriented goals and their focus on intimate, already established relationships, will lead them to take this route (Carstensen, 1995). In contrast, if a person wishes to gain long-term benefits, they may benefit more from alternative forms. For example, someone who has a goal to earn a promotion might be willing to put in long, stressful hours at work; someone who will repeatedly encounter an irritating colleague might intentionally age differences in use and effectiveness of positivity     

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engage with the person in order to improve the relationship, though this may be unpleasant at first. This is not to say that younger adults do not have prohedonic goals or that older adults never engage in contrahedonic behavior (in both cases, they do; see Riediger et al., 2009). Rather, on average, SST suggests that older adults should prefer strategies that maximize positive over negative experiences to a greater extent than younger adults. In terms of emotion regulation strategies, older adults should prefer the more positive “flavors” of strategies to a greater extent than younger adults. To examine this hypothesis, we need to address two questions (Isaacowitz & Blanchard-Fields, 2012): whether there are age differences in positivity of emotion regulation—do older adults use strategies that emphasize positive over negative engagement?—and whether there are age differences in the effectiveness of those strategies—do older adults benefit more from the emphasis of positive over negative forms of emotion regulation? Furthermore, what role do shifting resources, as proposed by SOC–ER and SAVI, play in such shifts? Next, we turn to empirical work that has focused on possible age-related positivity in one particular emotion regulation strategy: attentional deployment. REVIEW OF CURRENT RESEARCH: THE SAMPLE CASE OF ATTENTIONAL DEPLOYMENT Positive gaze preferences, which correspond to the emotion regulation strategy of attentional deployment, are the most well-researched example of age-related positivity effects in the process model of emotion regulation. In our eye-tracking research on age differences in attention to valenced stimuli, we found evidence that older adults look more at positive and less at negative stimuli, revealing age-related positivity effects in visual attention, which have been replicated in other labs as well (Isaacowitz, 2012). Our earliest work set out to describe differences between younger and older adults in their visual attention toward emotional information. To study this, we presented pairs of emotional and nonemotional faces to younger and older adults and simply asked them to look naturally at the face pairs “as if at home watching TV.” In two studies (Isaacowitz, Wadlinger, Goren, & Wilson, 2006a, 2006b) we found that older adults showed more “positive” looking patterns—more toward positive faces and less toward some types of negative faces. These findings were consistent with the idea of age-related positivity effects in cognitive processes, and thus suggested a link between older adults’ attentional preferences and their self-reported positive emotional experience. However, as with other descriptive research on age-related positivity effects, because emotional experience was not measured, it was impossible to know whether the observed age differences actually reflected 38       livingstone and isaacowitz

emotion regulation processes. In other words, how could we tell whether these age-related positivity effects in visual attention were also instances of the emotion regulation strategy of attentional deployment? Our first step was to determine whether older adults activate their positive gaze preferences in contexts where they would be likely to be motivated to regulate their emotions. To do this, we used mood induction to produce a range of affective states in a sample of younger and older adults, and then we tracked their gaze while they viewed pairs of faces in these mood states. Critically, age differences emerged primarily among participants who started the task in a negative mood. While younger adults in a bad mood showed mood-congruent looking and fixated relatively more on negative faces, older adults in bad moods showed mood-incongruent looking and fixated relatively more on positive faces (Isaacowitz et al., 2008). Having established age differences in the use of attentional deployment, we next turned to effectiveness: Do these positive gaze preferences help older adults regulate out of bad moods? In the mood induction study mentioned above, we examined links between positive gaze preferences (favoring positive relative to negative stimuli) and mood change over the course of the study. Most participants’ mood declined over 15 minutes of looking at face pairs. However, when we used fixation to predict mood change, we found an interaction between age, fixation, and executive control, a type of individual difference in attentional ability. Older adults’ moods were relatively best (with the least negative mood change) when they had good executive control of attention and also showed more positive gaze preferences (more at positive, less at negative). Younger adults actually felt relatively best when they had good executive control of attention but showed more negative gaze preferences (more at negative, less at positive; Isaacowitz, Toner, & Neupert, 2009). In another study in which younger and older participants were explicitly told to regulate their emotional state while viewing negative emotion-eliciting images, age and fixation again interacted with individual differences in attention to predict mood change, in a similar direction. Specifically, older adults with good attentional abilities felt best when they looked least at negative parts of the images, whereas younger adults again felt best when they looked more at the negative parts of the images (Noh, Lohani, & Isaacowitz, 2011). More recently, we considered links between attention and emotion in the context of mood-disrupting video stimuli about skin cancer (Isaacowitz & Choi, 2012). Eye-tracking analyses of fixation to these videos found patterns similar to the studies of images described above: Older adults tended to look least at the negative clips in the videos, compared with younger adults. Both age groups showed equal mood decline during the emotion-focused skin cancer video, but older adults felt better than the younger adults starting right after the video ended and continuing for the rest of the experimental session. age differences in use and effectiveness of positivity     

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In other words, though older adults’ positive gaze preferences in this case did not protect them from being affected in real time by the upsetting film, they did help them recover more quickly from it. The example of attentional deployment highlights the need to distinguish use from effectiveness in examining age differences in emotion regulation. The presence of positivity effects in cognitive processing is not sufficient to demonstrate effective emotion regulation (Isaacowitz & Blanchard-Fields, 2012). The outcome—emotional experience—must be measured as well. In several studies, we found age differences in how positive gaze preferences predict real-time mood change (Isaacowitz, Allard, Murphy, & Schlangel, 2009; Noh et al., 2011). Positive gaze preferences led some older adults to feel better, but this was not the case for younger adults. Importantly, only older adults with stronger executive control abilities were able to effectively use their positive attentional deployment to improve their mood. The findings that cognitive resources are indeed important for effective positive attentional deployment are consistent with the resource-focused theories of SOC–ER (Urry & Gross, 2010) and SAVI (Charles, 2010). POSITIVITY IN THE PROCESS MODEL: FUTURE WORK AND CHALLENGES One promising direction for future research is to examine the question of age-related positivity effects with regard to other strategies within the process model (see Table 2.1). There are several possibilities regarding how positivity may exist across the process model. First, positivity effects may exist in use and effectiveness of all forms of emotion regulation. Second, such positivity effects may appear only in early stages of emotion regulation (i.e., situation selection, situation modification, and attentional deployment), which are theorized to be more effective for older adults (Charles, 2010; Urry & Gross, 2010). Third, there may be age differences in the use of more positive forms of emotion regulation across the process model, but the effectiveness of such strategies could depend on resource variables, such as cognitive resources and emotion regulation self-efficacy. In the following, we review research that gives some hints of answers and suggests ways of addressing these possibilities more directly. Situation Selection Despite being heralded as an effective way for managing emotions, there is little research on situation selection. To remedy this, we created an affective environment (AE), a room in which participants spend time and 40       livingstone and isaacowitz

freely choose from among a range of emotional and nonemotional stimuli under experimentally controlled conditions. In this paradigm, a situation is defined as engaging with a particular stimulus (e.g., watching a video, reading an article, or viewing an image); situation selection is defined as choosing to engage with a particular stimulus or choosing to avoid engaging with it. In our first study in the AE, we examined situation selection use; there were no main effects of age in the choices that people made, but an age-individual difference interaction emerged: Older adults with strong emotion regulation self-efficacy selected more positive choices (Rovenpor et al., 2013). Two additional studies in the AE used mobile eye tracking to measure attentional selection (a combination of situation selection and attentional deployment), allowing participants to choose which stimuli they viewed (Isaacowitz, Livingstone, Harris, & Marcotte, 2015). These studies also assessed mood to investigate possible age differences in situation selection effectiveness. In both studies, participants of different age groups selected similar proportions of emotionally valenced stimuli to look at, which in turn had similar effects on mood across groups. Taken together, this research suggests that though there may not be main effects in positivity in situation selection, there may be person- or situation-level variables that influence situation selection use in different ways for different age groups. Situation Modification Once a person has entered into a situation, there are many different ways he or she can change that situation in order to influence his or her emotions. However, there is surprisingly little research on situation modification. Most of what we know is extrapolated from the problem-solving literature (e.g., see Blanchard-Fields, Stein, & Watson, 2004). Problem-focused or active coping has been conceptually linked to the emotion regulation strategy of situation modification (see John & Gross, 2004), and although emotion regulation and coping share some similarities, they are distinct forms of self-regulation (Gross, 1998). Therefore, much more research is needed on situation modification in general—direct attempts to change one’s situation in a way that will influence one’s emotion—and on age differences specifically. Examining positivity will require identifying actions that change the situation in positive ways—reducing the likelihood or impact of potentially negative factors and/or increasing the likelihood or impact of potentially positive factors. For example, a person could minimize the effects of a worrisome storm by stocking up on supplies beforehand, or by calling up neighbors for social and instrumental support (or perhaps to take advantage of a snow day by socializing). age differences in use and effectiveness of positivity     

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Cognitive Change After the situation is entered and attended to, people can regulate their emotions by changing the way they appraise that situation (i.e., reappraising). There appear to be age differences in the use of reappraisal: One crosssectional study found that older women self-report using general reappraisal more often than younger women (John & Gross, 2004). The same study also asked the older women to retrospectively report how frequently they had used reappraisal when they were younger, and found that they reported using it more often now that they were older. Even though older adults report using reappraisal more, it requires active cognitive engagement with emotion-eliciting stimuli, which may be less effective for older adults due to age-related cognitive declines (Urry & Gross, 2010). However, research suggests that it depends on the type of reappraisal considered. One particular form of reappraisal, known as positive reappraisal, involves interpreting situations and stimuli in a positive light (e.g., Lohani & Isaacowitz, 2014; Shiota & Levenson, 2009). Because older adults show cognitive patterns of attention and memory that are characterized by positivity, one wonders whether they are able to make positive appraisals more efficiently. One study found age-related declines in the effectiveness of detached reappraisal (adopting a “detached and unemotional attitude”) but age-related improvements in the effectiveness of positive reappraisal (thinking “about the positive aspects of what you are seeing”; Shiota & Levenson, 2009). The authors concluded that “these results are consistent with studies documenting the age-related positivity bias, in which older adults tend to allocate greater attention to positive stimuli” (p. 898). To our knowledge, no one has examined age differences in use of positive compared with other forms of reappraisal in everyday life. Response Modulation Response modulation targets behavioral and physiological aspects of emotional response and occurs after the full-blown emotion has already begun. Most research on response modulation has focused on the expressive suppression strategy—hiding the expression of emotion on one’s face. In terms of use, self-report research suggests that older adults use suppression less often than do younger adults (John & Gross, 2004). In terms of effectiveness, laboratory studies have consistently shown that older adults are able to suppress their expressions as well as younger adults (e.g., Lohani & Isaacowitz, 2014; Shiota & Levenson, 2009). Shiota and Levenson (2009) found no age differences in the influence of suppression on emotional experience or physiology. There could also be important age differences in other forms of response modulation, particularly positive forms. For example, having participants 42       livingstone and isaacowitz

smile during a stressful task has emotional and physiological benefits (Kraft & Pressman, 2012). However, there is no research to our knowledge about age differences in the tendency to “grin and bear it” or “put on a brave face.” Moreover, most of the research on response modulation has focused on expressivity, but people can also influence their physiological or behavioral responses to emotions. It would be particularly interesting to study how physiological response modulation changes with age, given the physiological changes that occur in older adulthood (Charles, 2010). Positive physiological modulation may involve cultivating more positive and relaxed baseline functioning, as in meditation. Finally, it is worth noting that research derived from the process model has generally focused on one or two strategies within a study. To date, no one has compared all strategies in a study or series of studies (though metaanalyses exist; see Webb et al., 2012), and thus we know very little about how the stages of emotion regulation function and compare within individuals. Moreover, it is likely that age and other individual difference variables moderate within-person comparisons among strategies. Given the previous research the process model has generated, it is likely that systematic withinsubject research will yield interesting results, and also likely that age differences will emerge (Urry & Gross, 2010). In sum, much more research is needed to investigate changes in the use and effectiveness of emotion regulation strategies across the lifespan. We believe that combining two major groups of theoretical perspectives, one from emotional aging and one from emotion regulation, will be useful in generating research questions and testable hypotheses regarding how emotion regulation and emotional experience change with age. OTHER FUTURE DIRECTIONS AND CHALLENGES Individual Difference Moderators and Mediators There are indications both from theory and from research that individual differences in resources influence emotion regulation preferences and effectiveness. For example, both Isaacowitz and Blanchard-Fields (2012) and the SOC–ER and SAVI frameworks address the role of individual differences in resources (e.g., cognitive, physical, social) in influencing the ability to implement different emotion regulation strategies. In previous empirical studies on age differences in emotion regulation, there are often moderators of preferences and effectiveness. For example, only older adults with strong emotion regulation self-efficacy used more positive situation selection (Rovenpor et al., 2013), and positive attentional deployment seems to benefit age differences in use and effectiveness of positivity     

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mood only for older adults with good attentional abilities (Isaacowitz et al., 2009; Noh et al., 2011). Both person and situation variables can enhance or interfere with the effectiveness of an emotion regulation strategy. Cognitive and physical resources are likely to be important candidates for investigation, as well as social connections and support, physical health, and level of education. Personality traits such as optimism and emotional stability may also influence emotion regulation and perceptions of time horizons. Motives and Strategies at All Ages In examining lifespan development, it is important to understand what is occurring at all stages of life. Age-related positivity findings are often framed in terms of what older adults are doing, but it is just as interesting to pay attention to what younger and middle-aged adults are doing. Some research suggests that younger adults are likely to choose to engage with negative stimuli, at least those of low arousal, when they have cognitive resources available, rather than disengaging (Sheppes et al., 2014). This is consistent with the idea that younger adults are willing to experience negative emotions in order to gain long-term benefits such as knowledge acquisition (Carstensen et al., 1999). Yet younger adults do not always feel worse when engaging with negative stimuli. In our research, younger adults with good attentional abilities who looked more at negative images actually felt better (Isaacowitz et al., 2009; Noh et al., 2011). This raises the question of what they are doing while paying attention to those stimuli—are they reappraising, or perhaps using another form of emotion regulation (e.g., social comparison, distraction)? Another possibility is that they are prioritizing information acquisition goals over emotion regulation goals, and they feel better not because they are trying to do so but because their goals are being met. SST proposes that while older adults tend to have more chronically activated prohedonic goals, this is not always the case for younger adults (see also Riediger et al., 2009). Moving forward, we must keep this in mind when investigating the effectiveness of emotion regulation. This can be done by experimentally manipulating situational goals to be prohedonic (or not), or by measuring goals at the trait or state level. Another concern is that most research to date has used extreme age groups, comparing younger (e.g., 18–25 years) and older adults (e.g., over 60 years); more research is needed on the full adult lifespan (see also Freund & Isaacowitz, 2013). We therefore know very little about emotion regulation in middle adulthood and when positivity preferences emerge. Interestingly, one study found that middle-aged adults generally showed fixation and mood patterns similar to older adults (Isaacowitz & Harris, 2014). These findings suggest that the links between positivity in attention and emotion regulation via attentional deployment may not be unique to late life. 44       livingstone and isaacowitz

Methodological Design Almost all research to date is cross-sectional in design, that is, we can only draw conclusions about age differences rather than age change. There may be generational differences in the ability to “grin and bear it,” or in the tendency to take charge of the situation versus accepting it and reframing your interpretation. Cross-sectional studies can compare across age groups and capture differences among cohorts, which is useful because it allows for consideration of factors that vary across generations. However, longitudinal research is also needed to examine how preferences and effectiveness of emotion regulation strategies change and develop within individuals as they age. Moreover, it will be important to understand how changes in life circumstances (e.g., retirement, death of a spouse) influence shifts in goals, strategy preferences, and strategy effectiveness. CONCLUSIONS AND IMPLICATIONS The study of aging and emotion regulation is fortunate to have multiple theoretical models to guide research and hypothesis testing. On the one hand, there are motivation-based approaches such as SST; on the other hand, there are strategy-based approaches such as the process model, SOC–ER, and SAVI. Our goal in this chapter has been to provide a framework for formally considering the intersection of these two approaches, both to review research that has already considered their intersection (especially work on attentional deployment/positive gaze preferences), as well as to encourage future research to do the same for other possible strategies. We believe that systematically exploring how these types of models do and do not intersect, conceptually and empirically, will help researchers design studies that test complementary and competing hypotheses, refine theories based on the evidence that emerges, and advance the field of emotional aging. REFERENCES Aldao, A. (2013). The future of emotion regulation research: Capturing context. Perspectives on Psychological Science, 8, 155–172. http://dx.doi.org/10.1177/ 1745691612459518 Blanchard-Fields, F., Stein, R., & Watson, T. L. (2004). Age differences in emotionregulation strategies in handling everyday problems. The Journals of Gerontology: Series B. Psychological Sciences and Social Sciences, 59, 261–269. http://dx.doi. org/10.1093/geronb/59.6.P261 age differences in use and effectiveness of positivity     

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Isaacowitz, D. M., & Harris, J. A. (2014). Middle-aged adults facing skin cancer information: Fixation, mood, and behavior. Psychology and Aging, 29, 342–350. http://dx.doi.org/10.1037/a0036399 Isaacowitz, D. M., Livingstone, K. M., Harris, J. A., & Marcotte, S. L. (2015). Mobile eye tracking reveals little evidence for age differences in attentional selection for mood regulation. Emotion, 15, 151–161. http://dx.doi.org/10.1037/emo0000037 Isaacowitz, D. M., Toner, K., Goren, D., & Wilson, H. R. (2008). Looking while unhappy: Mood-congruent gaze in young adults, positive gaze in older adults. Psychological Science, 19, 848–853. http://dx.doi.org/10.1111/j.1467-9280.2008.02167.x Isaacowitz, D. M., Toner, K., & Neupert, S. D. (2009). Use of gaze for real-time mood regulation: Effects of age and attentional functioning. Psychology and Aging, 24, 989–994. http://dx.doi.org/10.1037/a0017706 Isaacowitz, D. M., Wadlinger, H. A., Goren, D., & Wilson, H. R. (2006a). Is there an age-related positivity effect in visual attention? A comparison of two methodologies. Emotion, 6, 511–516. http://dx.doi.org/10.1037/1528-3542.6.3.511 Isaacowitz, D. M., Wadlinger, H. A., Goren, D., & Wilson, H. R. (2006b). Selective preference in visual fixation away from negative images in old age? An eye-tracking study. Psychology and Aging, 21, 40–48. John, O. P., & Gross, J. J. (2004). Healthy and unhealthy emotion regulation: Personality processes, individual differences, and life span development. Journal of Personality, 72, 1301–1334. http://dx.doi.org/10.1111/j.1467-6494.2004.00298.x Kennedy, Q., Mather, M., & Carstensen, L. L. (2004). The role of motivation in the age-related positivity effect in autobiographical memory. Psychological Science, 15, 208–214. http://dx.doi.org/10.1111/j.0956-7976.2004.01503011.x Kraft, T. L., & Pressman, S. D. (2012). Grin and bear it: The influence of manipulated facial expression on the stress response. Psychological Science, 23, 1372–1378. http://dx.doi.org/10.1177/0956797612445312 Lohani, M., & Isaacowitz, D. M. (2014). Age differences in managing response to sadness elicitors using attentional deployment, positive reappraisal and suppression. Cognition and Emotion, 28, 678–697. http://dx.doi.org/10.1080/02699931. 2013.853648 McRae, K. (2013). Emotion regulation frequency and success: Separating constructs from methods and time scale. Social and Personality Psychology Compass, 7, 289–302. http://dx.doi.org/10.1111/spc3.12027 Mikels, J. A., Larkin, G. R., Reuter-Lorenz, P. A., & Carstensen, L. L. (2005). Divergent trajectories in the aging mind: Changes in working memory for affective versus visual information with age. Psychology and Aging, 20, 542–553. http:// dx.doi.org/10.1037/0882-7974.20.4.542 Noh, S. R., Lohani, M., & Isaacowitz, D. M. (2011). Deliberate real-time mood regulation in adulthood: The importance of age, fixation and attentional functioning. Cognition and Emotion, 25, 998–1013. http://dx.doi.org/10.1080/02699931. 2010.541668 age differences in use and effectiveness of positivity     

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Reed, A. E., Chan, L., & Mikels, J. A. (2014). Meta-analysis of the age-related positivity effect: Age differences in preferences for positive over negative information. Psychology and Aging, 29, 1–15. http://dx.doi.org/10.1037/a0035194 Riediger, M., Schmiedek, F., Wagner, G. G., & Lindenberger, U. (2009). Seeking pleasure and seeking pain: Differences in prohedonic and contrahedonic motivation from adolescence to old age. Psychological Science, 20, 1529–1535. http:// dx.doi.org/10.1111/j.1467-9280.2009.02473.x Rovenpor, D. R., Skogsberg, N. J., & Isaacowitz, D. M. (2013). The choices we make: An examination of situation selection in younger and older adults. Psychology and Aging, 28, 365–376. http://dx.doi.org/10.1037/a0030450 Sheppes, G., Scheibe, S., Suri, G., Radu, P., Blechert, J., & Gross, J. J. (2014). Emotion regulation choice: A conceptual framework and supporting evidence. Journal of Experimental Psychology: General, 143, 163–181. http://dx.doi.org/10.1037/ a0030831 Shiota, M. N., & Levenson, R. W. (2009). Effects of aging on experimentally instructed detached reappraisal, positive reappraisal, and emotional behavior suppression. Psychology and Aging, 24, 890–900. http://dx.doi.org/10.1037/ a0017896 Tamir, M. (2009). What do people want to feel and why? Pleasure and utility in emotion regulation. Current Directions in Psychological Science, 18, 101–105. http:// dx.doi.org/10.1111/j.1467-8721.2009.01617.x Urry, H. L., & Gross, J. J. (2010). Emotion regulation in older age. Current Directions in Psychological Science, 19, 352–357. http://dx.doi.org/10.1177/0963721410388395 Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: A meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. Psychological Bulletin, 138, 775–808. http://dx.doi.org/10.1037/a0027600

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II Regulatory Frameworks

3 RESOURCES FOR EMOTION REGULATION IN OLDER AGE: LINKING COGNITIVE RESOURCES WITH COGNITIVE REAPPRAISAL HEATHER L. URRY

Looking in the mirror, my skin has visible lines and spots. Grasping my toothbrush, my fingers ache. I can run, but not fast, in part because my knees hurt and my hamstring muscles are knotted up. I forget things, sometimes in mid-sentence. None of these statements were true in my younger form, so it strikes me as pretty accurate to say that getting old isn’t altogether fun. And yet, I have a friend who is the same age as me—a couple of years older, in fact—who has few if any of these problems. Examples like this suggest that the impact of older age on any outcome of interest must be dependent in part on the unique characteristics and experiences of each individual. In this chapter, I focus on emotion regulation as an outcome of interest and argue that one’s resources to carry out emotion regulation strategies will affect the

The author acknowledges the countless contributions of the many students and collaborators who have shaped the thinking represented in these pages over the past several years. Given the content of this chapter in particular, Philipp C. Opitz and James J. Gross deserve special mention. http://dx.doi.org/10.1037/14857-004 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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extent to which one chooses to use a given strategy and ends up being successful in the attempt. To the extent that aging impacts resources, then emotion regulation may be impacted as well. Emotion regulation (ER) refers to a set of psychological processes that may be used to manage the intensity and duration of our responses to emotioneliciting situations. As I elaborate below, I find it useful to consider the resources that might make it possible to choose and execute ER processes successfully. My plan for this chapter is to articulate how differences in resources—such as the ability to maintain representations of a message to be communicated, a resource that is compromised in my case—may impact emotion regulation in older adulthood. I begin by defining emotion and emotion regulation. In this context, I will call into relief an important distinction, namely, the difference between the strategies people choose and their success in using them. I then outline some of the factors that may explain variation in ER strategy choice and success, including the resources people have available. Honing in on one form of emotion regulation in particular, cognitive reappraisal, I then review what some of the resources for cognitive reappraisal might be and how these resources vary within and between persons. I focus specifically on one between-person source of variation, older age, and ask whether there are age differences in resources for reappraisal and corresponding age differences in the use and success of reappraisal strategies. I conclude by suggesting some potentially fruitful directions for future research. EMOTION AND EMOTION REGULATION Emotions arise when situations are construed as “good” or “bad” (or both) in light of one’s goals. Emotion-eliciting situations often interrupt ongoing behavior and lead one to establish a new immediate goal. Emotion-eliciting situations are associated with changes in subjective experience, expressive behavior, and/or autonomic physiology, changes which many believe represent mobilization of resources to respond with behavior that allows us to meet our newfound goal to handle that situation. For example, if someone were to knock suddenly and loudly on the door as I’m typing this, I might feel momentarily fearful, my heart would race, and I might jump and say “AAAAAH!” If the knock represented a threat to my safety, this multisystem response will have prepared me well to deal with the threat. If not, this multisystem response will have been a mildly embarrassing false-positive experience. An emerging consensus across emotion researchers suggests that emotional responses are generated as a function of a constellation of processes that include being exposed to an emotion-eliciting situation, attending to aspects of that situation, and appraising (i.e., interpreting) what one is 52       heather l. urry

experiencing in light of one’s goals (Gross, 2014). These processes represent the antecedents—the ingredients, if you will—that produce a suite of changes in one or more of the response channels described above. If I don’t hear the loud knock on my door, then I’m essentially unexposed to the situation and won’t experience fear and a racing heart, and I won’t jump or scream. If I interpret that loud knock as an indication that my friend from upstairs has arrived for our 4:15 postteaching debrief session, I’m essentially exposed to a different situation; assuming I like this person, I won’t experience fear, a racing heart, jumping, or screaming. These observations suggest an intriguing proposition, namely, that modifying the antecedents of emotion—the situation, how we attend to it, and how we appraise it—should effect change in the emotional response. Indeed, according to the process model of emotion regulation, there are five families of strategies one can adopt if motivated to effect change in our emotions (Gross, 2014). Each strategy targets one of the components of the emotion generative cycle just described. One can select or modify situations (situation selection and situation modification, respectively), attend to certain aspects of situations and avoid attending to other aspects (attentional deployment), or appraise situations or our responses to them differently (cognitive change). One can also directly alter one or more aspects of the emotional response (e.g., exaggerate or diminish one’s subjective experience, expressive behavior, or autonomic physiology; response modulation). Quite a lot of research supports the idea that many of these strategies can successfully effect change in emotional responding (for a meta-analysis, see Webb, Miles, & Sheeran, 2012). As described in Webb and colleagues’ meta-analysis (2012), researchers have relied on a range of measures of emotional responding to demonstrate this, including self-reported ratings of subjective emotional experience, measures of expressive behavior derived from coding of videotapes or from electromyographic recordings over facial muscle regions implicated in emotion expression (e.g., corrugator supercilii), and physiological recordings tapping sympathetic and/or parasympathetic activation of the autonomic nervous system (e.g., heart rate, skin conductance, finger temperature). Notably, these measures vary not only in which component of the emotional response they capture but also in the extent to which various participant and experimenter biases might influence them. For example, self-report measures of subjective experience are necessary if one wishes to index change in that component of the response. However, self-report measures are also subject to biases. Participants may respond to the demand characteristic inherent in much of this work to report subjectively experienced emotions that accord with the experimental conditions. From that perspective, it is heartening to note that studies using the measures that resources for emotion regulation in older age     

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are less subject to such biases support the idea that reappraisal can successfully alter emotional responding (Webb et al., 2012). In one of the earliest demonstrations that use of cognitive change strategies can alter emotional responding, Speisman, Lazarus, Mordkoff, and Davison (1964) used a between-subjects design to demonstrate with undergraduate and airline executive participants the impact of cognitive changes strategies on stressful responding to a video depicting a subincision rite. As their measure of stressful responding, they recorded skin conductance, an index of sympathetic nervous system activation. They observed that skin conductance was lower when the disturbing film was paired with narration that encouraged detached objectivity (intellectualization) or that denied negative impacts on the patient and extolled the cultural value of the procedure (denial and reaction formation) versus a silent, control version of the film without narration (silent). In contrast, skin conductance was higher relative to the silent condition when paired with narration that extolled sources of threat, including the danger of the procedure and intense pain experienced by the person depicted (trauma). More recently, in both between- and within-subjects designs with younger adults, instructions to decrease emotional responding by thinking differently about film clips or pictures that otherwise provoke strong negative affect (e.g., pictures of seriously injured or dead humans and animals) served to reduce emotional responding versus instructions to simply experience (e.g., Gross, 1998) or maintain one’s emotions (e.g., Jackson, Malmstadt, Larson, & Davidson, 2000). Thus, enacting cognitive change strategies can alter emotional response in accordance with one’s regulatory goal. In an important caveat, Webb et al. (2012) suggested that different types of cognitive change are differentially effective. For example, perspective taking and reappraising emotion-provoking stimuli are both more effective than reappraising one’s own emotional response. Many neuroimaging studies have contributed to our understanding of emotion regulation, in particular, cognitive reappraisal. In their recent meta-analysis, Buhle and colleagues (2014) surveyed the functional magnetic resonance imaging literature (N = 48 studies) to assess evidence for the idea that blood oxygenation level dependent (BOLD) signal in regions of the brain underlying the cognitive control of behavior (e.g., areas falling within prefrontal, temporal, and parietal cortex) would be higher under conditions requiring participants to reappraise emotion-eliciting situations or responses in order to alter one’s emotion compared to control conditions in which participants respond naturally. They also sought evidence for the idea that BOLD signal in regions of the brain underlying the generation of emotional responses (e.g., amygdala) would exhibit the opposite effect. Results were highly consistent with this interpretation; across studies, bilateral dorsolateral 54       heather l. urry

(DLPFC), ventrolateral (VLPFC), posterior dorsomedial (DMPFC) prefrontal cortex, and posterior parietal cortex were all activated by reappraisal, whereas the amygdala was the only region to exhibit the opposite effect. The prefrontal effects were interpreted to reflect the idea that reappraisal requires manipulation of appraisals in working memory (DLPFC), selection and inhibition of appraisals (VLPFC), and meaning-based semantic processes (DMPFC). The amygdala effect was interpreted to reflect the idea that this region generates emotion to different degrees as a function of the reappraisals one employs. A KEY DISTINCTION: STRATEGY CHOICE AND STRATEGY SUCCESS In much of the initial experimental research on emotion regulation, the regulatory goal was given to participants and the focus of the research was to determine whether, when given the goal and some instructions about how to achieve it, people could alter one or more components of their emotional response. For example, many authors have evaluated the ability to decrease subjectively experienced emotional responses using cognitive reappraisal. In other words, extant research has emphasized strategy success—the degree to which emotional responding is modulated in accordance with the regulatory goal. However, strategy success may be distinguished from strategy choice, at least conceptually. A person who is able to successfully alter her emotions using a particular strategy may or may not choose to use that strategy in emotion-eliciting situations. Conversely, a person who chooses to use a particular strategy may or may not successfully alter her emotions. The question in both cases is, why? What factors direct the choice to use one or more ER strategies in the context of emotion-eliciting situations? And what factors direct whether the use of chosen ER strategies is successful? Many factors may govern strategy choice and/or strategy success. For example, in the domain of strategy choice, Sheppes and colleagues (2014) conducted a series of elegant studies that highlighted three factors: the intensity of the situation, the complexity of generating a reappraisal, and the motivation to alter one’s emotions. Their results indicate that one is more apt to choose reappraisal, a cognitive change strategy, over distraction, an attentional deployment strategy, when the situation is relatively low in intensity, the complexity of generating a reappraisal is low, and/or when one’s motivation is to choose a strategy that is likely to reduce one’s emotional response on a subsequent exposure to the same stimulus. Sheppes and colleagues (2014) proposed that the effect of factors such as the intensity of the situation on emotion regulation strategy choice occurs as a function of a push-pull dance between emotion generative and emotion resources for emotion regulation in older age     

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regulatory processes that draw on the same limited-capacity resource and compete for priority in directing behavior. Cognitive change strategies require one to engage the emotional situation at a late semantic meaning stage of emotion generation in order to rework one’s interpretation of it. However, when one’s goal is to decrease negative emotional responses, attempts to adopt neutral appraisals are in direct conflict with ongoing negative appraisals; as such, they promote a preference for disengagement emotion regulation strategies that occur at an earlier attentional stage of emotion generation. Many other factors might similarly govern strategy choice and/or strategy success, including other aspects of motivation (e.g., whether one’s goal is to regulate one’s own feelings or the extent to which those feelings are expressed for others to see), perceived self-efficacy to alter one’s emotions, the specific emotional state in question (e.g., some discrete emotions may be more malleable than others), one’s knowledge of the existence of different ER strategies and how to use them, one’s skill in putting that knowledge to use, and the resources one has available. While all of these factors are ripe for investigation in the context of all five families of ER strategies, this chapter focuses on the last one, resources. In particular, in light of the available research on this topic, this chapter considers what we know so far about resources for cognitive reappraisal and how both resources and reappraisal are impacted by aging, primarily because cognitive reappraisal is the best studied at this point. RESOURCES FOR COGNITIVE REAPPRAISAL The term resources refers to internal abilities or environmental affordances that help make a particular type of ER possible. In other words, resources reflect aspects of the person or situation that contribute to strategy choice and strategy success. There are many potential resources for cognitive reappraisal. Urry and Gross (2010) proposed, for example, that resources reflecting environmental affordances might include people who encourage beneficial interpretations of emotion-eliciting situations. Resources reflecting internal abilities might include the ability to take a different perspective, working memory to hold the regulatory goal state in mind, and inhibitory processes to resist interference from emotion-generative appraisals. The cognitive resources described above that potentially contribute to reappraisal all reflect abilities that are either part of, or tightly linked with, executive functions. Executive functions comprise a suite of cognitive processes that facilitate goal-directed behavior in complex environments, including attempts to manage emotional states. According to their two-factor theory, Engle and Kane (2004) suggested that executive functions, termed executive 56       heather l. urry

control, involve the maintenance of task goals in active memory and the resolution of response conflict. This meshes well with the proposition that executive functions have at least three components: shifting between tasks or mental sets, updating and monitoring of working memory representations, and inhibiting dominant, automatic, prepotent responses (Miyake et al., 2000). Despite high correlations between different components of executive functions, it is reasonable to think of them as conceptually distinct (Heitz et al., 2006). As such, working memory and inhibitory processes might in some cases contribute differentially to emotion regulation strategy choice and success. At this point, the literature base is relatively small, but there is some direct evidence that a number of resources—particularly cognitive resources—support cognitive reappraisal choice and success. On the strategy choice side, a few studies have taken an individualdifference perspective to examine to what extent higher levels of cognitive resources in the domain of executive functions relate to reported habitual use of cognitive reappraisal. In these studies, habitual use of reappraisal is often indexed by Gross and John’s (2003) Emotion Regulation Questionnaire (ERQ). For example, Joormann and Gotlib (2010) studied people with and without current depression (ages 18–60 years). Participants completed the ERQ and a withinsubject negative affective priming task using word stimuli. Across all members of their sample, a reduction in inhibition of negative material in the priming task was related to less habitual use of cognitive reappraisal. Andreotti and colleagues (2013) studied undergraduates (mean age = 19 years) and found that higher working memory index scores, assessed using the Wechsler Adult Intelligence Scale—Fourth Edition (WAIS–IV) and higher self-reported executive function, assessed using the Behavior Rating Inventor of Executive Function, were associated with higher self-reported cognitive restructuring, assessed as a proportion of the total number of items endorsed on the Responses to Stress Questionnaire [RSQ]). Incidentally, these latter two correlations were not observed for habitual use of cognitive reappraisal measured with the ERQ; proportional scoring of the RSQ restructuring items may help explain the discrepancy. Beyond executive functions, Haga, Kraft, and Corby (2009) examined a construct called private self-consciousness (e.g., insight, self-reflection); in a survey study of psychology undergraduates in Norway, Australia, and the United States (mean age = 23 years), these authors found that higher self-reported insight and selfreflection—which might facilitate awareness of one’s own emotions—were associated with greater self-reported habitual use of cognitive reappraisal. Overall, these studies are consistent with the idea that higher levels of cognitive resources contribute to choosing reappraisal more frequently. On the strategy success side, several studies have taken an individualdifference perspective to examine to what extent higher levels of cognitive resources relate to the success of cognitive reappraisal in a laboratory task. resources for emotion regulation in older age     

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In such tasks, emotions are induced (often via video clips or pictures) and responses (e.g., self-reported emotional experience, expressive behavior, physiology) are compared between a condition in which reappraisal is used to decrease one’s emotion and a condition in which one responds naturally to the emotion-eliciting stimuli. This literature was recently reviewed by Schmeichel and Tang (2014), who identified three studies in which both cognitive ability and emotion regulation were assessed using performancebased measures. In one of the earliest studies, Schmeichel, Volokhov, and Demaree (2008) used a between-subjects design in which undergraduate participants (mean age = ~19 years old) either adopted “a detached and unemotional attitude” (neutral appraisal; p. 1532) in response to a negative, disgust-eliciting video clip or watched the clip without special instructions about how to appraise it (express). Participants also completed two 2-back tasks (verbal and spatial) to index individual differences in working memory capacity. They found that working memory capacity moderated the effect of the reappraisal manipulation on emotional responses; specifically, only people with higher working memory capacity reported lower levels of disgust in the neutral appraisal condition relative to the express condition. This suggests that working memory capacity may be a resource for reappraisal success. The same conclusion was supported in the work by McRae, Jacobs, Ray, John, and Gross (2012). In their study of healthy younger adults ranging in age from 18 to 36 years old, participants completed an operation span task in which they encoded a block of target words in the midst of completing demanding math problems. Participants also completed a within-subjects picture-based reappraisal task in which they followed instructions to respond naturally to unpleasant pictures (look) or to try to tell themselves something about the picture that would make them feel less negative (decrease). For each participant, the authors calculated a reappraisal success score by subtracting ratings of negative emotion in the decrease condition from those in the look condition. By correlating operation-span task scores with reappraisal success scores, McRae et al. found that higher working memory capacity was associated with greater reappraisal success. A third study implicated inhibitory control as another potential resource for reappraisal success. Specifically, in the context of their neuro­ imaging work, Tabibnia et al. (2011) found that better motor inhibitory control, as reflected in faster correct reactions to a “stop” signal, was associated with greater reappraisal success in healthy adults (mean age = 33 years), as reflected in performance on a picture-based task very similar to the ones described previously. This effect was present but not significant among a group of similarlyaged adults diagnosed with methamphetamine dependence that, the authors suggested, occurred at least in part because of differences between the two 58       heather l. urry

groups in right inferior frontal gyrus gray matter. Such differences in gray matter suggest a lack of structural integrity in this brain region, which may underlie the ability to inhibit a prepotent motor response. This is the same VLPFC area that was implicated in meta-analytic work of functional (rather than structural) neuroimaging studies of reappraisal (Buhle et al., 2014). In another study that implicates both working memory and inhibitory control, Winecoff, Labar, Madden, Cabeza, and Huettel (2011) examined reappraisal in younger (mean age = 23 years) and older (mean age = 69 years) adults in a functional magnetic resonance imaging study. In a within-subjects task, emotions were prompted using positive and negative pictures and participants were instructed to use detached reappraisal to decrease their response (reappraise) on some trials and to respond naturally (experience) on other trials while blood-oxygenation level dependent signal was recorded. Prior to scanning, participants completed performance-based tasks assessing a number of cognitive abilities (e.g., simple and choice reaction time, Stroop, digit span forward and backward), some of which assess working memory and inhibitory control. Across all participants, higher levels of cognitive ability, based on a composite score, were associated with greater decreases in reappraisal-related amygdala activation (i.e., lower signal in the reappraise condition relative to the experience condition, consistent with the meta-analytic work described earlier). The authors did not report whether their composite index of cognitive ability was similarly associated with reappraisal success based on self-reported negative emotion either across or within groups. Nevertheless, they reasonably inferred that “cognitive functioning predicts neural markers, if not behavioral manifestations, of emotion regulation” (Winecoff et al., 2011, p. 175). Overall, these four studies converge to suggest that working memory capacity and inhibitory control may be cognitive resources for successful reappraisal. Additional work by Opitz, Lee, Gross, and Urry (2014) implicated other aspects of cognition, specifically fluid cognitive ability, defined by Horn and Cattell (1966) as “processes of reasoning in the immediate situation in tasks requiring abstracting, concept formation and attainment, and the per­ ception and eduction of relations” (p. 255). Opitz, Lee, Gross, and Urry (2014) examined individual differences in cognitive ability and reappraisal success in a sample of younger (mean age = 20 years) and older (mean age = 62 years) adults. In their work, participants completed several subtests of the WAIS–IV to index fluid (Block Design, Digit Span, and Coding) and crystallized (Vocabulary) cognitive ability. The block design task assesses perceptual reasoning, the digit span task is a simple span task that assesses working memory capacity, and the coding task assesses processing speed. Participants also completed a within-subjects reappraisal task in which they were instructed on each trial to use reappraisal to increase or decrease their response to an unpleasant picture or to respond naturally (view). Several dependent variables resources for emotion regulation in older age     

