Efficacy and Safety of Four Psychedelic-Assisted Therapies for Adults with Symptoms of Depression, Anxiety, and Posttraumatic Stress Disorder: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
There has been a resurgence in psychedelic research for managing psychiatric conditions in recent years. This study aimed to present a comprehensive review of the current state of the field by applying a systematic search strategy for articles on the effectiveness and tolerability of four psychedelic-assisted therapies (psilocybin, lysergic acid diethylamide [LSD], 3,4-Methylenedioxymethamphetamine [MDMA], and ayahuasca) for adults with symptoms of depression, anxiety, and posttraumatic stress disorder (PTSD). Psychometric scores and adverse events were pooled using random-effects meta-analysis models with Hedges' g bias-corrected standardized mean differences (g) and rate ratios (RR) with 95% confidence intervals (CI). Bias evaluation followed PRISMA and Cochrane guidelines. Eighteen studies were identified, which suggested that psychedelic therapies were well tolerated and presented a large effect size for the management of depression symptoms in a transdiagnostic population with psilocybin (g = -1.92, 95% CI, -2.73 to -1.11) and MDMA (g = -0.71; 95% CI, -1.39 to -0.03). These are promising results that complement the current literature. However, evidence certainty was low to very low due to methodological limitations, small sample size, blinding, study heterogeneity, and publication bias. These results also highlight the need for more adequately powered studies exploring these novel therapies.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".