The ENGAGE study: Integrating neuroimaging, virtual reality and smartphone sensing to understand self-regulation for managing depression and obesity in a precision medicine model
Precision medicine models for personalizing achieving sustained behavior change are largely outside of current clinical practice. Yet, changing self-regulatory behaviors is fundamental to the self-management of complex lifestyle-related chronic conditions such as depression and obesity - two top con...
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| Published in | Behaviour research and therapy Vol. 101; pp. 58 - 70 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Elsevier Ltd
01.02.2018
Elsevier Science Ltd |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Precision medicine models for personalizing achieving sustained behavior change are largely outside of current clinical practice. Yet, changing self-regulatory behaviors is fundamental to the self-management of complex lifestyle-related chronic conditions such as depression and obesity - two top contributors to the global burden of disease and disability. To optimize treatments and address these burdens, behavior change and self-regulation must be better understood in relation to their neurobiological underpinnings. Here, we present the conceptual framework and protocol for a novel study, “Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes (ENGAGE)”. The ENGAGE study integrates neuroscience with behavioral science to better understand the self-regulation related mechanisms of behavior change for improving mood and weight outcomes among adults with comorbid depression and obesity. We collect assays of three self-regulation targets (emotion, cognition, and self-reflection) in multiple settings: neuroimaging and behavioral lab-based measures, virtual reality, and passive smartphone sampling. By connecting human neuroscience and behavioral science in this manner within the ENGAGE study, we develop a prototype for elucidating the underlying self-regulation mechanisms of behavior change outcomes and their application in optimizing intervention strategies for multiple chronic diseases.
•Uses a novel approach integrating neuroscience with behavioral medicine.•Includes self-regulation assays across lab, virtual reality, and natural settings.•Utilizes a brain-based experimental medicine approach to behavioral intervention.•Aims to identify self-regulation profiles to tailor intervention strategies.•Identifies a new taxonomy based on emotion, cognition, and self-reflection domains. |
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| AbstractList | Precision medicine models for personalizing achieving sustained behavior change are largely outside of current clinical practice. Yet, changing self-regulatory behaviors is fundamental to the self-management of complex lifestyle-related chronic conditions such as depression and obesity - two top contributors to the global burden of disease and disability. To optimize treatments and address these burdens, behavior change and self-regulation must be better understood in relation to their neurobiological underpinnings. Here, we present the conceptual framework and protocol for a novel study, “Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes (ENGAGE)”. The ENGAGE study integrates neuroscience with behavioral science to better understand the self-regulation related mechanisms of behavior change for improving mood and weight outcomes among adults with comorbid depression and obesity. We collect assays of three self-regulation targets (emotion, cognition, and self-reflection) in multiple settings: neuroimaging and behavioral lab-based measures, virtual reality, and passive smartphone sampling. By connecting human neuroscience and behavioral science in this manner within the ENGAGE study, we develop a prototype for elucidating the underlying self-regulation mechanisms of behavior change outcomes and their application in optimizing intervention strategies for multiple chronic diseases. Precision medicine models for personalizing achieving sustained behavior change are largely outside of current clinical practice. Yet, changing self-regulatory behaviors is fundamental to the self-management of complex lifestyle-related chronic conditions such as depression and obesity - two top contributors to the global burden of disease and disability. To optimize treatments and address these burdens, behavior change and self-regulation must be better understood in relation to their neurobiological underpinnings. Here, we present the conceptual framework and protocol for a novel study, “Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes (ENGAGE)”. The ENGAGE study integrates neuroscience with behavioral science to better understand the self-regulation related mechanisms of behavior change for improving mood and weight outcomes among adults with comorbid depression and obesity. We collect assays of three self-regulation targets (emotion, cognition, and self-reflection) in multiple settings: neuroimaging and behavioral lab-based measures, virtual reality, and passive smartphone sampling. By connecting human neuroscience and behavioral science in this manner within the ENGAGE study, we develop a prototype for elucidating the underlying self-regulation mechanisms of behavior change outcomes and their application in optimizing intervention strategies for multiple chronic diseases. •Uses a novel approach integrating neuroscience with behavioral medicine.•Includes self-regulation assays across lab, virtual reality, and natural settings.•Utilizes a brain-based experimental medicine approach to behavioral intervention.•Aims to identify self-regulation profiles to tailor intervention strategies.•Identifies a new taxonomy based on emotion, cognition, and self-reflection domains. |
