The transition of surgical simulation training and its learning curve: a bibliometric analysis from 2000 to 2023

Abstract

Background: Proficient surgical skills are essential for surgeons, making surgical training an important part of surgical education. The development of technology promotes the diversification of surgical training types. This study analyzes the changes in surgical training patterns from the perspective of bibliometrics, and applies the learning curves as a measure to demonstrate their teaching ability.

Method: Related papers were searched in the Web of Science database using the following formula: TS=[(training OR simulation) AND (learning curve) AND (surgical)]. Two researchers browsed the papers to ensure that the topics of articles were focused on the impact of surgical simulation training on the learning curve. CiteSpace, VOSviewer, and R packages were applied to analyze the publication trends, countries, authors, keywords, and references of selected articles.

Result: Ultimately, 2461 documents were screened and analyzed. The USA is the most productive and influential country in this field. Surgical endoscopy and other interventional techniques publish the most articles, while surgical endoscopy and other interventional techniques is the most cited journal. Aggarwal Rajesh is the most productive and influential author. Keyword and reference analyses reveal that laparoscopic surgery, robotic surgery, virtue reality, and artificial intelligence were the hotspots in the field.

Conclusion: This study provided a global overview of the current state and future trend in the surgical education field. The study surmised the applicability of different surgical simulation types by comparing and analyzing the learning curves, which is helpful for the development of this field.