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Record W3132789252 · doi:10.1177/0706743720979917

Plant-based Medicines (Phytoceuticals) in the Treatment of Psychiatric Disorders: A Meta-review of Meta-analyses of Randomized Controlled Trials: Les médicaments à base de plantes (phytoceutiques) dans le traitement des troubles psychiatriques: une méta-revue des méta-analyses d’essais randomisés contrôlés

2021· review· en· W3132789252 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2021
Typereview
Languageen
FieldMedicine
TopicMedicinal Plant Extracts Effects
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsMeta-analysisPsychiatryMedicineRandomized controlled trialDepression (economics)Major depressive disorderAnxietySchizophrenia (object-oriented programming)MEDLINESystematic reviewTraditional medicineMoodInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Plant-based medicines have had a long-standing history of use in psychiatric disorders. Highly quantified and standardized extracts or isolates may be termed "phytoceuticals," in a similar way that medicinal nutrients are termed as "nutraceuticals." Over the past 2 decades, several meta-analyses have examined the data for a range of plant-based medicines in the treatment of psychiatric disorders. The aim of this international project is to provide a "meta-review" of this top-tier evidence. METHODS: We identified, synthesized, and appraised all available up to date meta-analyses... of randomized controlled trials (RCTs) reporting on the efficacy and effectiveness of individual phytoceuticals across all major psychiatric disorders. RESULTS: Our systematic search identified 9 relevant meta-analyses of RCTs, with primary analyses including outcome data from 5,927 individuals. Supportive meta-analytic evidence was found for St John's wort for major depressive disorder (MDD); curcumin and saffron for MDD or depression symptoms, and ginkgo for total and negative symptoms in schizophrenia. Kava was not effective in treating diagnosed anxiety disorders. We also provide details on 22 traditional Chinese herbal medicine formulas' meta-analyses (primarily for depression studies), all of which revealed highly significant and large effect sizes. Their methodology, reporting, and potential publication bias were, however, of marked concern. The same caveat was noted for the curcumin, ginkgo, and saffron meta-analyses, which may also have significant publication bias. CONCLUSIONS: More rigorous international studies are required to validate the efficacy of these phytoceuticals before treatment recommendations can be made. In conclusion, the breadth of data tentatively supports several phytoceuticals which may be effective for mental disorders alongside pharmaceutical, psychological therapies, and standard lifestyle recommendations.

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.

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)0.039
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.156
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0390.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0470.025
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.316
GPT teacher head0.462
Teacher spread0.146 · 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