ArticleJMIR formative research2022
Consistency With and Disengagement From Self-monitoring of Weight, Dietary Intake, and Physical Activity in a Technology-Based Weight Loss Program: Exploratory Study.
Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Associations Between the Use of Fitness and Diet Tracking Technology and Disordered Eating Behaviour: A Systematic Review.European eating disorders review : the journal of the Eating Disorders Association · 2025Pooled it
- Brief coaching intervention to reverse weight regain during weight loss maintenance: a preliminary randomized controlled trial.Journal of behavioral medicine · 2025Trial
- Adherence to self-monitoring and behavioral goals is associated with improved weight loss in an mHealth randomized-controlled trial.Obesity (Silver Spring, Md.) · 2025Trial
- Understanding Heterogeneity in Individual Responses to Digital Lifestyle Intervention Through Self-Monitoring Adherence Trajectories in Adults With Overweight or Obesity: Secondary Analysis of a 6-Month Randomized Controlled Trial.Journal of medical Internet research · 2024Trial
- Pilot of a Micro-Randomized Factorial Trial of Self-Monitoring Feedback in a Behavioral Weight Loss Intervention.Obesity science & practice · 2026Article
- Article
- Participant food tracking in psychiatric ketogenic metabolic therapy: an unresolved clinical, psychosocial, and implementation question.Frontiers in nutrition · 2026Review
- Systematic review of dynamically tailored eHealth interventions targeting physical activity and healthy diet in chronic disease.NPJ digital medicine · 2025Article
- Feasibility of mHealth Strategies to Promote Use of Wrist-Worn Alcohol Biosensors Among Young Adults With HIV: Protocol for the Engage Microrandomized Trial.JMIR research protocols · 2025Article
- Application of the Supportive Accountability Model in Digital Health Interventions: Scoping Review.Journal of medical Internet research · 2025Article
- Exploring the Dynamics of Dietary Self-Monitoring Adherence Among Participants in a Digital Behavioral Weight Loss Program: Model Development Study.Journal of medical Internet research · 2025Article
- Within-week and within-year patterns in self-monitoring of dietary intake in adults with obesity participating in a behavioral weight loss program.Health psychology and behavioral medicine · 2025Article
- Accountability Frameworks in Medical Weight Loss Programs: A Comprehensive Literature Review.Cureus · 2024Review
- Identification of minimum thresholds for dietary self-monitoring to promote weight-loss maintenance.Obesity (Silver Spring, Md.) · 2024Article
- The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination.JMIR mHealth and uHealth · 2023Article
- Development of a Digital Behavioral Intervention to Reduce the Consumption of Sugar-Sweetened Beverages Among Rural Appalachian Adults: Multiphased, Human-Centered Design Approach.JMIR human factors · 2023Article
- Remotely Conducted App-Based Intervention for Cardiovascular Disease and Diabetes Risk Awareness and Prevention: Single-Group Feasibility Trial.JMIR human factors · 2022Article
- Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundDigital self-monitoring tools offer promise to improve adherence to self-monitoring of weight and weight-related behaviors; however, less is known regarding the patterns of participant consistency and disengagement with these tools.
objectiveThis study characterizes the consistency of use and time to disengagement with digital self-monitoring tools during a 6-month weight loss intervention and investigates whether the provision of phone-based intervention improved self-monitoring adherence.
methodsParticipants were 54 adults with overweight or obesity (mean age 49.6 years, SD 12.4 years; mean BMI 32.6 kg/m
resultsParticipants consistently self-monitored physical activity for more weeks (mean 17.4 weeks, SD 8.5 weeks) than weight (mean 11.1 weeks, SD 8.5 weeks) or dietary intake (mean 10.8 weeks, SD 8.7 weeks; P<.05). Similarly, participants had a significantly longer time to disengagement from self-monitoring of physical activity (median 19.5 weeks) than weight (4 weeks) or dietary intake (10 weeks; P<.001). Participants randomized to receive additional interventionist contact had significantly greater consistency and longer time to disengagement for self-monitoring of dietary intake compared with participants who did not (P=.006); however, there were no statistically significant differences between groups for self-monitoring of weight or physical activity (P=.24 and P=.25, respectively). Greater consistency and longer time to disengagement were associated with greater weight loss for self-monitoring of weight and dietary intake (P<.001 and P=.004, respectively) but not for physical activity (P=.57).
conclusionsResults demonstrated that self-monitoring adherence differed by behavioral target, with greater consistency and longer time to disengagement associated with lower-burden tools (ie, self-monitoring of physical activity). Consistent with supportive accountability theory, additional interventionist contact improved consistency and lengthened time to disengagement from self-monitoring of dietary intake. Given the observed associations between consistency, disengagement, and weight loss outcomes, it is important to identify additional methods of increasing consistency and engagement with digital self-monitoring tools.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.