Mobile health applications for epilepsy in Indian app stores: A systematic review and content analysis using the mobile app rating scale

Objective: The growing prevalence of smartphones may prompt individuals with epilepsy to pursue unfulfilled healthcare requirements through mobile health (mHealth) apps, but the content and quality of these mHealth apps are rarely analysed. Hence, this study aimed to identify and assess the quality of epilepsy apps for patients with epilepsy (PWE), their caregivers, and healthcare practitioners (HCPs) available in the Play Store and App Store of India. Methods: We performed a systematic search on the Google Play Store and Apple App Store of India to identify the mHealth apps for epilepsy which were released and updated till May 2023. The identified applications were downloaded and the quality was assessed using a Mobile app rating scale (MARS) for the overall quality, Aesthetics, Engagement, Functionality, and Information by three independent reviewers. The intraclass correlation coefficient (ICC) was calculated to assess the interrater reliability between the reviewers. An unpaired t -test was calculated to analyse the difference in mean scores for Android and iOS applications. Results: The systematic search yielded a total of 2518 apps, out of which 26 were selected for inclusion in the study. Among these, 9 apps were compatible with Android, 11 with iOS, and 6 on both platforms. The mean (SD) MARS score of the apps was 3.5 (0.6) and the ICC for the overall app quality was 0.90 (95% CI: 0.82 -0.96). Overall, apps scored highest in functionality (3.9), followed by aesthetics (3.6), information (3.3), and engagement (3.2). Among the included apps, the overall quality score was found to be higher for iOS apps than Android (MD = 0.54; 95% CI: 0.02 - 1.07; p -value: 0.042). Conclusion: Our study identified twenty-six mHealth applications for epilepsy that integrated various aspects of epilepsy self -management. The results of this study emphasize the importance of ensuring that current and future applications offer evidence -based information, integrate features that align with patient preferences, and generate evidence regarding the effectiveness of application usage.