The purpose of this study is to determine the feasibility of providing personalized incentives for dietary self-monitoring and/or interim weight loss to people enrolled in a weight-loss program
In this study, community outpatients will participate in a clinician-facilitated, group-based behavioral weight-loss program for 24 weeks. Dietary self-monitoring data (input by patients via a mobile phone dietary application) and weight data (input by patients via cellular scale) will be collected by a software platform. A reinforcement learning algorithm will use data collected during the trial to predict which participants will respond to a financial incentive. Incentives will be provided to participants predicted to respond, and they will be notified of incentives via text messaging.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
TREATMENT
Masking
NONE
Enrollment
94
Every week, a reinforcement learning algorithm will process data on weight loss, calorie logging, and incentives earned to predict that their weight loss is positively influenced by incentives.
University of Utah
Salt Lake City, Utah, United States
Screening-to-enrollment ratio
number of potential participants screened for the study/ number of participants who provide a baseline weight for the intervention
Time frame: Week 0
Retention for outcomes
number of participants who provide a weight at 25 weeks/number of participants who provide a baseline weight for the intervention
Time frame: 25 weeks
Adherence to calorie logging
Proportion of weeks participants achieve adequate calorie logging (5 days per week)
Time frame: 24 weeks
Adherence to self-weighing
Proportion of weeks participants weigh at least twice per week on a study-provided cellular scale
Time frame: 24 weeks
Body weight
Changes in body weight from baseline to week 25, measured by study-provided cellular scales
Time frame: baseline to 25 weeks
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