%0 Journal Article
%@ 2291-5222
%I JMIR Publications
%V 9
%N 7
%P e18741
%T Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study
%A Farage,Gregory
%A Simmons,Courtney
%A Kocak,Mehmet
%A Klesges,Robert C
%A Talcott,G Wayne
%A Richey,Phyllis
%A Hare,Marion
%A Johnson,Karen C
%A Sen,Saunak
%A Krukowski,Rebecca
%+ Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, 66 N Pauline St, Memphis, TN, 38163, United States, 1 901 448 2426, rkrukows@uthsc.edu
%K weight loss
%K self-monitoring
%K obesity
%K apps
%K behavioral intervention
%D 2021
%7 14.7.2021
%9 Original Paper
%J JMIR Mhealth Uhealth
%G English
%X 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 did not contribute to either model (4 months: P=.77; 12 months: P=.15). Conclusions: We found that app use and daily reported caloric intake had a substantial impact on weight loss prediction at 4 months. Our analysis did not find evidence of an association between participant self-monitoring exercise information and weight loss. As 12-month weight loss was completely mediated by 4-month weight loss, intervention targets should focus on promoting early and frequent dietary intake self-monitoring and self-weighing to promote early weight loss, which leads to long-term success. Trial Registration: ClinicalTrials.gov NCT02063178; https://clinicaltrials.gov/ct2/show/NCT02063178 
%M 34259635
%R 10.2196/18741
%U https://mhealth.jmir.org/2021/7/e18741
%U https://doi.org/10.2196/18741
%U http://www.ncbi.nlm.nih.gov/pubmed/34259635