Handbook of Gerontology Research Methods: Understanding successful aging 9781138779037, 9781138779068, 9781315771533

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HANDBOOK OF GERONTOLOGY RESEARCH METHODS

The Handbook of Gerontology Research Methods offers a clear understanding of the most important research challenges and issues in the burgeoning field of the psychology of aging. As people in developed countries live longer, so a range of research methods has evolved that allows a more nuanced understanding of how we develop psychologically and neurologically. Allied to this is an increasing concern with the idea of well-being, a concept that places cognitive performance and development within a more socially grounded context. With contributions from a range of top international scholars, the book addresses both typical and atypical aging, highlighting key areas such as physical and cognitive exercise, nutrition, stress, diabetes and issues related to death, dying and bereavement. Successful aging is emphasised throughout the text. Each chapter concludes with a series of practical tips on how to undertake successful research in this area. This unique collection is the first book to provide both a concise overview of the major themes, findings and current controversies in this growing field, as well as an understanding of the practical issues when researching older adults that may impact on research outcomes, intervention, policy and future directions. Designed for both students and researchers interested in the psychology of aging, but also highly relevant for students or researchers in related fields such as health psychology and social care, the Handbook of Gerontology Research Methods is essential reading for anyone wishing to understand more about the psychology of aging. Dr Leigh Riby is Associate Professor of Neuropsychology at Northumbria University, United Kingdom.

Research Methods in Developmental Psychology A Handbook Series

Research Methods in Developmental Psychology is a series of edited books focusing upon research challenges for conducting research in developmental psychology. Ideally suited to both students coming to this area for the first time and more experienced researchers each volume provides an invaluable overview of research in this growing field, and how it can inform both education and interventions. Volumes include research challenges in neurodevelopmental disorders, child development and gerontology. Published titles: Neurodevelopmental Disorders: Research Challenges and Solutions Edited by Jo Van Herwegen and Deborah Riby Practical Research with Children Edited by Jess Prior, Jo Van Herwegen

HANDBOOK OF GERONTOLOGY RESEARCH METHODS Understanding successful aging

Edited by Leigh Riby

First published 2017 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 711 Third Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2017 selection and editorial matter, Leigh Riby; individual chapters, the contributors The right of the editor to be identified as the author of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Riby, Leigh, editor. Title: Handbook of gerontology research methods : understanding successful ageing / edited by Leigh Riby. Description: Abingdon, Oxon ; New York, NY : Routledge, 2017. Identifiers: LCCN 2016011099 (print) | LCCN 2016017407 (ebook) | ISBN 9781138779037 (hardback : alk. paper) | ISBN 9781138779068 (pbk. : alk. paper) | ISBN 9781315771533 (Ebook) Subjects: LCSH: Gerontology—Research—Methodology. | Aging— Research—Methodology. Classification: LCC HQ1061 .H33534 2017 (print) | LCC HQ1061 (ebook) | DDC 305.260072/1—dc23 LC record available at https://lccn.loc.gov/2016011099 ISBN: 978-1-138-77903-7 (hbk) ISBN: 978-1-138-77906-8 (pbk) ISBN: 978-1-315-77153-3 (ebk) Typeset in Bembo by Apex CoVantage, LLC

CONTENTS

Acknowledgements Editor contact details Biographical profile of editor Biographical profile of contributors

viii ix x xi

SECTION I

Introduction 1 Understanding successful ageing, key challenges and research methods Riby, Leigh, Greer, Joanna, Martinon, Léa M. and Reay, Jonathon L.

1

3

SECTION II

Lifestyle factors and psychological functioning

15

2 Physical and cognitive exercise in ageing Rabipour, Sheida, Miller, Delyana, Taler,Vanessa, Messier, Claude and Davidson, Patrick

17

3 Nutrition, health and the ageing process Peters, Riccarda, White, David and Scholey, Andrew

43

4 Stress, coping and resilience in an ageing population Phillips, Anna C. and Vitlic, Ana

60

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Contents

5 The dual continua model of mental health and illness: theory, findings, and applications in psychogerontology Westerhof, Gerben

79

6 Successful ageing in the workplace: a resources-oriented intervention perspective Stamov Roßnagel, Christian and Jeske, Debora

95

7 Ageing and retirement behaviour Shultz, Kenneth and Fisher, Gwenith

118

SECTION III

Less successful ageing

137

8 The frontal ageing hypothesis: evidence from normal ageing and dementia MacPherson, Sarah and Cox, Simon

139

9 Examining cognitive function in type 2 diabetes: the importance of an inclusive research approach Jones, Nicola, Greer, Joanna, Riby, Leigh and Smith, Michael

159

10 Alzheimer’s disease: interaction of lifestyle factors and traumatic head injury Scholes-Balog, Kirsty, Albrecht, Matthew and Foster, Jonathan

180

SECTION IV

Novel interventions for dementia

203

11 The effect of music therapy for people with dementia Vink, Annemieke and van Bruggen-Rufi, Monique

205

12 Poetry as a means of (re)creating satisfying levels of personhood and social integration for people diagnosed with dementia: method, discussion and outcomes Petrescu, Ioana

223

Contents

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SECTION V

End of life

233

13 Death, dying and bereavement in old age: working towards a ‘good death’ for elderly individuals Wylie, Belinda and Smith, Michael

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Index

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ACKNOWLEDGEMENTS

To my Gran Margaret (1923–2015) the perfect example of successful ageing. Thank you to my parents and daughters Jessica and Amelia Riby.

EDITOR CONTACT DETAILS

Leigh Riby, PhD Associate Professor Neuropsychology, Department of Psychology, Northumbria University, Northumberland Building, Newcastle-upon-Tyne, UK. Email: [email protected]

BIOGRAPHICAL PROFILE OF EDITOR

Leigh Riby earned a BSc (Hons) in Psychology from the University of Lincolnshire.

He achieved a PhD in Experimental Psychology in the area of cognitive ageing and frontal lobe deficits at the Department of Experimental Psychology, Bristol University. During post-doctoral work at the University of Stirling Dr. Riby gained expertise in multi-modal brain imaging (EEG and fMRI). More recently, Dr. Riby has published a catalogue of research papers on the topic of glycaemic modulation of cognitive processes, memory and mind wandering using behavioural and neuroimaging techniques in younger adults, older adults and patient groups. Dr. Riby is currently an Associate Professor Neuropsychology at Northumbria with teaching interests in ageing, neuropsychology and the creative mind.

BIOGRAPHICAL PROFILE OF CONTRIBUTORS

Matthew Albrecht holds a PhD in Pharmacology from the University of Western Australia. He is currently an Australian National Health and Medical Research Council Early Career Research Fellow situated at the Maryland Psychiatric Research Center, University of Maryland and at the School of Public Health at Curtin University. His is currently working on electrophysiological markers of reward processing in schizophrenia and translational animal models of psychosis. Simon Cox carried out his PhD at the University of Edinburgh (UK), examining

relationships between cortisol, brain structure and cognitive ability in older age. He is currently an MRC-funded Research Associate in Brain Imaging and Cognitive Ageing at the Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh (UK). His interests include the potential determinants of structural brain changes in older age and their cognitive correlates, which he investigates primarily in the Lothian Birth Cohort 1936. Patrick Davidson (PhD) is an Associate Professor in the School of Psychology at the University of Ottawa, where he is also a Scientist at the Bruyère Research Institute and an Associate Member of the Brain-Mind Research Institute and the Canadian Partnership for Stroke Recovery. He works on the cognitive neuroscience of human memory, executive functions and emotion, including in normal aging and in brain injuries, disorders and diseases. Gwenith Fisher earned her PhD in Industrial/Organizational Psychology from

Bowling Green State University. She is currently Assistant Professor of Industrial/ Organizational Psychology and Director of Training in Occupational Health Psychology at Colorado State University. Her research examines occupational

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health, retirement and well-being among older workers and work/life issues. Prior to joining the faculty at CSU, Gwen spent twelve years working at the Institute for Social Research (ISR) Survey Research Center at the University of Michigan. Jonathan Foster holds a doctorate in behavioural neuroscience from the University

of Oxford, subsequent to which he completed clinical and experimental training in neuropsychology at the Roman Institute in Toronto. He has been awarded university chairs in the United Kingdom and Australia. He is currently a Consultant Neuropsychologist (Health Department of Western Australia and Private Practice) and a Clinical Professor at Curtin University and the University of Western Australia. His research focuses on the neurological basis of cognition, including lifespan developmental perspectives. Joanna Greer is a Senior Research Assistant at Northumbria University (UK)

working on a diverse range of projects including behavioural and neuropsychological processing in healthy children and adults, and clinical research studying cognitive and linguistic deficits in aphasic stroke patients. She is currently in the final year of her PhD, investigating executive dysfunction in older adults with Williams syndrome. Debora Jeske holds a PhD in Industrial-Organizational Psychology from Northern

Illinois University (USA). She is a lecturer in Human Resource Management in the Business School at Edinburgh Napier University (UK). Her research interests include studying different approaches of training and development, virtual working and the use of social media for personal and work purposes. Nicola Jones is Lecturer at Liverpool Hope University. She completed her PhD at Northumbria University investigating the impact of glucoregulatory efficiency on neurocognitive mechanisms in older adults. She currently works as a post-doctoral fellow at Liverpool Hope University. Her research interests include investigating the impact of glucoregulation on memory processing and how these processes are represented behaviourally and at a neural level in both typical and atypical populations. Sarah MacPherson’s PhD work was the first to propose the dorsolateral prefrontal

theory of cognitive aging. Since then her research interests have focused on cognitive and neuropsychological investigations of memory, executive abilities and social functioning in healthy and pathological ageing and damaged brains. She is currently a Senior Lecturer in Human Cognitive Neuroscience at University of Edinburgh (UK). Léa M. Martinon holds a Masters in cognitive psychology from Université de

Bourgogne. She is currently doing her PhD in the Faculty of Health and Life Sciences in Northumbria University in Newcastle-upon-Tyne. Her research focuses on aging and ubiquitous phenomenon like mind-wandering.

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Claude Messier, during his Masters and PhD thesis at McGill University, discovered

that ingestion or injection of glucose could improve memory. He went on to study the effect in humans and discovered that the effect was more prominent in people with impaired glucose tolerance. In 1996, he wrote a review that explained why and how diabetes would be a risk factor for Alzheimer’s disease and proposed several of the hypotheses that have proven useful. Claude Messier also discovered that the expression of the main blood to brain glucose transporter (GLUT1) increases when neurons are being activated by new learning. Delyana Miller obtained her PhD in Clinical Psychology from the University of Ottawa, where she researched the cognitive factors that predict successful interaction/ communication with interactive voice response technology in older adults. She also completed a methodological review of the literature that measures the impact of physical exercise on cognitive aging. Dr. Miller completed her doctoral residency in clinical neuropsychology at the Ottawa Hospital and her research evaluated the effectiveness of computer-based cognitive neurorehabilitation interventions in adults. She is currently working at her private practice and in the Children’s Hospital of Eastern Ontario as a clinical psychologist and neuropsychologist. Her research interests include cognitive function and interventions geared towards preserving cognitive function later in life. Riccarda Peters holds a MSc in Behavioural and Cognitive Neurosciences from the

University of Groningen, the Netherlands. She is currently enrolled as a PhD candidate at Swinburne University, Australia, in the Centre for Human Psychopharmacology, where she is exploring brain changes associated with advancing age and nutritional interventions. Ioana Petrescu is a widely published academic and poet, who teaches Creative Writing at the University of South Australia. She is the author of three poetry collections, more than a hundred poems published in literary and academic journals, editor of many books of poetry, and has successfully supervised Honours, Masters and PhD theses in Creative Writing. Her interest in the effects of poetry on Alzheimer’s sufferers began in the family and over time expanded into her research and community engagement. Anna C. Phillips is an internationally renowned researcher and Health Psychologist working in Psychoneuroimmunology and Psychophysiology. She has conducted award-winning work on stress and vaccination response across the life course. Dr. Phillips was appointed as a research associate during her PhD at the University of Birmingham, and undertook post-doctoral research for one year following her PhD with Professor Douglas Carroll. She then went on to win a prestigious fiveyear RCUK Roberts Fellowship, which is a fast-track fellowship that segues into a lectureship following its completion. On completion of the fellowship in 2011 she was promoted to Senior Research Fellow, and then again to Reader in Behavioural

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Medicine in 2012. She has received three Early Career Awards for research: the Herbert Weiner Early Career Award 2010 from the American Psychosomatic Society – one of only two UK scientists to ever win this award, which is made in recognition of importance and sophistication of research for this career stage; the Neal Miller Early Career Award 2010 from the Academy of Behavioral Medicine Research – a very prestigious award for research; and the Stress and Anxiety Research Society Early Career award in 2014. In 2011 Dr. Phillips became the inaugural winner of the award for Outstanding Contribution to Research from the British Psychological Society Division of Health Psychology. Sheida Rabipour is completing her PhD in Psychology at the University of Ottawa, following BSc and MSc in Neuroscience at McGill University. Her research centers on cognitive training and psychological well-being. She also works to raise awareness on brain health through public blogs and workshops. Jonathon Reay holds a BSc in Psychology and a PhD in psychopharmacology from

Northumbria University. He is currently head of Psychology at Teesside University. His research focuses on exploring the efficacy of nutritional interventions for psychological health. Kirsty Scholes-Balog is a Postdoctoral Research Fellow within the Learning Sciences

Institute, Australian Catholic University. Her research focuses on longitudinal predictors and consequences of health and behaviour of young people. Her main research interests include substance use, mental health and problem behaviors. Andrew Scholey holds a PhD in cognitive neuroscience from the Brain and

Behaviour Research Centre, Open University. He is currently director of the Centre for Human Psychopharmacology, Swinburne University, Melbourne, Australia. He studies many aspects of human psychopharmacology including the influence of dietary bioactives. His current research focuses on understanding the mechanisms of cognitive enhancement in both cognitively intact and clinical populations. Kenneth Shultz earned his PhD in Industrial/Organizational Psychology

from Wayne State University in Detroit, Michigan. He is currently a Professor of Industrial/Organizational Psychology and Interim Director of the Center on Aging at California State University, San Bernardino. His research focuses on aging workforce issues, including mid- and late career issues, bridge employment and retirement. Previously he worked for the City of Los Angeles as a Personnel Research Analyst and has consulted with a wide variety of companies. Michael Smith holds a PhD in Psychology from the University of Western

Australia. He is currently Senior Lecturer in Psychobiology and Health Psychology

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at Northumbria University (UK) and Adjunct Senior Lecturer in the Medical School at the University of Western Australia. Christian Stamov Roßnagel holds a PhD in Psychology. He is currently a professor

in organisational behaviour at Jacobs University Bremen (Germany). His research focuses on generational differences in work-related learning competency, resourceoriented interventions to increase learning motivation and personalised e-learning. Vanessa Taler holds an MA in Linguistics from McGill University and a PhD in Biomedical Sciences from Université de Montréal. She is currently an Associate Professor in the School of Psychology at University of Ottawa and a Scientist at the Bruyère Research Institute in Ottawa, Canada. Her research focuses on language and cognitive processing in people with mild cognitive impairment and Alzheimer’s disease. Monique van Bruggen-Rufi holds a Master’s degree in music therapy and was trained

as neurological music therapist-fellow. She works as a lecturer in music therapy and guitar skills at the music therapy bachelor program offered by ArtEZ Conservatory School of Music in Enschede, the Netherlands. Furthermore, she lectures for the Master of Arts Therapies program at Zuyd University in Heerlen, the Netherlands. She is a regular guest speaker at (national and international) universities and conferences. She is currently working on her PhD-research on music therapy with Huntington’s Disease at the Neurology Department of the Leiden University Medical Center in Leiden, the Netherlands. She also works as a researcher at Atlant Care Group in Apeldoorn, the Netherlands, a long-term care facility specialized in Huntington’s Disease. Her main areas of expertise are neurodegenerative diseases such as Huntington, Parkinson and dementia. Before Monique committed herself completely to music she worked as an operation room nurse and a physician’s assistant. Annemieke Vink has been trained as a psychologist and in Neurological Music Therapy. She carried out a PhD to study the effects of music therapy to reduce agitation in elderly people with dementia at the University of Groningen (the Netherlands). She works as a lecturer in theory of music therapy at the bachelor music therapy program offered by ArtEZ Conservatory School of Music in Enschede, the Netherlands. Furthermore, she lectures for the Master of Music and Master of Music Therapy at ArtEZ and is also a core team member and lecturer on the Master of Arts Therapies Course (Zuyd University). She works as a researcher at ArtEZ (research center for music therapy) and KenVaK (research center for the art therapies). Her main areas of expertise are the effect of music therapy on people with dementia and music psychology. Annemieke Vink has presented at various national and international congresses on the topic of music therapy and effects of music therapy for elderly people specifically and has written various publications about music therapy, music psychology and the effects of music therapy on people with dementia and related diseases.

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Ana Vitlic was a European Commission FP7 Marie Curie Innovative Training Network PhD student with Dr. Anna Phillips at the University of Birmingham School of Sport, Exercise and Rehabilitation Sciences until she graduated in 2014. Her research area was stress and immunity in ageing. She now works as a research scientist for a small assay development company in the UK. Gerben Westerhof (PhD, 1994) is adjunct professor of Narrative Psychology at the University of Twente, Enschede, the Netherlands, and director of the Story Lab at this university. His research focuses on well-being and personal meaning in aging. He is also interested in the use of narrative and life review methods to promote well-being and meaning in life. David White holds a PhD in Cognitive Neuroscience from Swinburne University, Melbourne, Australia. He is currently a Post-doctoral Research Fellow with the Centre for Human Psychopharmacology at Swinburne, where his primary research focus uses neuroimaging methods to assess the neurocognitive outcomes from a range of nutritional and psychopharmacological interventions. Belinda Wylie holds a degree in Social Sciences. She has previously worked as

a Cancer Services Coordinator at Macmillan Cancer Support, and lectures on the topic of bereavement to MSc Health Psychology students at Northumbria University (UK).

SECTION I

Introduction

1 UNDERSTANDING SUCCESSFUL AGEING, KEY CHALLENGES AND RESEARCH METHODS Riby, Leigh, Greer, Joanna, Martinon, Léa M. and Reay, Jonathon L.

During the previous two decades, academics, health care professionals, and members of the general public have been relentless with their desire to further explore and understand the multidimensional relationship between ageing, physical health, and psychological wellbeing. In particular, there has been substantial interest in the role that individual differences, lifestyle choices, and the environment play in typical and atypical ageing; exploring their impact on disease aetiology, disease progression, treatment plans, and more recently, disease prevention is essential. This increased interest and scientific enquiry is largely due to the estimated additional 400 million adults who will be 80 years and over by the year 2050 (World Health Organization, 2014). Moreover, the associated exponential rise in age-related health care problems is coupled with a current lack of suitable interventions and understanding. As a result, there is now a race to uncover and understand the secrets of ‘successful ageing’ to slow the onset and progression of the inevitable age-related health problems. Although difficult to define, as we will explore below and throughout the text, successful ageing is a key contemporary concept that arouses much debate; as living longer should not be assumed as synonymous with good news, if one’s prolonged life results in more years of disease and suffering. Regardless, with life expectancy increasing, successful ageing is extremely important and we need to treat the ageing population in a positive light, to be celebrated and seen as active contributors to society (see Stephens & Flick, 2010). Defining successful ageing is in itself problematic; however, let’s first consider Bowling and Dieppe (2005) who state that any definition “. . . needs to include elements that matter to elderly people” (p. 1548). This certainly needs to be kept in mind, as we soon become lost in lab-based experimental data and theoretical positions with no obvious link nor application to the everyday lives and wellbeing of elderly individuals. Indeed, it could be argued that there is often a misalignment between academic researchers and older adults’ definitions of successful ageing. When successful ageing

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is rated by older adults themselves, 50.3% of them seemed to have aged successfully whereas only 18.8% of them did when using research criteria (Strawbridge, Wallhagen, & Cohen, 2002). Often, all components rated as important by the elderly are not always considered in their entirety by research workers (i.e. physical, functional, psychological, and social health; Phelan, Anderson, Lacroix, & Larson, 2004). We know, from a plethora of research, that illness, disability, and distress occur concomitantly with the ageing process; however, we know far less about the factors that contribute to successful independent living and quality of life during the ageing process in the face of these challenges. Rowe and Kahn (1987) were one of the first to introduce the idea of successful ageing and their model will provide the groundwork. According to their model there are three inter-related factors that make positive outcomes more likely as we age (see Fig. 1.1). It is worthwhile keeping in mind that older adults are resilient even in the presence of impairment in one of these three domains; compensation drawing on strengths and stability is key to growing older successfully. Minimal impact of disease and disability The physical changes that occur during ageing are well documented (e.g. reduced arterial elasticity, reduced immune, lung, kidney, and the endocrine function, and more observable changes to the musculoskeletal system; for a review, see Lowry, Vallejo, & Studenski, 2012). Even in the absence of disease these changes impact upon normal everyday living and quality of life; however, we know that disease processes amplify these difficulties, especially in the presence of debilitating diseases such as Alzheimer’s disease, arthritis, osteoporosis, heart disease, and diabetes. In this regard, the active life expectancy (years of independent living) has proven to be a useful conceptualisation of ageing well. Undeniably, improvements in healthcare provisions, medical advances, and novel strategies for compensation have helped ameliorate the negative impact of ageing and disease, allowing older adults to be active members of society for longer. In the present text we focus on psychological function, brain, and behaviour and use dementia as an example. In a meta-analytic review, Prince et  al. (2013) report a worldwide estimate of 36 million people living with dementia in 2010 and

Minimal Disease/ Disability

Social Engagement

FIGURE 1.1

Superior Cognitive and Physical Function

Factors contributing to successful ageing. Based on Rowe and Kahn (1987).

Understanding successful ageing

5

a worrying anticipated increase, to 66 million in 2030 and 115 million in 2050. Neuro-cognitive deficits are central to the disorder with declines in the early stages of the disease seen in the psychological constructs of episodic memory, working memory, executive function, and perceptual speed (see for example Bäckman, Jones, Berger, Laukka, & Small, 2005). Therefore, expectancies of an active life become critical. Indeed, the uniqueness of the cognitive profile compared to ‘normal’ ageing and mild cognitive impairment (Riby et al., 2009) can impact extensively on the everyday activities and ability to live independent lives. Therefore, the notion of an active life expectancy becomes critical. Indeed research has identified modifiable risk factors for dementia (e.g. years of education, Brayne et al., 2010; nutritional imbalance such as low vitamin D concentrations, Balion et al., 2012, Brown, Riby, & Reay, 2009, Reay, Smith, & Riby, 2013; and physical exercise, Lindsay et al., 2002) and has demonstrated the effectiveness of compensation strategies (e.g. external memory aids, Fried-Oken et al., 2012; aerobic and resistance exercise, Brown et al., 2015) for managing disease symptoms and extending active life (for a recent review, see Baumgart et al., 2015). Thus, all of these possibilities of compensations imply a strong individual variability in how people deal with ageing or diseases. Recent findings indicate that this inter-individual variability could be explained by different degrees of cognitive reserve, meaning that brain differences could lower or offset the effect of ageing (Ducharme-Laliberté, Boller, & Belleville, 2015). Superior cognitive and physical function Relatively stable mental and physical function in addition to being free from disease is an important consideration for seniors seeking quality of life in later years. Uncovering the mechanisms that might result in stability or at least minimal decline in physical and cognitive function is paramount in a successful ageing agenda. The obvious route is to promote research activities aimed at examining predictors (e.g. diet, exercise, lack of smoking) of successful ageing and also targeting these to healthy behaviour in midlife (Britton, Shipley, Singh-Manoux, & Marmot, 2008). For example, epidemiological studies support the notion that regular exercise in midlife can reduce the risk of cognitive decline and dementia in older adults (Forbes et al., 2015a, 2015b). Forbes et al. (2015a, 2015b) in their recent reviews outline the plausible biological basis of exercise on cognitive outcomes in middle age; for example, exercise might promote reductions in systemic inflammation, promote efficient brain insulin function, and may reduce oxidative stress. A final component to consider in this second domain of successful ageing is that there is a reciprocal relationship between physical function and psychological performance with the former having been shown to have clear benefits to the latter. Weuve et al. (2004) investigated the long-term effects of physical exercise on cognitive function and demonstrated the beneficial effects of not only vigorous exercise but even lighter forms of physical activity (i.e. walking). The mechanisms driving this relationship (e.g. improved vascular health and more direct effects on neurochemistry) will receive coverage throughout the text but the findings over performance benefits even for light exercise is promising and would mean only small adaption would be needed in the lives of the older adults. Interestingly from a cognitive perspective, physical exercise has been demonstrated to improve

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those numerous psychological constructs known to be vulnerable to ageing (e.g. verbal episodic memory; executive function; e.g. Colcombe & Kramer, 2003). Social engagement The final component of successful ageing that provides compensation for the debilitating effects of disease and the physical and psychological changes that occur in normal ageing is the presence of a strong social support network. In a recent report from the Office of National Statistics (2013) 46% of the elderly over the age of 80 reported a feeling of loneliness some of the time or often. This statistic is particularly worrying given the association between loneliness and reported difficulties in everyday task performance, emotional and physical wellbeing, and quality of life (Pinquart & Sörensen, 2000). Growing older brings about a number of significant life changes that are associated with being alone such as loss of partner and restrictions caused by disability but an important consideration is that being alone predicts health concerns (e.g. depression, cardiovascular impacts) and difficulties on everyday activities. Interventions that target social isolation and loneliness are welcomed by policy makers if the end result is improvements in wellbeing and a sense of social belonging in the community (Stanley et al., 2010). A large-scale study on social support is particularly relevant here. Matthews (1984) in an early paper on the topic rightly points out that the complexity of social support makes it extremely difficult to uncover how detrimental effects of ageing can be minimised. Difficulties in definitions are here problematic with loneliness and social isolations being often used interchangeably (Stanley et al., 2010). Social isolation does not necessarily lead to loneliness and other concerns include the lack of older adults’ perspective on loneliness that is often neglected by researchers (see influential paper by Stanley et al., 2010). Similarly what seems to be disregarded in the research is the fact that both receiving and giving social support has a positive impact on health, quality of life (e.g. life satisfaction), and psychological wellbeing. Kim, Hisata, Kai, and Lee (2000) make this precise point with reciprocal exchange being beneficial, whereas an unequal exchange of social support often leads to distress. Even social media has proven beneficial with this being ideal in keeping in touch with loved ones and family members and maintaining their sense of belonging in a community and good mental health (Senior Care Corner, 2015). Indeed, an innovative cross-cultural computer training study has stressed digital inclusion to promote active ageing and the reduction of social isolation (AGES 2.0, 2015).

Organisation of the book This book brings together the work of prominent researchers within the field of gerontology, taking a successful ageing approach already outlined. We have specifically selected chapters focusing on some of the key challenges facing the gerontologist and ‘hot topics’ in the field. As the title of the volume suggests, the collection of chapters particularly focus on a number of practical issues when researching older adults, which may impact on research outcomes, interventions, policy, and future directions in the area. Practical research tips will be considered in each chapter. It is worthwhile highlighting that successful ageing will be a key theme of all chapters

Understanding successful ageing

7

and work will cover both ‘normal’ and pathological ageing. As a result, the reader will acquire specialist knowledge about impairment and disease processes that might accompany the ageing process as well as an understanding that decline is not an inevitable consequence of growing old. In Chapter 2, Rabipour and colleagues outline the increasingly popular intervention of physical exercise as a route to stabilising cognitive and mental performance. The authors rightly point out that there are significant methodological limitations that make it difficult to argue for a direct link between physical interventions and cognitive enhancement. Observational studies are of course problematic as it is difficult to ascertain the cause and effect relationship. Furthermore, other factors that we have already identified as being critical to successful ageing such as social interaction may make up a more complex model when explaining the link between increased physical exercise and optimal psychological function. Besides considering methodological limitations the authors outline key studies suggesting clear impacts on brain systems and processes. For example, both structural and functional imaging techniques have proven fruitful in revealing anatomical and connectivity changes in the brain. At a cellular level, vascular and potential effects on growth and self-repair of neurons are outlined. Turning to cognitive exercise the authors discuss the types of activities that might constitute ‘exercise’ and may lead to positive outcomes (e.g. formal schooling, crossword puzzles, meditation). Interestingly, combined physical and cognitive exercise is a promising but understudied research endeavour. In Chapter 3, Peters and colleagues discuss the role of nutrition on the cognitive ageing process. After outlining some of the main pharmacological interventions available for the treatment of older adults and patients with dementia the authors outline dietary compounds that have the potential to target and prevent cognitive decline. Following a Mediterranean diet has received much interest in the popular press and here the authors critically evaluate this dietary pattern. Multicentre studies have been informative and point to lower risk of death from cardiovascular disease, cancers, obesity, and particularly relevant here age-related brain impairment (e.g. Parkinson’s and Alzheimer’s disease). Coverage of Omega-3 fatty acids and brain function follows with review, an examination of possible mechanisms leading to facilitation and methodological challenges. Identifying the populations that can benefit is critical, as not all older adults can profit, with later progression of Alzheimer’s disease highlighted as an example where neural substrates has deteriorated such that response to dietary intervention is no longer possible. An insightful final section on general considerations for nutritional interventions closes the chapter, with inclusion of how traditional behavioural methods can be used alongside imaging techniques to explore nutrition and the ageing process. In Chapter 4, Phillips and Vitlic outline elegantly the impact of stress on the immune system and consider implications for reliance in old age. Indeed, once the putative mechanisms linking immunological and endocrinological changes to resilience in old age have been discussed, the authors evaluate older caregivers’ difficulties (focusing on older caregivers of dementia patients) and their psychological wellbeing. Chronic stress in older individuals has major impacts on immunity with older

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dementia carers’ wound healing reported to be slower and responsiveness to vaccines to be impaired. Telomere length, which has recently been considered a clear marker of disease and the ageing process, is evaluated (for review see Mather, Jorm, Parslow, & Christensen, 2011). For example, telomere length has been reported to be shorter in older caregivers of dementia patients, and for that reason a valuable marker of environmentally induced differences in rates of ageing (Damjanovic et al., 2007). Social support is once more considered as an important component of successful ageing being linked to psychological stress and coping. Immune function is known to be moderated by loneliness and social network size across the lifespan. Further ‘healthy’ behaviours (e.g. exercise, balanced diet, adequate sleep) are evaluated for their direct impact on both perceived stress and immune system functioning. Getting the balance right is of course very important as stress during some activities and situations can be beneficial to health. In Chapter 5, Gerben Westerhof examines mental health and illness in an older population. The author begins by emphasising the multidimensional nature of mental health and illness to include different aspects of psychological and social functioning. The dual continua model is proposed before evaluating empirical work in support of this model. According to this model the presence or absence of poor mental health and illness represents two distinct but related dimensions (factor analyses suggest two rather than one dimension). Importantly, the suggested model appears to provide a good fit to the ageing data, including both losses and gains as we grow older and will prove to be influential in future experimental work in this area. The authors evaluate interventions that promote positive mental health across the lifespan. Reminiscence and life reviews are seen as extremely effective. Encouraging an individual to think back and reflect on life events and adding meaningfulness to the individual is seen as a valuable tool to minimise mental health problems as we grow older. Research including comprehensive meta-analyses has indicated positive outcomes such as reduced depressive symptoms. Reminiscence activities are diverse and may include autobiographical writing, family genealogy, and blogging. In Chapter 6, Stamov Roßnagel and Jeske evaluate applied research in the workplace and propose that such a setting provides the ideal context for studying successful ageing. The resource orientation approach is emphasised throughout the chapter with strategies and compensation in the management of limited resources as we grow older a primary concern. Since older adults are beginning to outnumber younger colleagues in the workplace and there is an increasing trend for working beyond the traditional retirement age, strategies for scaffolding performance is essential in the constantly changing work environment. Gains and losses are the focus with setting new goals and acquiring new skills beneficial. Losses are associated with the known biological and cognitive decline with strategies and the employment of those abilities known to be stable as we grow older important. Methodological implications of resources-oriented research in the work settings and survey-based studies are discussed with motivation used as an example. Age differences in motivation at work and how the consideration of affective processes is critical in the study are discussed. The chapter concludes with

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resource-orientated interventions, which are designed to help an individual become more aware and efficiently use existing resources as well as acquiring new resources to aid task performance. Importantly the contributors highlight that work on motivation and ageing is in good shape but suggest theories tend to emphasise cognitive components at the expense of affect. Overall the resource approach outlined will provide the groundwork for subsequent work in the area, helping researchers, practitioners, and managers in their endeavours to support successful ageing. Shultz and Fisher in Chapter 7 introduce and discuss retirement and appropriate methods that may be employed to evaluate this difficult to define concept. By examining how retirement has changed in recent decades the authors are able to effectively explore this important life transition. The historical account is followed by an evaluation of why a senior may wish to continue work. In addition to economic reasons, maintaining a sense of identity or just a great way to continue to receive social support are outlined. Much like successful ageing itself, retirement is difficult to define but the researchers stress the temporal nature of the process with longitudinal research encouraged (especially given the easy access to existing datasets). The processes may include retirement planning, decision making, and the final stages involved in the adjustments during the transition into retirement. Individual differences are considered, for instance, women (particularly divorced or widowed) are more likely to have interrupted careers due to childbearing and subsequent financial concerns impacting on retirement decision making, impacting on life satisfaction in later years. Key research designs are discussed and evaluated in detail. Other themes include the importance of other family commitments in the retirement decision, the impact of early retirement on psychological and cognitive function, and the importance of multidisciplinary research teams. This final point is particularly noteworthy, as traditionally, retirement studies draw from various fields such as public health, psychology, economics, and even within psychology subdisciplines such as developmental, cognitive, and organisational. In the Less successful ageing section, Chapter 8, MacPherson and Cox in their contribution describe the frontal lobe hypothesis of ageing, which claims that healthy adult ageing is associated with the deterioration of the frontal lobes of the brain (volume, cortical thickness, and white matter) earlier and more severely than other brain areas. Due to this selective decline in the frontal lobes, a very distinct cognitive profile is observed in seniors. The authors were the first to propose and outline here neuroimaging work from their lab that suggests differential effects of healthy adult ageing on sub-regions of the frontal cortex. Indeed, precise anatomical classification techniques have enabled the fractionation of frontal lobes and linkage to dissociable cognitive and psychological processes. The authors argue for the dorsolateral prefrontal theory of cognitive ageing rather than a model based on global impairment of more anterior regions of the brain. Healthy and pathological ageing (e.g. behavioural variant frontotemporal dementia, Alzheimer’s disease) studies alongside converging, neuropsychological, and neuroimaging work points to the distinctive cognitive profiles of older compared to younger counterparts. Methodological issues associated

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with the synthesis of previous work and the design of new studies examining the frontal lobe hypothesis of ageing are considered in detail. Methodological issues are evaluated in relation to the contributors’ own work, and difficulties mapping experimental work and achieving ecological validity when assessing frontal lobe functions (e.g. emotional processing, multitasking) are discussed. In Chapter 9, the less successful ageing theme is continued with the consideration of the psychological and cognitive abilities impaired and spared in type 2 diabetes (DM2). Evidence suggests patients suffer from accelerated ageing in memory domains (particularly episodic) and these impairments have significant impacts on disease management and performance of everyday activities. Evaluation of behavioural work starts the chapter and factors that might account for the mixed findings in the literature are identified (e.g. duration of disease, treatment given, and presence of complications). Indeed, exploring potential physiological mechanisms, co-morbid conditions such as glycaemic control, hypertension, dyslipidemia, and how these link to poor cognitive ability provide major challenges to the researcher. One solution is to capitalise on new advances in neuroscience (e.g. MRI, fMRI, and EEG) and use such tools in the understanding the neuro-cognitive profile of older adults with DM2. This method section of the chapter will prove to be useful for those considering mixed behavioural and neuroscience techniques to disentangle the precise cognitive processes impaired. For example, neuroimaging (particularly EEG) has been successfully used to track the precise aspects of episodic memory impaired in ageing and dementia (encoding vs. storage vs. retrieval). There has been recent interest in putative protective and risk factors for Alzheimer’s disease (AD). In particular, dietary factors (e.g. consumption of various fats) and lifestyle modifications (e.g. physical exercise) have received considerable attention in relation to successful ageing in the presence of disease. These modifications are likely to have maximum impact in those who are predisposed (genetically, environmentally) to develop AD at a higher incidence than the population at large. Indeed, significant genetic/environmental (e.g. apolipoprotein genotype/diet) and environmental/environmental (e.g. physical exercise/diet) relationships have been reported in the extant literature. In Chapter 10, those studies are critically evaluated by Scholes-Balog and colleagues with a view to providing the groundwork for researchers proposing studies in the area. The authors focus on literature implicating traumatic head injury as a significant risk factor for Alzheimer’s disease. Studies suggest that dietary and lifestyle factors may interact with head injury to influence the risk of cognitive decline and potentially alter the risk of developing AD. These interactions may be mediated by common biological processes. Notably a proposed conceptual model suggesting that the accumulation of brain amyloid-β represents the most likely candidate mechanism underlying these interactions. With this model in mind, future research will be able to perform well designed studies in the area. In our section Novel interventions, we learn how music can contribute to enhanced psychological function and wellbeing even in the latter stages of the disease. Music

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listening and therapy are the focus of Vink and van Bruggen-Rufi, Chapter 11, who examine the musical parameters that may be central to music’s emotion arousing enhancement properties. The historical account is particularly perceptive as we learn how music and its healing properties have a long history. The emotional arousing properties and direct impacts on the brain of music should not be underestimated and for that reason music therapy can be seen as a remarkable intervention. Even in Alzheimer’s disease it is known that musical ability (e.g. rhythm) appears preserved during the course of the disease. An evaluation of music-based exercise is undertaken with findings suggesting episodic recall to be superior when stimuli is presented in songs compared to verbal information alone. In keeping with a common theme for successful ageing, music therapy is also of benefit due to the increased social interaction from group work during sessions. Together the chapter is extremely informative and argues strongly for the inclusion of music therapy within general care. The purpose of Chapter 12 (Dr. Ioana Petrescu) is to examine novel interventions that may capitalise on creative abilities in the elderly. Creative activities such as poetry are evaluated for their utility for enhancing quality of life in the elderly and those individuals with dementia. The focus in the chapter is the evaluation of six poetry workshops conducted by the group that resulted in the writing of successful poetry by Alzheimer’s sufferers in an early intervention group. The accomplishment was exceptional with the work of the group subsequently collected and published in a volume. Furthermore, the participants were actively involved in the poetry writing workshops and were proud of their poetry-writing achievements and publication. Overall, the work demonstrated the utility of such interventions in successful ageing programmes and the experience was reported to have a positive influence on the sense of self as persons and writers with dementia. The volume draws to a close with an insightful Chapter 13 by Wylie and Smith on the topic of death, dying, and bereavement. Living longer and a protracted dying process due to accompanying chronic disease can place terrible demands on the individual and family caregivers. For this reason investigating optimal strategies for end of life care should be treated as a priority area. A ‘good death’ focus is emphasised throughout the chapter with care targeting minimising suffering and distress. The authors evaluate Bradbury’s (1999) account of idealised death, which includes dying in one’s own home, having one’s close relatives present, and an alert mind. Unfortunately, these conditions are often not met. An evaluation of difference between younger and older adults with respect to end of life care and the implications for research and policy suggests the work on seniors is poorly understood. A further concern for researchers promoting a good death in elderly individuals is that perspectives on the specific components that comprise a good death differ cross-culturally. This needs to be kept in mind when developing culturally sensitive care programmes, as potentially good death could be compromised in those from minority backgrounds.

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References Ages 2.0 (03/08/2015). Activating and Guiding the Engagement of Seniors through Social Media. Final Report. Retrieved from http://ages2.eu/sites/default/files/page/Ages-finalreport-EN.pdf Bäckman, L., Jones, S., Berger, A. K., Laukka, E. J., & Small, B. J. (2005). Cognitive impairment in preclinical Alzheimer’s disease: A meta-analysis. Neuropsychology, 19(4), 520–531. http://dx.doi.org/10.1037/0894-4105.19.4.520 Balion, C., Griffith, L. E., Strifler, L., Henderson, M., Patterson, C., Heckman, G., . . . Raina, P. (2012). Vitamin D, cognition, and dementia: A systematic review and meta-analysis. Neurology, 79(13), 1397–1405. http://dx.doi.org/10.1212/WNL.0b013e31826c197f Baumgart, M., Snyder, H. M., Carrillo, M. C., Fazio, S., Kim, H., & Johns, H. (2015). Summary of the evidence on modifiable risk factors for cognitive decline and dementia: A population-based perspective. Alzheimer’s & Dementia, 11, 718–726. http://doi:10.1016/j. jalz.2015.05.016 Bowling, A., & Dieppe, P. (2005). What is successful ageing and who should define it? British Medical Journal, 331, 1548–1551. http://dx.doi.org/10.1136/bmj.331.7531.1548 Brayne, C., Ince, P. G., Keage, H. A. D., McKeith, I. G., Matthews, F. E., Polvikoski, T., & Sulkava, R. (2010). Education, the brain and dementia: Neuroprotection or compensation? EClipSE collaborative members. Brain, 133, 2210–2216. http://dx.doi.org/10.1093/brain/ awq185 Bradbury, M. (1999). Representations of Death: A Social Psychological Perspective. New York: Routledge. Britton, A., Shipley, M., Singh-Manoux, A., & Marmot, M. G. (2008). Successful aging: The contribution of early-life and midlife risk factors. Journal of the American Geriatrics Society, 56, 1098–1105. http://doi:10.1111/j.1532-5415.2008.01740.x Brown, D., Spanjers, K., Atherton, N., Lowe, J., Stonehewer, L., Bridle, C. . . . Lamb, S. E. (2015). Development of an exercise intervention to improve cognition in people with mild to moderate dementia: Dementia And Physical Activity (DAPA) Trial, registration ISRCTN32612072. Physiotherapy, 101, 126–134. http://doi:10.1016/j.physio. 2015.01.002 Brown, L. A., Riby, L. M., & Reay, J. L. (2009). Supplementing cognitive aging: A selective review of the effects of ginkgo biloba and a number of everyday nutritional substances. Experimental Aging Research, 36, 105–122. http://doi:10.1080/03610730903417960 Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the cognitive function of older adults: A meta-analytic study. Psychological Science, 14(2), 125–130. http://doi.org/10.1111/ 1467-9280.t01-1-01430 Damjanovic, A. K., Yang, Y., Glaser, R., Kiecolt-Glaser, J. K., Nguyen, H., Laskowski, B., . . . Weng, N. P. (2007). Accelerated telomere erosion is associated with a declining immune function of caregivers of Alzheimer’s disease patients. Journal of Immunology, 179, 4249– 4254. http://doi:10.4049/jimmunol.179.6.4249 Ducharme-Laliberté, G., Boller, B., & Belleville, S. (2015). Bases cérébrales et neurofonctionnelles de la réserve dans le vieillissement normal. NPG Neurologie—Psychiatrie—Gériatrie, 15(87), 164–168. http://doi.org/10.1016/j.npg.2014.10.010 Forbes, S. C., Forbes, D., Forbes, S., Blake, C. M., Chong, L. Y., Thiessen, E. J., . . . Rutjes, A. W. S. (2015a). Exercise interventions for maintaining cognitive function in cognitively healthy people in mid life. Cochrane Database of Systematic Reviews, Issue 5. http:// doi:10.1002/14651858.CD011705 Forbes, S. C., Forbes, D., Forbes, S., Blake, C. M., Chong, L. Y., Thiessen, E. J., . . . Little, J. P. (2015b). Exercise interventions for maintaining cognitive function in cognitively

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healthy people in late life. Cochrane Database of Systematic Reviews, Issue 5. http:// doi:10.1002/14651858.CD011704 Fried-Oken, M., Rowland, C., Daniels, D., Dixon, M., Fuller, B., Mills, C., . . . Oken, B. (2012). AAC to support conversation in persons with moderate Alzheimer’s disease. Augmentative and Alternative Communication, 28, 219–231. http://doi:10.3109/07434618.2012.732610 Kim, H. K., Hisata, M., Kai, I., & Lee, S. K. (2000). Social support exchange and quality of life among the Korean elderly. Journal of Cross Cultural Gerontology, 15, 331–347. http:// doi:10.1023/A:1006765300028 Lindsay, J., Laurin, D., Verreault, R., Hebert, R., Helliwell, B., Hill, G. B., & McDowell, I. (2002). Risk factors for Alzheimer’s disease: A prospective analysis from the Canadian Study of Health and Aging. American Journal of Epidemiology, 156, 445–453. http:// doi:10.1093/aje/kwf074 Lowry, K. A., Vallejo, A. N., & Studenski, S. A. (2012). Successful aging as a continuum of functional independence: Lessons from physical disability models of aging. Aging and Disease, 3(1), 5–15. Mather, K. A., Jorm, A. F., Parslow, R. A., & Christensen, H. (2011). Is telomere length a biomarker of aging? A review. J Gerontol A BiolSci Med Sci, 66A(2), 202–213. http:// doi:10.1093/gerona/glq180 Matthews, A. M. (1984). Social support in normal aging. Canadian Family Physician, 30, 676–680. Office of National Statistics (11/04/2013). Measuring National Well-being, Older People and Loneliness. Retrieved from http://www.ons.gov.uk/ons/rel/wellbeing/measuringnational-well-being/older-people-and-loneliness/art-measuring-national-well-beingolder-people-and-loneliness.html Phelan, E. A., Anderson, L. A., Lacroix, A. Z., & Larson, E. B. (2004). Older adults’ views of “successful aging”—how do they compare with researchers’ definitions? Journal of the American Geriatrics Society, 52, 211–216. http://doi:10.1111/j.1532-5415.2004.52056.x Pinquart, M., & Sörensen, S. (2000). Influences of socioeconomic status, social network, and competence on subjective well-being in later life: A meta-analysis. Psychology and Aging, 15(2), 187–224. http://doi.org/10.1037/0882-7974.15.2.187 Prince, M., Bryce, R., Albanese, E., Wimo, A., Ribeiro, W., & Ferri, C. P. (2013). The global prevalence of dementia: A systematic review and meta-analysis. Alzheimer’s & Dementia, 6, 63–75.e2. http://doi:10.1016/j.jalz.2012.11.007 Reay, J. L., Smith, M. A., & Riby, L. M. (2013). B vitamins and cognitive performance in older adults: Review. ISRN Nutrition, 2013, 1–7. http://doi:10.5402/2013/650983 Riby, L. M., Marriott, A., Bullock, R., Hancock, J., Smallwood, J., & McLaughlin, J. (2009). The effects of glucose ingestion and glucose regulation on memory performance in older adults with mild cognitive impairment. European Journal of Clinical Nutrition, 63, 566– 571. http://doi:10.1038/sj.ejcn.1602981 Rowe, J. W., & Kahn, R. L. (1987). Successful aging. The Gerontologist, 37(4), 433–440. http://doi:10.1093/geront/37.4.433 Senior Care Corner (03/08/2015). Retrieved from http://seniorcarecorner.com/5-benefitsof-social-media-for-seniors Stanley, M., Moyle, W., Ballantyne, A., Jaworsky, K., Corlis, M., Oxlade, D., . . . Young, B. (2010). Nowadays you don’t even see your neighbours: Loneliness in the everyday lives of older Australians. Health & Society Care in the Community, 18(4), 407–414. http:// doi:10.1111/j.1365-2524.2010.00923.x Stephens, C., & Flick, U. (2010). Health and ageing—challenges for health psychology research. Journal of Health Psychology, 15, 643–648. http://doi:10.1177/1359105310368178

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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(6), 727–733. http://doi. org/10.1093/geront/42.6.727 Weuve, J., Kang, J. H., Manson, J. E., Breteler, M. M. B., Ware, J. H., & Grodstein, F. (2004). Physical activity, including walking, and cognitive function in older women. Journal of the American Medical Association, 292, 1454–1461. http://doi:10.1001/jama.292.12.1454 World Health Organization (17/07/2014). Ten Facts on Aging and the Life Course. Retrieved from http://www.who.int/features/factfiles/ageing/ageing_facts/en/index1.html

SECTION II

Lifestyle factors and psychological functioning

2 PHYSICAL AND COGNITIVE EXERCISE IN AGEING Rabipour, Sheida, Miller, Delyana, Taler, Vanessa, Messier, Claude and Davidson, Patrick

Introduction As people age worldwide, preserving and improving cognition in later life is becoming more urgent. Most of us share the intuition that physical exercise is a good way to ensure a healthier aging mind. After all, many of the older people who are cognitively successful are also physically active. This observation has generated a multitude of studies seeking a causal link between physical exercise and cognitive health. Indeed, the hundreds of studies that have already been conducted in older adults generally suggest a positive correlation between physical exercise and cognition (for reviews, see Angevaren, Aufdemkampe, Verhaar, Aleman, & Vanhees, 2008; Blondell, Hammersley-Mather, & Veerman, 2014; Colcombe & Kramer, 2003; Kelly et al., 2014b). We must be mindful, however, that a positive correlation between exercise and healthy cognition indicates only that they are found in the same people. Based merely on correlational evidence, we cannot know whether exercise directly improves cognitive aging or, conversely, whether healthy cognitive aging supports a more active lifestyle. Exercise and cognitive health may be inter-related in more complex ways, and third variables such as social interaction might be keeping people active and cognitively intact in aging. Most of us prefer the idea that we can influence the course of our cognitive aging through physical and/or mental exercise over the thought of being subject to the uncontrollable fate of cognitive decline. Scientists often share this perspective, leading them to frequently adopt the optimistic attitude that age-related cognitive decline can be attenuated significantly by physical exercise. However, a closer look at the existing data reveals significant methodological limitations that make it surprisingly difficult to establish a direct, causal link between physical exercise and the preservation of cognition in aging. Likewise, although cognitive exercise (i.e., “brain training”) is becoming an increasingly popular and lucrative intervention to

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preserve cognitive function in aging, brain-training studies have suffered from many of the same challenges as those of physical exercise. In a previous review, we delved into this literature in detail, noting methodological issues that make it difficult to confidently infer a direct, causal relationship between physical exercise and cognition in older adults (Miller, Taler, Davidson, & Messier, 2012). Here, we summarize the evidence on the effects of physical and cognitive exercise on cognitive aging, highlight the main methodological challenges in the area, and suggest key questions to consider when undertaking research on this topic. We point out various factors that deserve serious consideration when evaluating existing reports or undertaking new research. We conclude with suggestions to help researchers and practitioners in the design, implementation, and evaluation of research on physical and cognitive exercise. Throughout, we adopt a cautious attitude about causal relationships between exercise and cognitive aging. Of course, as the field accumulates more good data, our approach in this review may prove to be overly cautious. However, as we will outline, we think that at this stage care is warranted in claiming which factors contribute to healthy cognitive aging and in recommending what people do to increase their odds of successful cognitive aging.

A general consideration: choosing the right design for the right question The overall design of a study determines the questions it can answer. Observational studies can be either retrospective or prospective, including data from one point in time (i.e., cross-sectional) or several (i.e., longitudinal). Their advantages include the possibility of being relatively inexpensive, large, and easy to run. Moreover, observational studies can provide insights into cross-sectional and longitudinal differences in cognition and physical exercise. Observational designs do not allow us, however, to establish causality. Experimental (or intervention) designs, in contrast, attempt to systematically control a variable of interest (i.e., exercise), while reducing the influence of potentially confounding factors. In this regard, experiments are better able to uncover causal relationships. This design is no panacea, however. Interventions are not immune to confounds, are often costly – which usually leads to smaller sample sizes evaluated over a shorter period of time than ideal – and suffer from selection biases and dropout.

Considerations in designing and interpreting studies of physical exercise and cognition What, exactly, is physical exercise? At first glance, this question might seem pedantic, but it is both important and difficult to answer. What is the operational definition of exercise in the study? Aside from questions about the duration and intensity of activity (see below for a discussion of these), there is little agreement across the literature on exactly which activities count as “exercise.” Most researchers (and participants) would endorse swimming

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laps in the pool as an obvious example, but what about gardening? Housework? Sex? Each of these has been included in some previous studies but not others, which, at the very least, hinders the comparison of results across the literature. Although universal agreement on the definition of “exercise” seems unlikely, greater consistency and a common vocabulary are needed urgently (Warren et al., 2010). Another consideration in defining exercise regards the target physiological energy systems. An implicit consensus appears to exist across the literature that cardiorespiratory-focused exercise (e.g., swimming, running) contributes the most to effects on cognition, whereas strength-focused exercise (e.g., weight training) is less effective, followed by balance, toning, and flexibility (e.g., Tai Chi, yoga), which are least effective. This distinction often leads researchers to use activities that ostensibly belong to the last of these three categories as a control for activities from one of the first two categories. Nevertheless, the evidence for the superiority of cardiovascular exercise is mixed, particularly when one looks at interventions rather than observational studies (Colcombe & Kramer, 2003; Snowden et al., 2011). This may stem from the difficulty in assigning certain physical activities to only one of these three categories. For example, many aerobic exercises (e.g., running) cannot help but also yield improvements in strength as well as in balance, toning, and flexibility. Conversely, strength training can benefit cardiovascular function, either directly (e.g., by changing arterial stiffness; Li et al., 2014) or indirectly (for example, by increasing a jogger’s core and leg muscle strength to allow her to run further and/or faster, driving her heart rate that much more). Ambiguity surrounding the specific cognitive benefits of particular kinds of exercise may also stem from the possibility that any activity that is physically, cognitively, or socially stimulating can boost cognition (Hayes, Hayes, Cadden, & Verfaellie, 2013; for more, see “What other factors must be ruled out?”, below).

How should physical exercise be measured? After deciding which behaviours are defined as exercise, the next challenge is to measure them. Researchers usually choose between subjective and objective measures. Subjective reports (i.e., self-report) can be formalized as questionnaires, diaries, logs, and so forth. Although they are inexpensive and easy to administer, their value can be diminished by participants changing their behaviour or their report to fit what is socially desirable (i.e., impression management) or what they believe the experimenters expect or want (i.e., demand characteristics) and by memory failures and biases, which may be especially relevant if participants are asked to recollect details about exercise from long ago. The importance of memory may help explain why test–retest reliability of exercise self-reports is notoriously low (Geda et al., 2010). Objective methods of measuring and monitoring exercise vary. Laboratory measures include pulse, blood pressure, and the volumes of oxygen and carbon dioxide inhaled and exhaled when breathing under controlled maximal physical exertion, from which we derive the maximum oxygen consumption: VO2 max. This last test is costly, takes significant time, and requires a specialized facility. Because the VO2 max test typically requires participants to reach their maximal cardiorespiratory capacity, it

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can be counter-indicated for people with low fitness or significant health problems. As a real-world alternative, the first generation of personal devices for continuous monitoring of activity (e.g., stand-alone motion sensors, pedometers, accelerometers, and so forth) has now given way to a second generation of more accessible, easier to use, and less expensive measures. These small, discreet wearable sensors detect variables such as heart, pulse and respiration rates, and footsteps (which, depending on the system, can be categorized into walking, running, and stair-climbing). Typically, these allow continuous collection of data using a smartphone. New devices are coming onto the market every year, and prices are falling accordingly, increasing the likelihood that such devices will be used in larger studies. Of course, these devices are useful only if participants use them properly and continuously. The rapid pace of product development for exercise monitors means that the scientific literature is lagging behind industry by several years. For instance, in July 2016, only 100 PubMed entries existed for “FitBit,” one of the most popular wearable monitor companies; more crucially, only one entry existed for “Fitbit and cognition.” The bulk of the current literature on objective monitoring of physical activity has used the previous generation of devices, which often had problems with comfort and compliance, especially over the long term. Although these problems might be mitigated by newer technology, caution is warranted in their use: These devices can fail or deliver inaccurate data (Lee, Kim, & Welk, 2014; Sasaki et al., 2014),1 and the data they do yield can be difficult to interpret. It is possible to estimate VO2 max from resting and maximum heart rates (Uth, Sorensen, Overgaard, & Pedersen, 2005), but this estimate must be acquired during controlled exercise intensity, which may be difficult for all participants to attain without supervision – notwithstanding the risk for older adults exercising at peak intensity (Noakes, Myburgh, & Schall, 1990). Furthermore, some older adults may be uncomfortable using these wearable technologies. Choices about measurement are important, because these different ways of measuring exercise are not interchangeable: Although within-subjects studies assessing subjective and objective estimates of exercise generally find positive correlations between subjective and objective measures, these correlations are usually weak (Jurca et al., 2005; Mailey et al., 2010; Moy, Scragg, McLean, & Carr, 2008; Zlatar et al., 2015).

How much physical exercise is required for maximal effectiveness? On this topic, several questions are intermingled: How often should exercise sessions occur, how long should sessions be, over how long a term, and at what intensity, to produce benefits for cognition in aging? Getting these questions straight is paramount: Exercise programs that are too low in intensity or too brief may fall short of showing any cognitive benefits, whereas programs that are too arduous or too longlasting may increase drop-out, especially of participants with poorer initial physical and/or cognitive functioning. Is more frequent exercise better? The old adage that “more is better” might fit with our intuitions, but might not actually be true (or, the answer might depend

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on whether by “more” you mean session schedule [how often], session length [how long], program length [over how long a term], or intensity of activity). For example, in their classic meta-analysis of exercise interventions for cognitive aging, Colcombe and Kramer (2003) found that programs that lasted more than six months were more effective, implying that more sessions are better. However, the “more is better” maxim did not apply to the length of each session: The ideal session length was between 30 and 45 minutes, with longer sessions not conferring as great a benefit to cognition. Is more intense exercise better than less intense? Perhaps going against one’s intuitions, many interventions and longitudinal studies have suggested that moderateintensity exercise is often as good as, and sometimes even better than, high-intensity exercise (Blondell et al., 2014; Colcombe & Kramer, 2003; Etnier et al., 1997; Gates, Singh, Sachdev, & Valenzuela, 2013; Hindin & Zelinski, 2012; Kelly et  al., 2014b; Lindwall, Rennemark, & Berggren, 2008; Lindwall, Rennemark, Halling, Berglund, & Hassmen, 2007; Smith et  al., 2010; Snowden et  al., 2011; Sofi et  al., 2011; Yaffe, Barnes, Nevitt, Lui, & Covinsky, 2001). Two points seem pertinent, however. First, the debate over different effects of low-, moderate-, and high-intensity exercise is complicated by the fact that intensity is particularly difficult to measure and agree on. This is especially the case in longitudinal and epidemiological studies, which often rely on self-report. Some researchers have chosen to categorize different activities a priori as being high intensity (e.g., jogging, basketball) versus low intensity (e.g., walking, gardening), but such categorization risks confounding type of activity with intensity. Other researchers (e.g., Hillman et al., 2006) have relied on people reporting how often they break into a sweat as a proxy for intensity. This approach is hindered, however, by the weak relationship between sweating and physical exertion (Buono & Sjoholm, 1988). Moreover, sweating tends to decrease in aging (Foster, Ellis, Dore, Exton-Smith, & Weiner, 1976). Alternative measures of the intensity of physical activity include multiplying the estimated amount of time taking part in each activity by the amount of energy presumably expended during that activity (e.g., van Gelder et al., 2004), but in many cases these still rely on participants’ self-reports. Second, an interesting recent development is the introduction of very high intensity exercise for very brief periods (e.g., 90% maximum heart rate for only 1 minute). Referred to as high intensity training (HIT) or high intensity interval training (HIIT), this usually occurs under the supervision of medical personnel using objective physiological exertion measures. Virtually nothing has been published on the cognitive effects of these very high intensity protocols, but given the claims of beneficial effects on blood sugar regulation and processing and on aerobic capacity (for a review, see Gibala, Little, MacDonald, & Hawley, 2012), this could be a very fruitful area of research.

