Traditional Chinese medicine for promoting mental health of patients with COVID-19: a scoping review
Bibliographic record
Abstract
Objective: This study aimed to systematically review and depict the current studies of traditional Chinese medicine for the mental health of patients with coronavirus disease 2019 (COVID-19). Methods: A scoping review was conducted by searching PubMed, Web of Science, CNKI, Wanfang database, VIP database, and SinoMed, with the retrieval time being from the establishment of the database to April 18, 2022. The basic information of the included studies, objective, design, types of patients, interventions, outcomes, etc., was reviewed and summarized narratively. Methodological quality was assessed using the Cochrane Risk of Bias assessment tool, the methodological index for non-randomized studies or the Newcastle–Ottawa scale. Results: We identified 30 traditional Chinese medicine (TCM) studies from six databases. Among them, finished randomized controlled trials (n = 16) accounted for most of the studies, followed by single-arm studies (n = 9). In terms of study theme, 20 studies defined the mental health of patients with COVID-19 as the research theme. Psychological assessment was included in the inclusion criteria (performed before participation) of nine studies, whereas the other studies only mentioned the mental outcomes. TCM interventions included TCM exercises (Yijinjing, Baduanjin, Liuzijue, Taichi), acupoint stimulation (auricular and body points), moxibustion, decoction, or granules based on TCM syndrome differentiation, decoction, or granules with fixed formulae (Baidu Jieduan granules, Xuanfei Baidu decoction, and Qingfei Paidu decoction), Chinese patent medicine (Jinhua Qinggan granules), TCM psychological therapy (TCM ideological therapy, TCM five-tone therapy, and TCM psychological sand table), and TCM nursing (dialectical care, dialectical diet, and psychological counseling). Anxiety and depression were the main outcomes evaluated in regard to mental health in patients with COVID-19. The limitations of methodological quality were predominantly from follow-up, blinding, and registration. Positive results were reported by 27 studies (90%, n = 30). Conclusion: We summarized the existing literature about the impact of TCM on mental health in patients with COVID-19. The number of studies evaluating the impact of TCM on mental health is encouraging, but overall methodological quality was low. Several TCM interventions warrant further evaluation, particularly among populations outside of China, for the purpose of establishing supporting evidence. More importantly, research with stronger methodological quality needs to be developed. Graphical abstract: http://links.lww.com/AHM/A36.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".