Incentivizing behavior change skills to promote weight loss

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 DESCRIPTION (provided by applicant): Two-thirds of the United States population is now classified as obese or overweight. Despite the existence of effective behavioral weight loss interventions, many people do not adhere to them, and even people who lose significant weight regain it in the year following intervention. Novel methods are needed to improve adherence to effective weight loss interventions and promote long-term weight loss maintenance. One promising strategy is reinforcement via financial incentives. Positive reinforcement with variable-ratio schedules has received theoretical and empirical support in various behavioral domains. However, the few studies testing this type of strategy for weight loss have been largely ineffective. A key issue is whether incentives should be provided for process (e.g., dietary self-monitoring) or outcome (weight loss). Incenting dietary self-monitoring and weight loss may be more effective than incenting either alone. In previous studies, patients had to attend in-person sessions to turn in self-monitoring records and be weighed, so self- monitoring and interim weight loss were confounded with attendance. To deliver incentives in real-time for dietary self-monitoring and interim weight loss alone, data collection and processing must be automated. In this study, obese community outpatients will participate in an effective, 24-week, low-carbohydrate weight loss program delivered via biweekly group classes. We will develop an innovative information technology (IT) solution that will collate dietary self-monitoring data (inpt by patients via a mobile phone dietary application) and weight loss data (input by patients via remote scale). An algorithm will classify participants as achieving adequate or inadequate dietary self-monitoring and weight loss to earn intermittent rewards of varying value in real-time. The 2 (incentive for self-monitoring: yes vs. no) X 2 (incentive for weight loss: yes vs. no) between-subjects design will allow us to establish feasibility and acceptability of incenting self-monitoring and interim weight loss alone and in conjunction. Specific aims are: (1) Determine feasibility and acceptability of using automated algorithms that analyze dietary self-monitoring and interim weight loss data to provide real- time reinforcement using variable-ratio incentives; (2) Evaluate the effectiveness of various recruitment methods and describe recruitment, intervention adherence, and outcome assessment adherence rates; (3) Estimate cost of delivering the intervention and cost to patients. This project will provide the foundation for a comprehensive effectiveness trial to test the impact of incenting dietary self-monitoring and interim weight loss on short- and longer-term weight outcomes while incentives are delivered and once they are withdrawn. If effective, this approach could reduce the prevalence, adverse outcomes, and costs of obesity for millions of Americans.