Sharing Digital Self-Monitoring Data with Others to Enhance Long-Term Weight Loss: A Randomized Trial using a Factorial Design

Digital devices for self-monitoring (i.e., smart scale to measure weight, sensor for physical activity (PA), and app to record dietary intake) are commonly used by adults in lifestyle modification (LM) programs who are attempting weight loss. Sharing digital self-monitoring data with others has the potential to facilitate long-term behavior change in a scalable way, but the benefit of data sharing has not been rigorously tested and traditional LM programs do not yet incorporate digital data sharing in a systematic way. The proposed study will give a coach, fellow program members, and/or a friend or family member access to participant self-monitoring data and train those parties to monitor participant performance. This creates supportive accountability, which should enhance motivation for target behaviors, because it is human nature to strive to meet goals when others can monitor goal progress. The “data sharing partner” will be trained to elicit reflection from the participant on his/her performance, which is a key component of self-regulation. The data sharing partner also will provide praise or express concern, which should further enhance motivation. Adults with overweight/obesity will be enrolled in a 24-month LM program and instructed to use digital tools for self-monitoring of weight, PA, and eating on a daily basis. Groups will meet face-to-face weekly to initiate weight loss (months 1-3), followed by remote intervention contact (months 4-24), consisting of quarterly virtual groups meetings; brief, individual phone calls with the coach; and monthly text messages with the coach, a small group of fellow participants, and a friend or family member outside of the program. A factorial design will be used to efficiently test the independent effects of three digital data sharing partnerships: 1) Coach Share: The behavioral coach will view digital self-monitoring data throughout the program and will directly address data observations during intervention contacts. 2) Group Share: Participants in a given LM group will view each other’s self-monitoring data in their small-group text messages and be trained to respond in ways that enhance supportive accountability. 3) Friend/Family Share: A friend/family member will view the participant’s data (via automated text message) and be trained to provide supportive accountability. Amount of intervention contact between the participant and each party is comparable regardless of treatment condition, isolating the effects of data sharing. Outcomes will be measured at months 0, 6, 12, and 24. The study will determine if Coach Share, Group Share, and Friend/Family Share each improve long-term weight loss, PA, and calorie intake (i.e., outcomes will be compared for participants who are randomized to engage in that data sharing partnership, versus those who are not). The study also will examine if effects are additive when participants are assigned to engage in more than one data sharing partnership. Meditators and moderators of intervention effects will be examined. As digital technology makes data sharing increasingly feasible, it is critical to determine how to optimize these partnerships to improve long-term outcomes in LM.