Kava and St. John's Wort: Current Evidence for Use in Mood and Anxiety Disorders
Bibliographic record
Abstract
BACKGROUND: Mood and anxiety disorders pose significant health burdens on the community. Kava and St. John's wort (SJW) are the most commonly used herbal medicines in the treatment of anxiety and depressive disorders, respectively. OBJECTIVES: The objective of this study was to conduct a comprehensive review of kava and SJW, to review any evidence of efficacy, mode of action, pharmacokinetics, safety and use in major depressive disorder, bipolar disorder, seasonal affective disorder (SAD), generalized anxiety disorder, social phobia (SP), panic disorder (PD), obsessive-compulsive disorder (OCD), and post-traumatic stress disorder (PTSD). METHODS: A systematic review was conducted using the electronic databases MEDLINE, CINAHL, and The Cochrane Library during late 2008. The search criteria involved mood and anxiety disorder search terms in combination with kava, Piper methysticum, kavalactones, St. John's wort, Hypericum perforatum, hypericin, and hyperforin. Additional search criteria for safety, pharmacodynamics, and pharmacokinetics were employed. A subsequent forward search was conducted of the papers using Web of Science cited reference search. RESULTS: Current evidence supports the use of SJW in treating mild-moderate depression, and for kava in treatment of generalized anxiety. In respect to the other disorders, only weak preliminary evidence exists for use of SJW in SAD. Currently there is no published human trial on use of kava in affective disorders, or in OCD, PTSD, PD, or SP. These disorders constitute potential applications that warrant exploration. CONCLUSIONS: Current evidence for herbal medicines in the treatment of depression and anxiety only supports the use of Hypericum perforatum for depression, and Piper methysticum for generalized anxiety.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| 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) | 0.006 | 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".