Global trends of traditional Chinese exercises for musculoskeletal disorders treatment research from 2000 to 2022: A bibliometric analysis

BackgroundTraditional Chinese exercise has been shown to be effective in relieving long-term chronic pain, physical dysfunction, decreased ability to participate in society and decreased quality of life in musculoskeletal diseases. In recent years, there has been a steady increase in publications on the treatment of musculoskeletal disorders by traditional Chinese exercises. The purpose of this study is to review the characteristics and trends of Chinese traditional exercise studies on musculoskeletal diseases published since 2000 through bibliometric analysis, and identify current research hotspots, so as to guide the direction of future research. MethodsPublications regarding traditional Chinese exercises for musculoskeletal disorders from 2000 to 2022 were downloaded from the Web of Science Core Collection. VOSviewer 1.6.18 and CiteSpace V software were used for bibliometric analyses. Bibliometric visualization and comparative analysis were conducted for authors, cited authors, journals, co-cited journals, institutions, countries, references, and keywords. ResultsA total of 432 articles were obtained, with an upward trend over time. The most productive countries and institutions in this field are the USA (183) and Harvard University (70). Evidence-based Complementary and Alternative Medicine (20) was the most prolific journal, Cochrane Database System Review (758) was the most commonly cited journal. Wang Chenchen published the largest number of articles (18). According to high frequency keywords, the hot spot musculoskeletal disorder and the type of traditional Chinese exercise are knee osteoarthritis and Tai Chi. ConclusionThis study provides a scientific perspective for the research of traditional Chinese exercises for musculoskeletal disorders and provides valuable information for researchers to discover the current research status, hot spots and new trends of future research.