Group Retreat Psilocybin Therapy for People with Metastatic Cancer with Anxiety and Depression: A Rite of Passage Facilitation Model for a Phase 1/2 Study
Bibliographic record
Abstract
Background: Psilocybin therapy is an emerging treatment for cancer-related anxiety, depression, and existential distress. Most clinical trials to date have studied individual models of psilocybin therapy, but group models may offer increased access and benefits of community. Purpose: This technical report describes a group facilitation model developed for an food and drug administration (FDA)-approved Phase 1 to 2 clinical trial that recruited people with metastatic cancer who had moderate or severe symptoms of anxiety or depression in which psilocybin was administered at a 3-day, in-person retreat. Results: The facilitation model we developed for this intervention is based on anthropological studies of ritual, specifically rites of passage, to develop a secular ritual with therapeutic aims. Using rites of passage terminology, "separation" corresponds to preparation, "liminal" corresponds to the psilocybin dosing session, and "reincorporation" corresponds to integration. In our usage, the term "ritual" refers to intentionally structured, symbolic acts that embody and reinforce shared meaning, guiding participants through experiences that may otherwise feel unbounded or overwhelming. In the group psilocybin retreat model, ritual functions both psychologically-by supporting emotional regulation, orientation, and meaning-making-and communally-by embedding the individual's process within a shared field of intention and care. Conclusion: To our knowledge this is the first FDA-approved clinical trial of a secular ritual-based group facilitation model for psychedelic therapy that is associated with empirically demonstrated safety and efficacy outcomes.
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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 | 0.013 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".