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Record W4400240387 · doi:10.1038/s44184-024-00065-y

Disability rights and experiential use of psychedelics in clinical research and practice

2024· article· en· W4400240387 on OpenAlexaff
Maryam Golafshani, Daniel Z. Buchman, Muhammad Ishrat Husain

Bibliographic record

Venuenpj Mental Health Research · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsCentre for Addiction and Mental HealthPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsExperiential learningPsychologyClinical PracticePsychotherapistClinical psychologyEngineering ethicsMedicineNursingPedagogyEngineering

Abstract

fetched live from OpenAlex

Given the renewed interest in the use of psychedelics for the treatment of mental and substance use disorders in recent decades, there has also been renewed discussion and debate about whether it is necessary or beneficial for those who study and deliver psychedelic-assisted psychotherapy (PAP) to have had personal experience of using psychedelics. This paper provides a brief history of this debate and brings a disability-rights perspective to the discussion, given increasing efforts to dismantle ableism in medical training, practice, and research. Many psychiatric conditions and psychotropic medications, including ones as commonly prescribed as antidepressants, may preclude one from being able to safely and/or effectively use psychedelics. As such, we argue explicitly mandating or even implying the necessity of experiential training for psychedelic researchers and clinicians can perpetuate ableism in medicine by excluding those who cannot safely use psychedelics because of their personal medical histories. As PAP research and practice rapidly grow, we must ensure the field grows with disability inclusion amongst researchers and clinicians.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.732
GPT teacher head0.716
Teacher spread0.015 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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