What do health professionals think about implementing psilocybin-assisted therapy in palliative care for existential distress? A World Café qualitative study
Bibliographic record
Abstract
OBJECTIVES: Promising studies show that psilocybin-assisted therapy relieves existential distress in patients with serious illnesses, a difficult condition to treat with current treatment options. There is growing interest in this therapy in palliative care. Canada recently amended its laws to allow physicians to request psilocybin for end-of-life distress. However, barriers to access remain. Since implementing psilocybin-assisted therapy within palliative care depends on the attitudes of healthcare providers willing to recommend it, they should be actively engaged in the broader discussion about this treatment option. We aimed (1) to identify issues and concerns regarding the acceptability of this therapy among palliative care professionals and to discuss ways of remedying them and (2) to identify factors that may facilitate access. METHODS: A qualitative study design and World Café methodology were adopted to collect data. The event was held on April 24, 2023, with 16 palliative care professionals. The data was analyzed following an inductive approach. RESULTS: Although participants were interested in psilocybin-assisted therapy, several concerns and needs were identified. Educational and certified training needs, medical legalization of psilocybin, more research, refinement of therapy protocols, reflections on the type of professionals dispensing the therapy, the treatment venue, and eligibility criteria for treatment were discussed. SIGNIFICANCE OF RESULTS: Palliative care professionals consider psilocybin-assisted therapy a treatment of interest, but it generates several concerns. According to our results, the acceptability of the therapy and the expansion of its access seem interrelated. The development of guidelines will be essential to encourage wider therapy deployment.
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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 | 0.029 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".