JMIR Publications

ABSTRACT

Background:

Pharmacotherapy for common mental disorders is often limited by adverse effects and suboptimal adherence. While music therapy offers a promising nonpharmacological alternative, its clinical utility is currently constrained by limited accessibility, variability in efficacy, and a lack of mechanistic clarity.

Objective:

To describe the development of Individualized (Receptive) Music Therapy (IMT)—an artificial intelligence (AI)–enabled, neuroscience-guided intervention—and to evaluate its efficacy, safety, and biological mechanisms in adults with major depressive disorder (MDD), generalized anxiety disorder (GAD), and primary insomnia (PI).

Methods:

This multistage research program conducted at Peking Union Medical College Hospital comprises four sequential studies: (1) a cross-sectional pilot study (n=20) to benchmark clinical and electroencephalography (EEG) features; (2) a prospective cohort study (n=80) evaluating the efficacy and safety of non-individualized receptive music therapy; (3) a pilot randomized clinical trial (RCT; n=200) comparing non-individualized therapy with IMT over 8 weeks; and (4) a prospective validation study (n=60) of a treatment-response prediction model. Participants include adults aged 18 to 60 years with mild-to-moderate MDD, GAD, or PI, alongside healthy controls. In the non-individualized arm, participants engage in daily 30-minute listening sessions using therapist-curated instrumental tracks designed to regulate mood. In the IMT arm, an AI generation pipeline creates bespoke instrumental tracks based on weekly participant preferences regarding tempo, instrumentation, and emotional valence. The primary outcomes are the response rate at 8 weeks (defined as ≥50% reduction in MADRS, HAMA, or PSQI scores) and changes in quantitative EEG characteristics. Secondary outcomes include continuous symptom severity scores and safety metrics (adverse events, psychotogenic effects, and suicidality).

Results:

Ethical approval was obtained from the Ethics Review Committee of the Peking Union Medical College Hospital (I-24PJ0689). Written informed consent is obtained from all participants. The recruitment started on 24 May 2024, and the study is expected to be completed by December 2027. Results will be disseminated via peer-reviewed publications, conference presentations, and stakeholder communications. Authorship follows the ICMJE criteria. The participant-level dataset will be available upon reasonable request.

Conclusions:

This protocol outlines a translational framework to overcome the "therapeutic ceiling" of traditional music therapy. By integrating generative AI with neurophysiological monitoring, this program aims to establish a scalable, precision-medicine approach to mental health care that is both clinically effective and biologically grounded. Clinical Trial: ChiCTR2400083246 (Chinese Clinical Trial Registry).