Listener-level aesthetic appraisal in personalized music-listening interventions for older adults: a closed-loop framework

Music-listening interventions yield modest average benefits in later life, but substantial heterogeneity remains unexplained. Existing systems commonly organize music by symptom labels, mood, acoustic features, cultural categories, expert judgment, or preference, and often infer listener response from liking, skips, completion, duration, or mood check-ins. We define listener-level aesthetic appraisal as a person-specific appraisal profile accumulated across listening events and operationalized through event-specific evaluations, distinct from preference, familiarity, autobiographical salience, engagement, exposure, adherence, and therapeutic outcome. For repeated use in personalized music-listening interventions, we propose a provisional, low-burden three-item assessment of meaningfulness, emotional or aesthetic resonance, and overall satisfaction. Each item is rated from 0 ("not at all") to 4 ("very much") immediately after listening. Direct appraisal measurement is intended for listeners able to provide interpretable self-report, independently or with support; a separate observational care pathway is proposed when such self-report is unavailable, without treating observation as first-person appraisal. We then outline a two-component closed loop comprising a quality-controlled repertoire-side candidate space and a listener-side component with event-specific appraisal, illustrative hierarchical ordinal modelling, Bayesian updating, constrained probabilistic selection, and separate computational and participant-level stopping rules. The framework is illustrative and testable, not a fitted or validated algorithm. We propose prospective tests of incremental predictive value, adaptive versus static matching, and the balance among aesthetic fit, intervention goals, safety, autonomy, consent, and assessment burden.