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Record W4394755797 · doi:10.1177/02698811241239206

Psychedelics and the ‘inner healer’: Myth or mechanism?

2024· article· en· W4394755797 on OpenAlexaff
Joseph Peill, M. Marguilho, David Erritzøe, Tommaso Barba, Kyle T. Greenway, Fernando E. Rosas, Christopher Timmermann, Robin Carhart‐Harris

Bibliographic record

VenueJournal of Psychopharmacology · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsMcGill UniversityJewish General Hospital
FundersAlexander Mosley Charitable Trust
KeywordsPsilocybinPlaceboHallucinogenPsychologyPlacebo responseInner cityMechanism (biology)PsychiatryTelepathyClinical psychologyPsychotherapistMedicineAlternative medicinePhilosophyEpistemology

Abstract

fetched live from OpenAlex

BACKGROUND: Reference to an intrinsic healing mechanism or an 'inner healer' is commonplace amongst psychedelic drug-using cultures. The 'inner healer' refers to the belief that psychedelic compounds, plants or concoctions have an intrinsically regenerative action on the mind and brain, analogous to intrinsic healing mechanisms within the physical body, for example, after sickness or injury. AIMS: Here, we sought to test and critique this idea by devising a single subjective rating item pertaining to perceived 'inner healing' effects. METHODS: = 29) dose of psilocybin in a double-blind randomised controlled trial of psilocybin for depression. RESULTS: < 0.001). Within the high-dose sub-sample only, inner healer scores predicted improved depressive symptomatology at 2 weeks post-dosing. CONCLUSIONS: The principle of activating inner healing mechanisms via psychedelics is scientifically nascent; however, this study takes a positivist and pragmatic step forward, asking whether it warrants further examination.

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 categoriesInsufficient payload (model declined to judge)
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 score0.442
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.407
Teacher spread0.373 · 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 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

Citations15
Published2024
Admission routes1
Has abstractyes

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