Knowledge, perceptions, and use of psychedelics for mental health among autistic adults: An online survey
Bibliographic record
Abstract
Psychedelics such as psilocybin, LSD, and MDMA have shown promise in treating mental health conditions (e.g., depression, post-traumatic stress disorder) among neurotypical individuals, i.e., typically developing individuals without a diagnosed neurodevelopmental condition. However, their therapeutic potential for treating co-occurring mental-health conditions in autistic individuals remains under-explored. Autistic individuals often face co-occurring mental health challenges but are frequently excluded from clinical trials, creating a gap in effective treatments. This study aimed to explore knowledge, perceptions, and experiences of autistic adults regarding psychedelics. In this survey, "psychedelics" included classical psychedelics such as psilocybin and LSD, as well as MDMA. A cross-sectional online survey was conducted with English-speaking autistic adults. We assessed participants' knowledge of psychedelics, willingness to use them for mental health treatment, and any past psychedelic experiences. Data were analyzed using descriptive statistics and chi-square tests to assess group differences. A total of 424 participants began the survey, with 261 completing it. Nearly half resided in Canada. Participants generally viewed psychedelics positively, with 77.8% expressing a willingness to try them, and 69.7% reported past use-most commonly psilocybin mushrooms. Higher doses and highly meaningful experiences correlated with longer-lasting mental health improvements. Barriers included legal concerns, health risks, and logistical challenges. Participants with prior experience reported greater perceived knowledge and lower perceived risks. Autistic adults in this self-selecting sample demonstrated strong interest in psychedelics as potential treatments for mental health, despite significant barriers to access and research participation. These results highlight the importance of considering education, policy reform, and inclusive research practices to ensure that autistic people have opportunities to explore psychedelic therapies. These findings should be interpreted cautiously, as the sample may not be representative of the broader autistic population. Future trials should optimize dosing and explore long-term benefits of psychedelics in this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".