Increasing the Evaluation and Reporting Rigor of Psychotherapy Interventions in Treatments Involving Psychedelics
Bibliographic record
Abstract
Psychedelic treatments are emerging as promising interventions for many mental health conditions. These interventions are not offered in a standardized fashion across studies and between different healthcare centers. Beyond differences in substances and doses, there is also a great heterogeneity in the interventions provided by therapists. The current review offers a summary of important elements that should be reported when describing psychedelic-assisted therapies. Clinical trials involving psilocybin for depression are systematically reviewed to synthesize available descriptions of their interventions. This review demonstrates that the exact nature of these psychotherapeutic interventions tends to be poorly defined in most scientific papers on psychedelic treatments. This problem and its implications are examined. The field stands to gain from optimized psychotherapeutic methods; however, insufficient documentation in scientific papers currently hinders the dissemination and improvement of evidence-based protocols. This article offers ideas to encourage the progress of research on psychedelic-assisted therapies.
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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 | 0.671 | 0.849 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.005 | 0.005 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".