Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program

Gabrielle M. Turner-McGrievy, Michael W. Beets, Justin B. Moore, Andrew T. Kaczynski, Daheia J. Barr-Anderson, Deborah F. Tate

Research output: Contribution to journalArticlepeer-review

203 Scopus citations

Abstract

Objective: Self-monitoring of physical activity (PA) and diet are key components of behavioral weight loss programs. The purpose of this study was to assess the relationship between diet (mobile app, website, or paper journal) and PA (mobile app vs no mobile app) self-monitoring and dietary and PA behaviors. Materials and methods: This study is a post hoc analysis of a 6-month randomized weight loss trial among 96 overweight men and women (body mass index (BMI) 25-45 kg/m2) conducted from 2010 to 2011. Participants in both randomized groups were collapsed and categorized by their chosen selfmonitoring method for diet and PA. All participants received a behavioral weight loss intervention delivered via podcast and were encouraged to self-monitor dietary intake and PA. Results: Adjusting for randomized group and demographics, PA app users self-monitored exercise more frequently over the 6-month study (2.6±0.5 days/week) and reported greater intentional PA (196.4±45.9 kcal/day) than non-app users (1.2±0.5 days/week PA self-monitoring, p<0.01; 100.9±45.1 kcal/day intentional PA, p=0.02). PA app users also had a significantly lower BMI at 6 months (31.5±0.5 kg/2) than non-users (32.5±0.5 kg/m2; p=0.02). Frequency of self-monitoring did not differ by diet self-monitoring method (p=0.63); however, app users consumed less energy (1437±188 kcal/day) than paper journal users (2049±175 kcal/day; p=0.01) at 6 months. BMI did not differ among the three diet monitoring methods ( p=0.20). Conclusions: These findings point to potential benefits of mobile monitoring methods during behavioral weight loss trials. Future studies should examine ways to predict which self-monitoring method works best for an individual to increase adherence.

Original languageEnglish (US)
Pages (from-to)513-518
Number of pages6
JournalJournal of the American Medical Informatics Association
Volume20
Issue number3
DOIs
StatePublished - 2013

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