Acute and Sustained Reductions in Loss of Meaning and Suicidal Ideation Following Psilocybin-Assisted Psychotherapy for Psychiatric and Existential Distress in Life-Threatening Cancer
Bibliographic record
Abstract
People with advanced cancer are at heightened risk of desire for hastened death (DHD), suicidal ideation (SI), and completed suicide. Loss of Meaning (LoM), a component of demoralization, can be elevated by a cancer diagnosis and predicts DHD and SI in this population. We completed a randomized controlled trial in which psilocybin-assisted psychotherapy (PAP) produced rapid and sustained improvements in depression, demoralization, and hopelessness in people with cancer. Converging epidemiologic and clinical trial findings suggests a potential antisuicidal effect of this treatment. To probe our hypothesis that PAP relieves SI through its beneficial impacts on depression and demoralization (LoM in particular), we performed secondary analyses assessing within- and between-group differences with regard to LoM and an SI composite score. Among participants with elevated SI at baseline, PAP was associated with within-group reductions in SI that were apparent as early as 8 h and persisted for 6.5 months postdosing. PAP also produced large reductions in LoM from baseline that were apparent 2 weeks after treatment and remained significant and robust at the 6.5 month and 3.2 and 4.5 year follow-ups. Exploratory analyses support our hypothesis and suggest that PAP may be an effective antisuicidal intervention following a cancer diagnosis due to its positive impact on hopelessness and demoralization and its effects on meaning-making in particular. These preliminary results implicate psilocybin treatment as a potentially effective alternative to existing antidepressant medications in patients with cancer that are also suicidal, and warrant further investigation in participants with elevated levels of depression and suicidality.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".