Social acceptability of psilocybin-assisted therapy for existential distress at the end of life: A population-based survey
Bibliographic record
Abstract
Background: Internationally, there is a growing interest in the potential benefits of psilocybin-assisted therapy to treat existential distress at the end of life. However, the social acceptability of this therapy is not yet well known. Aim: This study assesses the social acceptability of the medical use of psilocybin to treat existential distress at the end of life. Design: An online survey was conducted in Canada between November 23 and December 4, 2022. The questionnaire included items pertaining to perceptions, attitudes and concerns towards psilocybin-assisted therapy to treat existential distress at the end of life. Participants: The sample ( n = 2800) was stratified by province, age and sex. Participants were adults from four provinces of Canada: Québec, Ontario, Alberta and British Columbia. Results: Overall, 79.3% considered psilocybin-assisted therapy a reasonable medical choice for a patient suffering from existential distress at the end of life, 84.8% agreed that the public health system should cover the costs of the intervention and 63.3% would welcome the legalisation of psilocybin for medical purposes. Previous psilocybin use ( p < 0.0001, for all dependent variables), exposure to palliative care ( p < 0.05, for all dependent variables) and a progressive political orientation ( p < 0.05, for all dependent variables) were associated with more favourable attitudes towards psilocybin-assisted therapy at the end of life. Conclusion: The social acceptability of psilocybin-assisted therapy for existential distress at the end of life is rather high in Canada. These findings may contribute to efforts to mobilise resources and improve access to this emerging therapy in palliative and end of life care settings.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".