Status Quo and Research Trends of Neurosurgical Departments in China: Bibliometric and Scientometric Analyses

• Published in: Journal of medical Internet research 2021-07, Vol.23 (7), p.e25700-e25700
• Main Authors: Ni, Bowen, He, Minyi, Cao, Bei, He, Jianmin, Liu, Yawei, Zhao, Zhen
• Format: Article
• Language: English
• Subjects: Analysis; Bibliographic literature; Bibliometrics; Citation indexes; Cluster analysis; Exports; Funding; Growth rate; Hospitals; Keywords; Natural sciences; Neurosurgery; Original Paper; Scientometrics; Software; Topics; Trends; Visualization; Words
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/25700

Background: Modern neurosurgery is a relatively young discipline characterized by finesse and complexity. In recent years, neurosurgery in China has made continuous developments, with long-term progress and outstanding discoveries in many aspects of the field. Objective: This scientometric investigation aimed to comprehensively provide insight into the development trends of neurosurgery in China, to demonstrate how the field has evolved. Methods: PubMed database was searched to retrieve relevant papers published between 1988 and 2018 from neurosurgery institutions in China. The database of the National Natural Science Foundation of China was also retrieved for funding information. Information (eg, year of publication, journal, institute of origin) and keywords were collected from each paper after removing duplicates and filtering unintentional words. Co-word analysis was performed on the papers’ keywords, and a time distribution matrix of coexisting keywords in a given paper (ie, termed co-words) was established. Co-words were clustered according to their growth rate within years and visually presented with a mountain plot and a heatmap. Trends and potential subspecialties were identified, and each topic, represented either by a co-word from publications or funding from the National Natural Science Foundation of China during the period from 2011 to 2018, was collected and analyzed. Results: Within 15,972 publications on neurosurgery from institutions in China, diagnostic image was found to coexist the most with other keywords. Cluster 0, represented by diagnostic image with retrospective study, contained emerging topics with great developmental potential and demonstrated high growth rates in recent years. This finding suggests that the topics represented in Cluster 0 may represent future areas of important neurosurgical research. We also found that the developmental trend of China’s neurosurgical research is highly correlated with National Natural Science Foundation of China funding acquisition. Conclusions: Co-word analysis and visualization results provided insight into the emerging research topics that are of vital importance, which can be used as a reference by neurosurgeons and researchers for future investigations. In this study, our analysis strategy based on co-word biclustering was able to clearly demonstrate current academic subject development; therefore, co-word biclustering is a reliable bibliometric analysis strategy.