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were recorded to index emotional responding, including subjective emotional experience, expressive behavior, and autonomic physiology. Using multilevel latent variable modeling based on the manifest indicators described above, Opitz et al. created a fluid cognitive ability latent variable and an emotional response latent variable. They found that, across all participants, higher fluid cognitive ability predicted greater reappraisal success. Follow-up analyses suggested that the results were likely driven primarily by perceptual reasoning and processing speed, not by working memory capacity, which may be because of the simple rather than complex nature of the digit span task. Importantly, the resources implicated in reappraisal success above, including working memory capacity, inhibitory control, and fluid cognitive ability, vary between people. For example, there are stable individual differences in working memory capacity such that some people have higher working memory capacity than others (Ilkowska & Engle, 2010), and between-persons variation in working memory capacity is relatively stable over time (e.g., Redick et al., 2012). However, cross-sectional studies suggest that working memory capacity declines as a function of older age (Verhaeghen & Salthouse, 1997). Moreover, as reviewed by Cabeza and Dennis (2013), there is substantial evidence of age-related decline in the frontal lobes of the brain as well as in their executive functions. These authors also allude to an oft-noted finding that older adults exhibit declines in fluid cognitive ability. Indeed, in a recent effort, Salthouse (2014) demonstrated age-related declines in memory, processing speed, reasoning, and spatial visualization, an effect that is moderated by the frequency of assessment. By extrapolation, if resources for emotion regulation vary as a function of aging, then age-related variation should, at least to some extent, predict variation in the ER strategies people choose and their success in using them to alter their emotions. We turn now to limited evidence suggesting, indeed, that there are sometimes age differences in ER, specifically reappraisal, and that these age differences may stem, in part, from age differences in some of the candidate resources discussed above. AGE DIFFERENCES IN REAPPRAISAL There is a growing body of literature that has examined whether older and younger adults exhibit differences in emotion regulation, as reviewed briefly by Urry and Gross (2010). In this chapter, I focus on studies addressing age differences in reappraisal specifically. Some of this work has been conducted in a functional magnetic resonance imaging context in which BOLD signal in the brain was also recorded. In this context, one must carefully consider the meaning of age differences in BOLD signal, since they may 60       heather l. urry

reflect differences in the application of cognitive resources to the task at hand and/or compensatory activation related to neural decline (Cabeza & Dennis, 2013). In the latter case, studies that link neural activation differences with the variables that reflect reappraisal choice or success can be particularly informative. Importantly, there are interesting age differences in emotional responding (Charles & Robinette, 2015). Thus, regardless of the types of dependent variables one is measuring, one must consider whether and how such age differences in emotional responding might contribute to age differences in emotion regulation. Of the few studies that have examined age differences in reappraisal, most have focused to date on the success with which participants use reappraisal to alter their self-reported experience of emotions in accordance with the regulatory goal. In one recent exception, Scheibe, Sheppes, and Staudinger (2015) studied the choice to use distraction versus reappraisal in a picturebased task in older (65–75 years) and younger (19–28 years) adults. In this within-subjects task, participants viewed negative pictures that were low and high in intensity. After receiving training to distinguish distraction and re­appraisal, they viewed each picture briefly (1 second) and were prompted to choose which of the two strategies they preferred to use on a second, longer exposure to the picture (15 seconds). All participants also completed a traditional flanker task to index executive function. As would be expected if older adults have fewer cognitive resources to support reappraisal, older adults less frequently opted for reappraisal over distraction than younger adults, regardless of stimulus intensity. Solidifying the cognitive resource interpretation, they also found that lower levels of executive function across the whole sample were associated with choosing reappraisal over distraction less frequently. Considering studies of age differences in reappraisal success, one of the first was published by Shiota and Levenson (2009). In their work, younger, middle-aged, and older participants (in their 20s, 40s, and 60s, respectively) viewed sad and disgusting video clips. For each video clip, they followed an instruction to either suppress their expressions of emotion or to use re­appraisal to feel less negative emotion. Two forms of reappraisal were examined, detached reappraisal (“adopt a detached and unemotional attitude”) and positive reappraisal (“think about positive aspects of what you are seeing”). Using measures of self-reported emotion as well as physiological measures, the pattern suggested that older adults were less successful using detached reappraisal than younger adults. However, older adults were more successful using positive reappraisal than younger adults, and this was unlikely to be accounted for by age differences in emotional responding. Thus, this study supports the idea of age differences in the success of reappraisal, which seem to be moderated by the specific type of reappraisal in use. As suggested by Shiota and Levenson, this specificity may reflect a difference in the degree to resources for emotion regulation in older age     

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which detached and positive reappraisals draw on cognitive resources such as working memory, inhibition, and fluid cognitive ability. It may also reflect a difference in motivation; older adults may devote more attention to the positive reappraisal condition. More recently, Tucker, Feuerstein, Mende-Siedlecki, Ochsner, and Stern (2012) presented older (60–78 years) and younger (18–30 years) adults a set of negative pictures and asked them on each trial in this within-subjects task to either view the picture and respond naturally or to use reappraisal to decrease their emotional response by doing one of the following: “interpreting the image as not real, thinking about how the event depicted in the image might get better, and seeing the image from a new perspective” (p. 870). After the picture was removed from the screen, participants rated their level of negative emotion. Across age groups, participants reported lower negative emotion when they were instructed to reappraise compared to when they simply viewed the unpleasant pictures. This reappraisal benefit was smaller for the older adults than it was for the younger adults. Overall, this study suggests that older adults may be less successful using reappraisal to decrease their negative emotions. Based on Shiota and Levenson’s (2009) results, one wonders whether participants primarily used the detached form of reappraisal. A conceptually similar finding was reported by Opitz, Rauch, Terry, and Urry (2012), who conducted a functional magnetic resonance imaging study in which older and younger adults viewed negative pictures in the scanner. For each picture, participants followed an instruction to respond naturally (view), to use reappraisal to decrease their negative emotion (decrease), or to use reappraisal to increase their negative emotion (increase). Thus, these authors evaluated the success of reappraisal in enhancing and attenuating the emotional response. Participants rated intensity of their emotional response and whole-brain activation as reflected in BOLD signal was also recorded. Opitz et al. (2012) found that neither younger nor older adults successfully decreased their negative emotions, as evidenced by a nonsignificant difference between the view and decrease conditions. However, for younger adults, the means were in the expected direction (decrease < view); for older adults, the means bordered the threshold for significance in the opposite direction (decrease > view). Moreover, older adults reported significantly higher emotional intensity than younger adults when using reappraisal to increase their response. Interestingly, older adults exhibited lower activation in two prefrontal regions, the DMPFC and the left VLPFC. Lower activation in these regions is significant because both regions are implicated in cognitive control processes; lower activation may signal a reduction in cognitive control. Activation in these two regions collectively helped explain the older-age advantage when using reappraisal to increase negative emotions: Older age was associated with lower activation in DMPFC, which in turn was associated 62       heather l. urry

with lower increase reappraisal success. Older age was also associated with lower activation in VLPFC, but this in turn was associated with greater increase reappraisal success. The mediating effect of DMPFC may indicate an age-related reduction in somatic preparation for action when reappraising to enhance negative emotion. The mediating effect of VLPFC may indicate an age-related reduction in inhibitory processes that would otherwise contradict the “increase negative emotion” goal. Together, these findings confirm the presence of age differences in reappraisal success and suggest that one’s reappraisal goal (i.e., whether to enhance or attenuate one’s emotions) may moderate these effects. Specificity with respect to the reappraisal goal may reflect a difference in the degree to which cognitive resources such as selection and inhibition of appraisals and meaning-based semantic processes are applied on balance. That being said, levels of DMPFC and VLPFC activation were similar for the increase and decrease conditions relative to the view condition, thus the BOLD signal data in this study do not support this conjecture. However, at least one other study has noted activation differences that do support this conjecture (Ochsner, Bunge, Gross, & Gabrieli, 2002). These authors also showed greater self-reported effort when using reappraisal to decrease rather than increase negative emotion. The increase condition specificity of age effects on reported emotional intensity and prefrontal activation may also reflect a difference in motivation; older adults may have devoted more attention to that condition, which is supported by behavioral data reported by Opitz et al. (2012). In the study by Winecoff and colleagues (2011), younger adults reported less negative emotion than did older adults in the decrease reappraisal condition. In addition, while there were no age differences in many prefrontal regions, younger adults did exhibit greater activation in the left inferior frontal gyrus (similar to the ventrolateral prefrontal effect in the study by Opitz et al. (2012) than older adults. Among the latter, greater activation in this left inferior frontal gyrus region was associated with greater decrease reappraisal success on the basis of self-reported negative emotion. Thus, this pattern indicates that younger adults may be more successful using reappraisal to decrease negative emotion, perhaps in part by virtue of greater activation in a region of the brain involved in inhibitory processing; not surprisingly, then, older adults who engage inhibitory processes to a greater degree may enjoy greater reappraisal success. In a more recent neuroimaging study by Allard and Kensinger (2014), older (mean age = 69 years) and younger (mean age = 23 years) adults completed a within-subjects film clip–based task in which they engaged in passive viewing of emotional film clips or regulated their emotional responses (increase positive and decrease negative) using two different strategies, reappraisal and selective attention. For reappraisal, participants resources for emotion regulation in older age     

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were instructed to use detached or positive reappraisal, similar to Shiota and Levenson (2009). For selective attention, participants were instructed to deploy visual attention to the film clips in such a way as to meet the assigned reappraisal goal. As shown in previous studies, younger adults displayed greater BOLD signal in lateral and medial prefrontal regions across both regulation strategy conditions relative to passive viewing. However, there was evidence of an age difference in the extent to which there was common activation across the two strategies; older adults displayed greater reappraisal-related activation in posterior cingulate, anterior cingulate cortex, bilateral VLPFC, and OFC than younger adults, whereas younger adults displayed greater selective attention-related activation than older adults in bilateral DLPFC, VLPFC, and DMPFC. Not at all studies that compare younger and older adults on tasks assessing reappraisal success have demonstrated age differences. A case in point is our recent study (Opitz et al., 2014), described previously. Although we found that higher levels of fluid cognitive ability were associated with greater reappraisal success and that older adults exhibited lower fluid cognitive ability than younger adults, there was no age difference in reappraisal success. Means suggested that older adults were less successful than younger adults but the differences were small and not statistically significant. Importantly, in this work, the two predictors of interest—age and cognitive ability—were confounded. Therefore, this was not an ideal context in which to assess the extent to which age differences and cognitive ability contribute unique variance to reappraisal success. Still, it raises interesting questions about the conditions under which age differences in reappraisal might be observed. Similarly, if studies that successfully unconfound age from cognitive ability identify unique effects of age on reappraisal success over and above cognitive ability, it will be important to identify the processes that are responsible. Candidates may include differences in attention, motivation, and wisdom. In sum, the above studies offer some compelling, albeit limited, evidence that older and younger adults exhibit different patterns of emotion regulation strategy choice and are differentially successful using reappraisal to alter their emotions in the face of emotion-provoking stimuli such as pictures and video clips. The neuroimaging work also suggests that age differences in cognitive control, aspects of which may be resources for reappraisal, as discussed above, may in part explain the age difference in reappraisal. Indeed, as summarized in the meta-analysis described previously, support for hypothesized activation of lateral and dorsal regions of prefrontal cortex and the anterior cingulate in neuroimaging studies of reappraisal led early investigators (e.g., Ochsner et al., 2004) to infer that cognitive control processes, also known as executive functions, are brought to bear in the service of reappraisal. 64       heather l. urry

DIRECTIONS FOR FUTURE RESEARCH In this chapter, I have focused on one particularly well-studied form of emotion regulation, cognitive reappraisal, to illustrate the idea that the strategies we choose to regulate our emotions and the success with which we implement them should depend in part on the extent to which we have adequate levels of required resources. Moving forward, there are three particularly compelling directions for future research on emotion regulation in older age. First, our ability to form strong inferences is limited by the low number of studies that do all of the following: recruit participants across the lifespan, measure or manipulate resources, and measure or manipulate the choice and/or success of specific emotion regulation processes of interest. It will be useful to carry out this work such that we may explicitly test whether levels of resources mediate age differences in reappraisal outcomes. It will furthermore be useful to determine to what extent certain specific cognitive resources (e.g., working memory, inhibition) contribute more or less to different tactics within each family of emotion regulation strategies (e.g., detached reappraisal and positive reappraisal, both members of the cognitive change family). In studies that take an individual-difference perspective, investigators will ideally recruit participants such that age is not systematically associated with naturally occurring levels of the resources of interest. For example, if one wishes to know whether individual differences in working memory capacity and age are each uniquely associated with reappraisal success, one should construct a sample in which working memory capacity is equivalent at all ages. Otherwise, shared variance will be treated as noise rather than a signal of great interest. One should also measure the constructs that would explain any unique effects of age on emotion regulation outcomes, things like motivation and wisdom. Second, my colleagues and I have found it productive to think about emotion regulation in older age from the perspective of the selection, optimization, and compensation with emotion regulation framework (Opitz, Gross, & Urry, 2012; Urry & Gross, 2010). The keystone of this framework is the notion highlighted in this chapter that resources may impact the extent to which one chooses, and is successful using, specific emotion regulation strategies. Importantly, this framework allows for the possibility that having insufficient resources will not necessarily lead to an inability to regulate one’s emotions successfully. Rather, in the absence of sufficient resources, one might compensate by selecting emotion regulation strategies that do not require the resource in question. This is important because the notion of compensation provides a way of potentially understanding why one might observe an age difference in a resource that is important for the emotion regulation strategy in question but no age difference in emotion regulation resources for emotion regulation in older age     

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success. Future studies will be most useful if they are designed to identify not only the resources required for specific emotion regulation strategies but also the compensatory maneuvers people make when resources change. Most of the existing work focuses on between-person variation in resources and cross-sectional differences in age as they relate to emotion regulation outcomes. Moving forward, we’ll also need to focus on within-person variation in resources and longitudinal differences in age. Such contexts may reduce concerns about cohort effects and provide greater sensitivity to detect the ways in which resources contribute to emotion regulation strategy choice, success, and compensatory maneuvers as we age. Third, there is great translational potential in this domain. Specifically, the results of laboratory studies that identify resources for emotion regulation, age differences in emotion regulation, age differences in resources, and how people compensate for changing resources by selecting alternative emotion regulation strategies may have near-term effects on the way in which we treat people who are struggling with disorders characterized by emotional disturbance in older age. For example, if we were to discover that age-related declines in cognitive resources are primarily responsible for age-related variation in emotion regulation strategy choice and success, that would suggest a few options for developing treatments. Specifically, such results might lead us to shore up those resources, optimize older adults’ skills at implementing the emotion regulation strategy, or encourage compensation (i.e., the selection of alternative emotion regulation strategies that might facilitate one’s emotion regulation goals). Future studies that address these possibilities, as well as those that link aging, resources, and emotion regulation to longer term health and well-being outcomes, will bring us closer to making advances that have an enduring impact on daily functioning across the life span. REFERENCES Allard, E. S., & Kensinger, E. A. (2014). Age-related differences in neural recruitment during the use of cognitive reappraisal and selective attention as emotion regulation strategies. Frontiers in Psychology, 5, 296. http://dx.doi.org/10.3389/ fpsyg.2014.00296 Andreotti, C., Thigpen, J. E., Dunn, M. J., Watson, K., Potts, J., Reising, M. M., . . . Compas, B. E. (2013). Cognitive reappraisal and secondary control coping: Associations with working memory, positive and negative affect, and symptoms of anxiety/ depression. Anxiety, Stress, and Coping, 26(1), 20–35. http://dx.doi.org/10.1080/ 10615806.2011.631526 Buhle, J. T., Silvers, J. A., Wager, T. D., Lopez, R., Onyemekwu, C., Kober, H., . . . Ochsner, K. N. (2014). Cognitive reappraisal of emotion: A meta-analysis of

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human neuroimaging studies. Cerebral Cortex, 24, 2981–2990. http://dx.doi. org/10.1093/cercor/bht154 Cabeza, R., & Dennis, N. A. (2013). Frontal lobes and aging: Deterioration and compensation. In D. T. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function (2nd ed., pp. 628–652). New York, NY: Oxford University Press. Charles, S. T., & Robinette, J. W. (2015). Emotion and emotion regulation. In P. A. Lichtenberg & B. T. Mast (Eds.), APA handbook of clinical geropsychology (Vol. 1, pp. 235–258). Washington, DC: American Psychological Association. http:// dx.doi.org/10.1037/14458-011 Engle, R. W., & Kane, M. J. (2004). Executive attention, working memory capacity, and a two-factor theory of cognitive control. In B. Ross (Ed.), The psychology of learning and motivation (Vol. 44, pp. 145–199). New York, NY: Elsevier. Gross, J. J. (1998). Antecedent- and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology, 74, 224–237. http://dx.doi.org/10.1037/0022-3514.74.1.224 Gross, J. J. (2014). Emotion regulation: Conceptual and empirical foundations. In J. J. Gross (Ed.), Handbook of emotion regulation (2nd ed., pp. 3–20). New York, NY: Guilford Press. Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85, 348–362. http://dx.doi.org/10.1037/0022-3514.85.2.348 Haga, S. M., Kraft, P., & Corby, E. (2009). Emotion regulation: Antecedents and well-being outcomes of cognitive reappraisal and expressive suppression in cross-cultural samples. Journal of Happiness Studies, 10, 271–291. http://dx.doi. org/10.1007/s10902-007-9080-3 Heitz, R. P., Redick, T. S., Hambrick, D. Z., Kane, M. J., Conway, A. R. A., & Engle, R. W. (2006). Working memory, executive function, and general fluid intelligence are not the same. Behavioral and Brain Sciences, 29, 135–136. http://dx.doi. org/10.1017/S0140525X06319036 Horn, J. L., & Cattell, R. B. (1966). Refinement and test of the theory of fluid and crystallized general intelligences. Journal of Educational Psychology, 57, 253–270. http://dx.doi.org/10.1037/h0023816 Ilkowska, M., & Engle, R. W. (2010). Trait and state differences in working memory capacity. In A. Gruszka, G. Matthews, & B. Szymura, Handbook of individual differences in cognition: Attention, memory, and executive control (pp. 295–320). New York, NY: Springer Science + Business Media. http://dx.doi.org/10.1007/ 978-1-4419-1210-7_18 Jackson, D. C., Malmstadt, J. R., Larson, C. L., & Davidson, R. J. (2000). Suppression and enhancement of emotional responses to unpleasant pictures. Psychophysiology, 37, 515–522. http://dx.doi.org/10.1111/1469-8986.3740515 Joormann, J., & Gotlib, I. H. (2010). Emotion regulation in depression: Relation to cognitive inhibition. Cognition and Emotion, 24, 281–298. http://dx.doi.org/ 10.1080/02699930903407948 resources for emotion regulation in older age     

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McRae, K., Jacobs, S. E., Ray, R. D., John, O. P., & Gross, J. J. (2012). Individual differences in reappraisal ability: Links to reappraisal frequency, well-being, and cognitive control. Journal of Research in Personality, 46, 2–7. http://dx.doi. org/10.1016/j.jrp.2011.10.003 Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100. http://dx.doi.org/10.1006/cogp.1999.0734 Ochsner, K. N., Bunge, S. A., Gross, J. J., & Gabrieli, J. D. E. (2002). Rethinking feelings: An fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience, 14, 1215–1229. http://dx.doi.org/10.1162/089892902760807212 Ochsner, K. N., Ray, R. D., Cooper, J. C., Robertson, E. R., Chopra, S., Gabrieli, J. D. E., & Gross, J. J. (2004). For better or for worse: Neural systems supporting the cognitive down- and up-regulation of negative emotion. NeuroImage, 23, 483–499. http://dx.doi.org/10.1016/j.neuroimage.2004.06.030 Opitz, P. C., Gross, J. J., & Urry, H. L. (2012). Selection, optimization, and compensation in the domain of emotion regulation: Applications to adolescence, older age, and major depressive disorder. Social and Personality Psychology Compass, 6, 142–155. http://dx.doi.org/10.1111/j.1751-9004.2011.00413.x Opitz, P. C., Lee, I. A., Gross, J. J., & Urry, H. L. (2014). Fluid cognitive ability is a resource for successful emotion regulation in older and younger adults. Frontiers in Psychology, 5, 609. http://dx.doi.org/10.3389/fpsyg.2014.00609 Opitz, P. C., Rauch, L. C., Terry, D. P., & Urry, H. L. (2012). Prefrontal mediation of age differences in cognitive reappraisal. Neurobiology of Aging, 33, 645–655. http://dx.doi.org/10.1016/j.neurobiolaging.2010.06.004 Redick, T. S., Broadway, J. M., Meier, M. E., Kuriakose, P. S., Unsworth, N., Kane, M. J., & Engle, R. W. (2012). Measuring working memory capacity with automated complex span tasks. European Journal of Psychological Assessment, 28, 164–171. http://dx.doi.org/10.1027/1015-5759/a000123 Salthouse, T. A. (2014). Frequent assessments may obscure cognitive decline. Psychological Assessment, 26, 1063–1069. http://dx.doi.org/10.1037/pas0000007 Scheibe, S., Sheppes, G., & Staudinger, U. M. (2015). Distract or reappraise? Age-related differences in emotion-regulation choice. Emotion. http://dx.doi. org/10.1037/a0039246 Schmeichel, B. J., & Tang, D. (2014). The relationship between individual differences in executive functioning and emotion regulation: A comprehensive review. In J. P. Forgas & E. Harmon-Jones (Eds.), The control within: Motivation and its regulation (pp. 133–151). New York, NY: Psychology Press. Schmeichel, B. J., Volokhov, R. N., & Demaree, H. A. (2008). Working memory capacity and the self-regulation of emotional expression and experience. Journal of Personality and Social Psychology, 95, 1526–1540. http://dx.doi.org/10.1037/ a0013345

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Sheppes, G., Scheibe, S., Suri, G., Radu, P., Blechert, J., & Gross, J. J. (2014). Emotion regulation choice: A conceptual framework and supporting evidence. Journal of Experimental Psychology: General, 143(1), 163–181. http://dx.doi. org/10.1037/a0030831 Shiota, M. N., & Levenson, R. W. (2009). Effects of aging on experimentally instructed detached reappraisal, positive reappraisal, and emotional behavior suppression. Psychology and Aging, 24, 890–900. http://dx.doi.org/10.1037/ a0017896 Speisman, J. C., Lazarus, R. S., Mordkoff, A., & Davison, L. (1964). Experimental reduction of stress based on ego-defense theory. The Journal of Abnormal Psychology, 68, 367–380. http://dx.doi.org/10.1037/h0048936 Tabibnia, G., Monterosso, J. R., Baicy, K., Aron, A. R., Poldrack, R. A., Chakrapani, S., . . . London, E. D. (2011). Different forms of self-control share a neurocognitive substrate. The Journal of Neuroscience, 31, 4805–4810. http://dx.doi.org/10.1523/ JNEUROSCI.2859-10.2011 Tucker, A. M., Feuerstein, R., Mende-Siedlecki, P., Ochsner, K. N., & Stern, Y. (2012). Double dissociation: Circadian off-peak times increase emotional reactivity; aging impairs emotion regulation via reappraisal. Emotion, 12, 869–874. http://dx.doi.org/10.1037/a0028207 Urry, H. L., & Gross, J. J. (2010). Emotion regulation in older age. Current Directions in Psychological Science, 19, 352–357. http://dx.doi.org/10.1177/0963721410388395 Verhaeghen, P., & Salthouse, T. A. (1997). Meta-analyses of age-cognition relations in adulthood: Estimates of linear and nonlinear age effects and structural models. Psychological Bulletin, 122, 231–249. http://dx.doi.org/10.1037/00332909.122.3.231 Webb, T. L., Miles, E., & Sheeran, P. (2012). Dealing with feeling: A meta-analysis of the effectiveness of strategies derived from the process model of emotion regulation. Psychological Bulletin, 138, 775–808. http://dx.doi.org/10.1037/a0027600 Winecoff, A., Labar, K. S., Madden, D. J., Cabeza, R., & Huettel, S. A. (2011). Cognitive and neural contributors to emotion regulation in aging. Social Cognitive and Affective Neuroscience, 6, 165–176. http://dx.doi.org/10.1093/scan/nsq030

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4 REGULATORY FLEXIBILITY AND ITS ROLE IN ADAPTATION TO AVERSIVE EVENTS THROUGHOUT THE LIFESPAN CHARLES L. BURTON AND GEORGE A. BONANNO

As we age, we are constantly confronted with stressful situations that vary in quality and severity. For example, most of us are exposed to multiple stressors, including violent or life-threatening events, at different points in our lifespan (LaLande & Bonanno, 2011; Ozer, Best, Lipsey, & Weiss, 2003). What, then, are the psychological mechanisms that help us regulate our emotions and behaviors in preparing for divergent stressor events that may range from an important high school test early in life to adjusting to the death of a spouse in our more advanced years? Traditional theories of selfregulatory behaviors (e.g., coping, emotion regulation) viewed individuals as primarily static in their response to stressful situations and considered certain behaviors as being inherently adaptive and mature and others as maladaptive and immature (Vaillant, 1977). However, research in the coping and emotion regulation literatures suggests that the efficacy of certain self-regulatory behaviors is far from uniform (Folkman & Moskowitz, 2004; Webb, Miles, & Sheeran, 2012) and that individuals are fairly inconsistent in their use http://dx.doi.org/10.1037/14857-005 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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of coping strategies from one situation to the next (Cheng, 2001; Folkman, Lazarus, Dunkel-Schetter, Delongis, & Gruen, 1986). Research increasingly suggests that the reason for this within-person variability is that individuals choose their self-regulatory strategy according to the details of the stressful situation at hand (Bonanno, Papa, Lalande, Westphal, & Coifman, 2004; Sheppes et al., 2014). The convergence of these studies has led researchers to challenge the static assumption that specific regulatory behaviors are inherently adaptive or maladaptive, which we have elsewhere termed “the fallacy of uniform efficacy” (Bonanno & Burton, 2013), and to instead investigate how the relative utility of regulatory behaviors may change depending on who is using them and in which contexts they are used (Aldao, 2013). This chapter is dedicated to one specific branch of this scientific movement: the investigation of regulatory flexibility (Bonanno & Burton, 2013). OVERVIEW AND GENERAL BACKGROUND The underlying assumption of flexibility is that the static use of any specific self-regulatory behavior is maladaptive, whereas changing behavior to be able to address the specific challenges that change from one stressful situation to the next is adaptive. This reasoning extends especially to the process of aging, as the stressors we encounter and our means of dealing with them and our emotions are likely to change (Brandtstädter & Renner, 1990; Brennan, Holland, Schutte, & Moos, 2012; Rodin, 1986). While the emphasis on flexibility and its importance in coping and emotion regulation is not new (Barrett & Gross, 2001; Bonanno et al., 2004; Cole, Michel, & Teti, 1994), direct research into aspects that constitute flexibility has only recently begun, and studies on the topic have varied significantly in the time scale used and the behaviors measured. Recently, in an attempt to summarize and integrate the extant research, we argued that regulatory flexibility is unlikely to be a single uniform construct but rather a collection of ongoing and multifaceted processes that are activated in response to stress. More specifically, we proposed that regulatory flexibility can be understood in terms of three sequential components, where individuals differ in their ability to enact each component (Bonanno & Burton, 2013). The first component of regulatory flexibility is context sensitivity, which is the ability to identify and understand the environmental demands presented in a specific stressful situation. This information is then used to inform the second component in which a person determines the regulatory strategy most appropriate to meet the situational demands. Because not everyone is equally able to enact all regulatory strategies, this component is influenced heavily by the extent of a person’s self-regulatory repertoire. 72       burton and bonanno

Finally, once a regulatory strategy is chosen, it is important to monitor its efficacy to meet situational demands and to modify it or chose another strategy as needed. This component depends on the individual’s ability to monitor and incorporate situational feedback. In the sections that follow, we consider each of these component abilities and their relation to emotional well-being in greater detail. REVIEW OF THE CURRENT RESEARCH Flexibility Through Context Sensitivity Regulatory systems are widely understood from a cost–benefit evolutionary perspective (Kalisky, Dekel, & Alon, 2007; Orr, 2005), in which the most likely adaptations are those that provide the greatest benefit at the smallest cost. Of course, no adaptation is perfect, and even the most beneficial adaptations come with at least some cost. The extent of those costs depends on context (e.g., Tooby & Cosmides, 1990). Extending this line of reasoning to coping and emotion regulation suggests that the success or failure of any particular behavior will depend on when and why it was used (Aldao, 2013; Bonanno & Burton, 2013; Folkman, 1984; Gross, 1998; McCrae, 1984; Sheppes et al., 2014; Tamir, 2009). This is why the first step in flexible self-regulation necessarily involves evaluating what task(s) need to be addressed in a given stressful situation, and what type of behavior is best suited to accomplish them. This process does not occur in a vacuum, but rather a background of ongoing appraisal processes involving general monitoring of goals (Carver & Scheier, 1982), social interactions (Taylor, Wayment, & Carrillo, 1996), affect and mood (Russell & Barrett, 1999), and preexisting motivations (Ryan & Deci, 2000). A situation’s demands and opportunities may not always be obvious. While some stressors provide relatively clear contextual information about what type of behavior would best address the situation, others are more complex and may require a blend of strategies and consequently a more nuanced assessment on the part of the individual experiencing the stressor. The activation and experience of emotion is one of the first observable reactions to stress exposure. A widely agreed-upon aspect of emotions is that they are context bound, that is, they are thought to have evolved to help direct behavior to address specific situations (Cole et al., 1994; Tooby & Cosmides, 1990). Thus, it is important that a certain emotion occurs in situations in which the problems at hand are best addressed by behaviors initiated by that emotion. Anger, for example, is often activated when a stressful situation is perceived as being unjust or caused by another person (Lazarus, 1991). In this regard, the experience of anger would be beneficial and could facilitate regulatory flexibility and its role in adaptation     

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adaptive behavior in a context in which one’s personal resources are being infringed upon by an aggressor. Conversely, if anger is expressed in a situation where developing social relationships with others is important, it can impede the development of social bonds and thus be considered maladaptive (Bonanno & Keltner, 1997; Keltner, Ellsworth, & Edwards, 1993). A large proportion of the research on context sensitivity in emotion has focused on deficits in this construct, or context insensitivity (Coifman & Bonanno, 2010). The inability to respond in a context-sensitive fashion can be considered a form of emotion dysregulation that, in extreme cases, is characteristic of psychopathology (Cole et al., 1994; Davidson, 2000; Kring, 2008). One manifestation of context insensitivity has been found in major depressive disorder. Using standardized film stimuli, Rottenberg, Kasch, Gross, and Gotlib (2002) measured participants’ subjective levels of sadness across a series of video clips. Patients with depression reported similar levels of sadness as nondepressed patients following a “sad” video clip, but they reported significantly more sadness than their nondepressed counterparts in a neutral or positive video clip. These findings held even when controlling for initial levels of sadness, which suggests that it was not simply that depressed individuals felt sadder, but that they were unable to modulate their sadness across variable contexts. Similar studies focusing on facial expressions during bereavement found that individuals with complicated grief, another mood-regulation disorder, were less variable in expressing sadness than their healthy bereaved counterparts. These effects were demonstrated using both idiographic interview contexts (Diminich & Bonanno, 2014) and experimental film contexts (Bullock & Bonanno, 2013). Other studies have longitudinally linked impoverished emotional context sensitivity with symptom development, severity, and recovery (Coifman & Bonanno, 2010; Rottenberg, Gross, & Gotlib, 2005). Positive emotions have also been associated with context effects. Persons with bipolar disorder, for example, experience strong positive emotions but are unable to modulate their mood between positive and nonpositive contexts (Gruber, Eidelman, Johnson, Smith, & Harvey, 2011). A similar difficulty in modulating positive emotions across contexts has also been observed for individuals at risk of developing bipolar disorder (Gruber, Johnson, Oveis, & Keltner, 2008). As intimated above, depressed individuals react less positively to positive contexts than nondepressed individuals (Gruber, Oveis, Keltner, & Johnson, 2011; Rottenberg et al., 2002). Interestingly, symptomatic bereaved persons who were able to modulate their positive emotional reactions in appropriate contexts reported less symptoms of depression at a later time (Coifman & Bonanno, 2010). Just as experiencing a diverse array of emotions is important across life’s many stressors, employing coping behaviors that are appropriate for addressing the relevant situation and emotion experienced is also important. 74       burton and bonanno

Individuals differ significantly in their coping behavior use, which is dependent upon how they appraise their current context. Perhaps the most widely researched dichotomy by which people vary their coping behaviors is whether they appraise the stressful context as being controllable or uncontrollable (Folkman, 1984). Multiple studies have further suggested that the ability to accurately discern whether a situation is controllable or not will moderate the efficacy of the coping behavior that is ultimately employed (Cheng & Cheung, 2005; Cheng, Chiu, Hong, & Cheung, 2001; Conway & Terry, 1992). In their numerous studies on coping flexibility in and outside the workplace, Cheng and colleagues measured participants’ ability to determine contextual cues by assessing to what extent participants responses to hypothetical stressors (e.g., “You are visiting a clinic for a checkup and learning that you have a treatable form of cancer”) agreed with responses that were previously rated as being the most adaptive by a panel of independent raters. The degree to which individuals responses matched a priori assessments of these contexts has been shown to predict more flexible variations in coping strategies (Cheng, 2003; Cheng & Cheung, 2005) as well as greater cognitive complexity (Cheng et al., 2001). Flexibility Through Repertoire The ability to discern the impinging demands of a stressful situation helps people to select an adaptive regulatory strategy, and less sensitivity to contextual demands will in turn make it increasingly difficult to select an appropriate regulatory strategy. Regardless of the quality of an appraisal, addressing a stressful situation still requires the person experiencing the stressor to enact some self-regulatory behavior, and their capacity to execute that behavior is dependent on the second component of flexibility: the quality and breadth of their self-regulatory repertoire of strategies. Such strategies may include cognitive reappraisal, seeking social support, and any other type of behavior employed by individuals experiencing a stressful situation. The underlying theory behind the importance of repertoire is that even the most context-sensitive person will struggle in stressful contexts that require a certain action or behavior that is not included in that person’s behavioral repertoire. For example, in the aftermath of losing a spouse in older age, it is widely believed that healthy adjustment requires making use of one’s social resources (Dimond, Lund, & Caserta, 1987; Vanderwerker & Prigerson, 2004). If a bereaved person lacks social skills or is otherwise cut off from their social network, they will likely struggle in the wake of their spouse’s death. The ability to draw on social resources is just one of many self-regulatory behaviors that are possible to enact during a stressful event, and the research on repertoire has not yet reached consensus on the best way to measure this regulatory flexibility and its role in adaptation     

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construct. At present, the most common methods for assessing repertoire have been to measure (a) the size of the person’s repertoire, (b) the temporal variability of strategy use, and (c) the categorical variability of strategy use within the person’s repertoire. Repertoire Size The total number of strategies that encompass an individual’s selfregulatory repertoire is often measured by self-report. For example, one study measuring participants’ general use of coping strategies found that individuals who used a larger number of strategies were generally less distressed and were buffered from greater levels of life stress. In a context-specific study, Orcutt, Bonanno, Hannan, and Miron (2014) assessed posttraumatic stress disorder symptoms of students before and after a mass shooting, while also measuring their ability to access different emotion regulation strategies. They observed that individuals who were able to use more emotion regulation strategies were more likely to be resilient in the aftermath of the trauma. Repertoire Categorical Variability A second approach for measuring repertoire is assessing an individual’s ability to use diverse types of self-regulatory behaviors. In contrast to assessing a repertoire’s size, measuring a repertoire’s categorical variability places greater emphasis in how certain behaviors cluster together according to relevant attributes, such as the social dimensions of a certain behaviors (e.g., interpersonal vs. intrapersonal) or their intended functions (e.g., problemfocused vs. emotion-focused). Assessing repertoire through measuring categorical variability has been especially common in contexts of traumatic life events (Bonanno, 2004, 2005). This approach is useful for these events because the challenges, emotional and otherwise, are intensified, prolonged, and often require significantly different types of self-regulation across time. For example, the dual-process model of bereavement emphasizes the necessity of both lossoriented coping strategies that deal with the immediate and practical consequences of the loss, and restoration-oriented coping strategies that address secondary stressors that are also consequences of bereavement (Stroebe & Schut, 1999). Another group of studies assessing individual differences in repertoire categorical variability has focused on the larger contextual umbrella of potentially traumatic events, employing the Perceived Ability to Cope With Trauma scale (PACT; Bonanno, Pat-Horenczyk, & Noll, 2011). This questionnaire consists of items designed to measure sets of distinct and contrasting coping strategies (e.g., “Distract myself to keep from thinking about the event” vs. “Face the grim reality head on”). These items, when applied 76       burton and bonanno

through exploratory and confirmatory factor analysis, yielded two main factors similar to the loss and restoration-oriented coping styles explored by Stroebe and Schut (1999). The first, trauma focus, consists of coping behaviors that aim to address the traumatic event itself, such as fully experiencing the event’s emotional consequences or to focused on the event and think critically about what has occurred. In contrast, the forward focus factor comprises coping strategies that aim to distract or disengage from the event. These behaviors can include maintaining previous (i.e., pretrauma) goals and plans, attending to the needs of others, diminishing negative or otherwise unwanted emotions via distraction and amusement. These scales can be used in one of two ways. One method involves first assessing the trauma focus and forward focus scales and then examining their suitability to address changes in contextual demands. A second method is to combine the scales using various formulas to create an index of repertoire flexibility that indicates the extent participants are able to engage in both types of coping. For example, one such formula involves adding the scales together and subtracting the absolute value of the difference. Using this approach, greater use of both types of coping will result in the highest repertoire flexibility score, while greater use of one type of coping more than the other will produce a lower repertoire flexibility score. One of the first studies to use the PACT did so within a community of Israeli adults with high potential trauma exposure to terrorist violence. Individuals who were high in repertoire flexibility had relatively few symptoms of posttraumatic stress, regardless of whether they had high levels of exposure to terrorist violence. In contrast, individuals who were relatively low in repertoire flexibility had markedly greater levels of posttraumatic stress symptoms when exposed to higher levels of terrorist violence (Bonanno, Pat-Horenczyk, & Noll, 2011). Another study employing the PACT sampled college students exposed to more diverse stressors (Galatzer-Levy, Burton, & Bonanno, 2012), and found that the most well-adjusted students had higher repertoire flexibility. Finally, in a third sample measuring coping flexibility in the context of loss, bereaved individuals who were measured as having high repertoire flexibility on the PACT were asymptomatic and similar to a control group of married individuals who had not lost their spouse. Bereaved individuals meeting diagnostic criteria for Complicated Grief, however, were less flexible in their repertoire of coping behaviors and in particular were less able to use forward focus coping (Burton et al., 2012). In another study that employed a different approach to measuring catego­rical variability in adolescent’s repertoires, Lougheed and Hollenstein (2012) conducted a latent profile analysis on a variety of emotion regulation types from which they derived six main categories of self-regulatory strategies. Adolescents whose emotion regulation repertoires consisted of a greater number of the six identified types evidenced better functioning, regulatory flexibility and its role in adaptation     