| Author | Gevaert, Olivier Williams, Leanne M. Lewis, Megan A. Wandell, Brian Venditti, Elizabeth M. Correa, Carlos Smyth, Joshua M. Kullar, Monica Snowden, Mark Dagum, Paul Simmons, Janine M. Perry, L. Michael Suppes, Trisha Lavori, Philip W. Greenleaf, Walter Ma, Jun Goldstein-Piekarski, Andrea N. Sacchet, Matthew D. Rosas, Lisa G. Bailenson, Jeremy Pines, Adam |
| AuthorAffiliation | i Department of Psychology, Stanford University, 450 Serra Mall, Stanford, CA, United States o Affect, Social Behavior & Social Cognition Program, National Institute of Mental Health, 6001 Executive Boulevard, Rockville, MD, United States h Mindstrong Health, Inc., 248 Homer Avenue, Palo Alto, CA, United States b MIRECC VISN21, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, United States e Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine and Department of Biomedical Data Science, Stanford University, 1265 Welch Road, Stanford, CA, United States k Departments of Biobehavioral Health and of Medicine, The Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA, United States g Department of Biomedical Data Science, School of Medicine, Stanford University, 291 Campus Drive, Stanford, CA, United States j Biploar and Depression Research Program, Veteran Affairs Palo Alto Health Care System, 3801 Mira |
| AuthorAffiliation_xml | – name: e Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine and Department of Biomedical Data Science, Stanford University, 1265 Welch Road, Stanford, CA, United States – name: l Center for Communications Science, RTI International, 351 California Street Suite 500, San Francisco, CA, United States – name: d Department of Medicine, Stanford University School of Medicine, 291 Campus Drive, Stanford, CA, United States – name: f Department of Communication, Stanford University, 450 Serra Mall, Stanford, CA, United States – name: b MIRECC VISN21, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, United States – name: n Department of Psychiatry and Behavioral Sciences, University of Washington, 2815 Eastlake Avenue, Seattle, WA, United States – name: j Biploar and Depression Research Program, Veteran Affairs Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, United States – name: a Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – name: p Department of Health Policy and Administration, School of Public Health, 1603 West Taylor Street, Chicago, IL, University of Illinois at Chicago, United States – name: i Department of Psychology, Stanford University, 450 Serra Mall, Stanford, CA, United States – name: o Affect, Social Behavior & Social Cognition Program, National Institute of Mental Health, 6001 Executive Boulevard, Rockville, MD, United States – name: g Department of Biomedical Data Science, School of Medicine, Stanford University, 291 Campus Drive, Stanford, CA, United States – name: k Departments of Biobehavioral Health and of Medicine, The Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA, United States – name: h Mindstrong Health, Inc., 248 Homer Avenue, Palo Alto, CA, United States – name: m Western Psychiatric Institute and Clinic, 3811 O’Hara Street, Pittsburgh, PA, United States – name: c Palo Alto Medical Foundation Research Institute and Department of Medicine, 795 El Camino Real, Palo Alto, CA, United States |
| Author_xml | – sequence: 1 givenname: Leanne M. surname: Williams fullname: Williams, Leanne M. email: leawilliams@stanford.edu organization: Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – sequence: 2 givenname: Adam surname: Pines fullname: Pines, Adam organization: Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – sequence: 3 givenname: Andrea N. surname: Goldstein-Piekarski fullname: Goldstein-Piekarski, Andrea N. organization: Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – sequence: 4 givenname: Lisa G. surname: Rosas fullname: Rosas, Lisa G. organization: Palo Alto Medical Foundation Research Institute and Department of Medicine, 795 El Camino Real, Palo Alto, CA, United States – sequence: 5 givenname: Monica surname: Kullar fullname: Kullar, Monica organization: Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – sequence: 6 givenname: Matthew D. surname: Sacchet fullname: Sacchet, Matthew D. organization: Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – sequence: 7 givenname: Olivier surname: Gevaert fullname: Gevaert, Olivier organization: Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine and Department of Biomedical Data Science, Stanford University, 1265 Welch Road, Stanford, CA, United States – sequence: 8 givenname: Jeremy surname: Bailenson fullname: Bailenson, Jeremy organization: Department of Communication, Stanford University, 450 Serra Mall, Stanford, CA, United States – sequence: 9 givenname: Philip W. surname: Lavori fullname: Lavori, Philip W. organization: Department of Biomedical Data Science, School of Medicine, Stanford University, 291 Campus Drive, Stanford, CA, United States – sequence: 10 givenname: Paul surname: Dagum fullname: Dagum, Paul organization: Mindstrong Health, Inc., 248 Homer Avenue, Palo Alto, CA, United States – sequence: 11 givenname: Brian surname: Wandell fullname: Wandell, Brian organization: Department of Psychology, Stanford University, 450 Serra Mall, Stanford, CA, United States – sequence: 12 givenname: Carlos orcidid: 0000-0001-9138-7818 surname: Correa fullname: Correa, Carlos organization: Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – sequence: 13 givenname: Walter surname: Greenleaf fullname: Greenleaf, Walter organization: Department of Communication, Stanford University, 450 Serra