Trial reportJMIR mHealth and uHealth2019
Association Between User Engagement of a Mobile Health App for Gout and Improvements in Self-Care Behaviors: Randomized Controlled Trial.
Trial report in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07004231 (Using Gout Buddy to Enhance Dietary Literacy and Gout Management-A Mixed Method Clinical Trial), which is not on this map. Cited by 33 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.
Using Gout Buddy to Enhance Dietary Literacy and Gout Management-A Mixed Method Clinical Trial
Who cites it
33 citing papers in PubMed, 3 syntheses or guidelines pooled it, 55 citations in OpenAlex.
- User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis.RMD open · 2022Pooled it
- Mobile Health Interventions and RCTs: Structured Taxonomy and Research Framework.Journal of medical systems · 2022Pooled it
- The Impact of mHealth-Based Continuous Care on Disease Knowledge, Treatment Compliance, and Serum Uric Acid Levels in Chinese Patients With Gout: Randomized Controlled Trial.JMIR mHealth and uHealth · 2024Trial
- Evaluation of the effectiveness of the FOCUS ADHD App in monitoring adults with attention-deficit/hyperactivity disorder.European psychiatry : the journal of the Association of European Psychiatrists · 2023Trial
- Influencing factors of continuance intention of medical applications for the elderly.Scientific reports · 2026Article
- Knowledge, attitudes, and practices regarding gout management among patients in Xiamen, China: a cross-sectional study.Frontiers in public health · 2026Article
- Validity and reliability assessment of the Persian version of the User Mobile Application Rating Scale.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2026Article
- Experiences of social support and the role of engagement in a digital educational support group for adolescent mothers' health in the Dominican Republic.PLOS digital health · 2025Article
- Determinants of Self-Management Behavior in Gout: A Scoping Review.Arthritis care & research · 2025Article
- Between regulatory functions and emotional burden: balancing engagement in digital health interventions for self-care in chronic illness.Frontiers in psychology · 2025Article
- Digital-Based Nutrition Interventions Employing the Dietary Approaches to Stop Hypertension (DASH) Diet: A Systematic Scoping Review.International journal of hypertension · 2025Review
- Persian adaptation and validation of the user version of The Mobile Application Rating Scale (uMARS).PloS one · 2025Article
- Exploring Participants' Experiences of Digital Health Interventions With Qualitative Methods: Guidance for Researchers.Journal of medical Internet research · 2024Article
- Evidence for telemedicine heterogeneity in rheumatic and musculoskeletal diseases care: a scoping review.Clinical rheumatology · 2024Article
- Exploring the Feasibility and Initial Impact of an mHealth-Based Disease Management Program for Chronic Ischemic Heart Disease: Formative Study.JMIR formative research · 2024Article
- Empowering Potential of the My Assistive Technology Guide: Exploring Experiences and User Perspectives.Disabilities (Basel, Switzerland) · 2024Article
- Article
- Support needs of gout patients and suitability of eHealth to address these needs.Rheumatology advances in practice · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile health (mHealth) apps represent a promising approach for improving health outcomes in patients with chronic illness, but surprisingly few mHealth interventions have investigated the association between user engagement and health outcomes. We aimed to examine the efficacy of a recommended, commercially available gout self-management app for improving self-care behaviors and to assess self-reported user engagement of the app in a sample of adults with gout.
objectiveOur objective was to examine differences in self-reported user engagement between a recommended gout app (treatment group) and a dietary app (active control group) over 2 weeks as well as to examine any differences in self-care behaviors and illness perceptions.
methodsSeventy-two adults with gout were recruited from the community and three primary and secondary clinics. Participants were randomized to use either Gout Central (n=36), a self-management app, or the Dietary Approaches to Stop Hypertension Diet Plan (n=36), an app based on a diet developed for hypertension, for 2 weeks. The user version of the Mobile Application Rating Scale (uMARS, scale: 1 to 5) was used after the 2 weeks to assess self-reported user engagement, which included an open-ended question. Participants also completed a self-report questionnaire on self-care behaviors (scale: 1-5 for medication adherence and diet and 0-7 for exercise) and illness perceptions (scale: 0-10) at baseline and after the 2-week trial. Independent samples t tests and analysis of covariance were used to examine differences between groups at baseline and postintervention.
resultsParticipants rated the gout app as more engaging (mean difference -0.58, 95% CI -0.96 to -0.21) and more informative (mean difference -0.34, 95% CI -0.67 to -0.01) than the dietary app at the 2-week follow-up. The gout app group also reported a higher awareness of the importance of gout (mean difference -0.64, 95% CI -1.27 to -0.003) and higher knowledge/understanding of gout (mean difference -0.70, 95% CI -1.30 to -0.09) than the diet app group at follow-up. There were no significant differences in self-care behaviors between the two groups postintervention. The gout app group also demonstrated stronger negative beliefs regarding the impact of gout (mean difference -2.43, 95% CI -3.68 to -1.18), stronger beliefs regarding the severity of symptoms (mean difference -1.97, 95% CI -3.12 to -0.82), and a stronger emotional response to gout (mean difference -2.38, 95% CI -3.85 to -0.90) at follow-up. Participant feedback highlighted the importance of tracking health-related information, customizing to the target group/individual, providing more interactive features, and simplifying information.
conclusionsParticipants found the commercially available gout app more engaging. However, these findings did not translate into differences in self-care behaviors. The gout app group also demonstrated stronger negative illness perceptions at the follow-up. Overall, these findings suggest that the development of gout apps would benefit from a user-centered approach with a focus on daily, long-term self-care behaviors as well as modifying illness beliefs.
trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12617001052325; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373217.
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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.