On-demand therapy 24/7! Mental mHealth app features and social metrics as predictors of use

This study investigates social metrics and features of mental health mobile applications (mHealth apps), a growing digital health tool used by individuals often facing social stigma, barriers to care, and the need for privacy-preserving support. Drawing on an app-derived dataset of 434 mental mHealth apps, we developed a conceptual framework to examine a comprehensive set of 35 app metrics and feature characteristics relevant to mHealth apps' user ratings, functionality, ease-of-use, credibility, privacy assurance, and monetization and test whether these app attributes can explain the patients' intention-to-use (download) these apps. Data collection provides a detailed map of these apps current state-of-the-art. Results indicate that app downloads positively relate to stars rating and user evaluations, app's description length, number of screenshots and readability in the app store, app's age, recent updates and developer information. Interestingly, features related to functional support, privacy, monetization and expert endorsement are not found significant. These findings offer preliminary guidance for developers and organizations aiming to create effective mental mHealth apps, while also advancing the dialogue on assessment criteria to support informed choices by patients and clinicians. By emphasizing objective app data and design features, we highlight how digital health tools shape help-seeking behaviours, particularly among vulnerable populations.