Comparing Self-Monitoring Strategies for Weight Loss in a Smartphone App: Randomized Controlled Trial

Abstract

BackgroundSelf-monitoring of dietary intake is a valuable component of behavioral weight loss treatment; however, it declines quickly, thereby resulting in suboptimal treatment outcomes.ObjectiveThis study aimed to examine a novel behavioral weight loss intervention that aims to attenuate the decline in dietary self-monitoring engagement.MethodsGoalTracker was an automated randomized controlled trial. Participants were adults with overweight or obesity (n=105; aged 21-65 years; body mass index, BMI, 25-45 kg/m2) and were randomized to a 12-week stand-alone weight loss intervention using the MyFitnessPal smartphone app for daily self-monitoring of either (1) both weight and diet, with weekly lessons, action plans, and feedback (Simultaneous); (2) weight through week 4, then added diet, with the same behavioral components (Sequential); or (3) only diet (App-Only). All groups received a goal to lose 5% of initial weight by 12 weeks, a tailored calorie goal, and automated in-app reminders. Participants were recruited via online and offline methods. Weight was collected in-person at baseline, 1 month, and 3 months using calibrated scales and via self-report at 6 months. We retrieved objective self-monitoring engagement data from MyFitnessPal using an application programming interface. Engagement was defined as the number of days per week in which tracking occurred, with diet entries counted if ≥800 kcal per day. Other assessment data were collected in-person via online self-report questionnaires.ResultsAt baseline, participants (84/100 female) had a mean age (SD) of 42.7 (11.7) years and a BMI of 31.9 (SD 4.5) kg/m2. One-third (33/100) were from racial or ethnic minority groups. During the trial, 5 participants became ineligible. Of the remaining 100 participants, 84% (84/100) and 76% (76/100) completed the 1-month and 3-month visits, respectively. In intent-to-treat analyses, there was no difference in weight change at 3 months between the Sequential arm (mean −2.7 kg, 95% CI −3.9 to −1.5) and either the App-Only arm (−2.4 kg, −3.7 to −1.2; P=.78) or the Simultaneous arm (−2.8 kg, −4.0 to −1.5; P=.72). The median number of days of self-monitoring diet per week was 1.9 (interquartile range [IQR] 0.3-5.5) in Sequential (once began), 5.3 (IQR 1.8-6.7) in Simultaneous, and 2.9 (IQR 1.2-5.2) in App-Only. Weight was tracked 4.8 (IQR 1.9-6.3) days per week in Sequential and 5.1 (IQR 1.8-6.3) days per week in Simultaneous. Engagement in neither diet nor weight tracking differed between arms.ConclusionsRegardless of the order in which diet is tracked, using tailored goals and a commercial mobile app can produce clinically significant weight loss. Stand-alone digital health treatments may be a viable option for those looking for a lower intensity approach.Trial RegistrationClinicalTrials.gov NCT03254953; https://clinicaltrials.gov/ct2/show/NCT03254953 (Archived by WebCite at http://www.webcitation.org/72PyQrFjn).

Early weight loss in a standalone mHealth intervention predicting treatment success

“…Because weight change did not differ between treatment arms at 1 or 3 months in the parent study (14), data were collapsed across arms in the current analysis.…”

“…Because weight change did not differ between treatment arms at 1 or 3 months in the parent study , data were collapsed across arms in the current analysis. Consistent with previous behavioural weight loss research , participants were categorized into early responders (i.e.…”

15 Smartphone Apps for Older Adults to Use While in Isolation During the COVID-19 Pandemic

“…59,65 Limitations of MyFitnessPal include unreliable estimation of (micro-) nutrients ingestion and ineffectiveness in patients without goals and willingness to self-monitor calories. [66][67][68][69] Therefore, although MyFitnessPal may be recommended to promote healthy behavior, OAs should not use MyFitnessPal by itself, and work in conjunction with a dietitian if possible. 70…”

Real-Time Model Predictive Control of Human Bodyweight Based on Energy Intake

“…Currently, there are numerous smartphone applications available to track in an individualized and objective manner weight, physical activity and dietary energy intake [16,17]. However, studies show that the engagement of individuals with these apps decreases after some time, even when personalized suggestions are provided [15,18,19]. One of the contributing aspects to this may rely on the fact that nowadays, empirical equations describing the nutrition process are used to predict weight loss and/or to advise dietary energy intake levels.…”

“…Therefore, inaccurate predictions or suggestions are obtained when applied to data from a single individual. This can diminish the trust in the smartphone app, leading to a loss of engagement and adherence to the suggestions, finally quitting its use [18][19][20].Past and current theoretical models describing the nutrition process are based on the first thermodynamics law on energy conservation [2,21]. Based on some of the earliest models proposed, still nowadays, many health institutions recommend reducing daily calorie intake with 2 MJ to lose 0.5 kg in 1 week, known as the 3500 kcal rule [21].…”