Risks and benefits of psilocybin use in people with bipolar disorder: An international web-based survey on experiences of ‘magic mushroom’ consumption
Bibliographic record
Abstract
Background:Psilocybin, the primary psychoactive component of psychedelic ‘magic mushrooms’, may have potential for treating depressive symptoms, and consequent applications for bipolar disorder (BD). Knowledge of the risks and benefits of psilocybin in BD is limited to case studies.Aim:To support the design of clinical trials, we surveyed experiences of psilocybin use in people with BD.Methods:An international web-based survey was used to explore experiences of psilocybin use in people with a self-reported diagnosis of BD. Quantitative findings were summarised using descriptive statistics. Qualitative content analysis was used to investigate free-text responses, with a focus on positive experiences of psilocybin use.Results:A total of 541 people completed the survey (46.4% female, mean 34.1 years old). One-third (32.2%; n = 174) of respondents described new/increasing symptoms after psilocybin trips, prominently manic symptoms, difficulties sleeping and anxiety. No differences in rates of adverse events overall were observed between individuals with BD I compared to BD II. Use of emergency medical services was rare (n = 18; 3.3%), and respondents (even those who experienced adverse effects) indicated that psilocybin use was more helpful than harmful. Quantitative findings elaborated on perceived benefits, as well as the potential for psilocybin trips to contain both positively and negatively received elements.Conclusions:The subjective benefits of psilocybin use for mental health symptoms reported by survey participants encourage further investigation of psilocybin-based treatments for BD. Clinical trials should incorporate careful monitoring of symptoms, as data suggest that BD symptoms may emerge or intensify following psilocybin use.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".