Effect of self-monitoring on long-term patient engagement with mobile health applications.
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Abstract
Despite the growing adoption of the mobile health mHealth applications apps few studies address concerns with low retention rates This study aimed to investigate how the usage patterns of mHealth app functions affect user retention We collected individual usage logs for 1 439 users of single tethered personal health record app which spanned an 18 months period from August 2011 to January 2013 The user logs contained timestamps whenever an individual uses each function which enables us to identify the usage patterns based on the intensity of using a particular function in the app We then estimated how these patterns were related to 1 the app usage over time using the random effect model and 2 the probability of stopping the use of the application using the Cox proportional hazard model The analyses suggested that the users utilize the app most at the time of the adoption and gradually reduce their usage over time The average duration of use after starting the app was 25 62 weeks SD 18 41 The degree of the usage reduction however decreases as the self monitoring function is more frequently used coefficient 0 002 P 0 013 none of the other functions has this effect Moreover engaging with the self monitoring function frequently coefficient 0 18 P 0 003 and regularly coefficient 0 10 P 0 001 significantly also reduces the probability of abandoning the application Specifically the estimated survival rate indicates that after 40 weeks since the adoption the probability of the regular users of self monitoring to stay in use was about 80 while that of non user was about 60 This study provides the empirical evidence that sustained use of mHealth app is closely linked to the regular usage on self monitoring function The implications can be extended to the education of users and physicians to produce better outcomes as well as application development for effective user interfaces