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• W2973475842 abstract "The objective of this study was twofold: classifying diabetes smartphone apps using content review, and identifying the factors that influence the app download through regression analysis. From Google Play Store, a total of 5557 apps that matched the search criteria ‘diabetes’ were identified and extracted using a structured sheet. Purposeful sampling technique and selection criteria were applied to identify 500 apps, and content review was done to characterize the apps. Multiple regression analysis was employed to find the association between app download and app characteristics. Content analysis revealed that 464 out of the 500 apps (92.8%) were free. The most common app features were monitoring and tracking (39%), treatment information (23%) and nutrition (18%). Two-thirds of the apps were intended for patients. The most common business models were advertising (34%), freemium (20%), and razor-and-blade (19%). Regression results explained the preference for apps that provide nutrition function and monitoring capabilities. As per the study results, factors that boost application download include: high ratings, frequent updating, long standing market presence, and those offered by US companies. Content review highlights the various self-management capabilities offered by diabetes apps. This study adds to the extant literature on mobile application classification by introducing the business model dimension." @default.
• W2973475842 created "2019-09-26" @default.
• W2973475842 creator A5030344278 @default.
• W2973475842 creator A5071040468 @default.
• W2973475842 date "2019-12-01" @default.
• W2973475842 modified "2023-10-10" @default.
• W2973475842 title "Factors influencing the download of mobile health apps: Content review-led regression analysis" @default.
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• W2973475842 doi "https://doi.org/10.1016/j.hlpt.2019.09.001" @default.
• W2973475842 hasPublicationYear "2019" @default.
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