What predicts meditation app engagement? an evaluation of user characteristics and motivation

Objective: Mindfulness meditation apps are associated with significant health benefits, yet many new app subscribers have low engagement and are unlikely to attain these benefits. This study examined the user characteristics that predict meditation app usage during the first eight weeks after subscribing. Methods & Measures: New meditation app subscribers (N = 304) completed a baseline survey which measured demographics, personality traits, intrinsic motivation for meditation, and symptoms of stress, anxiety, and depression, and objective app usage data were collected over eight weeks. Negative binomial, logistic, and ordinary least squares linear regression models assessed associations between user characteristics and five different outcomes 1) days with any session, 2) average min/day of any session, 3) completing any meditation session, 4) days with any meditation sessions, and 5) average min/day of meditation. Results: Strong intrinsic motivation was associated with greater odds of completing any meditation session (OR = 3.63, p <.01), more days with meditation sessions (IRR = 1.75, p <.01), and greater average min/day of meditation (B = 0.32, p <.01). The effort and pressure subdomains of intrinsic motivation were also significant predictors of app usage. Men had more meditation days (IRR = 2.13, p <.01) than women, and a mental health diagnosis was associated with longer daily meditation durations (B = 0.41, p =.038). Conclusion: Intrinsic motivation is an important mechanism for maintaining an app-based meditation practice, along with gender and chronic health diagnoses. App developers and researchers should consider tailoring content or providing additional support to users based on these characteristics.