What are the likely cognitive effects? Not all cognitive processes are affected equally by aging: Processing speed, executive functions, working memory, and episodic memory are perhaps the most sensitive

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(for brief reviews, see Davidson & Winocur, 2010; Drag & Bieliauskas, 2010). Sensibly, these are usually the cognitive domains that receive attention in exercise studies. However, universal agreement does not yet exist on this list of cognitive domains, or on how best to measure them using behavioural testing. Moreover, not all older adults decline at the same rate, and some appear to decline little if at all. Several challenges exist in interpreting the current literature: First, many studies do not probe cognition in detail, but rather use relatively coarse cognitive screening tools such as the Mini Mental State Exam (Folstein, Folstein, & Mchugh, 1975). Although these tools have the advantages of being brief and easy to administer and score, they may lack the sensitivity to probe cognition with high-enough resolution to detect any subtle benefits of exercise (Gagnon et al., 1990). Instead, more detailed assays of cognition may often be more appropriate. For example, if learning and memory is the target cognitive function, a good tool is the California Verbal Learning Test-II (Fine, Kramer, Lui, Yaffe, & R, 2012; Lamar, Resnick, & Zonderman, 2003). It provides a wealth of information, allowing the comparison of memory over the short term versus over the longer term, assessing memory in several ways (free recall, category-cued recall, and yes–no recognition), and providing additional information on memory organization and consistency. Putting the myriad scores together can allow one to make inferences about the participant’s executive functioning, shortterm/working memory, and episodic memory. The test includes relatively good (American) norms from across the adult age range, and comparison data from different neurological patient groups (e.g., dementia). It is available in a standard and an alternative version, meaning that it can be administered twice without item-specific practice effects. Of course, the most appropriate cognitive measures depend on the population and cognitive processes of interest (Bahar-Fuchs, Clare, & Woods, 2013). In general, however, researchers should prefer measures with well-established reliability, validity, sensitivity to both potential cognitive gains and losses (including no ceiling or floor effects), and availability in multiple parallel forms to yield minimal (or, at least, predictable) practice effects. The California Verbal Learning Test-II meets these criteria reasonably well. One special problem to note, however: To avoid ceiling and floor effects these tests must have an appropriate level of difficulty. Yet, this is not always as easy as it sounds. Many clinical measures are designed for people with reduced levels of performance, and may be inappropriate for high-functioning participants (such as those healthy, highly-motivated older adults who often sign up enthusiastically for an exercise study). Even the California Verbal Learning Test-II, for all its advantages, has problems with potential ceiling effects in high-functioning individuals (Uttl, 2005).

What are the likely brain effects? Ideally, cognitive effects of exercise should be accompanied by measurable brain effects. Because of the overwhelming number of brain systems and processes that

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one could examine, researchers must decide where to focus (for suggestions, see Hayes et al., 2013).

Systems level Most researchers have taken a macro or systems-level approach, often using structural or functional neuroimaging to examine the whole brain. Even when restricting oneself to this level, the possibilities remain numerous: Structural studies can focus on different regions of the brain and different tissues (e.g., grey versus white matter), and use different methods (e.g., manual versus semi-automated or automated selection and quantification of volumes) to look at different characteristics. Grey matter integrity can be operationalized in terms of the estimated volume or percentage of grey matter in a given slice, compartment, or region, or the thickness of the cortex. White matter integrity can be operationalized in terms of the estimated volume or percentage of white matter in a given slice, compartment, or region, the number of discrete lesions evident to a human or computer decision-maker, or spatial patterns in the movement of water (as in diffusion imaging, which itself can be done in several different ways). Functional studies can focus on one or several regions or on the interaction among them, examining activity at rest or during a cognitive task. Note that the two most common functional neuroimaging methods, Positron Emission Tomography (PET; measuring glucose utilization with a radioactive tracer) and the blood oxygenation level dependent signal in functional Magnetic Resonance Imaging (fMRI measuring brain oxygen use), provide different but complementary information about the interactions among brain activity, energy consumption, and blood supply (Detre & Wang, 2002; Lauritzen & Gold, 2003). A final consideration is that some brain features, such as neurofibrillary tangles, beta-amyloid plaques, and cell loss, are more characteristic of dementia than of healthy aging. The choice of brain variable(s) is important, because some phenomena (e.g., neurofibrillary tangles) cannot easily be detected with neuroimaging, and many of these variables (e.g., beta-amyloid deposition, metabolic changes, and atrophy) are at least partially independent of one another in normal aging and dementia (Chen, Rosas, & Salat, 2011; La Joie et al., 2012; Vemuri et al., 2015). One could imagine exercise having dissociable effects on each of these factors (Radak et al., 2010).

Cellular/molecular level Although most of the work on exercise and cognition in aged humans has looked at the brain at the macro/systems level (for example, using MRI and PET), the physiological mechanisms invoked to explain the cognitive benefits of exercise are usually at the micro/cellular-molecular level. Some researchers emphasize vascular health (e.g., improving neuron-blood supply coupling, reducing risk of stroke by reducing blood pressure and clearing cholesterol, and so forth), which can be summed up by the adage “What’s good for the heart is good for the brain” (Angevaren et al., 2008). Others emphasize the potential effects of exercise on growth and self-repair

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of neurons, which include reducing inflammation, promoting neurogenesis and synaptogenesis, or boosting levels of brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF; Cotman, Berchtold, & Christie, 2007). For example, light, moderate, and vigorous levels of physical activity have been inversely correlated with inflammatory responses and risk of coronary heart disease (Ford, 2002). Exercise can also have systemic effects on the stress response and glucose processing, both of which can have profound effects on neural structure and function, as well as immune functioning. Moderate exercise, in particular, has been linked to improved immune function and lower incidence of upper respiratory tract infection; excessive exercise, on the other hand, may lead to immunosuppression (Gleeson, Nieman, & Pedersen, 2004; Nieman & Pedersen, 1999). Here several caveats should be highlighted. First, much of the experimental work on the brain and behavioural effects of exercise has used animal (primarily rodent) models: Yet, in this literature, the putative effects of exercise may actually be attributable, at least in part, to reduced social or environmental deprivation in the conventional animal exercise paradigms (Hatchard, Ting, & Messier, 2014). Second, even if exercise can be convincingly demonstrated to have a direct effect on cognition and the brain, different kinds of exercise (e.g., cardiorespiratory/aerobic versus strength/anaerobic) might have different effects from one another (Voelcker-Rehage & Niemann, 2013).

What other factors must be ruled out? One of the greatest challenges for this field is that several other variables, including physical health, personality, sleep, baseline cognitive abilities, mood, and social stimulation may mediate or moderate the relationship between exercise and cognition (for more detail see Miller et al., 2012). Some of these factors may be present at the beginning of the study. For example, in interventions, the people who are in good physical health will be able to take up and maintain a more rigorous exercise program. Conscientious people are also more likely to take up and follow their exercise programs, but then also to engage in other health-related behaviours that may improve their cognitive functioning and prevent decline (Low, Harrison, & Lackersteen, 2013). Other factors may coincide with or follow physical exercise, such as improved sleep and mood, or acquiring new friendships in exercise class. These are all potential confounds, and are all too rarely considered in exercise studies. Even when they are measured, especially in observational studies, they can be difficult to disentangle from one another (Robitaille et  al., 2014). If any of the preceding factors were to make a greater contribution than is usually assumed, then the recommendations made to older adults regarding physical exercise would be different: For example, you don’t need to exercise that much, but do it with friends and family.

Who benefits? Not all participants may benefit equally from physical exercise, but the jury is still out on whether factors such as age and sex are important. For example, although

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Colcombe and Kramer (2003) observed that studies that included more women in their older adult samples showed stronger cognitive effects of exercise, ensuing research has been equivocal on potential sex differences (Blondell et al., 2014; Colcombe & Kramer, 2003; Etnier et al., 1997; Gates et al., 2013; Hindin & Zelinski, 2012; Kelly et al., 2014b; Smith et al., 2010; Snowden et al., 2011; Sofi et al., 2011). Similarly, recent meta-analyses have found little difference in the effect of exercise on cognition in older adults with good cognition versus those with reduced cognitive function (Boyle et al., 2015). On this point, it is important to note that older adults with good versus reduced cognition are rarely compared head-to-head in the same study, and that many studies are underpowered, making null effects ambiguous. Another potentially important factor is mood: People with depression may be difficult to recruit and retain, but these may be the very people who show the greatest cognitive benefits of physical exercise (Blake, 2012; Carek, Laibstain, & Carek, 2011). Because most published studies on physical exercise and cognition have a serious lack of statistical power (Blondell et  al., 2014; Colcombe & Kramer, 2003; Etnier et al., 1997; Gates et al., 2013; Hindin & Zelinski, 2012; Kelly et al., 2014b; Smith et al., 2010; Snowden et al., 2011; Sofi et al., 2011), thinking a priori about what to expect regarding individual differences in potential benefits of exercise will be advantageous. First, if one can predict problems with adherence or drop out due to cognitive and concomitant health difficulties (including depression), one can over-recruit to have an adequate number of participants by the end of the study. Second, even in cases where drop-out isn’t an issue, planning analyses in advance (for example, by planning to contrast men with women or to separate participants into age groups by decade) will ensure that power isn’t diluted by sub-dividing groups post-hoc. Physical exercise may well contribute, directly or indirectly, to better cognition in the aged (Erickson, Hillman, & Kramer, 2015). However, as we have outlined, to make progress on this question, more careful design, conduction, and evaluation of research is needed now. Accounting for the factors discussed above will enable this. Identifying the “active ingredients” in physical exercise will enable us to use it more effectively to benefit cognitive health in old age. With these challenges and opportunities in mind, we turn to similar problems with the cognitive exercise literature.

Studies of cognitive exercise: familiar considerations Recently, we have seen an explosion in research and commercial ventures aiming to enhance cognition in older adults through cognitive exercises (Kelly et al., 2014a; Kueider, Parisi, Gross, & Rebok, 2012; Reijnders, van Heugten, & van Boxtel, 2013; Rabipour & Raz, 2012). This work is motivated in part by observations of an association between cognitive stimulation throughout life and successful cognitive aging (e.g., Smart, Gow, & Deary, 2014). This research follows a similar logic to the work on physical exercise, and as a consequence it suffers from many of the same methodological imperfections as physical exercise research. Rather than attempting

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an exhaustive review of this vast literature, here we point out parallel considerations for cognitive exercise as for physical exercise research.

What, exactly, is cognitive exercise? What real-life activities count as cognitive exercise? Formal schooling? Interacting with different people socially or at work? Crossword puzzles? Poker? Meditation? Although most researchers would agree on the first activity, that is where the consensus ends. Consequently, longitudinal observational studies are inconsistent on the activities that count as “cognitive exercise.” One potential way around this problem is to introduce and control a particular cognitive training program. This can range from specific, targeted activities such as strategy training (Foer, 2011; Skidmore et al., 2011) and other unitary training modules (Jobe et al., 2001) to more general approaches including video games (Green & Bavelier, 2008), meditation (Kozasa et  al., 2011), and leisure activities involving socialization or strategies (e.g., Tesky, Thiel, Banzer, & Pantel, 2011). In future, it will be helpful for the field to establish more refined, standardized distinctions between such terms as “cognitive training,” “cognitive rehabilitation,” and “cognitive stimulation” (Bahar-Fuchs et  al., 2013). These classifications could be based on the intervention’s specific objectives (e.g., to enhance a typical function vs. treat impairment) and approach (e.g., computerized tasks vs. non-invasive brain stimulation).

How should cognitive exercise be measured? Similar to physical exercise, researchers usually choose between subjective and objective measures of cognitive exercise. Subjective reports (i.e., self-report on questionnaires, diaries, logs, et cetera) are of limited value, due to the distorting influences of impression management, demand characteristics, and faulty memory (Kanfer, 1970). Although objective measures are to be preferred, they can still be inaccurate (Shipstead, Redick, & Engle, 2012). For instance, computerization of cognitive exercises is often seen as a relatively easy way to facilitate administration of training and monitoring of performance. Yet, at the very least, remote, automated monitoring of performance makes it difficult to control the environment in which each person completes his/her cognitive exercises (typically at home). Even if participants are producing training data that look normal, it can be difficult to verify that people are actually doing what they’re supposed to during training (for example, not completing their computer exercises while also watching television and conversing with family members), and, indeed, difficult to verify that the data are actually being produced by the participants in question (rather than by someone else). In these types of situations it is probably best to “trust but verify,” erring on the side of caution in monitoring participants’ behaviour (for example, using web-cams, personal login codes, random in-person checks, and so forth). It should also be emphasized that objective measures are not immune to impression management and demand characteristics (Kanter, Kohlenberg, & Loftus, 2004).

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How much cognitive exercise is required for maximal effectiveness? Similar to physical exercise, many people would probably intuit that “more is better” regarding cognitive training (Rabipour & Davidson, 2015). At present, however, we have woefully little information on how often cognitive training should occur, how long sessions should be, or over how long a term to produce maximal benefits for cognition. So far, two meta-analyses of cognitive training have failed to find consistent evidence that “more is better” in healthy older adults (Karbach & Verhaeghen, 2014; Lampit, Hallock, & Valenzuela, 2014). Note, however, that these comparisons were all across different studies, which used different cognitive exercise protocols; it is all too rare for different levels of intensity of the same cognitive exercise protocol to be contrasted within the same study. One additional complication is that follow-up “booster” sessions are sometimes administered as part of cognitive training protocols. These can take place months or years after the initial training, and their presence and timing may influence the likelihood of training success (Willis & Caskie, 2013; Wolinsky, Vander Weg, Howren, Jones, & Dotson, 2015).

What are the likely cognitive effects? Similar to physical exercise, the targets of cognitive exercise studies are often those cognitive functions that decline the most in aging. Cognitive training presents a unique challenge, however: That of generalization or transfer of training. Specifically, improvements following cognitive training should generalize or transfer to tasks that draw on the same underlying cognitive and neural processes but are not exactly the ones that were trained. Ideally, cognitive training should also lead to improvements on everyday activities rather than solely on laboratory tasks that measure isolated cognitive functions (Bugg & McDaniel, 2012; McDaniel et al., 2014). The question of generalization/transfer remains the focus of vigorous debate. Many initial studies demonstrated benefits of cognitive training by showing improvement on tasks that closely resembled the cognitive training exercises. However, such a narrow improvement may simply represent “training-to-task” or practice effects. Mounting criticism has propelled a new generation of research seeking evidence of transfer of training to untrained measures of cognition, wellbeing, and clinical symptoms (e.g., Morimoto et al., 2014; Schmiedek, Lovden, & Lindenberger, 2010; Wolinsky et al., 2006; Wolinsky et al., 2015). In some cases, these transfer effects have been claimed to last for several years (Rebok et al., 2014), leading to high hopes for long-term sustainability. Transfer may become more likely when training involves game-like programs that require adaptive and independent learning, and tap multiple cognitive modalities, compared to simpler approaches such as strategy training (Green & Bavelier, 2008; Morrison & Chein, 2011). In cases where focused training is desirable, and perhaps even necessary for transfer (e.g., for rehabilitative or therapeutic purposes), game-like programs can be streamlined for ease of training or to provide explicit

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guidelines. Nevertheless, current evidence for the generalization of cognitive exercise programs is weak, and how to optimize transfer is uncertain.

What are the likely brain effects? The effects of cognitive training on brain structure will probably differ based on the type of cognitive exercises undertaken. Myriad studies suggest that increased activation of brain regions underlying commonly-used functions can lead to increases in the volume and connectivity of that region. For example, London taxi drivers develop larger posterior hippocampi, probably related to the spatial memory demands of their training (Maguire, Woollett, & Spiers, 2006; Woollett & Maguire, 2011), and professional musicians tend to have broader cortical representations of finger somatosensation and motor control, and also of auditory, spatial, and motor processing (Elbert, Pantev, Wienbruch, Rockstroh, & Taub, 1995; Gaser & Schlaug, 2003). Non-musicians who undergo auditory discrimination training, moreover, show post-training improvements in pitch discrimination and enhanced neural activity patterns (Bosnyak, Eaton, & Roberts, 2004). Similarly, learning complex tasks such as juggling appears to increase grey and white matter densities in areas related to visual processing (Draganski et  al., 2004; Scholz, Klein, Behrens, & JohansenBerg, 2009). We are only beginning to scratch the surface regarding cellular and molecular effects of cognitive exercise, but potential variables of interest include neurogenesis (van Praag et al., 2002), development of dendritic branches or spines (Xerri, 2011), and increased myelination of axons (Zatorre, Fields, & Johansen-Berg, 2012). The theory behind these suggested mechanisms is that repetitive practice of a cognitive task will strengthen the neural mechanisms that underlie the targeted behaviour (McNab et al., 2009). In addition, hippocampal neuroplasticity following cognitive training has been linked to an increase in brain-derived neurotrophic factor (BDNF; Lu, 2003).

What other factors must be ruled out? As with physical exercise, potentially confounding variables including physical health, personality, sleep, mood, and social stimulation must be ruled out. Traditionally, such factors have largely remained unaddressed in studies of cognitive exercise, despite evidence suggesting that individual differences in these may independently influence cognition (Fratiglioni, Paillard-Borg, & Winblad, 2004). In additional, motivation, engagement, and expectation of outcomes can influence the effects of cognitive intervention (Boot, Simons, Stothart, & Stutts, 2013; Rabipour & Davidson, 2015). Motivations for taking part in a cognitive exercise study can be complex. For instance, cognitive health is a particular concern of many middle-aged and older adults, and so one might predict that a stronger sense of one’s cognitive decline would lead to a stronger motivation for cognitive intervention. In people with mild cognitive impairment, however, perceived degree of cognitive decline may be a less powerful motivation than in healthy people (Werheid, Ziegler, Klapper, & Kuhl, 2010).

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Who benefits? Commercial advertisements often suggest, either explicitly or implicitly, that everyone can benefit from cognitive exercise. The nascent scientific literature, however, suggests that the benefits of cognitive training are not straightforward. Basic characteristics such as age (Toril, Reales, & Ballesteros, 2014) and sex (Li, 2014) can influence the likelihood of success. Further, baseline abilities may be important. Some cognitive training studies have observed a “Matthew effect,” whereby the “cognitively rich” grow richer after training. In other words, people with greater baseline cognitive abilities, younger ages, or higher education levels show greater improvement than those with lesser cognitive abilities, older ages, or lower education levels (Lustig & Flegal, 2008; Stamenova et al., 2014; Willis & Caskie, 2013; but see Kulzow et al., 2014; Kelly et al., 2014a). Further complicating matters, even one’s perceived quality of life and perceived baseline cognitive functioning can influence training outcomes (a “pseudo-Matthew effect”; McDougall & House, 2012). The effects of cognitive exercise, including the extent to which different people benefit, may depend on the context in which the exercise occurs. High-functioning older adults may benefit most from challenging, complex game-based software that combines multiple types of tasks and requires adaptive problem solving. Such programs recruit several cognitive processes and might therefore provide more generalizable benefits (Morrison & Chein, 2011). Improvements in a range of cognitive abilities – including memory, processing speed, visuospatial skills, and cognitive control – have been reported in healthy older adults following training with various multimodal programs (Anguera et al., 2013; Lampit et al., 2014). These programs may be more successful when administered in groups or in the laboratory, rather than at home (Wadley et al., 2006). On the other hand, simpler or highly specific cognitive exercises may help regain specific functions lost as a result of injury or disease (Gross et al., 2012; Reijnders et al., 2013), as part of rehabilitative programs. Identifying the primary goal of cognitive exercise – i.e., to uphold or improve normal-level performance vs. restore an impaired function – is fundamental to determining what type of activity has the greatest likelihood of yielding the desired results. Across the various populations and protocols to date, cognitive exercise studies have been seriously under-powered (Bogg & Lasecki, 2014; Karbach & Verhaeghen, 2014), so advance planning of who you will include in your study, and of how you will conduct your analyses, is paramount.

Combining physical and cognitive exercise: a promising but under-researched topic Integrating physical exercise with cognitive training might maximize cognitive benefits. For example, one could imagine that exercising cognitive faculties such as working memory (WM) might produce local changes in the specialized brain substrates supporting these functions (e.g., in the prefrontal and parietal cortex circuits supporting performance) that would build on the more widespread changes

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brought on by physical exercise (e.g., increased blood flow and synaptogenesis). Two broad approaches have been taken: The first is to merge physical with cognitive training in the same task, for instance exercising with virtual reality games (“exergames”) using haptic interfaces and motion trackers (Moreau & Conway, 2013). Such platforms aim to increase aerobic capacity, muscle strength, flexibility, and balance, while participants complete cognitively demanding tasks. There is reason to think that these may be beneficial. Dual-task training, for example, may facilitate greater improvement compared to single-task training (Erickson et al., 2007), particularly when the program includes both a motor and a cognitive component (Wu, Liu, Hallett, Zheng, & Chan, 2013). These games are offered by commercial interests [Wii (Nintendo, 2014), EyeToy (Sony Computer Entertainment America LLC, 2014), and X-Box (Microsoft, 2014)] and not-for-profit ones [e.g., The Long Lasting Memories (LLM) Project (2009), (Bamidis, 2013)]. Although enthusiasm among potential users, clinicians, and researchers is high, few studies have been published on these platforms so far. Nevertheless, one positive early report stands out: Exergaming with the Nintendo Wii led to improved cardio-respiratory fitness and executive function and processing speed (albeit, compared to no-treatment controls) after 24 hours of training over two weeks (Maillot, Perrot, & Hartley, 2012). The second approach is a factorial one, in which physical and cognitive stimulation are crossed to examine the individual, combined, and possibly synergistic effects of the two. In a few cases, combining physical and cognitive training has appeared to be especially powerful. For example, in healthy seniors combined memory and aerobic training was reported to have a greater beneficial effect on memory compared to training on only one or the other (Fabre, Chamari, Mucci, Masse-Biron, & Prefaut, 2002; Fabre et al., 1999; Shah et al., 2014). In adults over 75 years of age, combined cognitive and non-aerobic exercise – compared to cognitive exercise alone – was reported to enhance attention, memory, processing speed, everyday functioning, objective health status, and self-rated depression (Oswald, Gunzelmann, Rupprecht, & Hagen, 2006). These improvements lasted up to five years. Effects of combined training, however, are often small, restricted to specific functions, or no greater than the effects of physical training alone or cognitive training alone. For example, following 10 weeks of simultaneous physical exercise – walking on a treadmill – and verbal WM training, healthy older adults improved on measures of learning, executive control, reasoning, memory span and speed of information processing, compared to controls (Theill, Schumacher, Adelsberger, Martin, & Jancke, 2013). The benefit of combining WM training and walking was only apparent for paired-associates learning. People who completed physical exercise alone, training on verbal WM alone, or both, improved equally on other cognitive measures (see also Linde & Alfermann, 2014; Shatil, 2013). Similarly, a more recent study (McDaniel et  al., 2014) examined the separate and combined effects of aerobic exercise – a choice between supervised treadmill walking or cycling – and cognitive training in healthy community dwelling older adults, controlling for the degree of

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social interaction in all groups. Rather than using the standard cognitive/neuropsychological measures to assess cognitive functions in isolation from one another (e.g., attention, memory, executive function), the researchers used outcome measures based on functional everyday tasks adapted for laboratory administration, including cooking breakfast (Craik & Bialystok, 2006), planning a Virtual Week (Rendell & Craik, 2000), and remembering important health information. Members of the aerobic exercise groups improved in VO2 max following the training, but showed no improvements on the cognitive outcome measures. The cognitive training led to a modest improvement on the real-world measure of prospective memory (the Virtual Week), but nothing more. Combining physical and cognitive training provided no special advantage. The literature on combining physical and cognitive exercise is still meagre, likely because such studies are particularly resource-intensive. For example, at the time we wrote this chapter, Law, Barnett, Yau, and Gray (2014) could find fewer than a dozen trials combining physical and cognitive exercise. Many of these used small samples, and only one was rated as being of high methodological quality. There is a great need for high-quality studies on the potential benefits of combining physical and cognitive training, both in healthy older adults and in those manifesting cognitive decline.

Practical research tips good, better, and best designs: addressing as many considerations as possible Undertaking any research project entails making choices, because we are rarely if ever given the funding, time, participants, equipment, and other resources that the research question truly warrants. Nonetheless, thinking about the list of topics we have reviewed above should help in guiding choices during the design of one’s research project (and the evaluation of existing research). We would argue that research on exercise and cognition falls along a continuum from good (enough?) to better to best research methods, with the evidence generated by them progressing, respectively, from relatively weak to stronger to strongest.

Good (enough?) Hundreds of retrospective self-report studies have shown that physical and cognitive exercise are correlated with cognition. Self-reports have been considered sufficient in the past, but their time may be coming to an end. Recently, Dhurandhar et al. (2015) have gone so far as to argue that self-report measures of exercise and caloric intake are so poor that they should be abandoned immediately by researchers: “We go beyond the commonly voiced view that self-report measures . . . are imperfect but nevertheless suitable for use, and offer the contrary view that they are so poor as measures . . . that they no longer have a justifiable place in scientific research [italics added].” We agree.

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Better Better studies use prospective methods and measure exercise objectively. As mentioned above, this is getting easier: It is now feasible to track physical (and cognitive) activity in large numbers of people, over the long term, in a relatively unobtrusive way (for example, using participants’ smartphones). Better studies also include a control group and/or incorporate control variables into analyses, although the best way to do so can vary from study to study. It should go without saying that better studies explicitly estimate power and effect size, and from this plan for an adequate number of participants (including the possible need to over-sample to mitigate the effects of drop-out over time). Better studies also address participants’ willingness and capacity to adhere to the intervention. Treatment adherence varies widely across studies, particularly those merging virtual reality or gaming systems with physical activity (Miller et al., 2014). This can influence the program’s chances of success (and the interpretability of the data), but can be addressed through careful design. Strategies for reducing drop-out include inconspicuous monitoring of participants (e.g., using digital technology), face-to-face interactions with trainers and small groups of fellow participants (Bamidis, 2013), and visits to a training center.

Best Trials that use the “gold standard” of a randomized, double-blind, placebo-controlled (RDBPC) design are needed urgently. The field has probably matured to a point where open-label designs, no-contact control groups, and case studies are of limited use. This is not to say that the RDBPC design is perfect. This work is expensive and time-consuming. Further, even with the most rigorous RDBPC design it can be difficult to make physical exercise truly double-blind (although for a clever attempt to address this see Stothart, Simons, Boot, & Kramer, 2014), and to prevent imitation of treatment (i.e., imitation bias, where the control group adopts the behaviours of the experimental group). Furthermore, even when researchers do their best to minimize the influence of expectations by blinding both participants and experimenters, high expectations held by many participants before they begin the trial may inflate the apparent benefits of the intervention (Rabipour & Davidson, 2015). To combat these problems, several strategies are possible. To tease treatment effects apart from expectation effects in other literatures, researchers often use a balanced placebo design: Half of the members of the treatment and control groups are told they are in the treatment condition (and should expect an effect), whereas the other half are told they are in the placebo condition. This is an under-used method in research on exercise and cognition. A useful alternative is a parametric design, in which all participants are subject to exercise (and, thus, all participants should expect to benefit), but at different levels (for example, low-, medium-, and highlevels), with no knowledge of level to which they have been assigned, or even of the other groups’ existence. This method helps all participants think they are part of the “active” group (rather than the placebo control group), and as a bonus addresses

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the question of whether a higher “dose” of exercise leads to a better cognitive outcome. Of course, using a parametric design still requires careful thinking about how to define and measure exercise, as we have reviewed above. The clearest evidence of an intervention’s success would come from comparing two groups – the intervention group and a close control group – that are similar on baseline cognitive performance, with only the intervention group showing improved cognition after the physical or cognitive exercise program. In other words, we should see a statistically significant interaction between group and time. Regrettably, this logic is followed all too rarely (Nieuwenhuis, Forstmann, & Wagenmakers, 2011). What should the control group(s) be? The best control will vary depending on the situation or group of interest. In high functioning, active older adults, an appropriate comparison for a physical or cognitive exercise intervention might be other physically, cognitively, and/or socially stimulating activities, whereas in patient populations the best comparisons might be other forms of treatment. In many cases using multiple control conditions or groups is advisable. A so-called “active control” group (i.e., a group that undergoes a comparable type of program or treatment, but without the key component believed to yield the desired results) can help minimize confounding factors such as desire to participate in an intervention, motivation, and expectation of outcomes (Boot et al., 2013). In addition, many studies might benefit from also including a no-contact group – a group tested on the same cognitive outcome measures at the same time intervals as the other groups, to account for practice effects and factors related to the passing of time or the natural progression of disease.

Conclusions Studies of physical and cognitive exercise in aging are accumulating, and interest in the topic is growing exponentially. No research method is perfect, and all study designs can potentially provide useful information. Yet, the information yielded by a research project will depend crucially on the specific details taken into account during its design and implementation. Following our suggestions will not guarantee unanimity across the literature: For example, even when researchers conduct similar exercise intervention protocols to one another and see similar cardiorespiratory benefits between studies, the cognitive outcomes can conflict (compare McDaniel et al., 2014 and Colcombe et al., 2004). But addressing the issues we have outlined in this chapter will make it easier to compare one study with another, and make one more confident in one’s new data. To be clear, we are not claiming that there is no relation between exercise and healthy cognitive aging. Rather, we have endeavored to point out how much work is still needed to understand this relationship. Given how often it has been assumed that there is a direct, causal relationship between exercise and healthy cognitive aging, the relative lack of strong experimental evidence to support this supposition is disquieting. Considering the questions we have highlighted in this chapter should help us make future studies more informative and worthwhile. With better data, hopefully soon we will know how best to exploit physical and cognitive exercise in our quest for optimal cognitive aging.

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Acknowledgements We are grateful for grant support during the preparation of this chapter from the Natural Sciences and Engineering Research Council of Canada, the Canadian Institutes of Health Research, the Alzheimer’s Society of Canada, the France-Canada Research Fund, and les Fonds de la recherche du Québec – Santé.

Note 1 In January 2015, the actor Jeff Goldblum recounted to talk-show host David Letterman and his audience that his previous Fitbit device erroneously registered his piano-playing as footsteps.

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Schmiedek, F., Lovden, M., & Lindenberger, U. (2010). Hundred days of cognitive training enhance broad cognitive abilities in adulthood: Findings from the COGITO study. Front Aging Neurosci, 2. doi: 10.3389/fnagi.2010.00027 Scholz, J., Klein, M. C., Behrens, T. E. J., & Johansen-Berg, H. (2009). Training induces changes in white-matter architecture. [10.1038/nn.2412]. Nature Neuroscience, 12(11), 1370–1371. doi: http://www.nature.com/neuro/journal/v12/n11/suppinfo/nn.2412_S1.html Shah, T., Verdile, G., Sohrabi, H., Campbell, A., Putland, E., Cheetham, C., . . . Martins, R. N. (2014). A combination of physical activity and computerized brain training improves verbal memory and increases cerebral glucose metabolism in the elderly. Transl Psychiatry, 4, e487. doi: 10.1038/tp.2014.122 Shatil, E. (2013). Does combined cognitive training and physical activity training enhance cognitive abilities more than either alone? A four-condition randomized controlled trial among healthy older adults. Frontiers in Aging Neuroscience, 5. doi: 10.3389/ Fnagi.2013.00008 Shipstead, Z., Redick, T. S., & Engle, R. W. (2012). Is working memory training effective? Psychological Bulletin, 138(4), 628–654. doi: 10.1037/A0027473 Skidmore, E. R., Holm, M. B., Whyte, E. M., Dew, M. A., Dawson, D., & Becker, J. T. (2011). The feasibility of meta-cognitive strategy training in acute inpatient stroke rehabilitation: Case report. Neuropsychological Rehabilitation, 21(2), 208–223. Smart, E. L., Gow, A. J., & Deary, I. J. (2014). Occupational complexity and lifetime cognitive abilities. Neurology, 83(24), 2285–2291. doi: 10.1212/WNL.0000000000001075 Smith, P. J., Blumenthal, J. A., Hoffman, B. M., Cooper, H., Strauman, T. A., Welsh-Bohmer, K., . . . Sherwood, A. (2010). Aerobic exercise and neurocognitive performance: A metaanalytic review of randomized controlled trials. Psychosomatic Medicine, 72(3), 239–252. doi: 10.1097/Psy.0b013e3181d14633 Snowden, M., Steinman, L., Mochan, K., Grodstein, F., Prohaska, T. R., Thurman, D. J., . . . Anderson, L. A. (2011). Effect of exercise on cognitive performance in communitydwelling older adults: Review of intervention trials and recommendations for public health practice and research. Journal of the American Geriatrics Society, 59(4), 704–716. Sofi, F., Valecchi, D., Bacci, D., Abbate, R., Gensini, G. F., Casini, A., & Macchi, C. (2011). Physical activity and risk of cognitive decline: A meta-analysis of prospective studies. Journal of Internal Medicine, 269(1), 107–117. doi: 10.1111/J.1365-2796.2010. 02281.X Sony Computer Entertainment America LLC. (2014). Eyetoy: Kinetic, 2014, from http:// www.playstation.com/en-us/games/eyetoy-kinetic-ps2/ Stamenova, V., Jennings, J. M., Cook, S. P., Walker, L. A. S., Smith, A. M., & Davidson, P. S. R. (2014). Training recollection in healthy older adults: Clear improvements on the training task, but little evidence of transfer. Frontiers in Human Neuroscience, 8. doi: 10.3389/ Fnhum.2014.00898 Stothart, C. R., Simons, D. J., Boot, W. R., & Kramer, A. F. (2014). Is the effect of aerobic exercise on cognition a placebo effect? Plos One, 9(10). doi: 10.1371/journal.pone.0109557 Tesky, V. A., Thiel, C., Banzer, W., & Pantel, J. (2011). Effects of a group program to increase cognitive performance through cognitively stimulating leisure activities in healthy older subjects. GeroPsych: The Journal of Gerontopsychology and Geriatric Psychiatry, 24(2), 83–92. Theill, N., Schumacher, V., Adelsberger, R., Martin, M., & Jancke, L. (2013). Effects of simultaneously performed cognitive and physical training in older adults. BMC Neuroscience, 14. doi: Artn 103 10.1186/1471-2202-14-103 Toril, P., Reales, J. M., & Ballesteros, S. (2014). Video game training enhances cognition of older adults: A meta-analytic study. Psychology and Aging, 29(3), 706–716. doi: 10.1037/A0037507

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Uth, N., Sorensen, H., Overgaard, K., & Pedersen, P. K. (2005). Estimation of VO2max from the ratio between HRmax and HRrest—the heart rate ratio method. European Journal of Applied Physiology, 93(4), 508–509. doi: 10.1007/S00421-004-1268-1 Uttl, B. (2005). Measurement of individual differences: Lessons from memory assessment in research and clinical practice. Psychol Sci, 16(6), 460–467. doi: 10.1111/j.09567976.2005.01557.x van Gelder, B. M., Tijhuis, M. A. R., Kalmijn, S., Giampaoli, S., Nissinen, A., & Kromhout, D. (2004). Physical activity in relation to cognitive decline in elderly men—the FINE study. Neurology, 63(12), 2316–2321. van Praag, H., Schinder, A. F., Christie, B. R., Toni, N., Palmer, T. D., & Gage, F. H. (2002). Functional neurogenesis in the adult hippocampus. Nature, 415(6875), 1030–1034. doi: 10.1038/4151030a Vemuri, P., Lesnick, T. G., Przybelski, S. A., Knopman, D. S., Preboske, G. M., Kantarci, K., . . . Jack, C. R., Jr. (2015). Vascular and amyloid pathologies are independent predictors of cognitive decline in normal elderly. Brain, 138(Pt 3), 761–771. doi: 10.1093/brain/awu393 Voelcker-Rehage, C., & Niemann, C. (2013). Structural and functional brain changes related to different types of physical activity across the life span. Neuroscience and Biobehavioral Reviews, 37(9), 2268–2295. doi: 10.1016/J.Neubiorev.2013.01.028 Wadley, V. G., Benz, R. L., Ball, K. K., Roenker, D. L., Edwards, J. A., & Vance, D. E. (2006). Development and evaluation of home-based speed-of-processing training for older adults. Archives of Physical Medicine and Rehabilitation, 87(6), 757–763. doi: 10.1016/J. Apmr.2006.02.027 Warren, J. M., Ekelund, U., Besson, H., Mezzani, A., Geladas, N., & Vanhees, L. (2010). Assessment of physical activity—a review of methodologies with reference to epidemiological research: A report of the exercise physiology section of the European Association of Cardiovascular Prevention and Rehabilitation. European Journal of Cardiovascular Prevention & Rehabilitation, 17(2), 127–139. doi: 10.1097/Hjr.0b013e32832ed875 Werheid, K., Ziegler, M., Klapper, A., & Kuhl, K. P. (2010). Awareness of memory failures and motivation for cognitive training in mild cognitive impairment. Dementia and Geriatric Cognitive Disorders, 30(2), 155–160. doi: 10.1159/000318755 Willis, S. L., & Caskie, G. I. (2013). Reasoning training in the ACTIVE study: How much is needed and who benefits? J Aging Health, 25(8 Suppl), 43S–64S. doi: 10.1177/0898264313503987 Wolinsky, F. D., Unverzagt, F. W., Smith, D. M., Jones, R., Wright, E., & Tennstedt, S. L. (2006). The effects of the ACTIVE cognitive training trial on clinically relevant declines in health-related quality of life. Journals of Gerontology—Series B Psychological Sciences and Social Sciences, 61(5), S281–S287. Wolinsky, F. D., Vander Weg, M. W., Howren, M. B., Jones, M. P., & Dotson, M. M. (2015). The effect of cognitive speed of processing training on the development of additional IADL difficulties and the reduction of depressive symptoms: Results from the IHAMS randomized controlled trial. J Aging Health, 27(2), 334–354. doi: 10.1177/0898264314550715 Woollett, K., & Maguire, E. A. (2011). Acquiring “the Knowledge” of London’s layout drives structural brain changes. Current Biology, 21(24), 2109–2114. doi: 10.1016/J. Cub.2011.11.018 Wu, T., Liu, J., Hallett, M., Zheng, Z., & Chan, P. (2013). Cerebellum and integration of neural networks in dual-task processing. Neuroimage, 65, 466–475. doi: 10.1016/J. Neuroimage.2012.10.004 Xerri, C. (2011). Experience-Dependent Reorganization of Somatosensory and Motor Cortical Areas: Towards a Neurobiology of Rehabilitation. In H. Duffau (Ed.), Brain

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3 NUTRITION, HEALTH AND THE AGEING PROCESS Peters, Riccarda, White, David and Scholey, Andrew

Introduction During early development, our cognitive abilities improve, peaking in young adulthood, after which they remain relatively steady until some level of decline with old age. However, this decline is not inevitable and depends on both the individual and the specific cognitive domain in question (Craik & Bialystok, 2006). The deficits in cognitive abilities associated with age have been termed ‘Age-related cognitive decline’ (ARCD). They can be observed in a wide spectrum of cognitive functions, spanning attention, episodic memory, spatial ability, processing speed to executive function (Verhaeghen & Cerella, 2002). Up to half of all adults over the age of 64 years report experiencing difficulties with their memory (Reid & MacLullich, 2006). In addition to the observed normal cognitive decline with aging, it has been estimated that around 46.8 million people worldwide live with dementia, a number predicted to reach 74.7 million by the year 2030 (Ali, Guerchet, Wu, Prince, & Prina, 2015). The most prevalent form of dementia is Alzheimer’s disease (AD), of which it is estimated that there is a new case every seven seconds (Cornutiu, 2015). Distinct from dementia is a syndrome termed mild cognitive impairment (MCI). MCI has been operationally defined as cognitive decline that is more severe than expected given an individual’s age and education level, but not notably affecting activities of daily life (Gauthier et al., 2006). MCI has consistently been shown to be a frequent precursor to overt dementia, especially of the Alzheimer’s type, and thus has been conceptualised as a transition state between normal aging and dementia. Less severe forms of cognitive impairment include age-associated memory impairment (AAMI) and subjective memory impairment (SMI) both of which increase AD risk. SMI, AAMI and MCI represent realistic targets for interventions that may protect against future dementia, including through diet. This chapter will discuss the role of nutrition in cognitive aging, where research exploring omega-3 fatty

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acids and the Mediterranean diet will be the focus. Research tips based around the literature exploring the role of nutrition, and omega-3 fatty acids and the Mediterranean diet in particular, will conclude the chapter.

Aging What causes ARCD and dementia? Although various hypotheses have been proposed to explain the etiology of cognitive decline, it is not fully understood and it is not clear what can be done in order to prevent it. A number of factors have been suggested to play significant roles in cognitive decline. The list includes depletion of endogenous antioxidants (Gracy, Talent, Kong, & Conrad, 1999), elevation in nitric oxide (Calabrese et al., 2007) and homocysteine (HCy) levels (Haan et al., 2007), chronic inflammation (Zipp & Aktas, 2006), glutamatergic excitotoxicity (Hynd, Scott, & Dodd, 2004), accumulation of redox metals (Rogers & Lahiri, 2004), mitochondrial dysregulation (Kidd, 2005), as well as abnormal insulin levels and/or responsiveness (Craft & Watson, 2004). It is believed that in AD the brain undergoes additional pathological changes. These include changes in brain proteins leading to the ‘hallmarks’ of AD – extracellular senile plaques containing beta-amyloid proteins and intracellular neurofibrillary tangles from abnormal processing of tau proteins. These changes cause widespread damage to neural structures, which in turn lead to profound impairments in cognitive abilities (Hardy & Selkoe, 2002; Kidd, 2008; Selkoe, 2001).

How do we treat pathologies of aging? There are a number of pharmaceutical treatments for dementia available that have been approved by the US Food and Drug Administration (FDA). These fall into two classes, there are the cholinesterase inhibitors tacrine, donepezil, rivastigmine and galantamine, on the one hand, and the N-methyl-D-aspartate receptor antagonist memantine on the other (O’Brien, Burns, & Group, 2011). Cholinesterase inhibitors are used for mild as well as moderate AD, however they are often not well tolerated. All four cholinesterase inhibitors listed here have adverse side effects including nausea, vomiting, diarrhoea, fatigue, muscle cramps and dizziness – all attributed to cholinergic hyperactivity (Jones, 2003). Few studies have assessed the efficacy of cholinesterase inhibitors for periods longer than one year and few have examined the question whether they significantly delay the progress from mild cognitive impairment (MCI) to AD (Raina et al., 2008). This has led to the search for non-pharmaceutical compounds that may delay the progression of ARCD and dementia including research into dietary compounds for their potential to target and potentially prevent cognitive decline. In light of the broad etiology of ARCD and dementia and the limitations of current pharmaceutical treatments, the research of dietary constituents for their potential to simultaneously target multiple mechanisms and prophylaxis is of increasing relevance (Van der Schyf, Gal, Geldenhuys, & Youdim, 2006).

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Can we prevent pathologies of aging? Healthy aging is best conceptualised as an ongoing process (Schulz & Heckhausen, 1996). Definitions of healthy aging vary and have been defined from various perspectives at the level of the person, society, psychology and physiology. It is likely that the best definition of healthy aging will draw from each of these perspectives to create a coherent picture (Hansen-Kyle, 2005). Various human studies have established the association between lifestyle choices and cognitive decline later in life. Exercise, avoidance of fatty foods, non-smoking, moderate alcohol consumption and mental and social engagement have been linked to a reduced risk of ARCD (Weih, Wiltfang, & Kornhuber, 2007). Healthy dietary patterns and nutritional factors are also commonly reported as being associated with a decreased risk for dementia (Mangialasche, Kivipelto, Solomon, & Fratiglioni, 2012). The saying ‘you are what you eat’ is relevant to cognitive aging. Nutrition plays a very important role in brain health, throughout the lifespan. First, the brain is provided with energy (mainly glucose) directly and indirectly from food. In addition, food provides building blocks of the brain-like lipids and amino acids, and a healthy diet contains micronutrients that are required for enzymatic and endocrine processes, for instance iron, zinc and B-vitamins. Further, food can deliver bio- or psychoactive molecules that play roles in a variety of actions relevant to the brain (Schmitt, 2010). Some realistic targets for dietary interventions are shown in Figure 3.1. The association between diet and certain diseases has attracted a great deal of attention (de Groot, van Staveren, & Burema, 1996). It is now widely accepted that a healthy dietary pattern can reduce morbidity and mortality risk. Several dietary practices as well as specific nutrient components of these diets have been researched

FIGURE 3.1 Influences on cognitive aging. Grey panels show target processes where dietary change (including omega-3s, flavanols and Mediterranean diet) could realistically benefit cognitive performance.

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in relation to healthy aging and cognitive performance. Below, two examples of this relationship will be considered: the Mediterranean diet and omega-3 fatty acids.

The Mediterranean diet and cognition The Mediterranean diet (MedDi), traditionally followed by inhabitants of the countries bordering the Mediterranean Sea, can be better summarised as a collection of eating habits, than a specific diet per se (Sofi, Abbate, Gensini, & Casini, 2010). MedDi is characterised by high consumption of vegetables, fruit, legumes, cereals and fish, lower consumption of meats and dairy products, and moderate consumption of red wine as well as the use of olive oil as the main source of fat (Trichopoulou, Bamia, & Trichopoulos, 2009). This dietary pattern has been linked to a lower risk of all-cause mortality, death from cardiovascular disease (CVD) and cancers, obesity and age-related diseases of the brain including Parkinson’s and Alzheimer’s disease (Martinez-Gonzalez & Bes-Rastrollo, 2014; Sofi et al., 2010; Sofi, Cesari, Abbate, Gensini, & Casini, 2008). These findings have been observed in multicentre studies across a range of countries, suggesting the benefits of MedDi may be generalisable (Couto et al., 2011; Sofi et al., 2010; Sofi et al., 2008). While these prospective cohort studies have provided evidence supporting the association between MedDi and health, it is not a simple task to study diet as an intervention. Two recent studies from our research group have demonstrated potential positive outcomes associated with even short-term periods of dietary change towards MedDi. These two studies, both investigating the effects of 10-days adherence to MedDi, reported positive mood effects, with possible benefits to cardiovascular indices and secondary memory (Lee et al., 2015; McMillan, Owen, Kras, & Scholey, 2011). Randomised Controlled trials (RCTs) using MedDi are difficult to conduct, with challenges associated with controlling a number of confounding factors, such as ensuring adherence to the diet and defining the characteristics of the intervention. Efforts to assess compliance with MedDi interventions typically rely on self-report instruments that describe the intake of MedDi components. Validated food frequency questionnaires exist for adherence to MedDi based on daily intake (Panagiotakos, Pitsavos, Chrysohoou, & Stefanadis, 2005; Rumawas et  al., 2009; Trichopoulou, Costacou, Bamia, & Trichopoulos, 2003). To date, considerable heterogeneity in what constitutes the MedDi intervention also complicates the comparability of results across studies. Sources of heterogeneity are manifold and include the type and length of intervention, mode of delivery of intervention, study design, sex, ethnicity and geographic origin of studies (Lara et al., 2014) as well as the assessment of efficacy of the intervention. Due to these issues with interpretation, an alternative strategy has been to evaluate the cognitive effects of single nutrients. Several dietary constituents have been found to be protective against ARCD, including antioxidants, vitamins E and C and B vitamins (B6, B12 and folate) (Smith & Blumenthal, 2010). One of the most widely researched components are fish-derived long chain omega-3 fatty acids eicosapentaenoic acid (EPA) and

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docosahexaenoic acid (DHA). The following sections will examine some of the research that established the connection behind the link of omega-3 fatty acids and brain health, illustrate how these components can be studied and emphasise potential methodological issues with the study of specific nutrients and brain functioning.

Omega-3 fatty acids and brain function There are two general subtypes of dietary fatty acids: unsaturated fatty acids and saturated fatty acids. The primary sources for saturated fatty acids are meat and dairy products and over-consumption of saturated fatty acids is generally associated with unfavourable health outcomes. The consumption of saturated fatty acids has dramatically increased in Western civilization over the past 100 years, while the intake of omega-3 FAs has decreased (Gómez-Pinilla, 2008). Illustrating a possible link between nutrition and brain function, it has been suggested that the increased occurrence of major depression in countries like the USA and Germany may be partly explained through this relationship (Hibbeln, 1998). Unsaturated fatty acids can be further divided into monounsaturated (MUFAs) and polyunsaturated fatty acids (PUFAs). PUFAs in turn can be divided further into n-3 and n-6 PUFAs, which are commonly referred to as omega-3 and omega-6 fatty acids (FA). Omega-3 PUFAs consist of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Omega-3 FAs are typically derived from fish and marine sources. Omega-6 FAs on the other hand consist of α-linoleic acid (ALA) and are derived from nuts, legumes and other plant-based sources (Smith & Blumenthal, 2010). A common finding in research regarding nutrition has been that greater fat intake is associated with greater cognitive dysfunction and dementia. However, greater consumption of omega-3 FAs compared to omega-6 FAs has been associated with reduced risk of these outcomes. With regards to the link between healthy cognitive aging and nutrition, a number of mechanisms have been identified through which the ratio of omega-3 to omega-6 FA intake may protect against ARCD. These mechanisms include alterations in the metabolism of cholesterol, reduction of inflammation in the brain, modulation of central growth factors and alterations in neuronal signal processing (Boudrault, Bazinet, & Ma, 2009). The brain is highly enriched in DHA, making up 15–25% of total fatty acids compared to less than 5% in most other body tissues. DHA performs numerous structural and metabolic roles, particularly at the synapse. However, the human body is not efficient in the synthesis of DHA, making us dependent on dietary DHA (Crawford et al., 1999). EPA makes up only about 1% of total brain fatty acid, however, it is thought to be neuroprotective possibly through indirect effects on the cerebral vasculature. Studies in both animals and humans have shown that low dietary fish (EPA + DHA) intake leads to low levels of omega-3 fatty acid status, which in turn is associated with neurocognitive dysfunction as well as a greater risk of cognitive decline and dementia (Cunnane et al., 2009; Schaefer, Bongard, Beiser, et al., 2006; Tully et al., 2003).

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Furthermore, lower plasma and red blood cell EPA and DHA levels (markers of systemic levels) are associated with smaller brain volume as well as atrophy in brain regions associated with dementia (e.g. the medial frontal lobe) (Samieri et al., 2012; Tan et al., 2012). Prospective studies investigating the link between fatty fish intake or omega- 3 FAs and the risk of dementia or AD indicate that omega-3 FAs are associated with lower prevalence of cognitive decline and may protect against the onset of cognitive decline (Devore, Kang, Breteler, & Grodstein, 2012; Roberts et al., 2010). These findings have prompted investigations into the potential for DHA supplementation to reduce the risk or slow down the progression of AD. Findings from randomised controlled trials (RCTs) have shown that supplementation with fish oil (EPA+DHA) or DHA is of greatest benefit in individuals with mild cognitive impairment (MCI) or mild AD. Fish oil supplementation has been shown to improve cognition in samples of MCI patients (Chiu et  al., 2008; Kotani et  al., 2006). A study on the effects of omega-3 supplementation on patients with mild AD revealed a significant reduction in the Mini Mental State Examination (MMSE), a widely used test of cognitive abilities relevant to dementia.

Methodological issues in omega-3 PUFA interventions Epidemiological studies consistently report an association between high levels of DHA in plasma and membranes and a reduction in the risk for cognitive decline. It has been suggested that dietary supplementation of a small amount of DHA (as little as 180mg/day) is beneficial (Schaefer, Bongard, Beiser, Lamon-Fava, et al., 2006). This value is exceeded in most studies, but a meta-analysis reported that the dose was not related to treatment effects (Mazereeuw, Lanctot, Chau, Swardfager, & Herrmann, 2012). Therefore it has been suggested that the benefit of supplementation with omega-3 PUFAs may not be dependent on a high amount of plasma DHA, but may be contingent on exceeding and maintaining a certain threshold DHA level (Mazereeuw et al., 2012). A critical issue in a number of existing clinical trials is that baseline plasma or membrane DHA levels are not always measured. Furthermore, trial durations are relatively short (typically from 90 days to 18 months) and it is likely that this amount of time is simply too short for any beneficial cognitive effects of omega-3 FA supplementation to emerge. Animal studies have shown that omega-3 supplementation with a minimum period of 10% of the total lifespan decreased the ratio of omega-6 to omega-3 FAs, reduced the amount of amyloid-β in the brain tissue of animal models of AD, improved cognitive functioning and decreased the amount of neural loss (Hooijmans, Pasker-de Jong, de Vries, & Ritskes-Hoitinga, 2012). If these results are translated to human trials, they stress the importance for the need of more long-term human trials in order to determine the effects of fish oil supplementation. Research into the benefits of omega-3 FAs with human participants have thus far provided mixed results, demonstrating that the outcome of n-3 FA supplementation is not uniform. Thus it is important to elucidate which populations would benefit

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most from treatment (and for which populations omega-3 FAs may not be beneficial). To illustrate this, RCTs looking at the effects of omega-3 supplementation in patients with moderate or advanced AD have not shown improvements in cognitive functioning (Freund-Levi et al., 2006). Since the supplement was administered relatively late in AD progression it appears possible that it is too late in the disease process for DHA to act. This may be because the neural substrates underlying the effects of omega-3s are no longer able to respond to supplementation. Another important aspect to consider is the nutritional status of the study sample. For example, one of the largest published RCTs on omega-3 fatty acids for cognition to date showed a lack of efficacy (Dangour et al., 2009). The study included regular fish consumers (92% consumed fish at least once per week). This pattern of fish consumption is very unusual for the population (in this case UK) and therefore the study likely over-represented regular fish-consumers. For regular fish-consumers habitual omega-3 intake may be close to optimal and thus making further benefit unlikely. Therefore, when setting up an RCT it is of importance to carefully consider the target sample population, the treatment formulation and outcomes assessed (Mazereeuw et al., 2012). Research has established an important link between omega-3 consumption and brain functioning. Epidemiological studies consistently report a positive effect of EPA + DHA on reducing the risk for cognitive decline and AD. In contrast, randomized controlled trials to date have yielded mixed results. There are a number of potential reasons for these inconsistent results, including the measuring and reporting of baseline omega-3 plasma levels, the length of the intervention trials and the choice of sample populations. These are just examples of certain aspects that are important to consider when planning an intervention trial with nutritional supplements. There are many factors that can bias the outcomes of a trial and make it more difficult to compare across trials. From animal models of AD, there is evidence to suggest more long-term intervention trials are needed to allow better characterisation of potential health benefits. In addition, study outcomes have to be carefully chosen in order to best determine the efficacy of the treatment and facilitate comparison with existing literature. Comparing results across studies is not straightforward, as a result of variability in study design and outcomes. However, standards and methods for clinical trials are improving and advances in science add new valuable measures that will be useful in the future of clinical trials. The criterion standard in establishing the role of nutritional intervention in cognitive aging is the RCT (de Jager & Kovatcheva, 2010), however, RCTs are not the only source for information about the efficacy of nutritional compounds. Especially with regards to long-term effects of nutritional interventions, important insights are gained from mechanistic animal and epidemiological approaches (Schmitt, 2010). These kinds of studies have provided many hypotheses and mechanisms of the potential interactions between nutrition and cognition (Gómez-Pinilla, 2008). In order to establish support for nutritional effects on cognition, systematic reviews, meta-analyses, epidemiological studies and animal studies are all valuable.

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Epidemiological studies provide interesting insights that may contribute to our understanding of relationships between diet and cognition. However, it is essential that causal behavioural effects are demonstrated in high-quality RCTs in order to establish a solid evidence base for the effects of nutrition, which are in turn important for the associated dietary recommendations, communication and claims to the public (Benton, 2010). Particularly in the literature regarding cognitive aging, RCTs are rare compared with epidemiological studies. This lack of confirmatory RCTs may be the result of incorrect original hypotheses or it may be related to inadequate methodology in design and/or execution of the RCT.

General considerations for nutritional interventions Nutritional status When conducting an RCT on the effect of nutritional compounds, it is important to collect information about the nutritional status of participants. Reliable assessments for nutritional factors especially in people at risk for cognitive decline are still evolving (Bowman et al., 2011). The best indirect method to assess nutritional status is the Food Frequency Questionnaire (FFQ). FFQs are relatively inexpensive and can be comprehensive (Hu, 2002). With the FFQ it is possible to construct dietary patterns and in this line assess long-term dietary intake, which is the kind of dietary exposure of interest in the study of neurodegeneration (Bowman et al., 2011). However, FFQs depend on the individual’s free recall of dietary intake, which clearly can be compromised in populations with poor cognitive function. Furthermore they do not account for variability in nutrient absorption. Especially in studies with older participants these issues can be problematic (Krasinski et al., 1986). Blood tests can be used to assess nutritional status, which can be particularly useful in the study of people at risk for dementia (Bowman et al., 2011), however these bring with them additional costs. Nutritional RCTs routinely measure individual biomarkers, for instance plasma homocysteine, folic acid and vitamin B12 levels. However, it may be more informative to measure a range of biomarkers to gain a better understanding of risk factors, such as inflammatory markers of oxidative stress, markers of metabolic diseases and stable breakdown products of homocysteine metabolism (de Jager & Kovatcheva, 2010). Creating profiles of these risk factors may inform knowledge of mechanisms and pathways underlying age-related declines in cognition. Furthermore, changes in numerous biomarkers may be more sensitive than measures of single markers (de Jager & Kovatcheva, 2010).

