已发表论文

过去 22 年针灸治疗肩痛的文献计量分析

 

Authors Chen YL , Liang YD , Guo KF , Huang Z , Feng WQ 

Received 23 November 2022

Accepted for publication 3 March 2023

Published 14 March 2023 Volume 2023:16 Pages 893—909

DOI https://doi.org/10.2147/JPR.S397168

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Houman Danesh

Purpose: Acupuncture is widely used to relieve shoulder pain. A survey was conducted in order to recognize hotspots and frontiers of acupuncture for shoulder pain from the year 2000– 2022.
Methods: The Web of Science Core Collection was used to collect literature related to acupuncture therapy for shoulder pain, which spanned January 2000 to August 2022. The number of publications yearly, countries/institutions, journals, and keywords was analyzed and visualized in shoulder pain with acupuncture therapy by CiteSpace v.5.7.R5.
Results: We totally analyzed 214 articles that met the inclusion criteria. The overall trend of publication volume continues to increase. The most productive authors in the field were César Fernández las Peñas and José L Arias-Buría, and the most influential author was Green S. Kyung Hee University and the People’s Republic of China had the highest volume of publications, respectively. The most influential journal is Pain with high citation and impact factor. The hot keywords were “acupuncture”, “shoulder pain”, “dry needling”, “randomized trial”, and “injection”. The research frontier in acupuncture for treating chronic shoulder pain was mainly “mechanism”.
Conclusion: Over the last 22 years, the findings of this bibliometric analysis have provided research trends and frontiers in clinical research on acupuncture therapy for patients with shoulder pain, which identifying hot topics and exploring new directions for the future may be helpful to researchers. Studying mechanisms underlying acupuncture therapy for shoulder pain remains a focus of future research.
Keywords: acupuncture, shoulder pain, bibliometric analysis, CiteSpace