Energy Balancing Modeling and Mobile Technology to Support e-Weight Loss

Behavioral lifestyle treatment for obesity produces clinically significant weight loss and corresponding improvements in disease risk and severity when delivered via in-person group and/or individual treatment sessions. Online versions have been developed in order to reduce costs. These programs typically include weekly weight loss lessons and tailored feedback on patients' weight loss progress. However, online programs often produce suboptimal outcomes compared to programs delivered in-person due to insufficient adherence to prescribed behavioral strategies, and a lack of objective methods for behavioral self-monitoring to support adherence. One approach to monitoring and improving adherence involves tracking patients' weight loss progress on a personalized nomogram (i.e., graph). The nomogram is based on a dynamic energy balance equation and depicts the expected weight loss over time if the participant is adherent to a prescribed goal for caloric intake and physical activity. A complementary approach to measuring and intervening on adherence involves the use of mobile technology to monitor eating behavior. The Bite Counter is a wrist-worn device similar to a wristwatch that measures the timing, frequency, rate, and duration of eating events by monitoring the "wrist roll" motion that occurs when food is brought to the mouth. By using mathematical models to "calibrate" the Bite Counter to the weight loss nomogram, it may be possible to identify the optimal number of bites that any given patient should take each day in order to facilitate weight loss. The purpose of the proposed study is to conduct a small randomized controlled trial to test the feasibility, acceptability, and preliminary efficacy of adding weight loss nomograms and the Bite Counter to an established online weight loss program. A sample of 30 participants with overweight/obesity will be randomly assigned in equal proportions to one of three 12-week weight loss programs: (a) online behavioral weight l