Psychedelic‐assisted therapy for palliative care within a home treatment setting: A case report
Bibliographic record
Abstract
Key Clinical Message: This case study describes the feasibility and safety of psychedelic-assisted therapy (PAT) as a home-based intervention for a patient with throat cancer experiencing significant existential distress. The patient tolerated the intervention well. This case supports the feasibility and safety of PAT for patients with life-threatening conditions in a home setting. Abstract: Psychedelic-assisted therapy (PAT), as it is practiced today, merges traditional psychotherapeutic techniques with the use of psychedelics such as LSD, psilocybin, or MDMA with the aim of unlocking deeper insights in patients and treating mental conditions that are resistant to other forms of therapy. The present case study describes the safety of PAT as a home-based intervention for a patient with throat cancer experiencing significant existential distress. The patient tolerated the intervention well and was asked to report on measures of anxiety, depression, and distress related to his somatic condition. The observations provided by this clinical case report align with previous findings, suggesting that PAT can be safely applied to potentially provide relief from existential distress in patients with life-threatening conditions. As this is a single-case study, generalizations should be made cautiously. Moreover, placebo effects, expectancy effects, and the natural course of the disease may influence outcomes. Future research should consider controlled trials to ascertain the efficacy and safety of such interventions in diverse 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| 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".