Abstract
Simulation-based education in medicine (SBME) constitutes a notable paradigm shift in teaching methodologies. Utilizing simulation involves replicating authentic patient experiences and enabling learners to develop skills and practice without putting patients at risk. Despite its growing popularity, limited data are currently available on the perceived value and impact of SBME in oncology. To bridge this gap, this paper presents a bibliometric analysis that maps the global implications and potential future directions of SBME in the field of oncology.Publication trends on SBME were retrospectively analyzed during the period from January 2010 to April 2024, using a number of bibliometric parameters based on the PubMed database and other resources (SpringerLink, Google Scholar, EM-Consulte, and ScienceDirect).A total of 428 publications related to simulation in oncology were identified and included in the bibliometric analysis. The United States of America (USA) was the clear leader, with the largest number of papers (164, 38.3%). Original articles (357, 83.4%) dominated the publications. The majority of the articles (413, 96.5%) were published in the English language. The articles were published in the fields of surgical oncology (165, 38.6%), medical oncology (130, 30.4%), and radiation oncology (77, 18.0%). Additionally, most of the publications were covered by the PubMed and Web of Science core collections. Importantly, articles were frequently published in influential journals, with 232 journals selected and a median impact factor of 2.6 [0.3-81.1]. Besides, the median H-index of authors was 10, the median i-10 index was 12, and the highest number of publications by an author was 3.SBME serves as an essential learning tool in oncology sciences across different domains, such as formation curricula, continued education, and recertification. SBME has the ability to teach technical, procedural, and communication skills. The future research prospects involve the broad incorporation of high technology and innovative simulation methods in oncology fields.