“ <i>Facing Death. . . Now, That’s a Serious Thing to Confront</i> ” A Qualitative Analysis of Patient Perspectives on Psychedelic-Assisted Therapy for Cancer-Related Psychosocial Symptoms
Bibliographic record
Abstract
People living with cancer (PLWC) often face profound existential distress that is insufficiently addressed by conventional psychosocial supports. This qualitative study explored PLWC's attitudes, beliefs, and experiences regarding psychedelic-assisted therapy (PAT) as a novel approach to addressing psychosocial suffering, particularly existential distress. Fifteen participants with varying cancer types and stages were recruited from a national survey. Semi-structured interviews were analyzed using reflexive thematic analysis informed by the Theory of Planned Behavior. Four key themes were identified: (1) Cautious Optimism and Substance-Specific Attitudes Toward Psychedelics reflected varied knowledge, openness, and perceptions of specific agents; (2) Relational and Societal Influences: Stigma, Support, and Cultural Framing; (3) Structural and Systemic Barriers: Cost, Legality, Provider Attitudes, and Unequal Access; and (4) Cancer Context and Psychosocial Needs: Seeking Relief from Existential and Emotional Distress captured the emotional, spiritual, and existential dimensions of living with and beyond cancer. Participants expressed cautious optimism about PAT, driven by unmet needs in conventional care, particularly after active treatment and at advanced stages of cancer, where existential and spiritual concerns often go unaddressed. PAT was seen as a potential adjunct that could meaningfully engage with suffering beyond symptom management. However, concerns about safety, access, and stigma underscore the need for culturally responsive, patient-informed, and equity-focused implementation strategies. Integrating PAT into oncology will require dismantling structural barriers and shifting toward a model of care that embraces the full human experience of serious illness.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".