Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Psychosocial Domain

Angelina R. Sutin, Kerri Boutelle, Susan M. Czajkowski, Elissa S. Epel, Paige A. Green, Christine M. Hunter, Elise L. Rice, David M. Williams, Deborah Young-Hyman, Alexander J. Rothman

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Background: Within the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, the psychosocial domain addresses how psychosocial processes underlie the influence of obesity treatment strategies on weight loss and weight maintenance. The subgroup for the psychosocial domain identified an initial list of high-priority constructs and measures that ranged from relatively stable characteristics about the person (cognitive function, personality) to dynamic characteristics that may change over time (motivation, affect). Objectives: This paper describes (a) how the psychosocial domain fits into the broader model of weight loss and weight maintenance as conceptualized by ADOPT; (b) the guiding principles used to select constructs and measures for recommendation; (c) the high-priority constructs recommended for inclusion; (d) domain-specific issues for advancing the science; and (e) recommendations for future research. Significance: The inclusion of similar measures across trials will help to better identify how psychosocial factors mediate and moderate the weight loss and weight maintenance process, facilitate research into dynamic interactions with factors in the other ADOPT domains, and ultimately improve the design and delivery of effective interventions.

Original languageEnglish (US)
Pages (from-to)S45-S54
JournalObesity
Volume26
DOIs
StatePublished - Apr 2018

Bibliographical note

Funding Information:
Funding agencies: The ADOPT Core Measures Working Group was supported by intramural funding from the following National Institutes of Health: The National Heart, Lung, and Blood Institute, the National Cancer Institute, and the Office of Disease Prevention. The Grid-Enabled Measures Database (GEM) is supported and administered by the National Cancer Institute. Disclosure: KB has a grant from the Egg Nutrition Board. All other authors declared no conflicts of interest that are directly relevant to the work under consideration. The views expressed in this paper are those of the authors and do not necessarily represent the positions of the NIH, the DHHS, or the Federal Government. Received: 21 December 2017; Accepted: 12 February 2018; Published online 23 March 2018. doi:10.1002/oby.22160

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