Psychedelic Treatment with Psilocybin: Addressing Medical Malpractice Risk and Physicians’ Concerns
Bibliographic record
Abstract
Psychedelic treatment with psilocybin is receiving increased attention following clinical trials showing it may help treat end-of-life anxiety, depression, and several other conditions. Despite this, physicians may be reluctant to prescribe psilocybin and carry out psilocybin treatment because of the stigma surrounding psychedelics and the potential for medical malpractice liability. This paper explores whether psilocybin treatment gives rise to a risk of medical malpractice liability for physicians. Following an overview of psilocybin treatment and its regulatory regime in Canada, exploratory vignettes are used to highlight the relevance and limits of malpractice claims. This paper argues that the lack of established medical standards, standardized training, and credentialing contribute to liability risks surrounding psilocybin treatment. More clinical trials, meta-studies of research analyses, and knowledge sharing will help to develop training programs and medical standards of practice to better realize psilocybin's potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".