Kampo, A Japanese Traditional Medicinal System for Psychiatric Conditions: A Narrative Review
Bibliographic record
Abstract
INTRODUCTION: Kampo is a Japanese traditional medicinal system and is represented by unity of mind and body. It is originally based upon Chinese traditional medicine but has uniquely developed in Japan. METHODS: A narrative review on the use of Kampo for psychiatric conditions is provided. RESULTS: Kampo formula is a combination of several crude ingredients; most derive from natural plants and some from animals and minerals. These Kampo formulae are widely prescribed in almost all medical disciplines, including psychiatry, in Japan; they have been used for various psychiatric disorders such as dementia, schizophrenia spectrum disorders, mood disorders, anxiety disorders, and personality disorders. Kampo is a versatile traditional medicine with a variety of positive effects on mental states with relatively benign side effect profiles. Kampo formulae can be adjunctively combined with or substituted for the Western psychotropic drugs, which will provide more treatment options to patients with psychiatric conditions. DISCUSSION: This review summarizes the current knowledge on Kampo for psychiatric conditions, highlighting a paucity of data and a need for further good-quality evidence on these medications.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".