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whereas adolescents with comparatively worse functioning were more likely to employ fewer self-regulatory categories. Many of the studies of repertoire reviewed thus far have relied on selfreports, but investigations of categorical variability have also employed experimental approaches that seek to measure how participants vary in their use of strategies that either increase (up-regulate) or decrease (down-regulate) their emotional experience. Neuroscientific research, for example, has shown that each type of regulation is associated with unique areas of neural activation (Kim & Hamann, 2007; Ochsner et al., 2004), even though they recruit common brain regions suggestive of at least some similar underlying processes. Extending this line of research to facial behavior, Bonanno et al. (2004) measured individual differences in the ability to enhance and suppress emotional expression. Participants were shown a series of emotionally evocative photos that consisted of images that ranged in their positive and negative valence. Participants were also informed that another person in an adjacent room would watch them from a monitor and try to guess what emotions the participant was experiencing. Given this information, participants were instructed to regulate their emotions across different trials to either help or hinder the observer. In the control condition, participants were informed to behave normally. In the enhance condition, participants were instructed to increase their emotional expression to make it clear what it was they were feeling. Finally, in the suppress condition, participants were instructed to conceal their emotion so that it would be difficult for another person to guess what they were feeling. Raters blind to the hypotheses of the study and the experimental conditions then coded videotapes of the participant’s facial expressions during the task. Because each participant engaged in all conditions, Bonanno et al. (2004) were able to create index scores of the extent a person was able to enhance (enhancement condition minus control condition) or suppress (control condition minus suppression condition) their emotional expression relative to their own behavior in the control condition. This design also made it possible to create an overarching flexibility score that indicated how diverse a participant’s repertoire was based upon their abilities in these two categories. To determine if participants’ expressive regulatory repertoire predicted adjustment to stress, Bonanno et al. (2004) measured these abilities in a sample of New York City college students following the September 11th terrorist attacks. The students’ distress levels were measured immediately following the attacks along with their expressive flexibility, and then their distress was measured again 2 years later. The results showed that both the ability to enhance emotional expression and the ability to suppress emotional expression independently predicted reduced distress 2 years after the terrorist attack, even when controlling for participants’ baseline distress. Moreover, 78       burton and bonanno

the overarching index score of each individual’s expressive repertoire was even more strongly associated with better adjustment 2 years after the event. In contrast, participants who evidenced a less diverse expressive repertoire had comparatively worse adjustment at follow-up. A separate study investigating expressive repertoire using the same sample observed that the ability to enhance and suppress emotion appear to have a trait-like quality (Westphal, Seivert, & Bonanno, 2010). In retesting the same New York City students 3 years later with the same experimental paradigm, the authors observed participants’ ability and flexibility had surprisingly high test-retest reliability. They also observed that participants with greater expressive repertoire again had better overall psychological adjustment. In their follow-up study, Westphal et al. (2010) introduced a subliminal social threat prime in the expressive regulation task to further examine expressive repertoire in threatening and nonthreatening social contexts, while continuing to measure each participant’s life stress since the terrorist attack. Once again, the relationship between adjustment and expressive repertoire was strongest under conditions of high stress exposure, that is, in the threat priming and among participants with the highest levels of life stress. In the most recent study to use the same experimental paradigm, bereaved individuals with complicated grief disorder had less expressive repertoire than bereaved asymptomatic counterparts (Gupta & Bonanno, 2011). The complicated grief group also had less expressive repertoire than a comparable group of married individuals. Repertoire Temporal Variability The third common method of assessing repertoire has been to measure changes in participants’ regulatory strategies across time and stressful situations. Gintner, West, and Zarski (1989) measured shifts in coping across time by examining students’ coping strategy use before they took a stressful examination and then again before the release of the exam’s results. They stratified students on resourcefulness, a dimension previously associated with use of a broader repertoire of coping strategies (Rosenbaum, 1980). The students who scored high on resourcefulness modulated their use of problem-focused coping from before to after the exam, whereas those scoring low on resourcefulness evidenced no change in their coping behavior and further­more reported higher levels of stress at both time points (Gintner et al., 1989). In a more recent and elaborate study of temporal variability in repertoire, Cheng (2001) identified groups of individuals that were distinguished by variability in perceptions of the kinds of coping strategies they would use across different types of situations. Those who were described as flexible copers used different types of coping strategies and modified their coping strategy use based on changes to contextual demands. Moreover, this flexible group regulatory flexibility and its role in adaptation     

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also reported themselves as more efficacious in their coping attempts and evidenced less depressive symptoms when compared with other participants cross-sectionally and longitudinally. Other studies that measured variability of coping strategy use across time have observed that individuals with a more flexible repertoire had improved adjustment at later time points (Gall, Evans, Bellerose, 2000; Gall, Guirguis-Younger, Charbonneau, & Florack, 2009). Flexibility Through Feedback Responsiveness The ability to assess the situational demands of a stressful event and the ability to enact a regulatory strategy that befits those demands are important components of regulatory flexibility. However, initial appraisal and regulatory efforts may be hampered by situational complexity, and in some cases it may be difficult or even impossible to select a single strategy that best addresses a given stressor. Situational ambiguity thus makes the self-regulatory process akin to a game of trial and error in which the person adjusting to the stress must decide whether or not their initial attempts to self-regulate need to be modified. This unavoidable scenario necessitates a third component of flexibility that involves monitoring and responding to feedback (i.e., the ability to determine whether a regulatory strategy had been effective and to adjust that strategy if it is not). The ability to monitor feedback has long been considered an important element of self-regulation and control theory (Carver & Scheier, 1982), and its important role has been acknowledged by both coping (Folkman & Moskowitz, 2004) and emotion regulation researchers (Aspinwall & Taylor, 1997; Scherer, 2001). The operational definition of individual differences in the use of feedback shares some similarity to the context sensitivity and repertoire components. However, the feedback component is distinguished in its function. The act of monitoring feedback is similar to the initial context sensitivity component in that both involve evaluative processes. However, the two processes differ crucially in their goals and timing. The aim of evaluation in the context sensitivity process is to determine which strategy might be selected to help maintain self-regulation, whereas the aim of evaluation during the feedback stage is to determine whether the selected strategy has been effective. When feedback suggests that the selected regulatory strategy has been effective, that strategy will likely be maintained or increased in effort. There may also be a renewed contextual appraisal to determine whether the impinging situational demands are still relevant, and whether the selected strategy is still necessary. However, in situations where feedback suggests that a selected regulatory strategy has not been effective, or where it appears that it might be useful to switch to another strategy to better maximize self-regulation, the breadth of an individual’s repertoire will again become crucial. In this case, there will be a need to select an 80       burton and bonanno

alternative self-regulatory strategy that is better suited to address the stressor context (Kalisch, 2009). In these examples, the act of incorporating feedback can be interpreted as prompting an individual to “start over” in the flexibility process so that they might attempt to reevaluate and/or readdress the stressful situation. The possible nuances of feedback use are illustrated in an implementationmaintenance model of reappraisal proposed by Kalisch and colleagues (Kalisch, 2009; Paret et al., 2011). In this model, effective regulation of emotion necessitates “continuous response adjustments” (Kalisch, 2009, p. 1217), and that flexibility in emotion regulation requires both the implementation and the maintenance regulatory strategy. If feedback indicates the need to shift appraisals toward more positive direction, a reappraisal strategy may be implemented early in the response to a stressful event and continuously adjusted to meet the desired aim. Should the attempted reappraisal be effective but the targeted emotion is strong, it may be necessary to repeatedly re­adjust the initial appraisal. However, if feedback indicates that the re­appraisal has not been effective, a later stage of reappraisal is required to achieve the desired effect (Paret et al., 2011). There are many other ways that feedback in self-regulation might come into play. Consider, for example, a man who has a fear of bridges but has recently started a new job where his commute requires him to take a bus across a river twice a day. Although he would prefer to move closer to his office, the cost of moving is prohibitive, and thus he decides to confront his fears by carpooling across the bridge on a daily basis with a coworker. During one particularly windy day, when it is his turn to drive, he feels his car shifted slightly by a strong gust of wind. His anxiety begins to swell, and he realizes he will need to regulate his anxiety so that he may continue to focus on safely driving across the bridge. He considers his repertoire of emotion regulation behaviors to determine what action to take and decides to distract himself by turning on the radio. Halfway into the song, he notices that his heart is continuing to race, and his carpool coworker asks if he is feeling okay. Now aware that he is not meeting his original goal of regulating his anxiety through distraction, he decides to try a new strategy. He instead employs cognitive reappraisal to remind himself that modern bridges, like the one he is currently driving on, are specially designed to withstand much higher wind speeds, and that the bridge has endured much stormier weather without incident. Feeling assured and less anxious, he safely completes his drive to work. The character in this story illustrates two important sources of feedback. Internal feedback is the ability to detect physiological cues (e.g., heart rate in the above example) to monitor shifts in affective states. Although there is surprisingly little research on interoceptive modes of evaluation, one recent study provided evidence toward an internal feedback model by linking regulatory flexibility and its role in adaptation     

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sensitivity to internal states with improved emotion regulation (Füstös, Gramann, Herbert, & Pollatos, 2013). Specifically, Füstös et al. (2013) measured individual differences in participants’ ability to accurately count their heartbeat during three brief periods of time, and used this measure to predict the same participants’ emotional intensity when exposed to emotionally evocative stimuli while attempting to use one of two regulation strategies. They found that the individuals who had greater interoceptive awareness (i.e., were more accurate in detecting their heartbeat) were also better able to decrease both objective and subjective measures of affect. Another mechanism by which individuals may monitor and modulate their self-regulatory strategies is through the use of social feedback. This form of feedback has long been accepted as critical in the development of self-regulatory skills (Cole, Michel, & Teti, 1994; Ryan & Deci, 2000) and has been shown to have an impact on emotion regulation (Coan, Schaefer, & Davidson, 2006) and coping behaviors (Taylor & Armor, 1996). Facial expressions of emotion, for example, both communicate the emotion and, in turn, influence other people’s behavior (Keltner & Haidt, 1999). The social interaction model (Côté, 2005), an emotion regulation model from the organizational psychology literature, posits that the communication of emotion instigates an ongoing reciprocal feedback loop in which an emotional expression produces emotional responses in receivers, which in turn elicit an emotional expression and emotional reaction in the person who expressed the original emotion. This ongoing emotional feedback between two or more persons will invariably alter the regulatory behaviors used by some or even all of the parties involved in the cycle as they assess and address the changes taking place in their social and nonsocial environments. By extension, individuals who struggle with social interactions, such as persons who have sustained lesions to the orbitofrontal lobe, have been found to struggle in their use of social feedback to regulate their emotions (Beer, Heerey, Keltner, Scabini, & Knight, 2003). The incorporation of social or internal feedback in self-regulation is useful only to the extent that a person is actually able to apply this information by changing their self-regulatory strategies. A questionnaire developed by Kato (2012) focused on this issue, defined specifically as “the ability to discontinue an ineffective coping strategy and produce and implement an alternative coping strategy” (p. 262). Factor analysis of this scale revealed two underlying factors. The first was an evaluation coping factor that taps into the ability to evaluate coping efficacy similar to the other studies on feedback we have described. The second factor was labeled as the adaptive coping component of flexibility and measures the ability to change coping responses by stopping one strategy and starting another. Both of these factors predicted better performance on an insight-based problem-solving task as well as better mental health outcomes. 82       burton and bonanno

Flexibility and Aging As the studies discussed thus far indicate, individuals experience a wide array of stressful events over the course of their lives, and flexibility in self-regulation plays an important role in determining emotional state and psychological health in the aftermath of adversity in all of its heterogeneous forms. A crucial question that has only just begun to be examined is whether the mechanisms that contribute to regulatory flexibility change across the lifespan. In other words, do we become more or less flexible as we age? One of the most widely known psychological consequences of age is the decline in several fluid cognitive abilities (Verhaeghen & Salthouse, 1997), some of which are implicated in emotional regulation, including memory and executive functioning. For example, studies suggest that aging-related impairments in cognitive control are associated with deterioration of the prefrontal cortex (Hedden & Gabrieli, 2004). The prefrontal region has in turn been closely linked to the ability to shift strategies and behaviors in response to changing environmental features (Ragozzino, 2007), which is a critical component of flexibility. Although these age-related changes might suggest that older adults are less able to regulate their emotions, a growing body of research provides evidence for quite the opposite (Birditt & Fingerman, 2005; Gross et al., 1997). Older adults in fact report less frequent experience of negative affect and more positive affect (Charles, Reynolds, & Gatz, 2001). This apparent paradox between decreasing cognitive ability and increasing emotional well-being has been attributed, in part, to shifts in attentional and motivational factors (Mather & Carstensen, 2005). In the next section, we consider how changes in self-regulatory flexibility might also contribute to greater emotional health in older age. Context Sensitivity As people grow older, they are exposed to an increasingly diverse set of stressful challenges that require them to behave, think, and feel differently from one stressful context to the next. It stands to reason, then, that as people age, they may develop improved sensitivity to contextual demands and opportunities, and by extension become increasingly able to discern what behaviors are most adaptive in specific situations. One study testing this idea presented older and younger adults with hypothetical situations and asked them to select strategies to address these situations. Older adults selected strategies that were rated as more effective by a panel of experts as compared with younger adults (Blanchard-Fields, Mienaltowski, & Seay, 2007). A follow-up comparison indicated that the advantage older adults have over younger adults in their strategy selection was especially pronounced in regulatory flexibility and its role in adaptation     

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situations that were interpersonal in nature. This study may suggest that older adults become more context sensitive, although prevailing theoretical frameworks on emotional aging adults suggest otherwise. According to socioemotional selectivity theory (Carstensen, 2006), older adults experience a shift in their emotional goals by maximizing their experience of positive emotion. This effect is theoretically achieved by focusing on positive information, but done at the cost of increasingly discounting negative information. Such a bias in contextual information processing would theoretically put older adults at a disadvantage in circumstances requiring them to perceive and act upon unpleasant and nonhedonistic emotions and goals. Repertoire As noted above, older adults tend to report less negative and more positive affect in their everyday lives. Positive affect has also been shown to increase creativity and broaden behavioral repertoire (Fredrickson & Branigan, 2005; Isen, Daubman, & Nowicki, 1987). Thus, improved mood in older adults may facilitate using a broader suite of self-regulatory strategies. In their study of a sample consisting of diverse age groups, Watson and Blanchard-Fields (1998) presented participants with a number of vignettes of interpersonal problems and asked them to rank a number of potential strategies for addressing these situations. Younger and middle-aged adults typically preferred strategies that aimed at dealing with the problem directly. In contrast, older adults preferred a combination of both problem-focused and emotion-focused strategies. These data suggest that older adults are indeed more flexible in their use of diverse self-regulatory behavior types. However, results from other studies report findings where this age discrepancy reverses or does not exist (Lester, Smart, & Baum, 1994). For example, using the expressive flexibility paradigm (Bonanno et al., 2004), described earlier, younger adults proved equally as flexible as young adults in their abilities to enhance and suppress emotional expressions (Emery & Hess, 2011). Older adults’ bias toward experiencing positive emotion as described within socioemotional selectivity theory (Carstensen, 2006) would likewise suggest that older adults narrow their selection of coping and emotion regulation strategies to help them achieve this goal. Labouvie-Vief (2009) attempted to address the discrepancy between apparent increases in emotional well-being in the face of compromised processing abilities in older age by proposing a dynamic integration theory. Similar to the flexibility model, the dynamic integration theory proposes that emotion regulation is not a trait, but varies according to the circumstantial challenges a person must face as well as general developmental changes as the person ages. Thus, an individual’s repertoire of self-regulatory strategies may change as a function of both their age as well as a specific stressor’s context. 84       burton and bonanno

Feedback Little research has directly tested the effects of age on individual differences in the use of the feedback component of regulatory flexibility. Interoceptive awareness, an important element of feedback, has been found to decline with age. For example, in one study participants’ age was negatively correlated with their accuracy in detecting their own heart rate (Khalsa, Rudrauf, & Tranel, 2009). However, it is possible that older adults compensate for such deficits in physiological detection ability by having greater motivation to regulate their emotions (Blanchard-Fields, 2009). Higher levels of motivation may allow older adults to become more acutely aware of their emotional states through alternative channels of emotional response, and thus allow them to sustain or modify their self-regulatory strategies accordingly. In addition to motivation, an individual’s resources may also change as they age. Older individuals may be less successful in employing certain strategies than when they were younger. The selection, optimization, and compensation with emotion regulation framework (Urry & Gross, 2010) proposes that compensation with alternative strategies is crucial in persons who find they are unsuccessful in using emotion regulation strategies they may have once preferred. Thus, awareness and compensation for age-related changes may be another important function of responsivity to situational feedback. Social feedback also plays an important role in helping determine whether to continue or adjust one’s regulatory strategy. Research comparing relationship qualities across ages suggests that older adults have higher quality and less conflictual relationships with persons in their social network when compared with younger adults (Birditt, Fingerman, & Almeida, 2005). Having access to higher quality sources of social support may also contribute to improved flexibility in older age. In a study of younger adults, individuals with higher quality relationships evidenced greater ability to identify internal emotional states, such as describing emotions using nonemotional vocabulary and specifying what emotions are better or worse suited to address various problems and situations (Lopes, Salovey, & Straus, 2003). CONCLUSION AND IMPLICATIONS As the study of emotion and emotion regulation across the lifespan progresses, it will continue to move further afield from the traditional fallacy of uniform efficacy (Bonanno & Burton, 2013), in which self-regulatory behaviors are assumed to be consistently “good” or “bad,” and toward a broader model that places greater emphasis on individual abilities that might facilitate flexibility regulatory flexibility and its role in adaptation     

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in self-regulation between contexts. The literature and research reviewed in this chapter converge on three sequential abilities we have elsewhere proposed (Bonanno & Burton, 2013), and help provide people with greater flexibility in facing the plethora of life’s stressors. These abilities include context sensitivity, breadth of repertoire, and the monitoring of feedback to adjust ongoing selfregulation. The studies we discussed represent significant innovation in coping and emotion regulation research, but much work remains to be done. In this chapter, as we attempted to extend the idea of regulatory flexibility to consider normative changes across the lifespan, a number of questions for future research emerged. For example, how does flexibility develop in younger years? In normal, benign, or safe developmental contexts, young children benefit from the stress-buffering effects of various protective factors, such as the neural plasticity of the developing brain, the cognitive inability to fully grasp the psychological implications of aversive events, and the protection and guidance of adult caregivers (Masten & Narayan, 2012). However, at key early developmental phases, excessive stress or deprivation can dramatically impact brain development and result, for example, in atypically large amygdala volume (Tottenham et al., 2010), precocious amygdalaprefrontal connectivity (Gee et al., 2013), and rigid and inappropriate patterns of response at later developmental phases (Lupien, McEwen, Gunnar, & Heim, 2009). Similarly, we might ask how flexibility once established might be maintained in later life. Although cognitive and neurological changes in older age suggest a decrease in some abilities, preliminary studies on context sensitivity, repertoire, and feedback monitoring suggest otherwise. Older adults appear to be more sensitive to emotional context and employ a more diverse repertoire of behaviors while being more motivated to monitor and address their internal states. These age-related differences may be attributable to the development of self-regulatory mastery gained over decades of emotional experiences rather than the maintenance of psychological flexibility, but future research can elucidate these points and may even contribute to the development of relevant psychological interventions. Indeed, continued advances in the measurement and conceptualization of flexibility will only deepen our understanding of the variability of mental health outcomes and emotional well-being observed in stress and aging. REFERENCES Aldao, A. (2013). The future of emotion regulation research: Capturing context. Perspectives on Psychological Science, 8, 155–172. http://dx.doi.org/ 10.1177/1745691612459518

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III Motivational Perspectives

5 HAPPY TO BE UNHAPPY? PRO- AND CONTRAHEDONIC MOTIVATIONS FROM ADOLESCENCE TO OLD AGE MICHAELA RIEDIGER AND GLORIA LUONG

Over the past few decades, a number of studies have found converging evidence of age-related differences in daily affective well-being from adolescence to young-old age (i.e., sixth and seventh decades of life). Adolescents, for example, report relatively more affective turmoil and greater negative emotionality than adults (e.g., Larson, Moneta, Richards, & Wilson, 2002; Riediger & Klipker, 2014; Silk, Steinberg, & Morris, 2003). Across adulthood, there is a shift such that healthy older adults (at least into young-old age) typically report more positive and fewer negative daily affective experiences and greater stability in their affective lives than do younger and middleaged adults (e.g., Carstensen et al., 2011; Charles, Reynolds, & Gatz, 2001; Riediger & Rauers, 2014; Stone, Schwartz, Broderick, & Deaton, 2010). This relatively positive profile of affective experiences and well-being seems to

We thank Antje Rauers for her helpful comments on an earlier version of this chapter. http://dx.doi.org/10.1037/14857-006 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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decline only toward the very end of life in the years preceding death (e.g., Gerstorf et al., 2010; Teachman, 2006). In recent years, investigators have attempted to disentangle the mechanisms underlying age-related differences in daily-life affective experiences. In the present chapter, we focus on one specific mechanism, affect-regulation motivation, which denotes how individuals want to proactively influence their daily affective experiences. After a brief note on our use of terminology in this chapter, we review evidence that age-related differences in affective experiences correspond to age-related differences in pro- and contrahedonic affectregulation motivations. Next, we introduce two complementary approaches to explaining variation in pro- and contrahedonic affect-regulation motivation: the instrumental-affect and the mixed-affect perspectives. We discuss the implications of this research for understanding affective development across the lifespan and highlight open questions and challenges for future investigations. A BRIEF NOTE ON TERMINOLOGY In this chapter, we follow the convention of using the term affect as an overarching category encompassing emotions and moods (e.g., Gross, 2014). Emotions are typically elicited by specific events or thoughts about those events. Moods, in contrast, have less specific causes and are more strongly influenced by the individual’s resource capacity (e.g., level of fatigue). Emotions are often short-lived, unfolding within seconds to minutes, whereas moods can extend across hours (e.g., Larsen, 2000). Despite these differences, boundaries between emotions and moods are often murky because both are characterized by inner feelings, physiological processes, and behavioral expressions. Empirical differentiation is therefore difficult, particularly in studies that assess naturally occurring affective experiences in everyday-life contexts. We therefore use the umbrella term affect in this chapter when reviewing findings on relatively short-term affective experiences. AFFECT REGULATION AND AFFECT-REGULATION MOTIVATION Affect regulation refers to the processes that allow individuals to influence the experience and expression of their affective states, including their specific types, intensity, and frequency (Gross, 2014). Regulation of affective states often occurs without awareness and intentional effort but can also be deliberately initiated by the individual. Affect regulation can be achieved via various strategies, including, for example, avoiding affect-eliciting situations, 98       riediger and luong

reappraising their significance, and suppressing affective expressions (Gross, 2015). Irrespective of its specific manifestation, affect regulation (just as any other form of regulatory behavior) is preceded by motivational processes. Such affect regulation motivation refers to how individuals want to influence their affective experiences. These motivations subsequently shape affectregulation efforts. They can be directed at maintaining, enhancing, or dampening affective experiences and expressions. It was long presumed that psychologically healthy people are generally guided by a prohedonic principle, that is, to always seek to maximize positive (pleasant) affective states and to avoid or minimize negative (unpleasant) affective states (for a discussion of relevant historical positions, see, e.g., Erber & Wang Erber, 2000). Contrahedonic tendencies, wherein individuals may forego positive feelings or seek out or maintain negative emotions, were assumed to occur only in mental pathology. Indeed, psychological disorders can involve such symptoms as the deliberate infliction of injury and pain upon oneself, or a pathological desire to sustain or enhance negative affective states. Recently, however, research has suggested that contrahedonic motivation can also occur in nonclinical populations (Riediger, Schmiedek, Wagner, & Lindenberger, 2009). Although prohedonic affect-regulation motivation is predominant in healthy individuals, there can also be occasional exceptions when people are inclined toward contrahedonic states. This is reflected, for example, in such everyday behaviors as listening to melancholy music to indulge in sadness, getting into a somber mood before delivering bad news, or working up a state of anger to assert one’s interests in an argument. In everyday life, most people likely do not consciously contemplate their affect-regulation motivation much, if at all. In fact, it seems likely that affect-regulation motivation may often operate automatically and outside of the individual’s conscious awareness. Research has shown, however, that when asked to do so, people can report on it and that there is inter- and intraindividual variation in these reports, which, in turn, covary with other (and also nonself-report) measures in a meaningful manner (e.g., Mares, Oliver, & Cantor, 2008; Riediger, Schmiedek, Wagner, & Lindenberger, 2009; Wood, Heimpel, Manwell, & Whittington, 2009). Affect-regulation motivation thus seems to be at least partly accessible to individuals’ introspection. In this chapter, we review some of these findings with a focus on agerelated differences from youth to old age. As mentioned before, evidence abounds that day-to-day affective experiences differ between individuals from various age groups. Several recent studies (reviewed below), among them the Multi-Method Ambulatory Assessment (MMAA) project conducted in our lab, have addressed the question of whether a corresponding pattern of age differences applies to affect-regulation motivation with respect to how people want to feel in their everyday lives. happy to be unhappy?     

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AGE-RELATED DIFFERENCES IN PRO- AND CONTRAHEDONIC AFFECT-REGULATION MOTIVATIONS: FROM ADOLESCENCE TO OLD AGE The MMAA project is an experience-sampling investigation on associations between motivational, cognitive, and physiological processes and everyday affective experiences (Riediger et al., 2009). The sample comprises more than 400 participants ranging in age from 12 to 86 years. Participants carried mobile phones while pursuing their normal daily routines. A subsample also wore ambulatory biomonitors that tracked several physiological parameters. These phones signaled participants, on average 54 times throughout 3 weeks, to complete two trials of a working-memory task and to report, among other things, their momentary affective states and whether they currently wanted to dampen, enhance, maintain, or not at all influence each of three positive (i.e., interested, joyful, content) and three negative affective states (i.e., angry, downcast, and anxious). Indices of momentary pro- and contrahedonic motivations were derived from these reports. Prohedonic motivations were indicated by reports to maintain or enhance positive affect or to dampen negative affect, whereas contrahedonic motivations were indicated by endorsements of wanting to dampen positive affect or to maintain or enhance negative affect. Results from the MMAA project replicated the age-related increase in day-to-day affective well-being from adolescence to older adulthood found in previous studies. Several theories have been developed to explain this apparent “aging paradox,” whereby cognitive, physical, and social resources show marked decline across adulthood and yet, affective well-being remains intact or even enhanced into young-old age (e.g., Charles & Luong, 2013). For example, many emotional aging theories posit that abilities to regulate or experience negative affective states change with age due to neurological dysregulation (aging grain model; Cacioppo, Berntson, Bechara, Tranel, & Hawkley, 2011), cognitive deficits (dynamic-integration model; LabouvieVief, 2003), or varying resource capacities across the lifespan (selection, optimization, and compensation with emotion regulation model; Urry & Gross, 2010). Implicit in these theories is the assumption that individuals of all ages share the same prohedonic orientations and that relatively greater negative affectivity during adolescence and young adulthood reflects failures to successfully attain prohedonic states. However, motivational factors may also partially explain these age effects. Socioemotional selectivity theory, for example, suggests that diminishing time horizons may lead to a greater focus on emotional goals, such as the pursuit of prohedonic states, in later adulthood (Carstensen, 2006). The role of contrahedonic motivations in explaining such age-related differences in daily affective well-being, however, has been largely overlooked in the literature. 100       riediger and luong

Interestingly, in the MMAA project, age differences in daily affective well-being largely corresponded to differences in affect-regulation motivations: Contrahedonic motivations were reported in 15% of the measurement occasions on average, and were thus considerably less prevalent than prohedonic motivations, which were reported in 92% of the measurement occasions on average. Nonetheless, contrahedonic motivations were most prevalent among adolescents and decreased with age. Prohedonic motivations, in contrast, were most prevalent in later adulthood (Riediger et al., 2009). Importantly, the age differences in pro- and contrahedonic motivations could not be attributed to age-related differences in daily-life affective experiences, activities, or social partners. Similar patterns of age-related differences emerged in another study wherein 18- to 82-year-old participants reported how much they sought or avoided various affective experiences in their everyday lives, and how much they regarded these experiences as useful or valuable (Mares et al., 2008). Preferences for negative affect were most pronounced among the youngest individuals, whereas preferences for positive affect and emotional stability increased throughout adulthood. The above studies used self-report measures and thus assumed that affectregulation motivation is at least partly accessible to introspection. In line with this assumption is evidence from a different research tradition, showing a corresponding pattern of age differences in entertainment use. For example, younger adults were more likely than older adults to report that they liked movies that elicit sadness or fear, while older adults were more likely to prefer heartwarming movies (Bartsch, 2012; Mares et al., 2008). Although the direction of causality cannot be judged on the basis of such cross-sectional findings, taken together, they nevertheless suggest the possibility that age-related differences in daily emotional experiences may be partially due to differences in affect-regulation motivations that shape how affective experiences are sought and maintained by the individual, either deliberately or unconsciously. It is still unclear, however, when and why people are inclined to seek prohedonic states versus pursue contrahedonic tendencies. Moreover, what might be the reasons for these age differences in pro- and contrahedonic affect-regulation motivations? In the following sections, we elaborate on two complementary explanations for variations in pro- and contrahedonic motivations, which extend the scope of previous theoretical perspectives on emotional aging. One perspective proceeds from the idea that affective states can occasionally be helpful or harmful for an individual’s goals and developmental tasks (i.e., instrumental perspective; Tamir, 2009). People might therefore strategically seek out those affective states that facilitate the pursuit of their interests (even if these states might be unpleasant) or avoid affect states that are harmful in this regard. A complementary perspective, which is particularly relevant for explaining happy to be unhappy?     

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potential occurrences of contrahedonic motivation, argues that such tendencies may arise when apparently positive experiences are accompanied by negative affective states (or vice versa), that is, when the affective episode is mixed (i.e., mixed-affect perspective; Riediger, Wrzus, & Wagner, 2014). We discuss how these two perspectives offer explanations for when and why individuals may pursue prohedonic versus contrahedonic affect-regulation goals and for why there are age-related differences in the prevalence of proand contrahedonic motivations. Instrumental Perspective on Affect-Regulation Motivation The instrumental account posits that affective states can be helpful or harmful for an individual’s goals and life tasks, depending on the context (Tamir, 2009). This idea is commensurate with evolutionary theories that propose that emotions evolved because they prepared individuals for quickly executing adaptive behaviors and communicated important information to conspecifics, thus enhancing the chances of survival (and, consequently, of reproduction and gene transmission to future generations; e.g., Tooby & Cosmides, 2008). A classic illustration of this idea is the instrumental value of fear in threatening situations. The experience of fear, along with the accompanying physiological and cognitive processes (e.g., enhanced autonomic arousal, attentional narrowing), prepares the individual for rapid and adaptive actions, such as fleeing from danger. The expression of fear furthermore signals danger to others, who can then prepare to seek safety themselves. Fear can thus be helpful in situations that require the avoidance of threats or dangers. In other contexts, however, fear can be detrimental to the individual’s interests. When desirable or necessary objects (e.g., food) are available in the absence of immediate danger, for example, fear and anxiety would hamper approach behaviors that would be necessary to obtain the items. Affective states have retained their context-dependent utility in this day and age. Although they may rarely be relevant for immediate survival in modern times, affective states can nevertheless be helpful (and at other times, harmful) for the attainment of individuals’ goals. Instrumental accounts propose that variation in pro- and contrahedonic affect-regulation motivations may derive from (conscious or unconscious) strategic efforts in seeking affective states that are instrumental in a given context. Contrahedonic motivations, for instance, are assumed to occur in situations where negative affect is facilitative for, or positive affect detrimental to, an individual’s goals, such as when experiencing anger helps individuals to assert their interests in a confrontation, or when expressing joy during the delivery of bad news elicits social bewilderment. Specifically, the instrumental account posits that contra­ hedonic motivations can occur in situations in which the expected momentary 102       riediger and luong

or future utility of affective experiences outweighs the immediate gratification of pleasure states. In contrast, individuals may be more inclined toward pro­ hedonic motivations when the long-term prospects of contrahedonic states (e.g., high negative affect, low positive affect) are poor and immediate emotional rewards are more highly valued (Tamir, 2009). Various empirical studies by Tamir and colleagues have supported such instrumental accounts of affect-regulation motivation, particularly for contra­ hedonic motivations. Young adult participants in two studies reported by Tamir and Ford (2012), for example, were assigned either a confrontational or collaborative goal in an interpersonal negotiation task. Participants with the goal to confront (vs. collaborate with) their partner showed a stronger preference for anger-inducing activities in anticipation of the negotiation (e.g., were more likely to prefer recalling past experiences in which they felt angry vs. happy). Other studies by Tamir and colleagues have demonstrated similar contrahedonic tendencies in different task contexts. For instance, enhanced preferences for fear-inducing activities were observed when participants expected to play a computer game in which their goal was to avoid threatening elements (Tamir, 2009), whereas enhanced preferences for anger-inducing choices were observed when participants expected to play a computer game in which the task was to attack virtual enemies (Tamir, Mitchell, & Gross, 2008). The authors argued that participants in these studies sought negative affective states when these were useful in pursuing the assigned goals and outweighed the momentary hedonic costs. Consistent with this interpretation, in the negotiation studies (Tamir & Ford, 2012), participants who were assigned the task of confrontation (vs. collaboration) with their partner were more likely to expect anger to be helpful in their negotiations. Furthermore, selection of anger-inducing activities did indeed lead to more intense feelings of anger during the negotiation, which in turn were associated with better negotiation outcomes in the confrontation condition (similar findings were observed in other task contexts as well; Tamir et al., 2008). Thus, when the short-term assaults to affective well-being are compensated for by the longer term utility of contrahedonic states, individuals may be motivated to seek out and maintain such affective experiences. Although the instrumental perspective has been primarily used to explain occurrences of contrahedonic motivation, it may also be used to explain prohedonic motivation. People should be more motivated to seek and maintain positive affective states or to dampen negative affective states the more helpful they perceive these states to be for their goals. Next, we discuss potential interpretations of the empirically observed agerelated differences in affect-regulation motivations from the instrumental perspective. happy to be unhappy?     

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Explanations for Age-Related Differences in Affect-Regulation Motivations From the Instrumental Perspective The instrumental perspective suggests that age differences in affectregulation motivation may arise because various affective states may be differentially functional in various phases of the lifespan. We explore this idea first with regard to age differences in contrahedonic motivation and then with respect to prohedonic motivation. Instrumentality of Contrahedonic Motivation From Adolescence to Old Age One reason for the comparatively higher prevalence of contrahedonic motivation among adolescents compared with other age groups is that it may facilitate mastery of the developmental tasks of that life phase. Repudiating prevailing hedonic conventions and seeking negative affect, for example, may help adolescents affirm a sense of maturity or refine their self-regulatory competencies. It might also be a means to explore the range and depths of possible experiences, which could help adolescents develop their own identity. A similar argument could be made for the pursuit of prominent developmental themes of younger adulthood, such as acquiring and expanding knowledge and skills. Anger may play a particularly salient role for facilitating persistence in the pursuit of the developmental tasks of adolescence and young adulthood, such as attaining autonomy from adults, promoting one’s career and establishing status, or communicating social boundaries and expectations in various types of relationships (Kunzmann, Kappes, & Wrosch, 2014). In middle adulthood and later life, however, anger (as used in confrontations or hostile communication strategies with others) may be less useful and even hinder the pursuit of the predominant developmental tasks, such as passing on experience and resources to younger generations or the maintenance of social harmony. Indeed, older adults have been found to engage more in conciliatory behaviors in reaction to interpersonal tensions than younger adults (Birditt & Fingerman, 2005; Blanchard-Fields, Mienaltowski, & Seay, 2007). Social partners are also less likely to confront older adults compared with younger adults, suggesting that social conflict situations are less frequent with age (for a review, see Luong, Charles, & Fingerman, 2011). Aside from anger, other negative experiences might also be more useful in early life than in later adulthood. Attending to negative affective experiences, for example, may aid younger individuals in the adaptive exploration of environments and in the recognition of threatening situations (e.g., Vaish, Grossmann, & Woodward, 2008). This might not be the case to the same extent in later life, when individuals typically live in more stable and confined contexts about which they have already acquired abundant information. Compared with adolescence 104       riediger and luong

and young adulthood, the utility of contrahedonic motivations may thus be reduced in later life. Furthermore, contrahedonic motivations appear to come at cognitive costs—resources that are limited and may need to be conserved in later life. For example, in the MMAA project, discussed previously, participants completed two trials of a numerical memory-updating task assessing momentary working memory capacity on each of the 54 experience sampling occasions, in addition to the momentary measures of affective states and pro- and contrahedonic motivations (Riediger, Wrzus, Schmiedek, Wagner, & Lindenberger, 2011). While prohedonic motivation was only weakly associated with withinperson fluctuations in working-memory performance, the association of contra­ hedonic motivation and working-memory performance was substantially more pronounced: The more contrahedonic motivation participants reported, the lower their momentary working-memory performance was, and this was independent of the participants’ momentary affective experience and also not merely due to nonadherence to the task. This effect of contrahedonic motivation on working-memory performance was about 10 times larger than that of prohedonic motivation. These findings could be due to the effort required to overcome one’s prevailing prohedonic orientation, which necessitates the allocation of cognitive resources. Consequently, the capacity remaining for simultaneously processing another resource-intensive task—storing and manipulating information in working memory—would be reduced in situations with contrahedonic motivation. Avoiding contrahedonic motivations could thus be a way to conserve older adults’ increasingly limited resources. It remains an interesting open question for future research to explore the extent to which the age-related decline in contrahedonic motivation reflects a compensatory response to age-related decline in fluid-cognitive capacity on the one hand and an age-related decrease in the instrumentality of negative affective states on the other, as discussed above. Instrumentality of Prohedonic Motivation From Adolescence to Old Age Research has suggested that positive affect may serve an important role in promoting physical health and psychosocial functioning in later life (Ong, Mroczek, & Riffin, 2011). Given that physiological flexibility and health decline with age, the maintenance of positive affective states may be especially important for older adults as it may help to slow the losses in physical functioning. Older adults may therefore benefit relatively more than younger individuals by defaulting to prohedonic motivations, which may be a reason for its relatively high prevalence in later adulthood. Relatedly, high-arousal negative affective states (e.g., feeling angry) may be especially detrimental for older adults’ health (and should hence be avoided) because happy to be unhappy?     