Genetics and epigenetics One of the great achievements of the 21st century is the exploration of the human genome (Lander et  al., 2001). With the investigation of the human genome we are provided with the tools to evaluate disposition, response or the expression of a

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living system, be it a cell, an organ or an entire organism, to environmental influences. One of these environmental factors is nutrition. Through transcriptonomics, proteomics and metabonomics we can gain detailed insights of biological conditions at the levels of gene transcripts, proteins and metabolites. The information provided by each can be illustrated as follows: genetics give us a blueprint (‘what may happen’), the transcripts give us an action plan (‘what appears to happen’), proteins ‘make it happen’ and the metabolites can tell us a story (‘what has happened’) (de Jager & Kovatcheva, 2010). In terms of nutritional research, human genetics (i.e. the human genome sequence and its inter-individual variations) can provide valuable insights into several domains. They can inform us about health expectations and disease susceptibility as well as potentially distinguishing ‘non-responders’ and ‘responders’. To date, several genes have been implicated in cognitive aging. The APOE4 gene is carried by 25% of the population. Even in the so-called ‘healthy aging population’ APOE4 is associated with poorer cognitive performance (Packard et al., 2007) and faster decline in cognitive functions (Hayden et al., 2009). Furthermore, APOE4 has been identified as the greatest genetic risk factor for Alzheimer’s disease and has been associated with a two-fold higher conversion rate from MCI to AD (Fei & Jianhua, 2013; Whitehair et al., 2010), as well as with an earlier onset of AD (Corder et al., 1993). APOE4 status may also be predictive of how well people respond to treatment. For example, several studies have indicated that omega-3 PUFA supplementation does not exert its protective effect in APOE4 carriers (Huang, 2010), and that even with supplementation little change of plasma DHA levels is observed in this population (Plourde et al., 2009). Given this information, carriers of the APOE4 genotype can be identified as a ‘high-risk’ group. Developing therapies that can slow down or prevent the conversion of MCI to AD in these risk groups will bring about substantial social and economic benefits. Epigenetics, translates into ‘above genetics’, was originally used to define how genotypes produce phenotypes through programmed changes in development (Waddington, 2012). Today, epigenetics refers to the study of stable changes of the genetic material that result in gene expression and function but have no influence on the DNA sequence itself (Fraga, 2009). These changes affect DNA methylation patterns, chromatin structure and histone codes, as well as non-coding small RNAs. DNA methylation can be influenced in sensitive life phases and can persist for an entire lifespan or even several generations (Jenuwein & Allis, 2001). Therefore it appears to shape the long-term metabolic imprint of an organism. This indicates that nutrition early on in life may exert effects on health outcomes later in life. The causal relationships, interactions and overlaps between genes, nutrition and the brain are still elusive. Questions about how genes affect the development and decline of the human brain or how people differ in their responsiveness to nutritional interventions that are aimed to prevent neurocognitive decline need to be investigated (Kussmann, Krause, & Siffert, 2010). In the future genomic medicine may provide clinicians with a complex and precise tool for the diagnosis and

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treatment of individual patients (Li & Meyre, 2014). Pharmacogenomic testing is already routinely performed before certain medications are administered (Frueh et al., 2008). As foods and nutrients can affect our genes and individual differences in genetic makeup can affect the response to nutritional compounds, taking genetic factors into account will be a valuable asset to nutritional research, providing us with knowledge about underlying inter-individual differences in response to treatment and will thus help in identifying the right treatment option for patients.

Microbiome Another relatively recent significant contributor to the study of nutrition, health and disease is the study of the human microbiome (HM). The human microbiome is the collective term for the microorganisms residing in the human body. Recent investigations in various domains have been undertaken in order to understand the link between gut microbiota and their influence on brain and behaviour (Forsythe, Kunze, & Bienenstock, 2012). The HM may conduce to the regulation of several neuro-metabolic and neuro-chemical pathways, through a complex signalling system that connects host and microbiome and interconnects the gastro-intestinal tract with the central nervous system (CSN) (Bhattacharjee & Lukiw, 2013). The human gastrointestinal tract contains 95% of the HM, which is made up of a genetically very versatile microbial population. These are suggested to play major roles in a number of systems, such as nutrition, digestion, inflammation and neurotrophism (Collins, Kassam, & Bercik, 2013; Forsythe et al., 2012). The signalling between intestine and the brain is bidirectional. Interestingly the composition of the microbiome changes in the individual with age (Yatsunenko et al., 2012). In nutritional intervention studies the microbiome can be taken into account. Evaluating the disposition of the microbiota in the gut before and after an intervention can lead to valuable information regarding the link between microbiota in the gut and brain functioning.

Neuroimaging Another method that is gaining increasing popularity in nutritional RCTs is neuroimaging. Neuroimaging methods continue to improve as clinical tools, and an increasing number of intervention studies include brain imaging biomarkers as secondary endpoints, supplementing clinical and/or cognitive measures. It has been proposed that innovative measures, such as neuronal plasticity, neuronal survival and synthesis of neurotransmitters, may even replace cognition as primary endpoints in clinical trials (de Jager & Kovatcheva, 2010). Not only can neuroimaging methods improve our knowledge of mechanisms of action, they may also be more sensitive measures and may be more efficient in predicting long-term effects, and thus shorten the duration required for a clinical trial (de Jager & Kovatcheva, 2010). Available techniques include magnetic resonance imaging (MRI), which has multimodal assessment capacity, electroencephalography (EEG), magnetoencephalography

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(MEG), near-IR spectroscopy (NIRS), positron emission tomography (PET) and single-photon emission computerised tomography (SPECT) (Sizonenko et  al., 2013). These techniques give the opportunity to measure structural, physiological and chemical changes in the brain that occur over the lifespan and after nutritional interventions. They further can advance our understanding of particular biological processes that are implicated in the alterations in brain function during development and aging, as well as the way in which nutritional interventions may modulate these changes (for a review of methods and their application see Sizonenko et al., 2013). An example of the application of brain imaging in an RCT is a study on the effects of flavonoids on memory performance in older adults (Brickman et  al., 2014). Specifically neural activity was assessed using functional magnetic resonance imaging in the dentate gyrus of the hippocampus, which is a region well known for its critical role in memory and learning. The dentate gyrus is furthermore characterised as a region where new neurons are formed, and is vulnerable to age-related decline (Small, Schobel, Buxton, Witter, & Barnes, 2011). One group of adults consumed a high-flavonol diet for 12 weeks. Compared to a group of adults consuming a low-flavonol diet, these adults showed improvements in memory performance and greater cerebral blood volume in the right dentate gyrus. Importantly, a correlation was found between increased cerebral blood volume in the dentate gyrus and increased performance on an object-recognition task. Thus we can relate neural function to changes in cognitive functioning.

Conclusion Healthy aging is best conceptualised as an ongoing process (Schulz & Heckhausen, 1996). Considerable research evidence supports the link between nutrition and healthy aging, however the complex interplay between nutrition and neurocognitive health remains incompletely understood. Details of the dietary components most beneficial (or detrimental) to the healthy aging process remain to be fully elucidated with a range of research designs, yet RCTs remain a cornerstone on which to study the importance of specific nutritional components in the healthy cognitive aging process. Aging can be accompanied by cognitive decline and neurodegenerative diseases such as dementia or AD. However, certain lifestyle strategies have been identified that decrease the risk for cognitive decline and support a healthy process of aging. However, preventative strategies are not a fail-safe method and causes for cognitive decline are manifold. Currently there is no cure for dementia or AD and pharmacointerventions as treatments often have negative side effects. Furthermore, the efficacy of these pharmacointerventions is still pending to be shown. Research into specific dietary habits like the Mediterranean diet has revealed that this specific dietary pattern leads to better health outcomes and longevity. It is however difficult to study dietary habits rigorously in a controlled manner. Another venture of research that is gaining increasing attention is the study of specific nutrients and their influence on brain function and brain health and as a

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potential prophylaxis or even treatment for cognitive decline. Amongst these are omega-3 PUFAs. The effects of omega-3 PUFAs have been studied in epidemiological studies, animal studies and have been translated into human RCTs. The epidemiological evidence for the efficacy in promoting brain health in old age is promising. Further, animal studies give reason to believe that long-term intervention of these nutrients may exert even more powerful effects in slowing or even reversing cognitive decline. RCTs are considered best standard in order to study the effects of nutrients on health. However, methodological considerations have to be made. Mixed results have been found in studies and it is difficult to compare results across studies due to methodological variations. Advances in the standard of conducting RCTs in nutrition have been made and there are recommendations of measures that should be taken and reported. Nutritional status should be assessed before entrance into the study, the study population has to be carefully sampled and randomised, outcome measures should be clearly defined. Science is not standing still but always advancing, which can improve the measures we can take in order to study the effects of nutrients. New methods allow the inclusion of several biomarkers that can greatly inform our understanding of the underlying processes of the intervention, including genomics and epigenomics, the study of the microbiome and neuroimaging methods.

Practical research tips and summary 1 2 3 4

There is growing evidence that diet, mood and cognitive function are inter-related There is growing evidence that omega-3 oils, flavanols and the Mediterranean diet have positive effects on mood and cognition A healthy diet, in combination with exercise, is likely to benefit the brain in the long term These effects are likely to be more beneficial (but not restricted to) individuals with a poor diet

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Sofi, F., Cesari, F., Abbate, R., Gensini, G. F., & Casini, A. (2008). Adherence to Mediterranean diet and health status: Meta-analysis. BMJ, 337, a1344. doi: 10.1136/bmj.a1344 Tan, Z. S., Harris, W. S., Beiser, A. S., Au, R., Himali, J. J., Debette, S., et al. (2012). Red blood cell omega-3 fatty acid levels and markers of accelerated brain aging. Neurology, 78(9), 658–664. doi: 10.1212/WNL.0b013e318249f6a9 Trichopoulou, A., Bamia, C., & Trichopoulos, D. (2009). Anatomy of health effects of Mediterranean diet: Greek EPIC prospective cohort study. BMJ, 338, b2337. doi: 10.1136/ bmj.b2337 Trichopoulou, A., Costacou, T., Bamia, C., & Trichopoulos, D. (2003). Adherence to a Mediterranean diet and survival in a Greek population. New England Journal of Medicine, 348(26), 2599–2608. doi: 10.1056/NEJMoa025039 Tully, A. M., Roche, H. M., Doyle, R., Fallon, C., Bruce, I., Lawlor, B., et al. (2003). Low serum cholesteryl ester-docosahexaenoic acid levels in Alzheimer’s disease: A case-control study. Br J Nutr, 89(4), 483–489. doi: 10.1079/bjn2002804 Van der Schyf, C. J., Gal, S., Geldenhuys, W. J., & Youdim, M. B. H. (2006). Multifunctional neuroprotective drugs targeting monoamine oxidase inhibition, iron chelation, adenosine receptors, and cholinergic and glutamatergic action for neurodegenerative diseases. Expert Opinion on Investigational Drugs, 15(8), 873–886. doi: 10.1517/13543784.15.8.873 Verhaeghen, P., & Cerella, J. (2002). Aging, executive control, and attention: A review of meta-analyses. Neuroscience and Biobehavioral Reviews, 26(7), 849–857. Waddington, C. H. (2012). The epigenotype. International Journal of Epidemiology, 41(1), 10–13. Weih, M., Wiltfang, J., & Kornhuber, J. (2007). Non-pharmacologic prevention of Alzheimer’s disease: Nutritional and life-style risk factors. J Neural Transm, 114(9), 1187–1197. doi: 10.1007/s00702-007-0704-x Whitehair, D. C., Sherzai, A., Emond, J., Raman, R., Aisen, P. S., Petersen, R. C., et  al. (2010). Influence of apolipoprotein E varepsilon4 on rates of cognitive and functional decline in mild cognitive impairment. Alzheimers Dement, 6(5), 412–419. doi: 10.1016/j. jalz.2009.12.003 Yatsunenko, T., Rey, F. E., Manary, M. J., Trehan, I., Dominguez-Bello, M. G., Contreras, M., et  al. (2012). Human gut microbiome viewed across age and geography. Nature, 486(7402), 222–227. doi: 10.1038/nature11053 Zipp, F., & Aktas, O. (2006). The brain as a target of inflammation: Common pathways link inflammatory and neurodegenerative diseases. Trends in Neurosciences, 29(9), 518–527. doi: 10.1016/j.tins.2006.07.006

4 STRESS, COPING AND RESILIENCE IN AN AGEING POPULATION Phillips, Anna C. and Vitlic, Ana

Introduction Ageing is a physiological process that is part of normal development (Cutler, 1991). However, the stress response in humans, although an adaptive mechanism initially, has the potential to be chronic and detrimental to the organism if too large and/ or prolonged (Sapolsky, 2007). This particularly appears to be the case later in the lifespan; in fact some of the changes in older age mirror the chronic effects of stress on several of the body’s biological systems. This chapter will mainly focus on the impact of stress on the immune system and the implications for resilience in older age, as stress effects on all bodily systems are beyond the scope of one chapter. Further, the immune system undergoes several changes with ageing, resulting in increased susceptibility to infectious and autoimmune diseases and cancer, all of which are also influenced by stress.

The stress response The physiological response to stress was characterized by Walter Cannon (1929) as the ‘fight or flight’ response. The main function of this response is to maintain bodily homeostasis. Biologically, the key site involved in this process is the hypothalamus (Barrett, 2005), a part of the brain that communicates by sending nerve impulses to other parts of the body. In this way, the hypothalamus acts within seconds and via the sympathetic nervous system stimulates the medulla of the adrenal gland to release catecholamines (adrenalin and noradrenalin), which act on receptors throughout the body to result in several effects such as increased heart rate, blood pressure and respiration, activation of smooth muscle, and increased core temperature and pain threshold (Charmandari, Tsigos, & Chrousos, 2005). In addition, the hypothalamus also produces chemical messengers that act more slowly and in the

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next minutes travel through the hypothalamic-pituitary-adrenal (HPA) axis (Sapolsky, Romero, & Munck, 2000). Chemical messengers in this pathway include a corticotrophin releasing hormone (CRH), which stimulates the anterior pituitary gland to release another hormone, adrenocorticotropic hormone (ACTH), into circulation. The target organ of ACTH is again the adrenal gland, but this time it is the cortical cells that synthesise and release species-specific glucocorticoids (GC) into the blood. The tight control of these GC (mainly cortisol in humans) is sustained via negative feedback that controls and terminates the release of CRH (Griffin & Ojeda, 2004). Cortisol potentiates the effects of catecholamines within the body (Charmandari et al., 2005) as well as initially activating the immune system, then later working as an anti-inflammatory agent generally suppressing immune function, to prevent harmful over-activation (Munck, Guyre, & Holbrook, 1984). However, when stress is prolonged, chronic, or there are repeated exposures to stressful events, dysregulation of the stress response axis can occur, resulting in detrimental effects throughout the body, for example, on the cardiovascular system (McEwen, 1998; Phillips, 2011; Sedova et al., 2004) and also by suppression of the immune system (Sorrells & Sapolsky, 2007).

The immune system The immune system can be considered as two distinct, but interconnected elements; the innate and the adaptive immune systems. The innate response is often referred to as the ‘first line of defence’ against infection as it comprises mechanisms that are the first to react to an infection. The adaptive immune system is slower to respond but has the advantage that it includes memory of pathogens encountered and that its response is specific for each pathogen, thus conferring a tailored and long-lasting protection against further infection by the same pathogen. The innate immune system consists of soluble components, namely the complement system, and cellular elements, including neutrophils, which deal with rapidly dividing bacteria and fungi; eosinophils, which respond to parasitic infections; macrophages, which secrete soluble factors (such as the cytokines TNFα, IL-1, IL-6) to co-ordinate and amplify the immune response and also provide immunity against intracellular bacteria; and Natural Killer (NK) cells, which detect and kill virally infected and tumour cells. Adaptive immunity is provided by T and B lymphocytes, which develop and mature in the thymus and bone marrow respectively. T cells can be further classified into CD4 expressing helper cells (which in turn can be split into Th1 and Th2 types), CD8 expressing cytotoxic cells and CD25 expressing T regulatory cells, which have immune suppressive function. B cells, when presented with an antigen (by dendritic cells or with T cell help) produce antibodies to provide extended protection against infections. When a naïve T or B cell encounters a pathogen it will proliferate and differentiate into an effector cell or a memory cell, so that if the pathogen is encountered a second time a more rapid response can be achieved. Ageing is known to have deleterious effects upon both the innate and adaptive immune responses, though the latter is much better characterized (Phillips, Burns, & Lord, 2007).

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Ageing and immunity With ageing the innate immune response goes through some changes. For example, complement activation appears to be unaffected, but neutrophil bactericidal and phagocytic function in vitro is dramatically reduced (Butcher et  al., 2001). Macrophage function is also modified, although the literature is rather contradictory, including reports of reduced phagocytosis and superoxide function as seen in neutrophils, but enhanced secretion of the cytokines IL-6 and IL-8 in response to mitogen and lipopolysaccharide (LPS). NK cells are also affected by ageing; while their numbers do not change with age, their cytotoxic capacity is reduced (Hazeldine, Hampson, & Lord, 2012), which has also been shown to relate to reduced survival in people aged over 75 years (Ogata et al., 2001). In the adaptive immune system, the thymus gland atrophies and thus fewer naïve T cells are produced. As the size of the T cell pool is maintained at a constant level, the proportion of T cells that are memory cells increases. Consequently, as we age, we are less able to deal with new pathogens. In addition to changes in the ratio of naïve to memory T cells, there is a shift from T-helper 1 to T-helper 2 cells, and the end result is reduced cell-mediated, Th1-type immunity. Finally, with ageing, antibody production in response to antigen declines; for example, older people produce a lower antibody titre in response to vaccination than younger individuals and the antibodies produced are of lower affinity. This is thought to be largely the result of a decline in T cell help for B cells in older adults. Another concept that frequently appears in the literature when discussing the ageing of the immune system is inflammageing (Franceschi et al., 2007). Inflammageing indicates an imbalance between inflammatory factors necessary to fight the infection, but is damaging in excessive amounts, and anti-inflammatory components act as a counterweight. It has been suggested that ageing and longevity could, therefore, potentially be dependent on this balance (Franceschi et al., 2007). This would mean that immunosenescence, together with inflammatory markers such as different cytokines (IL-6, IL-8, and IL-15), could contribute to the predictors of the longevity of organisms.

Stress hormones and ageing As outlined above, stress, whether physical or psychological, is broadly sensed by two systems within the hypothalamus, the HPA axis and the sympathetic-adrenal-medullary system. Stress induces the release of catecholamines from the adrenal medulla, and both cortisol and dehydroepiandrosterone (DHEA) from the adrenal cortex. Catecholamines and cortisol can both be immunosuppressive if chronically elevated. In contrast, DHEA is a precursor to sex hormones and is considered to be immune enhancing (Butcher et al., 2005). Due to the impact of these hormones on immunity, any change in their production could therefore have significant health implications. In humans, the production of DHEA and its sulphated form, DHEAS, declines with age, a process termed the adrenopause (Orentreich, Brind, Rizer, &

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Vogelman, 1984). The synthesis of DHEA is maximal in humans at age 20–30 and declines gradually thereafter, so that by the seventh decade, levels of DHEA can be as low as 10% of that seen in young adulthood (Orentreich, Brind, Vogelman, Andres, & Baldwin, 1992). This adrenopause occurs at similar rates in both males and females and is a physiological phenomenon unique to the higher primates. However, although DHEA/S levels fall with age the production of glucocorticoids such as cortisol is remarkably unaltered (Orentreich et  al., 1992), resulting in a relative excess of cortisol over DHEA/S and an imbalance of immune suppression over immune enhancement. The age-related immunological and endocrinological changes outlined above may have implications for resilience to stress in older adults. It is likely that the combination of adrenopause, leading to a relative preponderance of cortisol, and an already reduced immune defence against infection through immune senescence, may leave this population particularly vulnerable to the negative effects of stress on immunity (Graham, Christian, & Kiecolt-Glaser, 2006; Phillips et al., 2007).

Caregiver stress and immunity in ageing One commonly studied model of the impact of stress on immunity is role of caring for someone, be it a spouse or child with a physical or mental illness or disability. Older caregivers have most commonly been studied in this context, using the model of family dementia caregiving (Gouin, Hantsoo, & Kiecolt-Glaser, 2008). Caregiving is now well established as having a serious effect on psychological well-being, physical health, and self-efficacy among caregivers when compared to matched non-caregiving individuals (Pinquart & Sorensen, 2003). Both innate and adaptive immunity are affected by chronic stress experienced by older adults. For example, wound healing was slower in older dementia caregivers when compared to age, sex, and income-matched controls (Kiecolt-Glaser, Marucha, Malarkey, Mercado, & Glaser, 1995). Wound healing is a complex process comprised of various phases (immediate response, inflammatory response, proliferation, migration and contraction and resolution) that activates many different cells and molecules (Shaw & Martin, 2009). Cells such as neutrophils and macrophages, and high concentrations of cytokines are main players in the inflammatory phase with a role to protect from invading pathogens and set the conditions for the repair process (Shaw & Martin, 2009). Lower production of proinflammatory cytokines involved in the wound-healing process such as IL-1α, IL-8 (Glaser et al., 1999), as well as IL-1β (Kiecolt-Glaser et al., 1995) seen in caregivers compared to the controls, indicates the possibility of a direct effect of stress on cytokine production in wound healing. NK cells’ ability to kill target tumour cells between older dementia caregivers and controls was not different (Irwin et al., 1991), but in the presence of cytokine stimulation this similarity between stressed individuals and controls was not preserved; NK cells from caregivers responded more weakly compared to those from the controls (Esterling, Kiecolt-Glaser, Bodnar, & Glaser, 1994). All this, together with the stress-induced reduction in IFN-γ production (Glaser, Rice,

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Stout, Speicher, & Kiecolt-Glaser, 1986), indicates cytokines as a common target of the impact of chronic stress exposure, and a potential effector through which much immune suppression may occur. A further association with the chronic stress of caregiving was found for adaptive cell mediated immunity: elevated cortisol levels as well as poorer proliferation to antigens and lower IL-2 production was shown in the caregiving group (Bauer et al., 2000). Caregiving stress in older adults has also been shown to be associated with the T-helper 1 to T-helper 2 shift in the type of cytokine responses, with the difference that in the older stressed individuals this was driven purely by an increase in IL-10 production, with no difference in IFN-γ production by Th1 cells (Glaser et al., 2001). It is likely that stress-induced changes in catecholamine levels (Elenkov & Chrousos, 2002) during the psychological stress response drive this cytokine-related behaviour. Inflammageing, as observed in the elderly, might also be more severe among chronically stressed older adults, such as dementia caregivers. Indeed, when compared to non-caregiving older adults who also had immunosenescence, not only did older caregivers show higher levels of IL-6 (von Kanel et al., 2006), but its rate of increase was four times higher than in non-caregiving elderly controls, leaving them particularly vulnerable to IL-6 related diseases such as frailty, cardiovascular diseases, osteoporosis, and others (Ershler & Keller, 2000). In terms of humoral immunity, caregivers, but only those aged over 60 years, showed lower levels of a particular antibody, salivary immunoglobulin A, which targets pathogens in biological fluids, particularly saliva at mucosal surfaces (Gallagher et al., 2008). A novel approach for assessing the severity by which caregiving stress affects the immune system of older caregivers is that of studies of latent-virus antibody titres. It is known, for example, that reactivation of latent viral infections, such as those initiated by the herpes group (HSV-1, EBV, and CMV) is typical for immunosuppressed patients such as HIV and transplant patients (Rasmussen, 1991). Interestingly, older spousal caregivers had higher IgG antibody titres against EBV VCA (virus capsid antigen) compared to the matched controls, indicating poorer control of the latent infection in this group (Kiecolt-Glaser, Speicher, Glaser, Dura, & Trask, 1991). Together with the higher antibody titre to total viral antigen of HSV-1, caregivers also had a decreased virus-specific T cell response; another component of the immune system necessary for controlling the infection (Glaser & Kiecolt-Glaser, 1997). Older caregivers have also been characterized by higher antibody titres against CMV when compared to the controls (Pariante et al., 1997). Vaccination responses are affected among older adults, which makes them particularly vulnerable to frequent infections such as pneumonia and influenza, among the top five causes of high morbidity and mortality in this age group (Thompson et al., 2003). It would be expected that this aspect of immune incompetence would be further exacerbated in older adults affected by the chronic stress of caregiving. This is indeed the case; a significantly lower percentage of older caregivers of dementia patients showed a four-fold increase in antibody titre in response to vaccination against the influenza virus, a response that is clinically considered to

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be protective against infection (Vedhara et  al., 1999). This was accompanied by higher salivary cortisol concentration in the caregiver group when compared to the controls, pointing again to the role of HPA axis in immune regulation among chronically stressed individuals. Most antigens, however, trigger both humoral, i.e., the antibody response that is generated by B lymphocytes, as well as cellular responses, mainly mediated by cytotoxic CD8+ T-cells (Glaser, Sheridan, Malarkey, MacCallum, & Kiecolt-Glaser, 2000; Kiecolt-Glaser, Glaser, Gravenstein, Malarkey, & Sheridan, 1996; Siergist, 2008). In addition, CD4+ helper T-cells are necessary as mediators between those two. It has been shown that both the antibody response to medical vaccination against the influenza virus, as well as IL-2 production in response to antigen stimulation, was lower in caregivers compared to the controls (Kiecolt-Glaser et al., 1996). In the case of the pneumococcal pneumonia vaccine, even though caregivers managed to exert an adequate immune response initially, shown as a rise in IgG antibody titre, it declined over time more rapidly in this group than in the group of matched controls, likely either as a consequence of decrease in number of antibody-specific B-cells, or their ability to produce antibodies (Glaser et al., 2000; Vedhara et al., 1999). Finally, even the effect of molecular mechanisms in ageing appears to be exacerbated by chronic stress in older adults. Telomere shortening is commonly used as an index of biological ageing (Wolkowitz et al., 2011), which contributes to increased incidence of age-related diseases (Bauer, 2005; Blasco, 2005). Telomeres are specialized nucleoprotein complexes at the end of chromosomes. They function to cap the chromosome, enabling recognition of the end of chromosomes as a break in DNA, thus preventing chromosomal fusions. Telomeres typically shorten during somatic cell division as a consequence of the ‘end replication problem’ (Olovnikov, 1973; Watson, 1972), as well as through various processes of genetic damage, with oxidative stress a potentially prominent driver of this telomere erosion. Thus, telomere length has been regarded as a biomarker of biological ageing that may help explain environmentally induced differences in rates of ageing, such as those associated with caregiving stress (Damjanovic et  al., 2007; Epel et  al., 2004) and childhood adversity (Kananen et al., 2010; Tyrka et al., 2010). Indeed, caregivers of dementia patients had shorter immune cell telomere lengths, and this was not due to having a higher number of these cells with shorter telomeres (Damjanovic et al., 2007). On the other hand, caregivers also showed an increase in basal telomerase activity, the enzyme that works to preserve telomere length, which could indicate an attempt of these cells to compensate for the loss of their telomere length (Damjanovic et al., 2007).

Chronic stress and immunity in ageing Interestingly, most studies of stress and immunity in older adults have focused on the caregiver-control model outlined above, with less attention being given to elderly individuals experiencing a range of more mundane stress exposures. Although one study has reported that perceived stress, measured using the perceived

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stress questionnaire (Cohen, Kamarck, & Mermelstein, 1983), was associated with a poorer antibody response to the influenza vaccine in the elderly (Kohut, Cooper, Nickolaus, Russell, & Cunnick, 2002), another small-scale study found no association between perceived stress and antibody status following this vaccination in elderly nursing home residents (Moynihan et al., 2004). Very few studies have focused on stressful life events, despite these being a common means of assessing the impact of stress on immunity in younger samples (e.g., Burns, Carroll, Drayson, Whitham, & Ring, 2003; Phillips, Burns, Carroll, Ring, & Drayson, 2005). However, a study published in 2006 examined overall stressful life events using a life events rating scale and showed that middle-aged and older adults with higher ratings of stress and disruptiveness for the stressful events they had experienced in the past two years showed lower levels of IgA in saliva (Phillips et al., 2006). A further study in 184 community dwelling older adults examined the associations between stress and the antibody response to the annual influenza vaccination (Phillips et  al., 2006). In this study, it became apparent that participants’ overall stressful life events exposure was not significantly associated with the antibody response to influenza vaccination (Phillips et al., 2006). However, one particular life event, bereavement, was negatively associated with one-month antibody levels against two out of three of the flu strains contained in the vaccine. Further, these associations remained statistically significant following adjustment for age and the presence of chronic illness at baseline. The negative association between bereavement and antibody status following vaccination is in line with previous studies of bereavement and immune function. Bereavement has been associated with in vitro functional immune measures such as decreased natural killer cell cytotoxicity and poorer lymphocyte proliferation to antigens (Bartrop, Luckhurst, Lazarus, Kiloh, & Penny, 1977; Goodkin et al., 1996; Irwin, Daniels, Smith, Bloom, & Weiner, 1987; Kemeny et al., 1995; Schleifer, Keller, Camerino, Thornton, & Stein, 1983; Zisook et al., 1994). In follow-up work, focussing on the two-month period post-bereavement, it was shown that neutrophils’ killing ability was suppressed in bereaved older adults, an effect that was accompanied by the increase in cortisol:DHEAS ratio (Khanfer, Lord, & Phillips, 2011). The absence of an association between overall life events and antibody response to influenza vaccination in the older adults and vaccination study (Phillips et al., 2006) contrasts with the results of previous research on young participants (Burns et  al., 2003; Phillips et  al., 2005). However, in these student studies, the modal number of life events experienced in the past year was six, with no participants reporting one or less events (Phillips et al., 2005), whereas in the elderly sample, the modal number of major life events in the year prior to vaccination was zero, with 31% of the sample reporting no events, and a further 17% reporting only one. This might be due to differences between student and older adult life event stress scales. In the student studies, less serious events were included in the stress scale, for example, getting an unjustified low mark on a test or minor financial problems, along with more major events, whereas the older adult life events scale tended to focus on exposure to major life events. Accordingly, the absence of an association

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between antibody response and overall life events in older adults may reflect the use of a scale including only serious life events. However, the results for bereavement would argue against this explanation. In addition, it is also possible that the elderly simply experience fewer general life events than younger samples. There is certainly evidence to this effect: elderly individuals encountered fewer major life events than middle-aged participants in a large cohort study in the west of Scotland using the same life events measure as the present study, but retrospectively over two years. Middle-aged participants identified a mean of 2.0 events whereas the mean number of events for the elderly was 1.7 (Carroll, Phillips, Ring, Der, & Hunt, 2005). These data also suggest that our participants were not unusual in experiencing few life events, given that the mean number of events reported over one year was 2.9. Accordingly, it may be that individual differences in general life events exposure are less important for immunity as people age, whereas bereavement, a specific life event that the elderly are more likely to encounter than the young, assumes greater prominence.

Social support and immunity in ageing Given the substantial impact of various types of chronic stress on immunity in older adults, as outlined above, understanding psychological factors that can help to enhance or improve immunity in this group is particularly important. Social support, or comfort, caring, esteem, or help provided by other people or social groups, can be a key resource that helps individuals cope with life. It has also been shown to have a substantial impact on health, for example, individuals with low numbers of supportive relationships had two to three times the mortality risk compared to those with large social networks (Berkman & Syme, 1979). Indeed, social network size and quality and frequency of social support have been shown to impact on morbidity and mortality from serious diseases in many epidemiological studies (e.g. Barger, 2013; House, Robbins, & Metzner, 1982; Kaplan et al., 1988). Social support has also been shown to relate to immune function. For example, whereas students who had seroconverted after the first injection of the standard three-dose hepatitis B vaccination were less anxious and reported lower stress levels, those who reported greater social support demonstrated a stronger combined immune response to the booster third inoculation (Glaser et al., 1992). In another study of college freshmen, loneliness and smaller social network size were associated with a poorer antibody response to the A/New Caledonian strain of the influenza vaccination (Pressman et al., 2005). Finally, higher social support scores, particularly higher frequency of tangible support, was related to an increased antibody response to the A/Panama component of the influenza vaccination, again in university students (Phillips et al., 2005). In a study of social support in the elderly, social support was negatively correlated with A/Panama influenza strain antibody status following vaccination, findings that even the authors found difficult to explain (Moynihan et al., 2004).

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In contrast, a larger study of older adults considered the actual vaccination response, i.e., the change in antibody levels from pre- to post-vaccination (Phillips et  al., 2006). In this study, although social network size and functional social support were not related to antibody response, married/cohabiting participants showed a better antibody response to the A/Panama strain at one month than those who were not married, particularly widowed, participants. Also, for those who were married or cohabiting, higher marital satisfaction was related to higher titres to A/Panama at one month. This is not entirely surprising given that poorer marital quality, in terms of adjustment and negative marital interactions, are associated with inferior functional immunity evidenced through reduced proliferation to some antigens, poorer latent virus control (Kiecolt-Glaser et  al., 1987; KiecoltGlaser et  al., 1988; Kiecolt-Glaser et  al., 1993; Kiecolt-Glaser et  al., 1997), and weaker natural killer cell cytotoxicity (Miller, Dopp, Myers, Stevens, & Fahey, 1999) in the general population. Further, it is possible that the variations between older caregivers and controls in terms of vaccination response (Glaser, Kiecolt-Glaser, Malarkey,  & Sheridan, 1998; Glaser, Sheridan, Malarkey, MacCallum, & KiecoltGlaser, 2000; Kiecolt-Glaser et al., 1996; Vedhara et al., 1999) may be driven, at least in part, by the effects of caregiving on marital quality and satisfaction, although more specific measurement of stressful life events and marital parameters would be necessary to support this speculation. Whatever the case, these findings resonate with the broad consensus that both marriage (Gordon & Rosenthal, 1995; House, Landis, & Umberson, 1988; Johnson, Backlund, Sorlie, & Loveless, 2000; Verbrugge, 1979) and marital satisfaction (Coyne & DeLongis, 1986; Kiecolt-Glaser & Newton, 2001; Robles & Kiecolt-Glaser, 2003) are beneficial for health. Further, it is possible that in an elderly population, general social support is less critical, whereas the specific social support resource of a happy marriage becomes more important for health, including susceptibility to infection. Interestingly, the studies of social support and immunity show direct associations rather than an effect of social support via buffering the negative impact of stress. It is possible that for psychological and other health outcomes, social support can buffer stress effects (Lazarus & Folkman, 1984; Rosengren, Orth-Gomer, Wedel, & Wilhelmsen, 1993), whereas for immune function, social support might impact immunity independently.

Coping and immunity in ageing Coping, as a resource to moderate psychological stress and improve health, has received little attention in the immune literature. A few exceptions include a study of law students where active coping strategies, indexed through perseverance, was associated with larger delayed type hypersensitivity responses, an index of good immune function, but only among men (Flynn, Schipper, Roach, & Segerstrom, 2009). In contrast, in students, seeking less social support related to greater lymphocyte proliferation to antigens, and lower positive reappraisal strategies related to greater IL-2 production in a non-examination period but not in the stressful

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pre-examination period (Koh, Choe, Song, & Lee, 2006). Interestingly, in the case of acute short-term stress, where effects on immune function are generally positive and enhancing (Dhabhar, 2000, 2002), an active coping acute laboratory stress task (memory test) can increase the concentrations of salivary antibodies, while a passive coping task (surgical video) results in decreases in salivary antibodies, i.e., worsened immunity (Bosch et al., 2001). Coping and immunity research is even scarcer among older adults. One study showed that caregiving for a spouse with dementia was not related to impaired mucosal immunity measured in saliva, neither was coping (Bristow, Cook, Erzinclioglu, & Hodges, 2008). In contrast, higher levels of active coping measured by a questionnaire in healthy older adults related to greater lymphocyte proliferation to antigens if participants reported high stress levels, but not if they reported low stress. In contrast, avoidance coping was associated with greater proliferation in participants with low perceived stress levels, but not among those with high stress levels (Stowell, Kiecolt-Glaser, & Glaser, 2001). This suggests that coping interacts with individuals’ perceived stress in terms of its impact on immunity, playing its main role in the presence of high stress levels. This view resonates with that described by a Dutch clinical psychologist (Olff, 1999) such that chronic stress or repeated stress exposure might outweigh an individual’s coping resources, and result in feelings of depression. Depression can lead to immune system downregulation (Castle, Wilkins, Heck, Tanzy, & Fahey, 1995; Cruess et  al., 2003; Glaser & Kiecolt-Glaser, 1987; Irwin & Miller, 2007; Kiecolt-Glaser & Glaser, 2002; McGuire, Kiecolt-Glaser, & Glaser, 2002; Zisook et al., 1994). Consequently, stress itself can not only influence immunity directly via the effects of stress hormones, but also indirectly through its influence on individuals’ well-being and their capacity to cope effectively. Further, just as stress can contribute to both depression and worsened immunity, stress effects on immune function itself can also contribute to symptoms of depression through increased inflammatory cytokine levels, which induce feelings of depression (Anisman & Merali, 2003; Connor & Leonard, 1998; Cyranowski et al., 2007; Duggal, Upton, Phillips, & Lord, 2013; Trzonkowski et al., 2004). Thus, the relationship between stress, immunity, and coping is multi-directional as shown in the simplified diagramme in Figure 4.1.

Stress

Immunity

Coping

FIGURE 4.1

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Stress resilience in ageing In this system pictured above, the word coping might equally be replaced by depression, as an index of coping ability exceeded. Further, stress need not be only psychological stress, but could also be physiological stress such as physical disease or physical trauma such as a severe fracture or burn. This brings us to the topic of stress resilience in later life. In ageing adults, this picture is worsened by the presence of concomitant immune senescence and adrenopause, meaning that resilience to stress and its effects is likely to be lower than in younger adults (Phillips et al., 2007). Indeed, older adults undergoing the stress of bereavement had both a greater cortisol:DHEA ratio and poorer immune function than non-bereaved controls (Khanfer et al., 2011). Similarly, older adults who experienced the physical trauma or stress of hip fracture had higher cortisol:DHEA ratios than healthy controls and lower neutrophil function (Butcher et al., 2005), and individuals with lower neutrophil function were more likely to succumb to infection post-fracture (Butcher, Killampalli, Chahal, Kaya Alpar, & Lord, 2003). Further, older adults who developed depression post-hip fracture showed the highest cortisol:DHEA ratio and poorest neutrophil function (Duggal, Upton, Phillips, & Lord, 2013), as well as worse frailty and slower physical recovery (Phillips, Upton, Duggal, Carroll, & Lord, 2013).

Conclusion Throughout this chapter we have attempted to describe the impact of ageing on stress hormones and immune function as well as the effects of stress on immunity and the role of stress hormones. We then summarized the research on the interacting impact of stress and ageing on immunity and health, as well as the effects of resources to reduce stress and improve immunity such as social support and coping. This brings us to the conclusion that the combination of the normal processes of ageing (adrenopause, inflammaging, immune senescence) can contribute to a reduced state of resilience to stress in later life. Consequently, those older adults with a genetic predisposition to milder adrenopause and immunosenescence are likely to be more resilient. However, as stress can impact on stress hormone levels and immunity even in young healthy adults, it is likely that chronic stress throughout the life span and/or reduced resources to handle the impact of stress will further impact on resilience in older adults. In this way, individuals with a life history of fewer severe stress exposures may be at lower risk of a heightened cortisol:DHEA ratio, immune decrements, and greater inflammation, even in the presence of the normal hormonal and immune changes associated with ageing. These individuals are thus likely to be more resilient to stress or trauma if and when it does occur later in the lifespan, although longitudinal research would be needed to confirm these effects of lifetime stress exposure, and the limit of where these contribute to poorer immunity is likely to differ across individuals. Although avoiding stressful events themselves may not be a realistic undertaking for most individuals, certainly where stress levels can be reduced by changing

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behaviour, coping strategies, or seeking social support, these methods are likely to have positive psychological, immune, and thus health impact throughout life not just in older age. Healthy behaviours with direct effects on both perceived stress levels and immune function can also be pursued in order to increase resilience in later life. These would include exercise or physical activity, adequate sleep, a balanced diet, not smoking, and moderation of alcohol intake, but their effects on immunity and within healthy ageing warrant a separate chapter each. A certain level of stress can be beneficial for health, and indeed the immune system, as has been mentioned above in the case of acute stress, by acting as a resilience enhancer much the same way a vaccine challenges the immune system but builds resilience against disease (Lewitus & Schwartz, 2009), the key to resilience in later life is getting the balance right.

Practical research tips 1

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Take a lifespan approach by considering the differences between younger and older adults in terms of types of stress and social resources, so make sure you use age-appropriate psychological measures. In studies where you are interested in change over time, e.g., the antibody response to vaccination, always take a baseline measure of immune function first pre-vaccination, then compare this to after the vaccination. Remember to measure potential confounding variables such as health behaviours (sleep, alcohol intake, exercise, diet, smoking) when examining associations between stress and health, as changes in these due to stress can influence immunity and health.

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Watson, J. D. 1972. Origin of concatemeric T7 DNA. Nat New Biol, 239, 197–201. doi: 10.1038/newbio239197a0. Wolkowitz, O. M., Mellon, S. H., Epel, E. S., Lin, J., Dhabhar, F. S., Su, Y. L., et al. 2011. Leukocyte telomere length in major depression: Correlations with chronicity, inflammation and oxidative stress—preliminary findings. PLoS One, 6, e17837 doi: 10.1371/journal. pone.0017837. Zisook, S., Shuchter, S. R., Irwin, M., Darko, D. F., Sledge, P., & Resovsky, K. 1994. Bereavement, depression, and immune function. Psychiatry Res, 52, 1–10. doi: 10.1016/ 0165-1781(94)90114–7.

5 THE DUAL CONTINUA MODEL OF MENTAL HEALTH AND ILLNESS Theory, findings, and applications in psychogerontology Westerhof, Gerben Introduction Over the past three decades, we have witnessed a strong professionalization of psychology in mental health care. The development of protocolled treatments, mostly based on cognitive-behavioral therapy, the rise of randomized controlled trials, and the use of routine outcome measures are evidence of this professionalization. In gerontology alike, psychologists have started to develop evidence-based treatments for older adults (Scogin & Shah, 2012) and guidelines for psychological practice with older adults (APA, 2013). This process of professionalization has had its merits: psychology is much better established and recognized nowadays. However, it also comes with costs as the professionalization tended to go hand-in-hand with a focus on a medical model of mental health as the absence of mental illness (Westerhof & Bohlmeijer, 2010). Interestingly, gerontological psychology has always had a broader view on mental health and well-being than on mental illness alone. This may be related to the fact that older adults are a stereotyped group and that psychologists wanted to avoid affirming stereotypes of older persons as lonely, depressed, anxious, or demented. Hence, pathology has always been studied in relation to processes of normal aging. This is evidenced for example in the guidelines for practice with older adults (APA, 2013) that refer to many theories and studies about lifespan development and not to pathological development alone. From a perspective on aging, the absence of mental illness is only a minimal outcome. A lifespan perspective on aging asks for a broader perspective that not only includes pathological aging, but also normal, successful, and even optimal aging (Baltes, 1987). In defining mental health more broadly, theories on successful aging are informative in different ways. First, it is important to use a lifespan developmental approach rather than treating later life as a distinct phase even though it has

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its own characteristics. Second, there is widespread agreement that successful aging involves multiple dimensions, even though different models of successful aging tend to use different outcomes in assessing successful aging. Third, besides more objective assessment of different domains of functioning, it is important to also include the subjective view of people on how well they are doing in later life to define successful aging. Last, although successful aging has connotations of achieving goals, it involves more than growth alone. As aging includes both gains and losses, successful aging involves processes of stability and coping with loss as well. In this chapter, I will address mental health using these principles from research on successful aging. First, I will define mental health as a multidimensional phenomenon that involves different aspects of psychological and social functioning as well as subjective well-being. Second, I will present the dual continua model of mental health and illness that holds that mental health and mental illness are related, yet distinct phenomena. In the third step, I will review studies on mental illness and mental health across the lifespan. The dual continua model holds that it is possible that mental illness and mental health follow different age trajectories across adulthood, i.e., age groups that experience less mental illness do not necessarily experience better mental health. Last, I will assess available evidence on the dual continua model in interventions with a specific focus on the long tradition of reminiscence and life review in later life.

Positive mental health Over the past years, a new conceptualization of mental health has been forwarded that can also do more justice to the variety of aging experiences with regard to mental health. The World Health Organization (WHO, 2005) has defined three core components as essential in positive mental health: (1) well-being, (2) effective functioning of an individual, and (3) effective functioning for a community (WHO, 2005, p. 2). Psychological and sociological theories and research can be used to further operationalize these three core components. With the rise of positive psychology in the new century, there is a renewed interest in the concept of well-being. Nowadays, two approaches to well-being are distinguished: hedonic well-being and eudaimonic well-being (Keyes et  al., 2002; Ryan & Deci, 2001; Waterman, 1993). Hedonic well-being refers to positive feelings, like happiness, joy, interest, and love, as well as to positive evaluations of one’s life, i.e., satisfaction with different domains of life (health, activities, relations, etc.) and life in general. The concept of hedonic well-being was used by Waterman (1993) who argued that this approach is an empirical translation of the old Greek philosophy of hedonism, incorporated among others by Aristippus. Hedonistic philosophy describes that obtaining sensory pleasures is the highest goal for the good life. In the social sciences, hedonic well-being has been studied under the heading of subjective well-being (Diener, 1984; Diener et  al., 1999). Research on subjective well-being originates in the 1960s and 1970s. Researchers used large-scale survey research to study the quality of life from the perspective of citizens themselves (Andrews & Withey, 1976; Bradburn, 1969; Campbell et  al., 1976; Cantril, 1965; Gurin et  al.,

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1960). Besides gaining insight in the phenomenon of well-being, these studies also had an applied side as they were used to monitor the subjective well-being of the population in relation to social policies. These studies traditionally used a social indicators approach: they assessed which individual characteristics are related to subjective well-being, like age, gender, socioeconomic status, marital status, occupational status, or health status. Nowadays, it is recognized that the social indicators approach has its limits. Social indicators usually do not explain more than about 10% of the variance in subjective well-being in the adult population (Diener, 1984; Diener et al., 1999; Veenhoven, 1996; Westerhof, 2001). Nevertheless, the approach is still often used, also increasingly in the domain of economics, where gross national happiness is taken as an important indicator that goes beyond the gross national product. In the 1990s, psychologists expressed discomfort with the approach of subjective well-being as the concept was not rooted in psychological theories (Ryan & Deci, 2001; Ryff, 1989; Waterman, 1993). These researchers conceptualized well-being more in terms of optimal psychological functioning than in terms of feeling well and satisfaction with life. To distinguish this new approach from the hedonic approach of subjective well-being, the concept of eudaimonic well-being was used (Waterman, 1993). The concept is derived from the Greek words eu (good) and daimon (spirit and deity, but also fate and fortune). It dates back to the work of Aristotle, for whom not happiness, but the excellence of character was the essential element of a good life. Different researchers have given different definitions of the good life. For Waterman, eudaimonia refers to personally expressive activities, a concept that comes close to concepts like flow or optimal experience (Delle Fave et al., 2008). For Deci and Ryan (2008), eudaimonia refers to intrinsic motivation that is supported by the fulfillment of three basic psychological needs of autonomy, relatedness, and competence. For Baumeister and colleagues (2013), eudaimonia mainly refers to meaning in life. For Ryff (2008), eudaimonia refers to self-realization. The conceptual and empirical work of Ryff (1989, 2008, 2014) is most important from a gerontological perspective as it also originates in the work of lifespan psychology. To define psychological well-being, Ryff used theories on optimal lifespan development (Erikson, Jung, Neugarten), but also other classical theories on optimal functioning, self-actualization, and positive mental health (Allport, Jahoda, Maslow, Rogers). She searched the works of these classical psychological scholars for common criteria of positive functioning and found six of them. Each criterion is important in the striving to become a better person and to realize one’s potential across the lifespan: 1 2 3 4

Self-acceptance: a positive, acceptant attitude towards one’s own person in past and present; Purpose in life: having goals and beliefs that support a sense of direction and meaning in life; Autonomy: being able to direct one’s life according to one’s own internal standards; Positive relations with others: being involved in empathic intimate personal relationships;

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Environmental mastery: being able to manage changing environments according to one’s own needs; Personal growth: being able to realize one’s own potential for self-development.

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Ryff focuses mainly on optimal functioning in terms of individual fulfillment in social relationships. Although eudaimonia involves personal development, the work of Aristotle on virtue and character strengths also involves a broader, societal perspective. Likewise, Keyes (1998) argued that optimal functioning of individuals also involves their societal functioning in terms of social engagement and embeddedness. He found five indicators in the work of classical sociologists and social psychologists, including Marx, Durkheim, Seeman, and Merton, that show what it means to prosper socially. His conceptual analysis of social well-being thus consists of five criteria for optimal social functioning that are partly analogous to the criteria for optimal psychological functioning: 1 2 3 4 5

Social coherence: being able to attribute meaning to what is happening in society; Social acceptance: having a positive and acceptant attitude of others with both their strengths and weaknesses; Social actualization: being convinced that the community has the potential to evolve positively; Social contribution: being involved in activities that contribute to and are valued by society; Social integration: having a sense of belonging to a community.

We can thus conclude that theories on well-being and optimal functioning involve both hedonic and eudaimonic concepts and that eudaimonic concepts involve both individual psychological functioning as well as social functioning in a larger community. Over the past decade, there has been much debate about the distinction between hedonic and eudaimonic well-being. Some have argued that one type of well-being precedes the other. For example, the self-determination theory describes subjective well-being as the result of the satisfaction of basic eudaimonic needs of autonomy, relatedness, and competence (Deci & Ryan, 2008; Ryan & Deci, 2001). By contrast, the broaden-and-build-theory of positive emotions holds that positive emotions result in the accumulation of cognitive and social resources and thus contribute to optimal functioning in life (Fredrickson, 2001). Some researchers have even gone so far as to argue that it is not only difficult but also costly to distinguish between the two (Kashdan et al., 2008). From a mental health perspective, Keyes (2002) has argued that emotional, psychological, and social well-being are related but also separate dimensions of mental health. Emotional well-being matches the core component of well-being in the definition of the WHO, whereas psychological well-being covers the evaluation of optimal individual functioning and social well-being that of optimal functioning in society (Westerhof & Keyes, 2010). Hence, it takes a combination of emotional, psychological, and social well-being to be considered mentally healthy. Positive mental

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health, or flourishing, is a state where individuals combine high levels of subjective well-being with high levels of psychological and social functioning. This definition of positive mental health parallels the definition of depression in the DSM-IV, which includes both feelings of anhedonia (feeling sad or loss of interest and pleasure) and reported problems in functioning (such as problems in appetite, sleeping, or fatigue). We can thus conclude that positive mental health is a multidimensional phenomenon, which is firmly rooted in theoretical and empirical work from both psychologists and sociologists and involves criteria of optimal functioning as well as judgments about one’s own subjective well-being. From a gerontological perspective, it makes sense to use the different approaches of well-being as related, but separate criteria for assessing positive mental health in later life. Hedonic well-being is close to a subjective view on how well one is doing in later life, whereas psychological and social well-being provide theoretical criteria for evaluating how well older persons are doing in different domains of functioning. An important remaining question is how positive mental health is related to mental illness.

The dual continua model The traditional view of mental health as the absence of illness implicitly holds that when people do not have a mental illness, they function well. By contrast, the dual continua model of mental health and illness holds that the two are related, but distinct dimensions. One continuum indicates the presence or absence of mental illness, the other the presence or absence of mental health. According to this model, people can have reasonably good mental health, even when they experience a mental illness. Alternatively, people can have a low level of mental health, without experiencing a mental illness. Several studies have provided evidence for this dual continua model. Most studies have used confirmatory factor analyses to assess different models, like a one factor model (mental health and illness are opposites of one continuum), a two factor model (mental health and mental illness are two independent continua), and a model with two related factors (mental health and illness are separate, but related continua). These studies show that the last model fits the data best, for example in American adults (Keyes, 2005), American adolescents (ages 12 to 18; Keyes, 2006), Dutch adults (Lamers et al., 2011), and South-African adults (Keyes et al., 2008). Using different measures of mental illness and health, other studies have come to similar conclusions (Compton et al., 1996; Greenspoon & Saklofske, 2001; Headey et al., 1993; Masse et al., 1998; Suldo & Shaffer, 2008). A different way to assess the dual continua model is to study the reciprocal relations of mental illness and mental health over time. Studies that have taken this approach show that better positive mental health predicts less symptoms of mental illness later in time and vice versa (Lamers et al., under review; Wood & Joseph, 2009). These predictive relations also hold when controlling for the other continuum at baseline. The latter finding shows that even among people who do not differ in mental illness, positive mental health matters for the course of the illness continuum and vice versa.

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A third way to address the dual continua model is to study the relations of both mental health and mental illness to other aspects of functioning. For example, mental health and mental illness hold different relations to personality traits. Mental health is mainly related to extraversion and agreeableness, whereas mental illness is mainly related to neuroticism (Lamers et al., 2012). Furthermore, people who are in better mental health (i.e., high levels of positive mental health) report less physical diseases and healthcare utilization and more work productivity and psychosocial functioning (Keyes, 2002, 2004, 2005, 2006, 2007). This relation holds, independent of the level of symptoms of mental illness. Even among persons who are diagnosed with a mental illness, levels of mental health differentiate among levels of functioning. These studies show that the dual continua model is superior to a single continuum model. We can thus conclude that the dual continua model holds a much richer description of mental health than the traditional view of mental health as the absence of mental illness. The dual continua model also better fits the approach of lifespan development as involving both losses and gains. Last, it also allows for describing mental health outcomes across the lifespan using the whole spectrum of pathological, normal, successful, and even optimal aging. A further question is how mental health and illness are related to age.

Mental illness and mental health across the lifespan Although studies have examined lifespan trajectories of single dimensions of mental health and illness, there have been almost no studies using the broad conceptualization of the two continua model. I therefore review some of the age differences in existing studies on specific aspects of mental illness and mental health. Studies on anxiety and depression have almost universally found lower rates of both disorders in older than younger people (Byrne & Pachana, 2010). However, older adults often tend to experience clinically relevant depressive symptoms rather than a disorder (Büchtemann et al., 2012). With regard to depressive symptoms, there appears to be a curvilinear relationship with people in midlife showing least and people in young and later adulthood showing most symptoms (Mirowsky & Ross, 1999). When it comes to positive mental health, most studies have addressed emotional well-being. Although findings differ somewhat between life satisfaction and positive affects (Diener & Suh, 1998; Mroczek & Kolarz, 1998; Westerhof, 2001), George (2010) concludes that a consistent finding over 35 years of research is that the proportion of people who report high levels of subjective well-being increases substantially with age. Using data from the General Social Survey on happiness between 1972 and 2004,Yang (2008) found that across periods and cohorts, there is an increase in happiness with age. Studies on psychological well-being (Ryff & Essex, 1991; Ryff & Keyes, 1995) have found that self-acceptance and positive relations with others are unrelated to age, whereas younger adults experience less autonomy and environmental mastery than older adults, but more personal growth and purpose in life. A cross-cultural comparison between the United States and Japan has found some intriguing differences in this pattern (Karasawa et  al., 2011). However, an analysis of two longitudinal

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studies does not provide equivocal support for changes in psychological well-being with age (Springer et al., 2011). Studies on social well-being have shown that younger adults experience less social acceptation and social integration than older adults, but they report less social coherence and less social contribution with no age differences in social actualization (Keyes, 1998; Keyes & Shapiro, 2004). It can be concluded that age differences depend on the aspect of mental health under study. When summing the results across the different aspects of positive mental health, these studies suggest that the mental health of individuals of different ages does not differ much. To conclude, we have only limited insight in the lifespan trajectories of mental health and illness, because few studies addressed the dual continua model and most existing studies could only address cross-sectional differences. The existing studies show that the specific aspect of mental health and illness under study matters for which kind of age differences are found. A Dutch study involving all aspects of positive mental health and illness has shown that older adults experience somewhat less positive mental health than younger adults, whereas there is a curvilinear relationship for mental illness (Westerhof & Keyes, 2010). This study thus provides further evidence for the dual continua model as the age trajectories for mental health and illness do not mirror each other.

