A feature-oriented analysis of developers' descriptions and user reviews of top mHealth applications for diabetes and hypertension. (December 2021)

• Record Type: Journal Article
• Authors: Wang, Shengang; Lee, Hyun Seung; Choi, Wonchan
• Is Part Of: International journal of medical informatics. Volume 156(2021)
• Publication Date: 2021-12
• Subjects: mHealth application -- Diabetes -- Hypertension -- User reviews -- app descriptions -- multiple chronic conditions; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2021.104598
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: The proposed three-layer coding scheme could help analyze features of mHealth apps. mHealth apps for multiple chronic conditions (MCC) should help record different types of user data. mHealth apps for MCC should help export and share desired types of data. Abstract: Background and objective: Diabetes and hypertension are two prevalent and related chronic conditions. To inform the design and development of mobile health applications (mHealth apps) for people living with multiple chronic conditions, this paper examines features mentioned in developers' descriptions and user reviews of mHealth apps, along with users' attitudes toward associated features. Materials and methods: Eleven top apps for diabetes and hypertension were identified from Google Play as of January 2020. Based on a stratified sampling strategy, 1, 100 user reviews were selected to form the final dataset. Developers' descriptions were also collected for analysis. Using the grounded theory approach, we developed a feature-oriented coding scheme, which was used to identify three levels of features mentioned in app descriptions and user reviews: feature group (the highest level), feature type (the second level), and individual feature (the lowest level). Users' attitudes toward app features mentioned in user reviews were also analyzed. Results: Most top-rated apps for diabetes and hypertension under study were multifeatured, incorporating self-management, information sharing, and decision support features. At the feature-group level, most informative user reviews commented on features related to self-management, followed by decision support and information sharing. The four most frequently mentioned feature types were data entry, data export/import, data visualization, and assessment. Users expressed overwhelming positive attitudes toward app features across all feature categories. Based on users' assessments of existing features and requests for additional features, design implications for app development are provided. Conclusions: Despite the diversity of app features provided by mHealth apps and users' primarily positive attitudes toward existing app features, more comprehensive and personalized features are expected by app users to satisfy their health needs. Beyond identifying app features in user reviews, future research may seek more in-depth feedback from real-life patients for app development and design using methods like interviews and focus groups, to further enhance the overall quality of relevant mHealth apps to better support users.