Evaluating mobile mental health apps using the mobile application rating scale (MARS) in the U.S.

Abstract

ABSTRACT Objective The objectives of this study were to comprehensively review and evaluate the quality of mobile mental health apps using the MARS and to identify high-quality apps. Method A quantitative content analysis was undertaken. A systematic search of the U.S. Apple App Store and Google resulted in the selection of 25 mobile mental health applications. Coders evaluated these applications using a set of criteria derived from the literature. The intraclass correlation coefficient was employed to assess two-way mixed interrater reliability. Descriptive statistics, including frequency and mean (SD) scores, were calculated for each criterion. Results MARS has two parts: classification category and app quality criteria. For the classification category, we found the majority of apps (1) focused on relieving negative emotions, (2) relied on principles of Cognitive Behavior Therapy (CBT) and Acceptance and Commitment Therapy (ACT), and (3) offered reminders to perform an activity and required login information. Regarding app quality, the 25 apps scored highest in functionality, followed by aesthetics, engagement, and information among the four categories. Wysa was the highest-scoring mental health app, followed by Woebot and Youper. Discussion The study offers descriptive and technical information about the mobile mental health applications, including their focus, theoretical background, and technical aspects. The findings demonstrates that the majority of these applications are of high quality. Consequently, the results facilitate an objective and comprehensive understanding of commercial mental health mobile apps.