The dual continua model and psychological interventions in later life The dual continua model of mental illness and mental health provides an interesting framework for psychological interventions in later life. Over the past years, the effectiveness of several interventions and therapies for specific mental health problems like depression and anxiety has been proven (Scogin & Shah, 2012). An important question is whether such interventions also contribute to the promotion and protection of positive mental health in later life (Keyes, 2007). In a recent article, Jeste and Palmer (2013) have called for a positive psychiatry of aging that focuses on successful aging through interventions that enhance resilience, optimism, social engagement, and wisdom. Although there have been meta-analyses that show that interventions can increase emotional and psychological well-being (Bolier et  al., 2013; Sin & Lyubomirsky, 2009), few of these interventions have addressed older adults. A number of interventions have been developed over the last decade that attempted to promote positive mental health or aspects of it in later life. These include positive psychology interventions, focusing for example on gratitude and forgiveness (Ho et al., 2014; Killen & Macaskill, 2014; Ramírez et al., 2014), but also exercise programs (e.g., Solberg et al., 2014), a friendship course (Martina & Stevens, 2006), proactive aging (Bode et al., 2006, 2007), and self-management (Elzen et al., 2007; Frieswijk et al., 2006). The evidence base of such interventions directed at positive aging is still in its infancy, however. Research focusing on reminiscence and life review in later life fits both the goal of promotion and protection of positive mental health as well as that of the prevention

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and treatment of disorders. There is some 50 years of theory, research, and applications in this field of gerontology (Westerhof & Bohlmeijer, 2014; Westerhof et al., 2010). Reminiscence and life review address the memories of older persons with a focus on both losses and gains. The field uses a person-centered approach that addresses the own subjective perspective on a person’s own biography. The concepts of reminiscence and life review date back to the work of psychiatrist-gerontologist Robert Butler (1963) and lifespan-psychologist Erik Erikson (1950). Both theorists described how a return to the past is a naturally occurring process in later life that serves the function of death acceptance. Both described positive as well as negative forms of reminiscence and life review. Butler used the concepts of pathological and constructive life review, whereas Erikson coined the concepts of ego integrity and despair. Both see a successful life review as resulting in an integrated view of one’s past life that includes memories about positive events, achievements, and things to be proud of as well as the reconciliation and acceptance of past conflicts, failures, and disappointments. Based on empirical studies, most scholars nowadays agree that reminiscence and life review are not the universal aging processes proposed by Butler and Erikson (Westerhof, 2015). Not all older adults engage in life review and they also do not engage in reminiscence more than younger adults (Pasupathi & Carstensen, 2003; Webster, 1998). Although ego integrity is related to death acceptance (Fortner & Neimeyer, 1999), there are older adults who accept death without a process of life review and vice versa. Reminiscence and life review are nowadays seen as fulfilling many different psychological functions (Webster, 1993). Westerhof and Bohlmeijer (2014) describe social functions (like sharing personal memories to maintain or enhance social contact or leave a legacy), instrumental functions (like the use of memories for regulating emotions or for solving present problems), and integrative functions (like the use of memories for identity construction, providing life with meaning, or accepting death). These constructive functions can be distinguished from more counterproductive uses of memories like the bitter revival of negative memories, the escape to the past in order to reduce boredom in the present, or the long-term longing for people that have passed away. Studies using the self-reported Reminiscence Functions Scale (RFS; Webster, 1993) found that constructive uses of personal memories have a positive relation to mental health and well-being, whereas counterproductive uses of memories have a negative relation and social functions are only indirectly related to mental health and well-being through both constructive and counterproductive functions (Westerhof et al., 2010). These relations have also been confirmed in longitudinal studies (Cappeliez & Robitaille, 2010). Reminiscence and life review have been applied in many different types of interventions (Haber, 2006; Westerhof et  al., 2010). The basic idea is that stimulating people to think back and review their lives will diminish symptoms of mental illness as well as promote mental health and well-being. Nowadays, a wide variety of applications exists for many different target groups, varying from community residents, family members, voluntary aids to specific groups like rural-dwelling older adults,

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persons with chronic illness, lesbian and gay older persons, war veterans, migrants, and ethnic minorities. Activities are also very diverse: autobiographical writing, storytelling, instructing younger generations, oral history interviews, life story books, artistic expressions, family genealogy, blogging, and other internet applications. Interventions are used in different contexts, including neighborhoods, higher education, primary schools, museums, theatres, churches, voluntary organizations, assisted-living communities, nursing homes, dementia care, and mental health institutions. The evidence for the effectiveness of reminiscence and life review interventions has accumulated over the last decade. Meta-analyses have shown that they are effective in decreasing depressive symptoms. The most comprehensive metaanalysis, involving 128 studies (Pinquart & Forstmeier, 2012), found small effects on subjective well-being, involving measures of life satisfaction, positive affects, and self-esteem. Furthermore, small to moderate effects were found for measures that would count under psychological well-being: ego integrity, mastery, and purpose in life. Small effects for social integration were reported that would be subsumed under social well-being. Last, moderate improvements in depressive symptoms as well as smaller effects in other symptoms of mental illness were found. Two older meta-analyses focused only on randomized controlled trials and found that reminiscence and life review were effective in decreasing depressive symptoms (Bohlmeijer et al., 2003) as well as in increasing subjective well-being (Bohlmeijer et al., 2007). To conclude, interventions based on reminiscence and life review can be effective in promoting positive mental health as well as diminishing depressive and other psychopathological symptoms. Although these studies were not based on the dual continua model, this model can be helpful in guiding further research on the effectiveness of interventions based on reminiscence and life review. First, the studies did not use the dual continua model of mental health and illness. It therefore remains difficult to distinguish whether interventions affect both continua and how the relations between the changes on different continua are. Second, the goals of interventions are not always very clear in terms of what the primary outcome is in terms of mental health promotion of mental illness prevention and treatment. With regard to the first point raised, we recently carried out two studies that focused on positive mental health as well as mental illness in an intervention that combined life review with narrative therapy (Korte et al., 2012; Lamers et al., 2014). Both studies found a stronger decrease in depressive symptoms than increase in positive mental health. This was not only in line with the main goal of the intervention in terms of depression prevention, but also shows that interventions aimed at decreasing depressive symptoms do not likewise increase positive mental health, thereby supporting the dual continua model. In other studies, we found that mastery and meaning in life play a mediating role in explaining the changes in depressive symptoms in life review interventions (Korte et al., 2012; Westerhof et al., 2010). These findings suggest that changes in aspects of positive mental health (mastery and meaning) are related to changes in depressive symptoms, over and above the level of depressive symptoms at baseline. They thus provide further support for the dual continua model in intervention studies.

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With regard to the second point, we previously classified interventions broadly into three main types (Westerhof et al., 2010): reminiscence interventions (focusing mainly on the recollection of positive memories), life review interventions (focusing on the integration of positive and negative memories), and life review therapy (focusing on negative styles of remembering). This classification is mainly focused on the different types of constructive and counterproductive uses of personal memories. These interventions may be further categorized in terms of their main goals. For the purpose of this chapter, one might classify interventions on the basis of the goals they have in relation to the two continua model of mental health and illness: promoting subjective, social, or psychological well-being, or preventing and treating mental illness. Some interventions, mostly the reminiscence type of interventions, have the promotion of subjective well-being as their main goal. This is mainly done through the recollection of positive memories that may revive the positive affects related to these memories. There is increasing research on nostalgia that can further underpin these kinds of interventions (Routledge et al., 2013; Sedikides et al., 2008). Other interventions, also often of the reminiscence type, use the recollection of memories to enhance social well-being (e.g., Westerhof, 2011). These interventions use the exchange of memories to create bonds between people and within a community. Such interventions are used for example in nursing homes to bring residents together, but they are also used in intergenerational groups to foster bonding between people of different ages and in life story books that help staff recognize the biography of residents of nursing homes. A third goal of interventions might be to enhance psychological well-being (e.g., Birren & Deutchman, 1991; Haight & Webster, 1995). These kinds of interventions will be most often from the life review type, focusing on the integration of both positive and negative memories. Outcomes that are related to psychological wellbeing will be the main target of such interventions, such as self-acceptance, but also purpose in life, mastery, and personal growth. The last goal would be to prevent and treat mental illness. The main type of intervention would be life review therapy that combines methods from life review with methods from psychotherapy, like creative therapy, cognitive behavioral therapy, psychodynamic therapy, or narrative therapy. These interventions often target people with depression or who are at risk of developing depression. They are recognized as an evidence-based intervention for depression in older adults (Scogin et al., 2005). More recently, there is also a tendency to use these kinds of interventions for treating anxiety and posttraumatic stress (Maercker & Bachem, 2013).

Conclusion To conclude, psychologists who work with older adults have tended to use a broad framework that includes theories on lifespan development and does not only focus on pathology in later life. This chapter has made this approach more explicit by

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first defining positive mental health as the presence of subjective, psychological, and social well-being. Positive mental health can thus be seen as a multidimensional phenomenon just like the aging process itself. Furthermore, the presence of positive mental health and the absence of mental illness constitute two related but different continua just like aging involves gains and losses. This dual continua model is supported by studies that show that the different continua of mental health and illness do not follow the same age-related trajectories. Last, the model opens up new avenues for interventions. The field of reminiscence and life review resonates well with the two continua model, but interventions could explain their goals better in terms of the model. Studies could address the mutual relations of positive mental health and mental illness during interventions to provide further support of the model. The model thus provides new opportunities for research and interventions.

Practical research tips 1

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When studying positive mental health it is important to carefully choose your research instruments. Which aspects of well-being do you want to study? The most often used combination of instruments for subjective well-being is the Satisfaction With Life Scale (Pavot & Diener, 1993) together with the Positive and Negative Affect Schedule (Watson et al., 1988). The Ryff Scales for Psychological Well-Being exist in different lengths varying from three to 18 items per dimension (Ryff, 1989; Ryff & Keyes, 1995). The Keyes Scales for Social Well-Being also exist in a long form and a short form (Keyes, 1998). Keyes (2002) developed a combination of these instruments for subjective, psychological, and social well-being as the Mental Health Continuum – Long Form. There also exists a Mental Health Continuum – Short Form that measures each of the different dimensions of subjective, psychological, and social well-being with one item. It is among the best validated instruments in wellbeing research (Lamers et al., 2012, 2014). So make your choice in relation to the goals of your study as well as the practical possibilities for using longer or shorter forms! When studying mental health, it is wise to differentiate between the two continua: the absence of mental illness and the presence of mental health. Although the two are related, they may have different antecedents and consequences, so be careful in your definition of mental health and illness! Given the scope of interventions based on reminiscence and life review, the goals of interventions have not always been very explicit. In designing and evaluating interventions like those in reminiscence and life review, it is important to determine what will be the primary outcome and through which mechanisms you want to achieve them. The dual continua model can be helpful in determining outcomes and mechanisms.

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6 SUCCESSFUL AGEING IN THE WORKPLACE A resources-oriented intervention perspective Stamov Roßnagel, Christian and Jeske, Debora

Introduction The workplace is a unique setting for research into the conditions and processes of successful ageing. We spend a substantial part of our adult lives at work. To contribute to our organisations’ goals, we continuously develop ourselves by expanding our repertoire of knowledge and skills. That need for continuous development will last throughout our careers as work lives become longer and fewer young workers enter the workforce. From a theory-building and research point of view, a major implication of those trends is that we see in natural operation several of the processes that have been identified as powerful drivers of successful ageing. Moreover, given their need for effective ageing workforce management, many organisations seek research collaborations, which generate a wealth of opportunities for applied ageing researchers. The goal of this chapter is to help advance applied ageing research by drawing attention to the need for and benefits of research focusing on the role that job and personal resources play for successful ageing in the workplace. Also, we emphasise the importance of interventions to increase workers’ competencies to secure and use those resources. We begin by outlining resources management as conceptualised in the Job Demands-Resources Theory (see Bakker & Demerouti, 2014) as a starting point to support successful ageing in the workplace. Next, we consider major implications for theory-building and data collection. In the final section, we outline the rationale of interventions designed to increase personal resources. Also, we discuss how intervention studies can enrich our repertoire of methods to build theories that directly inform managerial and personnel professionals’ practice.

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The resources view on ageing in the workplace In most industrialised countries, older workers are beginning to outnumber their younger colleagues. An increasing number of people work past traditional retirement ages (e.g., Alley & Crimmins, 2007; Harkonmäki et al., 2009; Noone, Alpass, & Stephens, 2010), whilst the numbers of younger workers shrink as a result of birth rates that have been declining since the 1970s (Dychtwald et al., 2006; Piktialis & Morgan, 2003). Not surprisingly, the number of workers over 55 years old has been predicted to grow by 60 percent by 2050 (Carone & Costello, 2006). As a result, workforces are becoming increasingly age-diverse. This demographic change coincides with an increasingly competitive globalised marketplace, in which innovation has become more critical than ever for firms’ survival in the long run (Choi & Chang, 2009; Sampson, 2007); this in turn drives technological advances and numerous changes to work routines. In light of these trends, research on the relationships between age-related cognitive, motivational, and physical changes and work-related behaviours began to intensify in the late 1990s (e.g., Ambrose & Kulik, 1999). Researchers sought to establish a general theoretical framework to overcome “age-free” models (Griffiths, 1999), placing greater emphasis on contextual research (see Warr, 1997). Consistently, most research on ageing in the workplace has come to build on lifespan psychological concepts. Lifespan psychology is rooted in general models of developmental regulation (e.g., Baltes & Baltes, 1990; Brandtstädter, 1999; Heckhausen, 1997) and makes two core assumptions. First, affective, behavioural, cognitive, and social development continue over the entire lifespan, rather than coming to an end in adolescence or young adulthood, as was assumed by earlier theories. Second, people do not “passively undergo” development, but actively co-regulate their development. Resources management is one of the core processes. People constantly strive to match their resources to external demands in an attempt to manage the gains and losses that might come with any action they take. Gains comprise such things as the setting of new goals, the acquisition of new skills, or the achievement of higher levels of performance. Age-related losses are mostly tied to an overall decline in biological and cognitive resources, and entail the adjustment of personal goals, developing strategies to counteract imminent or actual losses by investing resources into maintaining performance (for an overview see Baltes, Lindenberger, & Staudinger, 2006). The lifespan psychological framework is a meta-theory (Börner & Jopp, 2007) that may accommodate a variety of smaller-scale theories, which account for a specific set of phenomena. For instance, in work settings, the theory of SocioEmotional Selectivity (see Carstensen, 2006) has been useful to study processes of goal-setting and emotion regulation in work-related motivation (e.g., Sheppes et al., 2014). As another example, theories of person-environment fit have helped further our understanding how worker age relates to occupational strain and well-being (see Zacher, Feldman, & Schulz, 2014). Resource management has been considered particularly by Job Demands-Resources Theory that has received substantial research attention in the past 15 years (for an overview, see Bakker & Demerouti, 2014). That line of research recognises the importance of both job resources and personal

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resources. Job resources are those physical, psychological, social, or organisational aspects of a job that help workers achieve their work goals, reduce job demands, and that may stimulate personal growth, learning, and development (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001). Those resources may have both intrinsic motivational potential by facilitating learning or personal development and extrinsic motivational potential by providing instrumental help or specific information for goal achievement (Schaufeli & Bakker, 2004). For example, an organisation’s supportive learning climate could be considered a job resource (see Hauer, Westerberg, & Nordlund, 2010; Tracey & Tews, 2005). Job resources such as social support, autonomy, performance feedback, supervisory coaching, and opportunities for development have been recognised as crucial for the majority of occupations (Bakker & Demerouti, 2007; Lee & Ashforth, 1996). Personal resources are defined as positive self-evaluations that facilitate goal achievement and protect the individuals against the physical and emotional costs of work-related demands (Hobfoll, Johnson, Ennis, & Jackson, 2003). Personal resources refer to one’s sense of the ability to control and impact successfully on one’s environment. An example of a personal resource is learning-related self-efficacy (Kyndt & Baert, 2013). Resources theories assume that job and personal resources interact with job demands. Only if their resources match job demands will workers make full use of their competencies and maintain their productivity and well-being over their entire working life. Job resources might buffer the impact of job demands such as work pressure and emotional demands, including burn-out, on work-related strain (e.g., Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2007). Similar buffering effects are assumed for personal resources, but evidence is limited (Bakker & Demerouti, 2014). Interactions of resources with demands may have longer-term effects in the form of resource cycles. According to Hobfoll (1998, 2001), people who possess resources are more likely to acquire further resources, so initial gains beget future gain. Workers with resource surpluses are less vulnerable to job demands and better able to invest in their reserve capacity (Hobfoll, 1998). This benefits their longerterm development. Conversely to this gain spiral, those who lack resources are more vulnerable to further losses, potentially initiating loss spirals. Certain personal resources serve as key resources that “unlock” the power of other resources. If key resources are missing, the beneficial effects of other resources might be limited. For instance, a company might have a positive learning and training climate and job design might be geared towards work-related learning. However, if supervisors fail to support and encourage learning, they may stifle their workers’ learning activities. In sum, it appears that workers who have access to more job resources may be able to cope more effectively with their job demands.

Methodological implications of resources-oriented research in work settings In organisational research, traditional survey-based quantitative studies have long been the most frequently used format of data collection. In such studies, research participants complete measures of one or more predictors and of one or more

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outcomes and a statistical indicator is computed to determine how much variance in the outcome(s) the predictor(s) explain(s). For instance, participants could rate the average (“usual”) level of decision-making authority in their jobs, representing a typical job resource, and also indicate their average level of job-related well-being. This approach would rely on aggregate ratings, which reflect general differences between people. However, in resources-oriented research, in addition to betweenpeople effects, variations within individuals across time and job situations are of importance. This has implications both for theory-building and for data collection. Using the example of work motivation, we first consider theory-building implications, followed by data collection implications, which will include a discussion of relatively new measures such as reconstruction methods.

Implications for theory building Several personal resources are essentially motivational constructs, such as self-efficacy beliefs and goal orientation. Work motivation can be regarded as a personal resource that is crucial, from the perspective of resources-oriented research, for successful ageing in the workplace. Motivation translates a worker’s knowledge, skills, and abilities into actual work behaviour and job performance. Knowledge, skills, and abilities enable workers to carry out their jobs as required, whilst the level of motivation determines the amount of effort workers actually put into their jobs. That is, motivation regulates the intensity, duration, and persistence of work behaviours (Pinder, 1998). Due to demographic change, organisations depend more than ever on reliable ways of securing high job performance in a sustainable fashion so that workers can meet high performance standards throughout their entire career. To that end, work must be arranged so that job demands match workers’ resources in terms of coping capabilities. Work motivation is an essential component of those capabilities. Given an ageing workforce, understanding age effects on motivation is of particular importance. Established theories of work motivation, however, are somewhat silent on the influence of age on motivation. Researchers have started to explore the relationships between worker age and motivation in more depth only in the past ten years. This research has shown that contrary to wide-spread stereotypes, motivation does not inevitably and linearly decline as a function of biological ageing. What is more, current evidence suggests that motivation is regulated in a multidirectional and multilevel fashion.

The multidirectional perspective The early view on age-related changes in work motivation was characterised by a notion of decline and seemed to justify the common stereotype that work motivation decreases as workers age (see also Posthuma & Campion, 2009). For instance, Warr (2001) listed a number of reasons as to why work motivation was likely to decrease with age. These included social comparisons with younger colleagues,

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insecurity associated with skills updating, and lower perceptions of the probability of attaining positive work outcomes. In that early view, motivation itself was depicted as a relatively passive and mostly negative “response” to personal (e.g., capability declines) and environmental (e.g., altered work demands) changes. More recent models posit that age effects on motivation may be multidirectional. According to this perspective, there may be decline in some aspects of work motivation, but stability – or even an increase – in other facets. Kanfer and Ackerman (2004), for example, suggested that as capabilities for the fast processing of complex information decline from middle to late adulthood, workers will expect to invest a particularly high effort compared to younger workers. This may lower their performance expectancies, and thus motivation, where such fast and complex processing is required. However, performance expectancies might remain unaffected or even increase with age if workers can use expertise, routines, or work experience because such experience-based capabilities remain stable or even increase well into late adulthood (Baltes, Lindenberger, & Staudinger, 2006). At least, in principle, this leaves older workers with the option of focusing on roles and tasks in which they can utilise their expertise and routine in order to experience feelings of mastery and accomplishment. Consistent with the aforementioned lifespan psychological assumption that people strive to match their resources to external demands, Socio-Emotional Selectivity Theory (Carstensen, 2006; Reed & Carstensen, 2012) predicts that the nature of subjectively important goals will change across the lifespan as people’s general sense of time shifts from “time since birth” to “time until death” around mid-life. As a consequence, goals that concern the acquisition of knowledge shift in importance and in response to efforts to maintain positive emotional states. When time is perceived as open-ended, prioritised goals rather relate to “investments,” focusing on gathering information, on experiencing novelty, and on expanding skills and knowledge. When time is perceived as constrained, goals that can be realised in the short term become more salient (related to “harvesting”). These goals may lead older workers to consider their emotional well-being in the present over long-term goals. Indeed, research suggests that work-related motives systematically differ in their relationship with age (e.g., Kooij, De Lange, Jansen, Kanfer, & Dikkers, 2011; Stamov Roßnagel & Biemann, 2012). For instance, age has been found to correlate negatively with pursuit of career advancement or promotion, development, and challenge. At the same time, older workers appear to value other motives more strongly, including accomplishment, job enjoyment, and utilising their existing skills. These findings are consistent with the assumption that work motivation may change with age in a multidirectional way and that work motivation does not uniformly decline with age, but may increase as well as decrease in relation to various job aspects.

The multilevel perspective The research summarised above primarily accounts for the determinants and consequences of motivation at work, i.e. the motivation workers experience whilst they

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perform their work roles on a daily basis. Motivation at work is largely determined by momentary and situational drivers and can be defined as the kind of motivation that one experiences at a specific time and toward a specific activity. A profound understanding of age-related changes in work motivation requires, however, that other levels of motivation are taken into account (other than just motivation at work). The multilevel perspective essentially suggests that workers’ motivation is determined by three levels of work-related goals and motives (see Kanfer, Beier, & Ackerman, 2013). These are motivation at work, motivation to work, and motivation to retire. Motivation at work was described in the previous section. Motivation to work refers to the general value and importance one attaches to one’s work. Technically speaking, motivation to work denotes the motivation to enter into a formal or informal public work arrangement in which workers allocate personal resources (e.g., time, attendance, mental or physical effort) in exchange for a portfolio of expected material (e.g., pay, healthcare benefits) and immaterial (e.g., sense of competence, recognition) rewards. The motivation to retire simply refers to the intention and preparedness to exit from one’s current work (Kanfer et al., 2013). There are two main reasons why it is important to consider both the motivation to work and the motivation to retire. First, it is around the age of 50 that the motives begin to change. Motivation to work and retire start to play a more influential role than in earlier phases of one’s work life. For instance, most workers’ careers will have reached or are near their “peak” in terms of the highest possible position and salary level. Also, benefits and compensation may become less important motives, particularly if older workers have repaid their mortgages and their children are independent. At the same time, retirement is now within reach. This means the motives pursued by older workers might be quite different to the motives pursued by younger and middle-aged workers. For these groups, motivation to work may not be as central as motivation at work and the motivation to retire may not be present at all. These marked differences between younger and middle-aged workers on the one hand and older workers on the other hand need to be considered in research on work motivation and ageing. The second reason for the multilevel view on older workers’ motivation is that a uniform, “hierarchical” relationship is less than likely between the motivation at work and the motivation to work and to retire. Even if motivation to work decreased and motivation to retire increased beyond the age of 50, this would not necessarily imply that motivation at work also went down. As mentioned above, motives of accomplishment, job enjoyment, and utilising one’s existing skills are positively related to age. These motives convey a sense of mastery and competence and thus are beneficial to one’s job-related well-being. Therefore, workers are likely to maintain relatively high levels of motivation at work even in light of decreasing motivation to work. In line with these assumptions, recent research on the transition from work to retirement in the age group of 55 to 70 years shows that sizeable percentages of workers who leave their jobs before the official retirement age – indexing relatively low motivation to work – engage in voluntary work after retirement (e.g., Büsch et al., 2014). This trend is most pronounced in workers who

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report having enjoyed their last position before retirement. This fits with Kanfer et al.’s (2013) proposition that the association between the motivations to work and at work is relatively weak, given that motivation to work is influenced by sociocultural and economic conditions, while at-work goals are most strongly influenced by local work conditions. Taken together, these considerations indicate the importance of conceptual clarity when defining resources and modelling their effects. The age-related dissociation of motivation to work and motivation at work suggests that what may be a resource to younger workers might not represent a resource for older workers. Such dissociations might emerge for other resources as well, pointing to the need for precise definitions and measurement (e.g., via careful scale selection). For instance, job-related autonomy is assumed to be a crucial job resource for the majority of occupations (Bakker & Demerouti, 2007; Lee & Ashforth, 1996). In work design research, autonomy is separated into the facets of work scheduling, decision-making, and work methods (Morgeson & Humphrey, 2006). Age differences might emerge in the beneficial effects of these resource facets. For example, older workers might value scheduling autonomy more relative to younger workers as it may help them to reduce perceived time pressure. On the other hand, older workers might not value work methods autonomy to the same degree as this may reveal their potential skills deficits (e.g., when using IT-related work methods).

Implications for data collection Specifying definitions of personal and job resources in terms of their scope is one issue, another is extending the repertoire of data collection methods. As mentioned above, most quantitative studies have been geared towards collecting aggregate, between-persons data. In recent years, researchers have become interested in withinperson differences. In general, this requires a variety of repeated measures designs that range from cross-lagged designs to experience sampling designs. Cross-lagged designs may feature two measurement points within a relatively long period (e.g., 12 or 18 months). Experience sampling often involves multiple short, but repeated measurements (e.g., several reports per day over one working week). With such designs, it is critical to measure subjective experiences in a detailed manner to capture potential resource effects over time. Such measures have been referred to as specific or experience-based (e.g., Csikszentmihalyi & LeFevre, 1989; Hormuth, 1986). Various methods have been developed to capture such momentary experiences “in situ.” For instance, experience sampling techniques measure thoughts and affect in the moment they occur. Also, diary methods picture the changes in people’s experiences in different settings (e.g., Ohly, Sonnentag, Niessen, & Zapf, 2010). Specific or experience-based measures systematically diverge from traditional global or attitudinal rating scales as has been shown both in non-work contexts and in work settings (see Hertel & Stamov Roßnagel, 2012). For instance, attitudinal and experience-based measures of job satisfaction have been shown to be only moderately correlated and to predict different outcomes. In a study using

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a signal-based experience sampling measure, Fisher (2002) found that attitudinal job satisfaction, but not experience-sampled affect, predicted turnover intention, whereas the reverse held for helping behaviour. Global rating measures implicitly assume that participants recollect relevant experiences before they aggregate these recollected experiences to an average judgement. However, in addition to biases of such recall processes (e.g., memory distortions, current emotional states, overestimation of extreme experiences; see Schwarz & Strack, 1999), people often recall judgements from earlier occasions instead of taking the effort to compute a new judgement (e.g., Hastie & Park, 1986; Hertel & Bless, 2000). These recalled global judgements (e.g., about job satisfaction) often do not overlap with momentary experiences. Methods that can capture momentary experiences are therefore important complements of – or even alternatives to – global measures. It should be noted, however, that such measures can be relatively time-consuming, which may limit their use in work settings. Moreover, some job events are rare or hard to predict (e.g., conflicts with customers or supervisors) so these methods may not be suited to all situations. However, several options exist to solve some of the issues, including reconstruction methods. The general idea is to use episodic memory traces in order to access momentary experiences without interfering with a person’s ongoing activities (see Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004a). In contrast to semantic memory, episodic memory includes direct access to thoughts or feelings during the actual event. Participants are instructed to vividly re-experience recent episodes, focusing on what exactly has happened rather than why things have happened. This vivid re-experience of specific episodes re-activates thoughts and emotions people had during this episode, an approach often utilised in mood induction (see Schwarz & Clore, 1983). For the re-experiencing to come as close as possible to the original experience, participants are asked a series of specific questions about the target episode. These questions serve as recall cues. The aim is to reinstantiate as many aspects from memory as possible, thereby allowing access to episodic memory traces (Robinson & Clore, 2002). After re-experiencing a specific episode or event, participants are asked to assess their thoughts and feelings on rating scales just like they would in an experience sampling study. In other words, global measures capture memories of affect, rather than the momentary experience of affect. Reconstruction methods, in contrast, make affect re-happen in order to capture it. Reconstruction thus grants “near real-time,” non-invasive access to momentary thoughts and feelings. Reconstruction methods are therefore particularly useful whenever traditional experience sampling is not feasible and the experience reports need to be particularly accurate. The advantages of reconstruction methods may therefore be worthwhile considering when researchers find themselves facing very specific situations. We outline four instances. Reconstruction methods may represent an alternative to using traditional experience sampling as this sampling method is less likely to be perceived as invasive and interfere with regular job duties. This might, for instance, be a problem in time-pressured jobs such as production-line jobs. Even if workers agree to participate, they might feel more pressured by this additional task,

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which may then in turn bias their affect ratings. In addition, sampling may represent a disruption that might alter the way work tasks are carried out and therefore also influence the affect ratings obtained in momentary ratings. This may be particularly the case in more complex jobs (e.g., R&D positions). The fact that reconstruction methods rely on the post-hoc assessment of momentary thoughts and feelings reduces interference effects of data collection and greatly facilitates worker participation. Two other scenarios are worth noting here. Experience sampling can be quite cumbersome when it involves several reports (e.g., high sampling frequencies). Such sampling can result in substantial drop-out unless participants are highly committed (e.g., Stone, Shiffman, Schwartz, Broderick, & Hufford, 2002). Similarly, experience sampling methods may be difficult to implement in large samples if they rely on handheld computers or paper-and-pencil questionnaires, if only for budget constraints. However, reconstruction methods do not require costly devices as most data can be collected with traditional questionnaires, paper-and-pencil as well as online surveys (which make data collection easier with large samples). In this regard, reconstruction methods are similar to traditional attitudinal measures, meeting participants’ expectations of what surveys “are usually like,” which if at all influences participation positively. And finally, given that traditional experience sampling usually collects job experiences randomly, it is difficult to capture specific and rare job events, such as conflicts with supervisors or customers or positive feedback by colleagues. Reconstruction methods overcome this issue as they can address very specific job events. Reconstruction methods are therefore an elegant way of addressing various concerns about experience sampling because they are easier to use and can provide more accurate experience sampling data. Two variants of reconstruction methods have been developed to date, which differ in the duration and recency of their reference period, and thus their applications. These include the Day Reconstruction Method (DRM) and the Event Reconstruction Method (ERM).

Day Reconstruction Method The Day Reconstruction Method (DRM) was introduced by Kahneman et  al. (2004a) and combines elements of experience sampling and diary methods. Whilst traditional diary methods merely capture memories of events, reconstruction methods try to make events re-happen in order to capture cognition and affect during these events. The method features several steps. First, participants produce a diary comprising a sequence of episodes to re-instantiate the previous day into working memory. Such episodic re-instantiation facilitates retrieval from autobiographical memory and attenuates biases commonly observed in retrospective reports (e.g., Robinson & Clore, 2002; Schwarz & Oyserman, 2001). These initial diaries are confidential and allow participants to use idiosyncratic notes, including details they may not want to share. In the next step, participants draw on their confidential diaries to reconstruct the previous day in terms of the research question at hand. To do so, they complete a structured (usually self-administered) questionnaire asking them to describe key features of the episodes in the diaries, including (1) when the

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episode began and ended, (2) what they were doing (by selecting activities from a provided list), (3) where they were, (4) whom they were interacting with, and (5) how they felt on a variety of affect dimensions. Participants usually report the intensity of their momentary experiences “in situ” on a scale (e.g., from 0 “Not at all” to 6 “Very much”). Affect categories are specified by descriptors, mostly mood adjectives (for a detailed documentation of the DRM instrument, see Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004b). The DRM thus features several advantages. It was designed specifically (but not exclusively) to facilitate accurate emotional recall. However, compared to concurrent experience sampling methods, the DRM requires less time and does not disturb everyday activities as the DRM focuses more explicitly on experiences “in situ” by activating episodic memory traces with a specific instruction. According to initial studies, participants bring up 14 episodes per day on average, and take between 45 and 75 minutes to complete all materials (Kahneman et al., 2004b). Moreover, the DRM reduces the burden on participants and is less likely to interfere with work behaviours, a definite advantage when conducting research in work contexts. Yet, with completion times of up to 75 minutes, the DRM is still time-consuming for regular employee surveys, and not very different from traditional diary methods (cf. Sonnentag & Binnewies, 2013). Moreover, daily ratings as required by the DRM do not seem appropriate with job experiences that occur, say, once a week, rather than on a daily basis.

Event reconstruction As a solution to these problems, the Event Reconstruction Method (ERM) has been developed. It focuses on the most recent occurrence of specific, discrete events (e.g., interaction with customers, conversation with supervisor) rather than on an entire day (see Grube, Schroer, Hentzschel, & Hertel, 2008). Like the DRM, the ERM is non-invasive as events are reconstructed post-hoc. In addition, the ERM can be used to look at several events, allowing for within-person comparisons. The ERM rests on the same cognitive principles as the DRM and is intended to systematically access workers’ episodic memory of specific work events by guided re-experience. Beyond facilitating access to episodic memory, this technique helps minimise recall biases. The context of the event in focus (e.g., ‘Your latest interaction with a customer.’) is evoked in the ERM by recall cues (‘Where were you?’, ‘Who else was there with you?’ etc.) that have been shown to be effective in recalling daily life events (see also Wagenaar, 1986). Describing how the events evolved instead of explaining why things happened facilitates the re-experience of affect and emotions. Limiting reconstruction to a short and recent reference period further increases the probability of precise recall (Schwarz & Oyserman, 2001). Initial research has shown that ERM ratings of job satisfaction are distinct from attitudinal job satisfaction (Grube et al., 2008) and that experience-based job satisfaction is a better predictor of more spontaneous behaviour at work such as helping. Moreover, some 75 percent of the variance in ERM affect and ERM job satisfaction ratings

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was within-person variance, suggesting that the ERM is a sensitive instrument to measure intra-individual differences (Grube et al., 2008). Both DRM and ERM thus have potential applications to research in work settings. However, which of the two methods are most appropriate may depend on the specific circumstances. By making participants re-experience the job events in focus, both DRM and ERM allow for reliable answers to questions about workers’ feelings and thoughts during specific job events. With its focus on entire days, the day reconstruction method is of a similar nature as diary methods and experience sampling. Day reconstruction allows for assessing the time course of, for instance, work-related stress during an average working day. The DRM might therefore be a good choice whenever time-course data are required and traditional experience sampling is not an option. The ERM, on the other hand, focuses on specific events, offering the opportunity to examine rather infrequent events that may not be typical of the average working day, but have high impact on personal resources and on behavioural outcomes (e.g., conflicts with a superior). As the work events in question may be chosen by the participant, the ERM is particularly suitable to assess rare job events that are difficult to target with random experience sampling methods or the DRM. A number of researchers have already used both methods. Their findings have some bearing on the applicability of these tools in resource-oriented interventions and research on successful ageing in the workplace. Kahneman et al. (2004a) collected DRM and attitudinal data on satisfaction with one’s work as a function of job resources as diverse as social support at work and time pressure. DRM measures of affect were more strongly related to context variables (time pressure, the opportunity to chat with coworkers, etc.) than attitudinal job satisfaction. ERM has been applied successfully in studies on global and experience-based job satisfaction. One example is the study by Hertel et al. (2007) who explored the relationships between global job satisfaction and experience-based affect at work. They noted that older workers’ overall job satisfaction seems to be mainly determined by their momentary affect at work. However, in the case of younger workers, their overall job satisfaction was also influenced by the prospect of future gains and opportunities. In line with this hypothesis, convergence of global and experience-based judgements was higher for older than for younger workers.

An application example We use the aforementioned work motivation example to outline the use of reconstruction methods. When assessing age differences in motivation at work, discrete work tasks are often the most useful level of analysis, rather than the entire job (Stamov Roßnagel & Hertel, 2010). Such work tasks are a regular part of one’s work and defined by specific work-related goals. Any one worker usually performs a variety of tasks during his or her daily work. Tasks vary in the level of demands they place on that worker – and so does the level of motivation for each of the tasks. Increased motivation in some tasks might compensate for motivation decline in

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other tasks as a result of the resource matching processes that are central to successful ageing. In this context, reconstruction methods may provide interesting opportunities for further research. In a traditional questionnaire approach, workers would rate their level of motivation per task type and also fill in global measure of work-related affect. This then enables the researcher to analyse the relationship between task type, level of motivation, and affect. However, such an approach would not enable the researcher to assess affect per task type. What is more, the global affect measure usually requires participants to recall their affect for several tasks simultaneously. This invites all sorts of carryover effects. In addition, a general or global affect measure may not enable researchers to determine the relationships between task types and affect. Finally, the motivation ratings themselves would be global, further obscuring the relationship between momentary affect and task-level motivation. Using the ERM, participants would go back to a specific episode, re-instantiate this episode into working memory, and indicate their affect. This method would help researchers capture the real affect experienced by participants at the time, whilst eliminating disruptions at work. An ERM approach can also be used when workers complete only a subset of tasks on a given day. Researchers would therefore instruct workers to recall the most recent opportunity of working on the task type in question.

Interventions: an obvious extension of resources-oriented research Resource-oriented interventions are aimed at helping workers become aware of and activate existing resources, as well as acquiring new resources. Many interventions build on the fact that resource effects depend on workers’ appraisal of those resources (see Karasek, 1979; Karasek & Theorell, 1990). For instance, workers who might initially feel that their job experience got them “stuck in a mental rut” might learn to see the beneficial side of such experience (e.g., in terms of facilitating decision-making) and thus through a change in appraisal turn a perceived obstacle into a resource (see Demerouti, Eeuwijk, Snelder, & Wild, 2011; Peterson, Luthans, Avolio, Walumbwa, & Zhang, 2011). In general, interventions may focus on job or personal resources. On the job resources side, job redesign is a typical intervention. It aims to change job demands and resources by structuring and modifying work processes and task assignments at the individual and group levels (see Grant & Parker, 2009). For the purpose of this chapter, we focus on interventions that primarily address personal resources. Such interventions are often referred to as strengths-based interventions and aim at increasing those personal resources that can hardly be reached with traditional training and development measures that focus on expanding work-related knowledge and skills. These latter measures might not necessarily have positive effects on the more intangible resources such as self-efficacy. The need for strength-based interventions stems from the fact that organisations’ training and development activities are shifting from “training” to “learning” (see Streumer, 2006), resulting in training formats beyond the more traditional instructor-led trainings, such

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as blended learning, web-based learning, and informal learning (see Boud & Garrick, 1999; Clarke, 2004; Cross, 2007; Marsick, 2006; Tjepkema, 2002; Tjepkema et al., 2002). These formats put learners in charge of their learning. Learners self-set their learning goals, monitor their progress, and might even choose the time and place of learning (e.g., Kraiger & Jerden, 2007; Sitzmann, Kraiger, Stewart, & Wisher, 2006). This means workers need to effectively self-regulate their learning (Sitzmann & Ely, 2011). At the same time, although various techniques have been developed to enhance workers’ self-regulated learning (see Mesmer-Magnus & Viswesvaran, 2010), little is known about effective learning-to-learn interventions for older workers. This is particularly concerning in light of two major meta-analyses (Kubeck, Delp, Haslet, & McDaniel, 1996; Ng & Feldman, 2008) that found a negative relationship between age and training performance although no such effect emerged for other dimensions of job performance (Ng & Feldman, 2008). Also, higher age is seldom associated with lower levels of real-world functioning despite sizeable cognitive decline (Salthouse, 2012). These findings are compatible with the view that deficits in malleable resources, such as learning-related self-efficacy, are responsible for negative age effects rather than the more stable cognitive resources (see also Jeske & Stamov Roßnagel, 2015). On that backdrop, given that strengths-based interventions have seldom been evaluated in work contexts (Bakker & Demerouti, 2014), we outline here an intervention that sought to increase learning-related self-efficacy. The intervention was inspired by both survey findings (Schulz & Stamov Roßnagel, 2010) and experimental results (Stamov Roßnagel, Schulz, Picard, & Voelpel, 2009) showing a mediation effect. These studies showed that the relationship between learning skills and performance was mediated by memory self-efficacy, suggesting that older workers may not use the learning potential they do have because they do not believe they have got it. After all, older workers are less likely to receive the same support for learning as their younger colleagues (Maurer, Weiss, & Barbeite, 2003) and negative age stereotypes contribute to lowered beliefs in one’s skill malleability (e.g., Maurer et  al. 2003). However, self-efficacy plays a crucial role in self-regulated learning. Compared to learners with low self-efficacy, highly efficacious trainees set more challenging goals, develop more useful task strategies, persist longer, and expend more effort (e.g., Carver & Scheier, 2000; Locke & Latham, 2002; Pintrich, 2000; Schunk & Ertmer, 2000; Vancouver & Kendall, 2006). Also self-efficacy is instrumental in assessing learning goal progress as well as determining whether trainees will either begin or continue striving to make progress towards their goals. Consistently, Sitzmann and Ely (2011) in their meta-analysis found that self-efficacy is a significant predictor of learning performance, independent of cognitive ability and pre-training knowledge.

A cognitive-behavioural intervention The intervention was designed as a small-group training combining individual resource-activating exercises and moderated group discussions. The rationale of

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the training is to increase participants’ learning-related self-efficacy beliefs and to increase their awareness of and strategies to use personal and job resources for learning. The intervention comprises four training sessions (two hours each) in four consecutive weeks and one evaluation session of one hour. In the first session, we let participants establish their individual “learning model” by having them define in their words what they consider to be “successful learning” and what influences they see as either facilitating or impeding that successful learning. When listing those influences, they consider both external (e.g., colleagues, supervisors, working time arrangements) and internal (e.g., personal learning, “tricks” and strategies, learning-related anxiety) influences. Also, participants note what they know about age-related changes in learning behaviours and performance. The first session primarily serves a diagnostic purpose and contains no specific intervention. The second session focuses on cognitive restructuring and the activation of personal resources. Using a variant of the five-column thought record protocol (see Wright, Basco, & Thase, 2006), participants recall as vividly as possible a specific learning-related episode at their workplace and record the negative thoughts they have had in that situation together with a rating of the strength of their negative emotions in that situation. Participants then rephrase those negative thoughts into positive ones, imagine the same situation in light of those positive thoughts and rate the emotions they then feel. Next, participants record any successful recent “project” in which they felt mastery and competence. They are encouraged to mention off-the-job projects if they cannot come up with work-related projects. A moderated group discussion on the power of internal resources concludes the second session. The third session addresses participants’ learning-related belief systems. The trainer briefly presents central findings of cognitive ageing research and their implications for age-related changes in learning. Based on that input, participants revise their portfolio of personal and job resources they compiled in the first session. Going back to the restructuring exercise in the second session, participants focus on personal resources they were previously unaware of and include them in their resources portfolio. In addition, they are encouraged to develop their individual strategy of how to “re-enliven” feelings of mastery and competence to unlock their personal resources and boost their learning performance in future learning episodes. The session concludes with a moderated group discussion on ways to make external and job resources available (e.g., how to best request more supervisor support and make learning more of a group-based endeavour, rather than an individual project). In the final session, participants compile their individual “learning guide.” In this guide, they summarise what they have learnt from the training, outline the cornerstones of their new personal learning strategy, and formulate their resolutions on how to approach upcoming learning episodes. The learning guide includes strategies on how to deal with setbacks. Participants discuss some of the apparent “failures” in adopting a new learning strategy and why those failures do not actually represent setbacks, but normal “indicators” of a change process, which,

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when appropriately anticipated, can be used to increase and strengthen one’s self-management skills. This intervention approach has been successfully implemented and evaluated. For example, an intervention with 57 older workers from a company in the car parts industry yielded two important outcomes for participants (Stamov Roßnagel & Richter, 2014). First, learning efficiency was considerably higher in the intervention group, relative to a control group of non-participants. Whilst both groups performed similarly well on a knowledge test in the evaluation session, the intervention group needed 20 percent less time to study materials. Second, participants in the intervention group reported higher confidence in their learning. This was confirmed when participants were asked about the accuracy of their responses following the test and reflected in higher learning success ratings. Also, whilst both groups had not differed significantly in epistemic beliefs and learning-related selfefficacy before the intervention, participants in the intervention group reported more favourable epistemic beliefs and higher self-efficacy at the end of the intervention than the control group.

Preliminary results The cognitive-behavioural intervention significantly decreased learning time and increased learning-related self-efficacy. The benefits of the intervention also appear to remain stable over the course of the next few months at least (the evaluation took place three months after the intervention). Also, the effects appear to be sizeable in that we found them with a relatively small sample that included a number of participants who had limited vocational training and were not native German speakers. This suggests that the intervention does not require particular verbal and self-reflection skills, but may be useful for virtually all types of workers. What adds to the usefulness of the approach is that the total time investment per participant is less than ten hours, making it an attractive option for participants and organisations alike as this intervention may be relatively easily integrated into their “normal” operational procedures. Further research is needed to shed more light on the underlying processes and to disentangle specific and unspecific effects associated with the intervention. For instance, assessing affective processes concomitant to the motivational processes might help model potentially negative effects of the intervention. A look at this “dark side” is definitely warranted when it comes to training the trainers. Cognitive restructuring exercises can be very powerful intervention tools. However, their successful implementation depends on the trainer’s expertise, their knowledge of this method, and when it might be applied most effectively.

Practical research tips From our research collaborations with a number of organisations both in the private sector and in public administration (e.g., Bosch, Hannover Police Department,

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Michelin, Vodafone), we suggest the following success factors of applied research in the workplace. 1

2

3

Develop your research questions together with stakeholders. Have your general design worked out when speaking to your company research partners, but leave room for modifications of details. When you present that general design, invite the main stakeholder groups (works council representatives, personnel professionals, and supervisors) to finalise the design together with you. Such collaboration will build trust and increase buy-in through participation and transparency, which will not only boost response rates, but also ensure high data quality. Participants will be much more likely to report their “real” attitudes and not just half-heartedly “tick off boxes.” This is not the only benefit of collaborating, however. By adding their perspectives, your company research partners might give you ideas for richer hypotheses. For instance, they might suggest mediating or moderating relationships between your key variables you might not have derived from your specific model, but that reflect influential drivers of behaviour in the real-life workplace. Work with the companies’ trainers to ensure effective interventions. The theoretically sound design of your intervention is key and so is its effective implementation. However, running intervention workshops requires a set of skills many researchers might not have acquired in their academic teaching. Therefore, involving your company partners’ in-house trainers or coaches might help ensure effective interventions. Not only can trainers help you find the most appropriate established workshop techniques beyond mere lecturing, they might also be happy to run the actual workshops together with you. As company “insiders,” they have usually built a working relationship with your target group, which will contribute tremendously to the effectiveness of your intervention. If you would like to run the workshops yourself, you could consult with the trainers and ask their review of your workshop design. Manage your data collection proactively. Propose a questionnaire that is longer than required. More often than not, your company partners will not accept your suggested questionnaire right away, but discuss with you ways to shorten it. This holds especially if your questionnaire is longer than 20 minutes and if you try to reach a sample size of more than, say, 200 participants. Therefore, it is a good idea to include in your initial proposal scales that would be “nice to have,” but that you can drop without losing the essence of your study. When you invite participants, do not only tell them what the study is about, but also how participants and their company might benefit from your findings. Telling participants they will “help advance the scientific understanding of XYZ” is not enough. Whilst your questionnaire is in the field, give updates and feedback. Keep stakeholder groups informed of the number of questionnaires completed and involve them in sending out reminders. Participants may get back to you with questions; answering them will ensure high response rates

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and low attrition. Finally, allow for sufficient project duration. Be aware that the time between your initial proposal and the start of the data collection might be anywhere between one month and half a year.

Conclusion Based on the variety of current models of ageing, motivation and resources, we come to the following conclusions. First, as far as the “big picture” is concerned, research on work motivation and ageing appears to be in good shape. Current models integrate the global level of motivation to work and the specific level of motivation at work. By looking at the interactions of these levels, researchers are able to take a more fine-grained look at motivation. This is less of an option when using established “age-free” theories of motivation. Second, by considering how motivation links to age, several crucial issues have become recognised. For example, research on work motivation and ageing indicates that affective processes are important determinants of motivation and that certain aspects of motivation cannot be reasonably studied in isolation to affect. That said, many theories of work motivation tend to overemphasise cognitive processes at the price of neglecting affect. By adopting a lifespan psychology perspective, researchers are able to incorporate work-related affect into theories of work motivation. In the face of longer work lives, understanding the links between affect and motivation will be of growing importance to enable the design of physically and psychically sustainable work. The work is far from done, however. We outline three areas that warrant further research. First, further research is clearly needed into how resource cycles operate. For example, little is known about how ‘specific’ or focused, or conversely how ‘general’, resource cycle effects are. For instance, to the extent that the provision of the job resource of training and development measures increase personal job-related knowledge and skills, that effect would be said to be ‘specific’. If, however, these resources not only increase knowledge and skills but also improve a participant’s learning-related self-efficacy, the effect would be more ‘general’ and wide-ranging. Also, age-related issues have not been explored in the research that used Job Demands-Resources (JD-R) theory, which appears to be a promising platform for research on successful ageing in the workplace. Second, more coherent and integrated models are needed to reflect research on ageing, resource theories, and support the evaluation as well as development of interventions in the workplace to secure successful ageing. Some developments suggest that researchers and practitioners are moving forward, although there is still a need for further integration. For example, several meta-theories of motivation have been proposed. However, several established theories exist in the field of general work motivation. The extent to which these different theories relate to one another still remains to be explored. And finally, further research is required to “tidy up” the conceptual landscape as more and more concepts are considered, often in a theoretically eclectic fashion, in the research on work motivation and ageing. Greater integration and clarification

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will help to create well-rounded models that consider the interplay of job and personal resources and help researchers, practitioners, and managers understand all the elements that are involved in supporting successful ageing.

Acknowledgements Work on this chapter was sponsored through Grant No. 01HH12002 from the German Ministry of Education and Research (BMBF) to the first author.

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7 AGEING AND RETIREMENT BEHAVIOUR Shultz, Kenneth and Fisher, Gwenith

Introduction Understanding retirement is central to the process of aging because it represents an important life transition for the majority of older adults throughout the world. There are many economic, social, and psychological reasons why individuals engage in paid work, as well as many concordant factors related to leaving the workforce. The transition from paid work to retirement is characterized as a complex, dynamic longitudinal process (Shultz & Wang, 2011). The objective of this chapter is to describe this increasingly complex process and offer recommendations pertaining to methodological issues in order to advise researchers studying the retirement process. We have organized this chapter as follows. First, we examine how retirement has changed and been redefined in recent decades. What does it mean to be “retired” in the 21st century and how is that different from earlier times? What implications does this have for studying retirement? Next, we examine retirement as a longitudinal, temporal process, detailing the key individual attributes, job and organizational factors, familial factors, and broader socio-economic factors that all impact retirement plans, decision making, and adjustment. We then move on to discuss how best to examine the longitudinal retirement process with various retirement relevant research designs and methods. We conclude the chapter by delineating some key practical concerns such as methodological issues as well as potential data and funding sources for conducting research on retirement.

The evolution of retirement Zickar (2013) provided a detailed history of retirement dating back to ancient times. Looking at relatively more recent times, Zickar noted that retirement was a somewhat rare phenomenon, reserved mostly for the wealthy, until relatively recently

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(in  historical terms). Rather than leaving the workforce altogether, most workers simply adapted to the inevitable physical declines experienced with age by changing to less demanding jobs rather than “retiring.” In the United States, the first government sponsored pensions were developed after the civil war (circa 1860s). Although these pensions were limited in size and scope, they were the first hint of what was to follow in the 20th century, in which states, counties, and municipalities, as well as eventually the U.S. federal government (i.e., Social Security), enacted pension systems in the early to mid-20th century. The prosperity that followed World War II allowed private companies to enact their own defined benefit pension plans, with strong endorsements from labor unions. As a result of this newfound retirement income, the average age of retirement for men in the United States continued to decline throughout the 20th century. In the mid-1990s, however, the average age of retirement for men in the U.S. leveled out. Due to more recent economic changes, we have observed a slow increase in retirement ages since the mid-1990s (Maestas, 2013). In addition, since the 1990s, the political, economic, and social landscape has changed dramatically with regard to retirement (Wang, 2013a; Wheaton & Crimmins, 2013). The age of eligibility for full government sponsored Social Security retirement benefits is slowly increasing from 65 to 67 in the U.S. State and local pensions for public sector workers are increasingly being scrutinized by law makers and political watchdogs. In some cases, pensions are being drastically reduced or even eliminated. Many employers are rapidly replacing fixed income defined benefit pension plans, where payments are primarily based on years of service, age, and final salary, with variable income, and less stable, defined contribution (e.g., 401(k), 403(b), 457) plans, where payments are based on the dollar amount invested and the returns (or losses) produced in the financial markets. According to Butrica, Iams, Smith, and Toder (2009), employee participation in defined benefit pension plans was reduced from 38% to 20% between 1980 and 2008. Meanwhile, participation in defined contribution plans increased from 8% to 31% during the same time period. This shift in pension plan type provides some economic incentives for employees with a pension plan to remain in the workforce – to continue saving for retirement and postpone spending down retirement savings. In addition, private saving rates for retirement are down compared to past generations, yet individuals are living longer on average and so need to make their retirement investments last even longer than past generations. As a result of the less stable, and often less generous, income sources available in retirement, older workers are increasingly engaging in encore careers and bridge employment jobs to bridge the gap between career employment and full retirement (Wang, Adams, Beehr, & Shultz, 2009). However, on the positive side, some new financial opportunities for retirement savings among workers in the U.S. have surfaced in the last several decades, such as Roth IRAs (Individual Retirement Accounts) and, most recently, MyRA (targeted to low and middle income Americans who don’t have employer sponsored retirement plans). The recent Great Recession led to longer spells of unemployment for older workers. Unemployment results in missed opportunities to contribute to defined

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contribution retirement plans, thus making it difficult for older workers to plan for when, where, and how to retire. In addition, wages in the U.S. have stagnated, making it more difficult for most Americans to put money aside for retirement and still pay their bills, especially the high costs of higher education and healthcare, which have dramatically outpaced inflation in general. Although many older workers primarily continue working during their later years for economic reasons, others have noted social and psychological reasons to stay attached to the workforce (Fisher, Ryan, & Sonnega, 2015). Working may help individuals maintain their sense of identity, may be perceived as meaningful, and can provide a source for social relationships, connections, or social support. For example, many individuals derive satisfaction or a sense of purpose by working. Some researchers have pointed to generativity as a motivation for continued work (Templer, Armstrong-Stassen, & Cattaneo, 2010). Generativity refers to “having opportunities to share one’s knowledge and experience with younger generations” (Templer et al., 2010, p. 481). Steger and colleagues (e.g., Steger & Dik, 2009) have also highlighted the pursuit of meaningful work as an important reason for working. As a result of these recent political, economic, and social changes, the definition of retirement has become more heterogeneous and less predictable and clear over time. So much so, that researchers are unable to agree on a single definition of what actually constitutes retirement. As Ekerdt (2010) noted, “The designation of retirement status is famously ambiguous because there are multiple overlapping criteria by which someone might be called retired, including career cessation, reduced work effort, pension receipt, or self-report” (p. 70). Similarly, Denton and Spencer (2009) identified eight different common ways that researchers have identified individuals as retired: (1) nonparticipation in the labor force, (2) reduction in hours worked and/or earnings, (3) hours worked or earnings below some minimum cutoff, (4) receipt of retirement/pension income, (5) exit from one’s main employer, (6) change of career or employment later in life, (7) self-assessed retirement, (8) and some combination of the previous seven. Consequently, how retirement is defined depends in large part on the research questions being addressed and the researcher’s discipline.

The changing nature of retirement The process of retirement may vary considerably across workers. Retirement is no longer considered simply a time of leisure and the complete absence of paid employment. Increasingly, individuals continue to remain engaged with paid and unpaid employment in retirement. The fact that individuals can “un-retire” or “reretire” by rejoining the workforce and starting a new career after they retire, which has become a relatively common phenomenon in the last few decades (Alley & Crimmins, 2007; Maestas, 2010; Wang et al., 2009), only complicates matters. Thus, there are individuals now who retire multiple times throughout their working life (Shultz  & Wang, 2011). As a result, today’s retirement researchers need to study retirement as a longitudinal process that includes various pre-retirement phases, in

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addition to the retirement decision-making process itself. However, the retirement process does not end with the retirement decision. Rather the retirement process continues into retirement where researchers need to investigate retirement adjustment and satisfaction, especially now that retirement can last decades, rather than just a few years as was true for past generations. Moreover, dual career couples must now navigate the often treacherous retirement waters together. Moen (2012) goes so far as to postulate that retirement has moved from being a single event to a “life course project” where not just individuals, but usually couples, need to make multiple decisions leading up to, during, and post-retirement. Key factors such as when to retire, where to retire, and how to retire are all becoming increasingly important. Although traditionally the focus was on the first two questions (i.e., when and where to retire), more recently the focus has shifted to the latter question of how to retire (Adams & Rau, 2011). As a result of these demographic and economic shifts, studying retirement is a bit of a moving target. Hence, having a full appreciation of the key methodological issues surrounding the ever evolving longitudinal retirement process is essential.

Retirement as a longitudinal, temporal process Wang and Shultz (2010) presented an extensive review of the retirement literature. In their review, they offered a temporal model of retirement, which is presented in Figure 7.1 (this model is also discussed in Shultz and Wang [2011] and Shultz and Olson [2013]). The temporal model of retirement presented by Wang and Shultz begins with retirement planning, then examines the retirement decision-making process, and ends with the retirement transition and adjustment processes. In addition, the model depicted in Figure 7.1 of the temporal retirement process elucidates how individual attributes, job and organizational factors, family factors, and broader socioeconomic factors all influence the process of retirement. What is clear from examining Figure 7.1 is that retirement is not a single event. Instead, retirement represents a longitudinal, sequential process that occurs over the course of many years. As depicted in the right side of Figure 7.1, retirement begins with informal thoughts and ideas of retirement in one’s early and midcareer, and progresses to more deliberate and overt formal retirement planning as one approaches the retirement decision phase. The retirement decision process may occur several times as individuals move in and out of the paid workforce toward the end of their work life. Once the decision to retire is made and enacted for the final time, then the retirement transition and adjustment process begins. This third and final phase of the longitudinal retirement process can last for many years or even decades, as retirees adjust to their evolving family and personal situation (e.g., loss of a spouse). Shultz and Wang (2011) discuss how retirement is not a uniform and lockstep process for all older workers. That is, although the vast majority of older workers will go through the temporal progression of retirement planning, retirement decision making, and retirement adjustment depicted in the right side of Figure 7.1,

Longitudinal progression of the retirement process (Reprinted with permission from Wang, M., & Shultz, K.S. [2010] Employee retirement: A review and recommendation for future investigation. Journal of Management 36, 172-206).

FIGURE 7.1

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disadvantaged groups (e.g., women, minorities, the disabled, low-income workers, the chronically unemployed) are likely to have very different retirement experiences than individuals with stable, uninterrupted, professional careers. The factors that drive this differential process are depicted in the left side of Figure 7.1. Because this model is discussed in detail in Shultz and Olson (2013), Shultz and Wang (2011), and Wang and Shultz (2010), we only briefly discuss each of these four sets of factors here, with particular attention to how best to study this temporal process in the 21st century using a variety of research methods.

