Observational studyJMIR mHealth and uHealth2020
Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study.
Observational study in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed, 3 syntheses or guidelines pooled it, 82 citations in OpenAlex.
- Usability of Continuous Glucose Monitoring for Older Adults with Type 2 Diabetes: A Systematic Review.Diabetes technology & therapeutics · 2026Pooled it
- Understanding Adherence to Digital Health Technologies: Systematic Review of Predictive Factors.Journal of medical Internet research · 2025Pooled it
- Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Determinants of the Uptake and Frequency of Use of a Web Portal Digital Health Intervention in Patients With Type 2 Diabetes and/or Coronary Heart Disease: Secondary Analysis of a Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Engagement and predictors of use of a smartphone app for migraine self-management: A secondary analysis of the EMMA trial.Headache · 2026Trial
- Adherence to app-based dose guidance for once-weekly insulin icodec in insulin-naive individuals with type 2 diabetes: Post hoc analysis of ONWARDS 5.Diabetes, obesity & metabolism · 2025Trial
- Insights Into How Digital Health Interventions Shape Outcomes for Emerging Adults Living With Type 1 Diabetes: Qualitative Realist Process Evaluation.Journal of medical Internet research · 2025Trial
- Completion and Compliance Rates for an Intensive mHealth Study Design to Promote Self-Awareness and Self-Care Among Care Partners of Individuals With Traumatic Brain Injury: Secondary Analysis of a Randomized Controlled Trial.JMIR mHealth and uHealth · 2025Trial
- Patterns of Adherence to Home Blood Pressure Monitoring Among Older Adults With Ischemic Heart Disease: An Analysis From the RESILIENT Trial of Mobile Health Cardiac Rehabilitation.Journal of cardiopulmonary rehabilitation and prevention · 2025Trial
- Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial.Journal of medical Internet research · 2024Trial
- A Digital Platform to Support Self-management of Multiple Chronic Conditions (ProACT): Findings in Relation to Engagement During a One-Year Proof-of-Concept Trial.Journal of medical Internet research · 2021Trial
- Early Detection of Lower Adherence to Long-Term e-Diary Recording: A Checkpoint to Target Early Educational Intervention in Seasonal Allergic Rhinitis?Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2026Observational
- Continuous Glucose Monitoring for Personalized Nutrition in Real-World Vively App Users: Retrospective Observational Study.JMIR human factors · 2026Observational
- Real-World Long-Term Engagement With a Mobile App Intervention to Improve Self-Management of Type 2 Diabetes Mellitus in China (SMARTDiabetes): Mixed Methods Study.JMIR mHealth and uHealth · 2026Article
- Developing the i-MoMCARE application in Cambodia: an iterative co-design approach using rapid prototyping.BMJ digital health & AI · 2026Article
- The Convergence of Polymer Science and Predictive Modeling for Noninvasive Glucose Monitoring.Pharmaceutics · 2025Review
- Evaluation of Glycemia Risk Index and Continuous Glucose Monitoring Outcomes Following the Transition to an Advanced Hybrid Closed-Loop System in Type 1 Diabetes.Advances in therapy · 2025Article
- The Effect of a Mobile App (eMOM) on Self-Discovery and Psychological Factors in Persons With Gestational Diabetes: Mixed Methods Study.JMIR mHealth and uHealth · 2025Article
- The impact of digital health technologies on moral responsibility: a scoping review.Medicine, health care, and philosophy · 2025Article
- Effectiveness and Safety of the TRIO Optimal Health Management Program in Patients With Type 2 Diabetes Mellitus Initiating Basal Insulin Therapy: Prospective Observational Real-World Study.Journal of medical Internet research · 2025Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatient support apps have risen in popularity and provide novel opportunities for self-management of diabetes. Such apps offer patients to play an active role in monitoring their condition, thereby increasing their own treatment responsibility. Although many health apps require active user engagement to be effective, there is little evidence exploring engagement with mobile health (mHealth).
objectiveThis study aims to analyze the extent to which users engage with mHealth for diabetes and identify patient characteristics that are associated with engagement.
methodsThe analysis is based on real-world data obtained by Novo Nordisk's Cornerstones4Care Powered by Glooko diabetes support app. User engagement was assessed as the number of active days and using measures expressing the persistence, longevity, and regularity of interaction within the first 180 days of use. Beta regressions were estimated to assess the associations between user characteristics and engagement outcomes for each module of the app.
resultsA total of 9051 individuals initiated use after registration and could be observed for 180 days. Among these, 55.39% (5013/9051) used the app for one specific purpose. The average user activity ratio varied from 0.05 (medication and food) to 0.55 (continuous glucose monitoring), depending on the module of the app. Average user engagement was lower if modules required manual data entries, although the initial uptake was higher for these modules. Regression analyses further revealed that although more women used the app (2075/3649, 56.86%), they engaged significantly less with it. Older people and users who were recently diagnosed tended to use the app more actively.
conclusionsStrategies to increase or sustain the use of apps and availability of health data may target the mode of data collection and content design and should take into account privacy concerns of the users at the same time. Users' engagement was determined by various user characteristics, indicating that particular patient groups should be targeted or assisted when integrating apps into the self-management of their disease.
Indexed as
Identifiers
What OpenQuestion holds
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.