Trial reportJournal of medical Internet research2015
Short-term trajectories of use of a caloric-monitoring mobile phone app among patients with type 2 diabetes mellitus in a primary care setting.
Trial report in Journal of medical Internet research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
29 citing papers in PubMed, 77 citations in OpenAlex.
- Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial.Journal of medical Internet research · 2022Trial
- Digitally Supported Lifestyle Intervention to Prevent Type 2 Diabetes Through Healthy Habits: Secondary Analysis of Long-Term User Engagement Trajectories in a Randomized Controlled Trial.Journal of medical Internet research · 2022Trial
- Apps for IMproving FITness and Increasing Physical Activity Among Young People: The AIMFIT Pragmatic Randomized Controlled Trial.Journal of medical Internet research · 2015Trial
- Calorie-Counting Apps for Monitoring and Managing Calorie Intake in Adults Living With Weight-Related Chronic Diseases: Decade-Long Scoping Review (2013-2024).JMIR mHealth and uHealth · 2026Article
- Attitudes of Elderly Population Toward Mobile Health Applications in Aseer Region, Saudi Arabia: A Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2025Article
- Applications of artificial intelligence in the management of childhood obesity.Journal of family medicine and primary care · 2023Review
- Use of the Smoking Cessation App Ex-Smokers iCoach and Associations With Smoking-Related Outcomes Over Time in a Large Sample of European Smokers: Retrospective Observational Study.Journal of medical Internet research · 2023Observational
- Multimodal Diabetes Empowerment for Older Adults with Diabetes.International journal of environmental research and public health · 2022Article
- Great diversity in the utilization and reporting of latent growth modeling approaches in type 2 diabetes: A literature review.Heliyon · 2022Review
- Assessing Engagement With Patient-Generated Health Data Recording and Its Impact on Health Behavior Changes in Multicomponent Interventions: Supplementary Analysis.JMIR formative research · 2022Article
- Future Mobile Device Usage, Requirements, and Expectations of Physicians in German University Hospitals: Web-Based Survey.Journal of medical Internet research · 2020Article
- Acceptability and practicability of self-management for patients with Parkinson's disease based on smartphone applications in China.BMC medical informatics and decision making · 2020Article
- Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis.JMIR mHealth and uHealth · 2020Observational
- Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review.JMIR mHealth and uHealth · 2020Article
- mHealth Apps Assessment among Postpartum Women with Obesity and Depression.Healthcare (Basel, Switzerland) · 2020Article
- Smartphones and Apps to Control Glycosylated Hemoglobin (HbA1c) Level in Diabetes: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2020Review
- A Mobile Application to Collect Daily Data on Preexposure Prophylaxis Adherence and Sexual Behavior Among Men Who Have Sex With Men: Use Over Time and Comparability With Conventional Data Collection.Sexually transmitted diseases · 2019Article
- Mobile-Based Interventions for Dietary Behavior Change and Health Outcomes: Scoping Review.JMIR mHealth and uHealth · 2019Article
- A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review.JMIR mHealth and uHealth · 2019Article
- Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundSelf-management plays an important role in maintaining good control of diabetes mellitus, and mobile phone interventions have been shown to improve such self-management. The Health Promotion Board of Singapore has created a caloric-monitoring mobile health app, the "interactive Diet and Activity Tracker" (iDAT).
objectiveThe objective was to identify and describe short-term (8-week) trajectories of use of the iDAT app among patients with type 2 diabetes mellitus in a primary care setting in Singapore, and identify patient characteristics associated with each trajectory.
methodsA total of 84 patients with type 2 diabetes mellitus from a public primary care clinic in Singapore who had not previously used the iDAT app were enrolled. The app was demonstrated and patients' weekly use of the app was monitored over 8 weeks. Weekly use was defined as any record in terms of food entry or exercise workout entry in that week. Information on demographics, diet and exercise motivation, diabetes self-efficacy (Diabetes Empowerment Scale-Short Form), and clinical variables (body mass index, blood pressure, and glycosylated hemoglobin/HbA1c) were collected at baseline. iDAT app use trajectories were delineated using latent-class growth modeling (LCGM). Association of patient characteristics with the trajectories was ascertained using logistic regression analysis.
resultsThree iDAT app use trajectories were observed: Minimal Users (66 out of 84 patients, 78.6%, with either no iDAT use at all or use only in the first 2 weeks), Intermittent-Waning Users (10 out of 84 patients, 11.9%, with occasional weekly use mainly in the first 4 weeks), and Consistent Users (8 out of 84 patients, 9.5%, with weekly use throughout all or most of the 8 weeks). The adjusted odds ratio of being a Consistent User, relative to a Minimal User, was significantly higher for females (OR 19.55, 95% CI 1.78-215.42) and for those with higher exercise motivation scores at baseline (OR 4.89, 95% CI 1.80-13.28). The adjusted odds ratio of being an Intermittent-Waning User relative to a Minimal User was also significantly higher for those with higher exercise motivation scores at baseline (OR 1.82, 95% CI 1.00-3.32).
conclusionsThis study provides insight into the nature and extent of usage of a caloric-monitoring app among patients with type 2 diabetes and managed in primary care. The application of LCGM provides a useful framework for evaluating future app use in other patient populations.
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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.