Individual-level factors Various demographic factors, such as age, gender, social class, and race, will all impact the nature of the retirement experience for individuals. For example, women are more likely to have interrupted careers for childbearing and meeting family demands, and are also more likely to work part-time, thus being less likely to be covered by pension plans, compared to men. As a result, women (and in particular divorced or widowed women) are likely to have less in retirement savings and assets than men as they approach traditional retirement age (Goldberg, 2007). Consequently, women are likely to have fewer options as they approach both retirement planning and retirement decision making when compared to men. These fewer options are also likely to affect women’s retirement adjustment and satisfaction relative to men. As a result, it is important to examine potential gender differences in how the temporal retirement process of retirement planning, decision making, and adjustment is likely to play out differently for men versus women. As noted earlier, the temporal retirement process is often a coupled experience. Thus, researchers also need to distinguish between women who are married versus unmarried, as well as those who may still be caring for young children, dependent (e.g., disabled) older children, aging parents, or who may have custodial rights and responsibilities for their grandchildren, as we know women are much more likely than men to take on the caregiver role in families (Neal & Hammer, 2007). Such factors will dramatically impact how women in different familial situations experience the temporal retirement process (Matthews & Fisher, 2013). Further complicating the picture, Taylor and Geldhauser (2007) noted that women and minorities are overrepresented among low income older workers. Thus, the issues of race, gender, and income all become intertwined with one another when researchers seek to better understand the temporal retirement process depicted in Figure 7.1. Individuals’ attitudes toward and performance at work can also have a strong impact on their likelihood of engaging in retirement planning and decision-making behaviors (Adams & Beehr, 1998). Job attitudes can also influence their likelihood of accepting early retirement incentive offers. Furthermore, older workers’ competencies regarding work performance will impact retirement-related behaviors. For example, older workers with more up-to-date work-related competencies are more likely to want to remain in the workforce compared to older workers who do not

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have up-to-date competencies. In other words, it is not just an older workers’ desire to remain in the workforce that is critical, but also the talents they bring to the table that will determine their success in securing continued employment once retired from their career job (Shultz & Olson, 2013). In addition to issues regarding job performance, Finnish researcher Juhani Ilmarinen introduced the concept of work ability, which refers to a worker’s perceived job-related functional capacity, or a worker’s ability to continue working in his or her current job, given the challenges or demands of the job and his or her resources (Ilmarinen, 2009; Ilmarinen, Gould, Järvikoski, & Järvisalo, 2008). Prior research has demonstrated that work ability predicts retirement and labor force departure related to disability (McGonagle, Fisher, Barnes-Farrell, & Grosch, 2015; von Bonsdorff, Seitsamo, Ilmarinen, Nygård, von Bonsdorff, & Rantanen, 2011). Work ability research has also highlighted the importance of personal and work-related resources in facilitating continued work and thereby delaying retirement (McGonagle et al., 2015). Thus, it is critical that researchers interested in studying retirement incorporate the concept of workability. A great deal of research has examined the influence of health and wealth factors in the retirement planning, decision making, and adjustment processes (BarnesFarrell, 2003; Shultz & Wang, 2007). These are two clearly important proximal factors that influence retirement preparation and decision making, not to mention retirement adjustment and satisfaction. For example, McGarry (2004) studied how changes in health affect retirement expectations. Not surprisingly, she found large effects of self-rated health on when workers expected to retire. Importantly, she also showed that changes in retirement expectations were affected to a much greater degree by changes in health status than by changes in income or wealth. However, assuming that one is in adequate health to continue to work and that he or she has enough money to be comfortable, then other factors such as attitudes toward work and retirement will become increasingly influential in the retirement planning and decision-making process (Barnes-Farrell, 2003). Thus, health and wealth become baseline factors, which once satisfied, point us to other individual level factors that play increasingly prominent roles in how the temporal retirement process unfolds. Taken together, these various individual attributes are changing the way in which older workers plan for, enact, and adjust to retirement in the 21st century. With the removal of forced retirement for almost all jobs in the late 20th century (at least in the U.S.) and increases in the age of eligibility for Social Security retirement benefits, we are likely to observe even more heterogeneity in the retirement process moving into the future. As a result, contemporary retirement research needs to examine a wide variety of individual-level factors that impact the retirement process in order to capture the dynamic nature of retirement today. In addition, researchers also have to incorporate factors at various levels of analysis, including job and organizational-level factors, which are discussed next. Thus, multilevel analysis is needed to fully examine the temporal retirement process of retirement.

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Job and organizational factors Current job characteristics (e.g., physically demanding work) also impact older workers’ attitudes toward retirement, as will the organizational climate toward older workers (e.g., age stereotypes and biases). For example, Johnson, Kawachi, and Lewis (2009) found that older workers are willing to step down from more prestigious and well-paying positions if the tradeoff is less travel and less physically demanding work. In fact, these workers often report enjoying the lower level of work more due to reduced stress and pressure. In addition, organizational climates that promote and foster ageism and age bias in the workplace are likely to lead workers to want to retire in order to escape these toxic work environments. Thus, the organizational climate with regard to older workers may be just as important as individual factors in relation to retirement planning, decision making, and adjustment. In addition, the organizational and career attachment levels of the older workers will impact their attitudes toward retirement, retirement planning, and retirement decision making (Adams, 1999). That is, older workers who are more attached to their current organization and career are going to be less likely to engage in retirement planning and decision-making activities. Conversely, those older workers who may be disenchanted with their current employer and/or career will be much more likely to engage in active retirement planning and decision making in order to find other activities that better match their desires. As older workers take more control over their work careers in the 21st century, career-related factors are likely to become even more important in the retirement process (Hall, 2004; Kim & Hall, 2013). The variety of work options available to older workers will also impact retirement-related behaviors. For example, if an organization provides opportunities for phased or partial retirement, older individuals may be more likely to continue with their organization, as opposed to retiring completely or securing other employment (Wang et al., 2009). In addition, flexible work options (e.g., reduced hours, job sharing, part-year employment, and flexibility in time or location of work) are also likely to prolong the retirement process even longer than phased or partial retirement schemes, as the latter are more likely to have fixed time frames. Older workers consistently report the desire for more flexible work options (Johnson et al., 2009) in order to provide more balance in their life and to pursue other opportunities outside of work. Thus, to the extent that organizations provide the characteristics that older workers desire, they will be better positioned to influence the temporal retirement process of older workers (Loi & Shultz, 2007; Rau & Adams, 2005). In a meta-analysis examining the antecedents and outcomes of retirement planning and decision making, Topa, Mariano, Depolo, Alcover, and Morales (2009) examined more than 341 independent samples from 99 primary studies with 188,222 participants. They found that the work and organizational-level factors of work involvement and job satisfaction were two of the strongest predictors of retirement planning activities, while negative working conditions and positive attitudes toward retirement had smaller, but still meaningful, effects on retirement planning.

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However, the predictive efficiency of these variables in predicting actual retirement decisions was much smaller. Thus, it is clear based on meta-analytic findings that a variety of work- and organizational-related factors can have an impact on retirement planning and, to a lesser extent, retirement decision making. The various job- and organizational-level factors discussed above appear to have a consistent relationship with both retirement planning and decision-making outcomes. As a result, their impact will influence in what manner researchers investigate how the temporal retirement process unfolds over time. Thus, those interested in examining retirement from a dynamic and multilevel perspective will need to be sure to include job- and organizational-level factors in their investigations for retirement planning, retirement decision making, and retirement adjustment in order to capture the true picture of the temporal retirement process.

Family factors Family support networks, as well as marital quality and satisfaction, also have an impact on individuals’ attitudes toward work and retirement (Matthews & Fisher, 2013). For example, older workers who have spouses or significant others who are not supportive of their continued employment will be less likely to continue to work or seek out bridge employment jobs after retiring from a career job. These individuals are also more likely to have a more difficult time adjusting to retirement once they do retire (Wang, 2012). On the other hand, older workers who have supportive family members may or may not continue to work, but will be much more likely to be satisfied with their decision and adjust better to retirement when they do decide to retire, given the more perceived voluntariness of their retirement decision (Shultz, Morton, & Weckerle, 1998). Meanwhile, older individuals who have a poorer perceived marital relationship may continue to work in order to distract themselves from their adverse marital relationship. Conversely, individuals who express having a strong and vibrant relationship with their spouse would be more likely to try to time their retirement to coincide with that of their spouse so that they could continue to foster their relationship. Thus, both marital quality and spouses’ working status will have an impact on how individuals prepare for and execute their desired retirement plan, as well as how they may adjust once they themselves retire (Moen, 2012). Additional family factors such as the number and age of dependents one has will also impact retirement planning and decision making (Matthews & Fisher, 2013). For example, while traditionally most individuals of retirement age are empty nesters, today individuals approaching retirement may still have children in high school or college because of starting a second family later in life, through remarriage, or making the choice to defer having children until they are in their thirties or forties. In addition, workers approaching retirement may also be responsible for young grandchildren or aging parents, which can dramatically impact plans for retirement, as well as retirement decision making. For instance, having young school-aged grandchildren in the home may require postponing a planned retirement, while

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suddenly having to care for an infirm parent may require taking an unplanned early retirement. As a result, individuals’ retirement planning and decision-making activities will be influenced by factors at the family level. These family factors are likely to have an even bigger impact on the retirement adjustment process, compared to factors at the other levels discussed so far, due to the fact that the family situation will remain a strong proximal factor, while job and organizational factors, for example, will fade to having a more distal impact on retirement adjustment.

Socioeconomic factors As can be seen in the lower left portion of Figure 7.1, the final set of antecedents impacting the temporal process of retirement include macro-level factors such as the current unemployment rate, future economic trends, and changing government policies and programs toward work and retirement. All of these broader societal level factors are likely to have a significant impact on older workers’ attitudes and decisions with regard to retirement versus continued engagement in the workforce. For example, older individuals may perceive that they have no option but to retire if they lose their job. In addition, perceptions of future economic growth or decline are also going to impact older workers’ perceptions of the relative attractiveness of continued employment versus opting for retirement. Research has consistently shown that while older workers are less likely to lose their job compared to younger workers, when they do they are typically out of work more than twice as long. As a result, these discouraged older workers will be more likely to begin tapping into retirement savings and filing for Social Security benefits if they are eligible (AARP, 2005). Shultz and Wang (2011) also noted that government policies regarding retirement have shifted from a pro-retirement to a pro-work perspective. That is, in the early and mid-20th century, governments provided strong incentives to encourage older individuals to retire at relatively young ages. However, starting in the late 20th century and continuing in to the 21st century, government policies (including those in Europe; van Dalen, Henkens, Henderikse, & Schippers, 2010) have encouraged older workers to stay in the workforce. For example, in the U.S. the age to receive full retirement benefits from Social Security is slowly raising from 65 to 67 years old. In addition, financial penalties in Social Security for continuing to work past age 65 no longer exist. Thus, the U.S. government has removed the traditional disincentives to work at older ages and instead now provides strong incentives to remain active and employed (McNamara, Sano, & Williamson, 2012). While explicit government policies have some effect on retirement timing and experiences, more implicit societal-level norms about retirement also impact retirement timing. For example, up until the early to mid-20th century, the expectation was that individuals would work until they were simply no longer physically able to do so. Thus, retirement was viewed in a negative light, reserved only for the frail elderly. However, by the mid–20th century, the increased availability of company pensions and full implementation of Social Security retirement benefits led

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to a cultural shift in attitudes toward retirement, where retirement had become an earned rite of passage and something to which individuals should aspire after a long career. However, in the 21st century, the cultural expectations with regard to retirement are again shifting. Expectations for continued part-time work, or at least some form of productive involvement, whether paid or unpaid, are increasing (Ekerdt, 2010; Shultz & Wang, 2011). Taken together, the various implicit and explicit societal-level impacts on retirement planning and decision making are likely to be substantial. As societal attitudes toward retirement change, so do the government policies that impact retirement (e.g., raising the age to obtain full Social Security benefits). In addition, as macroeconomic conditions change, societal attitudes toward older workers and retirement are also likely to change. Thus, as retirement becomes a more dynamic and volitional process on the part of older workers and their family, explicit societal-level policies, as well as implicit societal-level norms, are going to continue to shape how individuals prepare for, make decisions about, and ultimately adjust to retirement. As a result, how we study retirement in the 21st century needs to adjust to this new reality.

Using longitudinal, archival data to study retirement Given the temporal nature of the retirement process depicted in Figure 7.1, and explicated in the text above, longitudinal designs for studying retirement are essential. No longer can we hope that a single cross-sectional snapshot of the predictors of retirement decisions or reported levels of retirement satisfaction will provide a meaningful picture of how the temporal process of retirement plays out. Doing so would be analogous to looking at a single snapshot of a sporting event and thinking that it somehow would accurately capture the nuanced way that the event actually played out. Recently Fisher and Willis (2013) provided an extensive review of research methods in retirement research across multiple disciplines, which included a detail discussion of longitudinal designs for studying the temporal retirement process. In addition to studying retirement as it unfolds over time, another benefit to longitudinal research is that it may increase the generalizability of the sample. For example, Lumsdaine and Mitchell (1999) suggested that cross-sectional research is more likely to omit important individuals from study, such as those who retire early or die at younger ages. Second, longitudinal research allows researchers to examine the effects of both corporate and public policy changes on retirement behavior and outcomes as these policies change and evolve over time. Developments in statistical modeling techniques and software, such as structural equation modeling (SEM), multilevel modeling or hierarchical linear modeling (e.g., HLM), latent growth/decline curve modeling (LGM), and growth mixture modeling (GMM) have also facilitated longitudinal data analysis in retirement research. As a result, future research will likely rely even more heavily upon the use of longitudinal designs and analytic strategies to further our understanding of retirement as a temporal process.

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Retirement research designs According to Fisher and Willis (2013), retirement research can be broadly classified as quantitative and/or qualitative. Retirement research methods found in the quantitative realm include survey research methods, with public use data sets (e.g., the Health and Retirement Study [HRS]), cross-national data sets (e.g., Survey of Health, Aging, and Retirement in Europe [SHARE]), government data sets, or survey research data sets gathered by the researchers themselves. Given the prominence of survey research methods in retirement research, Fisher and Willis discussed in detail the various issues often involved in conducting meaningful survey research to study the temporal retirement process. These include survey sampling, sample designs, as well as dealing with survey non-response. They then reviewed measurement issues such as reliability and measurement error, as well as innovations in survey measurement techniques, such as adaptive testing and bracketing techniques. Data analysis issues are prominent whenever survey research methods are used, whether the researcher is collecting the data herself or whether she is using a public use data set. These include issues around dealing with missing data and imputing missing data, in addition to sample weights and analytical strategies (e.g., regression analysis, multilevel modeling, structural equation modeling). Although the majority of quantitative retirement research is based on survey research data, important retirement research has also been conducted in lab and field experiments (Fisher & Willis, 2013). By using experiments, researchers have been able to manipulate key independent variables to observe the effect on dependent variables of interest. Laibson and colleagues have conducted numerous lab and field experimental studies to improve our understanding of retirement behavior. For example, Choi, Laibson, and Madrian (2010) examined portfolio choice in a hypothetical experiment to determine why individuals invest in high fee mutual funds. Results of their study indicated that participants failed to minimize fees and placed a high weight on annualized investment returns since inception. In addition to lab experiments, researchers can also use natural or quasi-experiments. For example, both private and public sector institutions have developed policies that can have a large impact on whether individuals continue working or leave, as well as whether and how employees financially plan for retirement by saving in defined contribution benefits plans (e.g., 401(k) plans). These policies can change, and an important aspect of retirement research involves careful examination of the policy implications. Variations in policies create quasi-(or natural) experimental conditions, which can then be examined to determine the effect of policies on behavior. For example, research in the 1990s examined “window plans,” referring to employer-provided defined benefit pension plans in which benefits would be highest if an employee retired during a particular “window.” Because employers did not necessarily anticipate the rise in defined contribution pension plans, research on these window plans constituted a natural experiment (Lumsdaine & Mitchell, 1999). In addition, Choi, Laibson, Madrian, and Metrick (2002) studied employees’ savings behavior using retirement savings plan administrative data from employees in

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several large corporations that implemented changes to the design of their 401(k) plans. These researchers concluded that employer pension plan administrators can have a powerful influence on employee savings and investment behavior based on 401(k) plan features. Subsequently, Beshears, Choi, Laibson, and Madrian (2010) examined the impact of automatic enrollment in employer-sponsored retirement savings plans, including an analysis of employee participation in a firm that switched from an employer match to a non-contingent employer contribution. Results of their study indicated that automatic enrollment seems to hold promise for increasing participation in employer-sponsored retirement savings plans, and that participation did not decline to a great extent when the employer match of contributions was eliminated. Natural experiments have also been exploited by using natural cross-national variation in laws and policies to examine retirement behavior. This approach is common in the field of macroeconomics. For example, Rohwedder and Willis (2010) used cross-sectional data from the U.S., U.K., and 11 other European nations to determine whether average age at retirement was related to aggregate levels of cognitive functioning. By examining comparable measures of episodic memory in relation to labor force participation among people in their fifties and sixties crossnationally at a country-aggregate level, they concluded that early retirement has a significant negative impact on cognitive functioning. Gruber and Wise (1999) evaluated the effects of changes in employment laws on retirement patterns in the U.S., Japan, and Western Europe and concluded that changes in laws had a large effect on retirement behavior. Finally, qualitative research designs (e.g., focus groups, in-depth interviews, and case studies) have also been used to study the retirement process (Fisher & Willis, 2013). Such qualitative designs have been used both on their own, as well as in combination with the quantitative designs discussed above. These qualitative methods of studying retirement often complement and expand on what is found via quantitative methods such as electronic surveys. They can provide vivid examples to illustrate the underlying themes and findings from quantitative analyses, as well as put “a face” on the various theories used as the rationale for studying retirement. A good example of such use of case studies can be found throughout Wang, Olson, and Shultz (2013). While qualitative studies of retirement can be both labor intensive to conduct and eventually code, as Fisher and Willis (2013) recently noted, “Nonetheless, qualitative research can be a valuable tool for helping us describe and understand retirement phenomena” (p. 193).

Potential funding sources for retirement-related research A major source of support for retirement research in U.S. comes from the National Institute on Aging (NIA), which funds research directly through a variety of grant mechanisms. In addition, the NIA supports 14 research centers on the economics and demography of aging and is the major funder of the Health and Retirement Study and other data sets often used by retirement researchers (Fisher & Willis, 2013).

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The Retirement Research Consortium (RRC) also coordinates research on retirement. The RRC is funded by the United States Social Security Administration via cooperative agreements and consists of three retirement research centers: the Center for Retirement Research at Boston College, the Michigan Retirement Research Center at the Institute for Social Research at the University of Michigan, and the National Bureau of Economic Research (NBER) in Cambridge, Massachusetts. According to the Social Security Administration, the purpose of these centers is to: “1) conduct research and evaluation on a wide array of topics related to Social Security and retirement policy; 2) disseminate information on Social Security and retirement issues relevant to policy makers, researchers, and the general public, and 3) train scholars and practitioners in research areas relevant to Social Security and retirement issues.” These centers also facilitate access to valuable data sources for the study of retirement. Collectively, these centers play a significant role in promoting and facilitating research on retirement by providing researchers with funding and disseminating working papers so that researchers and policy makers better understand key issues regarding retirement and relevant issues among the aging population. Two additional sources of funding include the Alfred P. Sloan Foundation, which currently has a research program on Working Longer, and the National Institute for Occupational Safety and Health (NIOSH), which is concerned with occupational health issues among the aging workforce (among other populations).

Practical research tips There are many practical research tips we could provide for studying the dynamic nature of the temporal retirement process in the 21st century. However, we will limit ourselves to the top four we believe to be both most prominent and that will be most useful to researchers interested in studying retirement in order to have the strongest possible impact. 1

Take advantage of existing, longitudinal public use data sets. Fisher and Willis (2013) provided detailed information on a wide variety of public use data sets dealing with aging and retirement, as well as how to best access those data (in particular, see Table 12.2, p. 197, of their chapter). As we have emphasized throughout this chapter, retirement is a longitudinal, temporal process that occurs over many years, if not decades. As a result, longitudinal data are indispensable to effectively decipher this process. However, most researchers (particularly students and untenured professors) can’t wait for years or decades to collect longitudinal data themselves. Luckily they don’t have to, as there are enough longitudinal data sets currently available to answer almost any research question a researcher might have with regard to retirement, be it with regard to retirement planning, decision making, or post-retirement adjustment. Take full advantage of these publicly available data sets!

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Take full advantage of the various methods we present in this chapter. Although we discussed many quantitative and qualitative methods for studying retirement in this chapter, they are neither mutually exclusive nor exhaustive. We highly recommend that researchers combine multiple methods, including both qualitative and quantitative research methods not discussed in this chapter, when studying retirement as a longitudinal, temporal process. While the large scale archival data sets we highlighted throughout this chapter tend to lend themselves nicely to quantitative analyses, adding qualitative analyses will help enrich the data and further our understanding of the reasons behind the quantitative results (Wang, 2013b). In addition, the four boxes on the left of Figure 7.1 remind us that there are multiple levels of antecedents that influence the retirement planning, decision making, and adjustment processes. The use of multilevel modeling (also referred to as hierarchical linear modeling, mixed modeling, random coefficients modeling, random effects models, or nested models) in retirement research has been on the rise in recent years. Such models are useful for estimating parameters that vary at more than one level, and have been useful for measuring change over time. Only through using multilevel modeling/data analysis can we fully understand how these various factors work interactively to influence the longitudinal temporal retirement process. Study retirement from an interdisciplinary perspective. As noted by Fisher and Willis (2013) and Wang (2013a), retirement is studied by researchers from numerous fields, including public health, psychology, sociology, economics, organizational sciences, social work, and the list goes on. Further, Shultz and Wang (2011) noted that even within certain disciplines such as psychology there are researchers from various sub-disciplines (e.g., lifespan developmental, industrial-organizational, clinical-counseling, and vocational psychology) who study the retirement process from their own, idiosyncratic sub-disciplinary perspective. As a result, the research on retirement can be somewhat fragmented and insular. It is difficult to advance a research area when researchers from various disciplines, and sub-disciplines, are not informed by each other’s research. Therefore, it is critical for anyone who is studying retirement to review the research broadly, not only cutting across disciplines but also integrating those disciplinary perspectives in order to create true interdisciplinary research on retirement. Thus, collaborating with colleagues from other disciplines, and subdisciplines within your own field, is a practical way to help advance the field of retirement research. Study retirement from a cross-cultural perspective. Just as retirement research can be somewhat insular from a disciplinary perspective; it can also be myopic from a cultural perspective. Each culture has a certain way of looking at aging and retirement and those particularities are likely to be reflected in one’s research on retirement. Furthermore, countries vary widely regarding retirement ages and the extent to which governments provide sources of retirement income to retirees (Associated Press, 2013). Extensive research has demonstrated strong behavioral responses to retirement incentives such as

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public pensions – finding that most people retire when the pensions become available (Gruber & Wise, 2002). Some countries have sought to address macroeconomic issues by increasing the age of eligibility for public pensions. For example, retirement ages in Italy and Germany have recently been increased. As the bottom left box on Figure 7.1 highlights, various social norms about retirement, as well as government policies and economic conditions are going to impact how the retirement process plays out for most individuals. Therefore, we encourage you to not only work with colleagues from other disciplines, but also colleagues from other cultures in order to obtain a more complete picture of how retirement is enacted across cultures. And, as noted earlier, there are many cross-cultural data sets that when combined provide insights well beyond what each one could individually (e.g., Crimmins, Kim, & Solé-Auró, 2010).

Conclusion Retirement in the 21st century is, and will be, much different than what previous generations have experienced. As a result, we need to critically examine our research methods used to study retirement. Our goal in this chapter was to highlight how retirement has evolved over time and briefly discuss Wang and Shultz’s (2010) model of retirement to provide a foundation to highlight key methodological issues when studying retirement. Through implementation of the various methodological suggestions and practical tips presented in this chapter, contemporary researchers who study the dynamic nature of retirement will help us to better understand the process of retirement as depicted in Figure 7.1.

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Matthews, R. A., & Fisher, G. G. (2013). The role of work and family in the retirement process: A review and new directions. In M. Wang (Ed.), The Oxford handbook of retirement (pp. 354–370). New York: Oxford University Press. McGarry, K. (2004). Health and retirement: Do changes in health affect retirement expectations? Journal of Human Resources, 39(4), 624–648. McGonagle, A., Fisher, G. G., Barnes-Farrell, J. L., & Grosch, J. (2015). Individual and work factors related to perceived work ability and labor force outcomes. Journal of Applied Psychology, 100, 376-398. DOI: http://dx.doi.org/10.1037/a0037974 McNamara, T., Sano, J. B., & Williamson, J. B. (2012). The pros and cons of pro-work policies and programs for older workers. In J. W. Hedge & W. C. Borman (Eds.), The Oxford handbook of work and aging handbook (pp. 663–683). New York, NY: Oxford University Press. Moen, P. (2012). Retirement dilemmas and decisions. In J. W. Hedge & W. C. Borman (Eds.), The Oxford handbook of work and aging handbook (pp. 549–569). New York, NY: Oxford University Press. Neal, M. B., & Hammer, L. B. (2007). Working couples caring for children and aging parents: Effects on work and well-being. Mahwah, NJ: Lawrence Erlbaum. Rau, B. L., & Adams, G. A. (2005). Attracting retirees to apply: Desired organizational characteristics of bridge employment. Journal of Organizational Behavior, 26, 649–660. Rohwedder, S., & Willis, R. J. (2010). Mental retirement. Journal of Economic Perspectives, 24, 119–138. Shultz, K. S., Morton, K. R., & Weckerle, J. R. (1998). The influence of push and pull factors on voluntary and involuntary early retirees’ retirement decision and adjustment. Journal of Vocational Behavior, 53, 45–57. Shultz, K. S., & Olson, D. A. (2013). The changing nature of work and retirement. In M. Wang (Ed.), The Oxford handbook of retirement (pp. 543–558). New York: Oxford University Press. Shultz, K. S., & Wang, M. (2007). The influence of specific physical health conditions on retirement decisions. International Journal of Aging & Human Development, 65, 149–161. Shultz, K. S., & Wang, M. (2011). Psychological perspectives on the changing nature of retirement. American Psychologist, 66, 170–179. Steger, M. F., & Dik, B. J. (2009). If one is looking for meaning in life, does it help to find meaning in work? Applied Psychology: Health and Well-being, 1, 303–320. Taylor, M. A., & Geldhauser, H. A. (2007). Low-income older workers. In K. S. Shultz & G. A. Adams (Eds.), Aging and work in the 21st century (pp. 25–50). New York, NY: Psychology Press. Templer, A., Armstrong-Stassen, M., & Cattaneo, R. J. (2010). Antecedents of older workers’ motives for continuing to work. Career Development International, 15(5), 479–500. Topa, G., Mariano, J. A., Depolo, M., Alcover, C. M., & Morales, J. F. (2009). Antecedents and consequences of retirement planning and decision making: A meta-analysis and model. Journal of Vocational Behavior, 75, 38–55. van Dalen, H. P., Henkens, K., Henderikse, W., & Schippers, J. (2010). Do European employers support later retirement? International Journal of Manpower, 31, 360–373. von Bonsdorff, M. B., Seitsamo, J., Ilmarinen, J. Nygård, C., von Bonsdorff, M. E., & Rantanen, T. (2011). Work ability in midlife as a predictor of mortality and disability in later life: A 28-year prospective follow-up study. Canadian Medical Association Journal, 183(4), E235–E242. Wang, M. (2012). Health, fiscal, and psychological well-being in retirement. In J. Hedge & W. Borman (Eds.), The Oxford handbook of work and aging (pp. 570–586). New York, NY: Oxford University Press.

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Wang, M. (2013a). Retirement: An introduction and overview of the handbook. In M. Wang (Ed.), The Oxford handbook of retirement (pp. 3–9). New York: Oxford University Press. Wang, M. (2013b). Retirement research: Concluding observations and strategies for moving forward. In M. Wang (Ed.), The Oxford handbook of retirement (pp. 603–615). New York: Oxford University Press. Wang, M., Adams, G. A., Beehr, T. A., & Shultz, K. S. (2009). Career issues at the end of one’s career: Bridge employment and retirement. In S. G. Baugh & S. E. Sullivan (Eds.), Maintaining focus, energy, and options over the life span (pp. 135–162). Charlotte, NC: Information Age. Wang, M., Olson, D. A., & Shultz, K. S. (2013). Mid and late career issues: An integrative perspective. New York, NY: Routledge Academic Press. Wang, M., & Shultz, K. S. (2010). Employee retirement: A review and recommendations for future investigation. Journal of Management, 36, 172–206. Wheaton, F., & Crimmins, E. M. (2013). The demography of aging and retirement. In M. Wang (Ed.), The Oxford handbook of retirement (pp. 22–41). New York: Oxford University Press. Zickar, M. J. (2013). The evolving history of retirement within the United States. In M. Wang (Ed.), The Oxford handbook of retirement (pp. 10–21). New York: Oxford University Press.

SECTION III

Less successful ageing

8 THE FRONTAL AGEING HYPOTHESIS Evidence from normal ageing and dementia MacPherson, Sarah and Cox, Simon

Introduction It has now been over 20 years since neuropsychological theories first proposed that the cognitive changes associated with healthy adult ageing are due to frontal lobe decline (Mittenberg, Seidenburg, O’Leary, & DiGiulio, 1989; West, 1996). While advocates of the frontal ageing theory recognise that age-related decline occurs in other brain regions such as the medial temporal lobes (Driscoll et al., 2009; Fjell et al., 2009), the frontal lobes have been found to be especially vulnerable to agerelated changes in terms of overall and cortical volume, cortical thickness and white matter compared to other brain regions (Driscoll et  al., 2009; Fjell et  al., 2009). Studies of cognitive ageing have demonstrated that age-related differences are most apparent on tasks that tap frontal lobe dysfunction (Mittenberg et al., 1989). More recently, however, better anatomical localisation through neuroimaging techniques and the development of tests that tap processes associated with distinct frontal subregions have led to the proposal that age might have differential effects on frontal processes. In this chapter, we will discuss the fractionation of frontal lobe functions and the impact that healthy and pathological ageing have on frontal subregions and their specific functions. The chapter will review research examining differential age-related changes in frontal lobe functions; the variation in the pattern of agerelated neurostructural change within the frontal subregions; the cognitive profiles observed in pathological ageing in relation to frontal lobe function; and finally it will highlight some of the important methodological issues that should be considered in past and future work related to the frontal ageing hypothesis. Other theories exist that attempt to explain the cognitive changes associated with healthy and pathological ageing and these theories are not mutually exclusive (e.g., inhibition deficit theory; Gazzaley, Cooney, Rissman, & D’Esposito, 2005). Nonetheless, the studies reviewed in this chapter are discussed in relation to the frontal ageing hypothesis.

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Frontal lobe hypothesis of ageing Older adults perform more poorly than younger adults on executive tasks used in clinical practice and research to assess frontal lobe dysfunction. These tasks tend to focus on understanding and assessing higher-order control of goal-directed behaviour. Older age is associated with poorer performance on tasks including the Wisconsin Card Sorting Test (WCST; Ashendorf, & McCaffrey, 2007), the SelfOrdered Pointing Task (Lamar, & Resnick, 2004), the Tower tests (Allamanno, Della Sala, Laiacona, Pasetti, & Spinnler, 1987) and the Stroop task (Van der Elst, Van Boxtel, Van Breukelen, & Jolles, 2006). While evidence supporting age-related decline in frontal executive abilities is robustly replicated, the obvious question we asked in the late 1990s concerned the dissociation between older adults and frontal patients’ behaviour, despite frontal involvement in both groups. Several single cases reported in the literature provided strong evidence that some frontal patients demonstrate severe social difficulties: Phineas Gage who experienced the passage of a tamping iron through his frontal lobes (Harlow, 1848); Vincenzo, a murderer who was later diagnosed with a frontal brain tumour (Agostini, 1914); and patient EVR, the chief accountant whose behaviour drastically changed after the removal of a orbitofrontal meningioma (Eslinger, & Damasio, 1985). The other detail to note was that frontal patients with impaired social processing may have intact executive function (Eslinger, & Damasio, 1985). These findings, coupled with the fact that neither older individuals themselves nor their friends and family report severe personality change in non-pathological ageing, were difficult to reconcile in relation to the traditional frontal ageing hypothesis (Phillips, & Della Sala, 1998; MacPherson, Phillips, & Della Sala, 2002). To account for this dissociation between the behaviour and cognitive performance of older adults and frontal patients, we considered the subdivisions of the frontal lobes of the brain. The frontal lobes are estimated to make up one-third of the total cortex and include 15 Brodmann areas, each with different cellular compositions and inter-connectivity with other brain regions (Petrides, & Pandya, 1994). Luria (1966) had the foresight to propose the existence of a number of “frontal lobe syndromes” where the frontal lobes are fractionated into subregions with different functions: the premotor area associated with motor and skilled movements, the prefrontal convexity associated with planning and monitoring in goal-directed behaviour and the orbital prefrontal region associated with changes in personality. Yet, it took nearly another 30 years for clinicians and researchers to consider whether frontal executive processes can be fractionated into several components (Burgess, & Shallice, 1994) and in different frontal subregions (Shallice, Stuss, Picton, Alexander, & Gillingham, 2008) or whether frontal functions simply overlap (Duncan, & Miller, 2002). More recently, frontal patients are being categorised into frontal subgroups rather than being considered as an undifferentiated frontal group (Stuss et al., 1998, 2000; Shallice et al., 2008). While the fractionation versus global accounts of frontal lobe function are still debated, the initial neuropsychological models of ageing had not considered that increasing age may affect the structure and function of some, but not all, frontal subregions.

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Fractionation of frontal processes Several models of frontal lobe fractionation have been proposed (Godefroy, Cabaret, Petit-Chenal, Pruvo, & Rousseaux, 1999). The existence of such models, as well as the availability of a greater number of patients with well-defined focal lesions (Stuss et al., 2005), influenced those working in the frontal lobe literature to use more detailed frontal lesion localisation. Anatomical classification techniques made it possible for clinicians and researchers to categorise their frontal patients based on their performance on frontal executive tasks, revealing dissociations between frontal processes (Stuss et al., 1998, 2000; MacPherson, Turner, Bozzali, Cipolotti, & Shallice, 2010). The lateral prefrontal regions have been associated with executive processes such as shifting, updating and inhibition (Yochim, Baldo, Nelson, & Delis, 2007; Yochim, Baldo, Kane, & Delis, 2009), while the medial (primarily the ventromedial) and orbitofrontal regions have been related to emotional and social processing (Eslinger, & Damasio, 1985; Hornak et al., 2003). In the early 2000s, we proposed our dorsolateral prefrontal theory of cognitive ageing where dorsolateral prefrontal deterioration rather than global frontal deterioration accounts for the cognitive decline associated with healthy adult ageing (MacPherson et al., 2002). This was not only based on the findings in the neuropsychological literature, but the limited neuroimaging data available at that time, which suggested that there was a decrease in brain weight, cortical thickness and the number of large neurons in the dorsolateral prefrontal cortex (Terry, DeTeresa, & Hansen, 1987) compared to the later shrinkage and smaller neuronal loss in the ventromedial prefrontal cortex (Haug, Barmwater, Eggers, Fischer, Kühl, & Sass, 1983). We administered the Wisconsin Card Sorting Test, the Self-Ordered Pointing Task and the Delayed Response Task as tasks tapping dorsolateral prefrontal function and the Emotion Identification Task, the Iowa Gambling Task and the Faux Pas Task as tasks tapping ventromedial prefrontal function. Our results revealed that older adults performed significantly more poorly than younger adults on the “dorsolateral” tests but not the “ventromedial” tests, except the Emotion Identification Task. In line with our dorsolateral ageing theory, age effects are consistently reported on executive tasks thought to tap dorsolateral prefrontal functions including the Wisconsin Card Sorting Test (Ashendorf, & McCaffrey, 2007), the Tower test (Allamanno et al., 1987) and the Self-Ordered Pointing task (Salat, Kaye, & Janowsky, 2002; Lamar, & Resnick, 2004). Support for our proposal that age effects are not found on tasks thought to tap ventromedial prefrontal functions is less consistent, with no clear consensus for age effects on tasks of emotion identification, the Iowa Gambling task, Theory of Mind stories, Reading the Mind in the Eyes and the Faux Pas test (see MacPherson, Della Sala, Cox, Girardi, & Iveson, 2015 for a review of age effects on frontal tasks). Around the same time as our study was published, Lamar and Resnick (2004) reported that orbitofrontal functions decline with age, while Salat et al. (2002) reported that frontal functions in general decline with age. Lamar and Resnick (2004) administered “dorsolateral” tasks (Self-Ordered Pointing Test, Phonemic Fluency and Digit Span and Months Backwards) and “orbitofrontal” tasks (Iowa Gambling Task,

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Delayed Match to Sample and Delayed Non-Match to Sample) and found that their older adults performed significantly poorer on the Self-Ordered Pointing Test and Delayed Match and Non-Match to Sample Tests. They argued that “orbitofrontal” tasks were more sensitive to the effects of ageing than “dorsolateral” tasks. Salat et al. (2002) argued for global frontal decline as they found age-related differences on the Self-Ordered Pointing Task, the Conditional Association Task, N-Back Task and the Object Alternation Task. This finding was echoed more recently when Baena, Allen, Kaut and Hall (2010) assessed younger adults and older adults on “dorsolateral” tasks (Wisconsin Card Sorting Test, the Trail Making Test, the Stroop Test and Digit Span Backwards) and “ventromedial” tasks (Iowa Gambling Task and Emotion Identification) and reported age differences on both task types. Attempts to characterise the influence of age on frontal lobe function have continued using neuropsychological methods but the cognitive ageing literature has yet to reach a consensus about how ageing affects the processes tapping various frontal subregions. The inconsistency among these findings may be due to no tests existing that specifically tap only one frontal subregion; even if there are tests where the evidence for the involvement of one frontal subregion is stronger than other tests. This might be particularly true of more complex tasks such as the Iowa Gambling Task where there is evidence for both dorsolateral and ventromedial prefrontal involvement (MacPherson, Phillips, Della Sala, & Cantagallo, 2009). Still, while the findings are somewhat inconsistent, there do appear to be more studies supporting dorsolateral prefrontal rather than orbitofrontal decline in healthy ageing.

Evidence from neuroimaging Conceiving of the frontal lobes as a single entity subserving a single unitary function is untenable. Rather, they can be parsed into several sub-regions based on neuronal density, presence of granule cells, glia content and patterns of afferent and efferent connectivity (Zald, 2007), phylogenetic development (Sanides, 1969) and function (discussed above). Furthermore, studies examining change to brain structure suggest that frontal lobe decline does not appear unitary. Several reports suggest that the lateral frontal cortex exhibits a greater age-related decline than other regions (Driscoll et  al., 2009; Fjell et  al., 2009), while others identify putative decline in lateral and anterior cingulate areas (Tisserand et al., 2002; Sowell, Peterson, Thompson, Welcome, Henkenius, & Toga, 2003; Grieve, Clark, Williams, Peduto, & Gordon, 2005). Such differential frontal decline may partially explain differences in cognitive ability in older age (MacPherson et  al., 2002; Tisserand, van Boxtel, Pruessner, Hofman, Evans, & Jolles, 2004), though some have identified either additional orbital (Convit et  al., 2001) or predominantly orbital and medial frontal volumetric decline (Raz, Ghisletta, Rodrigue, Kennedy, & Lindenberger, 2010). Methodological differences may well underlie some of the inconsistencies in these findings, but the relatively consistent report of dominant lateral frontal decline is commensurate with evidence of age-related decline on cognitive tasks linked to the functioning of these regions. Likewise, the

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putative stability in performance on tests of social and emotional processing in older age may be partially supported by the relative age-related invariance in orbital and ventromedial frontal regions. A recent meta-analysis of structural imaging studies across 3,272 participants (Yuan, & Raz, 2014) reported that a larger lateral (but not orbital) prefrontal cortex is indeed beneficial to performance on executive measures for which there is substantial evidence for age-related decrements. The particular importance of maintaining the lateral frontal cortex in older age may be further amplified when considering accounts of age-related “dedifferentiation” or compensation. Functional neuroimaging studies have observed mean increases in (mainly) frontolateral activation in older participants when compared to younger counterparts performing the same complex cognitive tasks (see Park, & Reuter-Lorenz, 2009). It remains unclear what this pattern of activity represents. It could reflect a breakdown in inhibitory processes, such that the brain is unable to direct appropriate neural resources to the task at hand and might be caused by a failure to inhibit right frontal activity – an ability that is proposed to be present in younger individuals (Logan, Sanders, Snyder, Morris, & Buckner, 2002). However, several lines of evidence suggest this additional involvement of right frontolateral areas reflects an adaptive neural response that might compensate for accumulated structural decline in regions traditionally engaged during the task, and is beneficial for performance (de Chastelaine, Wang, Minton, Muftuler, & Rugg, 2011; Cox et al., 2015). While it should be noted that the majority of this research has focussed on memory abilities, these data highlight a further possible reason why lateral frontal lobe decline may be particularly pertinent to cognitive decline. It is tempting to conclude that age-related cognitive decline is predominantly marked by a decline in complex cognitive functioning due to sub-regional prefrontal cortex atrophy, yet these areas are only one part of larger networks that support complex cognition. Increasing age is also associated with thinning or volumetric decline in temporal and/or parietal cortex (Tisserand et al., 2004; Fjell et al., 2009; Bakkour, Morris, Wolk, & Dickerson, 2013), though age effects on both parietal and temporal regions are not always co-incident. Sub-cortical brain structures also exhibit age-related decline (Fjell et al., 2013). This also appears to be true of the brain’s connective white matter. During the normal process of ageing, hyperintensities become visible in the white matter on MRIs, ventricular volume increases, overall white matter volume decreases (Raz, & Rodrigue, 2006) and the myelin sheath provides less complete coverage of the axon (Marner, Nyengaard, Tang, & Pakkenberg, 2003). Thus, additional variance in age-related cognitive decline may also be accounted for by declining white matter integrity. In older participants, white matter diffusivity (derived from Diffusion Tensor MRI; DT-MRI) is significantly related to individual differences in measures of cognition (Fjell, Westlye, Amlien, & Walhovd, 2011; Penke et al., 2012). As with studies of cortical ageing, researchers have also investigated whether there are differential effects of increasing age across different regions of white matter, and generally indicate that normal healthy ageing is characterised by a gradient of anterior > posterior change. Greater age effects on measures of white matter

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diffusivity are reported in the genu than the splenium of the corpus callosum, and in frontal white matter than in more posterior regions (Head et  al., 2004; Salat et  al., 2005). Further, the relationship between greater age and poorer cognitive performance on memory and executive function tests were mediated by differences in frontal and temporal white matter volume among a group of 199 participants (21–79 years; Brickman et al., 2006). In summary, these data indicate that normal ageing is associated with decreases in the volume and thickness of frontolateral and dorsomedial cortex, and also with reduced volume and degraded microstructure of frontal white matter. In addition, changes to parietal and temporal cortical and white matter are observed. These changes may be partly responsible for the observed patterns of cognitive decline described above. However, a fundamental question that remains to be adequately addressed is: how much of the variance in cognitive ageing can be attributed to degradation in i) frontolateral cortex, ii) associated cortical and sub-cortical structures and iii) white matter that connects structures that facilitate particular cognitive abilities? As will be addressed in the following section, an addendum to this question concerns the spectra between successful and pathological brain and cognitive ageing, which adds a further level of complexity.

Evidence from pathological ageing It appears that healthy and pathological ageing may be subject to different (and potentially multiple co-incident) patterns of brain ageing that have complex ramifications for cognition, dependent upon the severity and number of influences at play. While Head et al. (2004) identified an anterior > posterior pattern of white matter ageing among normal healthy participants, they found that Alzheimer’s disease (AD) patients exhibited greatest white matter changes in posterior lobar regions, in addition to comparable anterior changes found in their non-demented counterparts. In relation to cortical thickness, Bakkour et al. (2013) report that although there are some commonalities between cortical thinning in healthy ageing when compared to AD (such as dorsolateral prefrontal and inferior parietal cortex), medial temporal atrophy may be an indicator of pathological ageing. In addition, the pattern of brain ageing experienced by both groups was independently related to cognitive performance (Bakkour et al., 2013). In a separate study, individuals with amnestic mild cognitive impairment (MCI) may represent a heterogeneous group of patients exhibiting a variety of biological substrates of ageing. Carmichael et  al. (2013) reported five separate factors of cortical atrophic change among a group of 317 such patients who were scanned at six-month intervals over two years. These factors represented frontal ageing (exhibited in normal ageing), posterior default mode regions and medial temporal lobe changes (typical of early AD), sensorimotor and occipital regions (typically spared by the early onset of AD) and general global atrophy. In terms of neuropsychology, while most research has shown that episodic memory is the earliest indication of cognitive decline (Albert, & Blacker, 2006), a number of studies suggest that preclinical AD and AD individuals are also impaired on

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frontal executive tests as well as tests of attention, language and visuospatial abilities (Bäckman, Jones, Berger, Laukka, & Small, 2005; Rapp, & Reischies, 2005). However, when individuals who later developed AD were studied retrospectively, Mickes et  al. (2007) found that episodic and semantic memory were more significantly impaired than frontal executive abilities in the three years prior to diagnosis. This is consistent with the putative medial temporal brain changes that characterise the early stages of AD. In functional neuroimaging research, MCI patients show significant relationships between their performance on frontal executive tests and changes in frontal lobe activation (including hyperactivation). Clément, Gauthier and Belleville (2013) recently reported that MCI individuals who had higher levels of cognition showed over-activation of the left middle and superior frontal gyri and the left postcentral gyrus while performing an executive task involving manipulation. In the same study, MCI individuals with more severe cognitive decline demonstrated under-activation of similar left frontal regions (left inferior and middle frontal gyri). It has been proposed that additional brain regions are recruited in the early stages of MCI to compensate for cerebral atrophy and preserve cognition. However, there comes a point in the disease progression beyond which this mechanism can no longer compensate for further decline (Friston, & Price, 2003). The wide variability in cognitive performance among healthy and pathologically ageing individuals may be due to the amount of compensation available to slow cognitive decline (Stern, 2002). In the early stages of behavioural variant frontotemporal dementia (bvFTD), where individuals experience symptoms such as personality change, disinhibition and impulsivity, performance on tests of social cognition and multitasking are reportedly better disease predictors than traditional frontal executive tests (Torralva, Roca, Gleichgerrcht, Bekinschtein, & Manes, 2009; Gleichgerrcht, Ibáñez, Roca, Torralva, & Manes, 2010). It is only later in the progression of bvFTD that performance on traditional frontal executive tasks declines (Torralva et al., 2009). The changes in personality and aspects of social cognition have been associated with initial atrophy in the orbitofrontal and frontal pole regions (Rosen et al., 2002), with the atrophy extending into other prefrontal regions later in the disease (Williams, Nestor, & Hodges, 2005). In summary, the pathological ageing literature suggests that different pathological ageing syndromes confer different patterns of brain atrophy and cognitive decline that may be distinct from profiles of normal ageing.

Methodological considerations and future study design In this final section, we highlight important methodological issues pertinent to the synthesis of previous work and the design of new studies.

i) Ecological validity One issue with the assessment of frontal lobe functions is whether performance on frontal tests reflects performance in real-life (so-called ecological validity; Burgess,

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Evans, Emslie, & Wilson, 1998). Research has provided somewhat inconsistent results where some studies do show significant relationships between performance on frontal executive tests and everyday functioning (Burgess et al., 1998), but others do not (Amieva, Phillips, & Della Sala, 2003). Even some tests with good ecological validity report only moderate relationships with everyday life, leaving a considerable amount of the variance in everyday abilities unaccounted for (Chaytor, SchmitterEdgecombe, & Burr, 2006). The laboratory-based methods used to assess frontal abilities may contribute to the poor association with real-life performance. Older adults often perform as well as younger adults when they are assessed using naturalistic tasks. This may be due to older adults having developed significant experience throughout their lifetime that they can draw upon (Kliegel, Martin, McDaniel, & Phillips, 2007), or such tasks being more familiar to older adults (Provencher, Demers, Gagnon, & Gélinas, 2012). Multitasking paradigms are one example of frontal executive tasks devised to reflect real-life functioning. Multitasking assesses individuals’ abilities to complete several tasks within a time limit by effectively switching between these tasks and planning the order to perform them (Shallice, & Burgess, 1991). Ageing studies that have examined planning abilities and prospective memory (memory for future goals) in real-life, processes thought to be the foundation of multitasking, show that older adults are able to perform as well, and sometimes better, than younger adults (Kliegel et al., 2007). Paradoxically, prospective memory is poorer in older adults compared to younger adults when assessed using laboratory-based tasks (Henry, MacLeod, Phillips, & Crawford, 2004). Laboratory-based studies aimed at assessing multitasking more generally in cognitive ageing have reported age differences. Older adults make more overall errors and more rule breaks than younger adults in virtual shopping malls (Rand, Rukan, Weiss, & Katz, 2009) and demonstrate less efficient planning and task failures on the Breakfast task, a computerized cooking task where various foods should be cooked so they are ready at the same time (Craik, & Bialystok, 2006). In the real world, however, older adults are not typically reported to have difficulty performing tasks that involve multitasking such as cooking a family dinner or grocery shopping (Phillips, Kliegel, & Martin, 2006). Our own work found no decline in midlife ageing when multitasking in a shopping centre in Aberdeen, UK, and yet middleaged participants were significantly worse on two out of three traditional executive measures than younger adults (Garden, Phillips, & MacPherson, 2001). It should be noted that other work has reported significant positive correlations between age and the number of rule breaks and the total number of errors made when multitasking in a real-life setting (Alderman, Burgess, Knight, & Henman, 2003). Longer time to complete the tasks in our study may have resulted in less time pressure on participants. Some of our own preliminary data suggest that the absence of age effects in multitasking may be partly due to stimulus familiarity; age effects were only present for a multitasking paradigm where the stimuli were abstract, but not when they were more familiar. In her MSc dissertation project, McKeever (2014) devised two

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multitasking paradigms based on the Six Elements Test (Shallice, & Burgess, 1991) that were matched as closely as possible for structure and format except the features and materials adopted were either artificial or more proximal to real world tasks (see Table 8.1). In both versions, participants were informed that they had 10 minutes to attempt the tasks and points would be deducted for rule-breaks and errors. Points were gained by following the rules and attempting all tasks. Participants were able to recall the rules before and after the task (see Table 8.2). Points were awarded for: keeping track of the timing tasks; placing the correct values in the compartmented container; sorting the cards correctly; and responding to/ignoring the sounds. Participants were told that they would receive more points

TABLE 8.1 The various subtasks included in the abstract and familiar versions of the

multitasking paradigm. Abstract

Familiar

Timing task

Start a timer by pressing a green button and then switch it off again two minutes later by pressing a red button. Immediately afterwards, start the timer again by pressing the green button and then switch it off again one minute later.

Turn on a kettle and then switch it off again two minutes later. Immediately afterwards, lift up and down a teapot lid and repeat the action again one minute later.

Counting task

Sort coloured tokens with values printed on them (i.e., 100, 50, 20, 10 or 2) so that they make up a particular value (e.g., 162) and place each token in a separate compartment of a plastic container (e.g., place the 100, 50, 10 and 2 tokens in separate compartments).

Sort coins (i.e., £1, 50p, 20p, 10p and 2p) so that they make up a particular value (e.g., £1.62) and place each coin in a separate compartment of a plastic container (e.g., place the £1, 50p, 10p and 2p in separate compartments).

Card sorting task

Judge whether two geometric abstract shapes on a card were the same or different (e.g., a missing piece or including an extra line). Sort the card into one of two baskets clearly labelled ‘Same’ and ‘Different’.

Judge whether two nameable objects on a card were the same or different (e.g., a book and a hat or a book and a book). Sort the card into one of two baskets clearly labelled ‘Same’ and ‘Different’.

Interruption task

On hearing one non-meaningful synthetic sound, ignore it but on hearing the other non-meaningful synthetic sound, take a marker from the table and mark an ‘X’ on a sheet of paper hung on the door.

On hearing the dog barking, ignore it but on hearing the doorbell, take a marker from the table and mark an ‘X’ on a sheet of paper hung on the door.

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TABLE 8.2 Instructions for both the abstract and familiar versions of the multitasking

paradigm. 1.

You must complete three rounds of the timing task during the ten minutes. Points will be deducted if a fourth round is started.

2.

You must make up the values on the list with the minimum amount of tokens/ coins necessary.

3.

You must sort the cards into the correct baskets.

4.

When you hear sound A, you must ignore it.

5.

When you hear sound B, you must mark an ‘X’ with a marker on the piece of paper on the door behind you.

for performing the first half of the Counting and Card Sorting tasks. The scoring procedure resulted in an overall score out of 100 points. McKeever (2014) recruited 34 healthy younger adults (20–39 years) and 34 healthy older adults (60–80 years). Half the younger and older groups performed the familiar version and half performed the abstract version. Figure 8.1 demonstrates the mean overall scores for the younger and older adults. A 2 (age) x 2 (task type) analysis of variance demonstrated a significant age x task type interaction, F(1,56) = 4.526, p < .05, where older adults performed significantly more poorly than younger adults on the abstract version (p < .001) but not the familiar version ( p = .46). These preliminary data suggest that familiarity with stimuli influences whether age effects are found on multitasking performance. Poor ecological validity may also explain some of the inconsistent results reported in the social cognition and cognitive ageing literature. Anecdotally, older adults do not seem to behave inappropriately in their real-life social interactions and healthy ageing is associated with better interpretation and regulation of emotion (Blanchard-Fields, Jahnke, & Camp, 1995). Yet, age effects are still reported on tasks purported to assess the processes underlying successful social interactions, including emotion recognition (MacPherson et al., 2002), theory of mind (Maylor, Moulson, Muncer, & Taylor, 2002) and social decision-making (Denburg, Tranel, & Bechara, 2005). Our work has attempted to address the paradox between older adults’ experiences in the real world and laboratory assessments of emotion identification abilities. Laboratory-based studies tend to assess older adults’ ability to recognise emotion presented through one sensory modality (e.g., facial expressions, prosody from voices, body posture) and age affects are reported (Phillips, MacLean, & Allen, 2002; MacPherson, Phillips, & Della Sala, 2006). However, we did not find age differences when older adults were presented simultaneously with congruent static faces and non-verbal affective bursts (Hunter, Phillips, & MacPherson, 2010). Another study using congruent dynamic facial expressions and single words also found that older people benefited from being presented with congruent cross-modal emotional information, although the age effect did not disappear (Lambrecht, Kreifelts, & Wildgruber, 2012). Similarly,

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The means and standard deviations for the younger and older adults performing the abstract and familiar versions of the multitasking paradigm.

FIGURE 8.1

the inconsistent results across studies investigating theory of mind (understanding the mental states of others) where some studies have reported poorer performance in older adults compared to younger adults (Maylor et al., 2002; Phillips et al., 2002), but others show that older adults perform as well or even outperform younger adults (Happé, Winner, & Brownell, 1998; MacPherson et al., 2002), may be partly due to certain tasks not resembling real-life social situations. We are not suggesting that laboratory-based tasks are redundant when assessing frontal lobe abilities but rather the type of test used depends upon the nature of the question being asked. If clinicians and researchers are keen to understand whether their assessments reflect real-life in an ageing population, then consideration of the ecological validity of frontal lobe tests is important. However, to understand more specific aspects of frontal function (separate from individual differences in the ability to compensate through other means), the traditional, laboratory-based tasks should be used. Both types of test are important, but for different reasons, and can contribute valuable and complementary information about the neural and biological processes that underpin ageing and the actual impact that functional changes have on real-life functioning.

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ii) Methods of MRI analysis The use of structural and functional neuroimaging to investigate links between brain and cognitive decline in old age is widespread. However, the variety of different methodologies used – each with their own advantages and limitations – is likely to contribute a degree of noise to cross-study comparison. Understanding the theoretical assumptions on which different brain imaging methods rely can also help to refine research questions and fine-tune critical analysis of reported findings. Particularly pertinent to the study of regional neurostructural decline in older age are the ways in which a researcher chooses to identify specific brain regions from participants’ MRI scans. Though it is generally accepted that gyral landmarks on an MRI are a useful (but still imperfect) way of identifying distinct regions, there is a great deal of variance in how the prefrontal cortex and its subregions are measured in studies of frontal volumetry (Bohland, Bokil, Allen, & Mitra, 2009; Cox et al., 2014). Thus, paying attention to how cerebral regions are delineated may partially help to explain discrepant findings for the ‘same’ nominal region, though this should not preclude comparisons entirely, particularly where cohort studies or meta-analyses across large numbers might afford enough statistical power to partially offset such noise (Yuan, & Raz, 2014). However, in the context of future study design, we previously reported that the selection of a coherent frontal lobe parcellation schema is possible, based on extensive literature on the cytoarchitectural, functional and hodological topography of the brain (Cox et al., 2014). In addition, no single brain is entirely the same as another, which provides a challenge for any researcher wishing to directly compare them. The cortical folding pattern of the frontal lobes is highly complex with many well-documented variants. The orbital surface shows a wide variety of complex sulcal patterning (Uylings, Sanz-Arifita, de Vos, Pool, Evers, & Rajkowska, 2010) and c.30–60% of individuals possess a second cingulate gyrus known as the paracingulate (Fornito et al., 2004). There is variance in the degree to which parcellation protocols are able to account for these known variants (Cox et al., 2014), which might partly explain discrepancies between methods (Tisserand et  al., 2002; Lindberg, Manzouri, Westman, & Wahlund, 2012). Due to these individual differences in brain size and shape, comparisons among different brains necessitate a degree of compromise. Brain measures need to be normalised in some way to make them comparable, at the expense of reduced fidelity with which they can be compared. For example, methods of manual volumetry make measurements of the brain on each person’s scan separately (i.e., their ‘native’ space) and traditionally use intracranial volume (ICV) as a covariate to account for individual head size (Sanfilipo, Benedict, Zivadinov, & Bakshi, 2004). ICV is also considered to reflect maximal healthy brain volume in older individuals (because the brain fills the intracranial vault in younger healthy participants but decreases with age; Royle et  al., 2013). In ageing, the

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relative difference between individuals (i.e., how much is left as a proportion of what used to be there?) is informative (Davis, & Wright, 1977). While this archaeological measure of maximal brain size can be exploited to give longitudinal information from a single scan, even the method for estimating ICV itself can impact results (Nordenskjöld et al., 2013). Moreover, the appropriateness of correcting sub-regions for ICV is debatable because ICV pertains to maximal whole brain size, rather than giving an index of the maximal size of the specific region in question, so it measures the region’s volume relative to how much of the entire brain there used to be. Although imperfect, this method may still be preferable to comparing raw regional volumes in ageing where longitudinal data are unavailable (Cox et al., 2015). Automated methods often employ a method of image registration, whereby the brain scan of each individual is spatially transformed into a common ‘standard’ space (or a reference atlas is transformed to each individual’s ‘native’ space; see Hellier et al., 2003). Such methods perform a highly complex series of operations that allow for comparison of brain characteristics across large numbers of participants that may otherwise simply not be possible. However, in order to achieve the comparison, some fidelity is necessarily lost, such that researchers have diminished power to detect differences in brain areas that do not overlap well across all participants. For example, Tisserand et al. (2004) used VBM to examine relationships between gray matter density and longitudinal cognitive ability scores in older age. They explicitly examined possible effects of ‘anatomical noise’ on their results by plotting a probabilistic map of each voxel being classified as gray matter. The resultant map (Tisserand et al., 2004; Figure 3) suggested that anatomical variability leads to a diminished statistical power to detect individual gray matter covariances in frontal gyri with age or cognition. These issues are important considerations for measuring white matter tract characteristics too. In order to identify white matter pathways, a series of target or reference tracts might be used, or an entire white matter ‘skeleton’ might be created; each are of a predefined shape and location and are registered with each of the target brains to-be-analysed (Smith et al., 2006; Bastin et al., 2010). This allows consistent and reliable measurement of the same tract across individuals, but there is often the requirement to make the reference tracts or skeleton relatively narrow to minimise tractography errors (i.e., exclude unrealistic paths of the target tract and/or too inclusive of non-white matter, or white matter that is not of interest). Consequently, one should bear in mind that such outcome measures are derived only from central parts of well-aligned white matter tracts (see also Bach et al., 2014). These observations are particularly pertinent to the study of ageing because features of increasing age (atrophy, skull-thickening, white matter lesions and infarcts) increase the degree of morphological variance between participants than in younger healthy populations (Cabezas, Oliver, Lladó, Freixenet, & Cuadra, 2011). If the frontal lobes are particularly susceptible to age-related decline, this can potentially amplify the abovementioned difficulties for researching frontal

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brain areas (Aribisala et al., 2013). In addition to the points above (particularly relevant to the ageing frontal lobe), the reader is also referred to other informative commentaries on MRI-based methods such as fMRI (Logothetis, 2008), voxelbased morphometry (Scarpazza, Sartori, De Simone, & Mechelli, 2013), DT-MRI (Jones, Knösche, & Turner, 2013) on which connectome (Buchanan, Pernet, Gorgolewski, Storkey, & Bastin, 2014) and tract-based spatial statistics (Bach et  al., 2014) analyses are based.

