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Development and assessment of a psychedelic-assisted therapy music playlist for clinical trials

Theory, intentionality, and metrics

Bibliographic Data

ID7473777
AuthorsRafaelle L Lancelotta (0000-0002-7789-3463, The Ohio State University), Paul Nagib (0000-0001-8538-3116, Emory University), Paul B Nagib (Emory University School of Medicine, United States), B Armstrong (0000-0003-0869-7511, The Ohio State University), Stacey B Armstrong (The Ohio State University – Center for Psychedelic Drug Research and Education, College of Social Work, Columbus, Ohio, United States), Adam W Levin (0000-0002-9167-462X, The Ohio State University), Alan K Davis (The Ohio State University – Center for Psychedelic Drug Research and Education, College of Social Work, Columbus, Ohio, United States), A B Davis (0000-0002-5648-0889, The Ohio State University)
Year2026
Volume10
Issue2
Pages136-143
Publication date2026-02-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Psychedelic Studies (JOURNAL)
Journal identifiersISSN: 2559-9283 • E-ISSN: 2559-9283
PublisherAkademiai Kiado Zrt (PUBLISHER)
DOI10.1556/2054.2026.00462
OpenAlexW7128677415
LanguageEN
References cited11

Background and Purpose Music plays a central role in psychedelic-assisted therapy, yet few methodologies exist to create and assess therapeutic playlists. This study aimed to illustrate a methodology for developing and evaluating a music playlist for a clinical psilocybin trial using an integrative framework grounded in theory, intentionality, and metrics. Methods A playlist was designed based on clinical experience, phenomenological data, and therapeutic goals across pre-peak, peak, and post-peak phases of psilocybin administration. Each track was evaluated using Spotify's Application Programming Interface (API) metrics (Beats Per Minute, Danceability, Energy, and Valence). In addition, an exploratory human-rated measure of Transcendence was created and included to capture aspects of musical depth not represented by existing API metrics. Together, these tools provided a proof-of-concept model for how intentional playlist design may be supplemented with objective and experiential metrics in future psychedelic-assisted therapy research. Results Most musical features followed the hypothesized emotional arc of the psilocybin experience represented in prior literature. Some deviations occurred, including misclassification of nature-based tracks as high-energy by the Spotify API, highlighting the limitations of algorithmic classification. Transcendence ratings suggested continued emotional depth in the music during post-peak phases. Conclusions This proof-of-concept model demonstrates the value of combining intentional playlist design with exploratory use of algorithmic and experiential metrics. While Spotify metrics may lack stability and generalizability, the integrative approach offers a transparent example that future researchers may adapt and refine for their own clinical and cultural contexts

Artifact (error · Experiential learning · Exploratory research · Interface (matter · Preference · Psilocybin · Value (mathematics · Pain Management and Placebo Effect · Paranormal Experiences and Beliefs · Psychedelics and Drug Studies

  • Effects of Psilocybin-Assisted Therapy on Major Depressive Disorder

    Open Access•A K Davis, Frederick S Barrett et al.•JAMA Psychiatry•2021

  • Hallucinogenic Drugs and Plants in Psychotherapy and Shamanism

    Ralph Metzner•Journal of Psychoactive Drugs•1998

Citation velocityhistorical
Highly citedNo

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Open DOIOpen Access
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