The Use of Psychedelics for Grief Following Death due to Advanced Illness: A Scoping Review
Bibliographic record
Abstract
Background: There is promising evidence that psychedelic-assisted psychotherapy may be a powerful new treatment approach for mortality-related distress. However, less is known about the possible benefits for people experiencing grief. Aim: To explore what is known about using psychedelics to attend to grief following death due to advanced illness. Design: This scoping review followed Arskey and O’Malley’s methodological framework and adheres to the PRISMA-ScR reporting guidelines. Searches were conducted in seven databases in April 2023, and updated in December 2023. No limits or filters were applied. The quality of the papers was not appraised. Results: Of the 4614 records screened, 18 reports were included. Seven are empirical investigations of the impact of psychedelics on grief. This literature is informed by different epistemologies, ontologies, and conceptualizations of grief, adding a layer of complexity and potential for conflict to arise due to differing perspectives. Overall, there is little high-quality evidence about the use of psychedelics to attend to grief. However, across the empirical studies, positive outcomes were generally reported (i.e., reduction in grief symptom severity), with few studies reporting adverse events or negative outcomes. Conclusion: There is not a strong evidence base to guide clinical recommendations for applying psychedelics to the problem of grief at this time. Moving forward, psychedelic authors and researchers can explicitly situate their work (e.g., position, interests) to assist with interpretability of findings, and integrate theory from the field of grief studies, which may require collaborations with grief therapists and theorists to guide future work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".