Journal article
Patterns and Predictors of Engagement With Digital Self-Monitoring During the Maintenance Phase of a Behavioral Weight Loss Program: Quantitative Study
JMIR mHealth and uHealth, v 11, pp e45057-e45057
18 Jul 2023
PMID: 37463017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Background: Long-term self-monitoring (SM) of weight, diet, and exercise is commonly recommended by behavioral weight loss (BWL) treatments. However, sustained SM engagement is notoriously challenging; therefore, more must be learned about patterns of engagement with digital SM tools during weight loss maintenance (WLM). In addition, insight into characteristics that may influence SM engagement could inform tailored approaches for participants at risk for poor adherence.Objective: This study explored patterns of digital SM of weight, diet, and exercise during WLM (aim 1) and examined timing, patterns, and rates of disengagement and reengagement (aim 2). This study also assessed relationships between individual-level factors (weight-related information avoidance and weight bias internalization) and SM engagement (aim 3).Methods: Participants were 72 adults enrolled in a BWL program consisting of a 3-month period of weekly treatment designed to induce weight loss (phase I), followed by a 9-month period of less frequent contact to promote WLM (phase II). Participants were prescribed daily digital SM of weight, diet, and exercise. At baseline, self-report measures assessed weight-related information avoidance and weight bias internalization. SM adherence was objectively measured with the days per month that participants tracked weight, diet, and exercise. Repeated-measures ANOVA examined differences in adherence across SM targets. Multilevel modeling examined changes in adherence across phase II. Relationships between individual-level variables and SM adherence were assessed with Pearson correlations, 2-tailed independent samples t tests, and multilevel modeling.Results: During WLM, consistently high rates of SM (& GE;50% of the days in each month) were observed for 61% (44/72) of the participants for exercise, 40% (29/72) of the participants for weight, and 21% (15/72) of the participants for diet. Adherence for SM of exercise was higher than that for weight or diet (P<.001). Adherence decreased over time for all SM targets throughout phase II (P<.001), but SM of exercise dropped off later in WLM (mean 10.07, SD 2.83 months) than SM of weight (mean 7.92, SD 3.23 months) or diet (mean 7.58, SD 2.92 months; P<.001). Among participants with a period of low SM adherence (ie, <50% of the days in a month), only 33% (17/51 for weight, 19/57 for diet) to 46% (13/28 for exercise) subsequently had & GE;1 months with high adherence. High weight-related information avoidance predicted a faster rate of decrease in dietary SM (P<.001). Participants with high weight bias internalization had the highest rates of weight SM (P=.03).Conclusions: Participants in BWL programs have low adherence to the recommendation to sustain daily SM during WLM, particularly for SM of diet and weight. Weight-related information avoidance and weight bias internalization may be relevant indicators for SM engagement. Interventions may benefit from innovative strategies that target participants at key moments of risk for disengagement.
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Details
- Title
- Patterns and Predictors of Engagement With Digital Self-Monitoring During the Maintenance Phase of a Behavioral Weight Loss Program: Quantitative Study
- Creators
- Nicole Crane - Drexel UniversityCharlotte Hagerman - Drexel University, WELL CenterOlivia Horgan - Drexel University, WELL CenterMeghan Butryn - Drexel University, Psychological and Brain Sciences (Psychology)
- Publication Details
- JMIR mHealth and uHealth, v 11, pp e45057-e45057
- Publisher
- Jmir Publications, Inc
- Number of pages
- 16
- Grant note
- R21DK112741 / National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology); WELL Center
- Web of Science ID
- WOS:001047808900001
- Scopus ID
- 2-s2.0-85165520011
- Other Identifier
- 991021860729204721
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- Medical Informatics