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age-related declines in physiological flexibility impede recovery from these states (e.g., Charles & Luong, 2013). Research from the MMAA project, for example, has shown that older adults exhibit delayed heart rate recovery following a social-cognitive stress task compared with younger individuals (Wrzus, Müller, Wagner, Lindenberger, & Riediger, 2014), and that physiological arousal states associated with feeling nervous are linked to impaired momentary cognitive capacity in middle-aged and older adults but not in younger individuals (Riediger, Wrzus, Klipker, et al., 2014). These findings suggest that highly arousing or stressful situations may prolong physiological activation to a greater degree for older adults, thereby leading to greater wear-and-tear on their physical and cognitive resource capacities compared with younger individuals. Thus, prohedonic motivations may promote more adaptive physical and cognitive functioning in later life. Taken together, the instrumental perspective on affect-regulation motivation suggests that the observed age-related differences might be due to a differential instrumentality of affective states for the developmental themes of different life phases. For example, occasionally seeking negative affect might facilitate the persistent pursuit of predominant developmental tasks of adolescence and young adulthood, such as establishing autonomy and status, acquiring and expanding knowledge and skills, or exploring environments and opportunities. In older adulthood, however, the cognitive and physiological costs associated with contrahedonic motivations may often outweigh their potential benefits. In addition, the instrumentality of positive affect might increase with age, especially with regard to the conservation of physical and cognitive resources or the establishment and maintenance of social harmony. Mixed-Affect Perspective on Affect-Regulation Motivation Aside from the instrumental perspective, a complementary account of variation in affect-regulation motivation proceeds from the observation that affective experiences are not always unequivocally positive or negative but can entail a blend of various affective states of opposing valence (e.g., Ersner-Hershfield, Mikels, Sullivan, & Carstensen, 2008; Larsen & McGraw, 2011; Schimmack, 2001). For example, people can experience sadness and joy simultaneously, such as during nostalgic reminiscence, or fear and excitement, such as when engaging in risky sensation-seeking activities. It is also possible that a given affective state is not blended but is followed by a state of opposing valence (e.g., nervousness before a difficult task followed by elation when it has been accomplished). The mixed-affect perspective proposes that anticipated or actual mixed affect might motivate individuals to seek or maintain an apparently negative affective state because they associate enjoyable or otherwise positive aspects with it (e.g., when it feels good to be sad), 106       riediger and luong

or vice versa, to dampen an apparently positive affective state because they associate unpleasant aspects with it as well (e.g., when they are embarrassed to be proud; Andrade & Cohen, 2007; Riediger et al., 2009; Riediger, Wrzus, & Wagner, 2014). Experience-sampling evidence from the MMAA project indeed showed that individuals are more likely to report the contrahedonic motivation of wanting to maintain their momentary negative affect in situations where they experienced mixed affective states, that is, simultaneous positive and negative affect that were both more intense than the individual’s respective averages (Riediger et al., 2009). Additionally, studies by Andrade and Cohen (2007) showed that students who liked to watch horror movies were more likely to experience both negative and positive affect while watching, whereas persons who avoided horror movies tended to only experience negative affect while watching. Interestingly, the pattern and intensity of negative affect (e.g., fear) while watching did not differ between persons who liked to watch and those who avoided horror movies. This finding speaks against the possibility that individuals who look for apparently aversive experiences appraise them in a less negative manner. Instead, these studies suggest that people develop a preference for horror movies because of the positive affective experiences that accompany their fear. These findings thus support the mixed-affect account of contrahedonic motivation. In the following, we discuss how this perspective might contribute to an understanding of the observed age differences in affect-regulation motivation. Explanations for Age-Related Differences in Affect-Regulation Motivations From the Mixed-Affect Perspective Findings from the MMAA project showed pronounced age-related differences in the prevalence of mixed-affective experiences that followed the same pattern as those of contrahedonic motivation: Both mixed affective experiences (operationalized as the cooccurrence of positive and negative affect that were both more intense than the individual’s respective averages) and contrahedonic motivation were most frequent among adolescents and least prevalent among older adults (Riediger et al., 2009; Riediger, Wrzus, & Wagner, 2014). Adolescents might thus be more inclined than individuals from other age groups, and especially older adults, to seek or maintain negative states (which they also more frequently associated with pleasantness) or to decrease positive states (which they also more frequently associated with unpleasantness). Similar patterns of age-related decreases in mixed affect have also been found in previous studies (e.g., Ready, Carvalho, & Weinberger, 2008, Study 2). Other research, however, yielded divergent findings (for a happy to be unhappy?     

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review, see Riediger & Rauers, 2014), indicating either age invariance (e.g., Grühn, Lumley, Diehl, & Labouvie-Vief, 2013; Hay & Diehl, 2011) or an age-related increase across adulthood (e.g., Carstensen, Pasupathi, Mayr, & Nesselroade, 2000) in the likelihood of mixed affect as indicated indirectly by within-person associations between positive and negative affect. A potential limitation of this indirect measure is that low correlations between positive and negative affect can also result from lack of variance in participants’ reports of positive affect, negative affect, or both (Diener & Iran-Nejad, 1986; Löckenhoff, Costa, & Lane, 2008; Russell & Carroll, 1999). This limitation may be particularly relevant in age-comparative research because variability of certain (particularly negative) affective experiences has been shown to decline with age (Grühn et al., 2013; Röcke, Li, & Smith, 2009). Cultural differences as well as heterogeneity between studies regarding the specific affect facets (items) investigated could also be reasons for these diverging findings. In our own research, we found that the pattern of age-related decline in mixed affect was not restricted to individuals’ self-report but was also reflected in implicit representations of affect valence as assessed with an implicit association test. This is a measure of the relative association strength between happiness and pleasantness and unhappiness and unpleasantness, respectively, that is derived from differences in response times in simple categorization tasks (Riediger, Wrzus, & Wagner, 2014). Compared with younger individuals, older adults held the most distinctive mental representations of the valence of affective states, that is, they associated happiness distinctively with pleasantness (vs. unpleasantness) and unhappiness distinctively with unpleasantness (vs. pleasantness). In contrast, and compared with adults from various age groups, adolescents implicitly associated happiness least distinctively with pleasantness and unhappiness least distinctively with unpleasantness. Furthermore, and independent of the participants’ age, the more ambiguous people’s mental representations of affect valence were (i.e., the less distinctively they associated happiness with pleasantness, and unhappiness with unpleasantness), the more likely they were to report mixed affect and contrahedonic motivation in their everyday lives. It thus seems possible that individuals with less differentiated (i.e., more ambiguous) affect valence–pleasantness representations might be more inclined to dampen seemingly positive affective experiences because they also associate them with unpleasantness, and/or to occasionally seek seemingly negative affective states as they associate them with pleasantness. However, the factors that trigger age-related shifts in implicit representations of affect valence are still unknown. It is widely assumed that mental representations are formed and shaped throughout life, and that they reflect

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an individual’s prior life experiences (e.g., Carlston, 2010). Representations of affect valence should thus mirror the individual’s accumulated history of affect-related experiences, observations, thoughts, and motivations. When negative affect, for example, helps in dealing with the developmental tasks of adolescence (e.g., establishing emotional autonomy from parents and other adults or developing a sense of identity), it might be sought and experienced as rewarding to some extent, thus enhancing the likelihood of contrahedonic motivation and mixed affect. When the adolescent has resolved these developmental tasks, however, the instrumental value of negative affect might decline along with the frequency with which negative affective experiences are perceived as rewarding. This, in turn, should weaken the association of negative affect with pleasantness and thus enhance the distinctiveness of implicit representations of affect valence. Similarly, and as argued in more detail before, one could speculate that the instrumental value of positive affect might increase throughout adulthood and into older age because positive affect might facilitate the pursuit of generative and affiliation-related concerns, which gain in subjective importance as people grow older. Consequently, experiencing positive affect might become more rewarding throughout adulthood, and thus contribute to the observed increase in the distinctiveness of implicit affect valence. FUTURE WORK AND CHALLENGES Several studies over the past decade have demonstrated that affectregulation motivations show the same pattern of age-related differences as everyday affective experiences (Carstensen, 2006; Riediger et al., 2009). However, a number of open questions remain. One of the most pressing research challenges for this field is to establish the causal pathways between these constructs. That is, are the age differences in everyday affective experiences indeed due, at least in part, to differences in how people from different age groups want to regulate their feelings in their daily lives? Currently, the literature is predominantly based on cross-sectional correlational studies of these processes, precluding firm conclusions about the direction of the effects. It will therefore be important to use complementary longitudinal and experimental study designs to disentangle antecedents and consequences of the various affectregulation motivations, as well as potential mediating mechanisms for these effects (e.g., specific affect-regulation behaviors and strategies). The cross-sectional nature of these datasets also prevents conclusions regarding

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the origin of the observed age-related differences. Longitudinal studies are needed to disentangle the extent to which the observed age differences reflect within-person change in affect-regulation motivation over time and from the extent to which they are influenced by historical differences in life contexts of different birth cohorts. A related challenge in delineating these associations is based on the well-documented motivation-behavior gap in the human volition literature, which shows that individuals may not necessarily proactively pursue goals they value or may even fail to attain goals they try to achieve (e.g., Kuhl & Fuhrmann, 1998). Thus, in the affect-regulation literature, a key to understanding how motivations are linked to affective outcomes is to determine factors that may facilitate successful affect-regulation efforts in daily life. These factors may include individual differences in general self-regulatory abilities or personality traits as well as contextual influences such as the sociocultural environment, among others. From a lifespan developmental perspective, we also need to understand the long-term adaptiveness of these affect-regulation motivations. In line with the instrumental perspective introduced above, it would be vital to determine whether the adaptiveness of affect-regulation motivations indeed depends on the individuals’ age or life phase and their corresponding developmental tasks. For example, contrahedonic motivations may be more instrumental for adolescents and younger adults to master the developmental tasks they face. Speculatively, such processes may then contribute to long-term socioemotional adaptation for adolescents and younger adults, but less so for other age groups (Riediger et al., 2009). In addition, although prohedonic motivations are prevalent among psychologically healthy adults, such motivations may be especially beneficial for tackling the challenges in later life. Future research is needed to clarify these issues. In the long term, further research is also necessary to establish applied implications of the basic research discussed in this chapter. For example, the presented findings underscore that interventions aimed at fostering affectregulation skills should not proceed from the idea that all people are uniformly and always motivated to maximize positive and minimize negative affect and that such prohedonic motivation is equally appropriate and beneficial in all life situations. Instead, intervention programs should foster the development of affect-regulation motivation that is congruent with situational affordances and individual preferences. Development of affect-regulation interventions that can be tailored to the individual participants thus appears superior to those of one-size-fits-all solutions, and program participants’ age seems a characteristic that should be considered in this regard. Finally, much of the work in this field has focused on the valence (i.e., the pleasantness/unpleasantness) of affective regulation motivations (e.g., 110       riediger and luong

Riediger, Wrzus, & Wagner, 2014). Other affect-regulation motivation facets may be important to consider, such as the activation or arousal level, duration of the affective experience (e.g., short-lived emotional episodes or prolonged mood states), overall affective profiles (e.g., mixed, complex, or labile [fluctuating] affective states; Grühn, Lumley, Diehl, & Labouvie-Vief, 2013), and discrete emotions (e.g., sadness; Kunzmann et al., 2014). For example, research on age-related differences in ideal affect (i.e., affective states that people ideally want to feel) shows that older adults prefer low arousal positive states, such as feeling calm and relaxed, over high-arousal positive emotions, such as feeling excited and proud. In contrast, younger individuals prefer both types of positive emotional states equally (Scheibe, English, Tsai, & Carstensen, 2013). Moreover, throughout this chapter we have suggested that affect-regulation motivations may drive age-related improvements in affective well-being. Sadness may be an exception to this rule, however. In contrast to other negative emotions, such as anger, sadness may actually be stable or even increase in later life (Kunzmann & Thomas, 2014). Moreover, given that losses outweigh gains in later life (Baltes & Smith, 2003), sadness may serve important functions in that period, such as signaling to social partners that help is needed (Kunzmann et al., 2014). Recent studies have indeed suggested that experiencing sadness may be uniquely adaptive for older adults (Haase, Seider, Shiota, & Levenson, 2012). However, findings from the MMAA project suggest that in daily life, older adults are motivated to dampen a similar emotion, feeling downcast, to the same degree as they are motivated to down-regulate high-activating negative emotions like anger and nervousness. It is unclear, then, whether sadness may present a case in which an overreliance on prohedonic motivations to dampen all negative affective states may be problematic for older adults given that sadness may be instrumental in later life. Future investigations should therefore clarify these links. SUMMARY AND CONCLUSIONS Researchers have long been interested in resolving the aging paradox, whereby affective well-being exhibits stability and even increases across adulthood while other domains of functioning, such as cognitive processing and physical health, show substantial declines over the same life period. Although some theories are centered on affect regulatory abilities as a mediating mechanism, in this chapter we have reviewed age-related differences in affect-related motivations (the types of affective states people want to feel and how people want to influence their emotions) as a potential underlying explanation for this aging paradox. We have focused on interesting recent developments in happy to be unhappy?     

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the literature: differences in the relative prevalence of prohedonic and contra­ hedonic affect-regulation motivations at various life stages. Across the age range from adolescence to old age, for example, contrahedonic motivations to enhance or maintain negative affect or dampen positive affect, are most prevalent in adolescence, whereas prohedonic motivations to dampen everyday negative affect and maintain or enhance positive affect are most frequently reported by older adults. Moreover, these age-related differences in affectregulation motivations correspond to the actual experiences people report in daily life, that is, older individuals not only more often endorse prohedonic motivations but also indeed experience greater daily affective well-being than their younger counterparts. The instrumental-affect and the mixed-affect perspectives provide possible explanations for why the relative pursuit of pro- versus contrahedonic states may differ between individuals in different life phases. According to the instrumental perspective, individuals will consider the immediate emotional benefits versus longer term payoffs when pursuing affective goals. Given that adolescents have a more expansive future outlook, they may benefit from such investments in contrahedonic motivations to a greater degree than older individuals. Several developmental tasks of adolescence and younger adulthood may thus be facilitated by occasional contrahedonic states. Older adults, in contrast, have foreshortened time perspectives and may place greater value on short-term or momentary emotional gratification, as posited by socioemotional selectivity theory (Carstensen, 2006) and consistent with findings that the prevalence of prohedonic motivations is most pronounced in later life (Riediger et al., 2009). Moreover, contrahedonic states (e.g., high negative affect) may present assaults to the physiological system, cognitive resources, and social relationships—aspects that are more highly valued, and potentially more vulnerable, with age (e.g., Charles & Luong, 2013; Riediger et al., 2011; Wrzus et al., 2014). Mixed-affect approaches suggest that individuals may value contra­ hedonic states when negative emotional experiences are blended with positive ones. Findings from the MMAA project show that the prevalence of mixed affective states evince the same pattern of age differences as the prevalence of contrahedonic motivations, that is, it was lowest among older adults and highest among adolescents. Furthermore, older adults exhibit the strongest distinct implicit associations between positive affect and pleasantness (vs. unpleasantness) as well as between negative affect and unpleasantness (vs. pleasantness), whereas adolescents show the least distinct associations. In addition, in daily life, episodes of mixed affect (blends of concurrent positive and negative affect) were related to the momentary endorsement of contrahedonic motivation. Altogether, these results suggest that adolescents may not perceive negative affect to be as unpleasant, nor positive affect to 112       riediger and luong

be as pleasant and rewarding, as older individuals, which may contribute to their relatively greater likelihood of endorsing contrahedonic motivations in daily life. In this chapter, we have shown how a motivational account of how people want to feel and how people want to correspondingly influence their emotions contributes to a deeper understanding of emotional aging. We have highlighted some open questions and future challenges we believe will move the field forward. It will be important to account for how these agentic and proactive motivational and volitional aspects interact with other aspects of aging (e.g., physiological and cognitive vulnerabilities, social resources, contextual changes) to influence everyday affect-regulation efforts and emotional outcomes. Insights from such future research would be valuable to the extent that they may encourage scientists and clinicians, for example, to reconsider what types of affective profiles may be adaptive or functional depending on the age or life phase of the individual in question. These investigations will help researchers better understand how and why affectregulation motivations may contribute to age-related differences in affective well-being and their implications for promoting adaptive functioning and successful development. RECOMMENDED READINGS Gross, J. J. (2014). Emotion regulation: Conceptual and empirical foundations. In J. J. Gross (Ed.), Handbook of emotion regulation (2nd ed., pp. 3–20). New York, NY: Guilford Press. Riediger, M., & Rauers, A. (2014). Do everyday affective experiences differ throughout adulthood? A review of ambulatory-assessment evidence. In P. Verhaeghen & C. Hertzog (Eds.), The Oxford handbook of emotion, social cognition, and everyday problem solving during adulthood (pp. 61–82). New York, NY: Oxford University Press. Riediger, M., Schmiedek, F., Wagner, G., & Lindenberger, U. (2009). Seeking pleasure and seeking pain: Differences in pro and contrahedonic motivation from adolescence to old age. Psychological Science, 20, 1529–1535. http://dx.doi.org/ 10.1111/j.1467-9280.2009.02473.x Riediger, M., Wrzus, C., Schmiedek, F., Wagner, G. G., & Lindenberger, U. (2011). Is seeking bad mood cognitively demanding? Contrahedonic orientation and working-memory capacity in everyday life. Emotion, 11, 656–665. http://dx.doi. org/10.1037/a0022756 Riediger, M., Wrzus, C., & Wagner, G. G. (2014). Happiness is pleasant, or is it? Implicit representations of affect valence are associated with contrahedonic motivation and mixed affect in daily life. Emotion, 14, 950–961. http://dx.doi. org/10.1037/a0037711 happy to be unhappy?     

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Larsen, J. T., & McGraw, A. P. (2011). Further evidence for mixed emotions. Journal of Personality and Social Psychology, 100, 1095–1110. http://dx.doi.org/10.1037/ a0021846 Larsen, R. J. (2000). Toward a science of mood regulation. Psychological Inquiry, 11, 129–141. http://dx.doi.org/10.1207/S15327965PLI1103_01 Larson, R. W., Moneta, G., Richards, M. H., & Wilson, S. (2002). Continuity, stability, and change in daily emotional experience across adolescence. Child Development, 73, 1151–1165. http://dx.doi.org/10.1111/1467-8624.00464 Löckenhoff, C. E., Costa, P. T., Jr., & Lane, R. D. (2008). Age differences in descriptions of emotional experiences in oneself and others. The Journals of Gerontology: Series B. Psychological Sciences and Social Sciences, 63, P92–P99. http:// dx.doi.org/10.1093/geronb/63.2.P92 Luong, G., Charles, S. T., & Fingerman, K. L. (2011). Better with age: Social relationships across adulthood. Journal of Social and Personal Relationships, 28, 9–23. http://dx.doi.org/10.1177/0265407510391362 Mares, M.-L., Oliver, M. B., & Cantor, J. (2008). Age differences in adults’ emotional motivations for exposure to films. Media Psychology, 11, 488–511. http:// dx.doi.org/10.1080/15213260802492026 Ong, A. D., Mroczek, D. K., & Riffin, C. (2011). The health significance of positive emotions in adulthood and later life. Social and Personality Psychology Compass, 5, 538–551. http://dx.doi.org/10.1111/j.1751-9004.2011.00370.x Ready, R. E., Carvalho, J. O., & Weinberger, M. I. (2008). Emotional complexity in younger, midlife, and older adults. Psychology and Aging, 23, 928–933. http:// dx.doi.org/10.1037/a0014003 Riediger, M., & Klipker, K. (2014). Emotion regulation in adolescence. In J. J. Gross (Ed.), Handbook of emotion regulation (2nd ed., pp. 187–202). New York, NY: Guilford Press. Riediger, M., & Rauers, A. (2014). Do everyday affective experiences differ throughout adulthood? A review of ambulatory-assessment evidence. In P. Verhaeghen & C. Hertzog (Eds.), The Oxford handbook of emotion, social cognition, and everyday problem solving during adulthood (pp. 61–82). New York, NY: Oxford University Press. Riediger, M., Schmiedek, F., Wagner, G. G., & Lindenberger, U. (2009). Seeking pleasure and seeking pain: Differences in prohedonic and contra-hedonic motivation from adolescence to old age. Psychological Science, 20, 1529–1535. http:// dx.doi.org/10.1111/j.1467-9280.2009.02473.x Riediger, M., Wrzus, C., Klipker, K., Müller, V., Schmiedek, F., & Wagner, G. G. (2014). Outside of the laboratory: Associations of working-memory performance with psychological and physiological arousal vary with age. Psychology and Aging, 29, 103–114. http://dx.doi.org/10.1037/a0035766 Riediger, M., Wrzus, C., Schmiedek, F., Wagner, G. G., & Lindenberger, U. (2011). Is seeking bad mood cognitively demanding? Contra-hedonic orientation and

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working-memory capacity in everyday life. Emotion, 11, 656–665. http://dx.doi.org/ 10.1037/a0022756 Riediger, M., Wrzus, C., & Wagner, G. G. (2014). Happiness is pleasant, or is it? Implicit representations of affect valence are associated with contrahedonic motivation and mixed affect in daily life. Emotion, 14, 950–961. http://dx.doi.org/ 10.1037/a0037711 Röcke, C., Li, S.-C., & Smith, J. (2009). Intraindividual variability in positive and negative affect over 45 days: Do older adults fluctuate less than young adults? Psychology and Aging, 24, 863–878. http://dx.doi.org/10.1037/a0016276 Russell, J. A., & Carroll, J. M. (1999). On the bipolarity of positive and negative affect. Psychological Bulletin, 125, 3–30. http://dx.doi.org/10.1037/0033-2909.125.1.3 Scheibe, S., English, T., Tsai, J. L., & Carstensen, L. L. (2013). Striving to feel good: Ideal affect, actual affect, and their correspondence across adulthood. Psychology and Aging, 28, 160–171. http://dx.doi.org/10.1037/a0030561 Schimmack, U. (2001). Pleasure, displeasure, and mixed feelings: Are semantic opposites mutually exclusive? Cognition and Emotion, 15, 81–97. http://dx.doi.org/ 10.1080/02699930126097 Silk, J. S., Steinberg, L., & Morris, A. S. (2003). Adolescents’ emotion regulation in daily life: Links to depressive symptoms and problem behavior. Child Development, 74, 1869–1880. http://dx.doi.org/10.1046/j.1467-8624.2003.00643.x Stone, A. A., Schwartz, J. E., Broderick, J. E., & Deaton, A. (2010). A snapshot of the age distribution of psychological well-being in the United States. PNAS Proceedings of the National Academy of Sciences of the United States of America, 107, 9985–9990. http://dx.doi.org/10.1073/pnas.1003744107 Tamir, M. (2009). What do people want to feel and why? Pleasure and utility in emotion regulation. Current Directions in Psychological Science, 18, 101–105. http://dx.doi. org/10.1111/j.1467-8721.2009.01617.x Tamir, M., & Ford, B. Q. (2012). When feeling bad is expected to be good: Emotion regulation and outcome expectancies in social conflicts. Emotion, 12, 807–816. http://dx.doi.org/10.1037/a0024443 Tamir, M., Mitchell, C., & Gross, J. J. (2008). Hedonic and instrumental motives in anger regulation. Psychological Science, 19, 324–328. http://dx.doi.org/10.1111/ j.1467-9280.2008.02088.x Teachman, B. A. (2006). Aging and negative affect: The rise and fall and rise of anxiety and depression symptoms. Psychology and Aging, 21, 201–207. http:// dx.doi.org/10.1037/0882-7974.21.1.201 Tooby, J., & Cosmides, L. (2008). The evolutionary psychology of the emotions and their relationship to internal regulatory variables. In M. Lewis, J. M. HavilandJones, & L. F. Barrett (Eds.), Handbook of emotions (pp. 114–137). New York, NY: Guilford Press. Urry, H. L., & Gross, J. J. (2010). Emotion regulation in older age. Current Directions in Psychological Science, 19, 352–357. http://dx.doi.org/10.1177/0963721410388395 happy to be unhappy?     

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6 EMOTIONAL AGING IN DIFFERENT CULTURES: IMPLICATIONS OF AFFECT VALUATION THEORY JEANNE L. TSAI AND TAMARA SIMS

Demographers report that across the world, people are living longer (World Health Organization, 2014). And yet, even after controlling for economic factors, nations vary significantly in terms of average life expectancy. For instance, the average life expectancy in the United States (79.56 years) is 3 to 4 years lower than that of Japan (84.46 years) and Hong Kong (82.78 years; Central Intelligence Agency, 2013). These differences raise the possibility that cultural factors play some role in human aging. In this chapter, we explore how culture may shape emotional aging. We discuss different ways in which age and culture might interact to influence emotion and other affective phenomena, review previous research, describe our own work, and then discuss directions for future research. But first we define our terms.

http://dx.doi.org/10.1037/14857-007 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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DEFINITIONS By emotion and other affective phenomena, we broadly refer to states (feelings, emotions, moods, traits) that involve changes in physiology, subjective experience, and behavior in response to a meaningful event. By affect, we are referring to states that are described in terms of the dimensions of valence (negative–positive) and arousal (low–high; e.g., Barrett & Russell, 1999; Larsen & Diener, 1992; Watson & Tellegen, 1985; see Figure 6.1). The valence dimension refers to whether states are associated with gain (positive) or threat/ loss (negative), whereas the arousal dimension refers to whether states are associated with increased energy and mobilization (high arousal) or decreased energy and rest (low arousal). Thus, states such as excitement and enthusiasm are classified as high arousal positive states (HAP), whereas states such

High Arousal (HA) HAN

Aroused Astonished Surprised

Fearful Hostile Nervous

Negative (N)

Positive (P)

Unhappy Sad Lonely

Happy Content Satisfied

LAP

LAN

Dull Sleepy Sluggish

HAP

Enthusiastic Elated Excited Euphoric

Low Arousal (LA) Idle Passive Inactive

Relaxed Calm Peaceful Serene

Figure 6.1.  Two-dimensional model of affect. From Handbook of Culture and Consumer Behavior (p. 70), by S. Ng and A. Y. Lee (Eds.), 2015, New York, NY: Oxford University Press. Copyright 2015 by Oxford University Press. Reprinted with permission.

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as calm and relaxation are classified as low arousal positive states (LAP). We focus on affective states because previous studies have demonstrated that these dimensions hold across a variety of cultures and languages, and are therefore comparable across cultures (e.g., Russell, Lewicka, & Nitt, 1989). By aging, we refer to biological, psychological, and social processes that occur over the course of the human lifespan, from birth to death. In this chapter, we focus primarily on adulthood and therefore describe processes that occur from age 18 onward. By culture, we refer to the shared, historically derived, and socially transmitted ideas that are reflected in widely distributed artifacts, practices, and institutions and that are both products of human action (i.e., created by humans) and producers of future human action (i.e., shapers of future human behavior; Adams & Markus, 2004; Kroeber & Kluckhohn, 1952). Cultural ideas exist regarding almost all types of human activity (Shore, 1996), including affect and aging. For instance, in the context of affect, cultures differ in their beliefs about what feelings are desirable to experience as well as appropriate to express, and these beliefs are reflected in advertisements, books, and other forms of media (e.g., Tsai, Louie, Chen, & Uchida, 2007). In the context of aging, cultures differ in their views of older adults as well as in their beliefs about what constitutes a desirable way to age (Liu, Ng, Loong, Gee, & Weatherall, 2003). Because cultural ideas are so pervasive, people often assume they are “natural” and “universal.” For this reason, cross-national comparisons are critical for revealing and understanding how affect and aging are shaped by cultural factors. TWO HYPOTHESES REGARDING THE INTERSECTION OF AGE, AFFECT, AND CULTURE Two main hypotheses regarding the effects of age and culture on emotion and other affective phenomena exist. The first is that age-related changes in emotion are universal, and therefore, are similar across cultural contexts (universal hypothesis). For instance, socioemotional selectivity theory predicts that across cultures, as people approach the end of their lives, they become increasingly concerned with emotional versus informational goals (Carstensen, Isaacowitz, & Charles, 1999). As a result, people regulate their emotions and environments in order to optimize their emotional experience. Indeed, in both longitudinal and cross-sectional studies, Carstensen and others have observed that older adults experience similar or greater levels of positive affect and lesser levels of negative affect than younger adults (e.g., Carstensen, Pasupathi, Mayr, & Nesselroade, 2000; Carstensen et al., 2011; Charles, Reynolds, & Gatz, 2001; Mroczek & Kolarz, 1998). These findings emotional aging in different cultures     

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have been replicated in different cultural contexts (for a review, see Diener & Suh, 1998), such as Germany (Riediger, Schmiedek, Wagner, & Lindenberger, 2009) and China (Pethtel & Chen, 2010). The second hypothesis is that the effects of age on affective processes vary across cultures and are more pronounced in some contexts and less pronounced or even nonexistent in others (culture-specific hypothesis). For instance, while older adults reported higher intensity of positive experiences and lower intensity of negative experiences than younger adults in the United States, these age differences were not observed in Japan (Grossmann, Karasawa, Kan, & Kitayama, 2014). Almost by definition, the culture-specific hypothesis is more complex than the universal hypothesis because it highlights the importance of understanding not only cultural ideas about emotion but also cultural ideas about aging and other relevant constructs (see Yoon, Hasher, Feinberg, Rahhal, & Winocur, 2000, for an example on memory). To examine whether the universal or culture-specific hypothesis is most supported by the existing literature, we reviewed empirical studies that examined at least one aspect of emotional functioning, that included more than one ethnic or cultural group, and that systematically compared age groups in adulthood. These studies are listed by year and summarized in Table 6.1. As mentioned earlier and illustrated in Table 6.1, surprisingly little research has been conducted on affect and aging across cultures. Despite this, several patterns emerge from the handful of studies that do exist: (a) as most studies on aging, the majority of these studies are cross-sectional; (b) almost all have focused on age differences in people’s actual affective experiences (i.e., the feelings they are experiencing or have experienced); and (c) most studies reveal more cultural similarities than differences. For instance, as mentioned earlier, across cultures, actual affective experience has consistently been found to improve (typically characterized as either increases in positive affect, decreases in negative affect, or both) through middle age, eventually plateauing in older adulthood. One reason that previous studies have observed more cultural similarities than differences may be because they focus on how people actually feel (their “actual affect”) rather than how people ideally want to feel (their “ideal affect”). As described next, affect valuation theory (AVT) predicts that cultural factors may shape ideal affect more than actual affect. AFFECT VALUATION THEORY AVT has three main premises: (a) actual affect differs from ideal affect; (b) cultural factors shape ideal more than actual affect; and (c) how people want to feel has important consequences for a variety of outcomes, including what they do to feel good, how they conceive of health and well-being, what 122       tsai and sims

TABLE 6.1 Review of Cross-Cultural Studies Comparing the Effects of Age on Affect Study Carstensen, Pasupathi, Mayr, & Nesselroade (2000) Tsai, Levenson, & Carstensen (2000) Norris, Kaniasty, Conrad, Inman, & Murphy (2002) Blanchflower & Oswald (2004)

Dependent variable

Age range

Cultural groups

Experience sampling of positive and negative affect frequency

18–94

European American, African American

Online and retrospective reports of positive and negative affect after watching film clips Clinical assessment of PTSD symptoms after disaster

Young (20–34), Older (70–85)

European American, Chinese American

18–88

American (non-Hispanic), Mexico, Poland

Lifespan sample (age range not reported)

Black and White, American and British

Global single-item reports of happiness

Age effect None for positive affect; decrease in negative affect until middle age and then plateau in old age None for negative affect; decrease in retrospective report of positive affect Decrease through middle-age and then increase for U.S.; increase for Poland; decrease for Mexico Increase in happiness until 60s and then decline in old age

Universal vs. culture-specific Universal

Universal

Culturespecific

Universal (continues)

TABLE 6.1 Review of Cross-Cultural Studies Comparing the Effects of Age on Affect  (Continued) Study Blanchflower & Oswald (2008)

Dependent variable Global single-item reports of happiness

Age range 20–85+

Cultural groups

Age effect

Albania, Argentina, Australia, Azerbaijan, Belarus, Belgium, Bosnia, Brazil, Brunei, Bulgaria, Cambodia, Canada, Chile, China, Colombia, Costa Rica, Croatia, Czech Republic, Denmark, Dominican Republic, Ecuador, El Salvador, Estonia, Finland, France, Germany, Greece, Honduras, Hungary, Iceland, Iraq, Ireland, Israel, Italy, Japan, Kyrgyzstan, Laos, Latvia, Lithuania, Luxembourg, Macedonia, Malta, Mexico, Myanmar, Netherlands, Nicaragua, Nigeria, Norway, Paraguay, Peru, Philippines, Poland, Portugal, Puerto Rico, Romania, Russia, Serbia, Singapore, Slovakia, South Africa, South Korea, Spain, Sweden, Switzerland, Tanzania, Turkey, UK, Ukraine, Uruguay, U.S., Uzbekistan, Zimbabwe

Increase in happiness until 60s and then decline in old age

Universal vs. culture-specific Universal

You, Fung, & Isaacowitz (2009) Pethtel & Chen (2010)

Global reports of trait optimism

Young (18–28), Older (52–84)

American, Hong Kong Chinese

Global reports of trait positive and negative affect Experience sampling of positive and negative affect frequency

Young (18–29), Older (60–92)

American, Mainland Chinese

18–94

European American, African American

Fung & You (2011)

Situation sampling of anger responses in a relational context

Young (18–24), Older (57–87)

Hong Kong Chinese, Mainland Chinese

Karasawa et al. (2011)

Global reports of hedonic well-being (positive and negative affect frequency) Situation sampling of recalled emotion intensity in positive and negative experiences

25–74

American, Japanese

25–79

American, Japanese

Carstensen et al. (2011)a

Grossmann, Karasawa, Kan, & Kitayama (2014)

Note.  We mention only the affective variables for each study. aOnly study using longitudinal design; all others are cross-sectional.

Increase for U.S.; decrease for Hong Kong None for positive affect; decrease in negative affect Increase in positive relative to negative affect through old age and then plateaus In family situations, decrease in anger among Hong Kong and increase in anger for Mainland Increase in positive affect; decrease in negative affect; Higher intensity in positive experiences and lower intensity in negative experiences for U.S.; no effect for Japan

Culturespecific Universal Universal

Culturespecific

Universal

Culturespecific

consumer products they prefer, and even how they judge other people, above and beyond the effects of actual affect (Tsai, 2007). We next discuss each premise of AVT in more detail. Actual Affect Differs From Ideal Affect Most research in psychology has focused on how people actually feel, or what we refer to as their actual affect. Actual affect is a response to an immediate event or outcome (momentary actual affect) or a tendency to respond in a particular way to different events or outcomes (global actual affect). In contrast, ideal affect is a goal or desired state that people may work—consciously or not—to achieve. Whereas actual affect is a summary of one’s state (“How am I feeling?”), ideal affect provides a way of evaluating that state (“Is this feeling good and right?”). Ideal affect also serves as a guide for future behavior (“Is this person, activity, event going to make me feel how I want to feel?”). When we ask participants to rate how much they actually feel the various affective states listed in Figure 6.1, and how much they ideally want to feel them on average, across cultures, participants report wanting to feel more positive than negative, and wanting to feel more positive and less negative than they actually feel (Koopmann-Holm & Tsai, 2014; Sims, Tsai, Jiang, et al., 2015; Tsai, Knutson, & Fung, 2006). This distinction between ideal and actual affect has been observed in several other studies as well (Barrett, 1996; Chow & Berenbaum, 2012; Kämpfe & Mitte, 2009; Ruby, Falk, Heine, Villa, & Silberstein, 2012; Rusting & Larsen, 1995; Scheibe, English, Tsai, & Carstensen, 2013; Scollon, Howard, Caldwell, & Ito, 2009; Västfjäll, Gärling, & Kleiner, 2001). Structural equation modeling also reveals that actual affect and ideal affect are distinct constructs that are weakly to moderately correlated with each other (Koopmann-Holm & Tsai, 2014; Tsai et al., 2006). Moreover, across several studies, we have demonstrated that actual affect and ideal affect exert independent effects on various behaviors (e.g., Sims, Tsai, Koopmann-Holm, Thomas, & Goldstein, 2014; Sims & Tsai, 2015b; Tsai, 2007; Tsai, Miao, et al., 2007). Culture Shapes Ideal Affect More Than Actual Affect The second premise of AVT is that although most people want to feel good, culture shapes the specific positive states they want to feel. Shweder (2003) and Rozin (2003) argued that culture teaches people what is good, moral, and virtuous as well as what is bad, immoral, and sinful. In our work over the last 10 years, we have applied this idea to affect, and we argue that culture teaches people what feelings are good, moral, and virtuous. In recent work, we have also demonstrated that cultures teach people what feelings are 126       tsai and sims

undesirable, or which states people should want to avoid (avoided affect; see Koopmann-Holm & Tsai, 2014). We have primarily tested the notion that cultures differ in their ideal affect by comparing North American and Chinese contexts (Tsai et al., 2006; Tsai, Miao, et al., 2007). One major distinction between North American and Chinese contexts is the degree to which they are individualistic (vs. collectivistic), or the degree to which they emphasize individual vs. group goals. We predicted that differences in individualism–collectivism would shape the affective states that European Americans and Chinese ideally want to feel. North American contexts are more individualistic and promote an independent view of self in which one of people’s main goals is to influence others (i.e., express and assert their beliefs, desires, and preferences, and change their environments so that they are consistent with these beliefs, desires, and preferences). In contrast, Chinese and many other East Asian contexts are more collectivistic and promote an interdependent self in which one of people’s main goals is to adjust to others (i.e., suppress their beliefs, desires, and preferences in order to accommodate those of the group). We predicted that because influence requires action, and action involves increases in physiological arousal, the more cultures and individuals value influence, the more they want to feel HAP states such as excitement. Conversely, because adjustment requires suspended action (at least initially) so that individuals can assess the needs of others, and decreases in action involve reduced physiological arousal, the more cultures and individuals value adjustment, the more they want to feel LAP states such as calm (Tsai, Miao, et al., 2007). As predicted, in several survey studies, European Americans reported wanting to feel HAP states more than Hong Kong Chinese, and Hong Kong Chinese reported wanting to feel LAP states more than European Americans (Tsai et al., 2006; Tsai, Miao, et al., 2007, Study 1). In addition, Chinese Americans and other East Asian Americans (who are oriented to both American and Chinese/East Asian contexts) valued HAP states at similar levels as their European Americans counterparts and more than their Hong Kong Chinese counterparts, but valued LAP states at similar and sometimes greater levels as their Hong Kong Chinese counterparts and more than their European American counterparts. Moreover, these cultural differences were mediated by influence and adjustment goals (Tsai, Miao, et al., 2007), suggesting that ideal affect is not only hedonic but also instrumental. These cultural differences emerge in widely distributed cultural products such as web-based profiles, American advertisements, and bestselling children’s storybooks (Tsai, 2007; Tsai, Louie, et al., 2007). For instance, recently we found that American CEOs and university presidents displayed more excited smiles than Chinese CEOs, government leaders, and university presidents in official photographs posted on their websites (Tsai et al., in press). emotional aging in different cultures     

