Prospective Preference Assessment for the Psilocybin for Enhanced Analgesia in Chronic nEuropathic PAIN (PEACE-PAIN) Trial
Bibliographic record
Abstract
Background: Negative perceptions of psilocybin and challenges of participant enrollment may represent barriers to conducting a randomized controlled trial examining psilocybin for chronic neuropathic pain. Aim: Prior to trial initiation, we aimed to examine patient attitudes toward the trial via a prospective preference assessment. Methods: Twenty-six patients with chronic neuropathic pain participated in a prospective preference assessment comprising quantitative (survey) and qualitative (interview) components. Content analysis was used to inductively and deductively identify factors that would motivate or discourage participation in the proposed trial. Demographics, clinical characteristics, and perceptions of psilocybin were collected to explore differences in characteristics between patients who were willing and unwilling to participate. Results: Survey results showed that most participants (76.9%) were willing to participate in the PEACE-PAIN trial. "Willing" participants reported higher prior psychedelic use (75%) as compared to the "maybe willing" (0%) and "not willing" participants (0%). Interviews indicated that the top two factors that motivated participation included the need for new treatment options (31.7%) and benefits to personal pain management (31.7%). The top two discouraging factors included practical difficulties of research participation (16.7%), and adverse events associated with psilocybin (16.7%). Conclusions: The PEACE-PAIN trial study design is supported by patient survey responses but may benefit from modifications, namely incorporating thorough discussions of the current evidence for efficacy, safety, tolerability, and approaches to address adverse effects of psilocybin. Additionally, the interest in participation by individuals with prior psychedelic use holds important methodological implications for the inclusion/exclusion criteria of the trial.
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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 | 0.045 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".