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Record W4376106272 · doi:10.1101/2023.05.10.23289787

A Retrospective Study to Determine the Impact of Psychedelic Therapy for Dimensional Measures of Wellness: A Quantitative Analysis

2023· preprint· en· W4376106272 on OpenAlexaff
Victoria Di Virgilio, Amir Minerbi, Jagpaul Kaur Deol, Salena Aggerwal, Toufik Safi, Gaurav Gupta

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of OttawaUniversity of British ColumbiaUniversity of TorontoCarleton University
Fundersnot available
KeywordsMoodQuality of life (healthcare)AnxietyMental healthMedicineClinical psychologyScale (ratio)Depression (economics)PsychologyPsychiatryPhysical therapyNursing

Abstract

fetched live from OpenAlex

Abstract Background The World Health Organization (WHO) defines wellness as the optimal state of health of individuals and groups. No study to date has identified the impact of psychedelic medicines on optimizing wellness using a dimensional approach. Using this approach, treatment effects can be measured more broadly using a composite score of participants’ global perceptions of change for pain, function, and mood scores. Given the precedence in previous work for retrospective studies of participants’ self-medicating with these substances, the nature of this study design allows for a safe way to develop further evidence in this area of care, with wellness as the broad indication. Methods 65 civilian or military veterans above the age of 18, self-identifying as having used psychedelic medicines for non-recreational purposes in the last 3 years were recruited. Participants completed the following standardized questionnaires: Patient Global Impression of Change (PGIC) scale, Pain, Enjoyment of Life and General Activity (PEG) scale, Anxiety and Depression scale (ADS), and Disability Index (DI) scale. The analysis focused on reported PGIC outcomes and correlations between subscales. Given the nature of the study, a comparison to the baseline could not be made. Results On average, participants reported improvement in all domains (pain, mental health, function, and overall quality of life), regardless of the medicine. Perceived improvement was highest in mental health and overall quality of life, and lowest in pain. Kendall correlation showed a highly significant association between the perceived changes in all domains. Correlation coefficients were highest between the perceived change in function, quality of life, and mental health. Discussion The use of various psychedelic medicines may be associated with a broad range of changes that could help clarify the mechanism of how they impact wellness in the future. Pain, mental health, function, and overall quality of life accordingly improved after the use of these medicines. Minor differences between the drugs were not found as significant, indicating that the perceived benefits seemed to be specific to the psychedelic class. Numerous limitations exist to this type of study which was relatively small in size, retrospective and anonymous in nature. Conclusion The wellness of individuals or groups is not simply an absence of disease, symptoms, or impairments. Instead, it is an outcome that is shaped by a myriad of personal characteristics, psychophysiology, and choices, expressed throughout one’s lifespan, unfolding in dynamic interaction with a complicated sociocultural and physical environment.

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)0.003
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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.191
GPT teacher head0.453
Teacher spread0.262 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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