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These findings suggest that one way in which people learn to value specific affective states is by being exposed to various products that reflect a culture’s ideal affect. Indeed, when European American, Asian American, and Taiwanese preschoolers were exposed to stories that emphasized excitement (vs. calm) and were then asked whether an excited or calm face was “more happy,” preschoolers across cultural contexts were more likely to choose the excited smile if they had read the “exciting” story and the calm smile if they had read the “calm” story (Tsai, Louie, et al., 2007). These cultural differences in ideal affect often emerge against a backdrop of cultural similarities in actual affect. In cases in which group differences in actual affect do emerge, the group differences in ideal affect remain significant even after controlling for actual affect (e.g., Tsai et al., 2006). Furthermore, when we control for extraversion and neuroticism, these group differences in actual affect often disappear (e.g., Tsai et al., 2006). These findings support the second part of the second premise of AVT that temperamental factors shape actual more than ideal affect. Consistent with this prediction, survey studies have demonstrated that neuroticism and extraversion (which are associated with temperament) account for greater variance in actual LAP and HAP, respectively, than ideal LAP and ideal HAP, whereas cultural factors such as influence and adjustment goals shape ideal HAP and ideal LAP more than actual HAP and actual LAP (Tsai et al., 2006, 2007). Although many theories of emotion acknowledge the influences of temperamental and cultural factors, AVT is one of the first to specify the ways in which cultural and temperamental factors shape affective functioning. Ideal Affect Predicts Daily Behavior The third premise of AVT is that people’s ideal affect has various consequences for their behavior. Although most people want to feel good, what they specifically do to feel good should vary depending on how they ideally want to feel. For instance, the more a person wants to feel HAP, the more likely she may be to go to an exciting movie when she feels bad, whereas the more a person wants to feel LAP, the more likely she may be to stay at home and read a book when she feels bad. Indeed, the more people value HAP, the more likely they are to mention many different activities and to mention exciting (vs. calm) activities when describing their ideal vacations (Tsai, 2007). People’s ideal affect also predicts their consumer preferences: The more people value HAP states and the less they value LAP states, the more they prefer exciting (vs. calming) lotions, gums, music, and even physicians (Sims & Tsai, 2015b; Sims, Tsai, et al., 2014; Tsai, 2007; Tsai, Chim, & Sims, 2015). People’s ideal affect also shapes their conceptions of well-being and depression: The more people value HAP states, the more likely they are 128       tsai and sims

to define well-being in terms of feeling excitement and other HAP states, and the more likely they are to define depression as the opposite of HAP states—i.e., sluggishness, boredom, and other low arousal negative states (Tsai, 2007). Finally, ideal affect even appears to shape how people respond to others—people perceive targets whose affective characteristics match their ideal affect as more trustworthy (Sims et al., 2014). Thus, because ideal affect has consequences for daily behaviors, and cultures differ in their ideal affect, we predict that there are cultural differences in the degree to which people engage in excited versus calm activities. Indeed, European Americans mention more activities and more excitement compared with Hong Kong Chinese when describing their ideal vacations, and these differences are mediated by ideal affect (Tsai, 2007). European Americans are more likely to choose exciting (vs. calm) consumer products than their Hong Kong Chinese counterparts, and these differences are again due to ideal affect (Tsai, Chim, & Sims, 2015). European American conceptions of happiness and well-being contain more HAP and less LAP than Hong Kong Chinese conceptions of happiness and well-being (Tsai & Hong, 2015). European Americans are also more likely to choose and recall more recommendations from “exciting” vs. “calm” physicians compared to Asian Americans (Sims & Tsai, 2015a). Recent neuroimaging evidence even suggests that European Americans find excited (vs. calm) faces to be more rewarding compared to Chinese (Park, Tsai, Chim, Blevins, & Knutson, 2015). Together, these findings suggest that because cultures differ in their ideal affect, and ideal affect is linked to various behaviors, one source of cultural differences in these behaviors may be ideal affect. EFFECTS OF AGE ON ACTUAL AND IDEAL AFFECT Because most of the work described above has focused on college student samples, we know little about how ideal affect changes with age. Previous work has demonstrated age-related changes in affect regulation goals. For example, in a German sample ranging from 14 to 86 years of age, older participants reported wanting to maintain their current experience of positive affect and wanting to dampen their experience of negative affect more than their younger counterparts (Riediger et al., 2009). Interestingly, adolescents wanted to maintain or enhance the level of negative affect they were experiencing more than middle-aged or older adults. However, this work focused on how people want to change or influence their current affective states rather than what people ultimately want to feel, independent of how they are actually feeling. Moreover, the authors did not distinguish between different types of positive and negative states (Riediger et al., 2009). emotional aging in different cultures     

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Scheibe and colleagues (2013) addressed this gap by assessing in a North American sample how much people wanted to feel different types of positive and negative states. Specifically, Scheibe et al. compared global ratings of actual and ideal HAP and LAP in a primarily European American sample ranging from 18 to 93 years of age. How often people wanted to feel LAP states increased until age 70 and then declined. In contrast, the degree to which people wanted to feel HAP states remained relatively stable until age 70 and then declined. Moreover, with age, there was an increasing emphasis on LAP versus HAP states. In terms of actual affect, actual LAP increased steadily with age and then tapered off at advanced old age, whereas actual HAP remained steady with age. Importantly, the age-related changes in ideal HAP and LAP held after controlling for actual HAP and LAP, suggesting that they were not due to age-related changes in actual affect. However, because this study focused on an American sample, it remains an open question whether these age-related changes in ideal and actual affect hold across cultures. Role of Cultural Ideals of Healthy Aging Although there are many ways in which cultures might differ in their views of or attitudes toward aging (Löckenhoff et al., 2009), we have been particularly interested in cultural differences in people’s ideals of healthy aging and how they might impact people’s ideal affect. Because Americans believe that they exist independently of their circumstances and that they should influence their environments (Morling, Kitayama, & Miyamoto, 2002; Schwartz & Ros, 1995), the ideal way to age in American culture is to actively resist aging as a way of maintaining youth. Indeed, the more European Americans identify with being young, the happier and healthier they are (Barak & Rahtz, 1999; Montepare & Lachman, 1989). Thus, even while their minds and bodies are aging, Americans believe they can fight old age by exercising their minds and bodies, having cosmetic surgery, and keeping active (Bayer, 2005; Rubinstein & Canham, 2008). The American emphasis on maintaining youth may explain why European American contexts “rarely specify in any detail” roles for individuals after they reach 60 years of age (Kitayama, 2001, p. 223) and why many Americans deny the changes that accompany aging (Barak, Mathur, Lee, & Zhang, 2001; Barak & Rahtz, 1999; Öberg & Tornstam, 2001; Westerhof & Barrett, 2005). In contrast, because Chinese culture emphasizes adjusting to one’s circumstances (Morling et al., 2002) and accepting change (vs. stability) as a normal part of life (Ji, 2008), Chinese and people from other East Asian contexts may be more accepting of and even value age-related change compared with Americans (Kitayama, 2001). Indeed, whereas Americans want to be 10 to 130       tsai and sims

20 years younger than they are, Chinese want to be only 3 years younger than they are (Westerhof & Barrett, 2005). Moreover, rates of anti-aging cosmetic surgery are over 10 times lower for Asian Americans than European Americans (American Society of Plastic Surgeons, 2014). Together, these data suggest that Chinese may place more value on their current age than Americans do. We directly tested this prediction in an unpublished study of 109 European American, 59 Asian American, and 109 Hong Kong Chinese undergraduate college students (58.5% female, average age = 20.26 [SD = 2.10] years). To assess the value placed on accepting the aging process, we asked participants “How important is it to (act/feel/dress/be perceived as) your current age?” on a scale from 1 = not at all to 5 = extremely important. Our main prediction was that Hong Kong Chinese would endorse “being one’s current age” more than would European Americans, with Asian American falling in the middle. As illustrated in Figure 6.2 (left), our findings supported this prediction. Moreover, when asked how important it was for people in their 20s, 40s, and 60s to “act their current age,” we found a similar pattern across all ages: Hong Kong Chinese and Asian Americans rated that it was more important for people in their 20s, 40s, and 60s to be their current age than did European Americans (Figure 6.2, right). Although these findings are preliminary, they support the idea that Chinese people value being one’s current age more than European Americans do. It is important to note that although related, we conceptualize ideals of healthy aging as distinct from views of old age. While ideals of healthy aging refer to the desired process of aging (i.e., how people want to age over time), views of old age refer to a perceived outcome of aging (i.e., how people perceive themselves or others during old age). Although the two may be related, they are conceptually independent. For instance, while two people may hold similar negative views of old age (e.g., as undesirable), one person might believe that resisting old age and acting as young as possible is the best way

How Important Is It To YOU To Be Your Current Age?

5

European Americans

4

b a

3

2

Importance Rating

Importance Rating

5

How Important Is It That OTHERS Be Their Current Age?

European Americans Chinese Americans

Hong Kong Chinese

Hong Kong Chinese a

3

a b

2

1

1

Asian Americans

4

20s

40s

60s

80s

Others' Age

Figure 6.2.  Ideals of healthy aging by cultural group. emotional aging in different cultures     

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to age, whereas the other might believe that accepting one’s age and acting one’s age is the best way to age. In the cross-cultural literature, previous work has demonstrated that while most cultures associate old age with physical and cognitive decline, American culture holds a more negative societal view of old age than Chinese culture does (Barak et al., 2001; Chang, Chang, & Shen, 1984; Levy & Langer, 1994; Löckenhoff et al., 2009; Streib, 1987). Indeed, Löckenhoff et al. (2015) argued that the previous literature comparing attitudes toward aging in Eastern and Western contexts is mixed because studies differ in which attitudes they are examining (i.e., some examine attitudes toward older adults, whereas others examine attitudes toward one’s own aging). In our own work, we are interested in how American and Chinese ideally want to age (i.e., by resisting or accepting changes resulting from the aging process) because we expect this is especially relevant for age-related changes in ideal affect. For example, if European Americans believe they should resist aging, then European older adults should endorse affective ideals that are similar to those of their younger peers, regardless (or even in spite) of how they actually feel. Thus, we would predict few age-related changes in ideal affect among European Americans. However, if Chinese think they should accept aging, then they should adjust their affective ideals to be consistent with how they actually feel. Both the AVT and the universal hypothesis make similar predictions about actual affect. AVT predicts that culture would shape ideal affect more than actual affect. Therefore, we predicted that age differences in actual affect should hold across cultures in ways that are consistent with socioemotional selectivity theory (Jiang, Fung, Sims, Tsai, & Zhang, 2015; Scheibe et al., 2013). Specifically, across cultures, as people age, they should experience increases in LAP and no changes in HAP. To begin to test these hypotheses, in collaboration with Helene Fung and her students at the Chinese University of Hong Kong, we conducted a study of actual and ideal affect among 244 European Americans, 253 Chinese Americans, and 321 Hong Kong Chinese adults from 20 to 80 years of age (Tsai, Sims, Jiang, Fung, & Thomas, 2015, Study 1). Participants completed a survey, which included measures of global actual and ideal affect. Specifically, participants were asked to report how often, over the course of a typical week, they actually feel and ideally want to feel the affective states shown in Figure 6.1. Figure 6.3 illustrates the results of global actual and ideal HAP (top) and LAP (bottom) for European Americans (left), Chinese Americans (middle), and Hong Kong Chinese (right). The dotted lines reflect actual affect, and the solid lines reflect ideal affect. Consistent with our hypotheses and findings from Scheibe et al. (2013), across cultural groups, actual HAP remained stable with age, whereas actual LAP steadily increased with age, particularly after age 40. In other words, people’s experience of excitement and 132       tsai and sims

4

3

1 Younger

Middle

EA Ideal LAP

CA Actual HAP

HK Ideal HAP

4

3

2

4

3

2

1 Younger

EA Actual LAP

Middle

CA Ideal LAP

Older

4

4

4

Affect Frequency

5

3

2

Younger

Middle

Older

Older

HK Actual LAP

3

2

1

1

1

Middle

HK Ideal LAP

5

2

Younger

CA Actual LAP

5

3

HK Actual HAP

5

1

Older

Affect Frequency

Affect Frequency

emotional aging in different cultures     

2

CA Ideal HAP

5

Affect Frequency

Affect Frequency

EA Actual HAP

Affect Frequency

EA Ideal HAP

5

Younger

Middle

Older

Younger

Middle

Older

Figure 6.3.  Age differences in actual and ideal high arousal positive [HAP] states (top) and actual and ideal low arousal positive states [LAP] (bottom) for European Americans [EA] (left), Chinese Americans [CA] (middle), and Hong Kong Chinese [HK] (right). Error bars refer to standard error.

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other HAP states remained stable and their experience of calm and other LAP states increased with age, and this held across European Americans, Chinese Americans, and Hong Kong Chinese. In contrast, but also consistent with our hypotheses, the effects of age on ideal HAP and LAP varied across cultures. For European Americans, ideal HAP and ideal LAP remained stable with age: Older adults wanted to feel HAP and LAP as much as their younger counterparts did. This pattern is consistent with American ideals of being young and maintaining youthful ideals. However, for Chinese Americans and Hong Kong Chinese, there was a steady decline in wanting to feel HAP states across the lifespan, and a decline in wanting to feel LAP states from middle age to older age. This pattern is consistent with Chinese respondents adjusting their ideals to be more consistent with the aging process (i.e., with age-related change in actual affect). Implications for Well-Being We predicted that across cultures, older individuals would show smaller discrepancies between their actual and ideal affect than younger adults. However, we predicted that Hong Kong and Chinese American older adults would show even smaller discrepancies than European Americans because for these groups, age differences in actual affect would be accompanied by age differences in ideal affect. Indeed, as Figure 6.3 illustrates, European American older adults had greater discrepancies in ideal-actual HAP and LAP than did Chinese American and Hong Kong older adults. In other words, because Hong Kong older adults wanted to feel HAP and LAP to a lesser degree than did European American older adults, their actual affect more closely approximated their ideals. This was especially the case for LAP states: Hong Kong Chinese older adults wanted to feel LAP almost as much as they actually felt LAP. Importantly, because European Americans showed no changes in actual or ideal HAP, there were no age differences in the discrepancy between actual-ideal HAP. In other words, older and younger European Americans are equally unlikely to feel the excitement they want to feel. European Americans did show smaller discrepancies with age in ideal-actual LAP, largely due to increases in actual LAP. Together, these findings suggest that while the effects of age on the affective states that people actually experience appear to be similar across cultural contexts, the effects of age on the affective states that people ideally want to experience vary across cultural contexts. Furthermore, this cultural variation may have consequences for people’s emotional health. As demonstrated in previous work (Tsai et al., 2006), larger discrepancies between ideal and actual affect significantly predict worse emotional health outcomes, such as higher levels of depression. Although European American older adults did 134       tsai and sims

show smaller discrepancies than European American younger adults for LAP, they did not differ from their younger counterparts in terms of HAP. However, Chinese American and Hong Kong Chinese older adults showed even smaller discrepancies for both HAP and LAP than did their younger counterparts, suggesting that they may be in better emotional health than their European American peers. Future research is needed to explore this possibility further. Implications for Personal Expectations of Old Age What other implications do cultural differences have for the effects of age on ideal affect? Is it healthy for European Americans to not adjust their ideals and for Chinese Americans and Hong Kong Chinese to adjust their ideals as they age? To examine this question, in the same study described above (Tsai, Sims, et al., 2015), we asked participants to answer two questions that assessed their personal expectations of old age: “What are you looking forward to about being 75 and older?” and “What are you dreading about being 75 and older?” We tallied the number of responses to each question and then subtracted the number of responses to the dreading question from the number of responses to the looking forward question to create an overall measure of participants’ personal positive expectations of old age. Hong Kong Chinese and Chinese Americans reported more positive expectations of old age than did European Americans, particularly among older adults. Chinese American older adults had the most positive expectations of old age. We then examined the relationship between ideal HAP and personal expectations of old age. We predicted that because aging is associated with cognitive and physical decline that limits tolerance of highly arousing states (Charles, 2010), the more that people valued HAP states, the more negative their personal expectations of old age would be. In support of this hypothesis, analyses revealed that the more people valued HAP states, the more negative were their personal expectations of old age. In addition, the cultural differences in personal expectations of old age described above were mediated by ideal HAP. Importantly, the reverse mediation did not hold (i.e., cultural differences in ideal HAP among older adults were not mediated by personal expectations of old age). In other words, one reason Americans may hold more negative expectations of old age compared with Chinese and Chinese Americans—especially among those approaching old age—is that they value HAP states more. Valuing excitement may make people dread the times when they will be unable to be as physically active and cognitively alert as they would like to be. Finally, in another sample, we manipulated ideal HAP and ideal LAP using a values affirmation instruction. We randomly assigned 26 American, 25 Asian American, and 18 Hong Kong participants to one of two conditions. emotional aging in different cultures     

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In the value HAP condition, participants read a paragraph describing research findings that feeling “stimulated and invigorated” leads to successful life outcomes. They were then asked to write about three personally meaningful experiences that supported these findings. In the value LAP condition, participants read a paragraph about the benefits of feeling “tranquil and well rested” and then wrote about three personally meaningful experiences that supported these findings. Afterward, participants listed what they looked forward to and dreaded about being age 75 and older. Participants in the value HAP condition had less positive expectations of old age (i.e., listed fewer “looking forward” and more “dreading” items) than did those in the value LAP condition (Tsai, Sims, et al., 2015, Study 2). These findings provide some evidence that valuing HAP results in more negative personal expectations of old age. Given the importance of expectations and other views of old age for health (Levy & Langer, 1994; Levy, Slade, Kunkel, & Kasl, 2002), these findings suggest that the American ideal of excitement may ultimately hurt older adults, and might be one reason for the national differences in life expectancy described at the beginning of this chapter. FUTURE RESEARCH DIRECTIONS This work generates more research questions than answers. First, most of the research, including our own, has employed cross-sectional designs. Only multicohort longitudinal designs can truly demonstrate age-related change. Second, few studies have measured how cultural ideals of healthy aging or other relevant constructs interact with cultural ideals of emotion to shape emotional functioning. Instead, most work simply compares the affect of two cultural groups, without measuring anything about the culture. For instance, in the studies described above (Tsai, Sims, et al., 2015), we did not explicitly assess cultural ideals of healthy aging; therefore, we cannot demonstrate that this was the cause of our findings. Fortunately, cultural psychology has developed methods ranging from self-report measures to experimental manipulations to analyses of cultural products to assess cultural constructs, and these methods can be easily adapted to examine constructs relevant to emotional aging (see Zhang & Tsai, 2014). Third, we have argued for and demonstrated the importance of studying ideal affect. It would also be important to investigate age differences in avoided affect or the affective states that people want to avoid, which has not yet been investigated in age-diverse samples. While avoided affect refers primarily to negative states, it also varies across cultures. For instance, Americans want to avoid negative states more than do Germans, and as a result, Americans 136       tsai and sims

focus on the positive more and the negative less than Germans do when expressing sympathy (Koopmann-Holm & Tsai, 2014). It would be interesting to examine whether the degree to which people want to avoid negative affect decreases with age, whether this is related to increased experience of mixed emotions with age (e.g., Carstensen et al., 2011), and whether these relationships vary across cultures (cf. Williams & Aaker, 2002). In addition, future studies should examine the degree to which ideal and avoided affect moderate affect regulation goals, and whether this varies across cultures. Finally, in most studies of emotional aging, there is relatively little examination of the lives that participants lead (Sims, Hogan, & Carstensen, 2015). Such studies are needed to understand the degree to which culture shapes emotional aging relative to other factors such as biological change. Such studies would reveal potential accumulative effects of daily emotional experiences on aging, and whether this varies by cultural context. For instance, previous studies have shown cultural differences in the links between emotional experience and health (e.g., Consedine, Magai, & Horton, 2005; Curhan et al., 2014; Diener & Suh, 2000; Mauss & Butler, 2010; Miyamoto et al., 2013; Soto, Perez, Kim, Lee, & Minnick, 2011). However, no studies have examined whether these cultural differences apply to older adults. CONCLUSION Most cross-cultural studies of affect across the lifespan have demonstrated cultural similarities. We argue that this is because they have focused on people’s actual affect rather than their ideal affect, or how they ideally want to feel. Here, we described data demonstrating differences in ideal affect among European American, Chinese American, and Hong Kong Chinese older adults, and the implications the data have for well-being and personal expectations of old age. These findings, while only a first step, demonstrate the utility and importance of expanding studies to include other cultural groups, other cultural constructs, and other facets of emotion. REFERENCES Adams, G., & Markus, H. R. (2004). Toward a conception of culture suitable for a social psychology of culture. In M. Schaller & C. S. Crandall (Eds.), The psychological foundations of culture (pp. 335–360). Hillsdale, NJ: Erlbaum. American Society of Plastic Surgeons. (2014). 2013 Plastic surgery statistics report. Retrieved from http://www.plasticsurgery.org/news/plastic-surgery-statistics/ 2013.html emotional aging in different cultures     

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IV Health Implications

7 BRIDGING THE DYNAMIC ASPECTS OF PERSONALITY AND EMOTION THAT INFLUENCE HEALTH EMILY D. BASTARACHE AND DANIEL K. MROCZEK

The relationship between personality—including emotion and emotional styles—and health is dynamic. Personality and emotions change over the lifespan, and so does physical health. In this chapter, we describe two ways that personality and emotion are dynamic, and we show that these dynamic features influence an important health outcome: longevity, as defined by mortality risk. The first of these dynamic qualities is long-term personality trait change, and the other is short-term emotional reactivity. We aim to demonstrate in this chapter that dynamic aspects of psychological variables, whether long-term and estimated over years or short-term and estimated over days, both have an impact on health and mortality risk. First, we present previous empirical work establishing personality and emotional reactivity as predictors of mortality, followed by a brief discussion and some evidence for potential mediators of these associations. Next, we transition

http://dx.doi.org/10.1037/14857-008 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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into a discussion of the dynamics of these associations, that is, how the change in personality and emotional reactivity relate to change in mortality risk. We provide an in-depth look at two studies that look at predictors of mortality risk: Mroczek et al. (2013) demonstrated day-to-day change in emotional reactivity in response to daily stressors over a brief 8-day period, whereas Mroczek and Spiro (2007) demonstrated long-term change in personality traits over a more diffuse 10-year period. We discuss how bridging these short- and longrange measures may elucidate mechanisms for which the day-to-day experiences may contribute to long-term change that influences health. Through identification of links between short- and long-term measures, we may be able to mold large-scale constructs via their corresponding small-scale parallel construct. Throughout the chapter, we also briefly discuss the implications of these studies in the context of potential for promoting healthy aging, previous and potential interventions, as well as future directions in the field. PERSONALITY AND EMOTIONAL REACTIVITY AS PREDICTORS OF MORTALITY It has been well established that personality traits predict mortality risk. For instance, conscientiousness predicts mortality risk (Friedman et al., 1993), even upon adjusting for cognitive functioning and education (Hill, Turiano, Hurd, Mroczek, & Roberts, 2011). Several studies have also established neu­ ro­ticism as a risk factor, suggesting that on average, elevated levels of neuroticism are associated with elevated levels of mortality risk, controlling for many confounding variables (Almada et al., 1991; Hagger-Johnson et al., 2012; Mroczek, Spiro, & Turiano, 2009; Weiss & Costa, 2005; Wilson et al., 2003, 2004). Furthermore, long-term personality change has been implicated in mortality risk (Mroczek & Spiro, 2007), lending credence to the idea that not only level but also change in personality or emotional variables, can be a predictor of important health outcomes. Moreover, such change does not have to encompass long-term trajectories and can unfold over more brief periods of time. For instance, in previous work, daily changes in affect as a function of stress were shown to predict health outcomes (Piazza et al., 2013). While elevation in negative affect in response to daily stressors is a normative experience, the degree of increase in negative affect, or reactivity to stress (i.e., emotional reactivity) varies widely between individuals (Mroczek & Almeida, 2004). While not a personality trait per se, emotional reactivity, particularly negative emotional reactivity to threat, loss, or stress, is indeed a defining feature of the established Big Five trait Neuroticism. Change in affect in response to stressors is also in essence selfregulation of emotion in response to stressors. With that said, Bandura (1999) 148       bastarache and mroczek

would argue that self-regulation is a broad type of personality characteristic, with which Mroczek, Spiro, Griffin, and Neupert (2006) would agree, and designate mood regulation as one of three components of self-regulation. Some researchers would argue that emotional reactivity may also be considered a part of a layer of personality designated as characteristic adaptations, namely, idiosyncratic manners of responding and adjusting to the environment (McAdams & Pals, 2006). Hence, long-term trends in traits (growth curves) and short-term dynamics of emotional reactivity may be fundamentally linked. In fact, previous work has shown that between-individual variation in emotional reactivity is related to individual neuroticism (Mroczek & Almeida, 2004). This inter­ action between neuroticism and reactivity to daily stress suggests that those high on neuroticism experience greater negative affect in response to daily stress compared with those low on neuroticism experiencing comparable levels of daily stress. That is, individuals who exhibit heightened levels of neuro­ ticism also tend to have increased emotional reactivity. Healthier reactivity is designated by low reactivity, in other words, smaller increases in negative affect in response to stress, which implies “taking things in stride” (Piazza, Charles, Sliwinski, Mogle, & Almeida, 2013) and avoiding unnecessary overactivation of physiological responses (Mroczek et al., 2006) that may be bad for physical health and associated with chronic illness (Cacioppo, 1998). Recent work has been devoted to testing two theories that propose pathways through which personality and emotional reactivity might predict mortality risk. The first, the health behavior model (Smith, 2006), proposes that health behavior mechanisms mediate this association. For example, being high or low on a given personality trait or emotional reactivity may make one more likely to smoke, drink excessively, avoid exercise, and have high adiposity, or have low physician adherence, which, in turn, leads to higher mortality risk. The second theory, the physiological model of personality and health, suggests that physiological mechanisms (Hampson, 2008; Smith, 2006), such as chronically high levels of stress hormones and immune dysfunction (Turiano, Mroczek, Moynihan, & Chapman, 2013), may be the conduit through which personality is linked to mortality risk. Emotional reactivity may also be connected to health outcomes through some of the same conduits or mediators. For instance, stress hormones and inflammatory markers may mediate the association between emotional reactivity and health outcomes (Black, 2003; Sutin et al., 2010). In fact, the goal of specific therapeutic techniques, such as mindfulness-based stress reduction (Kabat-Zinn et al., 1998), focuses on decreasing responsiveness to stressors, which, in turn, results in positive health benefits, including improved immune function, and increased brain activation in regions promoting positive affect (Davidson et al., 2003). Both theories were tested in several different studies; however, for the purpose of the current chapter’s primary point of discussion, we focus on the bridging the dynamic aspects of personality and emotion     

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role of these mediators in terms of bridging the dynamic changes in personality and emotion that influence health. The health behavior model was examined in a 2009 study using a 30-year mortality follow-up in the Boston Veterans Affairs (VA) Normative Aging Study (NAS; Mroczek, Spiro, & Turiano, 2009). In this study, smoking lessened the neuroticism-mortality association, accounting for 25% of the variance in the relationship. A second study, in 2012, also using the VA NAS and having 20 years of mortality follow-up, found that current smoking also mediated the conscientiousnessmortality association, again, supporting the health behavior model (Turiano, Hill, Roberts, Spiro, & Mroczek, 2012). Moreover, using a much larger national sample, the Midlife in the United States (MIDUS) longitudinal study, a third study found three mediators between impulsivity and mortality risk: current smoking, excessive drinking, and adiposity (waist circumference; Turiano et al., 2015). Last, the interaction between two personality traits, in this case, conscientiousness and neuroticism, showed that high levels on both traits predicted healthier levels of interleukin-6, an inflammatory marker linked to chronic diseases, such as cardiovascular disease (Turiano et al., 2013), suggesting lower mortality risk. These studies, among others, provide evidence that both health behaviors and physiological factors are likely mechanisms through which personality predicts mortality risk. The current state of the literature provides far more evidence for health behaviors as mediators than for physiological factors as mediators. However, this is likely a function of the lengthier history of research on health behaviors than on physiological indicators in the field of health psychology. Dynamic factors in the prediction of health, particularly in terms of variables such as personality and emotion have been understudied, yet they represent an important and new area of inquiry. While some of the previous studies provided evidence for the personality–health association, specifically at the personality trait-level, personality change occurring throughout longterm development (Roberts & Mroczek, 2008) has also been shown to affect concomitant changes in mortality risk (Mroczek & Spiro, 2007). To date, more than 50 studies have done growth-curve analyses of personality traits, with at least three measurement occasions over a period of several years, modeling such trajectories of change. Specifically, there is evidence that neuro­t­ icism, as well as other traits, can change over time (Mroczek & Spiro, 2003; Roberts & Mroczek, 2008). Moreover, there are also individual differences in the level and rate of change over time, illustrating the lifespan developmen­ tal principle of individual differences in intra-individual change (Baltes, 1987) where variability in trajectories, that is, variability in slopes, holds. For instance, some individuals remain stable on neuroticism throughout the life course, while others decline at greater or lesser rates comparative to population trends. 150       bastarache and mroczek

While a small amount of previous work has focused on emotion as a predictor of health outcomes (Carstensen et al., 2011; Ong, Mroczek, & Riffin, 2011; Wilson et al., 2003), even less has been completed on the association between the dynamics of emotion (i.e., emotional reactivity) and health maintenance. However, in recent work, there appears to be an effect of greater declines in positive affect as a result of stress, and those who have larger declines seem to have higher mortality risk (Mroczek et al., 2013). SHORT- AND LONG-RANGE CHANGE AS PREDICTORS OF MORTALITY The trajectories described above indicate dynamic aspects of personality. More specifically, personality is a dynamic feature that is long-term in nature, unfolding over years or decades. Other dynamic components of personality unfold over shorter times (i.e., hours, weeks, or days) and represent aspects of change that may be witnessed through emotional reactivity, a defining feature of one of the Big Five personality traits, Neuroticism, as mentioned above. Emotional reactivity is the extent of a daily, hourly, or momentary variable being “pulled,” in terms of one’s experienced involuntary reaction, by a concomitant daily, hourly, or momentary external environmental stimulus, such as stress. For instance, one might imagine a stressor occurring with a commensurate increase in negative affect. This process occurs not on a long-range scale, such as over months or years, but rather over a more short-range time frame, such as seconds, minutes, hours, or days. To exemplify the nature of both short-range and long-range dynamic predictors of health, in the upcoming section, we describe two studies, each investigating the effect of dynamic personality and emotional reactivity on mortality risk. Each of these two studies modeled a dynamic aspect of personality or affect and then used those dynamic parameters to predict a common outcome: mortality risk. The first, Mroczek and Spiro (2007), examined personality change over a long-range time frame using growth-curve models to derive withinperson slopes to predict mortality risk. The second, Mroczek et al. (2013), used a 1-week daily-diary study to derive within-person slopes of emotional reactivity to predict mortality risk over a much shorter range of time. These two studies derived two types of dynamic coefficients from within-person slopes, one shortrange and one long-range, both predicting the same outcome, mortality risk. Long-Range Change in Personality Trajectories Based on previous findings of personality as a predictor of mortality risk (Wilson et al., 2004) and evidence that shows that neuroticism changes bridging the dynamic aspects of personality and emotion     

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throughout the lifespan (Mroczek & Spiro, 2003), Mroczek and Spiro (2007), the first of our two exemplifying studies, hypothesized that long-term decline in neuroticism would be associated with lower mortality risk. The study used a sample of 1,663 men ages 43 to 91 (M = 63, SD = 8) in the VA NAS. The longitudinal study assessed personality using the EPI–Q (Floderus, 1974), a shortened version of the Eysenck Personality Inventory (Eysenck & Eysenck, 1968) over a 12-year period (1988–2000). Individual long-term change in neuroticism was found to vary across individuals. Adjusting for age, demographics, and health (subjective and objective), growth curve parameters such as the level and slope of an individual’s neuroticism were applied to a survival analysis (Cox models) to predict whether individual variation would be associated with mortality risk. Indeed, both levels of neuroticism and change in neuroticism were predictive of mortality risk. This study found an interaction between intercept and slope of neuroticism, such that individuals possessing both high average neuroticism and an increasing level of neuroticism over time had the highest mortality risk compared with all other combinations of level and slope neuroticism. On the other hand, those who experienced a decline in neuroticism over time had a lower risk of mortality. However, interestingly, increasing neuroticism over time was not associated with a higher mortality risk for individuals who started with relatively low levels of neurot­ icism, suggesting that both the level of neuroticism and change in neuroticism are important to consider in predicting the risk of mortality. These findings raise questions for future research about whether modifying traits through personality interventions may lead to downstream improvements in health, health behaviors, and ultimately a reduction in mortality risk. In addition, modifying traits may also promote healthy aging by lengthening not only the lifespan but the healthspan as well. For instance, if trait enhancement were to lead to improved physician adherence, better health behaviors, and fewer negative health events and hospitalizations, it would lead to higher quality of life and greater quality-adjusted life years for midlife and older adults. In this way, trait enhancement could be an effective conduit for the promotion of healthy aging across the lifespan. What might such a personality intervention look like? A personality intervention that was intended to maximize effects on health might include elements of personality change as well as health-promoting features. For example, an intervention may employ mindfulness meditation training to reduce neuroticism, as well as self-control training to increase conscientiousness, while also utilizing electronic reminders to engage in particular health behaviors (e.g., take your statins, exercise daily, resist the dessert). Along these lines, Bogg, Marshbanks, and Doherty (2014) designed an intervention shown to decrease binge drinking in students that simultaneously showed potential to change personality traits. 152       bastarache and mroczek

Short-Range Change in Emotional Reactivity Coefficients While Mroczek and Spiro (2007) modeled change over a decade to predict mortality, Mroczek et al. (2013) in contrast, modeled change in emotional reactivity over a 1-week period, a much smaller range of time. Previous research found that emotional reactivity is, in fact, related to chronic health conditions as well as the risk for depression (Charles, Piazza, Mogle, Sliwinski, & Almeida, 2013). Such work provides a base for the current study of focus, where short-range change in emotional reactivity, in contrast to a static measure of emotion, as a predictor of mortality risk is investigated (Mroczek et al., 2013). While prior work traditionally quantified emotional reactivity through the association between daily stress and negative affect, the current study of focus also incorporated the variation in daily stress with positive affect. Previous work established positive affect as a factor in resilience and health (Fredrickson et al., 2003; Ong, Mroczek, & Riffin, 2011; Zautra et al., 1995). Defining emotional reactivity via both negative and positive affect in Mroczek et al. (2013) allowed for elucidation of the mechanisms through which emotional reactivity may predict mortality risk, by looking at both the amount of increase in negative affect and decrease in positive affect in the face of daily stressors. This study used a subsample (n = 181) of the NAS, and daily experiences of stress, negative affect, and positive affect were measured for each individual over an 8-day daily-diary study, yielding a total of 1,439 person-days of data. Stress measures were assessed using the Daily Inventory of Stressful Events (DISE; Almeida, Wethington, & Kessler, 2002) and the number of stressors each day, for each individual, was computed, yielding identical results to a simpler measure of stress, “stress day,” defined by whether a stressor occurred on a given day. Daily affect was assessed using the Positive and Negative Affect Schedule (PANAS), a brief measure consisting of two 10-item mood scales (Watson, Clark, & Tellegen, 1988). The association between daily stress and affect was analyzed using a multilevel modeling framework, previously described, to generate emotional reactivity coefficients for each individual. Emotional reactivity can be quantified using multilevel modeling, a within-person variation model in which daily experiences of stress and affect are modeled as a function of one another, which determines the withinperson association between these two variables and yields a within-person slope. These dynamic coefficients, generated for each individual, represent the individual variation in emotional reactivity and can be used to predict mortality risk. These reactivity coefficients were then incorporated into a proportional hazards (Cox) model to predict mortality risk. The results of this study did not find a relationship between negative affect-related emotional reactivity and mortality, despite generating a hazards ratio (HR = 1.88) in the bridging the dynamic aspects of personality and emotion     

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hypothesized direction, suggesting that greater increases in negative affect in response to stressors are related to greater mortality risk. In contrast, positive affect-based emotional reactivity did predict mortality risk, more than doubling one’s odds (HR = 2.32) of mortality when greater decreases in positive affect were experienced in response to daily stressors. These findings suggest that the reactivity-health association is perhaps more strongly linked to the decreases in positive affect than the increases in negative affect in response to daily stress. Previous research suggests that positive affect may mitigate this risk through promotion of adaptive health behaviors, or sustained protective interpersonal functioning as stressors occur (Folkman, 2008; Fredrickson et al., 2003; Ong, Mroczek, & Riffin, 2011; Zautra et al., 1995). Theoretical models such as the dynamic model of affect (Zautra et al., 2001) and the broaden-and-build model (Fredrickson, 2001; Kok et al., 2013) also support this relationship between affect and health. In essence, the amount of reported change in affect in response to daily stressors describes emotion regulation in response to stress. We know emotion regulation changes over the lifespan and that older adults tend to be better at regulating emotion than younger adults (Carstensen et al., 2011; Gross et al., 1997; Mather & Ponzio, in press). However, this is not true for all older adults; previous studies provide contrasting evidence for theories known as “dampening effects” and “kindling effects,” which posit, respectively, that older adults become better at emotion regulation due to habituation to experiencing negative effect, and older adults become worse at emotional regulation due to sensitization through repeated activation of negative affect. Therefore, further understanding of how individual differences in emotional reactivity throughout the lifespan are associated with health outcomes can ultimately help promote healthy aging. FUTURE DIRECTIONS: BRIDGING THE DYNAMIC SHORT- AND LONG-RANGE MEASURES Together, these two studies suggest that the use of dynamic within-person coefficients, whether they are growth-curve slopes of personality change based on decade-long longitudinal periods or processes, or emotional reactivity slopes over a period of days, can effectively predict health outcomes, over and above static level-based predictors. Dynamic large-scale processes may be fundamentally related to processes that occur and can be measured on a more small-range day-to-day level. Previous work lends credence to this notion as between-individual variation in emotional reactivity has shown to be positively related to individual neuroticism (Mroczek & Almeida, 2004). Establishing the links between dynamic processes of short-term, such 154       bastarache and mroczek

as emotional reactivity, and dynamic long-term processes, such as personality change, that is, short and long-term measures of change, may provide further insight into the pathways through which associated health outcomes, mortality risk, in this case, may be addressed and reduced via intervention. Personality, defined as patterns of thoughts, feelings, and behaviors, is made up of various layers, including dispositional traits, characteristic adaptations, and narratives (McAdams & Pals, 2006). The Big Five personality traits (Goldberg, 1990) themselves are defined in terms of subfacets and characteristic features. These defining features may provide an avenue for intervention that is more manageable and effective than targeting a complex multifeature trait. Perhaps intervening at one level of personality may impact an overarching or fundamental layer; in other words, change on one level may work to influence change on another. For example, in a recent study, a model of “lifespan dynamics” developed by Chapman, Hampson, and Clarkin (2014) explored the potential of personality-informed interventions for healthy aging through the mechanism of cognitive behavioral therapy, an actionbased treatment focused on changing individuals’ maladaptive thought patterns that are associated with particular behaviors and emotional states. Their dynamic model unifies the short- and long-range components through suggesting that variability and effectiveness in affect regulation (day-to-day and week-to-week throughout the lifespan) produces systematic concomitant changes in levels of trait neuroticism over the long term (Chapman et al., 2014). In other words, changes in these short-term processes feed into the processes occurring at the long-term level. This model also suggests that personality change can be brought about through interventions on the level of emotional reactivity. For example, increased effectiveness of affect regulation (Mather & Knight, 2005) gives rise to lessened intensity of negative affect, and distressed thoughts, feelings, and behaviors, which together, ultimately lead to a decrease in trait neuroticism over time (Chapman et al., 2014). These findings are supported by ideas that suggest neuroticism may moderate the stress-affect association as highly neurotic individuals report greater exposure to stressful life events and also appraise stress in terms of a threat, as opposed to viewing stress as a challenge, a more adaptive and constructive appraisal (Mroczek & Almeida, 2004). Furthermore, individuals higher on neuroticism also encode events differently, remembering more events as stressful, and also tend to use maladaptive coping strategies, particularly emotion-focus coping (Mroczek & Almeida, 2004). Over time, the employment of this set of adaptations by neurotic individuals may reinforce their neurotic tendencies and vice-versa (i.e., feedback loop), and consequently, lead to worse health outcomes and increased risk of mortality (Almada et al., 1991; Hagger-Johnson et al., 2012; Mroczek, Spiro, & Turiano, 2009; Weiss & Costa, 2005). Together, this suggests the relevance and importance of bridging the dynamic aspects of personality and emotion     

