Herbal medicines, other than St. John's Wort, in the treatment of depression: a systematic review.
Bibliographic record
Abstract
OBJECTIVE: To evaluate herbal medicines, other than St. John's wort, in the treatment of depression. DATA SOURCES/SEARCH METHODS: A computer-based search of Medline, Cinahl, AMED, ALT Health Watch, Psych Articles, Psych Info, Current Contents databases, Cochrane Controlled Trials Register, and Cochrane Database of Systematic Reviews, was performed. Researchers were contacted, and bibliographies of relevant papers and previous meta-analysis were hand searched for additional references. REVIEW METHODS: Trials were included in the review if they were prospective human trials assessing herbal medicines, other than St. John's wort, in the treatment of mild-to-moderate depression and utilized validated instruments to assess participant eligibility and clinical endpoints. RESULTS: Nine trials were identified that met all eligibility requirements. Three studies investigated saffron stigma, two investigated saffron petal, and one compared saffron stigma to the petal. Individual trials investigating lavender, Echium, and Rhodiola were also located. DISCUSSION: Results of the trials are discussed. Saffron stigma was found to be significantly more effective than placebo and equally as efficacious as fluoxetine and imipramine. Saffron petal was significantly more effective than placebo and was found to be equally efficacious compared to fluoxetine and saffron stigma. Lavender was found to be less effective than imipramine, but the combination of lavender and imipramine was significantly more effective than imipramine alone. When compared to placebo, Echium was found to significantly decrease depression scores at week 4, but not week 6. Rhodiola was also found to significantly improve depressive symptoms when compared to placebo. CONCLUSION: A number of herbal medicines show promise in the management of mild-to-moderate depression.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".