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

Abstract

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

Can Digital Technologies Be Useful for Weight Loss in Individuals with Overweight or Obesity? A Systematic Review

“…After the full-text assessment of the 133 articles that remained, 102 articles were excluded, 42 of them because they did not pertain to our question, 12 because the individuals were affected by other comorbidities, 16 because they were a different type of study from RCT, 7 because they considered a young age population (<18 years), 4 because did not have control groups, and 21 because they did not consider the assessment of changes in PA. Finally, we included 31 articles that met the inclusion criteria ( Figure 1 ) [ 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 ].…”

“…The included articles were published between 2013 [ 54 ] and 2023 [ 61 , 68 ], and 15 of them were performed in the USA [ 40 , 41 , 42 , 45 , 46 , 51 , 54 , 55 , 58 , 62 , 63 , 64 , 65 , 67 ], 9 in Europe [ 38 , 39 , 47 , 49 , 56 , 57 , 59 , 61 , 66 ], 5 in Asia [ 43 , 47 , 52 , 60 , 68 ] and 2 in Australia [ 44 , 50 ]. Both genders were represented in most studies, except in two studies that did not report this information [ 50 , 54 ], and two studies that included only women [ 47 , 48 ].…”

An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study

“…Obesity-attributable medical costs remain high for health care systems and patients and are on the rise [1,2]. Although there has been an increase in the number of mobile intervention based weight loss treatment programs [3][4][5], effective and economical interventions have not been adequately identified or disseminated. To save costs and improve health outcomes, interventions that can predict nonresponse early during a treatment program enable dynamic modification of intervention components (ie, stepped-care models [6]) to steer the course of treatment toward achieving a response or the desired health outcome, analogous to clinical decision-making over time.…”

Expert opinions on reducing dietary self‐monitoring burden and maintaining efficacy in weight loss programs: A Delphi study

“… 9 In addition, adherence to self‐monitoring typically declines over time. 10 , 11 However, there are limited data on how long it is necessary to complete detailed dietary self‐monitoring for optimal weight outcomes and when, or how, individuals can transition to less burdensome monitoring approach yet still achieve successful weight control.…”

“…However, dietary self‐monitoring is associated with significant burden, 8 with recent estimates indicating that dietary self‐monitoring takes about 23 min per day in the first month of a structured behavioral weight control program and only slight decreases in burden observed in subsequent months 9 . In addition, adherence to self‐monitoring typically declines over time 10,11 . However, there are limited data on how long it is necessary to complete detailed dietary self‐monitoring for optimal weight outcomes and when, or how, individuals can transition to less burdensome monitoring approach yet still achieve successful weight control.…”