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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.050 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.069 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".