Ostrand · Journal of psychopharmacology (Oxford, England) 2026 · retrospective cross-sectional survey and machine learning classification · n=>200

Defining 'psychedelic'.

Cited 2 times in the scientific literature.

Level 4 - case-series / case-control

Cross-sectional retrospective survey of subjective drug experiences.

PubMed 42605589 · doi:10.1177/02698811261464986 · record verified 2026-08-26

What was done

Over 200 participants with personal experience with psilocybin, ketamine, and MDMA rated Delphi-generated subjective rating scale items for all three substances. The authors performed factor analyses to identify dimensions of subjective experience and trained a machine-learning classifier to predict the drug taken based on reported effects.

What was found

Factor analyses identified three or four independent dimensions of subjective experience. The machine-learning classifier successfully predicted the specific drug from subjective effects, finding distinct profiles: psilocybin was characterized by visions and psychological insight, ketamine by dissociation, and MDMA by pro-social and loving feelings. Quantitative accuracy metrics, factor loadings, and effect sizes were not reported in the abstract.

Why it matters

This study provides an empirical phenomenological basis for taxonomically classifying psychedelics, identifying psilocybin as an exemplar psychedelic distinct from dissociatives and empathogens.

Limits

The study depends on retrospective self-report from naturalistic, non-standardized drug use with uncontrolled doses, settings, and recall bias. Exact participant numbers, population demographics, and statistical performance values are omitted from the abstract.

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