Evaluation of an Adaptive Intervention for Weight Loss Maintenance

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PROJECT SUMMARY Obesity remains a substantial public health challenge in the United States. Behavioral weight management programs have demonstrated effectiveness for weight loss, but long-term maintenance of these weight losses after the end of treatment tends to be poor. Evidence has demonstrated that individuals who can maintain their changes in eating and activity can successfully maintain their weight loss; thus, attempts to improve weight loss maintenance have often involved provision of continued support through monthly “extended-care” intervention sessions. While these interventions have demonstrated significant improvements in weight loss maintenance, effects have been modest. A key challenge is continued participant engagement (often assessed as attendance at intervention sessions). Attendance has been closely tied to weight outcomes, but rates tend to be poor and decline over time. The once-per-month, static treatment schedules of existing programs may contribute to these suboptimal outcomes; a participant experiencing a small lapse in weight-related behaviors may not receive support for several weeks, by which point they may be experiencing a larger lapse or weight regain. This can lead to feelings of frustration, shame, or embarrassment and disengagement from intervention. In contrast, tailoring intervention delivery such that sessions are provided when individuals are at “high risk” for weight regain offers potential to disrupt this cycle and significantly improve program engagement, adherence to program goals, and long-term weight maintenance outcomes. We propose to evaluate an innovative method of providing phone-based extended-care adaptive to participant needs. We have built a smartphone application that can be used by participants to track weight, dietary intake, and physical activity (key self-monitoring behaviors in traditional behavioral weight management programs) and can further query participants throughout the week regarding self-report factors (e.g., ratings of hunger and the importance of staying on track with weight management goals) that indicate high risk for weight regain. We have also developed a predictive algorithm that uses this data to identify when individuals are at “high risk” of weight regain. We propose to conduct a randomized controlled trial evaluating the impact of ADAPTIVE (delivered only when indicated by our algorithm or when initiated by participants via an in-app support request) versus STATIC (the monthly, pre-scheduled format used in existing extended-care programs) treatment provision on weight regain at 24 Months in 258 adults who successfully lose ≥ 5% of initial weight during a gold-standard 16-week behavioral weight management program. Results of this study have clear treatment implications for the timing/frequency of sessions within extended-care weight maintenance programs, and this study will result in an innovative, low-cost, and easily scalable intervention for weight loss maintenance. Further, the proposed research will fill a critical gap in the weight management literature by building a foundational evidence base of proximal predictors of weight-related behaviors for future adaptive intervention development.