Kathryn M Ross1, Peihua Qiu2, Lu You2, Rena R Wing3. 1. Department of Clinical and Health Psychology. 2. Department of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida. 3. Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University.
Abstract
OBJECTIVES: Despite increased interest in the development of individually tailored weight management programs, little is known about what factors proximally predict weight change. METHOD: The current study investigated proximal (week-to-week) predictors of weight loss and regain in 74 adults during a 3-month, Internet-based behavioral weight loss program followed by a 9-month "maintenance" period (during which no additional intervention was provided). Participants were asked to self-weigh daily using scales that transmitted weight via the cellular network and to answer a brief questionnaire each week querying mood, behaviors, and cognitions hypothesized to be associated with weight loss and regain. RESULTS: Longitudinal multilevel models demonstrated that weight loss during initial intervention was proximally predicted by (a) greater frequency of self-monitoring weight and caloric intake, consistency between eating choices and weight loss goals, and importance of "staying on track" with these goals and (b) less negative mood, boredom with weight control efforts, hunger, and temptation to eat foods "not on plan" (ps < .05). Greater weight regain after intervention was also proximally predicted by these factors (with effects in the opposite direction) and additionally by less physical activity, less positive mood, more stress, greater temptation to skip planned physical activity, and higher ratings of the amount of effort required to stay on track (ps < .05). CONCLUSIONS: Results confirmed the importance of self-monitoring for weight loss and maintenance and identified other key week-to-week predictors of weight change. Results also supported efforts to develop intervention approaches specifically focused on weight loss maintenance. Future research should investigate whether using identified predictors to tailor intervention content and timing can improve weight outcomes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
OBJECTIVES: Despite increased interest in the development of individually tailored weight management programs, little is known about what factors proximally predict weight change. METHOD: The current study investigated proximal (week-to-week) predictors of weight loss and regain in 74 adults during a 3-month, Internet-based behavioral weight loss program followed by a 9-month "maintenance" period (during which no additional intervention was provided). Participants were asked to self-weigh daily using scales that transmitted weight via the cellular network and to answer a brief questionnaire each week querying mood, behaviors, and cognitions hypothesized to be associated with weight loss and regain. RESULTS: Longitudinal multilevel models demonstrated that weight loss during initial intervention was proximally predicted by (a) greater frequency of self-monitoring weight and caloric intake, consistency between eating choices and weight loss goals, and importance of "staying on track" with these goals and (b) less negative mood, boredom with weight control efforts, hunger, and temptation to eat foods "not on plan" (ps < .05). Greater weight regain after intervention was also proximally predicted by these factors (with effects in the opposite direction) and additionally by less physical activity, less positive mood, more stress, greater temptation to skip planned physical activity, and higher ratings of the amount of effort required to stay on track (ps < .05). CONCLUSIONS: Results confirmed the importance of self-monitoring for weight loss and maintenance and identified other key week-to-week predictors of weight change. Results also supported efforts to develop intervention approaches specifically focused on weight loss maintenance. Future research should investigate whether using identified predictors to tailor intervention content and timing can improve weight outcomes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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