Therapeutic Use of Psilocybin in Depression: a Systematic Review of Clinical Evidence
Bibliographic record
Abstract
BACKGROUND: Major depressive disorder (MDD) is a significant public health concern, and current treatments often have limitations in effectiveness and adherence. Psilocybin, a psychedelic compound found in certain mushrooms, is being explored as a potential treatment for depression. It primarily acts through the serotonin 5-HT2A receptor but interacts with 5-HT1A and 5-HT2C receptors. Its precise mechanisms remain under investigation. OBJECTIVES: (1) To consolidate evidence on psilocybin’s efficacy and safety for depression and the role of 5HT2a, (2) to identify limitations in the literature, and (3) to highlight areas needing further research. METHODS: This systematic review follows PRISMA guidelines and analyses 22 studies, including randomised controlled trials (RCTs) and open-label studies. The studies cover various populations, including individuals with treatment-resistant depression, different dosing regimens, and adjunctive therapies. RESULTS: Psilocybin therapy shows substantial and rapid antidepressant effects, often after one or two sessions with psychological support. Improvements are sustained for weeks or months in many cases. Psilocybin is generally well-tolerated, with mild adverse effects such as anxiety during administration and transient headaches, which are manageable in controlled settings. CONCLUSIONS: Psilocybin demonstrates promise as a novel treatment for depression, especially for individuals unresponsive to conventional antidepressants. Further research is needed to refine dosing, explore long-term effects, and understand its mechanisms of action.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".