Mall, Stanford, CA, United States – sequence: 14 givenname: Trisha surname: Suppes fullname: Suppes, Trisha organization: Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States – sequence: 15 givenname: L. Michael surname: Perry fullname: Perry, L. Michael organization: Department of Psychology, Stanford University, 450 Serra Mall, Stanford, CA, United States – sequence: 16 givenname: Joshua M. surname: Smyth fullname: Smyth, Joshua M. organization: Departments of Biobehavioral Health and of Medicine, The Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA, United States – sequence: 17 givenname: Megan A. surname: Lewis fullname: Lewis, Megan A. organization: Center for Communications Science, RTI International, 351 California Street Suite 500, San Francisco, CA, United States – sequence: 18 givenname: Elizabeth M. orcidid: 0000-0002-4124-6555 surname: Venditti fullname: Venditti, Elizabeth M. organization: Western Psychiatric Institute and Clinic, 3811 O'Hara Street, Pittsburgh, PA, United States – sequence: 19 givenname: Mark surname: Snowden fullname: Snowden, Mark organization: Department of Psychiatry and Behavioral Sciences, University of Washington, 2815 Eastlake Avenue, Seattle, WA, United States – sequence: 20 givenname: Janine M. surname: Simmons fullname: Simmons, Janine M. organization: Affect, Social Behavior & Social Cognition Program, National Institute of Mental Health, 6001 Executive Boulevard, Rockville, MD, United States – sequence: 21 givenname: Jun surname: Ma fullname: Ma, Jun organization: Department of Health Policy and Administration, School of Public Health, 1603 West Taylor Street, Chicago, IL, University of Illinois at Chicago, United States |
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| Keywords | Neuroimaging Behavior change Obesity Depression Virtual reality Self-regulation |
| Language | English |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Author contribution LMW and JM are co-PIs on the ENGAGE project and JM is the original PI of the RAINBOW project, and both have contributed the study conception, design, and implementation. AP was the first research coordinator on the project (now a graduate student), who helped develop and implement the study protocols and undertook data collection and participant testing on the ENGAGE measures. MK is a current research coordinator on the ENGAGE project who has also helped implement the study protocols and has undertaken data collection and participant testing on ENGAGE measures. AGP commenced as a postdoctoral fellow on the project who implemented the ENGAGE data analysis pipelines for the imaging data, and is a now a faculty instructor. MDS is a postdoctoral fellow on the project who has contributed to developing the imaging analysis protocols. LGR is a co-PI with JM on the RAINBOW study following JM’s change of institution in August 2015, and contributed to the conception and design of the ENGAGE project. OG is a co-I on the ENGAGE project who shares responsibility with PWL for data analytic models. JB is a co-I who has contributed to study design, with emphasis on virtual reality environments and assays. PWL is a co-I who developed the original data analysis plan, and shares responsibility with OG for data analytic models. PD is a consultant who has contributed to study design and data analysis, with emphasis on passive smartphone sampling. BW is a consultant who has contributed to integrated data management, with emphasis on neuroimaging and integration with other data assays. CC is a research software engineer who has had designed and developed the data pipeline for integrating sources of data and for enabling computation of the data. WG is a consultant who has contributed to study design, with emphasis on virtual reality environments. TS is a consultant who has contributed to trial design and clinical protocols. LMP is a key personnel contributor to establishing the data pipeline. JMSm is a consultant who has contributed expertise in ambulatory assessment, emotion regulation, and naturalistic behavior. MAL is a co-I for RAINBOW and a consultant for ENGAGE who has contributed to mixed methods evaluations of behavioral interventions in primary care settings. EMV is a co-I for RAINBOW and a consultant for ENGAGE who has contributed to behavioral weight loss intervention design and data interpretation. MS is a co-I for RAINBOW and ENGAGE who has contributed to study design, with emphasis on clinical depression management. JMSi is the NIH scientific officer for the project who has contributed to study design and implementation. All authors have contributed to the writing of the manuscript and have approved the final manuscript. |
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| PublicationTitle | Behaviour research and therapy |
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| SubjectTerms | Behavior change Behavior Control - methods Behavior modification Behavioral sciences Body Weight Chronic illnesses Clinical medicine Clinical Protocols Cognition Comorbidity Computer applications Depression Depression - epidemiology Depression - therapy Disability Emotional regulation Humans Lifestyles Magnetic Resonance Imaging Medical imaging Mental depression Mood Nervous system Neuroimaging Obesity Obesity - epidemiology Obesity - therapy Precision medicine Precision Medicine - methods Sampling Self regulation Self-Control - psychology Selfmanagement Selfreflection Smartphone Virtual Reality |
| Title | The ENGAGE study: Integrating neuroimaging, virtual reality and smartphone sensing to understand self-regulation for managing depression and obesity in a precision medicine model |
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