Practical research tips 1 2

3

It is important to consider the fractionation of frontal lobe processes when assessing healthy and pathological ageing. Poor ecological validity may underlie the age effects reported on certain frontal tasks; consequently older adults’ performance may not reflect their abilities in real-life situations. When considering brain imaging bear in mind the limitations alongside your research question and study design.

Conclusions This current review has focused on the frontal ageing hypothesis, one of the most prominent theories within the cognitive ageing literature. The frontal theory claims that healthy adult ageing is associated with the deterioration of the frontal lobes of the brain, earlier and more rapidly than other brain areas, and it is this frontal lobe deterioration that results in many age-related cognitive changes. Rather than a functionally homogeneous region, a large body of evidence suggests that its sub-regions experience differential structural and functional decline with increasing age. The review also highlights some important methodological issues associated with frontal lobe assessment and cognitive ageing, which include the fractionation of frontal lobe functions, the importance of identifying frontal lobe sub-regions accurately and validly in MRI modalities and considering white matter ageing. These are some of the important considerations for clinicians and researchers when designing assessments and which necessitate further research within the topic of the frontal lobes and cognitive ageing. In particular, the real-life versus laboratory paradox within the context of experimental methodologies and relevance to everyday functioning in cognitive ageing should be considered.

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Stuss, D. T., Levine, B., Alexander, M. P., Hong, J., Palumbo, C., Hamer, L., Murphy, K. J., & Izukawa, D. (2000). Wisconsin Card Sorting Test performance in patients with focal frontal and posterior brain damage: Effects of lesion location and test structure on separable cognitive processes. Neuropsychologia, 38(4), 388–402. Terry, R. D., DeTeresa, R., & Hansen, L. A. (1987). Neocortical cell counts in normal human adult aging. Annals of Neurology, 21(6), 530–579. Tisserand, D. J., Pruessner, J. C., Arigita, E. J. S., Boxtel, M. P. J. V., Evans, A. C., Jolles, J., & Uylings, H. B. M. (2002). Regional frontal cortical volumes decrease differentially in aging: An MRI study to compare volumetric approaches and voxel-based morphometry. Neuro Image, 17, 657–669. Tisserand, D. J., van Boxtel, M. P. J., Pruessner, J. C., Hofman, P., Evans, A. C., & Jolles, J. (2004). A voxel-based morphometry study to determine individual differences in gray matter density associated with age and cognitive change over time. Cerebral Cortex, 14(9), 966–973. Torralva, T., Roca, M., Gleichgerrcht, E., Bekinschtein, T., & Manes, F. (2009). A neuropsychological battery to detect specific executive and social cognitive impairments in early frontotemporal dementia. Brain, 132(5), 1299–1309. Uylings, H. B. M., Sanz-Arifita, E. J., de Vos, K., Pool, C. W., Evers, P., & Rajkowska, G. (2010). 3-D cytoarchitectonic parcellation of human orbitofrontal cortex correlation with post-mortem MRI. Psychiatry Research, 183(1), 1–20. Van der Elst, W., Van Boxtel, M. P. J., Van Breukelen, G. J. P., & Jolles, J. (2006). The Stroop Color-Word Test: Influence of age, sex, and education; and normative data for a large sample across the adult age range. Assessment, 13(1), 62–79. West, R. L. (1996). An application of prefrontal cortex function theory to cognitive aging. Psychological Bulletin, 120, 272–292. Williams, G. B., Nestor, P. J., & Hodges, J. R. (2005). Neural correlates of semantic and behavioural deficits in frontotemporal dementia. NeuroImage, 24(4), 1042–1051. Yochim, B. P., Baldo, J. V., Kane, K. D., & Delis, D. C. (2009). D-KEFS Tower Test performance in patients with lateral prefrontal cortex lesions: The importance of error monitoring. Journal of Clinical and Experimental Neuropsychology, 31(6), 658–663. Yochim, B., Baldo, J., Nelson, A., & Delis, D. C. (2007). D-KEFS Trail Making Test performance in patients with lateral prefrontal cortex lesions. Journal of the International Neuropsychological Society, 13, 704–709. Yuan, P., & Raz, N. (2014). Prefrontal cortex and executive functions in healthy adults: A meta-analysis of structural neuroimaging studies. Neuroscience and Biobehavioral Reviews, 42, 180–192. Zald, D. H. (2007). Orbital versus dorsolateral prefrontal cortex: Anatomical insights into content versus process differentiation models of the prefrontal cortex. Annals of the New York Academy of Sciences, 1121, 395–406.

9 EXAMINING COGNITIVE FUNCTION IN TYPE 2 DIABETES The importance of an inclusive research approach Jones, Nicola, Greer, Joanna, Riby, Leigh and Smith, Michael

Introduction The world’s population is living longer and consequently the prevalence of problems in glucoregulation or glucoregulatory efficiency (i.e. the efficiency with which the human body processes blood glucose) is also increasing (World Health Organisation [WHO]). The combined detrimental effects of ageing and impaired glucoregulation on the brain and cognition have been well documented (Biessels, 1999; Biessels, van der Heide, Kamal, Bleys, & Gispen, 2002; Gispen & Biessels, 2000; Kodl & Seaquist, 2008; Kumar, Looi, & Raphael, 2009; Lamport, Lawton, Mansfield, & Dye, 2009; McCrimmon, Ryan, & Frier, 2012; Reijmer, van den Berg, Ruis, Kappelle,  & Biessels, 2010; Ryan & Geckle, 2000; Samaras & Sachdev, 2012; Starr & Convit, 2007; Strachan, 2011; Strachan, Reynolds, Marioni, & Price, 2011), particularly in episodic memory (Lamport et al., 2009; Messier, 2005). Glucoregulation is more frequently impaired in older adults, relative to younger adults (Messier, 2005). If older adults exhibit a decline in both their ability to metabolise glucose efficiently and memory performance, it is possible that impairments in glucoregulation may partly account for memory deficits in ageing.

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Type 2 diabetes and memory

The impact of type 2 diabetes (DM2) on cognition and memory performance has been of great interest to researchers, particularly as DM2 is associated with accelerated cognitive decline and dementia in older adults (Arvanitakis, Wilson, Bienias, Evans, & Bennett, 2004; Cukierman, Gerstein, & Williamson, 2005; Hassing et al., 2004a; Nooyens, Baan, Spijkerman, & Verschuren, 2010; Stewart & Loilitsa, 1999; Strachan, 2011). Impairments in episodic memory performance have been especially noted in newly diagnosed diabetes patients and those with untreated

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DM2 (Ruis et al., 2009; Saczynski et al., 2008). Ruis and colleagues (2009) studied the cognitive  functioning of newly diagnosed DM2 patients in order to establish what cognitive decrements are present in the very early stages of DM2. They compared cognitive performance of new DM2 patients to healthy controls across six cognitive domains: abstract reasoning, information processing speed, visuoconstruction, attention and executive functioning, and memory. After adjustment for IQ, those with newly diagnosed DM2 had significant deficits in memory function compared to healthy controls. These results bolster those seen in participants with impaired fasting glucose levels (IFG) and impaired glucose tolerance (IGT) as they indicate that detriments in memory performance are present even in the early stages of DM2, emphasising that controlling glucoregulation is important in maintaining maximal cognitive performance. Longitudinal research has indicated that those with DM2 exhibit impairments in memory performance both at baseline and over subsequent follow-up periods (Fontbonne, Berr, Ducimetière, & Alpérovitch, 2001; Rönnemaa et al., 2009; Yaffe et  al., 2012). In a study investigating cognitive performance (in individuals aged 59–71 years) over a four-year period, Fontbonne and colleagues (2001) examined the effects of differing levels of glucoregulatory efficiency on cognition. Participants were grouped based on whether they had normal glucoregulation, IFG or had DM2 at baseline, based on their fasting glucose levels. They underwent a battery of cognitive tests at baseline, two-, and four-year follow-ups. These included the Auditory Verbal Learning Test (AVLT), Benton Visual Retention Test, and the Facial Recognition Test, which are tests of verbal memory, visual memory, and attention respectively. The probability of serious decline on each of the tests was calculated for the IFG and diabetic groups as odds ratios (OR) compared to the normal glucoregulation group. The results indicated that the OR for those with IFG did not differ significantly from the ‘normal glucoregulation’ controls. However, those with diabetes demonstrated significant deterioration over the four years on a number of tests including the AVLT and the Facial Recognition Test compared to those with normal glucoregulation. Rönnemaa and colleagues (2009) conducted a study in men aged 71 years old, investigating glucose metabolism markers and their association with Alzheimer’s disease. Over a median follow-up period of 12 years, the researchers found that a number of indices including high fasting glucose, twohour plasma glucose after an oral glucose tolerance test (OGTT), and DM2 were all significantly associated with dementia or cognitive impairment. The above studies highlight the detrimental effects that DM2 has on cognition, particularly verbal memory. As such, the mechanisms that underpin these deficits need to be identified and investigated in order to prevent further decline and assist those at potential risk. In contrast, some studies reveal no observable deficits or accelerated decline in episodic memory in those with DM2 (Arvanitakis, Wilson, Li, Aggarwal, & Bennett, 2006; Cosway, Strachan, Dougall, Frier, & Deary, 2001; van den Berg et al., 2010; Yeung, Fischer, & Dixon, 2009). For example, Cosway and colleagues (2001) examined the cognitive performance of DM2 patients with ‘uncomplicated’ diabetes (had no other medical factors that may affect cognition e.g. cerebrovascular disease, treated hypertension etc.) to establish whether diabetes complications (such

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as those mentioned above) may particularly increase the risk of cognitive impairment. They compared the performance of 38 DM2 patients to 38 matched controls without diabetes on a number of cognitive domains including verbal and visual memory, executive function, and information-processing speed. No significant differences were observed between the two groups on any of the cognitive measures, and performance in the DM2 group was not related to levels of glycaemic control, as measured by levels of glycated haemoglobin (HbA1c), a marker of glycaemic exposure during the previous one to three months. Only duration of diabetes was found to correlate significantly with poor performance on measures of verbal memory. This study suggests that uncomplicated diabetes is not associated with cognitive deficits, and that duration of diabetes may be a reflection of ageing decline on performance. It also indicates that complications of diabetes e.g. hypertension etc., may put an individual at risk of cognitive decline. In a four-year longitudinal study, van den Berg et al. (2010) investigated cognitive decline in DM2 patients. Similarly to Cosway and colleagues (2001), DM2 patients were matched in terms of age, sex, and IQ to healthy controls and were administered tasks encompassing five cognitive domains (memory, abstract reasoning, information-processing speed, attention and executive function, and visuoconstruction). No significant differences were observed at baseline or four-year follow-up in memory performance between the two groups. Although information-processing speed, and attention and executive function were found to be impaired in the DM2 group at both baseline and followup, both groups showed decline in these domains over the four years and therefore no accelerated decline was observed in the DM2 group. The conflicting results revealed in the above studies in those with DM2 may primarily be due to methodological differences, such as the numbers and type of participants involved in each study, as well as the test batteries used to measure cognition. In those studies that revealed cognitive impairment, larger population-based samples were used. For example, Fontbonne and colleagues’ (2001) sample consisted of 961 participants, compared to the smaller sample of 76 used by Cosway et al. (2001); therefore statistical power should be greater in these larger studies and more representative of the population. Contrasts in the cognitive outcomes could be due to how comprehensive the test batteries used in each study were, and differences in the results observed between domains may be due to the type of test used. These differences in the stimuli used (i.e. choice of test) to assess episodic memory may account for the lack of memory impairment observed.

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Potential physiological mechanisms for cognitive impairment in DM2

Clinical research has indicated that a number of physiological mechanisms contribute to cognitive decline in DM2 and a number of these are discussed in brief below. It is beyond the scope of this chapter to go into great detail about each potential contributing factor, however excellent in depth reviews elsewhere provide further detail (Feinkohl, Price, Strachan, & Frier, 2015; Strachan et al., 2011).

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Glycaemic control Disturbances in glucose metabolism, such as hyperglycaemia and hypoglycaemia, have been associated with cognitive dysfunction in DM2 (Rizzo et al., 2010; Sommerfield, Deary, & Frier, 2004). Hyperglycaemia is a physiological state that intrinsically defines DM2. Problems with insulin cell receptors within the body result in a resistance to insulin and low uptake of glucose by the body. Sommerfield and colleagues (2004) found that when they induced acute hyperglycaemia in adults with DM2, their performance on cognitive tests of information processing, working memory, and attention was impaired. Relatively few studies have investigated the effects of chronic hyperglycaemia on cognition (Strachan, 2011). High levels of HbA1c have been associated with cognitive deficits in DM2, and improvements in glycaemic control and decreased insulin resistance have been shown to lead to improvements in cognition (Mahakaeo, Zeimer, & Woodward, 2011; Meneilly, Cheung, Tessier, Yakura, & Tuokko, 1993; Munshi et  al., 2006; Naor, Steingruber, Westhoff, Schottenfeld-Naor, & Gries, 1997; Ryan et al., 2006; Yanagawa et al., 2011). However, other research indicates that improvements in glycaemic control do not lead to improvements in cognition relative to those observed in healthy controls (Mussell, Hewer, Kulzer, Bergis, & Rist, 2004). Overall research does however indicate improving glycaemic control in older individuals with DM2 leads to improvements in cognition and memory performance, whether through the use of hypoglycaemic drugs or via treatment of insulin levels. As the studies above investigated the benefits of improved glycaemic control on cognition over a short period of time (a few weeks/months) it would be of interest to see if there are any longer-term benefits. The pivotal Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial’s sub-study, Memory in Diabetes (MIND), has recently revealed that intensive glycaemic therapy (involving the reduction of patient HbA1c levels to less than 6.0% through the use of different medications) versus standard glycaemic therapy (HbA1c levels targeted between 7.0–7.9%) does not reduce the overall effects of diabetes on cognition (Launer et al., 2011). The study was conducted using the data of 2,794 participants with 20-month and 40-month follow-up cognitive data (Digit Symbol Substitution Test [DSST, a measurement of psychomotor speed], RAVLT, and Stroop tests), so gives a better picture of the longer-term implications of glycaemic control on cognition. As improvements were not seen in either treatment group, this would suggest that the deficits caused by chronic hyperglycaemia are irreversible and that interventions should be put in place early on to identify individuals who may potentially develop DM2. The variability in results between the earlier studies and Launer et al.’s (2011) research are likely due to differences in sample population, size, duration of testing, and the tests of cognition used, although similar tests were used by Ryan and colleagues (2006). Uniformity in methodology is therefore imperative in future research to properly discern what the effects of hyperglycaemia are on DM2 cognition. Another aspect of glycaemic control often overlooked is the effect of hypoglycaemia. Hypoglycaemia in DM2 often occurs because of the effects of insulin treatment and medication on lowering glucose levels. In healthy young adults,

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induced hypoglycaemia using a hyperinsulinemic glucose clamp has been found to cause impairments in visual attention, attentional flexibility, and information processing speed (McAulay, Deary, Ferguson, & Frier, 2001), although verbal memory and face recognition appear to be unaffected (Warren et al., 2008). As these studies were carried out in young adults for only a short time period (< one hour), they do not necessarily portray the effects of hypoglycaemia on cognition in healthy older adults and those with poor glucoregulation, who may experience recurring, longer periods of hypoglycaemia. Nevertheless, hypoglycaemia has been shown to negatively affect both cognitive ability and quality of life in older adults with DM2 (Aung, Strachan, Frier, Butcher, & Price, 2012; Barendse, Singh, Frier, & Speight, 2011; Whitmer, Karter, Yaffe, Quesenberry Jr., & Selby, 2009). The research of Aung et  al. (2012) and Whitmer et  al. (2009) both suggest that hypoglycaemia has detrimental effects on cognition in DM2 and thus further highlight the need to investigate glycaemic control further. Despite this, the occurrence of hypoglycaemia in DM2 is not commonly reported, possibly due to patients being unaware of its symptoms when they occur (Davis & Alonso, 2004; MacLeod, 2000). It should also be noted that hypoglycaemia has been considered to be a product of impaired cognition and dementia rather than the cause (Feil et al., 2011; Punthakee et al., 2012). Further long-term investigation of hypoglycaemia’s effects in DM2 is needed, allowing the assessment of both the effects of medication and DM2 itself on patients’ cognition and vice versa.

Amyloid deposition and advanced glycation end-products (AGEs) A typical feature of Alzheimer’s disease (AD) is the presence of amyloid plaques that contribute to neurodegeneration and neurofibrillary tangles within the brain (Hardy & Selkoe, 2002). Similar amyloid deposits have been observed in rats with induced DM2 (Li, Zhang, & Sima, 2007) and observations in mice with both AD and DM2 suggest that the presence of both diseases leads to accelerated memory dysfunction and increased amyloid angiopathy (Takeda et al., 2010). These results suggest that increases in amyloid deposits may contribute to memory decline in those with DM2 and further investigation is warranted in humans. The accumulation of advanced glycation end-products (AGEs) (which are formed via the non-enzymatic reaction of sugars with long-lived proteins; Gella & Durany, 2009) as a consequence of oxidative stress (an imbalance in production of oxygen free radicals and anti-oxidative defence by the body) is believed to contribute to neuronal damage in DM2 and AD (Correia et al., 2012; Wellen & Hotamisligil, 2005). The presence of these AGEs has been observed in amyloid plaques and accumulation of these plaques within cortical areas of the brain has been observed in those with AD (Gella & Durany, 2009). This leads to speculation that such a mechanism may be a potential factor in cognitive decline in those with DM2. Individuals with AD also demonstrate impairments in insulin signalling similar to those with DM2 (Candeias et al., 2012; Morris & Burns, 2012). Desensitisation of insulin receptors and poor synthesis of the insulin-degrading enzyme results in

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the accelerating effects insulin has on the production of amyloid beta not being controlled and thus amyloid plaque formation may occur (Li & Hölscher, 2007). Insulin therapies have been suggested to combat AD, with some studies showing promising improvements in memory when hyperinsulinaemia is induced (Craft et al., 1996). Domínguez, Marschoff, González, Repetto, and Serra (2012) compared the cognitive performance (as measured using the Mini-Mental State Examination [MMSE]) of individuals with AD, DM2, both AD and DM2, and healthy controls over a one-year period. They found no difference in cognitive performance between healthy controls and those with DM2 alone, although both had lower levels of cognitive impairment compared to participants with combined AD and DM2, and those with AD alone. Participants with combined AD and DM2 demonstrated significantly lower levels of cognitive deterioration than those with AD alone. The authors suggested that this may be due to the glucoselowering effects of medication taken by those with combined AD and DM2, boosting insulin levels to protect against oxidative stress and neuronal damage. Further research is needed to investigate what the longer-term impact of DM2 therapies are on cognitive function and brain structure of those with dementia and AD. As both AD and DM2 appear to share similar pathologies, it is possible that accumulation of both AGEs and amyloid plaques contribute to problems in DM2 cognition. However, the results of autopsy samples of individuals with combined diabetes and dementia show they do not possess AD neuropathology (Arvanitakis et al., 2006; Beeri et al., 2005), leading to the suggestion that cerebral small vessel vascular disease via cerebral ischaemic lesions may be the cause of cognitive decline in DM2 (Umegaki, 2010). It is therefore important that future research discern whether AGEs do indeed play a role in DM2 cognitive decline and whether it is entirely separate from AD pathology.

Hypertension Increases in blood pressure (i.e. hypertension) have been linked to memory performance in healthy adults with relatively poor glucoregulation and those with DM2 (Elias et  al., 1997; Hassing et  al., 2004b; McFall, Geall, Fischer, Dolcos, & Dixon, 2010; van den Berg, Kloppenberg, Kessels, Kappelle, & Biessels, 2009; Xu, Qiu, Winblad, & Fratiglioni, 2007). These increases in blood pressure have been associated with atrophy in frontal brain regions related to memory in those with DM2 (Sakurai et al., 2006), and relatively higher systolic blood pressure has been found to increase the risk of Alzheimer’s disease in those with borderline diabetes (IGT) (Xu et al., 2007). The association between hypertension and DM2 is of particular interest as hypertension may be a potential moderator of memory deficits observed in those with poor glucoregulation. A systematic review by van den Berg et al. (2009) revealed that independently, DM2 and hypertension have detrimental effects on cognition compared to other vascular risk factors such as dyslipidaemia and obesity.

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A number of studies have considered the impact of blood pressure as a comorbid risk factor with DM2 on general cognition and memory performance (Elias et al., 1997; Hassing et al., 2004b; McFall et al., 2010). For example, Elias et al. (1997), as part of the Framingham Study, found that both i) DM2 diagnosis and ii) diabetes duration were associated with poorer performance on visual memory tests in participants with hypertension. Duration of DM2 was also related to poor verbal memory performance. Taking data from an on-going longitudinal study, Hassing et al. (2004b) investigated the independent and interactive influences of DM2 and hypertension on cognition (as measured by the MMSE) in 258 individuals aged 80 years and older. Of these participants, 128 were free from DM2 and hypertension, 92 had a diagnosis of hypertension, 16 had DM2 without hypertension, and 22 had both hypertension and DM2. Across a six-year follow-up period, significant decline in cognition was observed in those with DM2 alone but no such observations were made for those with hypertension alone. Interestingly, comorbid DM2 and hypertension resulted in the steepest decline in cognition. This may be due to the combined effects of both DM2 and hypertension on the brain; inefficient processing of glucose and poor cardiovascular reactivity leading to cognitive decline. As DM2 and hypertension are commonly reported in older adults, the findings of this study highlight the need to monitor blood pressure levels during cognitive task performance in DM2 studies. The observations of the above studies suggest that the presence of cardiovascular problems has a moderating impact on memory performance in those with DM2. Combined with long disease duration, the presence of hypertension appears to lead to increases in cognitive decline in individuals with poor glucoregulatory efficiency. Further investigation is required to determine what the precise impact of hypertension is on DM2 cognitive performance and whether the relationship is bi-directional in nature i.e. DM2 leads to hypertension and/or vice versa.

Dyslipidemia Dyslipidemia is the imbalance of lipids in the bloodstream either via a deficiency or, more commonly in DM2, an overproduction of lipoproteins. Levels of triglycerides and low density lipoproteins (LDL) are reported as frequently higher in individuals with DM2, whilst high density lipoprotein (HDL) concentrations are reduced. Indeed, abnormal lipid profiles in those with DM2 have been found to be associated with poor verbal declarative memory performance (Bruehl et al., 2009), as well as impaired attention and executive functioning (Xia et al., 2015). High levels of LDLs have also been found to be significantly associated with cognitive impairment on the MMSE in Japanese older adults (Umegaki et al., 2012). The precise mechanisms underlying these deficits have yet to be elucidated, although it may be that disruption to lipid balance in the bloodstream results in amyloid deposition (as discussed above). Functional magnetic resonance imaging (fMRI) research has revealed that a potential explanation is the disruptive impact high cholesterol (LDLs) has on functional connectivity of the hippocampus (Xia et al., 2015). Given the importance of

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the hippocampus to memory function, problems revealed in this brain region warrant further investigation. Future work should consider to what extent dyslipidemia affects DM2 cognition and how whether interventions to control cholesterol levels will aid in remedying DM2 cognitive decline.

HPA axis dysregulation Hypothalamic-pituitary-adrenal (HPA) axis dysregulation has been found to have a negative impact on cognitive performance in individuals with DM2 (Bruehl et al., 2007; Bruehl et al., 2009; Strachan et al., 2011). In individuals with DM2, examples of disruption to the HPA axis include raised basal plasma levels of cortisol and adrenocorticotropic (ACTH) levels (Strachan et al., 2011). High levels of cortisol in the bloodstream have been linked to other diabetic complications such as microvascular disease (including retinopathy, neuropathy, and kidney problems) (Chiodini et al., 2007). Bruehl and colleagues (2007) investigated whether feedback control of the HPA axis differed between adults with and without DM2, and whether cognitive impairment observed in DM2 could be attributed to HPA axis dysregulation. All participants underwent a number of neuropsychological tests examining processes of attention, declarative memory, working memory, executive functioning, and general intellectual functioning. They also provided blood samples to measure basal cortisol secretion and underwent a dexamethasone/CRH challenge, to measure the efficiency of their HPA axis. The results indicated that, relative to control participants, those with DM2 exhibited higher levels of basal cortisol secretion and impaired feedback control of the HPA axis. Impairments in declarative memory were observed in those with DM2, and across all participants elevated cortisol levels were associated with memory impairments, although these were moderated by glycaemic control (as measured by HbA1c levels). In a related study, Bruehl and colleagues (2009) also found impaired feedback control of the HPA axis (as measured by a dexamethasone/CRH challenge) resulted in verbal memory impairments, independent of a DM2 diagnosis. The authors suggested that damage to the hippocampus caused by DM2 results in HPA axis dysregulation. This in turn leads to high levels of cortisol being secreted, resulting in further damage to the hippocampus and further impairments to the HPA axis regulation. Further work is needed to examine whether this relationship does indeed affect memory decline in those with DM2 and whether interventions to improve HPA axis regulation would lead to improvements in memory performance in this population.

Macrovascular and microvascular disease Previous literature indicates that the presence of microvascular disease (e.g. retinopathy, nephropathy, and neuropathy) and macrovascular disease (e.g. coronary heart disease, artherosclerosis, and stroke) in those with DM2 can be detrimental to their cognitive performance (Ding et al., 2010; Feinkohl et al., 2013; Hugenschmidt et al., 2014; Imamine et al., 2011; Manschot et al., 2006; Reijmer et al., 2010).

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One frequently reported microvascular issue in DM2 is retinopathy, which is a disease of the retina resulting in vision impairment/loss. As part of the Edinburgh Type 2 Diabetes Study (ET2DS), Ding and colleagues (2010) examined the relationship between retinopathy and cognitive decline in DM2. They used a composite measurement of intelligence derived from multiple cognitive tests (including tests of verbal fluency, memory, information processing speed, mental flexibility, and non-verbal reasoning), which they called ‘g’. The authors found that DM2 participants with moderate to severe retinopathy had the lowest measurement of ‘g’ and had the poorest performance across individual tests. Interestingly, the relationship between retinopathy severity and cognitive impairment was stronger in men than women. As part of the ACCORD-MIND study, Hugenschmidt et al. (2014) also investigated the impact of retinopathy on cognition, as well as on brain structure, in participants with DM2. Their results indicated that baseline retinopathy was associated with lower gray matter volume, and also predicted change on the MMSE and DSST. The results seen in retinopathy studies may provide some insight into the microvascular network within the brain, as retinal and cerebral small vessels share similar characteristics (Ding et al., 2010). Considering this, the greater the impact of retinopathy severity on cognition, the greater the potential of there being microvascular issues within the brain. The results also suggest that there are sex differences in terms of the effects of retinopathy on cognitive decline in DM2, and further examination of this is needed to determine why these differences occur. Macrovascular disease has also been implicated as a potential factor in DM2 cognitive impairment (Reijmer et  al., 2010). Feinkohl and colleagues (2013) sought to determine the relationship between macrovascular measurements and cognitive decline in DM2 participants as part of the ET2DS. They also used ‘g’ (see above) as a measurement of cognitive ability and assessed the impact of baseline macrovascular measurements, including cardiovascular event history. They found that incidence of stroke, markers of cardiac stress (such as ankle brachial index), and generalised artherosclerosis were significantly associated with cognitive decline. However, in the Fremantle Diabetes Study, peripheral arterial disease (a measurement of macrovascular disease) was not found to be associated with cognitive decline (Bruce et al., 2008). The specific impact of macrovascular disease on memory decline in DM2 has not been determined and requires further clarification as to whether specific types of macrovascular disease (such as coronary heart disease and peripheral arterial disease) play more of a role than others in DM2 cognitive decline.

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Evidence from structural imaging

Episodic memory deficits in older adults are suggested to be the result of agerelated changes in brain physiology, structure, and function (Craik & Rose, 2012; Nyberg, Lövdén, Riklund, Lindenberger, & Bäckman, 2012). Structural brain imaging has allowed researchers to visualise structures and abnormalities (e.g.

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lesions, tumours etc.) that may occur within the brain. Magnetic resonance imaging (MRI) is a prominent tool frequently used in both structural and functional brain imaging. In MRI, signals from water molecule protons become differentially aligned by the large magnet of an MRI scanner, subsequently allowing the visualisation of the brain. Of particular interest is its use in investigating changes in brain structure resulting from diabetes-related complications. These DM2 complications may mediate the physiological mechanisms mentioned above, as well as affect functional connectivity between the hippocampus and surrounding brain regions related to memory (Zhou et al., 2010). As such, many structural imaging studies have investigated the effects of DM2 on the brain as a whole, as opposed to specific brain regions. Structural imaging has been predominantly used to explain how the physiological mechanisms mentioned above and the related changes in brain structure contribute to cognitive decline in older adults with poor glucoregulation, particularly those with DM2. The effect of controlling blood glucose levels has been of particular interest to many neuroimaging researchers, particularly as behavioural studies have yielded mixed results concerning the effects of improvements in glycaemic control on cognition (de Galan et al., 2009; Launer et al., 2011; Mahakaeo et al., 2011; Yanagawa et al., 2011). Neuroimaging studies have largely corroborated with behavioural studies indicating that DM2 patients who have insulin treatment (and therefore suffer from poorer glycaemic control) exhibit poorer cognitive performance in comparison to DM2 patients who do not (Tiehuis et al., 2009). This suggests that those patients with very poor glycaemic control are more likely to suffer insults to brain physiology that may result in cognitive deficits. In a related study, the authors also found that diabetes duration contributed to brain atrophy in those with both DM2 and arterial disease (Tiehuis et al., 2008), indicating that the duration of impaired glucoregulation is also a modifying factor in DM2 cognition. However, the ACCORD-MIND study, as previously mentioned, found that intensive glycaemic control did not reduce the effects of DM2 on cognition (Launer et  al., 2011). In spite of this, the results did indicate that those on the intensive therapy had higher total brain volumes at the end of the trial relative to those on standard therapy, suggesting that the rate of brain atrophy can be reduced with improved glycaemic control. A large proportion of neuroimaging research conducted to date has focussed on identifying specific regions of atrophy within the brain that link to the cognitive deficits demonstrated by DM2 patients. In particular, atrophy in the hippocampus has frequently been associated with impairments in cognitive performance, even in ‘healthy’ older adults with impaired glucose tolerance (Convit, Wolf, Tarshish, & de Leon, 2003). Research comparing DM2 participants and healthy controls suggests that those with DM2 have increased hippocampal atrophy (den Heijer et al., 2003) and that this is related to the cognitive deficits seen in DM2, such as verbal declarative memory impairments (Bruehl et al., 2009). Interestingly, new research has suggested that there is evidence of sex differences in DM2 hippocampal volume reductions. In the general population, when

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adjustments are made for total brain volume, women are found to have larger hippocampi than men (Goldstein et al., 2001). In a study investigating the influence of sex differences on hippocampal volume in DM2, Hempel and colleagues (2012) found that women with DM2 had more substantial reductions in volume relative to healthy controls than men with DM2. The authors suggested that women with DM2 might therefore suffer more brain complications relative to males, despite having better glucose control (Hempel, Onopa, & Convit, 2012). There is therefore robust evidence of an association between hippocampal integrity and cognitive performance in DM2. As the hippocampus appears to be preferentially affected in DM2 (Bruehl et al., 2009), the extent of the impact of its deterioration on cognitive function, particularly memory, may be further investigated using functional neuroimaging.

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Evidence from functional neuroimaging

Functional neuroimaging has been used to discern whether neurocognitive mechanisms known to support memory functioning are affected by ageing. It allows researchers to investigate regional brain activity during specific cognitive tasks. This is commonly measured through imaging changes in the blood-oxygen level dependent (BOLD) haemodynamic response in MRI (functional magnetic resonance imaging [fMRI]), or via electrical activity through the scalp using electroencephalography (EEG) associated with direct activation of neural populations. EEG is a methodology that offers excellent temporal resolution, allowing the measurement of brain responses to particular events (known as event-related potentials [ERPs]) with millisecond precision thus enabling researchers to examine neuronal speed. Both techniques have been used to investigate cognition in healthy ageing and in those with DM2. The majority of neuroimaging studies have sought to determine the mechanisms that cause cognitive decline in DM2, few studies have used neuroimaging to uncover what the functional bases of their impairments are, for example whether they lie in encoding of stimuli, recognition, or attentional processing. In MRI research, this may be due to the potential problems with blood-oxygenation levels within the brain that have been shown to be elicited by glucoregulatory abnormalities in individuals with type 1 diabetes (Driesen et al., 2007). However, studies have attempted to investigate cognitive brain function in DM2. One study by Yau et  al. (2009) used diffusion tensor imaging (DTI, a type of MRI that allows the examination of diffusion of water molecules in tissues and white matter) to investigate white matter abnormalities and emotional memory in DM2. They found that DM2 patients had impaired emotional memory, remembering fewer details of an emotional paragraph compared to healthy controls. Their DTI results revealed significant white matter abnormalities in DM2 patients, particularly in the frontal and temporal lobes – areas that are involved in memory processing. Zhou et  al. (2010) asked DM2 patients and healthy controls to complete a variety of cognitive tests, comparing their performance and resting-state functional connectivity of the

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hippocampus. They found that DM2 participants’ performance was significantly worse on a number of neuropsychological tests relative to healthy controls and this poor performance was negatively correlated with BMI and HbA1c levels. DM2 patients also showed reduced hippocampal connectivity to the surrounding bilateral brain regions including the frontal gyrus, fusiform gyrus, and temporal gyrus compared to healthy controls. The results of these studies suggest that the function of regions involved particularly in memory processing are adversely affected by DM2, and that further research should investigate the functional differences between healthy individuals and those with DM2. EEG is another neuroimaging method used to investigate cognitive function by measuring electrical brain activity through the scalp surface. Episodic memory is typically split into processes of recollection and familiarity. ERPs have been used to investigate these processes, both in healthy older adults and in glucose ingestion studies in adolescents, focussing on verbal episodic memory (Friedman, 2000; Friedman & Trott, 2000; Nessler, Johnson Jr., Bersick, & Friedman, 2006; Smith, Riby, Sünram-Lea, van Eekelen, & Foster, 2009). However, few studies in older adults with DM2 have investigated these processes using ERPs, and instead focus on the impact of DM2 on other ERP components, in particular the P300 component. The P300 component has been found to be affected by DM2, a component that is often split into two subcomponents: the P3a (associated with executive function and orientation of attention to task irrelevant stimuli) and the P3b (associated with memory updating and formation of memory representations; Polich, 2007). P300 latencies are indicative of stimulus classification speed and the speed with which attentional resources are allocated during a cognitive task (Polich, 2007). Some studies have indicated that patients with DM2 have a longer P300 latency and thus allocation of attentional resources may be slower in this population (Cooray et al., 2011; Kurita, Katayama, & Mochio, 1996; Mochizuchi, Oishi, Hayakawa, Matsuzaki, & Takasu, 1998), although others have found no differences between DM2 participants and healthy controls (Vanhanen et  al., 1997). Improvements in glycaemic control have been shown to lead to improvements in P300 latency (Cooray et al., 2011; Mochizuchi et al., 1998). By using neuroimaging to not only investigate DM2’s effects on brain structure but also function, possible mechanistic explanations for cognitive deficits such as alterations in glucose metabolism and neuron potentiation can be examined. Considering this, other research has indicated that the P300 is not affected by diabetic aetiology (Hissa, D’Almeida, Cremasco, & de Bruin, 2002). Hissa and colleagues (2002) also examined the auditory P300 in DM2 patients and its association with DM measures such as hypoglycaemia, retinopathy, blood glucose levels, and disease duration. The results revealed that DM2 patients had slower P300 latencies than controls, although no measures of DM (hypoglycaemic group, disease duration, glucose levels, triglycerides, or cholesterol) were related to P300; whereas age was found to correlate with P300 latency in both groups. This indicates that the

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older the participants were, the slower their ability to distinguish between rare and frequent stimuli, regardless of DM2 status. The results of this study therefore suggest that age is an overarching factor and that it has deleterious effects on the P300 in both healthy adults and those with DM2. As the majority of DM2 research is conducted in older adults (Lamport et al., 2009), the result found here is not surprising given the age ranges of the groups tested, despite having the same mean age (DM2 patients age range = 38–75; Controls age range = 43–69). As discussed above, the ERPs considered in the above studies are not directly related to the specific processes involved in episodic memory i.e. recollection and familiarity, which are considered to be indexed by a left-parietal old/new effect 400–800ms after stimulus onset and the FN400 respectively (Smith et al., 2009). Although these components have been studied in ageing research, little research has been conducted in those with poor glucoregulatory efficiency. It is therefore important that future studies also consider these components in order to accurately gauge the effects of impaired glucoregulation and DM2 on different memory processes.

6

Methodological considerations and future study design

What is evident from previous research investigating glucoregulation and memory processing is that the bulk of studies are conducted in young or older adults with very little research considering those who are middle-aged. Studies that have considered this age bracket have indicated intermediary levels of impairment between young and older adults (Fuh, Wang, Hwu, & Lu, 2007). It would therefore be of interest to conduct research across the lifespan to determine when the effects of impaired glucoregulation on memory performance are evident. It would also be interesting to gauge whether impairments in memory performance in middle-aged adults are the result of glucoregulation negatively affecting similar neurocognitive mechanisms as those observed in older adults. Longitudinal work, examining individuals considered at risk of developing glucoregulatory problems from an early age (young adulthood) through to old age, would give a more comprehensive picture of the impact of glucoregulatory efficiency on memory performance across time. A further consideration for future research is the exploration of sex differences in glucoregulation. If such differences exist across the spectrum of glucoregulatory efficiency i.e. if females with glucose intolerance that does not reach the clinical levels of DM2 have similar reductions in hippocampal volume, it is possible that this may be an underlying mechanism for memory decline in females. Given that there is sexual dimorphism within the brain (Sacher, Neumann, OkonSinger, Gotowiec, & Villringer, 2013), it would be of interest to investigate whether a difference between the sexes in memory performance would be evident with respect to glucoregulatory efficiency, and brain volume and activation using fMRI.

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Previous research has indicated that DM2 is more strongly associated with multiple-domain amnestic mild cognitive impairment in men compared to women (Roberts et al., 2014). It is therefore important to explore why these differences exist in order to understand the impact of glucoregulatory efficiency on each of the sexes respectively. It is evident from the literature that further information about the impact of physiological mechanisms on DM2 cognition is needed. DM2 is a disease with many complications, so it is therefore important to determine what aspects play a critical role in DM2 memory decline and to what extent such impairments can be relieved by appropriate interventions. Here we propose that the use of neuroimaging can be used to support the investigation of the role of physiological mechanisms in DM2 cognitive impairment, as well as help us understand what precise underlying neurocognitive mechanisms are being affected. For example, determining the role of HPA axis dysregulation and its effects on the hippocampus and DM2 cognition can be examined using biological testing (e.g. dexamethasone/CRH challenges) as well as through structural and functional neuroimaging. Although structural imaging has been used in previous research (Bruehl et al., 2007; 2009), the use of functional neuroimaging would help better determine what neurocognitive mechanisms are affected, whether via functional connectivity (diffusion tensor imaging) or enabling time course to be determined via EEG.

Practical research tips 1

2

3

When examining the domains of cognition impaired in DM2, careful consideration of task type is essential to effectively characterise the cognitive profile. For instance, previous research has been extremely vague examining deficits in memory function. Therefore, a battery of tasks tapping different forms of memory is necessary (e.g. working, episodic, and semantic), preferably versions with different levels of difficulty. Task domain versus task difficulty is often neglected. Patients with DM2 have a high prevalence of comorbid conditions (e.g. depression and hypertension). Indeed, treatment and management is problematic with considerations needed to be made of not only diabetes specific impairment but also accompanying debilitating chronic conditions. These difficulties can be mirrored in research design. When examining a particular psychological or cognitive process, appropriate matching of groups and/or sensible statistical control must be considered when disentangling mechanisms responsible for impairment. Although converging methods is critical to our understanding of psychological ability in DM2, selection of the appropriate method is dependent on the particular research question. Behavioural methods alone may be adequate. However, if we wish to track the timing (e.g. EEG/ERPs) or map the location (e.g. fMRI) new advances in the neurosciences might be appropriate.

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Acknowledgements Excerpts are taken from Jones (2015) doctoral thesis. See also Jones, Riby, Mitchell, and Smith (2014). Type 2 diabetes and memory: Using neuroimaging to understand the mechanisms. Current Diabetes Reviews, 10(2), 118–123.

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Takeda, S., Sato, N., Uchio-Yamada, K., Sawada, K., Kunieda, T., Takeuchi, D., . . . Morishita, R. (2010). Diabetes-accelerated memory dysfunction via cerebrovascular inflammation and Abeta deposition in an Alzheimer mouse model with diabetes. Proceedings of the National Academy of Sciences, 107, 7036–7041. Tiehuis, A.M., Mali, W.P.T.M., van Raamt, A.F., Visseren, F.L.J., Biessels, G.J., van Zandvoort, M.J.E., . . . van der Graaf, Y. (2009). Cognitive dysfunction and its clinical and radiological determinants in patients with symptomatic arterial disease and diabetes. Journal of the Neurological Sciences, 283, 170–174. Tiehuis, A.M., van der Graaf, Y., Visseren, F.L., Vincken, K.L., Biessels, G.J., Appelman, A.P.A., . . . Mali, W.P.T.M. (2008). Diabetes increases atrophy and vascular lesions on brain MRI in patients with symptomatic arterial disease. Stroke, 39, 1600–1603. Umegaki, U. (2010). Pathophysiology of cognitive dysfunction in older people with type 2 diabetes: Vascular changes or neurodegeneration? Age and Ageing, 39, 8–10. Umegaki, H., Iimuro, S., Shinozaki, T., Araki, A., Sakurai, T., Iijima, K., .  .  . Ito, H., the Japanese Elderly Diabetes Intervention Trial Study Group. (2012). Risk factors associated with cognitive decline in the elderly with type 2 diabetes: Pooled logistic analysis of a 6-year observation in the Japanese elderly diabetes intervention trial. Geriatrics & Gerontology International, 12(1), 110–116. van den Berg, E., Kloppenberg, R.P., Kessels, R.P.C., Kappelle, L.J., & Biessels, G.J. (2009). Type 2 diabetes mellitus, hypertension, dyslipidemia and obesity: A systematic comparison of their impact on cognition. BiochimicaetBiophysicaActa (BBA)—Molecular Basis of Disease, 1792(5), 470–481. van den Berg, E., Reijmer, Y.D., de Bresser, J., Kessels, R.P.C., Kappelle, L.J., & Biessels, G.J. (2010). A 4 year follow-up study of cognitive functioning in patients with type 2 diabetes mellitus. Diabetologia, 53, 58–65. Vanhanen, M., Koivisto, K., Karjalainen, L., Helkala, E-L., Laakso, M., Soininen, H., & Riekkinen Sr., P. (1997). Risk for non-insulin-dependent diabetes in the normoglycaemic elderly is associated with impaired cognitive function. NeuroReport, 8, 1527–1530. Warren, R.E., Sommerfield, A.J., Greve, A., Allen, K.V., Deary, I.J., & Frier, B.M. (2008). Moderate hypoglycaemia after learning does not affect memory consolidation and brain activation during recognition in non-diabetic adults. Diabetes/Metabolism Research and Reviews, 24, 247–252. Wellen, K.E., & Hotamisligil, G.S. (2005). Inflammation, stress, and diabetes. The Journal of Clinical Investigation, 115(5), 1111–1119. Whitmer, R.A., Karter, A.J.,Yaffe, K., Quesenberry Jr., C.P., & Selby, J.V. (2009). Hypoglycemic episodes and risk of dementia in older patients with type 2 diabetes mellitus. Journal of the American Medical Association, 301(15), 1565–1572. Xia, W., Zhang, B., Yang, Y., Wang, P., Yang, Y., & Wang, S. (2015). Poorly controlled cholesterol is associated with cognitive impairment in T2DM: A resting-state fMRI study. Lipids in Health and Disease, 14(47), 1–10. Xu, W., Qiu, C., Winblad, B., & Fratiglioni, L. (2007). The effect of borderline diabetes on the risk of dementia and Alzheimer’s disease. Diabetes, 56, 211–216. Yaffe, K., Falvey, C., Hamilton, N., Schwartz, A.V., Simonsick, E.M., Satterfield, S., . . . Harris, T. (2012). Diabetes, glucose control and 9 year cognitive decline among non-demented older adults. Archives of Neurology, 69(9), 1170–1175. Yanagawa, M., Umegaki, H., Uno, T., Oyun, K., Kawano, N., Maeno, H., . . . Sato, Y. (2011). Association between improvements in insulin resistance and changes in cognitive function in elderly diabetic patients with normal cognitive function. Geriatrics & Gerontology International, 11(3), 341–347.

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10 ALZHEIMER’S DISEASE Interaction of lifestyle factors and traumatic head injury Scholes-Balog, Kirsty, Albrecht, Matthew and Foster, Jonathan

Introduction Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with insidious onset characterised by a primary impairment in episodic memory but subsequently extending to more wide-ranging neurocognitive and neurobehavioural impairment. Related to the aging demographic in many countries around the world, AD represents a major current health concern. In this chapter, we will examine the relationship between later onset AD (as the most prevalent form of AD; van der Flier, et al., 2011), traumatic head injury and some of the most prominent environmental risk and protective factors for AD. We first provide a general overview of the neuropathology of AD before critically reviewing the relationship between head injury and AD, highlighting potential inconsistencies in the literature and suggesting possible means of addressing these issues in future. In addition, we examine possible mechanisms underlying this putative relationship. Next, we provide a brief overview of the burgeoning literature examining the effects of lifestyle and dietary interventions and their relationship to the incidence of AD. In the final section, an exploration of potential additive/synergistic interactions between head injury and lifestyle factors are considered.

1

Neurobiology and genetics of Alzheimer’s disease: a précis

Diagnosis of AD is usually based upon clinical signs including impairment in memory and at least one other cognitive domain, together with the absence of evidence of other brain or systemic disease that could account for the decline in function (Dubois, et  al., 2007). However, a recent revision of diagnostic guidelines has included a consideration of biomarkers (e.g. Aβ, tau) and neuroimaging

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investigations (e.g. MRI, PET) in AD diagnosis (McKhann, et al., 2011). Confirmation of a diagnosis of AD is currently made post-mortem. The two key pathological hallmarks of AD are neurofibrillary tangles (i.e. intracellular accumulation of tau protein secondary to abnormal metabolism of tau) and neuritic amyloid plaques (i.e. extracellular deposits of β-amyloid protein resulting from the enzymatic cleavage of amyloid precursor protein) (Alzheimer, 1987; Khachaturian, 1985; Newell, et al., 1999). The ‘amyloid cascade hypothesis’ proposes that the deposition of β-amyloid is the initial causative factor in the disease, initiating the formation of neurofibrillary tangles, cell loss and ultimately dementia (Hardy and Higgins, 1992). A modification to the amyloid hypothesis has been proposed in an attempt to reconcile more recent findings. According to this revised framework, it has been suggested that neuronal cell death is the initial stage of degeneration, triggered by aging of the brain and associated risk factors that can include vascular disease and head trauma (Armstrong, 2011). It is proposed that as neurons degenerate, various proteins are upregulated leading to formation of the hallmarks of AD pathophysiology (i.e. extracellular β-amyloid deposits and intracellular tau with the latter resulting in the development of neurofibrillary tangles) (Armstrong, 2011). These reactive lesions may be toxic and instigate a secondary phase of degeneration that accelerates the neuronal loss underlying the manifestation of dementia (Armstrong, 2011). It should also be mentioned that an alternative hypothesis of the aetiology of AD has been proposed that focuses primarily on the accumulation of the tau protein. Specifically, it has been proposed that rapid accumulation of hyper-phosphorylated tau protein results in the destabilisation of microtubules that serve as the major infrastructure for intraneuronal transport, and that these changes cause subsequent neurodegeneration and cognitive impairment (Iqbal, et  al., 2010; Jaworski, et  al., 2010). Mutations in three genes have been firmly implicated in the familial, early-onset form of AD: the gene encoding amyloid precursor protein (APP), which is located on chromosome 21; the gene for presenilin-1 (PSEN1) located on chromosome 14; and the presenilin-2 gene (PSEN2) located on chromosome 1 (for a review see Tanzi and Bertram, 2005). While the early onset form of AD is responsible for approximately 2% of cases, the later onset form with a more complex genetic determination is responsible for up to 75% of AD cases (Olgiati, et al., 2011). First degree relatives of patients diagnosed with late-onset AD have twice the expected lifetime risk of this disease compared with those individuals without a first degree relative with AD (Green, et al., 2000). Later onset AD also has a higher concordance in monozygotic than dizygotic twins (Gatz, et al., 2006), suggesting a substantial genetic contribution to this disorder. The most well established genetic risk factor for late-onset AD is the Apolipoprotein E gene, located on chromosome 19 (APOE denotes the gene for the protein, while ApoE denotes the protein apolipoprotein E for which the allele codes). ApoE is a plasma protein produced and secreted in the central nervous system by astrocytes (Boyles, et al., 1985) involved in cholesterol transport (Mahley, 1988). The APOE gene has three common polymorphisms: ε2,

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ε3 and ε4 (Mahley, 1988). The presence of one or more copies of the ε4 polymorphism has been shown to be more frequent in those with late-onset AD than in non-AD controls (Poirier, et al., 1993; Strittmatter, et al., 1993). Furthermore, a gene dose-outcome relationship has been noted between ε4 and AD (Corder, et al., 1993; Kukull, et  al., 1996). For example, one study found that individuals with the homozygous ε4/ε4 genotype had a diagnosis risk ratio of 30.1 whereas ε3/ ε4 heterozygotes had a risk ratio of 3.7 (Myers, et al., 1996). The presence of the ε4 allele has also been shown to lower the age of AD onset (Corder, et al., 1993; Kurz, et al., 1996). However, the presence of the ε4 allele is neither necessary nor sufficient for AD. For example, one population based study found that 55% of ε4 homozygotes developed AD by age 80, but 27% of ε3/ε4 heterozygotes developed AD by the age of 85 compared with 9% of those without an ε4 allele (Myers, et al., 1996). Ongoing research has therefore focused on identifying other risk factors for the development of AD, both genetic and environmental. One such risk factor that has received a considerable amount of research attention is the lifetime occurrence of significant head injury. This will be the focus of the current review, in particular concerning the possible interaction of head injury with biological and environmental risk factors for AD.

2 2.1

Head injury as a risk factor for AD Epidemiology

Initial evidence for an association between head injury and AD came from early studies showing an increased incidence of AD in those with a history of traumatic head injury compared to individuals without a history of traumatic brain injury (Amaducci, et al., 1986; Heyman, et al., 1984; Mortimer, et al., 1985). While many subsequent studies have observed similar findings (e.g. Fleminger, et al. 2003; Graves, et al., 1990; Guo, et al., 2000; Kondo, et al., 1994; Mayeux, et al., 1993; Nemetz, et al., 1999; O’Meara, et al., 1997; Plassman, et al., 2000; Rasmusson, et al., 1995; Sivanandam and Thakur, 2012), there are some studies that have failed to find such an association between significant head injury and incidence of AD (Broe, et al., 1990; Chandra, et al., 1989; Mehta, et al., 1999). This inconsistency may be due to relatively low statistical power of some studies conferred by the small number of patients who convert to AD. For example, even in the Mehta et al. (1999) study with an initial sample size of 6,645 participants, only 91 participants were eventually diagnosed with AD. Heterogeneity across studies with respect to the definition of head injury (such as variation in severity of injury, aetiology and methods of assessment) is another likely source of inconsistencies in findings across studies. A meta-analysis by Fleminger et  al. (2003) found a significant association between head injury and AD, but only in males (relative risk = 1.82, 95% confidence interval 1.26–2.67). As the prevalence of head injury is much greater among men than women (Kraus, et al., 1984), it may be that these studies were insufficiently powered to detect a significant association between head injury and AD in females.

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The proposed modulatory role of the female hormones oestrogen and progesterone offers another possible explanation for this apparent gender difference in the risk of AD after head injury (Fleminger, et  al., 2003). Animal models of stroke and traumatic brain injury suggest that these hormones confer a neuroprotective and neuroregenerative role (Roof and Hall, 2000; Stein, 2001). Furthermore, given that AD is more prevalent in women than men, it has been suggested that falling levels of circulating oestrogen after menopause increase a woman’s risk of developing AD (Henderson, 1997). Therefore, it may be that elevated levels of oestrogen (compared to men) pre-menopause may confer protection from the deleterious impacts of a traumatic brain injury in women. However, the plausibility of this argument is debatable given that oestrogen therapy, especially with respect to randomised controlled trials, has been shown to have little success in protecting against AD (for a review see Ryan, et al., 2008).

2.2

Common biological features of head injury and AD

A putative association between head injury and AD is supported by the observed similarity of these two conditions with respect to key neuropathological brain biomarkers. First, both animal studies (Itoh, et al., 2009; Li, et al., 2006; Pierce, et al., 1996) and post mortem human studies (Chen, et al., 2009; McKenzie, et al., 1994; Roberts, et al., 1991; Uryu, et al., 2007) have shown that increased amyloid precursor protein (APP) production and/or accumulation can occur after traumatic brain injury. Characteristic β-amyloid plaques are also observed in the brain parenchyma of humans following brain injury (Graham, et  al., 1995; Horsburgh, et  al., 2000; Ikonomovic, et al., 2004; Nicoll, et al., 1995; Roberts, et al., 1994; D.H. Smith, et al., 2003). Reductions in CSF β-amyloid (1–42) and ApoE have also been observed in the days following traumatic brain injury (Franz, et al., 2003; Kay, et al., 2003a, 2003b), suggestive of increased deposition of amyloid within the brain in the form of amyloid plaques (Kay, et  al., 2003a). However, the evidence for reduced CSF β-amyloid after traumatic brain injury is not conclusive, with two earlier studies finding increased β-amyloid (1–42) levels in the days following brain injury (Emmerling, et al., 2000; Raby, et al., 1998). Such contrasting findings may be attributed to different methods of sampling of CSF (ventricular, lumbar or mixed), as CSF obtained from ventricular versus lumbar puncture has been shown to have markedly different concentrations of biomarkers (Blennow and Nellgard, 2004; Clark, et al., 2009). Additionally, altered circulation of CSF after brain injury can occur (for example, as a result of post-traumatic hydrocephalus), further contributing to the inconsistency in findings (Kovesdi, et al., 2010). Alterations in tau and neurofilament accumulations have also been noted after traumatic brain injury. In animal models, induction of traumatic brain injury through ischemic, penetrating ballistic and repetitive percussive means have been noted to result in significant elevations of phosphyrylated tau and accumulation of amyloid beta (Kanayama, et al., 1996; Smith, et al., 1999; Yao, et al., 2008). A similar effect is seen following traumatic head injury in humans, including changes in tau

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concentrations in the CSF (Franz, et al., 2003; Kay, et al., 2003a; Zemlan, et al., 1999) and post mortem brain tissue (Irving, et al., 1996; Marklund, et al., 2009; C. Smith, et al., 2003). However, an increased presence of neurofibrillary tangles has not been clearly established subsequent to head injury (Ikonomovic, et al., 2004; C. Smith, et al., 2003). Similarities have also been noted between dementia pugilistica and AD. Dementia pugilistica or chronic traumatic encephalopathy (CTE) results from repeated trauma in athletes subject to repetitive head impact, particularly noted in boxers. Individuals with dementia pugilistica (or CTE) have been found with similar β-amyloid plaques and neurofibrillary tangles to those observed in AD (Allsop, et al., 1990; Corsellis, et al., 1973; Dale, et al., 1991; McKee, et al., 2009; Roberts, 1988; Roberts, et al., 1990; Tokuda, et al., 1991). However, these tangles have been shown to be smaller than those seen in AD and do not seem to possess plaque cores, suggesting they are a more primitive tangle type than those observed in AD (Roberts, 1988). Diffuse and abundant β-amyloid plaques have also been noted in an extensive area of the cortex in dementia pugilistica patients, resembling the pathology observed in AD (Roberts, et al., 1990; Tokuda, et al., 1991). These plaques appear to be at an early stage of formation in comparison to classical AD amyloid plaques (Roberts, et al., 1990). Nevertheless, it appears plausible that those neuropathological markers that emerge subsequent to HI and which show a family resemblance to pathological markers that are diagnostic for AD are consistent with the notion that common underlying mechanisms are associated with the sequale.

