Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study

• Published in: JMIR mHealth and uHealth 2021-07, Vol.9 (7), p.e18741-e18741
• Main Authors: Farage, Gregory, Simmons, Courtney, Kocak, Mehmet, Klesges, Robert C, Talcott, G Wayne, Richey, Phyllis, Hare, Marion, Johnson, Karen C, Sen, Saunak, Krukowski, Rebecca
• Format: Article
• Language: English
• Subjects: Behavior; Data collection; Exercise; Food; Original Paper; Physical fitness; Principal components analysis; Variables; Web sites; Weight control
• ISSN: 2291-5222; 2291-5222
• DOI: 10.2196/18741

Background: Electronic self-monitoring technology has the potential to provide unique insights into important behaviors for inducing weight loss. Objective: The aim of this study is to investigate the effects of electronic self-monitoring behavior (using the commercial Lose It! app) and weight loss interventions (with differing amounts of counselor feedback and support) on 4- and 12-month weight loss. Methods: In this secondary analysis of the Fit Blue study, we compared the results of two interventions of a randomized controlled trial. Counselor-initiated participants received consistent support from the interventionists, and self-paced participants received assistance upon request. The participants (N=191), who were active duty military personnel, were encouraged to self-monitor their diet and exercise with the Lose It! app or website. We examined the associations between intervention assignment and self-monitoring behaviors. We conducted a mediation analysis of the intervention assignment for weight loss through multiple mediators—app use (calculated from the first principal component [PC] of electronically collected variables), number of weigh-ins, and 4-month weight change. We used linear regression to predict weight loss at 4 and 12 months, and the accuracy was measured using cross-validation. Results: On average, the counselor-initiated–treatment participants used the app more frequently than the self-paced–treatment participants. The first PC represented app use frequencies, the second represented calories recorded, and the third represented reported exercise frequency and exercise caloric expenditure. We found that 4-month weight loss was partially mediated through app use (ie, the first PC; 60.3%) and the number of weigh-ins (55.8%). However, the 12-month weight loss was almost fully mediated by 4-month weight loss (94.8%). Linear regression using app data from the first 8 weeks, the number of self–weigh-ins at 8 weeks, and baseline data explained approximately 30% of the variance in 4-month weight loss. App use frequency (first PC; P=.001), self-monitored caloric intake (second PC; P=.001), and the frequency of self-weighing at 8 weeks (P=.008) were important predictors of 4-month weight loss. Predictions for 12-month weight with the same variables produced an R2 value of 5%; only the number of self–weigh-ins was a significant predictor of 12-month weight loss. The R2 value using 4-month weight loss as a predictor was 31%. Self-reported exercise