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

Adults attempting weight loss through lifestyle modification (LM) typically find maintenance of behavior change difficult. Outcomes might be improved if participants are provided with sustained sources of accountability and support and ongoing opportunities to reflect with others on goal progress. This study proposes that sharing digital data with other parties has the potential to improve long-term weight loss. The proposed study will enroll adults ("index participants") (N = 320) with overweight/obesity in a 24-month LM program and instruct them to use digital tools for self-monitoring of weight, physical activity, and eating on a daily basis. Groups will meet remotely each week in months 1-3 to initiate weight loss. In months 4-24, intervention contact will be remote and will include the following: quarterly group meetings held via videoconference; brief phone calls with the coach held twice per quarter; and monthly text messages with the coach, with a small group of fellow group participants, and with a friend or family member outside of the program. Text message content will vary according to treatment condition, i.e. three types of data sharing partnerships: Coach Share, Group Share, and Friend/Family Share. Outcomes will be measured at months 0, 3, 6, 12, and 24. Primary aims include determining if Coach Share, Group Share, and Friend/ Family Share each improve long-term weight loss, PA, and calorie intake, and examining if effects are additive when participants are assigned to engage in more than one type of data sharing partnership. The secondary aim is to explore mediators and moderators of intervention effects. The tertiary aim is to determine how the quality of relationship with coach, group members, and friends/family member over time may differentially moderate treatment effects and predict data sharing efficacy. 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.