Use of Psychedelics for Pain: A Scoping Review
Bibliographic record
Abstract
Chronic pain is a public health concern that affects approximately 1.5 billion people globally. Conventional therapeutic agents including opioid and non-opioid analgesics have been associated with adverse side effects, issues with addiction, and ineffective analgesia. Novel agents repurposed to treat pain via different mechanisms are needed to fill the therapeutic gap in chronic pain management. Psychedelics such as lysergic acid diethylamide and psilocybin (the active ingredient in psychedelic mushrooms) are thought to alter pain perception through direct serotonin receptor agonism, anti-inflammatory effects, and synaptic remodeling. This scoping review was conducted to identify human studies in which psychedelic agents were used for the treatment of pain. Twenty-one articles that assessed the effects of psychedelics in treating various pain states were included. The present scarcity of clinical trials and small sample sizes limit their application for clinical use. Overall, psychedelics appear to show promise for analgesia in patients with certain headache disorders and cancer pain diagnoses. Future studies must aim to examine the combined effects of psychotherapy and psychedelics on chronic pain.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".