A Bibliometric Analysis of Acupuncture Therapy in the Treatment of Musculoskeletal Pain from 2003 to 2022

Abstract

Background: Acupuncture therapy has been widely used in the treatment of musculoskeletal pain (MP) in many countries around the world. However, there are no bibliometric studies on acupuncture therapy for MP. Therefore, the aim of this study was to analyze the current status, frontiers and hot spots in the use of acupuncture therapy for the treatment of MP. Methods: Literature on acupuncture therapy for MP was extracted from the Web of Science Core Collection database from 2003 to 2022. CiteSpace 6.2.R4 (64-bit) software was used to analyze the number and centrality of journals, countries, institutions, authors, references and keywords, and the functions of co-occurrence and clustering were applied to draw a visual knowledge map. Results: Over the past 20 years, the annual journal publications have been on a steady upward trend, with 438 articles published in 143 journals, including Acupuncture in Medicine Journal published the most (28, 6.39%), JAMA-Journal of the American Medical Association was the journal with the highest impact factor (IF = 120.7003), USA dominated with the most publications (140, 31.96%) among 44 countries, and among 196 research organizations Kyung Hee University was the most prolific (19, 4.34%) and Ha, In-Hyuk was the most published author (9, 2.05%). “Acupuncture” is the most popular and highly sought after keywords. “Low back pain” is the keyword with the highest centrality. Conclusion: This article provides the current situation of the use of acupuncture therapy in the treatment of MP in the past 20 years, and statistical analysis reveals that “low back pain”, “knit osteoporosis” and “break cancer” are new research diseases related to acupuncture therapy for MP, and “myobasic trigger point” is a new research direction of acupuncture therapy for MP. Therefore, this study helps researchers grasp the research hotspots and provide certain references for in-depth research and future topic selection.