No open-access location is known for this record yet.
No open-access location is known for this record yet.
Background: The prevalent use of smartphones has contributed to a rise in mobile gaming addiction, especially in young people. This study aimed to describe the design of an enhanced version of the AI-based mGaming Wellness mobile app, to support young individuals in developing healthy mobile gaming habits. Methods: The study utilised a 4-phased methodology, based on user-centred design principles, the Mobile App Rating Scale, a focus group and in-depth interviews with the app's target audience, and a think-aloud method. Results: The first round of refinement of mGaming Wellness, guided by input from an expert panel, focused on enhancing engagement and information quality. Feedback led to the identification of 5 key components for digital interventions, including mood and sleep trackers, a statistics dashboard, and educational modules tailored to young users' needs. Subsequent user research prompted the simplification of mood trackers and adjustments in educational content to align closely with adolescents' experiences. Usability testing of a high-fidelity prototype highlighted the app's ease of use and identified areas for further improvement, particularly in understanding how to reduce gaming time and effectively manage gaming-related notifications. The refined mGaming Wellness app can be a valuable resource for mental health professionals, educators, and youngsters seeking support with problematic mobile gaming or interested in building healthy digital habits. Discussion: The findings advocate for the user-centred techniques in developing digital health interventions, contributing valuable input for research in mental health app development targeted at adolescents. Future research will evaluate the app's effectiveness in reducing problematic gaming behaviour.
Loading…
Stored only when both papers are in the corpus — 2 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.