The emergence of mobile health mHealth products has created a capability of monitoring and managing the health of patients with chronic diseases. These mHealth technologies would not be beneficial unless they are adopted and used by their target users. This study identifies key factors affecting the usage of mHealth apps based on user usage data collected from an mHealth app. Using a dataset collected from an mHealth app named mPower, developed for patients with Parkinson's disease PD , this paper investigated the effects of disease diagnosis, disease progression and mHealth app difficulty level on app usage, while controlling for user information.
App usage is measured by five different activity counts of the app. The results across five measures of mHealth app usage vary slightly. On average, previous professional diagnosis and high user performance scores encourage user participation and engagement, while disease progression hinders app usage. The findings potentially provide insights into better design and promotion of mHealth products and improve the capability of health management of patients with chronic diseases. Studies on the mHealth app usage are critical but sparse because large-scale and reliable mHealth app usage data are limited.
Unlike earlier works based solely on survey data, this research used a large user usage data collected from an mHealth app to study key factors affecting app usage. The methods presented in this study can serve as a pioneering work for the design and promotion of mHealth technologies. The authors thank the mPower and Sage Bionetworks for making the data set available to the research community.
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