Reliable data collection in participatory trials to assess digital healthcare apps

Abstract

Digital healthcare mobile apps are experiencing exponential growth due to the development of the mobile network and widespread usage of smartphones. Unlike high growth rates, sufficient validated apps are few. Because mobile health apps are low-risk technology, and it tends to reduce regulatory oversight. With this tendency, the apps have a direct trade characteristic between developers and end-users. The existing platforms are not suitable to collect reliable data for evaluating the effectiveness of the apps. Moreover, these platforms only reflect the perspectives of developers and experts, not end-users. For instance, the methods of data collection in clinical trials are not appropriate for participant-oriented assessment of healthcare apps since its complexity and high cost. Thus, we identified a need for a participant-oriented data collection platform for end-users as an interpretable, systematic, and sustainable tool-as a first step to validate the effectiveness of the apps. To collect reliable data in the participatory trial format, we have defined data preparation, storage, and sharing stage. Interpretable data preparation consists of a protocol database system and semantic feature retrieval method to create a protocol without professional knowledge. Collected data reliability weight calculation belongs to the systematic data storage stage. To sustainable data collection, we integrate the weight method and reward distribution function. We validate the methods with 718 of human participants to conduct statistical tests. The validation results showed that the methods have significant differences in the comparative experiment, and we convinced the methods are essential to reliable data collection. Furthermore, we created a web-based system for our pilot platform to collect reliable data in an integrated pipeline. We validate the platform features with existing clinical and pragmatic trial data collection platforms. In conclusion, we show that the method and platform support reliable data collection, forging a path to effectiveness validation of digital healthcare apps. 1/371 Digital healthcare has become one of the most promising fields in the healthcare 2 industry with the widespread popularity of wireless devices such as smartphones. 3Notably, approximately 200 mobile health apps are listed daily in mobile app stores, 4 and investments in digital health are booming [25,89]. While many of the apps are 5 general wellness applications that help users to manage their activities, some healthcare 6 apps claim to improve a symptom or disease directly. The treatments proposed by the 7 apps take the form of information or visual stimuli, which are effectively delivered to 8 users as digital therapy. reSET-O, an 84-day prescription digital therapeutic app for the 9 treatment of opioid use disorder, has been approved by the U.S. Food and Drug 10 Administration (FDA) [51]. Akili Interactive has clinically demonstrated that interactive 11 digital treatment through a video game, which is under review by the FDA, may 12 i...