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linking affect-regulation research with that of longitudinal research on personality change. Doing so may elucidate the pathways through which poor health outcomes may be mitigated and targeted for intervention. These questions for future research also extend to other dynamic traitfacet combinations. For example, trait conscientiousness may also be of important public health relevance; Jokela et al. (2013) showed that low conscientiousness, characterized in this study as poor self-control, lack of longterm planning, and low persistence, was related to increased mortality risk, even upon controlling for demographic variables, such as age, sex, ethnicity, marital status, education, and the other Big Five traits. According to a review by Eisenberg, Duckworth, Spinrad, and Valiente (2014), conscientiousness has been typically and reliably divided into four subfacets, including selfcontrol, industriousness, responsibility, and orderliness. This study also suggests that self-regulation may promote the development of future conscientiousness and that external factors, such as environmental influences, are likely contributors to this development. Together, this suggests that external forces such as personality interventions may also lend themselves to shaping the development of traits such as conscientiousness, and in doing so, increase the positive benefits associated with high conscientiousness, including occupational success, better marriages, lower divorce, and longevity (Friedman et al., 1993; Roberts et al., 2007). Again, future research should further elucidate the role of both dynamic conscientiousness, as well as the dynamic subfacets of this trait as predictors of mortality and health outcomes. Investigating the link between the dynamic processes that occur on a short-range and longrange level may inform targets for early intervention to promote the positive outcomes associated with conscientiousness. Furthermore, the conscientiousness–mortality association established in Jokela et al. (2013) held even upon controlling for health behaviors, suggesting that, in this study, health behaviors did not significantly mediate the personality-mortality association. However, other research suggests that personality interventions leading to personality change may work through altering the mediating mechanisms, such as health behaviors (Mroczek, Spiro, & Turiano, 2009) or physiological processes, that are proposed to link personality to mortality risk and other health outcomes. Chapman et al. (2014) also suggested that this may be an avenue for personality intervention, in other words, changing personality purposefully, in order to improve health behaviors, and one route may be through interventions of these short-range time frame processes, such as affect regulation. Through improvement of health behaviors across the lifespan, healthy aging would be enhanced. Future research by the current authors will extend prior research (Mroczek & Almeida, 2004) on the interaction between personality and weeklong daily experiences of emotional reactivity to stress. Further investigation 156       bastarache and mroczek

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Mroczek, D. K., Spiro, A., III, & Turiano, N. (2009). Do health behaviors explain the effect of neuroticism on mortality? Longitudinal findings from the VA Normative Aging Study. Journal of Research in Personality, 43, 653–659. http:// dx.doi.org/10.1016/j.jrp.2009.03.016 Mroczek, D. K., Stawski, R. S., Turiano, N. A., Chan, W., Almeida, D. M., Neupert, S. D., & Spiro, A., III (2013). Emotional reactivity and mortality: Longitudinal findings From the VA Normative Aging Study. The Journals of Gerontology: Series B. Psychological Sciences and Social Sciences, 70, 398–406. http://dx.doi. org/10.1093/geronb/gbt107 Ong, A. D., Mroczek, D. K., & Riffin, C. (2011). The health significance of positive emotions in adulthood and later life. Social and Personality Psychology Compass, 5, 538–551. http://dx.doi.org/10.1111/j.1751-9004.2011.00370.x Piazza, J. R., Charles, S. T., Sliwinski, M. J., Mogle, J., & Almeida, D. M. (2013). Affective reactivity to daily stressors and long-term risk of reporting a chronic physical health condition. Annals of Behavioral Medicine, 45, 110–120. http:// dx.doi.org/10.1007/s12160-012-9423-0 Roberts, B. W., Kuncel, N. R., Shiner, R., Caspi, A., & Goldberg, L. R. (2007). The power of personality: The comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes. Perspectives on Psychological Science, 2, 313–345. http://dx.doi.org/10.1111/ j.1745-6916.2007.00047.x Roberts, B. W., & Mroczek, D. (2008). Personality trait change in adulthood. Current Directions in Psychological Science, 17, 31–35. http://dx.doi.org/10.1111/ j.1467-8721.2008.00543.x Smith, T. W. (2006). Personality as risk and resilience in physical health. Current Directions in Psychological Science, 15, 227–231. http://dx.doi.org/10.1111/ j.1467-8721.2006.00441.x Sutin, A. R., Terracciano, A., Deiana, B., Naitza, S., Ferrucci, L., Uda, M., . . . Costa, P. T., Jr. (2010). High neuroticism and low conscientiousness are associated with interleukin-6. Psychological Medicine, 40, 1485–1493. http://dx.doi.org/10.1017/ S0033291709992029 Turiano, N. A., Chapman, B. P., Gruenewald, T. L., & Mroczek, D. K. (2015). Personality and the leading behavioral contributors of mortality. Health Psychology, 34, 51–60. http://dx.doi.org/10.1037/hea0000038 Turiano, N. A., Hill, P. L., Roberts, B. W., Spiro, A., III, & Mroczek, D. K. (2012). Smoking mediates the effect of conscientiousness on mortality: The Veterans Affairs Normative Aging Study. Journal of Research in Personality, 46, 719–724. http://dx.doi.org/10.1016/j.jrp.2012.08.009 Turiano, N. A., Mroczek, D. K., Moynihan, J., & Chapman, B. P. (2013). Big 5 personality traits and interleukin-6: Evidence for “healthy Neuroticism” in a US population sample. Brain, Behavior, and Immunity, 28, 83–89. http://dx.doi.org/ 10.1016/j.bbi.2012.10.020

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Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070. http://dx.doi.org/10.1037/00223514.54.6.1063 Weiss, A., & Costa, P. T., Jr. (2005). Domain and facet personality predictors of all-cause mortality among Medicare patients aged 65 to 100. Psychosomatic Medicine, 67, 724–733. http://dx.doi.org/10.1097/01.psy.0000181272.58103.18 Wilson, R. S., Bienias, J. L., Mendes de Leon, C. F., Evans, D. A., & Bennett, D. A. (2003). Negative affect and mortality in older persons. American Journal of Epidemiology, 158, 827–835. http://dx.doi.org/10.1093/aje/kwg224 Wilson, R. S., Mendes de Leon, C. F., Bienias, J. L., Evans, D. A., & Bennett, D. A. (2004). Personality and mortality in old age. The Journals of Gerontology: Series B. Psychological Sciences and Social Sciences, 59, P110–P116. http://dx.doi. org/10.1093/geronb/59.3.P110 Zautra, A., Smith, B., Affleck, G., & Tennen, H. (2001). Examinations of chronic pain and affect relationships: Applications of a dynamic model of affect. Journal of Consulting and Clinical Psychology, 69, 786–795. http://dx.doi.org/10.1037/0022006X.69.5.786 Zautra, A. J., Burleson, M. H., Smith, C. A., Blalock, S. J., Wallston, K. A., DeVellis, R. F., . . . Smith, T. W. (1995). Arthritis and perceptions of quality of life: An examination of positive and negative affect in rheumatoid arthritis patients. Health Psychology, 14, 399–408. http://dx.doi.org/10.1037/0278-6133.14.5.399

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8 POSITIVE PSYCHOLOGICAL FUNCTIONING: AN ENDURING ASSET FOR HEALTHY AGING LAURA D. KUBZANSKY AND JULIA K. BOEHM

Increasing evidence suggests that positive emotions and other aspects of positive psychological well-being (PPWB) protect physical health, independent of negative emotions. In this chapter, we consider key conceptual, methodological, and developmental questions about whether, how, and when PPWB influences physical health. First, we briefly consider the evidence supporting the health benefits of PPWB. Next, we argue that a broader definition of health will be needed beyond simply the absence of disease, and we consider how we can more comprehensively define what it means to be healthy. We then consider the behavioral and biological mechanisms by which PPWB may influence health and disease. We also consider the most rigorous method­ ological approaches to studying these associations, when associations are first evident, and if they change or persist over time. Finally, we consider whether interventions to improve PPWB can also improve health outcomes. Researchers have long recognized links between psychological and physical health, but most of the focus has been on how poor psychological http://dx.doi.org/10.1037/14857-009 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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functioning—such as being anxious or depressed—increases risk of disease. However, PPWB is not simply the opposite or absence of distress in its various forms (Ryff et al., 2006; Ryff & Singer, 1998). PPWB is a broad construct that reflects the positive feelings and cognitions of individuals who function well in their lives and evaluate their lives favorably. It is derived from a variety of theoretical approaches, including eudaimonic (purposeful functioning), hedonic (cognitive and affective functioning), and social well-being (social functioning; Gallagher, Lopez, & Preacher, 2009). Each approach emphasizes a different facet of well-being and is characterized by different constructs. Thus, multiple constructs are included under the broad category of PPWB and researchers generally consider them to be related but distinct (Gallagher et al., 2009; Keyes & Annas, 2009). PPWB can be characterized by both statelike and trait-like characteristics, although individuals with generally positive dispositions also tend to experience more frequent positive states than individuals with less positive dispositions. We are particularly interested in PPWB constructs that represent typical levels of well-being, but that can be modified. One example is “chronic” happiness, which is longer lasting than a specific mood, but is not so fixed that it cannot be altered (Lyubomirsky, Sheldon, & Schkade, 2005). For a more detailed discussion of state and trait PPWB in relation to health, see Boehm and Kubzansky (2012). The most rigorous evidence connecting PPWB, as defined by relatively chronic levels, to physical health has consistently shown that individuals who are satisfied with their lives, optimistic about the future, and generally have positive feelings show a reduced risk of experiencing a heart attack, stroke, or cardiovascular death in prospective studies (Boehm, Peterson, Kivimaki, & Kubzansky, 2011a, 2011b; Davidson, Mostofsky, & Whang, 2010; see Nabi, Kivimaki, De Vogli, Marmot, & Singh-Manoux, 2008, for an exception). Moreover, these effects seem to be independent of ill-being. For example, the most optimistic participants in a study of nearly 100,000 healthy women ages 50 to 79 had up to a 30% reduced risk of incident heart disease or cardiovascular mortality approximately 8 years later (Tindle et al., 2009). These findings were independent of sociodemographic characteristics, health behaviors, and depressive symptoms; furthermore, cardiovascular outcomes were verified based on hospital records, objective indicators (e.g., enzyme determinations), and national death index searches. A comprehensive review noted that the association between PPWB and cardiovascular disease (CVD) appears to be robust, with multiple studies replicating the protective effects of optimism (Boehm & Kubzansky, 2012). Most of this research has been conducted in middle-aged to older adults because this is the population at highest risk for developing CVD. Across these populations, effects are evident across a range of ages (samples include individuals ranging in age from 46 to 79).

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Of note is that most work to date regarding PPWB and health has been concentrated in the area of CVD, which is where work on negative emotions and stress has focused (Kubzansky, Winning, & Kawachi, 2014). However, it may also be that the cardiovascular system is particularly responsive to psychological perturbations or their behavioral sequelae. That said, PPWB is likely involved with additional health outcomes because many pathways linking PPWB to CVD (e.g., healthy diet, reduced inflammation) are relevant in the etiology of other chronic diseases. In fact, in one meta-analysis of 21 studies with healthy individuals, PPWB was associated with an 18% reduced risk of premature mortality (Chida & Steptoe, 2008). Findings were strongest among adults ages 60 or older, but too few samples were available to assess the magnitude of effect in younger samples. Findings were also slightly less strong in 19 studies of individuals already diagnosed with a disease, but still suggested that PPWB protects against premature mortality after disease onset.

NEW QUESTIONS AND NEXT STEPS Despite accumulating evidence associating PPWB with reduced risk of disease and premature mortality, many questions remain. Broadly, these can be separated into conceptual, methodological, and developmental issues. Conceptual Issues Health Versus Disease One of the most pressing issues involves the distinction between health and disease, especially in the context of aging. The World Health Organization (WHO; 1946) characterized health as “a state of complete physical, mental and social well-being, and not merely the absence of disease or infirmity” (p. 100). However, most empirical research maintains a disease perspective by characterizing health in terms of the presence or absence of disease. In other words, the absence of unhealthy psychological functioning (e.g., depression), behaviors (e.g., smoking), biological dysfunction (e.g., high total cholesterol), or conditions (e.g., diabetes) has implied the presence of health. However, health can only be understood comprehensively if the full spectrum of human functioning is considered (Keyes & Grzywacz, 2002). One way to gain greater insight will be to focus not only on how to reduce disease risk but also on how to maintain health and develop healthy trajectories across the lifespan. Aging researchers have recognized this critical issue and have suggested examining the phenomenology and predictors of successful aging, the notion that with

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age some individuals actually improve in cognitive skills, become happier, and are better able to manage interpersonal relationships (Rowe & Kahn, 1987). However, there is a lack of consensus on how to define successful aging (Lupien & Wan, 2004), and at present there are few health indicators relative to the number of disease indicators. Nonetheless, this greater appreciation for a more nuanced assessment of health has led to a renewed interest in the concept of positive health because such a focus may help not only to reduce the number of deaths due to chronic disease but also foster healthy aging more broadly. Effort has increasingly been directed toward conceptualizing positive health (Ryff & Singer, 1998; Seligman, 2008), since until there is a clear conceptual definition or metric beyond the absence of disease, empirical research will remain limited. One critical challenge to defining multiple aspects of health in a unified way is that including multiple components of health in a single definition may make it difficult to disentangle underlying processes. For example, the WHO’s definition of health combines indicators of physical, social, and mental function. However, if social and psychological processes contribute to physical health, then combining across domains may obscure mechanisms and the ability to identify causal relationships. Thus, it may be useful to separate out different components of health. Unfortunately, relatively few attempts have been made to define health as something more than the absence of disease without combining multiple different types of indicators. The only metric we are aware of has emerged in the domain of cardiovascular functioning. Favorable cardiovascular health (FCH) is a composite that comprises five indicators—healthy levels of blood pressure, cholesterol, and body mass index (BMI), as well as being diabetes free and not smoking cigarettes— that was developed to assess whether preventing risk factors for CVD would appreciably reduce likelihood of disease (Lloyd-Jones et al., 2006). Rather than evaluate the increase in relative risk of disease associated with each individual risk factor (e.g., cigarette smoking), investigators explored whether not having a particular risk factor would alter lifetime risk of CVD, a concept more easily understood by clinicians and patients (Lloyd-Jones et al., 2006). This work led to the realization that simultaneously maintaining optimal status on multiple indicators strongly predicts longevity and provides a metric of cardiovascular health (Lloyd-Jones et al., 2010). For example, men and women with FCH show drastic reductions in their risk for CVD and premature death (Lloyd-Jones et al., 2006). Much of the work with FCH has been conducted in middle-aged samples, but some studies have investigated younger individuals. One study found women in their mid-20s with optimal status on each of the five indicators had an 81% reduced risk of experiencing a CVD-related death over 31 years, relative to women with poor status on less than or equal to two indicators (Daviglus et al., 2004). Moreover, research has begun to suggest that psychosocial factors either in childhood or even 166       kubzansky and boehm

middle adulthood may contribute to whether FCH is achieved and/or maintained during adulthood (Appleton, Loucks, Buka, Rimm, & Kubzansky, 2013). Among studies considering FCH in later adulthood, the most prominent finding is how infrequently older adults are able to achieve or maintain FCH (e.g., Bambs et al., 2011). Although FCH does not completely separate domains (cigarette smoking, a key health behavior, is included with biological factors), domain overlap is limited, and therefore FCH may provide a useful metric for evaluating causal or contributing factors that promote cardiovascular health. We briefly note a related metric, ideal cardiovascular health. This is an expanded version of FCH that also includes indicators of physical activity and diet (LloydJones et al., 2010). While useful for traditional epidemiology, adding more health behaviors makes it more difficult to separate domains (e.g., behavioral vs. biological factors) and assess interrelationships between them. FCH may provide a better metric when evaluating how psychological and behavioral processes contribute to cardiovascular health. Factors That Contribute to Health and Disease Behavioral and biological processes are the two mechanisms most commonly posited to link PPWB with health and disease. Much like how health is most often defined in terms of the absence of disease, underlying behavioral and biological processes are most often conceptualized in terms of the absence of either unhealthy behaviors (e.g., cigarette smoking) or biological dysfunction (e.g., high blood pressure)—in other words, deteriorative processes. Underlying behavioral and biological processes are less often conceptualized in terms of the presence of healthy behaviors (e.g., fruit and vegetable consumption) or biological function (e.g., healthy autonomic cardiac control)— processes that may be considered restorative. This exclusive focus on the presence or absence of deteriorative processes has dwarfed efforts to evaluate the role of restorative processes in health and disease (Robles & Carroll, 2011; Smith & Baum, 2003) and yielded a one-sided view of health. Successful functioning requires more than simply minimizing deterioration in contexts of stress because most individuals do not spend the majority of their time in stressful states; indeed, a third of a human’s life is spent in the restorative state of sleep (Robles & Carroll, 2011). Both the absence of deteriorative processes (which contribute to biological harm) and the presence of restorative processes (which promote rest, regeneration, and repair within the body; Smith & Baum, 2003) are necessary for attaining and maintaining optimal physical health. In recent work, we proposed a novel theoretical model to account more explicitly for pathways related to both deteriorative and restorative processes (see Boehm & Kubzansky, 2012, for more detail). According to this model (see Figure 8.1), positive psychological functioning     

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Positive Psychological Well-Being

Stress

– +

+

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Health Behaviors

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Deteriorative Processes

Biological Function

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Figure 8.1.  Model of positive psychological well-being and disease risk, as mediated through restorative and deteriorative processes. Adapted from “The Heart’s Content: The Association Between Positive Psychological Well-Being and Cardiovascular Health,” by J. K. Boehm and L. D. Kubzansky, 2012, Psychological Bulletin, 138, p. 659. Copyright 2012 by the American Psychological Association.

PPWB is associated with a lower likelihood of engaging in deteriorative health behaviors (e.g., cigarette smoking) as well as with less biological dysfunction (e.g., inflammation). PPWB is also associated with engaging in restorative health behaviors, as well as with markers of restorative biological function. This, in turn, will impact the presence or maintenance of health and the risk of disease. Although research to date has not identified as many restorative as deteriorative processes, this likely reflects a lack of attention rather than that only a few processes operate. Restorative biological markers include serum antioxidants and high-density lipoprotein cholesterol (HDL–C). Serum antioxidants such as vitamins E and C and beta-carotene inhibit other molecules from oxidizing or producing free radicals that damage cells (Young & Woodside, 2001). Similarly, HDL–C moves “bad” cholesterol away from the arteries and is considered “good” cholesterol (Toth, 2005). Restorative 168       kubzansky and boehm

behaviors include exercising, which builds muscles, and getting sufficient and high-quality sleep, which fosters the consolidation of memories and promotes emotion regulation (Robles & Carroll, 2011; Walker, 2009). Quality of sleep is often conceptualized in terms of deficiencies and disorders, but investigators have started to define sleep health as a restorative process by considering whether sleep was appropriately timed, satisfying, of adequate duration, and promoted alertness in waking hours (Buysse, 2014). While the conceptual categorization of restorative versus deteriorative is appealing, not all processes clearly fit into one category or the other. Some processes are unmistakably restorative (e.g., meditation) or deteriorative (e.g., cigarette smoking), some may lie on a continuum (e.g., physical activity to physical inactivity), others may range from nondeteriorative to deteriorative (e.g., inflammation), and still others may be nonlinear in their effect on health (e.g., no vs. moderate versus excessive alcohol consumption). Exactly how each of these processes relates to the continuum remains to be determined (see Boehm & Kubzansky, 2012, for more detail). Indeed, research has yet to firmly establish whether restorative levels exist for most biological markers or if levels indicate something beyond the absence of deterioration (i.e., above or below normal levels). For example, levels of c-reactive protein (CRP; a widely used marker of inflammation) that indicate CVD risk have been identified, but it is unclear if some level of CRP is restorative per se. Identifying levels at which various processes may be restorative would enhance strategies for promoting positive health. Expanding models of health to identify not only which processes are restorative but also how various processes may combine to influence health will provide additional insight. For example, although health behaviors are often studied individually, they share common determinants and tend to cluster together (Cockerham, 2005; Laaksonen, Prättälä, & Lahelma, 2003). As a result, researchers can consider health behaviors in combination, and have developed a metric for assessing overall “healthy lifestyle.” This index includes the absence of smoking, moderate alcohol consumption, regular physical activity, healthy diet, and BMI under 25 kg/m2. The index appears to be valid and has been used in samples ranging in age from early to late adulthood, but it is likely to be applicable in childhood and adolescence as well (Chiuve, McCullough, Sacks, & Rimm, 2006). Although this metric includes behaviors that indicate both the absence of deterioration and the presence of restoration, the overall index emphasizes restorative processes. When considering single versus combined effects of health behaviors on allcause mortality among elderly Europeans, investigators found that adherence to a Mediterranean diet, moderate alcohol use, physical activity, and nonsmoking were each separately associated with lower risks of all-cause mortality (Knoops et al., 2004). However, engaging in all four health behaviors positive psychological functioning     

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compared with none or only one reduced risk for all-cause mortality further (Knoops et al., 2004), suggesting that prevention strategies focusing on multiple healthy lifestyle components may be more effective than those that consider single behaviors. Other metrics of restorative processes may also be developed. Such metrics, particularly those that consider biological processes, could be informed by animal models. For example, recent animal work has developed a calm mouse model to examine how reducing stress exposure may alter biology to improve health. Rodents are housed in environmentally enriched settings (e.g., in cages equipped with enhanced nesting materials). Findings suggest that stress reduction is associated with reduced production of stress hormones and enhanced secondary vaccine responses (Gurfein et al., 2014). At present it is unclear which biological responses may be most restorative or which aspects of the human experience this model mirrors, but the emphasis on restorative processes may pave the way for more studies and innovative research in this area. Evidence for Positive Psychological Well-Being and Pathways to Health Initial work on how PPWB influences health proposed links via stress buffering or by reducing the effects of deteriorative behavioral and biological processes (Pressman & Cohen, 2005; see also Figure 8.1). In support of the stress-buffering hypothesis, researchers have shown that the cardio­vascular reactivity stemming from a stressful task diminishes more quickly in individuals who experience positive rather than negative or neutral feelings (Fredrickson & Levenson, 1998; Fredrickson, Mancuso, Branigan, & Tugade, 2000). In another study, positive emotions also facilitated more efficient cardio­vascular recovery from stress, as indexed by heart rate variability and diastolic blood pressure (Papousek et al., 2010). However, most of this research has been conducted in younger adults, and little work has assessed whether these effects vary by age. PPWB also affects health by reducing deteriorative biological processes and behaviors. For example, middle-aged women with high versus low levels of life purpose and satisfaction had less aortic calcification (e.g., Matthews, Owens, Edmundowicz, Lee, & Kuller, 2006). Other work has shown that happiness aggregated over the course of a day was associated with lower blood pressure 3 years later (Steptoe & Wardle, 2005) and that high levels of hope, curiosity, and emotional vitality were associated with reduced risk of hypertension (Richman et al., 2005; Trudel-Fitzgerald, Boehm, Kivimaki, & Kubzansky, 2014). PPWB has also been linked with lower levels of inflammation (e.g., Ikeda et al., 2011; Roy et al., 2010; Steptoe, O’Donnell, Badrick, Kumari, & Marmot, 2007) and tends to be inversely associated with deteriorative behaviors such as smoking cigarettes and insufficient sleep (e.g., Strine, Chapman, Balluz, Moriarty, & Mokdad, 2008). However, these studies are 170       kubzansky and boehm

mostly cross-sectional and have not explicitly investigated associations at different points in the lifespan. PPWB also appears to enhance restorative biological function, although evidence is also largely cross-sectional. For example, two studies showed positive associations between PPWB and HDL–C (Boehm, Williams, Rimm, Ryff, & Kubzansky, 2013b; Steptoe, Demakakos, de Oliveira, & Wardle, 2012). Similarly, more optimistic adults showed higher levels of carotenoids (but not vitamin E) during midlife compared with their less optimistic peers (Boehm, Williams, Rimm, Ryff, & Kubzansky, 2013a). Evidence further suggests a positive association between PPWB and restorative behaviors. For example, elderly Dutch who were more optimistic tended to consume moderate amounts of alcohol and eat more fruits, vegetables, and whole grains (Giltay, Geleijnse, Zitman, Buijsse, & Kromhout, 2007). Multiple cross-sectional studies have also reported that higher levels of PPWB are associated with more physical activity (e.g., Grant, Wardle, & Steptoe, 2009), and a longitudinal study of initially inactive adults found that happy men were more likely to increase activity up to 10 years later compared with less happy men (Baruth et al., 2011). In addition, sufficient sleep and sleep quality were associated with greater optimism in 8-year-old children (Lemola et al., 2011). This evidence provides the first step in establishing that PPWB is linked with health through restorative pathways. However, longitudinal or experimental evidence is scarce, which limits conclusions about whether PPWB precedes and is causally related to these processes. Methodological Issues Assessing Health and Disease Although self-reported health outcomes are often readily available in existing data sets, the gold standard is an objective indicator such as a doctor diagnosis or clinical test. This is especially true when PPWB and other psycho­social characteristics are self-reported, as associations between two selfreported factors may be inflated due to common method variance. Moreover, the most rigorous study designs assess initial health status of participants when PPWB is assessed. Starting with an initially healthy sample can identify factors that are involved in the etiology of disease or that contribute to disease prevention. In contrast, starting with a patient sample and evaluating recurrence of disease provides insight into factors that may contribute to (or mitigate) the progression of disease. Associations and underlying pathways may differ in individuals who are disease free versus those who are not. Although there may be similarities in the correlates and mechanisms of incidence versus progression, they are best investigated separately. Failure to distinguish between these populations and processes may obscure important relationships. positive psychological functioning     

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Assessing Positive Psychological Well-Being Evidence regarding PPWB in relation to health, disease, and underlying pathways has largely relied on opportunistic use of existing data. As a result, PPWB assessment has been somewhat limited. Epidemiologic studies of risk or protective factors in relation to the maintenance of health or the development of disease require large samples with substantial follow-up, and few of these studies were designed to investigate the role of psychosocial factors per se. Thus, many studies using large-scale secondary data sets to investigate the health-related effects of PPWB have used single-item indicators of PPWB or scales that have not been validated. In addition, most indicators of PPWB are self-report, which may increase social desirability demands or other response biases. In fact, self-reported PPWB is associated with health in ways that are consistent with other assessment methods. For example, similar to self-reported PPWB, greater positive emotion assessed via facial expressions is inversely related to CVD risk (Davidson et al., 2010). That said, alternative assessment methods may provide additional insight. Furthermore, some forms of PPWB may be more relevant to maintaining or protecting physical health than others. For example, one review suggested that optimism is robustly related to better cardiovascular outcomes in both healthy and patient populations, while positive affect and other hedonic constructs show a fairly consistent association with CVD primarily in healthy populations (Boehm & Kubzansky, 2012). However, fewer studies have investigated eudaimonic well-being, so conclusions are difficult to make. Thus, it will be useful to investigate systematically which PPWB markers are especially relevant. Considering how different constructs operate at different stages of life may also be informative. Another issue is that most studies have conceptualized PPWB in terms of personal attributes such as optimism and satisfaction. However, given strong links between PPWB and social functioning (Diener & Seligman, 2002), interpersonal factors should also be considered as part of a broader conceptualization of well-being (cf. Gallagher et al., 2009). Ultimately, the goal should be to evaluate PPWB’s associations with health and aging using well-validated measures that tap affective, cognitive, and social components of PPWB as well as hedonia and eudaimonia. Developmental Issues Well-Being in Childhood Most chronic diseases develop in older age, but many have childhood origins. Both cardiovascular medicine and the field of life course epidemiology have encouraged greater recognition of this (Berkman, 2009; Lloyd-Jones et al., 2010). For example, several studies have demonstrated that children 172       kubzansky and boehm

who are distressed as early as 7 years old are at greater risk of developing adulthood CVD than their less distressed counterparts (e.g., Appleton, Loucks, et al., 2013). Few studies have considered PPWB among children in relation to later life health, but one study indicated the relevance of three positive childhood factors. After adjusting for demographics and childhood cardiovascular health, better attention regulation, better cognitive ability, and positive home environment at age 7 were associated with a 30% to 40% increase in the odds of having FCH in midlife (Appleton, Buka, et al., 2013). The effect of each attribute was additive, and children with high versus low levels of all three factors had 4.3 higher odds of FCH in midlife. Such findings are important because they point to a developmental approach to fostering PPWB and getting children onto resilient versus risky health trajectories. Well-Being in Older Age Older people tend to be happier than younger people. Socioemotional selectivity theory suggests that these age effects occur because motivation and goals shift toward maintaining positive emotion when time is perceived as limited, as begins to occur among older adults (Carstensen, Isaacowitz, & Charles, 1999). Longitudinal studies support this and provide evidence that PPWB increases with age (e.g., Holahan, Holahan, Velasquez, & North, 2008; Mroczek & Spiro, 2005). However, a potential limitation to these studies is raised by other research indicating that individuals with the highest versus lowest levels of PPWB tend to live longer (Chida & Steptoe, 2008). If individuals with lower PPWB have higher risk of mortality, they may be less likely to be included in studies of PPWB in older adults due to premature death, or they may drop out of longitudinal studies because of poor health. Such differential mortality could contribute to the apparent increase in PPWB that has been observed in aging individuals. Such effects are unlikely to account fully for the increase in PPWB observed with aging, but they could suggest the increase in PPWB is smaller than previously thought or less generalizable, which also raises the issue of whether individuals who remain in longitudinal studies differ in other important ways from those who no longer participate (i.e., individuals with initially lower PPWB). It is possible that effects of PPWB on stress response, or on behavioral or biological processes that protect health, are not uniform at all ages (e.g., of greater magnitude in older vs. younger individuals). Extant research suggests these effects operate throughout the life course, but a more nuanced assessment is needed. Can Well-Being Be Modified? While it is commonly thought that PPWB is fixed or largely determined by genetics (Lyubomirsky et al., 2005), many aspects of PPWB have been positive psychological functioning     

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estimated to be only about 30% to 40% heritable, with recent molecular genetic research suggesting that genetic factors contribute to only 12% to 18% of the variance in PPWB (Rietveld et al., 2013). Thus, there may be substantial room to modify PPWB. The past decade has seen a dramatic increase in the number of interventions designed not just to alleviate depression or anxiety but also to enhance PPWB (Bolier et al., 2013). Such well-being interventions include variations on traditional cognitive behavioral therapy (Seligman, Rashid, & Parks, 2006), meditative practices (Fredrickson, Cohn, Coffey, Pek, & Finkel, 2008), and other positively oriented cognitive and behavioral exercises (Layous & Lyubomirsky, 2014). Interventions designed to build assets tend to differ from those designed to mitigate deficits in that they are typically administered by nonclinicians and are intended to be scalable and implemented over both shorter and longer time periods. For example, researchers have designed gratitude interventions around tasks such as writing letters of gratitude (Seligman, Steen, Park, & Peterson, 2005) or describing things for which they are grateful (Emmons & McCullough, 2003). Another common intervention seeks to foster optimism by having individuals imagine and write about their best possible life in the future, which results in well-being improvements in the weeks following the intervention (King, 2001; Sheldon & Lyubomirsky, 2006). A specific type of meditation called loving-kindness meditation cultivates positive states by asking individuals to consider someone for whom they have warm feelings and then to expand those feelings to themselves and others (Salzberg, 1995). When loving-kindness meditation was randomly assigned to casual practitioners of meditation, a single 7-minute guided meditation session was linked to more positive mood and positivity toward strangers immediately after the activity, relative to a neutral imagery control condition (Hutcherson, Seppala, & Gross, 2008). Thus, there is accumulating evidence to suggest that levels of PPWB can be improved and that interventions are generally effective up to 3–6 months later (Bolier et al., 2013). Given the relatively minor inter­ ventions that have been tested, it is notable that improvements occur. Longterm effects are less clear, but such interventions are promising due to their low-cost and easy implementation. To date, most well-being interventions have been conducted with young or middle-aged adults. Some evidence suggests that well-being interventions show stronger effects for middle-aged to older adults relative to young adults, perhaps because older individuals exert more effort into intervention activities and take them more seriously (Sin & Lyubomirsky, 2009). However, this needs to be verified in research with a broad range of ages. Interventions with elderly adults remain limited, but an increasing number of studies have considered the efficacy of interventions in children and adolescents. For example,

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in one study of middle-school students, those participating in a gratitude condition showed subsequent increases in satisfaction relative to those in a hassles condition (Froh, Sefick, & Emmons, 2008). Thus, well-being interventions may be efficacious at all stages of life, but tailoring them for specific age groups on the basis of developmental needs may further bolster success (see also Nelson & Lyubomirsky, 2014, regarding age-related implications of well-being interventions). What remains to be seen is whether interventions will affect not only PPWB but also downstream outcomes related to physical health or health behaviors. If PPWB precedes and leads to better health outcomes, then it could provide a novel target for health promotion. To date, only preliminary work has investigated this question. For instance, Burton, Pakenham, and Brown (2009, 2010) tested a group-based resiliency-training program across 13 weeks in nearly 20 university employees ranging in age from 24 to 50 years. The program included education, discussion, and activities regarding positive emotions, meaning in life, and flexibility. Immediately after the intervention period, PPWB improved significantly and total cholesterol was significantly reduced. Other parameters, including physical activity, blood pressure, glucose, CRP, and cortisol, did not change. Nonetheless, the relatively small trial (with limited statistical power) showed the feasibility of such interventions and the potential for improvement in not only PPWB but also downstream behavioral and biological processes influenced by PPWB. Other work has demonstrated the feasibility of such interventions in cardiovascular patients, who are typically older. For example, one inter­ vention focused on exercises related to gratitude, optimism, and altruism in patients hospitalized with acute coronary syndrome or congestive heart failure (Huffman et al., 2011). While behavioral and biological outcomes are still being assessed, the investigators found the intervention was well-received by participants. In another study, patients were randomly assigned either to a treatment group designed to bolster positive feelings or to an educational control group after percutaneous coronary intervention (Charlson et al., 2007; Peterson et al., 2012). Changes in physical activity were assessed from baseline to 1 year later. Relative to those in the control group, participants in the treatment group were 1.7 times more likely to increase their physical activity. In a similar study of African Americans with hypertension, participants in a condition designed to elicit positive feelings were more compliant with their antihypertensive medication than were control participants (Ogedegbe et al., 2012). Thus, increasing evidence suggests PPWB inter­ventions are feasible, and may not only bolster positive thoughts and feelings, but may also improve health outcomes.

