ArticleJMIR mHealth and uHealth2022
The Quality of Indian Obesity-Related mHealth Apps: PRECEDE-PROCEED Model-Based Content Analysis.
Article in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Evaluation of Mobile Intermittent Fasting Applications in Chinese App Stores: Quality Evaluations and Content Analysis.JMIR mHealth and uHealth · 2025Article
- Exploring Heart Disease-Related mHealth Apps in India: Systematic Search in App Stores and Metadata Analysis.Journal of medical Internet research · 2025Article
- Assessment of Eye Care Apps for Children and Adolescents Based on the Mobile App Rating Scale: Content Analysis and Quality Assessment.JMIR mHealth and uHealth · 2024Article
- Effects of multicomponent exercise nursing intervention in elderly stroke patients with frailty: a randomized controlled trial.Frontiers in medicine · 2024Article
- Assessing the accessibility and quality of mobile health applications for the treatment of obesity in the German healthcare market.Frontiers in health services · 2024Review
- Don't judge a book or health app by its cover: User ratings and downloads are not linked to quality.PloS one · 2024Article
- Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany.NPJ digital medicine · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe prevalence of obesity in India is increasing at an alarming rate. Obesity-related mHealth apps have proffered an exciting opportunity to remotely deliver obesity-related information. This opportunity raises the question of whether such apps are truly effective.
objectiveThe aim of this study was to identify existing obesity-related mHealth apps in India and evaluate the potential of the apps' contents to promote health behavior change. This study also aimed to discover the general quality of obesity-related mHealth apps.
methodsA systematic search for obesity-related mHealth apps was conducted in both the Google Play Store and the Apple App Store. The features and quality of the sample apps were assessed using the Mobile Application Rating Scale (MARS) and the potential of the sample apps' contents to promote health behavior change was assessed using the PRECEDE-PROCEED Model (PPM).
resultsA total of 13 apps (11 from the Google Play Store and 2 from the Apple App Store) were considered eligible for the study. The general quality of the 13 apps assessed using MARS resulted in mean scores ranging from 1.8 to 3.7. The bivariate Pearson correlation between the MARS rating and app user rating failed to establish statistically significant results. The multivariate regression analysis result indicated that the PPM factors are significant determinants of health behavior change (F
conclusionsIn general, mHealth apps are found to be more effective when they are based on theory. The presence of PPM factors in an mHealth app can greatly influence the likelihood of health behavior change among users. So, we suggest mHealth app developers consider this to develop efficient apps. Also, mHealth app developers should consider providing health information from credible sources and indicating the sources of the information, which will increase the perceived credibility of the apps among the users. We strongly recommend health professionals and health organizations be involved in the development of mHealth apps. Future research should include mHealth app users to understand better the apps' effectiveness in bringing about health behavior change.
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