MétaCan
Menu
Back to cohort
Record W4367664319 · doi:10.47626/2237-6089-2022-0597

Psilocybin-assisted psychotherapy as a potential treatment for eating disorders: a narrative review of preliminary evidence

2023· review· en· W4367664319 on OpenAlexafffund
Elena Koning, Elisa Brietzke

Bibliographic record

VenueTrends in Psychiatry and Psychotherapy · 2023
Typereview
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsQueen's University
FundersQueen's University
KeywordsPsilocybinPsychotherapistDistressEating disordersPsychologyCognitionClinical psychologyPsychiatrySerotonergicHallucinogenMedicineSerotonin

Abstract

fetched live from OpenAlex

Eating disorders (ED) are a group of potentially severe mental disorders characterized by abnormal energy balance, cognitive dysfunction, and emotional distress. Cognitive inflexibility is a major challenge to successful ED treatment and dysregulated serotonergic function has been implicated in this symptomatic dimension. Moreover, there are few effective treatment options and long-term remission of ED symptoms is difficult to achieve. There is emerging evidence for the use of psychedelic-assisted psychotherapy (PAP) for a range of mental disorders. Psilocybin is a serotonergic psychedelic that has demonstrated therapeutic benefit in a variety of psychiatric illnesses characterized by rigid thought patterns and treatment resistance. The current paper presents a narrative review of the hypothesis that psilocybin may be an effective adjunctive treatment for individuals with EDs, based on biological plausibility, transdiagnostic evidence, and preliminary results. Limitations of the PAP model and proposed future directions for its application to eating behavior are also discussed. Although the literature to date is not sufficient to propose the incorporation of psilocybin in the treatment of disordered eating behaviors, preliminary evidence supports the need for more rigorous clinical trials as an important avenue for future investigation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.129
GPT teacher head0.482
Teacher spread0.352 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations13
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueTrends in Psychiatry and PsychotherapySame topicPsychedelics and Drug StudiesFrench-language works237,207