Global dynamics of robotic surgery research: a multi-method bibliometric investigation and focus on the top 100 most...

This study utilizes the Scopus database and adopts a multi-layered approach to provide a comprehensive and detailed overview of robotic surgery research. Specifically, three complementary strategies: (a) a title-abstract-keyword (TAK) search, (b) a title-specific search, and (c) a focused analysis of the top 100 most cited papers were employed. The TAK approach retrieved 49,026 publications, substantially surpassing the 8,029 identified via the title-only method, demonstrating that incorporating abstracts and keywords provides broader coverage. Analysis of prolific authors revealed Mottrie, A. as the most productive researcher in the TAK dataset, while Fukuda, T. led in the title-only set. Leading institutions such as the Cleveland Clinic Foundation and Yonsei University College of Medicine exhibited markedly higher outputs under TAK criteria. Country-level analysis confirmed the United States as the dominant contributor in both datasets, though absolute counts dropped significantly when limited to titles. The Journal of Robotic Surgery emerged as the most productive source across both methods. Funding sponsor analysis highlighted the National Natural Science Foundation of China as the leading funder, with the TAK dataset revealing greater international sponsorship diversity. Citation analysis of the top 100 most cited documents, spanning 1993-2021, showed an average of 279.6 citations per article, with recent papers (2018-2021) achieving unprecedented citation velocity, suggesting earlier peaks in influence for newer publications. Keyword analysis of the top 150 most frequently occurring terms in the title-specific dataset helped to map key research directions. From the title-based corpus, the 100 most cited papers were analyzed, reporting their total citations, citations per paper, and citations per year. A detailed author-level analysis was performed, including publication count, citation impact, and scholarly indices (h-index, g-index, m-index), complemented by visualizations of collaboration networks. Moreover, this study incorporates a co-word analysis of the top 100 cited papers, using unigrams, bigrams, and trigrams to illustrate central themes. The top 20 most cited papers are briefly discussed. The findings offer updated, actionable insights for researchers, clinicians, and policymakers seeking to navigate this rapidly advancing field.