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CONCLUDING REMARKS PPWB is not simply a marker of the absence of poor functioning; rather, it confers unique physical health benefits, especially in the domain of CVD. Mechanisms underlying this association include not only stress-buffering pathways but also reduced likelihood that deteriorative processes occur and increased likelihood of initiating or maintaining restorative processes. One of the exciting aspects of research regarding links between PPWB and health is that it promotes a focus on processes that are explicitly health promoting or restorative. Greater understanding of biology and behavior in this domain may provide new insight that is difficult to achieve with a focus on harm, deficits, or deterioration. Research has also begun to take a life-course perspective on the association between PPWB and health, considering both how early in life PPWB may start to exert influence and if effects are evident much later in life. If the presence of well-being in early life sets individuals on more resilient trajectories for health in later life, it would suggest the importance of relatively earlier PPWB interventions than those currently in practice, which are mostly implemented in adulthood. Despite significant advances, strategies for promoting and maintaining health throughout the life course remain limited, and there is a pressing need to refine existing approaches or develop new ones (Fjeldsoe, Neuhaus, Winkler, & Eakin, 2011). Furthermore, there is growing recognition of the importance of resilience and the factors that build it, particularly given concerns about high levels of stress and the documented health effects of adversity (NPR/Robert Wood Johnson Foundation/Harvard School of Public Health, 2014). Thus, rigorous research into psychological assets is not simply an esoteric exercise, but should receive priority. While developing PPWB is a desirable end in and of itself, research on PPWB and physical health suggests that positive psychological functioning may have effects well beyond those on psychological health. If that proves to be the case, and given that PPWB is modifiable, this could provide new targets for prevention and intervention that are designed to improve health. Moreover, consideration not only of deficits and deteriorative processes but also of assets and restorative processes may provide novel insights into defining positive health and how to achieve it. Considering the interplay of PPWB with physical health highlights critical new directions for research and contributes to building a science of well-being in relation to biology and health. REFERENCES Appleton, A. A., Buka, S. L., Loucks, E. B., Rimm, E. B., Martin, L. T., & Kubzansky, L. D. (2013). A prospective study of positive early-life psychosocial factors and

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Steptoe, A., O’Donnell, K., Badrick, E., Kumari, M., & Marmot, M. (2007). Neuroendocrine and inflammatory factors associated with positive affect in healthy men and women: The Whitehall II study. American Journal of Epidemiology, 167, 96–102. http://dx.doi.org/10.1093/aje/kwm252 Steptoe, A., & Wardle, J. (2005). Positive affect and biological function in everyday life. Neurobiology of Aging, 26(Suppl. 1), 108–112. http://dx.doi.org/10.1016/ j.neurobiolaging.2005.08.016 Strine, T. W., Chapman, D. P., Balluz, L. S., Moriarty, D. G., & Mokdad, A. H. (2008). The associations between life satisfaction and health-related quality of life, chronic illness, and health behaviors among U.S. community-dwelling adults. Journal of Community Health: The Publication for Health Promotion and Disease Prevention, 33, 40–50. http://dx.doi.org/10.1007/s10900-007-9066-4 Tindle, H. A., Chang, Y. F., Kuller, L. H., Manson, J. E., Robinson, J. G., Rosal, M.  C., . . . Matthews, K.  A. (2009). Optimism, cynical hostility, and incident coronary heart disease and mortality in the Women’s Health Initiative. Circulation, 120, 656–662. http://dx.doi.org/10.1161/CIRCULATIONAHA.108.827642 Toth, P. P. (2005). Cardiology patient page. The “good cholesterol”: High-density lipoprotein. Circulation, 111, e89–e91. http://dx.doi.org/10.1161/01.CIR. 0000154555.07002.CA Trudel-Fitzgerald, C., Boehm, J. K., Kivimaki, M., & Kubzansky, L. D. (2014). Taking the tension out of hypertension: A prospective study of psychological well being and hypertension. Journal of Hypertension, 32, 1222–1228. http://dx.doi. org/10.1097/HJH.0000000000000175 Walker, M. P. (2009). The role of sleep in cognition and emotion. Annals of the New York Academy of Sciences, 1156, 168–197. http://dx.doi.org/10.1111/ j.1749-6632.2009.04416.x World Health Organization. (1946, July). Preamble to the Constitution of the World Health Organization. International Health Conference, New York, NY. Young, I. S., & Woodside, J. V. (2001). Antioxidants in health and disease. Journal of Clinical Pathology, 54, 176–186. http://dx.doi.org/10.1136/jcp.54.3.176

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9 EMOTIONAL EXPERIENCE AND HEALTH: WHAT WE KNOW, AND WHERE TO GO FROM HERE SUSAN T. CHARLES, KATE A. LEGER, AND EMILY J. URBAN

Researchers have long investigated the link between emotional distress and physical health status (Selye, 1953). When strong enough, emotional experiences create a cascade of physiological reactions that can influence a range of health outcomes (Selye, 1953). For older adults who often live with chronic conditions that can be painful (such as osteoarthritis or muscular pain) and potentially disabling (e.g., cognitive impairment), these issues are increasingly germane to the quality of their life (see the review by Salive, 2013). The effect of health problems on daily life throughout adulthood is sobering: In a survey asking whether a physical or mental condition created difficulty carrying out daily activities, rates of disability increased with age: A disability was reported by 11% of 18- to 44-year-olds, 24% of 45- to 64-yearolds, and 52% of people 65 years and older (Brault, 2008). The current chapter reviews how emotional experiences vary across the adult lifespan and discusses the implications of these age differences for

http://dx.doi.org/10.1037/14857-010 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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health-related outcomes. We begin by recognizing the increased health risks with age, but not associated risk for emotional distress. Older adults often report worse physical, cognitive, and functional well-being than younger adults, yet similar if not higher levels of affective well-being (e.g., Charles & Carstensen, 2008; Piazza, Charles, & Almeida, 2007). We interpret this paradox using socioemotional selectivity theory (SST; Carstensen, 2006) and strength and vulnerability integration (SAVI; Charles, 2010) and differentiate these theories from other lifespan developmental perspectives. We then consider age differences in emotion-related behaviors and experiences within the context of these theories. In doing so, we highlight the importance of regulating emotion for physical well-being and illustrate how older adults engage in emotion regulation strategies that benefit their physical health. We conclude with a discussion of future work and challenges in the field of emotions and health within lifespan development. AGING, HEALTH, AND EMOTIONAL WELL-BEING Cognitive and physical health impairments are significant problems among older populations. To place this in concrete terms, the number of older adults with Alzheimer’s disease (4.5 million) equals the state populations of Wyoming, Vermont, Alaska, North and South Dakota, and Delaware combined (Hebert, Scherr, Bienias, Bennett, & Evans, 2003; U.S. Census Bureau, 2013). Among people ages 70 or older, 80% have at least one of the eight most common chronic physical conditions (arthritis, diabetes, angina/coronary heart disease, stroke, asthma, heart attack, hypertension, and cancer), and almost 20% have three or more of these conditions (Pearson, Bhat-Schelbert, & Probst, 2012). Moreover, as mentioned previously, more than half of people 65 years and older report a functionally limiting condition (Brault, 2008). Poor physical health, in turn, is associated with lower levels of emotional well-being, a construct typically defined by higher rates of positive emotions and lower rates of negative emotions and highly correlated with life satisfaction. For example, people with low levels of life satisfaction are 4 times more likely to report physical distress, almost 6 times more likely to experience pain, and 7.7 times more likely to have reported activity limitations than their more satisfied counterparts (Strine, Chapman, Balluz, Moriarty, & Mokdad, 2008). In terms of positive and negative affect, a greater number of chronic conditions is related to successively lower levels of positive affect and higher levels of negative affect (Piazza et al., 2007). Depressive symptoms and poorer cognitive functioning have been so strongly linked that researchers are investigating a shared pathophysiology between emotional

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dysregulation and both mild cognitive impairment and Alzheimer’s disease (e.g., Lee, Hermens, Porter, & Redoblado-Hodge, 2012). Extrapolating from models stating that poor health decreases affective well-being (e.g., Leventhal & Scherer, 1987), higher rates of disease and disability in old age would naturally portend worse emotional well-being. Extrapolating from stress models, worse emotional well-being would then lead to poorer physical health based on stress models of health (e.g., McEwen, 1998; Selye, 1953). Both scenarios, then, would predict spiraling physical and emotional distress with age. Yet, older adults often report better emotional functioning than younger adults, as indicated by many cross-sectional studies of age and affect. For example, older age was related to successively lower levels of stress and anger and higher reports of positive well-being items including happiness and enjoyment among people ranging from 18 to 85 years old (Stone, Schwartz, Broderick, & Deaton, 2010). Longitudinal studies find that negative affect decreases and positive affect remains relatively stable or increases over time (Carstensen et al., 2011; Charles, Reynolds, & Gatz, 2001). Given that emotions are so closely tied to health status, this ageassociated increase in emotional well-being is often considered to be a “paradox of aging.” Theories to Explain the Paradox of Aging Recent theoretical advances explain the discrepant findings regarding age and emotion in the literature, although the proposed mechanisms for such effects vary across theories. We use SST (Carstensen, 2006; Carstensen, Isaacowitz, & Charles, 1999) and SAVI (Charles, 2010; Charles & Piazza, 2007) to explain the paradox of aging. These theories describe age-related increases in well-being as the result of age differences in the valuation and appraisal of emotional experiences as well as the variations in the circumstances and timing under which emotional experience is assessed. Socioemotional Selectivity Theory SST (Carstensen et al., 1999) focuses on age-related motivational shifts and proposes that people are motivated by two types of goals: those focused on gathering information and knowledge and those based on deriving emotional meaning and well-being. SST posits that as adults age, they become increasingly aware of their limited time left in life. As a result, they increasingly favor emotion-focused goals. In so doing, older adults tend to value rewarding relationships over meeting new social partners. Their greater focus on emotional goals is also thought to shift attention to more positive and

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less negative emotional stimuli in the environment and to direct cognitive processing toward more positive and less negative appraisals, preferences, and memories. This latter phenomenon has been termed the age-related positivity effect (see the review by Reed & Carstensen, 2012) and in support of this effect, laboratory studies have found that older adults tend to focus away from negative stimuli and more toward positive stimuli than their younger counterparts (Isaacowitz, 2006; Mather & Carstensen, 2003). Furthermore, older adults recall more positive than negative images relative to younger adults (Charles, Mather, & Carstensen, 2003). The positivity effect can at least partially explain why older adults often report similar if not higher levels of emotional well-being than younger adults and can thus be considered as a benefit, or strength, of aging. However, a greater emphasis on positivity and an increased appreciation for close social relationships are not the only strengths of aging. Moreover, the practical implications of age-related strengths cannot be fully understood without also considering the vulnerabilities. Strength and Vulnerability Integration SAVI addresses these concerns by recognizing and integrating the strengths and vulnerabilities of aging for regulating emotional experience (Charles, 2010; Charles & Piazza, 2007). SAVI posits that strengths with age including increase use of emotion regulation strategies aimed to decrease exposure to negative experiences. These strategies, described by emotion theo­rists (e.g., Gross, 1998), include behaviors such as selecting situations that are less negative and more positive (situation selection), focusing attention away from negative stimuli, modifying the environment to reduce exposure to negative experiences (situation modification), and appraising and remembering events as more positive and less negative. They are motivated to do so based on time perspective (as described by SST; Carstensen, 2006), and they are more adept at navigating emotionally sensitive situations based on knowledge gained from earlier life experiences (e.g., Blanchard-Fields, 2007). However, when people cannot employ these regulation strategies they lose their age-related advantages. Moreover, when people cannot use avoidant strategies (a strength associated with aging) to avoid high and sustained levels of distress, SAVI posits that the ensuing sustained physiological arousal will be more difficult to tolerate for older adults. In this situation, age-related decreases in physiological flexibility (a vulnerability associated with aging) will create slower reactivity but will also create more problems in down-regulating high levels of arousal. By integrating such insights into the context of daily life, researchers can predict when strengths will lead to greater emotional wellbeing with age and when older adults will no longer benefit from age-related advantages. 188       charles, leger, and urban

Unfortunately, certain situations that prevent people from capitalizing on age-related strengths in cognitive and behavioral strategies are more likely to occur in old age. According to SAVI, situations such as loss of social belonging, uncontrollable chronic stressors, and neurological dysfunction are factors that often increase with age and may explain why some older adults report high levels of emotional distress. In addition, these types of situations often elicit high levels of physiological distress that pose a threat to physical wellbeing. Older age has been associated with a poorer physiological tolerance to stress (Graham, Christian, & Kiecolt-Glaser, 2006). For example, SAVI recognizes age-related vulnerabilities as conceptualized by biological models such as the glucocorticoid cascade hypothesis (Sapolsky, Krey, & McEwen, 1986). This hypothesis predicts that age-related physiological changes create greater problems down-modulating the reactivity of the hypothalamic– pituitary–adrenal (HPA) axis in response to stress. SAVI posits that because older adults have less physiological flexibility needed to recover from high arousal stressors, it is more costly to their systems to react to and then downregulate from negative experiences. Other Models of Emotion and Aging There are, of course, alternative models of emotion and aging, but in contrast to the two above, they focus on age-related losses without explicitly considering the role of strengths. For example, researchers have posited that age-related deterioration in certain brain regions (specifically the amygdala) can account for older adults’ greater attention to positive emotional stimuli relative to negative stimuli (Cacioppo, Berntson, Bechara, Tranel, & Hawkley, 2011). Similarly, according to dynamic integration theory (Labouvie-Vief, 2003), age is related to a reduced ability to navigate the tension between the optimization of happiness and the integration of negative information. As a result, older adults are thought to have poorer self-regulation abilities, and are seen as compensating for their inabilities by focusing on positive aspects of their lives and ignoring negative information. In contrast to such deficit-based models, the selective optimization and compensation with emotion regulation model (SOC–ER; Urry & Gross, 2010) offers a more differentiated view. According to this model, age-related losses—specifically in the area of cognitive control—motivate compensatory strategies to optimize emotional well-being in spite of such losses. SOC–ER focuses primarily on resources for response modulation (the down-regulation of negative emotions that have already occurred), including both emotional expressions and somatic responses, but it also considers behavioral strategies and situation selection. For instance, the smaller and more satisfying social networks seen among older adults are viewed as a compensatory mechanism through which they maintain high levels of well-being. emotional experience and health     

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Nonetheless, the SOC–ER model differs from SAVI and SST with regard to the proposed role of cognitive decline. SOC–ER conceptualizes reductions in cognitive control as partial motivation for age-related improvements in well-being. In this view, age-related reduction in cognitive control motivates people to engage more often in emotion regulation strategies to avoid negative affect and promote more positive experiences. In contrast, SST and SAVI view cognitive decline as a risk factor for effective emotion regulation. They incorporate the cognitive control hypothesis, which states that cognitive control is necessary for effective emotion regulation and that declines in control pose a risk to the use of cognitive and behavioral strategies (Nashiro, Sakaki, & Mather, 2012). Explaining Age Differences in Emotional Experience, Thoughts, and Behaviors Many studies are consistent with the predictions of SST and SAVI and show that older adults use thoughts and behaviors that allow them to minimize their exposure to negative experiences and promote more positive experiences (see the review by Charles & Carstensen, 2010). In addition, we see attenuation and sometimes absence of age-related improvements when people encounter situations where they cannot avoid unpleasant experiences. In the following we discuss empirical examples of the theory-based predictions regarding when age is related to emotion-enhancing thoughts and behaviors and when the benefits of age taper off. The studies described below reflect the existing literature, most of which is based on studies conducted in North America or Europe, and include predominantly Caucasian samples. For example, 87% of Americans 65 years and older were Caucasian in 2009 (U.S. Census Bureau, 2010), and most study samples reflect this. In addition, studies—particularly those using laboratory based methods—frequently assessed people living near large urban centers and involved cross-sectional data. Selection effects are always a concern when comparing current groups of older adults with younger adults. For example, average life expectancy of someone born in 1950 is 68 years compared with the 75 years and older expected for someone born in 1990 or later (Murphy, Xu, & Kochanek, 2013). Thus, more select older survivors are compared with samples of younger adults with unknown longevity status. This concern about selection effects should make us interpret cross-sectional findings with caution. Longitudinal data provide insight into questions of change with age as opposed to age differences, but these valuable studies are rare. The majority of the results noted below provide information about how older adults vary from younger adults. The findings are consistent with tenets of SST and SAVI, but only longitudinal studies will confirm whether these theories are describing 190       charles, leger, and urban

phenomena driven by age-related trajectories of change, or whether they are describing characteristic differences between the type of person who lives into old age and younger adults who may or may not survive into old age. Age, Social Support, and Health Interpersonal stressors are among the most potent and frequent stressors people face in their daily lives (e.g., Almeida, 2005). Social bonds in the form of self-reported close relationships are also critical for physical health, predicting morbidity and mortality on par with more traditional risk factors, such as smoking status and body mass index (see the review by Holt-Lunstad, Smith, & Layton, 2010; Uchino, Bowen, Carlisle, & Birmingham, 2012). Social relationships and health are linked together among people of all ages, but the ways in which people navigate conflict within their close social relationships vary with age. As predicted by SST, older people report less distress in response to social tensions (e.g., Birditt & Fingerman, 2003) and also tend to report more positive emotions in social interactions than younger adults (Charles & Piazza, 2007). Older adults may also use their life experiences, as suggested by SAVI, to refine their strategies to avoid social tensions (Blanchard-Fields, Mienaltowski, & Seay, 2007). One study, for example, showed that when older and younger adults were given hypothetical problem scenarios and asked how best to solve them, older adults were better at picking the more effective strategy (BlanchardFields et al., 2007). Importantly, this study revealed that older adults are not better at navigating social relationships simply because they use one successful strategy on which they consistently rely. Instead, older adults flexibly used different strategies across different types of social problems more so than younger adults, and were rated as more successful in their efforts. Despite using a variety of strategies, older adults are more likely to use passive regulation strategies in response to interpersonal conflict than younger adults (Birditt & Fingerman, 2005; Blanchard-Fields, 2007; Miller, Charles, & Fingerman, 2009). Not only do older adults endorse using these strategies more often, but they also recommend these more passive strategies to others as the best option in response to negative confrontation (Charles, Carstensen, & McFall, 2001). A longitudinal study showed that older married couples engaged in more avoidance behavior over time (13 years), which demonstrates that this tendency to engage in passive regulation strategies increases with age (Holley, Haase, & Levenson, 2013). As posited by SAVI, avoiding confrontation appears to provide more emotional benefits for older adults than younger adults (Charles, Piazza, Luong, & Almeida, 2009). For example, a diary study among adults ranging from 25 to 74 years old found that when potential arguments were avoided, older adults showed less affective reactivity than younger adults (Charles emotional experience and health     

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et al., 2009). However, when an argument actually occurred age was unrelated to stress reactivity. In another diary study, adults ranging from their 40s to their mid-90s were asked whether they had encountered distressing or potentially distressing social interactions, and whether they had avoided feeling actual distress (Birditt, 2014). The oldest adults reported lower levels of negative affect when they said they avoided these emotions. However, when they reported having a negative social encounter they reported higher levels of negative affect than the younger adults in this sample. Fewer studies have examined age differences in how negative emotions elicited by social experience influence physiology. One study showed that being lonely increased cardiovascular reactivity to stressors among both younger adults (predominantly in their 20s) and older adults (mid-60s to 80 years old), but this effect was even stronger among older adults (Ong, Rothstein, & Uchino, 2012). In another study that also compared younger and older age groups, younger adults were asked to ruminate or to sit quietly in a room after they had completed a social stressor in which they had given a speech in front of an evaluative audience (Robinette & Charles, 2014). During the task, everyone exhibited an increase in blood pressure, and the researchers examined the time it took for blood pressure to return to baseline levels during the recovery period. For younger adults, rumination was not related to blood pressure recovery. For older adults, however, rumination was related to delayed recovery after the stressor was over. Together, these findings lend support for SAVI in that older adults fare worse than do younger adults when they cannot avoid negative emotions. Aging, Appraisals, and Health A growing number of cross-sectional findings confirm that older adults engage in more positive and fewer negative appraisals of potentially threatening stimuli than younger adults. In laboratory tasks, older adults in their 60s and older appraise people who treat them rudely as more likeable (Luong & Charles, 2014) and less negative (Charles & Carstensen, 2008) than do younger adults in their late teens and 20s. Married adults in their 60s and older also rate the behaviors of their spouses during a conflict as less negative than do objective raters (Story et al., 2007) and as less negative compared with the ratings that adults in their 40s make of their own spouses in the same situations. Older adults also engage in more positive appraisals of their health. When asked about whether they were aging successfully, 50% of older adults agreed strongly in the affirmative (Strawbridge, Wallhagen, & Cohen, 2002). Yet, only 18% of these same individuals were rated as aging successfully when researchers categorized them based on Rowe and Kahn’s (1987) rubric consisting of absence of disease, disability or elevated risk factors, maintaining physical and mental functioning, and active engagement with life. In more 192       charles, leger, and urban

recent studies, the majority of older adults reported higher levels of well-being than did younger adults (Stone et al., 2010), and yet only an estimated 12% of adults in the United States over age 65 were reported as aging successfully when their health was assessed using the Rowe and Kahn (1987) definition mentioned above (McLaughlin, Connell, Heeringa, Li, & Roberts, 2010). SST does not interpret less negative appraisals of the daily stressors that older adults encounter as strategies to maintain physical health, yet they do seem to convey health benefits. For example, older age is related to a lower tendency to ruminate and express regret among samples of younger, middleaged, and older adults (e.g., Nolen-Hoeksema & Aldao, 2011). This is an age-related benefit to emotional well-being, especially because perseverative negative thoughts are related to prolonged physiological activity that can have long-term effects on physical health (e.g., Verkuil, Brosschot, Gebhardt, & Thayer, 2011). A recent study found that when people reported that they were preoccupied with thoughts about a previously experienced hassle in their daily lives, well-being was more affected with age among a sample ranging from 12 to 88 years old (Wrzus, Luong, Wagner, & Riediger, 2015). As noted above, a recent study suggests that perseverative cognition may be worse for the physiology of older adults than younger adults (Robinette & Charles, 2014). Only a few studies have tested the tenet of SAVI suggesting that selfreported highly negative affective experiences pose stronger physiological consequences for older as opposed to younger adults. One study found that when confronted with sadness-inducing stimuli, physiological reactivity was greater for older adults than middle-aged and younger adults (Seider, Shiota, Whalen, & Levenson, 2011). Another study found that higher levels of negative affect were related to higher cortisol AUC only for those ages 53 and older, but not for the younger adults in the sample, those ages 34 to 52 (Piazza, Charles, Stawski, & Almeida, 2013). Examining the effects of positive affect in this sample, only people age 60 and older showed a significant association between low rates of positive affect and higher levels of cortisol. Similar agerelated patterns emerged when examining the association between trait-like levels of anger and the metabolic syndrome (Boylan & Ryff, 2013). In a sample of adults ranging from 35 to 86 years old, aging was unrelated to metabolic syndrome among people who reported low levels of anger. For people with high levels of anger, older age was related to greater likelihood of being diagnosed with the syndrome. Age and the Temporal Dynamics of Affective Experiences SAVI predicts that how and when emotions are assessed are important factors influencing observed age differences. Older adults appraise potential stressors less negatively and reappraise prior stress less negatively in their recall of the events. As researchers query people closer to the time of the event, age emotional experience and health     

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differences are predicted to diminish. In one study examining people ranging from 18 to 89 years old, age was unrelated to affective reactivity to a stressor reported that day, but older age was related to less reactivity in response to the accumulation of past stressors that had occurred earlier in the week (Schilling & Diehl, 2014). Another study examining people ranging from 25 to 84 years old found that age differences were greatest when people reported how they felt across an entire month, a process that requires reconstruction of their past daily events (Charles et al., 2014). However, age differences diminished when asking people to recall negative emotions they had experienced across the prior week, and were lower still when asking about their prior day. In a study examining reactions and adjustment to cancer, age was unrelated to negative affect soon after the cancer diagnosis (Hart & Charles, 2013). However, over time older age was related to lower levels of negative affect. Researchers have found that more momentary reports of emotions are more strongly associated with health outcomes than more global reports (see the review by Conner & Barrett, 2012). If so, then age-related benefits for more global assessments of emotional well-being may not translate to better health outcomes for older adults than younger adults; instead, more immediate reports of emotional experiences are better correlates of health, and these experiences are more similar across age groups. Importance of Context Taken together, SAVI emphasizes the importance of life circumstances (i.e., the situations that people actively place themselves in based on their motivational priorities and life experiences) and considers their influence on physical and emotional well-being. Several large studies found that older adults are less likely to report having experienced stressors when asked about their experiences in the past week (Aldwin, Sutton, Chiara, & Spiro, 1996) or when asked nightly across a week in daily diary studies (Almeida & Horn, 2004; Brose, Scheibe, & Schmiedek, 2013). In one study examining people ages 63 to over 90, the occurrence of stressors fully accounted for the association between older age and lower negative affect (Charles et al., 2010). By integrating agerelated strengths and weaknesses in these life contexts, we predict that older adults will show age-related benefits in less stressful circumstances, for instance, when asked to examine negative and positive stimuli in the lab, or when asked to recall daily events. However, when older adults are exposed to a highly stressful situation, age differences will diminish if not disappear completely. Disadvantaged and Advantaged Groups Examining exceptional older adults, both those doing better than average and those doing worse, provides insight into the important role of context 194       charles, leger, and urban

in predicting emotional well-being with age. Researchers have documented pockets of older adults who are not aging successfully. High rates of depression and anxiety are seen among older adults who are faced with the chronic stress of caregiving (Seeher, Low, Reppermund, & Brodaty, 2013), those close to death (Gerstorf et al., 2010), and those with cognitive impairments (Lee et al., 2012) or even lower levels of executive functioning than their peers (Nashiro, Sakaki, & Mather, 2012). When examining older adults who had committed suicide, some common predictors in addition to mental illness include being widowed or divorced and not in contact with children, having poor physical health, and facing financial stressors (e.g., Duberstein, Conwell, Conner, Eberly, & Caine, 2004). These socially isolating, physical, and financial situations create a stressful context where age-related benefits of strong social networks and lower numbers of reported stressors are most likely absent. In contrast, studying people who display superior emotion regulation in late life similarly provides insight into age-related strengths and challenges. SAVI posits that physiological vulnerabilities create more difficulty when regulating arousal from highly emotional experiences. However, some older adults show reduced arousal and improved recovery compared with others. For example, older adults who regularly exercise and are physically fit exhibit emotion-related benefits (Traustadóttir, Bosch, & Matt, 2005). Specifically, older women (average age 66) who were rated as physically fit based on performance on a treadmill showed faster HPA recovery after a stressor (as indicated by cortisol levels) than nonphysically fit older women (Traustadóttir et al., 2005). For younger women who were, on average, 28 years old, physical fitness was unrelated to HPA recovery. Physical fitness is strongly related to emotional well-being and emotion regulation not only directly but also indirectly through its influence on cognitive functioning (e.g., see the review by Depp, Vahia, & Jeste, 2010). The pattern of results strengthens the importance of physical well-being as an asset and physical vulnerabilities as a risk for emotion regulation, particularly for older adults. FUTURE WORK AND CHALLENGES The opportunities to study the intersections between emotion, health, and aging have never been better. Research on emotion has burgeoned in recent years, and the areas of health and lifespan developmental psychology have now developed into strong disciplines. With the continuous development of more accessible and economical physiological assessments and faster and stronger computers to run sophisticated software programs, researchers can ask psychological questions that were limited by technology in years past. emotional experience and health     

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At the same time, questions regarding how emotions are associated with physical health in adulthood have never been more important. This association and its importance are not unique to older adults. Yet, society is aging. Medical advances allow people to live longer with serious physical conditions than they have in the past. Understanding how these physical processes are related to emotional experiences, and how these processes may vary by age and by health status, continues to be a pressing issue to an aging society. Age is a Factor, Not a Covariate, in Health Psychology Despite the unique importance of aging, health researchers often include age as a covariate in their research and include it less frequently as a moderating influence when studying emotion and health-related phenomena. The lack of studies examining how age is related to the health-emotion association may stem from a number of factors. First, psychological research is often hampered by an overreliance on young, college-age samples. This sampling bias is a concern among social psychologists but should be arguably more so to health psychologists. Second, when researchers examine age differences in health processes, null findings are often ignored. Psychological research has predominantly relied on statistics that rely on rejecting null effects, and the “file drawer phenomenon” for null effects is a concern. Perhaps the association between emotion and health is in fact fairly similar across age, but only significant differences are reported. Either way, we need to understand whether age changes the association between emotional well-being and health. If we ignore null findings, we lose important information that would provide a comprehensive understanding of potentially complex relationships. Examining Context By itself, a finding of “age differences” does not provide information about underlying mechanisms. Age is a proxy for thoughts, behaviors, physiology, and circumstances that shape emotional experiences. Armed with a theoretical framework, we highlight some future areas of needed research in the field of emotion, health, and aging to try to determine the cause of observed age differences. Yet, researchers need to continue to refine theoretical explanations. By integrating information about age-related strengths and weaknesses in the context of where, how, and why emotions are experienced, researchers can better understand the role of each when discussing age differences in levels of emotional well-being. To further complicate matters, emotion and health are each associated with a complex array of genetic and environmental factors that vary across individuals. In addition, the effects of these experiences are not uniform across age groups; the genetic contributions 196       charles, leger, and urban

of immunological factors, for example, vary by age depending on the immune marker studied (e.g., Sas et al., 2012). Even when researchers identify specific mechanisms that may underlie age differences (e.g., time perspective, physiological decline), these mechanisms may vary across different people. For example, age is often a proxy for physical health, yet a vast heterogeneity exists in physiological processes— both between people and within people across different organ systems. In addition, age is related to different perceptions, such as time left to live (Carstensen, 2006) and time to death (Gerstorf et al., 2010), and people who are the same age can hold different views of these constructs according to their current circumstances. Finally, the lives of younger, middle-aged, and older adults involve different occupational activities, social roles, and health statuses. Questions arise regarding what types of experiences we are comparing, and how they differ when they are “on-time” or typical for a life stage, or when they are atypical, such as bereavement at a young age or working full-time at age 80. In addition, many of these hypothesized mechanisms have been inferred but not directly tested. For example, physical health declines are often inferred on the basis of chronological age, and time perspective is often inferred on the basis of chronological age or health status. Moreover, emotion regulation strategies such as selective attention or memory have been discussed as efficacious by emotion researchers (e.g., Urry & Gross, 2010), yet few studies have directly tested the use of these strategies for regulating emotional experiences. This problem is pervasive across the emotion literature, including the literature examining age differences in these processes. Need for Longitudinal Analyses Finally, developmental processes can only be tested using longitudinal techniques, yet many existing longitudinal studies have only fairly recently included a comprehensive measure of emotions. Researchers are paying growing attention to age differences in high versus low arousal positive and negative emotions (Dolcos, Katsumi, & Dixon, 2014) and to cross-sectional age differences in both frequency and intensity of these emotional experiences (e.g., Carstensen et al., 2011). Disentangling cohort differences and historical trends from developmental processes remains limited by the lack of longitudinal data. CONCLUSION In combination, SST and SAVI highlight the strengths and vulnerabilities of aging and contend that older adults use cognitive behavioral strategies, motivational goal selection, and capitalization of existing resources to emotional experience and health     

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Schilling, O. K., & Diehl, M. (2014). Reactivity to stressor pile-up in adulthood: Effects on daily negative and positive affect. Psychology and Aging, 29, 72–83. http://dx.doi.org/10.1037/a0035500 Seeher, K., Low, L. F., Reppermund, S., & Brodaty, H. (2013). Predictors and outcomes for caregivers of people with mild cognitive impairment: A systematic literature review. Alzheimer’s & Dementia, 9, 346–355. http://dx.doi.org/10.1016/ j.jalz.2012.01.012 Seider, B. H., Shiota, M. N., Whalen, P., & Levenson, R. W. (2011). Greater sadness reactivity in late life. Social Cognitive and Affective Neuroscience, 6, 186–194. http://dx.doi.org/10.1093/scan/nsq069 Selye, H. (1953). The general-adaptation-syndrome in its relationships to neurology, psychology, and psychopathology. In A. Weider (Ed.), Contributions toward medical psychology: Theory and psychodiagnostic methods (Vol. 1, pp. 234–274). New York, NY: Ronald Press Company. http://dx.doi.org/10.1037/11419-011 Stone, A. A., Schwartz, J. E., Broderick, J. E., & Deaton, A. (2010). A snapshot of the age distribution of psychological well-being in the United States. PNAS Proceedings of the National Academy of Sciences, 107, 9985–9990. http://dx.doi. org/10.1073/pnas.1003744107 Story, T. N., Berg, C. A., Smith, T. W., Beveridge, R., Henry, N. J. M., & Pearce, G. (2007). Age, marital satisfaction, and optimism as predictors of positive sentiment override in middle-aged and older married couples. Psychology and Aging, 22, 719–727. http://dx.doi.org/10.1037/0882-7974.22.4.719 Strawbridge, W. J., Wallhagen, M. I., & Cohen, R. D. (2002). Successful aging and well-being: Self-rated compared with Rowe and Kahn. The Gerontologist, 42, 727–733. http://dx.doi.org/10.1093/geront/42.6.727 Strine, T. W., Chapman, D. P., Balluz, L. S., Moriarty, D. G., & Mokdad, A. H. (2008). The associations between life satisfaction and health-related quality of life, chronic illness, and health behaviors among U.S. community-dwelling adults. Journal of Community Health, 33, 40–50. http://dx.doi.org/10.1007/ s10900-007-9066-4 Traustadóttir, T., Bosch, P. R., & Matt, K. S. (2005). The HPA axis response to stress in women: Effects of aging and fitness. Psychoneuroendocrinology, 30, 392–402. http://dx.doi.org/10.1016/j.psyneuen.2004.11.002 Uchino, B. N., Bowen, K., Carlisle, M., & Birmingham, W. (2012). Psychological pathways linking social support to health outcomes: A visit with the “ghosts” of research past, present, and future. Social Science & Medicine, 74, 949–957. http:// dx.doi.org/10.1016/j.socscimed.2011.11.023 Urry, H. L., & Gross, J. J. (2010). Emotion regulation in older age. Current Directions in Psychological Science, 19, 352–357. http://dx.doi.org/10.1177/ 0963721410388395

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U.S. Census Bureau. (2010). Annual estimates of the resident population by race, Hispanic origin, sex and age for the United States: April 1, 2000 to July 1, 2009 (NC-EST2009-04). Retrieved from http://www.census.gov/popest/national/ asrch/NC-EST2009-asrh.html U.S. Census Bureau. (2013). Annual estimates of the population for the United States, regions, states, and Puerto Rico: April 1l, 2010 to July 11, 2013 (NST-EST2013-01). Retrieved from http://www.census.gov Verkuil, B., Brosschot, J. F., Gebhardt, W. A., & Thayer, J. F. (2011). Perseverative cognition, psychopathology, and somatic health. In I. Nyklicek, A. Vingerhoets, & M. Zeelenberg (Eds.), Emotion regulation and well-being (pp. 85–100). New York, NY: Springer. http://dx.doi.org/10.1007/978-1-4419-6953-8_6 Wrzus, C., Luong, G., Wagner, G. G., & Riediger, M. (2015). Can’t get it out of my head: Age differences in affective responsiveness vary with preoccupation and elapsed time after daily hassles. Emotion, 15, 257. http://dx.doi.org/10.1037/ emo0000019

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V Interventions

10 THE HUMANIZATION OF SOCIAL RELATIONS: NOURISHMENT FOR RESILIENCE IN MIDLIFE ALEX J. ZAUTRA, FRANK J. INFURNA, EVA K. ZAUTRA, CARMEN ÉCIJA GALLARDO, AND LILIAN VELASCO

The less I thought about myself, the more myself I became. —Akhil Sharma, “The Trick of Life”

In this chapter, we build a case for the humanization of social relations as a key to resilient adaptations to stress for people in midlife. Resilient adaptation is characterized by three qualities: the speed and thoroughness of stress recovery, the capacity to sustain purpose, and the capacity to attain the kind of psychological growth that reveals a greater maturity of the mind (Zautra, Arewasikporn, & Davis, 2010). We suggest that emotional health and the capacity to be resilient depend on healthy social relationships. When people humanize their social relations, they understand one another as unique individuals with minds, needs and goals, and emotions worthy of attention, and they do not objectify their identities on the basis of some group classification or to fill their own emotional needs. The stronger social bonds that result from humanization are more sustainable, encourage openness to new learning, and speed recovery following social stress. To examine this proposition,

http://dx.doi.org/10.1037/14857-011 Emotion, Aging, and Health, A. D. Ong and C. E. Löckenhoff (Editors) Copyright © 2016 by the American Psychological Association. All rights reserved.

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we provide some preliminary evidence that the quality of social relations can be improved through greater attention to the interests and perspectives of others. The past 25 years of social science research provides ample evidence that social connections play a critical role in mitigating the effects of life’s most stressful experiences (Cohen & Wills, 1985; Cook & Bickman, 1990; MacGeorge, Samter, Feng, Gillihan, & Graves, 2004). The value of social ties is also not limited to stressful times. Individuals with strong bonds have healthier cardiovascular functioning under challenge; more efficient immune activation when exposed to pathogens; are less likely to abuse substances; suffer less disability in response to illness; and live longer, healthier lives (Hawkley & Cacioppo, 2010; House, Umberson & Landis, 1988; Zautra, 2013). Mental health, as well as physical health, depends on strong social relations. Anxiety and depression are linked to lost or threatened social bonds and those with poor social ties are at greater risk of suicide (Bonanno & Hymel, 2010). People with positive social relations also live longer. Holt-Lunstad, Smith, and Layton (2010) reviewed 148 longitudinal studies of aging on this question, including a total of 308,849 participants, followed for an average of 7.5 years. The studies were conducted across the globe, and the average age of participants at initial evaluation was 64 years. Cumulative empirical evidence across the 148 prospective studies indicated a 50% increased likelihood of survival for participants with strong social relationships compared with those with weaker social relationships. Why are strong social relationships so beneficial for mental and physical health? There are at least two good reasons. First, people lean on others when in need, and do so naturally when in good relationships, usually without much thought. In response to caring for another, the parasympathetic system comes to life, providing balance to sympathetic arousal, which is necessary for the regulation of the nervous system (Uchino, 2006). Second, relationships with others are often the greatest sources of joy. It is important not to neglect the benefits not only of kindness and other emotions that calm the mind but also of those energy-enriched positive emotions that come from close social connection (Kok et al., 2013). Vitality is one of the engines of longevity (Fries & Crapo, 1981), and words like energy and curiosity define key items of one of the most widely used measures of resilience, the Ego Resilience Scale (Block & Kremen, 1996). Block and Kremen’s (1996) analysis of the correlates of their scale also revealed that socially intelligent behavior dominated the narratives of those scoring high on Block’s scale, even though the scale is labeled “ego” resilience.

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OUR RESEARCH: ARE SOCIAL RELATIONS THE KEY TO RESILIENCE IN MIDLIFE? Our own findings, emerging from analyses of a 5-year grant funded by the National Institute on Aging, are consistent with this line of reasoning. The key resources underlying resilience among middle-aged adults were strong, sustainable social relations, and the key threat to resilience appeared to be troubled social relations. In this project, we examined biopsychosocial resilience processes and outcomes for a community sample of 800 individuals in midlife, ranging in age from 40 to 65. Extensive questionnaires covered mental and physical health, personality, social relationships, and early life experiences, including reports of child abuse. Biological markers of allostatic load and genetic profiles were obtained through blood draws, and a 45-minute phone interview assessed stressful/traumatic life events (past year, lifetime), evidence of Diagnostic and Statistical Manual of Mental Disorders diagnosis of depression and anxiety disorder, and a discussion of the most stressful life experiences with a focus on resilience response. Thirty-day diaries were obtained from a randomly selected quarter of the sample. A 6-month follow-up phone interview recorded mental and physical health and cognitive functioning. Though not all analyses have been completed, there are key findings that have held up to close examination worthy of report here. In the initial assessment, we gathered considerable information on physical health and mental health of the sample to be able to identify three correlated factors that serve as markers of resilient adaptation to midlife for our sample: the preservation of physical functioning, high scores on selfreports of psychological well-being, and low levels of psychological distress. Well-being and distress share variance with physical functioning, and when cast in a regression equation, may strongly predict it. When seeking predictors of functional health, we looked to early life, a history of traumatic experiences, and also contemporaneous life events. Further, we examined current social relations across a range of indicators taken from the Midlife in the United States (MIDUS) study and formed into indices following careful confirmatory factor analytic work. We obtained retrospective accounts of emotional, physical, and sexual abuse in childhood (Bernstein et al., 2003). These accounts predicted psychological distress, reductions in well-being, and our key contemporaneous outcome, current levels of physical functioning. Also related to these measures was a count of lifetime traumatic episodes. Those reporting abuse in childhood were likely to have a higher number of traumas, which also predicted current physical functioning.

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Table 10.1 shows some of the detailed findings among those with a history of child abuse. More childhood trauma was associated with greater psychological distress at initial assessment, as well as poorer physical functioning, more somatic complaints, more frequent endorsement of total symptom counts for anxiety and depressive disorders, more chronic pain, more lifetime difficulties due to substance use, and lower scores on cognitive functioning and physical functioning at a 6-month follow-up. Furthermore, greater childhood trauma was also associated with higher levels in a key biomarker of inflammation: interleukin-6 (IL-6). Social relationships mediated links between reports of childhood trauma and mental and physical health. As a first step, we found that current family support and strain were associated with mental and physical health (more family support and less family strain was associated with lower psychological distress, depression, less bodily pain, and better physical functioning). Second, we tested whether childhood trauma was associated with family support and strain at baseline and interpersonal joy and stress at the 6-month follow-up. Greater childhood trauma was associated with less family support (b = -.30, p < .05) and more family strain (b = .24, p < .05), including less interpersonal joy (b = –.30, p < .05) and more interpersonal stress (b = .23, p < .05) at the 6-month follow-up. We next used the Sobel (1982) test to explore whether family support and strain mediated the link between childhood trauma and mental and physical health. We found that family support significantly mediated the association between childhood trauma and distress, IL-6, lifetime substance abuse, depression, pain, and Physical Component Score (PCS), and family strain mediated the association between child abuse and distress, depression, bodily pain, and PCS. Our findings showing that early life adversity is associated with premature declines in mental and physical health in midlife were consistent with those of Vaillant (2012), in his life’s work in the Harvard study, as well as investigators at Purdue (Schafer, Ferraro, & Mustillo, 2011) and elsewhere (e.g., Savla et al., 2013). The findings on mediation are novel in that we can begin to piece together possible mechanisms linking early life adversity to mental and physical health, namely social relationship quality (for possible daily mechanisms underlying this relationship, see Infurna, Rivers, Reich, & Zautra, 2015). Although there are limitations in that social relationship quality and most of the outcomes were assessed at one time point, the findings shown here provide evidence that suggests that social relationship quality is a key pathway through which early life adversity has such detrimental effects later in life (for a review, see Miller, Chen, & Parker, 2011). The data that underlie our research on resilience began with questionnaires and interviews of adult residents of their communities. We relied on their retrospective accounts of child abuse, which raises doubts of the accuracy 210       zautra et al.

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TABLE 10.1 Relations Between Childhood Trauma and Mental and Physical Health at Midlife Baseline questionnaire

CTQ-Total

6-month follow-up questionnaire

Psychological distress

IL-6

DHEA-S

Substance abuse

MHI– depression

TICS– cognition

Bodily pain

PCS

.36*

.13*

-.08*

.30*

.33*

-.20*

.31*

.36*

Note.  Shown are standardized estimates from regressing outcomes on Childhood Trauma Questionnaire (CTQ; Bernstein et al., 2003). DHEA-S = Dehydroepiandrosterone sulfate; IL-6 = interleukin-6; MHI = Mental Health Inventory (Veit & Ware, 1983); PCS = Pain Catastrophizing Scale; TICS = Telephone Interview of Cognitive Status (Brandt et al., 1988). Bodily pain and PCS are from the SF-36 (The Short Form [36] Health Survey; Ware & Sherbourne, 1992). Lifetime function loss from substance abuse measure from Johnston and Lloyd (2010). Age and gender were included as covariates. *p < .05.

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of those reports. Current mental health status and family stresses can cue as well as distort memories of past experiences. As Hardt and Rutter (2004) noted, it is wise to be cautious in making definitive interpretation of findings given the widespread evidence of both underreporting as well as overreporting of childhood maltreatment. Nonetheless, careful studies that have included prospective examinations of the role of early life on current functioning have shown that highly stressful social experiences early in life can begin a cascade of disturbances of mind, social life, and body that lead to functional limitations, emotional difficulties, and even a shortened lifespan (e.g., Norman, Byambaa, De, Butchart, Scott, & Vos, 2012; Widom, Czaja, Bentley, & Johnson, 2012). These problems are fundamentally social in origin, and in our opinion, the pathways to resilience to address them are also social. Financial Difficulties Are Linked to Psychosocial and Health Functioning Our study of resilience was conducted during one of the most distressing economic recessions of the past 50 years, one that affected adults at midlife in Arizona especially hard. For many Arizonans, the crisis erased home equity along with expectations of long-term economic security afforded by a booming housing market. We found that the financial downturn was among the most distressing events in our sample, which predicted lower scores on all our outcomes, including physical functioning. Our colleague, Professor Anthony Ong from Cornell, urged us to add one additional factor: emotional complexity. This is measured by the relative distinctiveness in ratings of positive and negative emotions. In our previous work, we referred to this as affective space (Zautra, Potter, & Reich, 1997). We found that those who were in dire financial straits at the time of the interview also showed a diminished affective space. The degree of (inverse) relationship between psychological distress and psychological well-being, as estimated by the covariance between those indicators, was 50% greater than for people without a major financial downturn: The correlation between distress and well-being was -.512 for no major financial events in the past year, and -.647 for those who reported at least one major stressful financial event. When we inspected the daily intercorrelations between positive and negative affective states for those who were administered 30-day diaries, the findings were similar: a more bipolar affective space for those facing serious financial hardship. This narrowing of the range of emotions might be adaptive in the short run, but over time it represents a diminished capacity to hold contradictory feeling states in mind, something others have viewed as essential to psychological growth and resilient adaptation (Ong, Bergeman, & Boker, 2009; Seligman, Railton, Baumeister, & Sripada, 2013). 212       zautra et al.

