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Behav Res Ther. 2018 Feb;101:58-70. doi: 10.1016/j.brat.2017.09.012. Epub 2017 Oct 7.

The ENGAGE study: Integrating neuroimaging, virtual reality and smartphone sensing to understand self-regulation for managing depression and obesity in a precision medicine model.

Author information

1
Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States; MIRECC VISN21, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, United States. Electronic address: leawilliams@stanford.edu.
2
Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States.
3
Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States; MIRECC VISN21, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, United States.
4
Palo Alto Medical Foundation Research Institute and Department of Medicine, 795 El Camino Real, Palo Alto, CA, United States; Department of Medicine, Stanford University School of Medicine, 291 Campus Drive, Stanford, CA, United States.
5
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.
6
Department of Communication, Stanford University, 450 Serra Mall, Stanford, CA, United States.
7
Department of Biomedical Data Science, School of Medicine, Stanford University, 291 Campus Drive, Stanford, CA, United States.
8
Mindstrong Health, Inc., 248 Homer Avenue, Palo Alto, CA, United States.
9
Department of Psychology, Stanford University, 450 Serra Mall, Stanford, CA, United States.
10
Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States; Department of Psychology, Stanford University, 450 Serra Mall, Stanford, CA, United States.
11
Department of Psychiatry and Behavioral Sciences, Stanford University, 401 Quarry Road, Stanford, CA, United States; Biploar and Depression Research Program, Veteran Affairs Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA, United States.
12
Departments of Biobehavioral Health and of Medicine, The Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA, United States.
13
Center for Communications Science, RTI International, 351 California Street Suite 500, San Francisco, CA, United States.
14
Western Psychiatric Institute and Clinic, 3811 O'Hara Street, Pittsburgh, PA, United States.
15
Department of Psychiatry and Behavioral Sciences, University of Washington, 2815 Eastlake Avenue, Seattle, WA, United States.
16
Affect, Social Behavior & Social Cognition Program, National Institute of Mental Health, 6001 Executive Boulevard, Rockville, MD, United States.
17
Department of Health Policy and Administration, School of Public Health, 1603 West Taylor Street, Chicago, IL, University of Illinois at Chicago, United States.

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.

KEYWORDS:

Behavior change; Depression; Neuroimaging; Obesity; Self-regulation; Virtual reality

PMID:
29074231
DOI:
10.1016/j.brat.2017.09.012
[Indexed for MEDLINE]

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