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JMIR human factors
By Stolberg L, Hieber D, Kuhn P and 2 others.
Esports athletes face substantial psychological stressors comparable to those experienced by traditional athletes, yet mental health tools tailored to their specific needs remain scarce.
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This study addresses this critical gap by introducing MindAthlete, a prototype for a user-centered mobile health (mHealth) app intended to enhance mental health monitoring and support among esports athletes.
A 3-stage development process was used over 5 months. First, structured qualitative interviews were conducted online via Google Meet with 7 experienced (sports) psychologists recruited through snowball sampling within professional esports networks. The interviews explored current mental health monitoring practices and key feature requirements for MindAthlete. Data were analyzed using Mayring's approach to qualitative content analysis. Subsequently, a 32-screen high-fidelity prototype was developed in Figma based on the identified requirements. In the final stage, usability testing was conducted with 25 semiprofessional and professional esports athletes recruited via convenience and snowball sampling. Participants interacted with the Figma prototype and completed an online questionnaire administered via LimeSurvey, which included demographic items, the validated 10-item System Usability Scale (SUS) rated on a 5-point Likert scale, and open-ended questions on navigation, aesthetics, and overall functionality. Inferential analyses included Mann-Whitney U tests, Kruskal-Wallis tests, and Spearman correlations. Open-ended responses were analyzed using Mayring's content analysis.
Expert interviews identified 8 core features for mental health monitoring in esports, clustered around 3 themes: continuous self-monitoring, structured assessment, and intervention and insight. Athlete usability testing yielded a median SUS score of 77.5 (IQR 67.5-87.5), classifying usability as "good" and exceeding a benchmark median of 68.3 derived from comparable mHealth apps. No significant differences were found by sex, age, years of professional experience, or prior mHealth usage. Qualitative feedback highlighted strengths including intuitive navigation and appealing aesthetics, alongside areas for improvement such as shorter animations and clearer initial onboarding. However, findings must be interpreted in light of the sample's demographic homogeneity, which limits generalizability to the broader esports population.
This research provides a stakeholder-driven, empirically validated blueprint for esports-specific mental health monitoring via mHealth. Future work will focus on technical implementation, integration of wearable sensor data, and broader evaluations with larger, more diverse samples to confirm generalizability and enhance usability.
Published in JMIR human factors. The abstract is shown as published and remains the work of its authors; read the full article at the source.
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