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Record W4306914642 · doi:10.1177/13634615221119388

Psychedelic medicine at a crossroads: Advancing an integrative approach to research and practice

2022· article· en· W4306914642 on OpenAlexafffund
Gabriella Gobbi, Antonio Inserra, Kyle T. Greenway, Michael Lifshitz, Laurence J. Kirmayer

Bibliographic record

VenueTranscultural Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsJewish General HospitalMcGill University
FundersCanadian Institutes of Health Research
KeywordsPsychotherapistPsychologyPsychological interventionContext (archaeology)Sociocultural evolutionMental healthConsciousnessIsolation (microbiology)Action (physics)PsychiatrySociologyNeuroscience

Abstract

fetched live from OpenAlex

Psychedelics have been already used by human societies for more than 3000 years, mostly in religious and healing context. The renewed interest in the potential application of psychedelic compounds as novel therapeutics has led to promising preliminary evidence of clinical benefit in some psychiatric disorders. Despite these promising results, the potential for large-scale clinical application of these profoundly consciousness-altering substances, in isolation from the sociocultural contexts in which they were traditionally used, raises important concerns. These concerns stem from the recognition that the mechanisms of therapeutic action of psychedelics are not entirely dependent on neurobiology, but also on the psychological, social and spiritual processes for their efficacy. For these reasons, physicians or psychotherapists involved in psychedelic-assisted psychotherapy need training in ways to accompany patients through this experience to promote positive outcomes and address potential side effects. Psychedelic therapies may foster the emergence of a novel paradigm in psychiatry that integrates psychopharmacological, psychotherapeutic, and cultural interventions for patients with mental health issues.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.114
GPT teacher head0.467
Teacher spread0.354 · 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.

Study designQualitative
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

Citations9
Published2022
Admission routes2
Has abstractyes

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