AI-Assisted Classical Piano Intervention for Enhancing Resilience, Mindfulness, and Emotional Processing in Young...

Mental-health-oriented interventions increasingly require structured, scalable, and nonpharmacological formats that can strengthen psychological functioning without reducing clinician oversight. This study examined whether a therapist-led, AI-assisted classical piano intervention could produce stronger process-level psychological gains than matched therapist-led piano instruction without adaptive AI feedback among young adults diagnosed with mild-to-moderate anxiety or depression. A randomized controlled mixed-methods design was used with 120 Mandarin-speaking participants aged 18-30 years assigned to either an AI-assisted condition or a non-AI control condition. Over a 10-week program, both groups completed weekly 90-min supervised sessions, and pretest/post-test changes were assessed in resilience, mindfulness, and music-related emotional processing. Quantitative data were analyzed using 2 × 2 mixed repeated-measures ANOVA and follow-up tests, while post-intervention interviews from a stratified experimental subsample were analyzed using interpretative phenomenological analysis. The findings showed significant improvement in both groups; however, the AI-assisted condition demonstrated larger gains across all three primary outcomes, together with a steeper trajectory of weekly musical performance development. Engagement indicators within the AI-assisted group were positively associated with psychological improvement. Qualitative findings reinforced this pattern, with emotional release, increased self-awareness, and stronger motivation to continue practice emerging as the most frequent themes. The study suggests that AI can contribute meaningfully to music-based intervention in supervised contexts, not as an autonomous agent but as an adaptive feedback layer. From a practical viewpoint, the model provides a viable framework for structured mental health-focused practice in various contexts.