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JMIR Mhealth Uhealth. 2019 Feb 28;7(2):e12209. doi: 10.2196/12209.

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

Author information

1
Department of Psychology and Neuroscience, Duke University, Durham, NC, United States.
2
Duke Digital Health Science Center, Duke Global Health Institute, Durham, NC, United States.
3
Stanford Prevention Research Center, Stanford University School of Medicine, Palo Alto, CA, United States.

Abstract

BACKGROUND:

Self-monitoring of dietary intake is a valuable component of behavioral weight loss treatment; however, it declines quickly, thereby resulting in suboptimal treatment outcomes.

OBJECTIVE:

This study aimed to examine a novel behavioral weight loss intervention that aims to attenuate the decline in dietary self-monitoring engagement.

METHODS:

GoalTracker 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 ‚Č•800 kcal per day. Other assessment data were collected in-person via online self-report questionnaires.

RESULTS:

At 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.

CONCLUSIONS:

Regardless 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 REGISTRATION:

ClinicalTrials.gov NCT03254953; https://clinicaltrials.gov/ct2/show/NCT03254953 (Archived by WebCite at http://www.webcitation.org/72PyQrFjn).

KEYWORDS:

caloric restriction; mobile app; mobile health; obesity, self-monitoring; randomized controlled trial; technology; treatment adherence and compliance; weight loss

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