On the surface, financial hardship hardly seems relevant to this chapter on social relations and resilience, except to reveal sources of influence on adaptation independent of social interaction. However, when we looked deeper, it became apparent that the relationships between major financial downturns, lower well-being, and greater loss of physical functioning were mediated either in whole, or in part, by accompanying social relations difficulties in the home. Analyses of those who completed daily diaries revealed the underlying processes at work. Major financial events predicted a daily life troubled by a surfeit of everyday troubles with money. First and foremost, the influence of these financial stressors in daily life was the increase in everyday interpersonal difficulties with family members. These negative events in turn increased the probability of greater interpersonal stress and, in turn, more negative affective states of mind. Turmoil at home, from the strains of everyday financial difficulties, was the primary mediator of those effects on emotional health (Sturgeon, Zautra, & Okun, 2014). We also counted positive interactions with spouse, family, and friends and their ratings of enjoyment with those experiences. These positive experiences, when frequent, not only raised positive effects but also diminished the impact of negative interpersonal events, moderating the harm of such events on emotional indices. Early Intervention Efforts: Changing Depressive Profiles in Midlife Midlife health is a function of past and present life stressors, but brains are plastic and, as Vaillant (2012) pointed out, there is room for change and development. With plasticity in mind, we turned toward the development and testing of interventions designed to enhance the daily lives of members of our communities. Our focus has been on the delivery of highly accessible interventions delivered to individuals and groups. In this chapter, we do not discuss community-level interventions other than to say that they hold considerable potential, and perhaps are even essential when cultural change is needed so that individual change can be sustained via a responsive social environment. In addition, even though some of our team’s work has been with interventions that rely on group delivery with expert facilitators (usually graduate students in clinical and counseling psychology), here we describe Internet-based e-health interventions because of their greater potential to increase public health. The National Institute on Aging supplemented our midlife grant with funding to examine whether we could budge the depressive profiles of those in midlife, some of whom were in the larger study. Only those with moderately high scores on a screening scale for depression were invited, excluding those with suicidal ideation. The intervention was an automated phone call program that was built on the premise that people’s problems are related to the humanization of social relations     

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how they think about themselves. The phone call system delivered daily phone messages for 27 days to those we recruited. Three treatment conditions were tested for relative value: a public health program to educate those enrolled on tips to healthy living, a program designed to boost personal mastery, and a program that invited enrollees to use mindfulness meditation. We collected outcome data from daily diaries and charted those scores across the days people were receiving the intervention and a few days later. Were we successful? Well, it depends on how you define success. Our findings (see Zautra et al., 2012) revealed that both intervention groups (personal mastery and mindfulness) showed improvements in most markers of emotional health assessed from daily diaries kept by participants during the intervention. The mindfulness group reported less depression and negative affect (ts -3.56, ps < .001) over the course of the intervention. The mastery group, likewise, reported decreases in depression and negative affect (ts -2.33, ps < .02). In contrast to the broader effects of both intervention groups, the health education group showed only one change over days in indicators of emotional health, decreases in depression (t = -3.14, p < .002). Overall, there was an edge to mindfulness due to its apparent greater beneficial influence on positive affect and improvements in physical functioning. However, the findings also revealed an important limitation: No lasting effects were observed on the follow-up measures taken after the phone calls ended. Thus, the intervention did not have sustained effects. What Was Missing? To answer this question we looked back at the midlife sample daily diaries to determine the degree to which positive social engagement played in this process. For instance, at the end of each day, participants were asked to report on the most positive event of the day (even if it was not that positive) and the extent to which that event was shared with others. As was expected, following the work by Gable, Reis, Impett, and Asher (2004) on “capitalization” and recent experimental evidence (Boothby, Clark, & Bargh, 2014), shared positive experiences events have a greater influence on positive emotions than those not shared (Arewasikporn, Zautra, & Sturgeon, 2015). We then asked whether “sharing” the positive was associated with ways of thinking we characterized as resilient. In addition to reporting on events, and effects, participants also reported on the extent to which they felt able to overcome difficulties in life, and energy to meet daily life’s challenges. A confirmatory factor analysis showed that the items held together as a single factor—a resilient state of mind. Table 10.2 shows the items for that scale and the means for the midlife sample. On days when people reported greater sharing of positive experiences, they also rated themselves as more resilient. 214       zautra et al.

TABLE 10.2 Resilient Cognitions Scale: Item Content and Descriptive Statistics Item content   1.  I could keep my mind open to new ways of looking at things.   2.  I felt I could get out of a jam if I had to.   3.  I could see ways around problems I faced today.   4.  I felt I could keep perspective.   5.  I felt able to bounce back from problems.   6.  I could understand my limitations.   7.  I felt I could stay engaged with the people I care about.   8.  I was curious about things.   9.  I was aware of my feelings. 10.  I was able to “recharge,” get a second wind.

M

SD

3.53 3.27 3.28 3.44 3.21 3.31 3.61 2.88 3.49 3.10

0.81 0.89 0.83 0.75 0.77 0.74 0.78 0.87 0.72 0.81

Note.  M = between-person mean; SD = between-person standard deviation.

People who reported more shared positive experiences across the 30 days were more likely to report resilient thinking across the month compared with those who shared less often. Next, we asked whether those with a more resilient mind-set were better off in the long run. Here we turned to follow-up assessments of health and mental health, conducted by phone, at a minimum of 6 months following the diary data collection. Those residents who reported more resilient ways of dealing with daily life had significantly higher scores on the WHO-5 WellBeing Scale (Bech, 2004) [r(151) = .46, p < .001], less anxiety [r(151) = -.32, p < .001], greater vitality [r(151) = .34, p < .001], and higher physical functioning [r(151) = .29, p < .001]. Ways of thinking resiliently mattered, and among the strongest predictors of a resilient mind-set were positive social relations. Healthy Social Relationships May Hold the Key Our interpretation of these results suggests that in prior interventions we developed to promote resilience we did not change what really matters in sustaining elevations in mood and sense of well-being. We did not change the person’s approach to their social worlds. The focus remained on the “self.” We now believe that a deeper understanding of the social nature of the human agenda is needed. In our interest to promote individual health, we neglected to look at how the quality of our relationships influences the capacity for resilient outcomes. Simply put, most of our problems are defined not by what we think about ourselves. Our greatest difficulties come when we think about ourselves to the exclusion of others. If resilience is fundamentally social, as Luthar, Crossman, and Small (2015) and we (Zautra, the humanization of social relations     

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2013) have proposed, then the humanization of social relations is the correct path to resilience. Our Initial Model These findings, informed by theoretical developments, have led us to sketch a model to guide our future efforts to examine how social relations may nourish resilient responses to stressful life experiences. In Figure 10.1, we display key components of that model. Clearly, negative social relations that begin in early childhood increase vulnerability. However, we list positive social relations as separate influences on emotional health and resilient responding, keeping with the strong evidence that positive is not simply the inverse of the negative (Reich, Zautra, & Davis, 2003). Also fundamental to this model is that how people relate to the world around them can and does change; improvements is this capacity can have a significant influence on the ways in which positive and negative social relations impact emotional wellbeing (Vaillant, 2012). We also have drawn on the nature of the relationship between positive and negative states of mind. We think that emotional complexity itself depends on depth of social understanding. These influences, in turn, nourish our capacity to be resilient. We have not drawn all the pathways by which these effects would manifest themselves. Certainly positive emotional and cognitive capacities, when strengthened, can boost resilient capacities, as many recent studies have demonstrated (e.g., Fredrickson, Cohn, Coffey, Pek, & Finkel, 2008; Langer, 2009). However, we should not only look within the self to find resilience; the willingness to reach out to

Early life adversity

Current social stresses Negative affects and cognitions

Resilient adaptations

Increasing social intelligence Positive affects and cognitions

Secure connections in early life

Current positive social experiences

Figure 10.1.  Changing the patterns of social relations to enhance resilience.

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others for help, and the willingness of others to provide support, also matters in times of crisis (Jenkinson et al., 2013). Social Intelligence (SI) Program The scientist within might object at this point; we have shown evidence of associations of social well-being and resilience and their covariation from day to day through the examination of diary data. However, we have not actually manipulated our independent variable, social relationships, to examine whether corresponding changes in well-being results. Perhaps we are simply observing how people differ from one another on a host of related variables, and not whether more thoughtful social connections actually improve people’s lives. There are many possible directions to pursue with this theme in mind. These include programs like Experience Corps (Fried et al., 2004) and community gardening (Okvat & Zautra, 2011), which broaden opportunities for meaningful social engagement. Increasing options for participation in community life creates new contexts within which people can connect with one another, but they do not teach people to evaluate and reflect on their place in the world around them. Nor do they teach the value and the how-to of engaging, forming, and sustaining healthy relationships. SI Training Prototype To address problems of social connection, social isolation, and social conflict, we developed an online training prototype for people age 13+. The program consists of 43 short 5- to 10-minute sessions designed to raise awareness of human nature and social relationships and urge small action steps (see http://www.socialintelligenceinstitute.org). Our approach is based on evidence that SI is best advanced through interventions that modify key social cognitions regarding social engagement and enhance efficacy expectations regarding performance in social situations (Masi, Chen, Hawkley, & Cacioppo, 2010). However, our approach extends beyond cognitive models and behavioral principles to include attention to evidence of barriers to social-emotional development from adverse experiences in childhood and adult life (Zautra, 2013). The program is new, and is empirically informed by the latest research evidence from fields of social and clinical psychology, cognitive, and social neuroscience. We are currently testing the impact of this prototype. SI Core Values The SI curriculum strongly endorses the core values associated with social awareness and attention to the concerns of others (e.g., Snow, 2010). the humanization of social relations     

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Fundamental to this proposition is that mutual respect, empowerment, and choice have substantial value-shaping social engagement. This core principle, which we refer to as the humanization of social relations, guides the SI intervention. Martin Buber (Horwitz & Buber, 1988) identified two distinct ways that people view those in their social worlds—I–It and I–Thou. People with the I–It perspective see the world in terms of objects and things, such that human beings (the “self” being the exception) are objects. The I–Thou worldview takes as its fundamental premise that humans are not objects; their existence takes on form and shape based on their connections with one another. The I–Thou worldview is one of social connection, mutuality, and reciprocity, and stands in stark contrast to the I–It view of separateness and detachment. Gazzaniga (2011) provided a useful summary of the social neuroscience evidence underlying Buber’s early work. He noted that a relationship between two people resides in the brains of each person. A single brain cannot capture the relationship between two people. Indeed, social neuroscience as well as philosophical discourse converge to advocate for the value of humanization (Lieberman, 2013). SI Core Principles To build this intervention, we first developed key principles that underlie socially intelligent behavior. The first principle, as introduced above, is humanization. Other people are not objects. They are humans with feelings, thoughts, hopes, and dreams. Humanization is the value orientation that has guided the first and all subsequent training prototypes. The second principle is uniqueness. Each person we encounter is different from any other. In order to connect with others we need to be willing and able to keep the perspectives of others in mind (Galinsky, Ku, & Wang, 2005; Jolliffe & Farrington, 2011; van den Bos, van Dijk, Westenberg, Rombouts, & Crone, 2011). The third principle alerts us to unconscious forces that often hold sway over our best of intentions. The mind naturally works to collect, process, and store information about the social world. It creates shortcuts to understanding by classifying and simplifying what we see. It formulates expectations for what we are about to experience and it automatizes our thoughts and routinizes our behavior toward ourselves and toward others. Thus, much of what we say, do, and think about others occurs without awareness, unconsciously (Kahneman, 2011). These processes are beneficial, but they are also potentially harmful to our aims to improve the quality of our relating. Since each person is unique, our understanding of him or her is invariably limited, shortsighted, and biased to some degree. Such biases are amplified by ingroup identification and pejorative labels when we apply to them to our outgroup (Galinsky & Moskowitz, 2000; Wang, Iannotti, & Nansel, 2009). 218       zautra et al.

The fourth principle concerns choice. Once we understand that we have choices in how to behave, that we are responsible for our actions, and that, with effort, we can change our ways of relating, then we can treat not only others with greater humanity but also ourselves (Langer, 2009). The human mind is inclined to be social, and personal projects responsive to our needs to belong are choices we can make to enrich our lives, but they require effort. In addition, our capacities are finite, and the temptations for shortterm advantage are ubiquitous (Baumeister & Leary, 1995; Brooks, 2012). Table 10.3 provides an overview of the key objectives in the SI curriculum built from these principles. Does SI Training Work? The most comprehensive evaluation of the program to date was conducted in a large-scale study of college students in Madrid, Spain (Zautra, TABLE 10.3 Key Social Intelligence Program Objectives: Awareness and Action Awareness components

Action components

I.  Social Connection

Understanding fundamental human needs for social connection Seeing emotion as information about self and others’ needs Seeing the value of understanding another for its own sake

II.  Social Isolation

Understanding social pain: disconnection from family and friends, loss of loved one, and social rejection Understanding both the hermit and the outcast

III.  Social Conflict

Understanding what underlies conflict: including perceptions of unfairness, distrust, and social sensitivity Identifying individual differences in conflictresolution styles

High and low roads of response: Learning when to trust intuition and when to question Finding an ally to prevent contagious spread of emotions Being responsive to the meaningful stories others tell about their lives Showing empathy: learning to listen Learning flexibility and acceptance in response to different social styles Leading by example by demonstrating “reciprocity”: the two-way street in human relations Engagement in humanizing others through perspective taking Interruption of one’s own cultural stereotypes, false assumptions, and harsh judgments Identification of one’s own best method of resolving conflict

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Zautra, Gallardo, & Velasco, 2015). Students in medical school, physiotherapy, and teachers training programs participated: 227 men and women, ages 18 to 22, provided complete pre- and postdata. Two members of the SI team guided students through the online material and led periodic class discussions to enhance program effects and encourage their students to engage in the experiential exercises contained within the program. Eightyseven students taking similar classes in subsequent semesters at the same university served as controls. The results, which were based on repeated analyses of variance of preand postscores for students taking the course versus controls, revealed significant increases in social well-being, including sensitivity to others’ emotions on the revised Snyder Self-Monitoring Scale (Lennox & Wolfe, 1984), higher scores on the perspective-taking subscale of Davis’s (1983) Empathy Scale, and higher scores on the social information subscales of the Tromsø Social Intelligence Scale (Silvera, Martinussen, & Dahl, 2001) with all Fs (1,311) > 7.66, ps < .01. We also examined the influence of preexisting individual differences on emotional intelligence (Salovey & Mayer, 1990). While it was possible that some initial capacity to identify and regulate one’s emotions would be needed to learn to be more socially intelligence, we found no evidence of limitations in program effectiveness due to emotional skills. Next Steps: Midlife Reversibility of Early Biobehavioral Risk Factors Initial evaluation of the SI training appears to be effective for college students. But would it work for people in midlife? In 2013, the National Institute on Aging issued a request for applications that proposed to explore the potential for midlife plasticity of biobehavioral or psychological systems affected by early life disadvantage (Division of Behavioral and Social Research, National Institute on Aging, 2013). Our application for funding to test the SI training program on the midlife sample has now been approved for funding. The goal of this project is to test whether the SI training program can improve social relationship quality for our community sample of people in midlife. A particular focus of the project is on those individuals who experienced early life adversity in the form of emotional, physical, and/or sexual abuse. Half of the 220 participants to be recruited for the study will have indicated on the childhood trauma questionnaire that they experienced high levels of abuse as children. Figure 10.2 illustrates the design of the SI training program aimed at improving social relationship quality, as well as the mental and physical health of people in midlife, with an emphasis on people who experienced early life adversity. The project involves collecting data at pre- and posttest and 3- and 6-month follow-up intervals and a 50-day daily diary during the course of the intervention to assess changes in social relationship enjoyment, stressfulness, as 220       zautra et al.

Personality, genetic risk, gender

Personality, genetic risk, gender

Social intelligence intervention Aim 1 Social relationships

Social relationships

Aim 3

Social relationships

Social relationships

Aim 1

Early life adversity

Childhood

50-day daily diary Day-to-day well-being and stressor reactivity

Aim 2

Mental and physical health

Mental and physical health

Mental and physical health

Mental and physical health

Midlife

Pretest

Posttest

3- and 6-month follow-up

Figure 10.2.  Conceptual model linking early life adversity to mental and physical health: The role of a social intelligence intervention in shaping these outcomes.

well as emotional reactivity to daily negative and positive events. The project is multifaceted in that we will gather data through self-reports of social relationships, mental and physical health, and well-being, but also collect saliva samples to be analyzed for pertinent biomarkers. Further, informant reports will be collected on a subset of the control and interventions groups, and qualitative interviews will be conducted on a subset to further examine possible changes in cognitive shift and how individuals relate with others in social relationships. In sum, the goal of the project is to improve social relationship quality, emotional well-being, and resilience capacity through SI training, especially in persons who experienced adversity in early life. We hope to find that even those harmed by abusive relations in childhood will be responsive to the training program, manifesting the plasticity needed to change the course of their lives in ways that enhance their resilience to social stressors and reduce their vulnerability to ill health as they age. CONCLUSION Recent trends in the scientific literature suggest that attention to social well-being is particularly important in our society and that positive social connections are essential to individual well-being. Unfortunately, there are signs that our culture is drifting away from social concern. For instance, there the humanization of social relations     

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is strong evidence of a decline in empathetic concern for others among the young (Konrath, O’Brien, & Hsing, 2011). Neglect of social needs has been manifest not only in passive forms like greater social isolation (Putnam, 2000), but evidence for emotional abuse and other active displays of inhumanity between caregivers and those older adults they are caring for is also mounting in the social science literature (e.g., Cooper, Selwood, & Livingston, 2008). Even life-care facilities with a reputation for providing person-centered care have been found to exhibit considerable dehumanizing treatment of older people in their care (Doyle & Rubinstein, 2014). We offer one possible antidote to these social ills: interventions that humanize our social relations. The humanization of social relations requires us to adopt a framework for relating to one another in which we change from a self-centered organism to a social being, able and willing to form and sustain meaningful social relationships. The adoption of this framework in theory could benefit all those exposed. We hope that our SI programs and others like ours can help reverse the trends toward inhumanity in how people care for one another as they age. As Wright (1999) put it, strong social relations are not zero sum games of costs and benefits that individuals play with one another. Rather, the social, psychological, and physical health of both parties advances when they treat one another with humanity.

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Index Active coping, 41 Actual affect, 126 Adolescence, negative affect in, 109 Affect. See also Negative affect; Positive affect and cortisol, 193 defining, 120 Affective environment (AE), 40–41 Affective experiences, 193–194 Affective phenomena, 120 Affective space, 212 Affect regulation, 98–99. See also Emotion regulation Affect-regulation motivations, 97–113 age-related differences in MMAA project, 100–102 future research on, 109–111 instrumental perspective on, 102–106 mixed-affect perspective on, 106–109 Affect valence, 108–109 Affect valuation theory, 119–137 actual affect in, 126 and cultural ideals of healthy aging, 130–134 effects of age in, 129–130 future research on, 136–137 ideal affect in, 126–129 and personal expectations of old age, 135–136 universal vs. culture-specific hypotheses for, 121–126 and well-being, 134–135 Age connectivity increased with, 19–21 effects of, in affect valuation theory, 129–130 as factor vs. covariate, 196 and mood disorders, 10 and negative affect, 193–194 personal expectations of old, 135–136 positive and negative effects of, 9–10 and positivity effect, 11–13

Age-related differences in cognitive reappraisal, 60–64 in instrumental perspective, 104–106 in mixed-affect perspective, 107–109 in MMAA project, 100–102 Age-related positivity effect, 188 See also Positivity effect Aging cultural ideals of healthy, 130–134 defining, 121 emotional, 119 and emotion regulation strategies, 34–36 healthy, 130–134 and regulatory flexibility, 83–85 successful, 165–166 theoretical frameworks of, 33–36 unsuccessful, 195 Allard, E. S., 63–64 Alzheimer’s disease, 186 Amygdala connectivity of, and depression, 17–18 connectivity of, with networks, 15–16 regulation of, by networks, 19 Anand, A., 17–18 Andrade, E. B., 107 Andreotti, C., 57 Anxiety, 195 Appraisal, 192–193. See also Reappraisal Arousal, 120–121 Asher, E. R., 214 Attention, positivity effects in, 33–34 Attentional deployment and emotion regulation, 38–40 as emotion regulation strategy, 35, 37, 53 Avoidant strategies, 188, 191, 192 Avoided affect, 136–137 Bandura, A., 148–149 Behavior choice in, 219 deteriorative vs. restorative, 167–170

229

Behavior, continued effect of personality and emotional reactivity on, 149–150 influenced by ideal affect, 128–129 and mortality risk, 156 socially intelligent, 208 Behavior Rating Inventor of Executive Function, 57 Bereavement, 76 Big Five personality traits, 155 Biobehavioral risk factors, 220–221 Biological processes, 167–170 Bipolar disorder, 74 Blanchard-Fields, F., 34, 43, 84 Block, J., 208 Blood oxygenation level dependent (BOLD) signal, 54–55, 59–61 Blood pressure, 170 Bogg, T., 152 Bonanno, G. A., 76, 78 Bronfenbrenner, Urie, 3–4 Brown, W. J., 175 Buber, M., 218 Buhle, J. T., 54 Burton, N. W., 175 Cabeza, R., 59, 60 Cardiovascular disease (CVD) associated with positive psychological well-being, 164–165 and childhood well-being, 172–173 and favorable cardiovascular health, 166–167 and positive affect, 172 Cardiovascular health and optimism, 172 and positive psychological well-being, 170 Caregiving role, as stressor, 195 Carstensen, L. L., 121 Categorical variability, in repertoire, 76–79 Chapman, B., 155, 156 Cheng, C., 75, 79 Childhood trauma in, and social relations, 210–212 well-being in, 172–173 Chinese context of aging, 130–134 for ideal affective states, 127–128

230       index

Choice, in behavior, 219 Clarkin, J., 155 Cognitive change as emotion regulation strategy, 35, 53 and intensity of situations, 55–56 research on, 42, 54 Cognitive control, 83 Cognitive function decline in, 190 and depression, 186–187 and physical fitness, 195 Cognitive reappraisal, 51–66 age differences in, 60–64 and emotion, 52–55 future research on, 65–66 networks active in, 15–16 resources for, 56–60 strategy selection vs. effectiveness, 55–56 Cognitive resource(s) and executive control, 56–57 memory as, 58–60 perceptual reasoning as, 59–60 processing speed as, 59–60 Cohen, J. B., 107 Collectivism, 127–128 Complicated grief, 74, 79 Connectivity, increased with age, 19–21 Conscientiousness, 156 Context insensitivity, 74, 83–84 Context sensitivity, 73–75, 80 Contrahedonic emotion regulation goals instrumental perspective on, 102–105 long-term adaptiveness of, 110 in MMAA project, 101 prohedonic vs., 99 shifting, with age, 33 Coping active, 41 forward focused, 77 loss-oriented, 76 problem-focused, 41 and regulation flexibility, 74–75 restoration-oriented, 76 and situation modification, 41 trauma focused, 77 Corby, E., 57 Corticolimbic functional connectivity, 19–20

Cortisol and affect, 193 C-reactive protein (CRP), 169 Cultural ideals, of healthy aging, 130–134 Culture defining, 121 ideal affect shaped by, 126–128 Culture-specific hypothesis, 121–126 CVD. See Cardiovascular disease Daily Inventory of Stressful Events (DISE), 153 Davison, L., 54 Default mode network (DMN), 9–22 connectivity increased with age in, 19–21 functional connectivity in, 13–19 and positivity effect, 11–13 Demaree, H. A., 58 Dennis, N. A., 60 Depression and cognitive function, 186–187 and functional connectivity, 17–18 and intranetwork connectivity, 21 and social relations, 213–217 and unsuccessful aging, 195 Detached reappraisal, 42, 61–62 Deteriorative processes, 167–169 Differential exposure model, 31–32 Differential reactivity model, 31–32 DISE (Daily Inventory of Stressful Events), 153 Disease, vs. physical health, 165–167 Distraction, as emotion regulation strategy, 61 DMN. See Default mode network Doherty, H. K., 152 Duckworth, A. L., 156 Dynamic integration theory, 84, 189 Ego Resilience Scale, 208 Eisenberg, N., 156 Emotion and cognitive reappraisal, 52–55 as context bond, 73–74 defining, 120 moods vs., 98 Emotional aging, 119

Emotional reactivity as predictors of mortality, 148–151 short-range change in, 153–154 Emotional well-being, 186–187. See also Positive psychological well-being Emotion regulation, 31–45 and attentional deployment, 38–40 future research on, 43–45 goals for. See Contrahedonic emotion regulation goals; Prohedonic emotion regulation goals and physical fitness, 195 positivity effects and process model for, 36–38 research on, 40–43 theoretical frameworks of aging and, 33–36 Emotion Regulation Questionnaire (ERQ), 57 Emotion regulation strategies. See also specific strategies and aging, 34–36 importance of differentiating among, 36 selection vs. effectiveness, 55–56 use v. success of, 32 Engle, R. W., 56–57 EPI (Eysenck Personality Inventory)–Q, 152 ERQ (Emotion Regulation Questionnaire), 57 Executive control and attentional deployment, 39–40 and cognitive resources, 56–57 Executive network decreased connectivity of, 21 functional connectivity of, 13–15, 17 Exercise. See Physical exercise Expressive regulatory repertoire, 78–79 Expressive suppression strategy, 42 Extraversion, 128 Eysenck Personality Inventory (EPI), 152 Favorable cardiovascular health (FCH), 166–167 Feedback and aging, 88 internal, 81–82 social, 82, 85 index     

231

Feedback responsiveness, 80–82 Feuerstein, R., 62 Financial difficulties, 212–213 Fluid cognitive ability, 59–60, 83 Ford, B. Q., 103 Forward focused coping, 77 Functional connectivity, 13–19 Functional health, 209 Fung, H., 132 Füstös, J., 82 Gable, S. L., 214 Gazzaniga, M., 218 Gintner, G. G., 79 Glucocorticoid cascade hypothesis, 189 Gotlib, I. H., 57, 74 Gratitude interventions, 174 Griffin, P. W., 149 Gross, J. J., 35–36, 56, 58, 59, 74 Haga, S. M., 57 Hampson, S. E., 155 Hannan, S. M., 76 HAP. See High arousal positive states Hardt, J., 212 HDL–C (high-density lipoprotein cholesterol), 168 Health. See specific types Health behavior model, 149–150 Health outcomes, improving, 175 Healthy aging, 130–134 “Healthy lifestyle” index, 169 High arousal positive states (HAP) cultural ideals of, 127, 132–135 defining, 120–121 and extraversion/neuroticism, 128 and ideal affect, 128–129 low vs., 111 and personal expectations of old age, 135–136 throughout lifespan, 130 High-density lipoprotein cholesterol (HDL–C), 168 Hollenstein, T., 77–78 Holt-Lunstad, J., 208 Huettel, S. A., 59 Humanization, of social relations, 215–217

232       index

Ideal affect behavior influenced by, 128–129 research on, 111 shaped by culture, 126–128 I–It perspective, 218 IL-6 (interleukin-6), 150, 210 Impett, E. A., 214 Implementation-maintenance model, of reappraisal, 81 Individualism, 127–128 Inhibitory control, 58–59, 63 Instrumental perspective, 102–106 Intensity of situations, 55–56 Interleukin-6 (IL-6), 150, 210 Internal feedback, 81–82 Internetwork connectivity, 17 Interpersonal stressors, 191 Interventions to enhance positive psychological well-being, 174–175 personality, 152, 155, 156 Intranetwork connectivity in default mode network, 16 and emotion regulation outcomes, 21 Isaacowitz, D. M., 34, 43 I–Thou perspective, 218 Jacobs, S. E., 58 John, O. P., 58 Jokela, M., 156 Joormann, J., 57 Kalisch, R., 81 Kane, M. J., 56–57 Kasch, K. L., 74 Kato, T., 82 Kensinger, E. A., 63–64 Kraft, P., 57 Kremen, A. M., 208 Labar, K. S., 59 Labouvie-Vief, G., 84 LAP. See Low arousal positive states Layton, J. B., 208 Lazarus, R. S., 54 Lee, I. A., 59 Levenson, R. W., 42, 61 “Lifespan dynamics” model, 155

Löckenhoff, C. E., 132 Long-range change, in personality, 151–152 Loss-oriented coping strategies, 76 Loughheed, J. P., 77–78 Loving-kindness meditation, 174 Low arousal positive states (LAP) cultural ideals of, 127, 132–135 defining, 120–121 and extraversion/neuroticism, 128 high vs., 111 and ideal affect, 128–129 and personal expectations of old age, 135–136 throughout lifespan, 130 Madden, D. J., 59 Major depressive order (MDD), 17–18, 74 Marshbanks, M. R., 152 McRae, K., 58 Medial brain regions, 10 Medial prefrontal cortical regions (MPFC) activated by positive and negative stimuli, 13 and amygdala, 15–16 Meditation, 174 Memory as cognitive resource, 58–60 and contrahedonic affect-regulation motivation, 105 positivity effects in, 33–34 Mende-Siedlecki, P., 62 Mental health, 209 Metabolic syndrome, 193 Middle adulthood, 44 Midlife in the United States (MIDUS), 150, 209 Midlife resilience, 209–212 Mindfulness default mode network connectivity increased with, 18–19 emotional reactivity decreased with, 149 intranetwork connectivity increased with, 21 and reappraisal strategies, 20 Miron, L. R., 76

Mixed-affect perspective, 106–109 MMAA (Multi-Method Ambulatory Assessment) project, 99–109 Mood, vs. emotion, 98 Mood disorders, 10 Mordkoff, A., 54 Mortality, predictors of, 148–151 Motivation-behavior gap, 110 MPFC. See Medial prefrontal cortical regions Mroczek, D. K., 148, 149, 151–153 Multi-Method Ambulatory Assessment (MMAA) project, 99–109 National Institute on Aging, 213 Negative affect and cortisol, 193 decreased with age, 193–194 decreased with social support, 191–192 and emotional reactivity, 153–154 Negative stimuli and emotion regulation, 12 willingness to engage with, 44 Networks, interconnectivity of, 17. See also specific networks Neupert, S. D., 149 Neuroimaging studies, 54–55 Neuroticism and actual affect, 128 affect-regulation research on, 155–156 changes in, over lifespan, 150–152 and emotional reactivity, 149 North American context of aging, 130–134 for ideal affective states, 127–128 Ochsner, K. N., 62 Old age, personal expectations of, 135–136 Ong, A., 212 Optimism and cardiovascular health, 172 interventions fostering, 174 and positive psychological well-being, 171 protective effects of, 164 and sleep, 171

index     

233

Optiz, P. C., 59, 62, 63 Orcutt, H. K., 76 PACT (Perceived Ability to Cope With Trauma) scale, 76–77 Pakenham, K. I., 175 PANAS (Positive and Negative Affect Schedule), 153 Passive regulation strategies, 191 PCS (Physical Component Score), 210 Perceived Ability to Coping with Trauma Scale (PACT), 76–77 Perceptual reasoning, as cognitive resource, 59–60 Perseverative cognition, 193 Personal expectations, of old age, 135–136 Personality, 147–157 long-range change in, 151–152 as predictor of mortality, 148–151 research on, 154–157 and short-range change in emotional reactivity, 153–154 Personality interventions, 152, 155, 156 Physical Component Score (PCS), 210 Physical exercise and emotion regulation, 195 positive psychological well-being increased with, 171 as restorative process, 168–169 Physical fitness, 195 Physical health, 185–198 and appraisals, 192–193 assessment of, 171–172 concepts of, 165–171 defining, 165 of disadvantaged and advantaged groups, 194–195 disease vs., 165–167 and emotional well-being, 186–187 future research on, 195–197 and positive affect, 105–106 and resilience, 209 in selective optimization and compensation with emotion regulation model, 189–190 and social support, 191–192 in socioemotional selectivity theory, 187–188 in strength and vulnerability integration theory, 188–189

234       index

and temporal dynamics of affective experiences, 193–194 Physiological model of personality and health, 149–150 Plasticity, of brain, 213 Positive affect and cardiovascular disease, 172 and cortisol, 193 and emotional reactivity, 153, 154 increasing throughout adult development, 109 and physical health, 105–106 Positive and Negative Affect Schedule (PANAS), 153 Positive emotions, 170 Positive gaze preference, 38–40 Positive psychological well-being (PPWB), 163–176 and assessment of health, 171–172 concepts of health and, 165–171 defining, 164 and development, 172–173 modification of, 173–175 Positive reappraisal, 42, 61–62 Positivity effect and age, 11–13 age-related, 188 in memory and attention, 33–34 and process model for emotion regulation, 36–38 PPWB. See Positive psychological well-being Private self-consciousness, 57 Problem-focused coping, 41 Processing speed, as cognitive resource, 59–60 Process model as emotion regulation strategy, 34–35 and positivity effects for emotion regulation, 36–38 Prohedonic emotion regulation goals contrahedonic vs., 99 instrumental perspective on, 102–103, 105–106 long-term adaptiveness of, 110 in MMAA project, 101 shifting, with age, 33 Rauch, L. C., 62 Ray, R. D., 58

Reappraisal cognitive. See Cognitive reappraisal detached, 42, 61–62 as emotion regulation strategy, 37 implementation-maintenance model of, 81 mindfulness and strategies for, 20 positive, 42, 61–62 research on, 42 Regulatory flexibility, 71–86 and aging, 83–85 components of, 72–73 through context sensitivity, 73–75 through feedback responsiveness, 80–82 through repertoire, 75–80 Reis, H. T., 214 Repertoire and aging, 84 categorical variability in, 76–79 expressive regulatory, 78–79 regulatory flexibility through, 75–80 size of, 76 temporal variability in, 79–80 Resilience, 176 Resilient adaptation, 207–208 Resources cognitive. See Cognitive resource(s) for cognitive reappraisal, 56–60 and contrahedonic affectregulation motivation, 105 for emotion regulation, 43–44, 65–66 Response modulation as emotion regulation strategy, 35, 37, 53 research on, 42–43 Responses to Stress Questionnaire (RSQ), 57 Restoration-oriented coping strategies, 76 Restorative processes, 167–170 Rottenberg, J., 74 Rozin, P., 126 RSQ (Responses to Stress Questionnaire), 57 Rumination, 17–18 Rutter, M., 212

Sadness, throughout life span, 111 Salience network decreased connectivity of, 21 functional connectivity of, 13–15, 17 Salthouse, T. A., 60 SAVI model. See Strength and vulnerability integration model Scheibe, S., 61, 130, 132 Schmeichel, B. J., 58 Schut, H., 77 Selection, optimization, and compensation in emotion regulation (SOC–ER) model compensation with alternative strategies in, 85 and physical health, 189–190 and strategy use vs. effectiveness, 35–36, 65 Self-reflection, 20–21 Self-regulation, 149 Self-related processing and default mode network, 15 increased connectivity with, 20–21 Self-relevant information, 12–13 Self-report measures, 53–54 Serum antioxidants, 168 Sheppes, G., 55–56, 61 Shiota, M. N., 42, 61 Short-range change, in emotional reactivity, 153–154 Shweder, R., 126 SI (Social Intelligence) Project, 217–220 Situation modification as emotion regulation strategy, 34–35, 37, 53 research on, 41 Situation selection as emotion regulation strategy, 34–35, 37, 53 research on, 40–41 Sleep and optimism, 171 as restorative process, 169 Smith, T. B., 208 SOC–ER model. See Selection, optimization, and compensation in emotion regulation (SOC–ER) model Social conflict and age, 104 in Social Intelligence Program, 219 index     

235

Social connection, 219 Social feedback, 82, 85 Social Intelligence (SI) Program, 217–220 Social interaction model, 82 Social isolation, 219 Socially intelligent behavior, 208 Social relations, 207–222 benefits of, 208 current research on, 209–212 and depressive profiles, 213–217 and financial difficulties, 212–213 reversing early biobehavioral risk factors with, 220–221 and Social Intelligence Program, 217–220 Social support, 191–192 Socioemotional selectivity theory (SST) emotion regulation goals in, 84, 100 goals and strategy selection in, 37–38 and physical health, 187–188 and positive psychological wellbeing, 173 and positivity effect, 12, 36–38 shifting emotion regulation goals in, 33–34 universal hypothesis in, 121 Speisman, J. C., 54 Spinrad, T. L., 156 Spiro, A., III, 148, 149, 151, 152 SST. See Socioemotional selectivity theory Staudinger, U. M., 61 Stern, Y., 62 Strength and vulnerability integration (SAVI) model and emotion regulation strategy selection, 35 and physical health, 188–189 Stress hormones, 149 Stressors in aging theories, 193 associated with unsuccessful aging, 195 caregiving role as, 195 and emotional reactivity, 153, 154 interpersonal, 191 rate of experiencing, and age, 194 response to, and health, 148–149 tolerance for, and age, 189

236       index

Stroebe, M., 77 Successful aging, 165–166 Tabibnia, G., 58 Tamir, M., 103 Tang, D., 58 Temporal dynamics, of affective experiences, 193–194 Temporal variability, in repertoire, 79–80 Terry, D. P., 62 Training prototype, for Social Intelligence Program, 217 Trait conscientiousness, 156 Trauma-focused coping, 77 Tucker, A. M., 62 Unconsciousness, and social relations, 218 Universal hypothesis, 121–126 Unsuccessful aging, 195 Urry, H. L., 35–36, 56, 59, 62 Valence, 120 Valiente, C., 156 Veterans Affairs Normative Aging Study (VA NAS), 150 Volokhov, R. N., 58 WAIS–IV (Wechsler Adult Intelligence Scale—Fourth Edition), 57, 59 Watson, T. L., 84 Webb, T. L., 53, 54 Wechsler Adult Intelligence Scale— Fourth Edition (WAIS–IV), 57, 59 Well-being. See also Positive psychological well-being in childhood, 172–173 and cultural ideals of aging, 134–135 emotional, 186–187 West, J. D., 79 Westphal, M., 79 Winecoff, A., 59, 63 World Health Organization (WHO), 165 Wright, R., 222 Zarski, J. J., 79

About the Editors

Anthony D. Ong, PhD, is an associate professor of human development at Cornell University. He received his PhD from the University of Southern California. His research broadly focuses on individual differences in developmental plasticity or the capacity of individuals to flexibly adapt to changing life circumstances with age. A major focus of his recent work involves expanding basic understanding of the behavioral and biological pathways by which positive emotions, interpersonal relationships, and cultural experience contribute to diverse health outcomes in later adulthood. His research has been supported by the National Institute of Aging. Corinna E. Löckenhoff, PhD, is an associate professor of human development at Cornell University. She received her undergraduate degree from the University of Marburg, Germany, and her PhD from Stanford University. Her National Institutes of Health–funded research examines age differences in personality and emotions and their influence on health-related decisions, behaviors, and outcomes. A central goal is to optimize health care choices across the lifespan. Another line of her research examines lifelong trajectories in personality traits and their relation to mental and physical health.

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