2.3

The role of apolipoprotein E

There is evidence to suggest that the factors of head injury and possession of the APOE ε4 allele have synergistic effects on the risk of developing AD. Mayeux et al. (1995) found that in participants with both a history of traumatic head injury and possession of the APOE ε4 allele the risk of AD was increased 10-fold compared with a two-fold increase in risk in those with possession of the ε4 allele alone. Such a powerful interaction is suggestive of common underlying neurobiological mechanisms. Similarly, another study showed a marked increase in the frequency of the ε4 allele in those with AD or mild cognitive impairment who had also experienced traumatic brain injury, relative to those who had not (Mauri, et al., 2006). However, two other published studies found that an increased risk of AD was present in those with a history of head injury but without the ε4 allele (Guo, et al., 2000; Jellinger, et  al., 2001) and one study found no significant synergistic relationship between APOE allele status and head injury (O’Meara, et al., 1997). Clearly further investigation of this possible relationship is warranted. While a relationship between head injury, APOE genetic status and the development of AD has not been consistently observed, there is a plausible neurophysiological rationale to suggest that the protein ApoE plays a significant role in response to acute brain injury. As has been already noted, the APOE allele codes for the apolipoprotein ApoE protein, which is involved in neuronal regeneration

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and repair (Handelmann, et  al., 1992; Nathan, et  al., 1994; Poirier, 1994; White, et al., 2001). ApoE-mediated lipid transport has been shown in some studies to be upregulated following acute brain injury (Hall, et al., 1995; Horsburgh and Nicoll, 1996; Poirier, 1994). Further, the presence of the ε4 isoform of ApoE (a product of the APOE ε4 allele) is associated with reduced growth and branching of neurites in cell culture, compared to the ε3 isoform (which is a product of the APOE ε3 allele) (Nathan, et al., 1994). Thus, it is biologically plausible that the presence of the ε4 allele may negatively modulate clinical outcome after head injury compared to the ε3 allele. Indeed, a number of studies have reported that individuals possessing the ε4 allele are significantly more likely to show an unfavourable outcome following head injury (Chiang, et  al., 2003; Friedman, et  al., 1999; Sundstrom, et  al., 2004; Teasdale, et al., 1997). Moreover, one study showed that individuals possessing the ε4 allele manifested significantly more β-amyloid protein in the brain post-mortem following traumatic brain injury than those without the ε4 allele (Nicoll, et  al., 1995). A similar finding has been reported in mice (Hartman, et al., 2002). Another study found that, among those individuals with signficant β-amyloid deposition measured following head injury, there was a higher frequency of APOE ε4 carriers than is seen in many studies of late-onset AD (Nicoll, et al., 1996). However, to our knowledge there have not been follow-up studies that have confirmed the findings of Nicoll et al. (1995) and Nicoll et al. (1996). Evidence for a role of the ε4 allele in modulating the sequelae of head injury is not conclusive, with three head injury studies finding no such difference in outcome between those with and without the ε4 allele (Chamelian, et  al., 2004; Nathoo, et al., 2003; Sundstrom, et al., 2004). However, Sundstrom and colleagues did observe a significant reduction in neuropsychological function post-traumatic head injury in those with the ε4 allele relative to these individuals’ own pre-injury performance (Sundstrom, et  al., 2004). Nonetheless, the statistical analysis methodology utilised by Sundstrom and colleagues has been criticised for failing to test for the interaction between head injury status and time in order to determine whether the ε4 group demonstrated a statistically significant increased risk of cognitive decline relative to the non-ε4 group (Collie, et al., 2004). However, studies that failed to find a significant difference in head injury outcome as a function of ε4 genotype may have suffered from insufficient power to detect between-group differences, given the small number of subjects who possessed the ε4 allele and also had a history of head injury that are typically reported in such studies. A recent study suggested that age of injury may be an important mediator of the relationship between APOE genotype and outcome following head injury. While Teasdale et al. (2005) found no significant overall relationship between APOE genotype and unfavourable outcome following head injury, they did find evidence for an interaction between age and genotype. Specifically, possession of the ε4 allele reduced the probability of a favourable outcome in children and adolescents (< 15 years old) but not in older adults. This finding may be associated with the maturation of the brain during the first two decades of life and the likelihood of sensitive maturational periods during which brain insult may impact more profoundly on functional outcomes.

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The inconsistencies noted in this literature could be addressed by consideration of a number of salient issues in future research. First, as noted previously there are inconsistencies in identification and classification of head injury, with many studies differing in terms of the specific study inclusion criteria and how head injury is assessed. Use of more detailed but also more consistent methods for assessment of head injury across studies would assist in providing better measures of head injury characterisation and severity, and would offer more direct comparability between studies. For example, instead of basing severity of head injury or inclusion/exclusion on one feature of the injury (e.g. location, aetiology), clinicians and researchers should be encouraged to report on as many facets of head injury sequelae as possible. This information should include: whether hospital admission was required; duration of hospital admission; other clinical assessment or medical attention received (such as hospital emergency department visit); whether concussion occurred; duration of post- and pre-traumatic amnesia; duration of loss of consciousness; score on the Glasgow coma scale (acutely and subsequently, if available); and whether a skull fracture occurred (Jennett, 1976). Second, variation in the definition of ‘outcome’ (e.g. cognitive, functional, behavioural) following head injury and the often limited ways in which outcome/s are assessed should be addressed in future research. Most extant studies have typically assayed a limited range of neurocognitive, biomarker or behavioural measures, which limits the value of the findings. Finally, as mentioned a number of times above, many studies suffer from relatively small sample sizes and therefore are powered only for detecting very strong genetic and other biological associations.

2.4

Summary: head injury and AD

Although the exact mechanisms underlying the relationship between head injury and AD incidence is not certain, the evidence presented thus far suggests that on balance this relationship is mediated by the effects of head injury on key biomarkers shown to be associated with AD (specifically brain β-amyloid and tau). Furthermore, an individual’s genetic profile (specifically their APOE genotype) is likely to play a significant role in modulating this relationship, possibly via the influence of APOE status on neuroprotective and/or neuroregenerative processes following injury. Although speculative, another possibility that could explain the apparent relationship between head injury and increased risk of AD centres on the theme of brain reserve or capacity. ‘Brain reserve’ can be regarded as an index of neural hardware that we possess. In the context of recent evidence of brain plasticity extending across adulthood, this reserve can be enhanced or deteriorate over the lifespan (Borensteain, et al., 2006). A related concept is that of ‘cognitive reserve’, which may be conceptualised in terms of the functional, behavioural and cognitive skills that we acquire across our life. Increased neural and/or cognitive capacity have been identified as possible protective factors for incident AD (Borensteain, et al., 2006; Galvan and Bredesen, 2007). Tissue loss and neural damage occurring at the time of traumatic head injury may induce significant cognitive impairment in

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individuals already at increased risk of developing AD (i.e. those in the prodromal state), due to diminished brain reserve resulting from the traumatic injury, and earlier conversion to frank dementia may therefore ensue (Broglio, et al., 2012). Such a hypothesis is, however, difficult to test and would require a prospective longitudinal investigation in order to determine definitely whether such a synergistic interaction between brain injury and APOE status/brain reserve applies.

3

AD and lifestyle interventions

While head injury is an environmental risk factor that appears to increase the risk of developing AD, there has been recent interest in examining links between other environmental lifestyle and dietary factors that may also increase or decrease the risk of AD. Indeed, there is a growing literature examining the impact of lifestyle modifications as potential preventative factors for AD. A comprehensive review of this literature is beyond the scope of this chapter, so we will here focus on some of the most widely researched interventions, with particular reference to potential interactions with the factors underlying the proposed biological relationship between head injury and AD.

3.1

Diet

There has been a vast amount of research investigating the effects of different foods on cognitive performance and risk of developing AD. The effect of the ‘Mediterranean diet’ (high consumption of plant food and olive oil; moderate consumption of fish; low consumption of saturated fat, dairy products, meat and poultry and wine; Willett, et  al., 1995) is one of the most widely investigated dietary modifications in terms of its effects on cognitive performance and risk of AD. Higher adherence to the Mediterranean diet has been associated with i) a reduction in risk for AD, ii) reduced conversion to AD in those at increased risk and iii) a slower rate of age-related cognitive decline in the healthy elderly, individuals with mild cognitive impairment and AD (Gardener, et al., 2012; Scarmeas, et al., 2006). Conversely, a diet high in total fat, saturated fats and dietary cholesterol has been shown to be linked to an increased risk of dementia (Grant, 1999). A diet high in saturated fats, in particular, has been shown to be linked to a greater decline in age-related cognitive function (Kalmijin, et  al., 2004; Morris, et  al., 2004) and an increased risk of AD (Kivipelto, et al., 2008; Morris, et al., 2003). This is the case particularly in those who possess the APOE ε4 allele (Kivipelto, et al., 2008; Laitinen, et al., 2006). While one study found no such relationship between saturated fat intake and AD (Engelhart, et al., 2002), such a relationship is supported by a vast array of animal studies suggesting that a diet high in saturated fat is causally associated with severely compromised cognitive function (e.g. Granholm, et al., 2008; Murray, et al., 2009; Winocur and Greenwood, 2005).

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3.2

Physical activity

There are a number of reports in the literature suggesting a protective role of exercise with respect to age-related cognitive change and risk for AD. For instance, among a sample of men it was found that a regime of walking was associated with a reduced risk of dementia (with the majority of dementia cases reported in this study representing AD; Abbott, et al., 2004). Similarly, another study showed that regular exercise (more than three times a week) was associated with a reduced incidence rate of dementia (majority AD cases) in people aged over 65 years. Additionally, a significant relationship between decreased risk of AD with increasing levels of physical activity was observed in one study in females (Laurin, et al., 2001), while another study showed risk of AD declined significantly with increasing physical activity in a sample of males (Taaffe, et  al., 2008). A randomised controlled trial of a 24-week physical activity intervention in volunteers who reported memory problems but did not meet the criteria for dementia found that participants in the intervention group showed a modest improvement in cognitive functioning over an 18-month follow-up period (Lautenschlager, et al., 2008). An interaction between possession of the APOE ε4 allele and the protective effect of physical activity has also been observed. One study found that individuals participating in at least twice a week leisure time physical activity had lower odds of AD, and this effect was more pronounced in those who carried the APOE ε4 allele (Rovio, et al., 2005). On the other hand, another study found that engaging in a number of different physical activities protected against AD, although this effect seemed to be limited to those who did not carry the APOE ε4 allele (Podewils, et al., 2005). These two studies are in direct contrast. This is likely to be due to the sample sizes being too small for the detection of reliable genetic associations, producing an insufficiently sensitive study design (i.e. type II statistical error), as well as differences in patient characteristics. Type I statistical errors are also possible. A systematic meta-analysis found that physical activity reduces the risk of AD by 45% (Hamer and Chida, 2009). However, this study highlighted the heterogeneity in the literature and attributed this to methodological issues in terms of definition of physical activity, and also possible gender differences in the effects of physical activity (Hamer and Chida, 2009). Specifically, gender differences in study outcomes could reflect gender differences in biological responses to exercise (Day, 2008; Hamer and Chida, 2009). Although conjectural, it should also be considered that at least some of the observed association between physical activity and reduced risk of AD might simply reflect the possibility that those with AD or prodromal AD undertake less exercise than do those without AD.

3.3

Obesity

There is a large amount of evidence suggesting a relationship between obesity (as measured by body mass index, BMI) and cognitive function. For example, obesity has been shown to be associated with reduced executive function performance in

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a number of studies (Fergenbaum, et al., 2009; Gunstad, et al., 2007; Lokken, et al., 2010; Walther, et al., 2010). There are also a number of studies that have shown that increasing BMI (from overweight to obese) confers a two- to three-fold increase in risk of AD in middle-aged men and women compared to normal range BMI (Kivipelto, et al., 2005; Whitmer, et al., 2007). This finding has been confirmed in a recent meta-analysis that found that mid-life obesity is associated with a significantly increased risk for AD (Profenno, et al., 2010). Some studies have suggested a U-shaped relationship between BMI and AD risk, i.e. midlife obesity was related to higher risk of dementia (predominantly AD) whereas BMI after age 65 years was inversely related to AD risk (Fitzpatrick, et al., 2009). This association between decreased BMI in late life and increased risk of AD is suggested to be connected with the consequences of the disease process (Fitzpatrick, et al., 2009), given that weight loss is one of the principal manifestations of AD (Gillette, et al., 2007). The mechanisms underlying the association between obesity and increased AD may be related to increased β-amyloid levels. Specifically, a positive association between BMI and plasma β-amyloid 1–42 levels has been observed (Balakrishnan, et al., 2005), while a post mortem study of morbidly obese patients found that AD-like neuropathological changes (tau and β-amyloid precursor protein) were frequently observed and in these individuals approached the levels of neuropathology observed in AD (Mrak, 2009). These obesity-related pathological changes were observed despite any clinical history of cognitive impairment, raising the more general question of whether elevated levels of these neuropathological markers are indeed sufficient to induce age-related cognitive decline. By comparison, a mouse model of AD long-term consumption of sucrose-sweetened water was shown to lead to increased body weight, learning and memory impairment and cerebral β-amyloid deposition (Cao, et al., 2007). Increased BMI in midlife has also been linked to neuronal and/or myelin abnormalities, principally in the frontal lobe (Gazdzinski, et al., 2008). Given that frontal lobe white matter is more prone to the effects of aging than white matter located within other lobes of the brain, these authors suggested that this finding may reflect accelerated aging in individuals with high BMI (Gazdzinski, et al., 2008).

4

Interaction between environmental factors and incidence of AD

While there are a multitude of environmental and lifestyle factors that have been shown to increase or decrease risk for development of AD, no single one of these factors is necessary and sufficient for development of AD. It is likely that these factors (including history of head injury) interact with one another, possibly via common biological mechanisms, to alter an individual’s risk for the development of AD. For example, the previously mentioned environmental factors that are strongly associated with reduced AD, diet and exercise, are likely to provide cumulative protection for AD. A recent study showed that an additive relationship exists between Mediterranean diet and physical activity, such that both Mediterranean diet and physical activity independently decrease the risk of AD (Scarmeas, et  al., 2009).

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The presence of an additive (rather than a synergistic) relationship here suggests that there is unlikely to be a common underlying mechanism mediating the effects of these interventions on AD risk. There are multiple proposed mechanisms by which physical activity decreases the risk of AD. Perhaps most relevant is the finding that physical activity can decrease cortical amyloid burden, possibly by mediating a change in the amyloid precursor protein (Adlard, et al., 2005). Physical activity has also been shown to promote neurogenesis, synaptic plasticity and learning (Pereira, et al., 2007), to promote neuronal survival and resistance to brain insults (Carro, et al., 2001), to reduce inflammation (Reuben, et al., 2003) and increase cerebral blood flow (Rogers, et al., 1990). There are also multiple possible mechanisms by which the Mediterranean diet may reduce AD risk, including reduced vascular risk factors (e.g. Chyrsohoou, et al., 2004; Singh, et al., 2002), lowered levels of oxidative stress (Dai, et  al., 2008) and reduced inflammation (Estruch, 2010; Panagiotakos, et  al., 2009). Although the Mediterranean diet and physical exercise appear to exert functionally independent alterations on risk of AD with respect to conventionally accepted statistical thresholds (p < 0.05), the mechanisms by which they lower Alzheimer’s risk are not necessarily entirely mutually exclusive. For example, reduced inflammation has been suggested to be a means by which both physical activity and Mediterranean diet may reduce the risk of incident AD.

4.1

Interactions between head injury and other risk factors: a heuristic framework?

What are the implications of this catalogue of findings for head injury? Interestingly, one animal study showed that nutritional factors and trauma can interact to produce effects on neural mechanisms and cognitive outcomes. Specifically, consumption of a high saturated fat diet for one month before injury was found to potentiate the deleterious effects of head injury on cognitive function and neuronal plasticity in rats (Wu, et al., 2003). This same research group also showed that dietary supplementation with omega-3 fatty acids can reduce the adverse effects of traumatic brain injury on cognition in rats (Wu, et al., 2004). These animal studies suggest that diet can either ameliorate or potentiate the detrimental effects of head trauma on cognitive function. These possibilities should be explored through further animal studies that are able to probe relevant biological mechanisms. In the context of older humans who have suffered a traumatic brain injury, it seems plausible that similar dietary factors may attenuate (in the case of consumption of omega-3 fatty acids, for example) or potentiate (for example, in the case of consumption of saturated fats) the deleterious effects of head trauma on cognitive decline. Should these relationships indeed be confirmed in humans, it would be of great relevance with respect to targeted interventions in those at greatest risk of sustaining a traumatic brain injury, such as in older people who are at increased risk of falls. Such an approach could offer substantial cost benefits to society. As reviewed earlier, β-amyloid plaques (similar to those observed in AD) have been noted in post mortem brain tissue of humans following traumatic brain injury (Graham, et al., 1995; Horsburgh, et al., 2000; Ikonomovic, et al., 2004; Nicoll, et al.,

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1995; Roberts, et al., 1994; D.H. Smith, et al., 2003). There is also evidence that dietary fat manipulations can affect brain β-amyloid levels. For example, a diet high in saturated fats and cholesterol has been shown to increase β-amyloid accumulation in the brain in animal models (Burns and Duff, 2006; Levin-Allerhand, et al., 2002; Oksman, et al., 2006; Refolo, et al., 2000). Cholesterol has also been implicated in the hyperphosphorylation of tau, which is another pathophysiological marker of AD (Burns and Duff, 2006). Reduced brain β-amyloid accumulation has also been observed in mice fed a DHA enriched diet (an omega-3 fatty acid) (Oksman, et al., 2006). Similarly, dietary DHA has been shown to decrease β-amyloid levels in detergent insoluble membrane fractions in a rat model of AD (Levin-Allerhand, et al., 2002). Accordingly, we believe it is plausible that an interaction between head injury and dietary modifications on cognitive function and risk for AD may be mediated by common effects on brain β-amyloid. As already indicated, we recommend that further studies are conducted to examine this question directly in both human and laboratory animals. The availability over the past several years of neuroimaging techniques that are able to measure amyloid burden in vivo, such as PIB-PET (Klunk, et al., 2001; Mathis, et al., 2002), is likely to be especially useful for examining this issue. Similarly, a significant interaction between head injury and obesity on modification of the risk of AD (although not yet examined to our knowledge) may be biologically plausible through the observed effects of head injury and obesity on β-amyloid levels. A significant positive association between BMI and plasma β-amyloid 1–42 levels has been observed previously (Balakrishnan, et  al., 2005). Furthermore, AD-like neuropathological changes (tau and β-amyloid precursor protein) have been found in the post mortem brains of morbidly obese individuals (Mrak, 2009). Animal studies also support the link between obesity and deposition of cerebral β-amyloid (Cao, et al., 2007). It remains to be investigated whether a significant interaction between head injury and obesity exists. Research in this area should be a priority, especially given the increasing incidence of obesity in western society and demographically aging populations in these societies. A further consideration concerns the relationship between physical activity and diet, specifically regarding the apparently independent (i.e. additive) contributions of some forms of physical activity with the Mediterranean diet in reducing the risk of AD (Scarmeas, et al., 2009). We have previously noted the evidence that physical activity can decrease cortical amyloid burden (Adlard, et al., 2005). Therefore, according to the β-amyloid mediated framework that we propose here to account for the observed effects of traumatic head injury on AD incidence, we can predict (at least indirectly) that there should be no or limited interaction between the effects of head injury and the Mediterranean diet on risk of AD. This proposal awaits further empirical investigation.

Conclusions Head injury has long been proposed as a potentially significant risk factor for the incidence of AD. There has been recent additional interest in putative environmental protective and risk factors for AD. In particular, dietary and lifestyle modifications

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have received a great deal of recent attention. These modifications are likely to be most useful and have greatest effects in those individuals who are predisposed (either genetically or through their personal history, e.g. previous incidence of head injury) to developing AD. Indeed, there is some evidence from the non-human literature that dietary and lifestyle factors can interact with head injury to alter the risk of cognitive decline and potentially alter the risk of AD. These interactions may be mediated by common biological processes, with the most likely proposed candidate mechanism underlying a number of these interactions being increased accumulation of brain amyloid-β. This is the focus of the conceptual model we propose here. It is of great interest for future research to examine whether such an interaction exists between head injury and environmental factors in human subjects – an issue that has not yet been comprehensively explored. Identification and implementation of relevant lifestyle and dietary modifications, which may be particularly effective in preventing or delaying the onset of AD in high risk populations, may offer significant value. Specifically, targeted interventions in head injured patients, who have a higher risk of developing AD, could have significant effects on quality of life in these individuals, and could offer a potential benefit for society with respect to the time and costs associated with accommodating individuals with age-related cognitive decline and caring for patients with AD.

Practical research tips box 1

2

3

Perhaps the most challenging consideration when evaluating associations between environmental factors (including head injury) and the risk of AD is identifying a sufficient number of relevant cases to detect meaningful associations. Future human studies will need to take further advantage of the number of large cohorts (e.g. AIBL in Australia and ADNI and NACC in the USA) that permit the rigorous assessment of relationships between environmental risk factors and incidence of AD. Heterogeneity in the assessment of head injury as well as the retrospective recollection of the severity and other characteristics of the injury represent significant methodological considerations across many published studies. Future, prospective studies can potentially address these issues by undertaking a comprehensive clinical assessment of the injury as close to the time of the event as possible. Such an assessment should include several measures of the severity of the injury, how the injury occurred, whether hospitalisation was required, whether the injury induced concussion or unconsciousness, duration of posttraumatic anterograde and retrograde amnesia, Glasgow coma scale score/s and other methods used at assessment. Greater methodological consistency would offer more direct comparability between studies. There needs to be greater effort invested in exploring interaction/s between different lifestyle factors and the risk of AD. Studies undertaken in laboratory animals are an excellent way to assess potential mechanisms. There are several procedures that have been developed to induce traumatic brain injury

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in animals, and the ability to tightly control environmental factors such as diet provides substantial experimental control and rigour. Moreover, the development of APOE genetic mice offers significant potential for complex geneticenvironmental interactions to be studied in depth.

Acknowledgements This work was supported by a National Health and Medical Research Council project grant (1011093).

Disclosure statement There are no actual or potential conflicts of interest for any authors.

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SECTION IV

Novel interventions for dementia

11 THE EFFECT OF MUSIC THERAPY FOR PEOPLE WITH DEMENTIA Vink, Annemieke and van Bruggen-Rufi, Monique

Introduction Sometimes you can be confronted with a particular tune and it suddenly brings you back in time. You relive all sorts of memories and feel the emotions as you experienced them before. When hearing a particular tune you can find yourself walking in Paris again, but also further back in time, at your grandmother’s kitchen table. At the same time, while you experience the pleasant childhood memories such as the kitchen smells, your grandmother herself may have well forgotten what her own house looked like as a result of dementia. Dementia is a progressive decline of cognitive functions in which people will gradually lose memories of their past. Bender and Cheston (1997) describe dementia patients aptly as ‘the inhabitants of a lost kingdom’. Many approaches have been developed to preserve or stimulate recollection of important life events with demented elderly people in order to improve their quality of life. Many of these approaches depend on verbal communication. One of the most powerful cues to regain access to ‘forgotten memories’ is music (Vink, 2001a). Music has many things to offer for people with dementia. In the earlier stages of dementia, music helps to recall important life events. Musical memories are generally often longer preserved than non-musical memories (Broersen et al., 1995). A couple may have pleasant memories listening to the music that was played at their wedding day, whereas talking about the wedding or watching pictures does not always incite responses. Elderly people with dementia in the more advanced stages will start to become restless and will often wander around the ward. Music therapy in the more advanced stages of dementia will bring rest for the demented person. Like a lullaby that is sung to soothe babies to sleep, music with slow tempi helps to bring rest for demented people who are often anxious at this stage.

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In the last phases of dementia, when people have become bedridden, music is one of the last cues that can be perceived (Norberg et al., 1986). Music therapists sing or play music for the patient while he or she lies in bed, and observe parameters such as respiration and heartbeat to see how the client is responding to music and observe how they can bring relaxation and rest for the patient. As the reader may not be familiar with music therapy, this chapter starts with an overview in which perspectives on effects of music listening, music psychology and music therapy are highlighted. What does music do with us in general as a listener? What is music psychology? Further will be described music therapy in the context of dementia care, illustrated with case examples by the second author.

Historical perspectives on music The idea that music has a healing effect has a long history. One of the first descriptions of the therapeutic effect of music was found on ancient Egyptian papyrus roles, dating to 1500 bc (Benenzon, 1981). In historical descriptions, ‘music as medicine’ has often been described. Music was considered to be a healing component when suffering from diseases, as we can read for instance in Hippocrates’ texts (5th century bc). The Roman physician Galen (2nd century ad) was one of the first to describe the ‘body-mind’ principle in relation to music. He formulated that music influences the ‘affect’ and as such music had a therapeutic function on the body or its bodily fluids (Pratt and Jones, 1985). The most detailed theoretical ideas on the effects of music are by Pythagoras. According to Pythagoras (ca. 582 bc), musical vibrations brought about healing in our body. Classical literature is full of anecdotes mentioning the healing, ‘medicinal’ capacities of music. The following is told in the biography of Pythagoras by Iamlichus, a student of Porphyry’s (James, 1993, p. 32): . . . A young man from Taormina had been up all night partying with friends and listening to songs in the Phrygian mode, a key well known for its ability to incite violence. When the aggravated lad saw the girl he loved sneaking away in the wee hours of the morning from the home of his rival, he determined to burn her house down. Pythagoras happened to be out late himself, stargazing, and he walked into this violent scene. He convinced the piper to change his tune from the Phrygian mode to a song in spondees, a tranquillizing meter. The young man’s madness instantly cooled, and he was restored to reason. Although he had stupidly insulted the great philosopher hours before, he now addressed him mildly and went home in orderly fashion . . . This example describes one of the most known qualities of music: its ability to activate or to find relaxation. Joggers walk in the same pace as the music they listen to on their headphones. In supermarkets too we adjust to the music played for us. Did you ever notice that it always seems to be slow music? This helps us to walk in slower pace between all the products the supermarket wants to show us. When

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French music is played, this will stimulate us to buy French wine and cheese instead of German products or vice versa (North et al., 1997). Often, it has been described how music influences our heart rate, respiration rate and even blood pressure or hormonal levels. Already in the 18th century an effort was made to study the effect of music in relation to physiological changes. One of the best known studies of that time is from Gétry, who published in 1741 about the influence of music on the frequency of heart rate (in Dainow, 1977). The average beat in music approaches the average heartbeat. The precise relationship between musical rhythm and heartbeat is still unclear, although support can be found that the heartbeat generally follows musical rhythms. Stimulating music tends to increase the heart rate and sedative music reduces the heart rate. Each type of music increases the heart rate when the listener starts to listen to music. This increase is higher when listening to stimulating music than to sedative music. Next to changes in heart rate, changes in breathing can be perceived as a result of intense emotional experiences. Ries (1969) found clear correlations between the respiration amplitude and the emotional response to music. The relationship between the breathing amplitude and the subject’s affective responses were highly correlated indicating that the more a subject reported liking the selection, the deeper his or her breathing became. Within the context of music psychology an important focus is the question how music induces emotions in the listener. Are there certain elements in music that may invoke emotional experiences in the listener? Examining the literature, we will find the impressive line of studies that Hevner has conducted. Hevner (1935, 1936, 1937) is one of the first researchers who systematically studied which musical parameters are related to the experience of emotion. She adapted various short existing piano pieces and played them for the subjects, both the original version and an adapted version. Tempo and mode had the strongest impact on the listener, when describing the experienced emotion in the music. Piano music played fast in major is cheerful and, in contrast, the slow piece in minor is considered dreamful and sensitive. After Hevner, it has been shown repeatedly that various musical elements, with a particular mode and tempo, are expressive of emotion in music. In the last few decades there has been a renewed interest in the functions of music within a medical setting from a variety of specializations. This interest can be found from fields such as medicine, musicology, (music) psychology and music therapy. The specific area where music influences our thought processes and emotional experiences in the general listener has become the study object for music psychologists and where specific patient groups are involved, the research area for the music therapist (Vink, 2001b).

What is music therapy? In the last century many instances have been described where music was used in a therapeutic manner. In many hospitals music interventions and music therapy are provided for the patients for relaxation purposes or for pain relief (see for instance

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Bradt and Dileo, 2009). This idea dates from 1891, when Canon Harford started to broadcast relaxing music through a phone network in a general hospital in Great Britain (Davis, 1891 in Bunt, 1995). The origins of music therapy as a profession go back to World War II. Musicians were asked to play for the wounded in the many often crowded and warm hospitals. They were asked to play for recreational purposes. Many of the victims were however severely traumatized, and musicians noted that music induced many profound emotions in them. Since that time, they started to use music therapeutically. The first formal training programme for music therapy started in 1944 in Michigan, USA, at Michigan State University. In the UK, Juliette Alvin, cellist and pupil of Pablo Casals, started the British Society of Music Therapy in 1958 (Bunt, 1995). Music therapy today is a form of therapy in which a qualified music therapist uses music within a therapeutic relationship to improve physical, psychological, cognitive and social functioning. A music therapist needs skills both as a musician and as therapist to achieve these goals. The music therapist may choose active or receptive approaches during therapy. Active music therapy implies that residents are actively involved in the music making, such as playing on musical instruments in a musical improvisation. The music therapist may introduce tasks, such as singing along with familiar tunes. The use of live music stimulates participation, expression and use of preserved skills. In groups, active music therapy techniques stimulate social interaction. In receptive music therapy, the music therapist plays or sings for the client or selects music for the client to listen to. The music therapist adjusts various musical parameters, such as tempo, to either activate the client or for relaxation purposes.

Music therapy for elderly people with dementia When dementia was first diagnosed by German physician Alois Alzheimer in 1906 Alzheimer’s disease was considered a rare disorder. Today, Alzheimer’s disease is the most common cause of dementia and the disease is afflicting more and more people. Other causes or types of dementia that have been distinguished are: vascular dementia, frontotemporal dementia, dementia of the Lewy bodies type, Parkinson’s dementia and so on. Many medicines have been tested in the process to reduce major behavioural problems associated with this disease. In comparison, less research has been directed towards non-pharmacological approaches, such as music therapy. Prinsley (1986) recommended music therapy for geriatric care as it may possibly reduce the individual prescriptions of tranquilizing medication. While most research offers solutions for future patients, it is also necessary to look for effective methods to improve the quality of life for those who are patients today. This means enhancing autonomy for the patients, but also improving the contact between the patient and other patients and caretakers e.g. nursing staff, family and friends. Music therapy is believed to be an effective intervention that can improve the quality of life and can relieve the major behavioural symptoms associated with this disease.

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While language and cognitive functions deteriorate during the course of the disease, many musical abilities appear to be preserved (Aldridge, 1996). The responsiveness of patients with Alzheimer’s disease to music is a remarkable phenomenon (Swartz et al., 1989). Even in the last stage of the disease, patients remain responsive to music where other stimuli can no longer provoke a reaction (Norberg et  al., 1986). Alzheimer’s patients, despite aphasia and memory loss, continue to sing old songs and dance to tunes from long ago. Explanations for this phenomenon are difficult to find. It can be assumed, as is seen with early infant–caretaker interactions, that melodic intonations are an essential component of communication. The fundamentals of language are possibly musical, and prior to lexical functions in language development (Aldridge, 1996). Yet, many aspects of the effect of music on demented elderly people are unknown. What is known is that music therapy has many benefits for elderly people with dementia. Musical rhythm seems to help Alzheimer’s patients to organize time and space. People with dementia lose their verbal skills first, but both general musical and rhythmic skills remain for a long time (Cowles et  al., 2003; Norberg et  al., 1986; Swartz et al., 1989). In the following, overviews of studies in the area of music therapy in relation to cognition, social and emotional functioning and behavioural disorders will be described.

Music therapy and cognition: musical mind gym How are musical memories stored in our brain and why does music have such a profound effect on demented elderly people? Making music and listening to music involves almost all cognitive functions of our brain. One area of research aiming to understand more about the effect of music on our brain is on how music is processed in professional musicians. In the general music psychology literature, it is has been described that in professional musicians the corpus callosum, which connects the left to the right brain hemisphere, has more strengthened pathways in comparison to non-musicians (Lee et al., 2003). The corpus callosum serves as the physical and functional connection between these two cerebral hemispheres. Each hemisphere receives sensory information and controls movement on the side of the body opposite its location. Both language and music are complex cognitive processes that are affected by dementia. Remarkably, musical skills are often preserved and others note that music seems to stimulate verbal functioning. Many people with aphasia who have difficulties speaking still have the capacities to sing-along. While language is primarily located in the left hemisphere, during singing, both hemispheres are active. Rhythm is considered to be processed in the left hemisphere. Currently, lateralization of most music functions to the right hemisphere is considered in terms of more efficient processing in contrast to the specialization of the left hemisphere for language (Polk and Kertesz, 1993). Some researchers have studied the effect of music in relation to cognition, for instance in younger children. This effect has been become known as the

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Mozart-effect, in which listening to Mozart leads to cognitive enhancement. Similarly, it has been studied if music listening and therapy can help to retain or stimulate cognitive capacities in elderly dementia patients. Van de Winckel et al. (2004) evaluated the effect of a music based exercise programme on cognitive functioning and mood state in demented elderly women (n = 15), compared to a control group (n = 10), who followed daily conversation sessions for three months. Music-based exercise training over three months had a slight effect on cognitive functioning in patients with moderate to severe dementia, based on subscales scores on the ‘fluency’ cluster on the Mini Mental State Examination (MMSE). The control group showed no improvement. Cuddy and Duffin (2005) presented a case study of an 84-year-old woman with severe cognitive impairment, for whom music recognition and memory, according to her caregivers, appeared to have been spared. In order to assess her music recognition abilities, various tests were conducted. Two tests involved the discrimination of familiar melodies from unfamiliar melodies. The third involved the detection of distortions (‘wrong’ notes) in familiar melodies and discrimination of distorted melodies from melodies reproduced correctly. The woman responded to familiar melodies by singing along. To distorted melodies she responded mostly with facial expressions. The contrast between her adequate responses to music and her minimental status test scores (8 out of 30) is remarkable, according to the authors. Hevele (1988) studied whether memory for language and melody is indeed spared in 52 elderly people with Alzheimer’s disease. Eight well-known songs were selected. The first line of the song was spoken to the patients with the task to complete the text. Then, the line was sung to them in la, la, la with the question to complete the melody line with la, la, la. Finally, the first line was sung to them with the question to complete the line singing the lyrics. The results were that patients recalled more when language and melody were combined in comparison to offering only the text or only the melody. Similar findings have been found by Pickett and Moore (1991) who described that patients remembered the words of songs they had sung better than spoken words. The recall of songs was better when the songs were relatively old in comparison to more recently learned songs. Foster and Valentine (2001) looked at the effect of auditory stimulation on recall of personal facts in 23 older adults with mild to moderate dementia. Participants participated in four conditions: a) background/cafeteria noise; b) familiar music (first movement of Vivaldi’s “The Four Seasons”), c) modern music (Fitkin’s “Hook”) and d) silence. Performance was significantly better with music compared to silence or cafeteria noise. There was no difference between familiar and novel music. Recall was best for questions asked about the time when the patients were young. Similar effects were found by Irish et al. (2006) who studied the effect of music on autobiographical memory recall in mild Alzheimer’s disease individuals (n = 10) and healthy elderly matched individuals (n = 10). A music condition (Vivaldi’s ‘Spring’ movement from “The Four Seasons”) was compared to a silence condition. Considerable improvement was found for Alzheimer’s individuals’ recall on the Autobiographical Memory Interview in the music condition (p < 0.005).

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They further found a significant reduction in state anxiety (State Trait Anxiety Inventory) for the patients in the music condition (p < 0.001), suggesting anxiety reduction as a potential mechanism underlying the enhancing effect of music on autobiographical memory recall. Hailstone et al. (2009) describes a client with a relatively well-preserved knowledge of music who was a musically untrained patient and suffered from semantic dementia, in which musical memory was assessed five years after clinical onset. The client was asked to sing or hum to familiar tunes and was successful in completing the melodies for 25 of the 40 presented tunes. For instance, she completed the pop songs with an average accurate text of 5.3 words. The performance formed a great contrast to her impaired verbal skills on other tests. The authors conclude that knowledge of music may be preserved in semantic dementia compared to other sources of knowledge as it does not depend on episodic memory. Overall, studies focusing on the effects of music and music therapy in relation to cognition show that information presented in songs is recalled more easily than verbal information alone. Further, music seems to facilitate general recall of important life events in mildly to moderately demented elderly patients. It should be noted that the evidence is not strong and is mostly described within case studies. Baird and Samson (2009) reviewed the findings of eight case studies and three group studies studying musical memory in Alzheimer’s disease patients and also state that musical memory in dementia becomes typically impaired during the dementing process. Specifically, memory for familiar music, engaging semantic and/or episodic musical memory, is impaired in the majority of reported cases.

Music therapy and social/emotional functioning Music provides an opportunity for people to engage socially, from which persons who are not able to speak any more can benefit too. Lord and Garner (1993) studied the improvement of social, cognitive and emotional functioning in dementia, in which 60 patients were randomized, stratified by sex, to three groups of 20. One group listened to six 30-minute sessions of ‘Big Band’ music and were given children’s musical instruments so that they could actively participate. A second group was given wooden jigsaws and other puzzles, and a third group was given no special activities except the usual pastimes of drawing, painting and watching television. Music therapy was found to be more effective than the control interventions: patients were happier, more alert and had higher recall of past personal history after music therapy than patients in the control groups (puzzle activities and general activities). Sherratt et al. (2004) studied whether social interaction in moderately to severely demented people (n = 24) can be improved by introducing music in the nursing home. Half of the people were listening to music, live as well as recorded, and they were compared to a no-music condition. Live music was significantly more effective in increasing levels of engagement and well-being, regardless of the level of cognitive impairment.

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Patients who have lost the ability to talk coherently often retain the ability to sing (Novick, 1982). Olderog Millard and Smith (1989) studied the therapeutic effect of singing familiar songs and in particular if social interaction differed between singing sessions and discussion sessions. In this study, ten patients with Alzheimer’s disease participated. Sessions were held twice weekly for 30 minutes for five weeks. A reversal design (ABABA) was implemented in which the patients both followed discussion sessions (A) and sessions with therapeutic singing (B). Both types of sessions seemed to have an effect rather than singing alone. Staff members expressed surprise at seeing the patients singing, especially those patients who were severely regressed and who rarely spoke. Pollack and Namazi (1992) noticed an increase (24%) in social behaviours such as smiling, talking and touching from before to after attending music therapy sessions. Clair and Allison (1997) report that activities like singing and rhythm playing are beneficial and stimulate the social contact between the patient and his or her family member. Results were non-significant between pre- and post-measurements in relation to perceived caregiver burden and feelings of depression, but offering music did significantly increase their satisfaction about the visit. Overall, it can be concluded that music therapy has a positive effect on emotional well-being and participating in music therapy increases social response and helps family caregivers as well.

Music therapy in practice: social and emotional well-being Mark and Jane were happy as can be: they had been married for almost 60 years, and after an equal number of years having worked very hard in their own little grocery store in a small, rural town, they enjoyed their retirement to the fullest. Their eight children, all grown up and married, had given them many grandchildren. Being grandparents was the most beautiful “job” they had ever enjoyed. They both loved singing very much, and they were loyal members of the choir in the city. They were very outgoing, they had a lot of friends and family surrounding them, their social live was very rich. A perfect life, so to speak. Until the day that Mark survived a severe stroke. After his recovery Mark seemed to be a different man, with a different character. The outside world didn’t notice very much of the change in his behaviour: he never lost his humor, he always had time for a nice chat, the door was always open for guests and his grandchildren were still the joy of his life. However, it was Jane who had to deal with the “new” Mark 24/7. Most of the time Mark was just grumpy towards Jane. On bad days however Mark showed paranoia behaviour: according to Mark, Jane was having an affair with the postman, with the neighbour, with every male in the village. Jane was not allowed to go anywhere, Mark had to see her and control her all the time. Sometimes he was so convinced about her being a bad woman that he physically abused her . . . The worst part was that Mark didn’t seem to realize afterwards what he had been doing to her. He could not be corrected in his behaviour.

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Mark and Jane turned into a couple that stayed home most of the time. Although people didn’t stop visiting them, it was a big change in their life. Especially for Jane this was very hard. Obviously this was a very big concern for the children who took care of their parents. They wanted so badly to find a way to get the happy moments back again. The only shared hobby they could think of was the music, the choir. Their parents had always sung in harmony and still knew all the songs from way back when by heart. Their case manager came up with the idea of involving a music therapist. The first time that I met them I entered the living room where Mark and Jane were sitting, carrying the guitar on my back. The very first thing Mark said was: “I challenge you . . . hardly anyone knows the song from my youth . . .” and he named his favourite song. My gain. . . . I knew the song! It was the same song that my father always sang for me when I was young . . . Mark was pleased to hear me sing the song, the ice was broken. I had brought along many songs from their past, lyrics and all. Jane made excuses right away that she hadn’t been singing for quite a while, so it probably would sound awful. I assured her that this had nothing to do with “how nice” we’d sing, that it had everything to do with the fun and joy we would have together while singing, no matter how it would sound. But I challenged them to sing together, in harmony, different voices, just like they always used to do. I saw “teamwork” right away: Jane asking Mark about the pitch, about the lyrics that Mark seemed to know all by heart. In short . . . they teamed-up right away! I played along and sang along, just to support and to encourage them. They liked it so much that they wanted me to come back every week, which I did. Especially for Jane it was the highlight of her week. And Mark had fun, you could tell! He and I bonded very well, having the same kind of humor. A regular session would consist of coffee drinking, talking about the past week, and then talking about their past life. Sitting in their own living-room this was easy because we were surrounded by many family pictures. The stories they told about their life I “translated” into songs, either existing ones or improvised ones, using songwriting techniques. After a while I also gave them small instruments to play along, like maracas, a shaking egg, a tambourine. They enjoyed this very much, and their teamwork in playing together grew stronger . . . Of course I also mentioned their problems every now and then. I saw a very sad Jane, reluctant of talking about this. Mark seemed to not get the message, and Jane tried very hard to avoid the subject. Obviously it just seemed too difficult for them to talk about this together. This is when I decided to make a song together, with lyrics made by them, and later on, sang by them. The song was about their life and their (grand)children, and between the lines it was about their problems ever since Mark got sick. . . . We intentionally choose a melody very well-known to them, from one of their favourite songs. In that way they didn’t have to bother about learning a new melody. We talked about what should be in the song, and I used the words that they came up with themselves . . . being THEIR song.

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When the song was finished we sang it over and over again, me playing the guitar, them singing. When both were satisfied we recorded it and made a CD. Their sixtieth anniversary came up, and the CD was copied 15 times. On the day of their get-together with the whole family they presented the CD and gave them away. The weekly music therapy-sessions couldn’t really change Mark’s character, his cognition being just too much damaged because of the stroke. But at least they gave Mark and Jane something they could enjoy together, thus improving the quality of life for both the patient AND the caregiver.

Music therapy and behavioural problems One of the most reported behavioural symptoms in demented elderly patients is agitation, which causes great distress both for the patients themselves and their caretakers. An estimated 70 to 90% of the people inflicted with dementia will eventually develop behavioural symptoms during the course of the disease (Zuidema et  al., 2007). Agitation is a broad term that includes a variety of behaviours. It includes behaviours such as aimless wandering, pacing, cursing and screaming (CohenMansfield and Billig, 1986). On several occasions it has been shown that feelings of agitation in demented patients can be relieved through music and music therapy (Brotons, 2000; Sherratt et al., 2004; Vink, 2000; Vink et al., 2011, 2012, 2014).

Wandering behaviour One of the behaviours that can typically be found in demented elderly is wandering behaviour. Often, patients are seen in the nursing homes restlessly pacing up and down the corridor. Doors have to be locked constantly, as it happens all too often that the wanderer falls and injures himself when he enters unknown areas. Wandering behaviour is part of the cluster of problem behaviours that make up anxious or agitated behaviour. Groene (1993) studied the effect of music therapy in reducing wandering behaviour with 30 Alzheimer’s disease patients (aged 60–91) in the late and severe stages of dementia. For the baseline measurements, the wandering behaviour of each participant was recorded for a minimum of three days, between 2.00 p.m. and 5.30 p.m. The subjects were randomly assigned to either a mostly musical condition (e.g. five music sessions and two reading sessions) or to mostly reading sessions (e.g. five reading sessions and two music sessions). Each subject received alternate sessions of individual reading sessions and individualized music therapy each day of the week, for a maximum of 15 minutes. Music therapy sessions consisted of listening to music, playing instruments, singing and movement or dance. Live music activities were incorporated into each session. Reading sessions consisted of the therapist reading aloud to the client or the patients themselves reading aloud. Both activities were, when possible, adjusted

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to personal preferences. The amount of time wandering subjects remained seated was longer for music sessions, regardless whether they participated in the mostly music or in the reading sessions. Wandering in general outside the sessions did not decrease. Several studies have shown that wandering behaviour decreases due to music therapeutic intervention (Clendaniel and Fleishell, 1989; Fitzgerald-Cloutier, 1993; Groene, 1993; Olderog Millard and Smith, 1989).

Agitation during bathing Behavioural problems are very time-consuming in the care for these patients. A simple task, such as bathing or toileting, can take hours due to aggression and nonco-operation. Management of behavioural symptoms in patients with dementia is essential to improve the quality of life for the patients and their caregivers. Clark et  al. (1998) studied the effect of tape-recorded music during bathing episodes with 18 residents with severe Alzheimer’s disease. For a period of ten weeks, the residents’ preferred music was played for them, and this was alternated with a period of ten weeks where no music was played. Results indicated that during the music period, decreases occurred for 12 of the 15 observed agitated behaviours. The five most frequently recorded behaviours were yelling, abusive language, hitting, verbal resistance and physical resistance. A direct effect of music was found as well as an indirect effect on the caretakers. Caregivers noted that during the music episodes, the mood of the residents was improved: they were smiling more and were more co-operative, making the bathing task more pleasurable for the caregivers. A similar study has been conducted by Thomas et  al. (1997). A total of 14 patients with Alzheimer’s disease were observed during bathing times. All were diagnosed as middle stage dementia. A music tape was recorded with the help of family members. Typical musical selections included music of Glenn Miller and Beethoven’s Moonlight Sonata. Music was played on three occasions for each resident. Significant reductions were found for aggressive behaviours, as was the case in the previous described study.

Mealtime agitation Agitation is often the result of sudden changes of environment. Any major environmental change may cause agitation as the place looks unfamiliar. Even such small changes as moving a chair can cause agitated behaviours like aggression. An environmental change is also apparent when residents are brought to the dining room, and residents often become highly agitated. Typical for the community rooms in a nursing home is the large amount of background noise. Several researchers have studied if background music can contribute to a less disturbing nursing environment. Goddaer and Abraham (1994) investigated if playing tape recorded music in the dining room could reduce the general noise level. Decreasing the noise

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level was expected to decrease agitated behaviours. Twenty-nine demented residents participated in a four-week music programme. In the first week, no music was played in the dining room and baseline observations of the prevalence of agitated behaviours were made. In the second week, relaxing music was introduced in the dining room. The music was selected on the basis of slow tempi, and additional music was selected from New Age recordings. In the third week, no music was played, but music was reintroduced in the fourth week. Significant reductions were observed in agitation. The presence of agitation followed the distinct pattern of the study design. Agitation decreased from week one to the second week when the relaxing music was introduced (54%), increased in week 3 (38.4% = control period) and decreased in week 4 (43% = music period) when music was played again during dinner. From this study it can be concluded that music indirectly affects feelings of agitation by reducing the general noise level. Similar results have been reported by Denney (1997). Ragneskog et  al. (1996) studied whether the observed effects depended on the type of music played and if food intake increased as a result of music listening. Three types of music were used. First, soothing music, then old popular Swedish songs from the 1920s and 30s (songs the patients would typically know from their youth) and last, contemporary pop music. Each type of music was played in the dining room for two weeks, while patients were coming in to have their dinner. Between the musical periods there were one week intervals in which no music was played. The reactions of the patients to the three different types of music were videotaped. Four out of five patients spent more time at dinner during the music periods than in the control periods. The study showed that all the patients who were having dinner were affected by music, particularly by soothing music. Individual responses that were observed during the study were that one of the typically restless patients became unusually calm, whereas another ate more than usual. Significant improvements in symptoms of irritability, fear and depressed mood were seen when music was played at meals compared to the control period without music. Soothing music was found to have the most beneficial effect. These benefits appeared to persist right through the control period. The study concluded that slow, relaxing music can indeed improve symptoms associated with dementia and stimulate elderly residents to eat more. Results were replicated in a study by Chang et al. (2010), which also demonstrated a decrease in agitation when music is presented at lunch/mealtime. To conclude, most studies indicate a decrease in agitated or related behaviours through a music or music therapy intervention and suggest that music therapy might be a viable non-pharmacological intervention to reduce agitation in demented elderly (see also Vink et  al., 2011, 2012, 2014). Specific behaviours that are part of the cluster of agitated behaviours that have been found to decrease are vocally disruptive behaviour, hitting, wandering, crying and pacing and an increase in hours of sleep (see Table 11.1).

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TABLE 11.1 Examples of specific agitation-related behaviour changes brought about by musical interventions (based on Vink, 2013)

vocally disruptive behaviour

(Casby and Holm, 1994; Denney, 1997; Thomas et al., 1997)

hitting

(Clark et al., 1998)

wandering

(Clendaniel and Fleishell, 1989; Fitzgerald-Cloutier, 1993; Groene, 1993; Olderog Millard and Smith, 1989)

crying and pacing

(Brotons and Pickett-Cooper, 1996)

increase in hours of sleep

(Hanser, 1990; Lai and Good, 2005; Lindenmuth et al., 1992)

Music therapy in practice: frontotemporal dementia “It looks like mother has gained a lot of weight over the past few months” .  .  . Anne’s daughter exclaims during a meeting between herself, the nurse and the physician in the nursing home where her mother resides. And she is right . . . in the past year Anne’s size has grown from size 10 to 16, gaining almost 50 pounds. Anne suffers from frontotemporal dementia (FTD). One of the symptoms is gluttony, due to the fact that she doesn’t know when or how to stop . . . not only with eating: she screams, curses, laughs in inappropriate moments. In short, Anne is a patient who is “hard to handle”. In the ward where she lives, she is a so called “disturbing factor” for the other residents and is very claiming towards the nursing staff as a result of FTD. I have known Anne for quite some time now and during music therapy I often see a complete other person: Anne loves music and the music seems to calm her down. The songs that we are singing together, sitting behind the piano, seems to be the perfect way for Anne to let her emotions go. Music and emotion . . . it is a small step to music and MOTION . . . could some physical exercise with music be beneficial for her and to lose weight? In the past Anne has had physical therapy, but this didn’t work out because of the behavioural problems mentioned above. I start with Anne soon after this meeting. Being trained as a Neurological Music Therapist (NMT) I think of some good exercises in which we can train her motor skills. Sitting behind the piano we start with simple hand/arm and feet/ leg movements. Choosing the exact right songs is essential: not only the rhythm has to be right for the movements itself, but also I choose songs that Anne likes. If not, I will “lose” her. I sing children-songs with a strong beat. I let Anne sing along, but more important, move along. In the meantime I give her simple tasks to accomplish: “move your right leg when I play high, your left leg when I play low”. By doing so I not only train her moving skills, but at the same time her cognitive skills: she has to pay attention to what I am asking, so her concentration is trained as well. On other occasions I play a prerecorded CD and I move along with her. We march through the room, walking on our toes or on our heels. We dance. We sing

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along. We have fun. I place different instruments in the room for Anne to play, but I do this so that Anne has to stretch out and reach for the instruments to play. Without her noticing it herself we exercise different muscle groups and different movements. The techniques that I use are all NMT-techniques: NMT is defined as “the therapeutic application of music to cognitive, sensory, and motor dysfunctions, caused by neurological diseases”. NMT uses a research-based system of standardized clinical techniques used for sensorimotor training, speech and language training and cognitive training (Thaut and Hoemberg, 2014). For Anne it seems to be the perfect combination of having fun AND exercise at the same time. It’s a perfect win-win situation: the only gain we hopefully don’t see any longer in the near future is the gaining of Anne’s weight . . . (van BruggenRufi, 2011).

Implications for practice In this chapter, it has been shown that music therapy is a viable method for the treatment of people with dementia. Music therapy is generally offered to the clients once or twice a week. It is advised to also integrate music in nursing interventions during the week. For those clients who follow music therapy, the effects will be enhanced during the weekdays when not following therapy. A music therapist can coach nursing home staff in doing so. Not all clients require therapy and many more nursing home residents can benefit from music when it is included in daily routine as a nursing intervention. For these clients, familiar music can help to induce pleasant feelings, or memories can be stimulated. Especially for people with dementia, who often cannot speak, music can be an important stimulus to recall pleasant memories and feelings. Listening to music is a pleasant activity for many people with dementia. They remember the “good old days” and often start to talk in response to the lyrics of a familiar tune. As a result, social contact with other residents, relatives and caretakers is enhanced. Preferred individual music listening is most effective to reduce agitation (Gerdner, 2000). To conclude, there are clear indications in the literature that music has many positive effects when integrated within general care. It is advised to implement this knowledge on a daily basis within nursing interventions. Besides integrating music during daily moments and nursing interventions, it is also advised to stimulate movement. Residents in a nursing home often lack sufficient exercise, with many consequences for their circulatory system and overall well-being. Residents spend their days mostly sitting or lying in bed. Scherder et al. (2010) state that a decline in physical activity has a detrimental effect on cognition and behaviour in patients with dementia. The more physical inactivity, the more agitation will develop. Vink et al. (2013) describe ten easy to use music and movement interventions that can be used by both professional and family carers to provide moments of interaction, stimulation or relaxation for demented elderly people. The advice is largely appreciated by both the residents and their caregivers.

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To conclude, the future for music and music therapy with demented elderly is promising. Nursing home care for institutionalized demented elderly has gone through many changes over the years. New care approaches focus on the social and emotional well-being of the client and stimulate present abilities. Approaches are required that focus on improving the quality of life of the residents and reduce problematic behaviours associated with dementia. Music therapy clearly serves all these goals!

Practical tips for new research To gain more insight in efficacy of music therapy more randomized or controlled studies are required or other robust research methods to ensure valid outcomes. New studies are welcomed that focus more on specific defined groups related to severity, symptoms and aetiology of the dementia. It is likely that specific forms of music therapy are more appropriate for specific subgroups, symptoms or settings. As such, clearer recommendations can be made for each stage of the disease for music therapists working in practice with demented elderly people. Further, more research is needed on which musical interventions within therapy are effective in relation to specific treatment goals. For instance, it is known that singing may stimulate hemispheric specialization. Clinical observations indicate that singing critically depends upon right-hemisphere structures. By contrast, patients suffering from aphasia subsequent to left-hemisphere lesions often show strikingly preserved vocal music capabilities. Singing may be exploited to facilitate speech reconstruction when suffering from aphasia (Riecker et al., 2000).

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Lai, H. L. & Good, M. (2005). Music improves sleep quality in older adults. [Clinical trial randomized controlled trial]. Journal of Advanced Nursing 49(3): 234–244. doi: 10.1111/ j.1365–2648.2004.03281.x Lee, D. J., Chen, Y. & Schlaug, G. (2003). Corpus callosum: Musician and gender effects. Neuroreport 14(2): 205–209. Lord, T. R. & Garner, J. E. (1993). Effects of music on Alzheimer patients. Percept Mot Skills 76(2): 451–455. Lindenmuth, G. F., Patel, M. & Chang, P. K. (1992). Effects of music on sleep in healthy elderly and subjects with senile dementia of the Alzheimer’s type. The American Journal of Alzheimer’s Care and Related Disorders & Research 2: 13–20. Norberg, A., Melin, E., & Asplund, K. (1986). Reactions to music, touch and object presentation in the final stage of dementia. An exploratory study. International Journal of Nursing Studies, 23(4): 315–323. North, A. C., Hargreaves, D. J. & McKendrick, J. (1997). In-store music affects product choice. Nature 390: 132. Novick, L. J. (1982). Senile patients need diverse programming. Dimensions in Health Service. 59(9): 25–26. Olderog Millard, K. A. & Smith, J. M. (1989). The influence of group singing therapy on the behavior of Alzheimer’s disease patients. Journal of Music Therapy 26(2): 58–70. Pickett, C. A. & Moore, R. S. (1991). The use of music to aid memory of Alzheimer’s patients. Journal of Music Therapy 28(2): 101–110. Polk, M. & Kertesz, A. (1993). Music and language in degenerative disease of the brain. Brain Cogn 22(1): 98–117. Pollack, N. J. & Namazi, K. H. (1992). The effect of musical participation on the social behavior of Alzheimer’s disease patients. Journal of Music Therapy 29(1): 54–67. Pratt, R. R. & Jones, R. W. (1985). Music and medicine: A partnership in history. In R. Spintge & R. Droh (Eds.), Muzik in der Medizin (pp. 377–388). Berlin: Springer Verlag. Prinsley, D. M. (1986). Music therapy in geriatric care. Aust Nurses J 15(9): 48–49. Ragneskog, H., Kihlgren, M., Karlsson, I., Norberg, A., Gerdner, L. A. & Buckwalter, K. C. (1996). Dinner music for demented patients: Analysis of video-recorded observations. Clinical Nursing Research 5(3): 262(221). Riecker, A., Ackermann, H., Wildgruber, D., Dogil, G. & Grodd, W. (2000). Opposite hemispheric lateralization effects during speaking and singing. Neuro Report 11:1997–2000. Ries, H. A. (1969). GSR and breathing amplitude related to emotional reactions to music. Psychonomic Science 14(2): 62–64. Scherder, E. J., Bogen, T., Eggermont, L. H., Hamers, J. P. & Swaab, D. F. (2010). The more physical inactivity, the more agitation in dementia. International Psychogeriatrics/IPA 22(8): 1203–1208. Sherratt, K., Thornton, A. & Hatton, C. (2004). Music interventions for people with dementia: A review of the literature. Aging & Mental Health 8(1): 3–12. Swartz, K. P., Hantz, E. C., Crummer, G. C., Walton, J. P. & Frisina, R. D. (1989). Does the melody linger on? Music cognition in Alzheimer’s disease. Semin Neurol 9(2): 152–158. Thaut, M. H. & Hoemberg, V. (2014). Handbook Neurologic Music Therapy. Oxford: Oxford University Press. Thomas, D. W. H., Robert, J. & Alexander, T. (1997). The effects of music on bathing cooperation for residents with dementia. Journal of Music Therapy 34(4): 246. van Bruggen-Rufi, C.H.M. (2011). “Bewegen en bewogen worden”, muziektherapie bij een cliënt met Frontotemporale Dementie (To move and being moved: Music therapy with a patient who suffers from frontotemporal dementia). Tijdschrift voor Vaktherapie (Ed. 2–2011).

