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Record W4226168848 · doi:10.1080/02791072.2022.2060773

Psychedelic Experiences and Mindfulness are Associated with Improved Wellbeing

2022· article· en· W4226168848 on OpenAlexafffund
Tianhong Tim Qiu, John Paul Minda

Bibliographic record

VenueJournal of Psychoactive Drugs · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsWestern University
FundersWestern University
KeywordsMindfulnessMeditationPsychologyMindfulness meditationModerationClinical psychologyMultilevel modelPsychotherapistWell-beingSocial psychology

Abstract

fetched live from OpenAlex

Both psychedelics and mindfulness are recently emerging topics of interest in academia and popular culture. The Prevalence of personal meditation practices and recreational psychedelic use has consistently increased in the past decade. While clinical work has shown both to improve long-term wellbeing, data on naturalistic applications of psychedelics and mindfulness are lacking. The current study examined the relationship between psychedelic use, mindfulness, and multi-faceted wellbeing as an outcome. Hierarchical regression was used to quantify these associations on a sample of people (N = 1,219) who engage in both meditation practices and psychedelic use. Results show that both mindfulness and mystical experiences are associated with substantial increases in wellbeing. Psychedelics were found to be a moderator of the relationship between mystical experience wellbeing. These data are among the first to establish a strong relationship between personal mindfulness practice, recreational psychedelic use, and overall psychological wellbeing in a naturalistic framework.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.018
GPT teacher head0.300
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2022
Admission routes2
Has abstractyes

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