CiteSpace visual analysis of depression research in traditional Chinese medicine
HE Chenhao1 WANG Xinyuan1 SUN-FU Tongyu1 WANG Feng1 TAN Xi2
1.School of Management, Beijing University of Chinese Medicine, Beijing 100029, China;
2.Department of Encephalopathy, Beijing University of Chinese Medicine Shenzhen Hospital (Longgang), Guangdong Province, Shenzhen 518100, China
Abstract Objective To explore the general situation and analyze the hot topics and research fronts of depression research in traditional Chinese medicine. Methods CNKI was used as the database, the literature sources of “SCI source Periodicals”, “EI source Periodicals”, “Peking University core”, “CSSCI” and “CSCD”, and the retrieval formula was “SU= depression AND SU= traditional Chinese medicine”, the retrieval period was from October 1991 to October 2021 and the search time was October 2021. Visual charts were drawn by CiteSpace software to analyze research hotspots and development trends. Results A total of 585 literatures were retrieved, the research on depression in traditional Chinese medicine showed an increasing trend, but the analysis showed that the cooperation among institutions was scattered; hot topics could be clustered into four categories:“traditional Chinese medicine syndrome”, “traditional Chinese medicine therapy”, “clinical research”, and “classification of depression”; prominent topics focus on “Meihe Qi”, “traditional Chinese medicine syndrome”, and “classification of depression”. Conclusion From 1991 to 2021, the cooperation of depression research in China is not close across institutions and fields. The research hotspots are traditional Chinese medicine syndrome, traditional Chinese medicine pathogenesis, traditional Chinese medicine therapy, clinical research, depression classification, etc. The research trend shows that the research fields focused on the characteristics of traditional Chinese medicine, the research method pay attention to the combination of traditional Chinese medicine theory and modern technology, the research content includes specific and details depression classification and other characteristics.
HE Chenhao1 WANG Xinyuan1 SUN-FU Tongyu1 WANG Feng1 TAN Xi2. CiteSpace visual analysis of depression research in traditional Chinese medicine[J]. 中国医药导报, 2023, 20(5): 14-19.