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Van de Winckel, A., Feys, H., De Weerdt, W., & Dom, R. (2004). Cognitive and behavioural effects of music-based exercises in patients with dementia. Clinical Rehabilitation, 18(3): 253–260. Vink, A. C. (2000). The problem of agitation in the elderly and the potential benefit of music. In D. Aldridge (Ed.), Music Therapy in Dementia Care (pp. 102–118). London: Jessica Kingsley Publishers. Vink, A. C. (2001a). Forgotten melodies: Music therapy with demented elderly. In D. Aldridge, G. di Franco, E. Ruud & T. Wigram (Eds.), Music Therapy in Europe (pp. 149–161). Rome: Ismez. Vink, A. C. (2001b). Music and emotion: Living apart together: A relationship between music psychology and music therapy. Nordic Journal of Music Therapy 10(2): 144–158. Vink, A. C. (2013). Music therapy for dementia: The effect of music therapy in reducing behavioural problems in elderly people with dementia. Doctoral Dissertation: Rijksuniversiteit Groningen, Netherlands. Vink, A. C., Bruinsma, M. S. & Scholten, R. J. S. (2011). Music therapy for people with dementia (updated Cochrane Review). In The Cochrane Library. Chichester, UK: John Wiley & Sons, Ltd. Vink, A. C., Erkelens, H. & Meinardi, L. (2013). Muziek en bewegen bij dementie (Music and movement for dementia). Amsterdam: Reed Business Education. Vink, A. C., Zuidersma, M., Boersma, F., de Jonge, P., Zuidema, S. U. & Slaets, J. P. (2012). The effect of music therapy compared with general recreational activities in reducing agitation in people with dementia: A randomised controlled trial. Int J Geriatr Psychiatry Dec 26. doi: 10.1002/gps.3924. Vink, A. C., Zuidersma, M., Boersma, F., de Jonge, P., Zuidema, S. U. & Slaets, J. P. (2014). Effect of music therapy versus recreational activities on neuropsychiatric symptoms in elderly adults with dementia: An exploratory randomized controlled trial. Journal of the American Geriatrics Society 62(2): 392–393. Zuidema, S. U., Derksen, E., Verhey, F. R. & Koopmans, R. T. (2007). Prevalence of neuropsychiatric symptoms in a large sample of Dutch nursing home patients with dementia. International Journal of Geriatric Psychiatry 22(7): 632–638.

12 POETRY AS A MEANS OF (RE)CREATING SATISFYING LEVELS OF PERSONHOOD AND SOCIAL INTEGRATION FOR PEOPLE DIAGNOSED WITH DEMENTIA Method, discussion and outcomes Petrescu, Ioana The narrative of research actualisation One evening my aunt who was in the early stages of dementia started reciting poems at the dinner table: they were poems she had learned many years before as a child and teenager. I asked what reminded her of those poems and her answer was that sitting at the dinner table with my family brought back the memory of safe and happy times at the dinner table with her parents. They were proud of her good grades at school and she was happy to show off what she’d learned. I discussed that happening with her doctor and he said that he would encourage her to keep reciting poetry as a means of keeping her mind working. And this is how it all started: I developed a keen interest in the impact of poetry reading/reciting/memorising (and why not writing it too?) on the wellbeing of people with dementia.

Introduction My research started with the support of the University of South Australia through a DRPF grant, and also the very generous support of Alzheimer’s Australia SA, who agreed to host my poetry workshops on their premises and advertise the availability of the workshops to members that were part of what is termed as early intervention. In time, colleagues and research assistants became involved for a while until their own research interests took them on different paths. I would need to acknowledge here the support of Dr. Rob Ranzijn, Dr. Jodie George, Dr. Cameron Fuller, Leeston McNab, and Dr. Kit MacFarlane. The project grew from a set of workshops, to a book of poetry by people with dementia, to articles, more poetry, a book chapter, and my interest in the topic is still unwavering.

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The initial idea I had was to offer poetry writing workshops to people with dementia in the early stages of the condition, in an effort to help them create something visible that would make them proud and help their carers, families, and community realise that the same valuable person was still there behind the screen of the illness; that the person and therefore their personhood were still very much present; and the capacity to create was still there, enabling them to tap into their lifelong baggage of accumulated knowledge and skills. I was interested in finding out at the end of the workshop series what the participants had to share about their experience of writing poetry, in view of putting the gleaned insights in the hands of researchers for the benefit of persons diagnosed and the community, all the time working according to university ethics approvals, and based on guidelines offered by Alzheimer’s SA.

Method I devised a series of six two-hour workshops that were held over six weeks once a week on the premises of Alzheimer’s SA. The workshops were advertised to members and several people with dementia showed interest. Several prospective participants came in the beginning, but the nature of the condition being fairly unpredictable even in its early stages, some only attended a couple of workshops, and four participants ended up attending all workshops. Participants attended with their respective carers, and while the workshops had not been designed for carers an unexpected outcome was the keen interest of the carers, some of them doing the exercises too and writing their own poems.

Workshop 1 The first workshop was dedicated to getting to know each other and creating a friendly atmosphere conducive to trust and sharing in writing. I read some of my own poems and talked about the fact that poems don’t always need to rhyme; the words, images, and emotions will do the work and create empathetic communication. The first exercise was to write about a tree. I read several tree poems and then the participants tried their hands at writing their own poems. Nature poems are a good start for any poetry workshops: relatable objects create familiarity and stimulate memory and imagination. Participants were happy to read their poems out loud and gave each other words of encouragement and appreciation. The quality of the poems from a strict literary point of view was very good, in fact so good that many tree poems made their way into the poetry collection we put together at the end of the workshop series. Jane’s work is an example in point: Tree poem

Skeleton reaching to the sky Tendrils tickling the clouds Going down through its strong trunk

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To the roots feverishly searching for nourishment Pushing between the soil clumps Breaking them into smaller lumps Like fingers massaging sore muscles. ( Jane in Words that shine, p. 3) We had not discussed notions such as alliteration, similes, metaphors, and yet Jane made use of all such devices, which she clearly knew and had most probably used before. She told us she had written articles for her local newspaper and obviously her way with words had not just vanished at the onset of the condition. At that time Jane was still living independently but carers visited on a regular basis, did chores, and took her shopping, to the workshops and other activities. She enjoyed the workshops and was very participative for the majority of the time spent in class teaching and learning mode.

Workshop 2 The second workshop introduced the participants to a much-loved fixed form poem, the haiku. I talked about the basic principles of writing haiku: three lines, five syllables – seven syllables – five syllables, compulsory nature word, emotion, and conclusive last line. The results were again at high levels of accomplishment: Rain

Rain across dry earth Gushing and rumbling downstream Waking up the creek (Kate in Words that shine, p. 14) Kate had studied poetry at the university and was very familiar with the haiku form, which she had in fact practiced several years before. Her poem came out beautiful, clear, evocative, and perfect in every way. Kate is a very good writer and has a lot of encouragement in her journey from family, friends, teachers, and the community. She has raised awareness about living with memory loss through participating at and organising specific events, and has gone on to publish her own poetry volumes. Her courage and civic conscience are amazing now as they were years ago when I met her first. Kate loves words and words love her back, they are a great part of her journey that she generously shares and informs about.

Workshop 3 I discussed this workshop with the Alzheimer’s SA staff, the idea was to ask the participants to focus on a very pleasant beautiful memory and write about it. I consulted the staff members on several occasions, before, during, and after the workshops, and they generously gave me their time and advice, which in this case was to

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go ahead and do the exercise because it would be a positive reinforcement of longterm memory. Participants were encouraged to focus on a time in their lives when they were very happy and proud of some particular achievement and the memory of it had been long-lasting. Mary’s poem Winter speaks about the snow of this season in the northern hemisphere where she had come from many years before: Slowly, gently and in silence the snowflakes’ dance is mesmerising. Bringing whiteness bringing calmness bringing beauty bringing peace. ( from Winter, by Mary in Words that shine, p. 31) Anyone who experienced winter and snow can relate to the images, feelings, and emotions evoked by Mary’s poetry lines. Poetry and creativity tap into universal experience and empathy, people reach to poetry in their moments of intense feeling, and this poem is no different. I often tell my university students that poetry cannot be measured in dollar value, but in the smiles of brides whose grooms recite poems for them at weddings, in the tears of people when they farewell their departed with a poem, in the commonality of thought and emotion. Mary has captured in her verses the whiteness, calmness, beauty, and peace of the snow, and no suffering or condition, even Alzheimer’s, can take that away from her.

Workshop 4 My choice of creative writing exercise for the fourth workshop was the portrait poem. Portraits evoke people and thus stimulate memory. For the workshops conducted at Alzheimer’s SA I tried to find exercises that could stimulate memory in a non-intrusive way and always checked with the Alzheimer’s SA staff if in doubt. Participants wrote mainly about their loved ones, children, partners, other family members. Kath’s choice is different, the portrait is that of a woman she photographed while travelling across the Peruvian high plain: We wanted a photo of a local peasant and you see her after she allowed me to tilt back her hat and accepted the money we offered. How lucky we are to live as we do. The photo shows the story of a hard life and

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an unkind climate. She looked seventy years old but is closer to forty. ( from Overseas by Kath in Words that shine, p. 24) Kath’s condition was more advanced, however, she was persistent and very proud of her work. She was enthusiastic about the thought of collecting the poetry resulting from the workshop in a volume, which was actually a suggestion that came from the participants. I had not thought of it mainly because of the sensitivity of the material, the ethics implications, and privacy issues about the condition itself. However, the participants themselves proposed that the poems be published, they said they felt empowered by the thought that a creative visible outcome would be the result of their workshop participation. I have often experienced such a sentiment being expressed by university students, i.e. the desire to share thoughts and experiences through publication, and the feeling was no different at the Alzheimer’s SA workshops: poets were generously offering their thoughts to the community and felt proud of their achievements.

Workshop 5 The fifth exercise is a tried and tested creative writing topic and arts subject of representation: teachers have been bringing real fresh fruit to their classes for centuries, asking participants to write about them or to paint them. My choice for this workshop were mandarins. Jane saw the fruit in her mind in children’s lunch boxes: Label peels off the pock-marked fruit Orange-yellow tinged with green Mandarin stalk pulls out of the fruit easily Easy to peel and break into segments Great for children’s lunch boxes ( from Mandarin—kids’ fruit by Jane in Words that shine, p. 7) Kate chose to describe the mandarin in front of her on the table: Sun burnt orange skin Cold and mottled Bruised and scarred Yet filled with delectable flesh (Mandarin by Kate in Words that shine, p. 16) Interestingly, Kate went on to write another poem inspired by the mandarin poem, this time about teenagers, sunburnt faces and blackheads.

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Another interesting development was the fact that Mary wrote a mandarin poem that she didn’t like, therefore, in the poetry collection she replaced it with a poem about other fruit, melons. The poem speaks about her grandfather bringing home sweet juicy melons for his grandchildren. Editing is a skill that writers need to become acquainted with early in their work, however, I did minimal editing in class, and certainly did not discuss discarding poems that their authors don’t believe are their best writing. However, participants got so much into the spirit of the poetry writing workshop that editing came naturally to all participants, most likely based on previous experience and personal literary taste. All participants came to the workshops with great interest, applied themselves to the work, enjoyed the time spent there, and rarely felt tired. Workshops were running for two hours with a break after the first hour. In the first hour I presented the kind of poetry to be worked on, offered examples and asked participants to write. After the break participants would finalise their poems and then read them out loud in class. They often commented how much they enjoyed sharing their work and listening to other people’s work. Socialisation just happened naturally as part of the workshop and the friendly, mutually supportive, creative environment.

Workshop 6 I called the final workshop the Writers’ Festival and everyone was enthusiastic about making it a small event for their own enjoyment. Participants dressed up for that day, Alzheimer’s SA offered some soft drinks, coffee, and cake, and everyone read all of their poems produced during the workshop series, including a couple of carers who wanted to share their own poems. It was at that time that participants suggested the poems be collected and published in a volume, to which research assistant Leeston McNab and I happily agreed. The very tangible result of the workshop series at Alzheimer’s SA is the poetry collection Words that shine, which Leeston McNab and I edited and published. Five years on from the workshops, one participant is still publishing poetry; Leeston McNab became a full-time editor; I have published articles about the poetry workshops for people with dementia; also, my interest in the topic has been additionally reinforced by my partner’s mother developing Alzheimer’s and moving into a nursing home. My partner and I are reading all materials we are aware of about this condition that affects a growing percentage of the population in contemporary times, and while a cure is yet to be found, my partner’s mother always smiles and recognises me when I visit and read for her poetry she studied at school, mainly Wordsworth and Yates.

Poetry writing for people with dementia Researchers have looked into the benefits of creativity in general and poetry in particular for people with dementia, but also for people with various other conditions related to dementia and ageing, a wealth of materials thus indicating the topicality of the issue and, unfortunately, its alarmingly widespread nature.

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Bennetts, Holden, and Postlethwaite from the University of Exeter, UK, published an interesting study that they called A Position Paper: Creativity, older people and health. The study is based on the idea of re-evaluating the role of the ageing population in the current context of longer time spent after retirement. What is especially of note is their discussion of health as social capital. It appears that there is an intriguing link between educational engagement and improved health status. But it also seems that these benefits have the capacity to affect neighbourhoods as well as individuals in terms of social capital (Bennetts, Holden and Postlethwaite 2005). The concept of health as social capital is of interest when looking at integration and socialisation of people with conditions that might isolate them and thus limit their independence much sooner than if they were leading a participative life in the family and community. In groups such as the early intervention group targeted by the poetry workshops for the project for people with dementia, maintaining a healthy connection with the social environment through creativity and workshop participation becomes less of a carer-driven and centred activity, and more of a fun involvement of the people with dementia themselves. Hagens, Beaman, and Bouchard Ryan conducted research that resulted in their very informative article, titled Reminiscing, Poetry Writing, and Remembering Boxes: Personhood-Centred Communication with Cognitively Impaired Older Adults. The notion that is of interest for the poetry for people with dementia research is that of personhood-centred communication. The model the authors of this article use, the Communication Enhancement Model of Ageing, “conceptualizes interventions in terms of their emphasis upon the older adult, the caregiver, or the environment, but the driving force of all interventions is that interactions with older adults become increasingly guided by the individual characteristics of each person” (p. 99). “Even for nursing home residents experiencing the communication, memory, and behavioural difficulties of dementia, such empowerment is possible” (Ripich, Wykle and Niles 1995 cited in Hagens, Beaman and Bouchard Ryan 2003, p. 99). What this suggests is that recognising individuality equates to recognising personhood, which is empowering for both carer and the person diagnosed. On researching creativity in later life, Price and Tinker concluded that, In the context of the ageing population, what it means to be “old” is changing. The older population is becoming increasingly diverse, with many retired people remaining active and contributing to society, whilst others suffer from deteriorating health and functional ability . . . Despite alterations in cognitive processing with age which decrease problem-solving ability and information retrieval, it can be argued that the older mind is more adept to imaginative thinking with increased distractibility and disinhibition. Studies in showing creativity across the lifespan even suggest that in later life despite a decline in quantity of work by professional artists, the quality and accreditation of work increases with age. (Price and Tinker 2014, p. 284)

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The poetry workshops I conducted indicated that people with dementia from the early intervention group were able to create valuable poetry at publication standards, despite their previous lack of engagement with poetry over various lengths of time. Their age and the Alzheimer’s diagnose were no impediments in looking at new forms of writing and stimulating topics, which resulted in creating relatable, evocative, and entirely beautiful pieces of writing. It was also interesting to see that carers engaged in poetry writing themselves and offered to read their work and receive feedback as part of a circle, together with all poetry participants. The sense of equality of personhood seemed to have been (re)established for the time of the reading.

Conclusions The number of participants that was reduced to four towards the end of the workshop series might be seen as insufficiently representative of all people with dementia. However, the differences between those diagnosed being fairly significant, the four participants’ experiences need to be taken at face value each; these experiences, as described and discussed by the participants in the feedback interviews, and the outcomes of the workshops (i.e. the participants’ published poems) are able to form the basis for preliminary conclusions and further study. Feedback interviews at the end of the workshop series suggested that all participants felt enriched and empowered by the poetry writing activity. Their mood was generally positive during the workshops and the two-hour format with a 15-minute break in-between proved to be adequate and not at all tiring for the participants, as researchers and staff feared it could be. The project benefited greatly from the support of Alzheimer’s SA staff, whose dedication to their work is truly admirable. Most staff members were very interested in the project and assisted in whichever way they could. Some of the Alzheimer’s SA staff initially had mixed feelings towards researchers and teachers: they were very protective of the participants, and some even interfered with the teaching in the beginning, but everyone realised gradually that we were there in good faith, we wanted to do something useful, and hopefully our work and findings could be transferable to similar organisations and help other people with dementia, carers, their families, and communities. The workshops taught me a lot about a field that I had read about extensively but was quite shy to get involved with, mainly because of respect for the persons diagnosed. I have learned that my respect earned me their respect and I am very grateful to everyone who participated at the workshops and made this work possible. I am dedicating to them a poem I have written inspired by their challenges, tribulations, courage, and perseverance: For people with dementia who write poetry

Who is there behind the blue eyes today, The child, the teenager, the mother, the bride?

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Who is there at the end of a different day, Who is there in the morning, who is there at night? Am I a person, a writer, an ‘other’? A searcher of mornings, admirer of space? You can call me your sister, you can call me your mother, I will be the poem that lights up your face. Ioana Petrescu

Research tips • • • •

Workshops were designed for early intervention groups, and most probably would work best mainly with participants in their early stages of dementia; Two-hour workshops with a 15-minute break in-between seemed to work well and weren’t too tiring for the participants; Instructions for poetry writing were simple but not simplistic; Reinforcement of the success feeling upon writing, and then publication, was valuable to and well received by participants.

Reference Bennetts C, Holden C and Postlethwaite K, A position paper: Creativity, older people and health, International Journal of Health Promotion and Education, 43:4, 125–130, 2005. Hagens C, Beaman A and Bouchard Ryan E, Reminiscing, poetry Writing, and rememberinwg Boxes, in activities, Adaptations and Aging, 27:3–4, 97–112, 2003. Price KA and Tinker AM, Creativity in later life, Maturitas, 78, 281–286, 2014.

SECTION V

End of life

13 DEATH, DYING AND BEREAVEMENT IN OLD AGE Working towards a ‘good death’ for elderly individuals Wylie, Belinda and Smith, Michael

Introduction In the Western world, life expectancy is at an all-time high, with mean life expectancy in many Western countries now exceeding 80 years (World Health Organisation, 2013). Further evidence suggests that the likelihood of living to very old age is set to continue further. Data from the UK predicts that 7.7% of individuals currently aged 80 years will live to reach the age of 100, whereas 23% of current 20-year-olds will live to be centenarians (Evans, 2011). The somewhat obvious consequence of a longer life expectancy is that people are more likely to die at an older age. Current statistics from England reveal that two-thirds of people die over the age of 75, while one in six people are aged over 90 years old at the time of death (Ruth & Verne, 2010). While statistics on the leading causes of death comprise a number of illnesses associated with ageing (e.g. dementia, heart disease; see Table 13.1), it is clear that the causes of death also change as individuals reach older adulthood. This aforementioned increase in life expectancy is largely due to substantial advances in medical treatments. Essentially, modern medicine now has the capacity to ‘stave off ’ death due to illnesses that were once considered incurable. Thus, a common feature of old age is that individuals are living with chronic illness. It is estimated that 40% of adults aged above 65 in the UK have a chronic illness. In many cases, the treatment will enable the individual to live a near-to-normal life. However, disease can result in a protracted dying process, which places considerable burden on both the patient and their informal familial caregiver(s). Consider that two-thirds of individuals who receive a cancer diagnosis survive for at least five years post diagnosis. Whereas in previous generations death was a sudden or imminent feature of illness, individuals are now living with such chronic illnesses

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TABLE 13.1 Leading causes of death in England and Wales (2012) separated by sex (All ages data from Office of National Statistics, 2013).

Males (all ages) Rank 1

Females (all ages)

Cause of death

%

Cause of death

%

Heart disease

15.6%

Dementia

11.5% 10.3%

2

Lung cancer

7.0%

Heart disease

3

Emphysema/bronchitis

6.0%

Stroke

8.4%

4

Stroke

5.9%

Flu/pneumonia

5.8%

5

Dementia

5.8%

Emphysema/bronchitis

5.5%

6

Flu/pneumonia

4.6%

Lung cancer

5.2%

7

Prostate cancer

4.0%

Breast cancer

4.0%

8

Bowel cancer

3.3%

Bowel cancer

2.5%

9

Lymphoid cancer

2.6%

Urinary disease

2.1%

Throat cancer

1.9%

Heart failure

2.0%

10

for a substantial period, often accompanied by other age-related health complications, such as cognitive decline. Thus, it is essential that improving end of life care for individuals living with chronic and terminal illnesses in later life is a very high priority on both research and policy agendas. In keeping with the theme of this volume on understanding ‘successful’ ageing, this chapter will focus on the concept of ‘a good death’ in later life, and will address the question of how enhanced end of life care can promote a good death. The quote “Life is a moderately good play with a badly written third act” rings true here—the fact that people are living longer, often with chronic health complaints, results in a more protracted dying process. In order to promote a ‘good death’, it is critical that end of life care is optimised.

A ‘good death’ So, what is meant by the notion of ‘a good death’? There is limited consensus among clinicians, policy makers and researchers with respect to what is meant by this concept (Kehl, 2006). The concept of a good death initially evolved as a synonym for euthanasia, but during the 1980s the basis for what makes a death good began to be more widely discussed (Kehl, 2006). Perhaps the most widely accepted definition of a good death is provided by the Institute of Medicine: “A decent or good death is one that is: free from avoidable distress and suffering for patients, families, and caregivers; in general accord with patients’ and families’ wishes; and reasonably consistent with clinical, cultural, and ethical standards” (Field & Cassel, 1997). In her text ‘Representations of Death: A Social Psychological Perspective’, Bradbury

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(1999) presents an anthropological account of an ‘idealised’ death, comprising such features as i) dying in one’s own home, ii) having one’s close relatives present and having their love and respect, iii) an alert mind, iv) a peaceful and dignified passing and v) limited discomfort. However, these conditions are infrequently met in the case of death in old age. A greater proportion of older adults die in a nursing/ care home, or in a hospital, than in their own home. This is potentially problematic, given that quality of care is rated as significantly lower for people who die in a hospital, compared to other settings (Office of National Statistics, 2014). Many older individuals are widowed and live alone (and are more likely to be women given the greater life expectancy of females), thus lack the care and support of their spouse at the time of death. Additionally, at the time of death, many older adults are likely to be experiencing age-related cognitive decline, with dementia among the leading causes of death in older adults. Finally, older adults are likely to be experiencing complications from chronic illness at the time of death. Thus, many of the conditions of a good death as suggested by the anthropological account are violated during the protracted dying process that is a feature of death in older adults in the 21st century. Bradbury (1999) also discusses the notion of a good death according to a contemporary, Western social psychological perspective. This theoretical model purports that a good death can be categorised into three main types: i) sacred, ii) medicalised and iii) natural. The notion of a sacred good death is one that is typically steeped in religion, with death being the vehicle by which rebirth occurs. Death is thus controlled via one’s faith. A sacred good death therefore aids acceptance not only for the dying individual, but also for the individual’s loved ones. The notion of the sacred good death evokes traditional mental images of dying, with the dying individual being comfortable and with close family present, not unlike the anthropological account discussed above. A sacred good death can be seen as a social event, transcending the time of death itself, during which important rituals follow that enable the deceased’s social network to mourn and grieve the loss of the individual who has died. A medicalised good death is one that is accompanied by quality medical care. This may be delivered in the form of pain relief, so that the dying individual is as comfortable as possible. However, the individual will sometimes be in a medically induced unconscious state, thus violating the aforementioned anthropological principle that the individual should be in a sound state of mind. In this case, control over one’s death is achieved by quality clinical care. Finally, a natural good death is one in which the dying individual has autonomy and control over their expected death. The individual is actively involved in the decisions relating to their care, and may elect for a less medicalised death. This notion of autonomy over the decisions relating to one’s own death is one that has largely shaped current conceptualisations of a ‘good death’. It is suggested that while the more ancient concept of a sacred death has largely been displaced by a medicalised account, and that we are rapidly moving towards the notion of a natural good death, that a three part typology is still a useful conceptualisation of a good death.

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The notion of a ‘good death’ was one that was discussed in a British Medical Journal editorial in 2000 (Smith, 2000), with the tagline “An important aim for health services and us all”. The editorial states that while the relatively few people who die in the care of palliative care teams may experience a good death, the majority die in hospitals or nursing homes, and it is suggested that the dying experience of these individuals may not be considered ‘good’ (Office of National Statistics, 2014). This implies that few individuals are afforded the opportunity to experience a good death, and it is likely that the situation has not changed substantially since the time that this editorial was published. Smith (2000) presents 12 principles of a good death (see Box 13.1) from a 1999 report (The Age Health and Care Study Group, 1999). He suggests that not only should these principles be incorporated into the plans of dying individuals, but that health services should also aim to adhere to these principles in providing care to the dying. It is worthy of note that the majority of these principles are aligned with both the anthropological and social psychological perspectives on a good death, which were outlined by Bradbury (1999). Smith (2000) additionally seems to suggest that death has become too much of a taboo topic, and that talking more openly about death and introducing death education into schools may facilitate the promotion of a good death. Munn and Zimmerman (2006) interviewed family members of individuals who died following long-term end of life care, to determine the most important aspects of end of life care from the perspective of the family members of the deceased individuals. This study determined that among the most important facets of quality end of life care provision was care delivery, including such aspects as staff training, staff attitudes and the quality of the facility, with these aspects being considered more important than such issues as the preferences of the dying individual. The quality of

BOX 13.1

PRINCIPLES OF A GOOD DEATH

To know when death is coming, and to understand what can be expected To be able to retain control of what happens To be afforded dignity and privacy To have control over pain relief and other symptom control To have choice and control over where death occurs (at home or elsewhere) To have access to information and expertise of whatever kind is necessary To have access to any spiritual or emotional support required To have access to hospice care in any location, not only in hospital To have control over who is present and who shares the end To be able to issue advance directives that ensure wishes are respected To have time to say goodbye, and control over other aspects of timing To be able to leave when it is time to go, and not to have life prolonged pointlessly

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care received was also a major predictor of whether family members believed that a good death had been achieved in a quantitative study by Patrick and colleagues (2003), with the degree to which the treatment was explained being significantly related to the quality of the death. Similarly to the qualitative findings of Munn and Zimmerman (2006), this study also observed that whether the patient was listened to carefully and respectfully was a predictor of a good death, although this statistical trend failed to reach significance. Thus the quality of end of life care received appears to be a particularly strong predictor of a good death, at least from the perspective of family members of the deceased. End of life care programmes must therefore emphasise the importance of the quality of care, including staff attitudes, empathy, training and adequacy as well as the quality of the care facility. In England, the Liverpool Care Pathway (LPC) for the dying patient was developed during the 1990s as an attempt to ensure that good care is consistently provided to individuals in the final days and hours of life. The aim of the pathway was to provide comfort and maintain the dignity of the dying individual, in addition to provision of appropriate support to the dying individual’s family. An objective of the pathway was to provide structured guidance to medical professionals with limited palliative care expertise on such issues as the emotional, social and spiritual needs of dying individuals and their families. However, the LCP has been subjected to criticism on the basis that it can be difficult to determine when death is imminent, so some individuals on the pathway may have lived longer. It has been further suggested that the LCP can indeed unnecessarily medicalise the dying experience with the aim of providing comfort to the dying individual, when in fact a more natural death might convey lower levels of pain and distress, particularly in elderly individuals (Millard et al., 2012). In response to criticisms such as this, the Leadership Alliance for the Care of Dying People (LACDP), a consortium of 21 stakeholder organisations in England, recommended that the LCP be phased out by July 2014. Instead, the LACDP proposes five patient-centred priorities for the care of a dying individual that provide a greater focus than the LCP on individualised care and the autonomy of the dying person (Leadership Alliance for the Care of Dying People, 2014). These priorities reflect many principles of a ‘good death’. Each of the priorities is listed in Box 13.2.

BOX 13.2

PRIORITIES FOR THE CARE OF THE DYING PERSON (LACDP, 2014)

The Priorities for Care are that, when it is thought that a person may die within the next few days or hours. 1

This possibility is recognised and communicated clearly, decisions made and actions taken in accordance with the person’s needs and wishes, and these are regularly reviewed and decisions revised accordingly.

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Sensitive communication takes place between staff and the dying person, and those identified as important to them. The dying person, and those identified as important to them, are involved in decisions about treatment and care to the extent that the dying person wants. The needs of families and others identified as important to the dying person are actively explored, respected and met as far as possible. An individual plan of care, which includes food and drink, symptom control and psychological, social and spiritual support, is agreed, co-ordinated and delivered with compassion.

Differences between younger and older adults: implications for research and policy It is important to consider how younger and older adults may differ with respect to what they would consider to be a ‘good’ death. Gott and colleagues (2008) point out that palliative care, at least in the UK, has been developed predominantly from the perspective of providing end of life care to middle aged and ‘younger’ elderly individuals with cancer, and that this ‘one size fits all’ approach may not be optimal when considering the care of older elderly individuals with illnesses other than cancer. Gott and colleagues (2008) suggest that older elderly individuals’ perspective of a good death differs to that which is reflected by current palliative care practice. For example, in their sample of older adults (median age = 77) with advanced heart failure and poor prognosis, a key theme that emerged was that individuals had a preference for a sudden death rather than an open awareness of death. In addition, the elderly participants in this study expressed very limited desire to retain control over their death. This finding is commensurate with that of a Chinese study in which old adults (> 60 years) rated autonomy (including the right to retain control over the dying experience) as less important than younger individuals (< 40 years; Leung et al., 2009). The findings of this study demonstrate that the views of elderly individuals with respect to a good death may deviate from several current palliative care principles (e.g. Box 13.1). This outlines an important role for researchers, to better understand older elderly individuals’ conceptualisation of a good death, and to develop and define best practice with respect to the palliative care of this group. An aim must be to inform a policy shift that will enable more tailored palliative care for different groups, given the clear differences that have emerged between current palliative care practice and the views of the older adults in the study of Gott and colleagues (2008). Differences in achievement of a good death between older (> 70 years) and younger individuals have been further investigated by Morita and colleagues (2014). The authors of this study found that, relative to the younger participants, the older individuals reported feeling less independent, less hope and pleasure and a poorer

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relationship with the family, resulting in increased loneliness. Again, these differences between the younger and older individuals highlight areas where the principles of a good death may be violated, and may impact upon the death experience of elderly individuals. The implications of these findings is that tailored palliative care for older adults should work to increase independence and autonomy, promote daily activities to improve pleasure and purpose in life and to facilitate social interaction. A further issue that may differentiate older from younger palliative care patients is that of ‘fear of death’. A Taiwanese study found that older adults (> 65 years) reported greater ‘fear of death’ two days prior to death, and that ‘fear of death’ was inversely related to a good death experience (Tsai et al., 2005). This suggests that healthcare workers in palliative care settings should actively work to decrease the ‘fear of death’ in elderly patients in order to promote the likelihood of a good death. What is clear is that the conceptualisation of a good death in elderly individuals is less well understood in older individuals as it is in middle aged and ‘younger’ elderly individuals. More work is needed by researchers to clearly define the notion of a good death in elderly individuals, and to develop interventions and tailored palliative care programmes that will increase the likelihood of achieving a good death in elderly individuals.

Patient versus professional perspectives on a good death As suggested by Gott and colleagues (2008) and discussed above, it is likely that older adults’ views on a good death are not entirely commensurate with the more widely accepted principles of a good death that inform current palliative care practice and policy. In addition, there is further evidence to suggest that researchers’ and healthcare workers’ conceptualisations of a good death do not directly correspond with those of dying patients. For example, with respect to the more general notion of ‘successful ageing’ (the topic of this volume), one study observed that elderly individuals reported a more multifaceted conceptualisation of successful ageing than the definitions typically presented in the published literature, suggesting a lack of convergence between older adults and researchers with respect to a conceptualisation of successful ageing (Phelan et al., 2004). Further, Steinhauser et al. (2000) compared seriously ill patients, recently bereaved family, physicians and other healthcare workers (e.g. nurses, social workers) with respect to their agreement with the importance of several attributes relating to end of life care. There were many attributes (e.g. pain management, preparation for end-of-life, sense of completion in life, relationship between patients and healthcare professionals) that were considered equally important across each of these groups. However there were also a number of attributes that differed with respect to their level of importance between the groups. For example, patients and their families placed a greater level of importance upon being mentally aware, while physicians placed more importance on sacrificing mental awareness in favour of pain control. Patients and bereaved families also rated spirituality as being a more important factor in the dying experience than

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physicians. However, what emerged from this study is that even within each group, there was vast dispersion with respect to the relative level of importance of some attributes. For example, there was considerable disagreement within the patient group with respect to the importance of personal control over the time and place of death, which are both widely acceptable principles of a good death. The lack of concordance both between and within groups with respect to the most important attributes of end-of-life care led the authors to conclude that “. . . there is no one definition of a good death; quality end-of-life care is a dynamic process that is negotiated and renegotiated among patients, families, and health care professionals, a process moderated by individual values, knowledge, and preferences for care” (Steinhauser et al., 2000). The observation that patient views on dying are heterogeneous has also been reported elsewhere. Research by Vig and colleagues (Vig et al., 2002; Vig & Pearlman, 2004) reported that the views of terminally ill men with cancer and heart disease differed with respect to their conceptualisation of a good death, bad death and preferred dying experiences. Further, this study also reported a lack of complete concordance between patients’ views of a good death, and those of healthcare workers, or patients’ with other terminal conditions. On the basis of the evidence presented in this section, it appears that there is only limited concordance not only between patients and healthcare professionals, but also among dying individuals, with respect to the notion of a good death. This is an issue that complicates matters for researchers, in that a universal definition of a good death both within and between key stakeholder groups is something that is not likely to be easy to achieve. As an alternative, it is likely that conceptualisations of a good death, as well as interventions and palliative care programmes aimed at providing a good death need to be malleable and flexible, so that they can be individually tailored to incorporate the views and wishes of not only the dying individual, but all stakeholders involved in their care.

Impact of a good death on the surviving spouse One of the major stakeholders in the death of an elderly individual is the surviving spouse. The spouse may have been acting as an informal caregiver for a substantial period leading up to the death, which itself may be associated with substantial physical and psychological health burden (Pinquart & Sorensen, 2003). However, while a good death may enhance the dying experience for the patient themselves, it is of interest to consider whether a good death can facilitate the bereavement process for the surviving spouse. Carr (2003) undertook a comprehensive analysis of prospective data, and determined that a good death can positively impact upon the wellbeing of the surviving spouse. For example, the perceived quality of the dying patient’s medical care was inversely related to the surviving spouse’s psychological distress. Further, positive relationships between the dying individual and their spouse during the final days of the dying patient’s life decrease the anger that the spouse feels in relation to the death. Additionally, painful deaths are associated

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with more yearning, anxiety and intrusive thoughts experienced by the bereaved spouse. However, it is of interest to note that three principles that are typically associated with a good death, namely, i) having led a full life, ii) acceptance of death and iii) not being a burden to surviving family do not predict spousal psychological distress after a six month follow-up period. This finding suggests that certain attributes of a good death from the perspective of the dying individual may not necessarily directly facilitate the bereavement process for the surviving spouse. This has implications for the development of bereavement programmes. While it is important for such programmes to focus on those aspects of a good death that do facilitate the bereavement process, it is important to consider that not all facets of a good death will necessarily translate to enhanced psychological wellbeing for the bereaved spouse. Carr (2003) makes reference to two different ‘types’ of good death from the perspective of the bereaved spouse. Individuals who die suddenly are likely to experience relatively less pain, which can be a source of comfort for the bereaved spouse. However, sudden deaths, unlike death from chronic illnesses, do not enable the couple to spend time together discussing and making sense of the dying process. This may prevent the couple from experiencing a positive relationship during the final days before the death, leading to greater anger on the part of the surviving spouse, as suggested above. Carr (2003) therefore argues for tailored bereavement programs for spouses of elderly individuals who have i) died suddenly, and ii) died as a result of chronic/terminal illnesses (which are also likely to be accompanied by a degree of informal caregiver burden). A further issue surrounding spouses is that of spousal decision making around the time of death. Often, when terminally ill elderly individuals lack the mental awareness to make informed decisions surrounding their end of life care, their spouses will make decisions pertaining to their treatment in collaboration with healthcare providers. These decisions will ultimately play a considerable role in determining the extent to which an individual will experience a good death. However, this brings into question the extent to which spouses are aware of their dying partner’s wishes with respect to end of life care. Moorman and colleagues (2009) investigated this question directly, by asking married couples aged in their 60s about their preferences, and those of their spouse, with respect to end of life care. The authors of this study observed a lack of concordance between individuals’ own preferences and their partners’ reports of their preferences. Most notably, it was reported that the source of this discrepancy could be attributed to spouses projecting their own preferences with respect to end of life care onto their partner. Additionally, inaccuracies in reporting spousal preferences for end of life care were greater for end of life scenarios relating to physical pain than for cognitive impairment, suggesting that physical pain at the end of life may be an issue that is discussed to a lesser degree with one’s spouse as they enter later adulthood. An avenue for future work will be to determine how to address this issue in order to decrease the likelihood that spousal choices with respect to end of life care which are disparate from those of the dying individual will prevent a good death from

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occurring. A further potential future research direction relates to the impact of spousal death on individuals from different cultural backgrounds. Carr (2004) reported differences in psychological outcomes following spousal death between Black and White individuals from Detroit. The following section will consider further cross-cultural differences in relation to the conceptualisation of a good death, and the importance of providing culturally sensitive end of life care in order to increase the likelihood of a good death in individuals from minority backgrounds.

Cross-cultural perspectives on a good death A further consideration for researchers aiming to better understand and promote a good death in elderly individuals is that perspectives on the specific facets that comprise a good death are likely to differ cross-culturally. This has implications for treatment and palliative care provision in individuals from different cultures, as such care may need to be tailored to take into account any preferences on end of life care and dying that may be influenced by differences in cultural preferences. For example, in a study comparing younger and older palliative care patients and their experiences of a good death in Taiwan, elderly individuals’ were found to be less likely to experience a good death due to less awareness of their condition, lower levels of autonomy and less decision-making participation (Cheng et  al., 2008). It was suggested that this may stem from reduced ‘truth-telling’ in some Asian cultures, whereby dying individuals may not be made fully aware of their condition or prognosis. The notion that family members disclose only limited details of the decision making surrounding end of life care in some Asian cultures was echoed by the findings of a systematic review of Japanese studies by Hattori and colleagues (2006). However Hattori and colleagues (2006) suggest that a cultural shift towards more self-oriented health decision making currently associated more with Western cultures is underway in Japan, and that this may lead to a more patient-focussed role in end of life care decision making as well as greater patient awareness of dying. This view is concordant with a Chinese study by Leung and colleagues (2009), which reported lower perceived autonomy during the dying process in older individuals relative to younger individuals. This could be evidence that the purported cultural shift towards more self-oriented health decision making is also occurring in Chinese cultures, or could be suggestive that in Chinese culture it is expected that older individuals will have lower independence over health decision making, which extends to end of life care. In saying that, it is suggested that in some Japanese cultures, patients don’t particularly want to be overtly aware of their impending death (Miyashita et al., 2007; Sanjo et al., 2007). In such cases, healthcare providers need to be sensitive to the wishes of an individual to be unaware of the seriousness of their condition and impending death, in order to promote a good death in this group. In addition to cross-cultural differences in perceived facets that constitute a good death, some studies have reported that access to optimal end of life care is

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not as widely available to some minority cultural groups. For example, Enguidanos and colleagues (2005) reported that some cultural minority groups may be relatively less likely to receive end of life care in a hospice setting. This may be an issue given that provision of end of life hospice care is considered to increase the likelihood of a good death. Although this study was conducted in the USA, where the healthcare system differs from that of many countries such as the UK where publically funded systems are in place, limited access to optimal end of life care provision for cultural minority groups is an issue that is clearly not confined solely to the USA. Despite a number of cross-cultural similarities with respect to the core principles of a good death (e.g. Hattori et al., 2006; Miyashita et al., 2007), it is clear that there are some facets of a good death that are not universal across cultures. It is therefore important that researchers and healthcare providers consider such cross-cultural differences in the development of palliative and end of life care programmes. For example, the UK Department of Health has clearly considered the importance of cross-cultural differences in end of life care preferences by highlighting in their End of Life Care Strategy that cultural sensitivity is paramount in the provision of quality end of life care (Department of Health, 2008). The Strategy makes reference to a successful model employed in a hospice situated in an East London district that is characterised by substantial cultural diversity. This mosque works closely with a local community development organisation that has worked to establish a dialogue between the hospice and local ethnic communities. This has enabled hospice staff to develop services that are commensurate with the needs of the diverse ethnic groups that it serves, and outreach activities have ensured that minority groups are aware of the services provided by the hospice that may be of benefit to them. Such examples of good practice demonstrate that providing quality, tailored end of life care to elderly individuals from vast cultural backgrounds is possible to achieve in practice. Further, formal research is needed in order to better ascertain cross-cultural differences in end of life care preferences, to enable the development of culturally sensitive care programmes that aim to facilitate a good death for individuals from minority backgrounds.

Conclusions Life expectancy is increasing every year in many Western societies, with many older adults living with chronic illnesses. Due to modern advances in medical technology, the end of life period can often be extended. Individuals now typically live longer with chronic illnesses than was the case in previous centuries, leading to a more protracted dying process. Truman Capote’s famous quote “Life is a moderately good play with a badly written third act” implies that the end of life, by its very nature, should be a fairly dismal time in an individual’s life. However that needn’t be the case. A massive challenge for researchers and practitioners is to better understand the universal and individualised facets that comprise a good death, and to develop end of life care programmes that facilitate a good death. LACDP (2014) priorities for

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the care of the dying person are working towards this agenda, but work is needed to evaluate the outcomes of this approach to ensure that end of life care optimally promotes a good death. Challenges include tailoring these programmes to fulfil vast inter-individual differences with respect to end of life care preferences, to ensure that not only the patient but all stakeholders, including spouses and family members of the deceased recognise the death as ‘good’. Further challenges and practical research tips are presented in the following text. Quality, cross-disciplinary research is needed in this area, in order to better inform policy and practice, and to increase the likelihood of achieving a good death for older adults with chronic illnesses.

Practical research tips 1

2

3

The notion of a good death in elderly individuals needs to be better defined, and needs to be high on the research agenda in this area. Only when a better conceptualisation of a good death in older adults is developed can researchers work towards developing tailored interventions and palliative care programmes to increase the likelihood of achieving a good death in this group. It is also important to note that principles that constitute a good death in younger individuals may be different from those of older adults and may be different again for very elderly individuals. These differences must be recognised by researchers in order to inform policy decisions and best-practice with respect to end of life care for older adults. The LACDP (2014) priorities are working towards this agenda, but future evaluation is needed to ensure that these priorities remain fit for purpose in terms of optimising end of life care. The views of the patient and their family with respect to a good death may differ from those of health professionals and policy makers. An important role for researchers working in this area is to ensure that these differences are recognised in order to promote a good death. Additionally, it is important to recognise that there are likely to be inter-individual differences in dying preferences, to the extent that end of life care programmes that are easily and cost-effectively tailored in accordance with the dying individual’s end of life preferences will increase the likelihood of achieving a good death. Cross-cultural differences in preferences relating to end of life care, as well as the relatively limited access to optimal end of life care in elderly individuals from minority ethnic/cultural groups must be recognised and addressed. These cross-cultural differences pose a challenge for researchers, but are issues that, if tackled, could drastically increase the likelihood of a good death for people from minority backgrounds.

References The Age Health and Care Study Group. (1999). The future of health and care of older people: The best is yet to come. London: Age Concern. Bradbury, M. (1999). Representations of death: A social psychological perspective. New York: Routledge.

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Carr, D. (2003). A “good death” for whom? Quality of spouse’s death and psychological distress among older widowed persons. J Health Soc Behav, 44, 215–232. Carr, D. S. (2004). Black/White differences in psychological adjustment to spousal loss among older adults. Research on Aging, 26, 591–622. Cheng, S. Y., Hu, W. Y., Liu, W. J., Yao, C. A., Chen, C. Y., & Chiu, T. Y. (2008). Good death study of elderly patients with terminal cancer in Taiwan. Palliat Med, 22, 626–632. Department of Health (2008). End of life care strategy: Promoting high quality care for all adults at the end of life. London. Enguidanos, S., Yip, J., & Wilber, K. (2005). Ethnic variation in site of death of older adults dually eligible for Medicaid and Medicare. J Am Geriatr Soc, 53, 1411–1416. Evans, J. (2011). Differences in life expectancy between those aged 20, 50 and 80 – at 2011 and at birth. Department for Work and Pensions, UK. Field, M. J., & Cassel, C. K. (1997). Approaching death: Improving care at the end of life. Washington, DC: National Academy Press. Gott, M., Small, N., Barnes, S., Payne, S., & Seamark, D. (2008). Older people’s views of a good death in heart failure: Implications for palliative care provision. Soc Sci Med, 67, 1113–1121. Hattori, K., McCubbin, M. A., & Ishida, D. N. (2006). Concept analysis of good death in the Japanese community. J Nurs Scholarsh, 38, 165–170. Kehl, K. A. (2006). Moving toward peace: An analysis of the concept of a good death. Am J Hosp Palliat Care, 23, 277–286. Leadership Alliance for the Care of Dying People (2014). One chance to get it right: Improving people’s experience of care in the last few days and hours of life. NHS, UK. Leung, K. K., Liu, W. J., Cheng, S. Y., Chiu, T. Y., & Chen, C. Y. (2009). What do laypersons consider as a good death. Support Care Cancer, 17, 691–699. Millard, P., Cole, A., Bearcroft, R., Craig, G., Hill, D., et al. (2012, 8 July). Deadly one-way street. The Daily Telegraph. (Letters). Miyashita, M., Sanjo, M., Morita, T., Hirai, K., & Uchitomi, Y. (2007). Good death in cancer care: A nationwide quantitative study. Ann Oncol, 18, 1090–1097. Moorman, S. M., Hauser, R. M., & Carr, D. (2009). Do older adults know their spouses’ endof-life treatment preferences? Res Aging, 31, 463–491. Morita, T., Kuriya, M., Miyashita, M., Sato, K., Eguchi, K., & Akechi, T. (2014). Symptom burden and achievement of good death of elderly cancer patients. J Palliat Med, 17, 887–893. Munn, J. C., & Zimmerman, S. (2006). A good death for residents of long-term care: Family members speak. J Soc Work End Life Palliat Care, 2, 45–59. Office of National Statistics (2013). What are the top causes of death by age and gender?, Retrieved from http://www.ons.gov.uk/ons/rel/vsob1/mortality-statistics—deathsregistered-in-england-and-wales—series-dr-/2012/sty-causes-of-death.html Office of National Statistics (2014). National Survey of Bereaved People (VOICES), Retrieved 2013, from http://www.ons.gov.uk/ons/dcp171778_370472.pdf Patrick, D. L., Curtis, J. R., Engelberg, R. A., Nielsen, E., & McCown, E. (2003). Measuring and improving the quality of dying and death. Ann Intern Med, 139, 410–415. Phelan, E. A., Anderson, L. A., LaCroix, A. Z., & Larson, E. B. (2004). Older adults’ views of “successful aging”: How do they compare with researchers’ definitions? J Am Geriatr Soc, 52, 211–216. Pinquart, M., & Sorensen, S. (2003). Differences between caregivers and noncaregivers in psychological health and physical health: A meta-analysis. Psychol Aging, 18, 250–267. Ruth, K., & Verne, J. (2010). Deaths in older adults in England. Bristol: National End of Life Care Intelligence Network.

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Sanjo, M., Miyashita, M., Morita, T., Hirai, K., Kawa, M., Akechi, T., et al. (2007). Preferences regarding end-of-life cancer care and associations with good-death concepts: A population-based survey in Japan. Ann Oncol, 18, 1539–1547. Smith, R. (2000). A good death: An important aim for health services and for us all. BMJ, 320, 129–130. Steinhauser, K. E., Christakis, N. A., Clipp, E. C., McNeilly, M., McIntyre, L., & Tulsky, J. A. (2000). Factors considered important at the end of life by patients, family, physicians, and other care providers. JAMA, 284, 2476–2482. Tsai, J. S., Wu, C. H., Chiu, T. Y., Hu, W. Y., & Chen, C. Y. (2005). Fear of death and good death among the young and elderly with terminal cancers in Taiwan. J Pain Symptom Manage, 29, 344–351. Vig, E. K., Davenport, N. A., & Pearlman, R. A. (2002). Good deaths, bad deaths, and preferences for the end of life: A qualitative study of geriatric outpatients. J Am Geriatr Soc, 50, 1541–1548. Vig, E. K., & Pearlman, R. A. (2004). Good and bad dying from the perspective of terminally ill men. Arch Intern Med, 164, 977–981. World Health Organisation. (2013). Retrieved 4 July 2014, from http://apps.who.int/gho/ data/node.main.688?lang=en

INDEX

adrenopause 62–3, 70 agitated behaviours 214–16, 218, 220–2 allele 51, 181–8, 193–4, 200–1 Alzheimer’s disease 43, 46, 51, 144, 164, 180, 187, 189, 191, 193–201, 208, 210, 212, 215, 219–21; biology and genetics 163, 180–1, 183, 185; glucose 160; music 209, 211, 214 amyloid plaques 163–4, 181, 183–4, 190 anger 242–3 animal models 48–9, 183, 191 aphasia 209, 219 bereavement 66–7, 70, 235, 237, 239, 241–3, 245 β-amyloid levels 191 biomarkers 50, 54, 65, 180, 183, 186 blood pressure 19, 60, 164–5, 207 BMI 170, 188–9, 191 brain atrophy 145, 168 brain-derived neurotrophic factor (BDNF) 24, 28 brain imaging 52–3, 150, 152, 168 brain injury 183–5, 187, 190 brain reserve 186–7 brain structure 28, 48, 142, 150–1, 164, 167–8, 170–1 brain training 17 California Verbal Learning Test-II 22 cancer 46, 60, 240, 242 capacity, cognitive 186, 210 careers 95, 98, 100, 119–20, 125

caregivers 63–5, 68, 210, 214–15, 218, 224–5, 228–30, 236 caregiving stress 64–5 catecholamines 61–2 choir 212–13 cholesterol 47, 170, 191, 193, 196, 199 cholinesterase inhibitors 44, 58 chromosomes 65, 181 chronic stress 63–5, 67, 69–71, 73–5 chronic traumatic encephalopathy (CTE) 184 clinicians 30, 36, 51, 140–1, 149, 153, 186, 236 cognition 17–25, 27, 29, 31–3, 43–52, 54, 103, 140, 142–5, 151, 159–71, 187–8, 190–1, 209, 211; deficits 43, 47–8, 160–8, 170, 172, 181, 186, 189, 210–11, 243; social 145, 148 cognitive, exercise 17–19, 21, 23, 25–31, 33, 218 community 80, 82, 88, 113–14, 220, 224–5, 227, 229–30 compensation 100, 112, 143, 145, 154 conflicts 33, 75, 86, 102–3, 105 context 29, 63, 87, 104, 106, 150, 153, 186, 190, 206–7, 229 continua model 84, 88–9, 94 corpus callosum 144, 209, 221 cortex 23, 154–5, 184 cortisol 61–3, 66, 70, 75–6, 166 creativity 228–9, 231 cross-cultural differences 132–3, 244–6 CSF 183–4 cytokines 62–4

250

Index

death 46, 86, 235–47; bad 242; medicalised 237; natural 239; painful 242 death acceptance 86 dementia 22–3, 43–5, 47–8, 50, 53, 159–60, 163–4, 181, 187–9, 205–11, 213–16, 218–19, 228–9, 231, 235; caregivers 63–4; semantic 211 depression 25, 47, 69–70, 83–5, 87–8, 94, 172, 212 design 18, 25, 31–3, 46, 49–50, 103–4, 110–11, 130, 145, 150, 152, 171, 188; exercise measures 32–3; experience sampling 102–3, 105; parametric 32–3 diabetes 159–63, 165, 167, 169, 171–3; cognition 162, 164, 166, 168, 172 diet 43, 45–6, 50, 54, 187, 189–93; β-amyloid levels 191; dairy products 46–7, 187; fatty acids 7, 44, 46–9, 187, 190–1; fish 46–7, 49, 187; fruit 46, 227–8; Mediterranean diet 44–6, 53, 187, 189–91 dorsolateral tasks 141–2 DRM (Day Reconstruction Method) 103–5 dual continua model 79–81, 83–5, 87, 89 early retirement 123, 127, 130 EEG 52, 169–70, 172 emotions 82, 91, 99, 104, 108, 141–2, 148, 205, 207–8, 212, 217, 219, 224–6 employment 120, 124–7 EPA 46–7, 49 epigenetics 50–1 ERM (Event Reconstruction Method) 103–6 ERPs 169–71 executive functions 43, 140–1, 145–6, 161, 170 exercise 20–1, 24, 85 fMRI 23, 53, 152, 165, 169, 171–2 frontal lobes 139–53, 189 frontotemporal dementia 208, 217, 221 gender differences 183, 188 genetics 50–2, 180–2, 185 glucocorticoids 61, 63 glucoregulation 159–66, 168, 170–2 gray matter density 151 head injury 180, 182–7, 189–92 healing, wound 63 healthcare professionals 241–5 heart disease, coronary 24, 166–7 hippocampus 53, 165–6, 168–70, 172 hospital 237–8

HPA axis 61–2, 166, 172 hypertension 161, 164–5, 172 hypoglycaemia 162–3, 170 idealised death 237 immune system 60–2, 64–71; antibodies 61–2, 64–9, 71 interventions 21, 24, 26, 32–3, 43, 46, 52, 54, 85–9, 106–11, 162, 166, 190, 192, 241–2; cognitive-behavioural 107, 109; dietary 45, 180; life review 87–8; musical 217–19; nutritional 49–51, 53; positive psychology 85 job resources 96–8, 101, 105, 108, 111 learning 22, 28, 30, 53, 97, 106–9, 189–90, 213 life care programmes 239, 245–6 life expectancy 235, 237, 245 loneliness 67 macrovascular disease 166–7 magnetic resonance imaging see MRI marriage 68, 75–7, 126 MCI see mild cognitive impairment medications 52, 162–4 meditation 26 memory 30–1, 53, 86, 88, 102–3, 106, 144, 146, 159–69, 171–3, 205, 210–11, 223, 226, 229; autobiographical 103, 210–11; declarative 166; episodic 21–2, 43, 102, 104, 130, 144, 160–1, 170–1, 180, 211; negative 86, 88; positive 88; prospective 31, 146; verbal 160–1, 163; visual 160–1; working memory (WM) 21–2, 29, 103, 106, 162, 166 memory cells 61–2 mental illness 63, 79–80, 82–9 mild cognitive impairment (MCI) 28, 43–4, 48, 51, 144–5, 172, 184, 187 MMSE (Mini Mental State examination) 48, 164–5, 167, 210 MRI (magnetic resonance imaging) 23, 52, 143, 150, 168–9, 181 multilevel modeling 128–9, 132 multitasking 145–9 music 205–19, 222; listening 206, 210, 216, 218; memories 205, 209–11, 220; therapist 205–9, 211–19 musicians, professional 28, 36, 208–9 neurofibrillary tangles 23, 163, 181, 184 neuroimaging 23, 37, 52, 54, 139, 142–3, 150, 154, 168–70, 172, 191

Index

neutrophils 61–3, 66 nursing homes 87–8, 211, 214–15, 217–18, 228, 238 nutrition 43–5, 47, 49–54 obesity 46, 164, 188–9, 191 Omega-3, 43–9, 51, 54, 190–1 organizational-level factors 124–6 palliative care 240–1, 244 parents 123, 126, 135 pensions 119, 133 PET (positron emission tomography) 23, 53, 181, 197 physical activity 17–21, 24–30, 32, 71, 188–91, 217–18 poetry 223–31 positive mental health 80–1, 83–5, 87, 89 RCTs (Randomised Controlled trials) 46, 48–50, 53–4, 183 reconstruction methods 98, 102–3, 105–6 reminiscence 80, 85–7, 89 resources 68, 70, 95–9, 101, 106, 111, 124 retinopathy 166–7, 170 retirement 100–1, 118–21, 123–33, 212, 229 risk factors 50, 182, 190–1

251

self-efficacy 63, 106–7, 109 single-photon emission computerised tomography (SPECT) 53 sleep 24, 28, 71, 216–17 smoking 71 social interaction 17, 31, 45, 67–8, 70–1, 82, 85, 97, 105, 120, 148, 208, 211–12, 228–9, 241; network size 67–8 social well-being 82–3, 85, 87–9 spouses 242–3 stress 60–3, 65–71, 113; hormones 62, 69–70; perceived 65–6; response 24, 60 stroke 23, 166–7, 183, 212, 214 tau 44, 180–1, 183, 186, 189, 191 telomere length 65 traumatic brain injury 182–5, 190, 192 vaccination 62, 64, 66–7, 71 validity 145, 148–9, 152 vascular dementia 208 vitamins 46 Wisconsin Card Sorting Test 140–2 workers age 96, 98 work motivation 98–100, 111 workplace 95–9, 101, 103, 105, 107–11