The project aimed to conduct an up-to-date and comprehensive bibliometric analysis of robotic surgery to provide a detailed and holistic understanding of the field. Three strategies were employed in the data analysis i.e. search terms were explored in (A) the title, abstract, and keywords and (B) only in the title of the documents. In 3rd part we analyzed the top 100 most cited papers. Vosviewer and R Studio were utilized for detailed bibliometric and network analyses. Strategy one identified 38,469 publications, and strategy two identified 6451 publications from 2001 to 2023. The top authors, universities, countries, sponsors, and sources based on the number of publications were identified for both strategies. The top 100 most cited papers were analyzed, providing the annual number of publications and various citation metrics. Top authors (by number of publications, total citations, h-index, g-index, and m-index), universities, and countries within these highly cited papers, along with their co-authorship networks and dynamics, were examined. Co-words analysis of the top 100 most cited papers revealed the primary focus of these documents across 25 categories. This comprehensive bibliometric analysis of robotic surgery highlighted significant contributions and collaborations in the field, emphasizing the importance of global and collaborative efforts in advancing robotic surgery research.

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Over the past six decades, authorship numbers in academic publications have increased significantly, a phenomenon known as authorship inflation. This study aims to analyze comparative authorship trends and the influence of multicenter collaborations across major orthopedic, medical, and surgical journals. We reviewed metadata from The New England Journal of Medicine (NEJM), Annals of Surgery (AS), and The Journal of Bone and Joint Surgery (JBJS) from January 1, 1960, to December 31, 2019. The number of authors per publication, the prevalence of multicenter studies, and their correlation were analyzed. Data was visualized using heat maps and box plots, and trends were statistically tested using the Jonckheere-Terpstra, Mann-Kendall, and generalized linear mixed models (GLMMs). A total of 73,062 articles were analyzed, with 1,190 articles identified as originating from multicenter studies. The number of multicenter trials was found to have increased significantly over time (p < 0.001), plateauing in NEJM but continuing to rise in JBJS and AS. There was a significant increase in authorship numbers per publication over time, across all journals (p < 0.0001). There was a significant statistical correlation (p < 0.0001) as indicated by the coefficient of determination (r2), for the association between the proportion of publications with >10 authors and the proportion of multicenter publications across all three journals. Authorship inflation in academic publishing may be attributable to the rise in multicenter collaborations. The rate of increase in authorship was more pronounced in medical and surgical journals compared to orthopedic journals, reflecting differing trends across specialties. These findings highlight the evolving nature of research collaboration and authorship practices in academic publishing.

OBJECTIVE: To evaluate where orthodontic research papers are published and to explore potential relationships between the journal of publication and the characteristics of the research study and authorship.
METHODS: An online literature search of seven research databases was undertaken to identify orthodontic articles published in English language over a 12-month period (1 January-31 December 2022) (last search: 12 June 2023). Data extracted included journal, article, and author characteristics. Journal legitimacy was assessed using a ternary classification scheme including available blacklists and whitelists, cross-checking of indexing claims and history of sending unsolicited emails. The level of evidence (LOE) of all included studies was assessed using a modified Oxford LOE classification scale. Univariable and multivariable ordinal logistic regression analyses were performed to examine possible associations between the level of evidence, journal discipline, and authorship characteristics.
RESULTS: A total of 753 studies, published by 246 unique journal titles, were included and further assessed. Nearly two-thirds of orthodontic papers were published in non-orthodontic journals (62.8%) and over half (55.6%) of the articles were published in open-access policy journals. About a fifth of the articles (21.2%) were published either in presumed predatory journals or in journals of uncertain legitimacy. Journal discipline was significantly associated with the level of evidence. Higher-quality orthodontic studies were more likely published in established orthodontic journals (likelihood ratio test P < .001).
CONCLUSIONS: The identification and classification of predatory journals are challenging due to their covert nature.
CONCLUSIONS: The majority of orthodontic articles were published in non-orthodontic journals. In addition, approximately one in five orthodontic studies were published in presumed predatory journals or in journals of uncertain legitimacy. Studies with higher levels of evidence were more likely to be published in established orthodontic journals.

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This study assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on academic productivity in oncology, measured by conference abstracts, journal publications and individual authorship trends, using a reference time frame of 2018 to 2022. To assess overall academic productivity, data was obtained on the number of abstracts and articles submitted and published from a selection of oncology conferences and journals. To assess individual authorship patterns, 200 articles were randomly selected from 2018, and for the first or last authors, publications were tracked over subsequent years. Factors assessed included gender, continent, specialty, MD vs. non-MD and career status (early vs. late). The number of submitted and published conference abstracts trended downward over time between 2018 and 2022 (p=0.11 and p=0.16 respectively). Journal submissions increased to a peak in 2020 and then declined thereafter, but this did not translate into changes in the number of papers published. For the author-level analysis, factors significantly predictive of increasing publication rates in multivariable analysis were late career status (vs. early), clinician status (vs. non-clinician), surgery or public health/epidemiology specialty, and author located in Asia. Further research is needed to help ameliorate the impact of these disparities.

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The landscape of research roles within academic journals often remains uncharted territory, with authorial contributions frequently reduced to linear hierarchies (e.g., professor and assistant professor). The Kano model, traditionally used in customer satisfaction research, offers a nuanced framework for identifying the multifaceted roles of authors in scholarly publications. This study utilizes the Kano model to dissect and categorize the roles of authors in the medicine field. To conform to the hypothesis, China is the research leader while the US is the research collaborator, as reflected in the publications of the journal of Medicine (Baltimore) in the year 2023. We conducted a comprehensive bibliometric analysis of all research articles published in the journal of Medicine (Baltimore) in 2023. The Kano model was applied to classify authors into 5 categories reflective of their research roles: followers, leaders, partners, contributors, and collaborators. Data on author publications and co-authorship networks with multi-author rates (MARs) were analyzed to assign Kano categories based on the authorship positions of first and corresponding authors. Descriptive statistics and network analysis tools were used to interpret the data, including radar plots, geographical maps, and Kano diagrams. The analysis covered 1976 articles, uncovering a complex network of author roles that extends beyond the conventional binary distinction of lead and supporting authors (i.e., leading, and following researchers). A research leader in China and a collaborator in the US were conformed to support the hypothesis, based on their publications (1148 vs 51) and MARs (12.20% vs 19.61%). The Kano classification was visually adapted to classify authors (or entities) into 5 categories. The combined choropleth and geographical network maps were illustrated to identify author roles in research briefly. The Kano model serves as an effective tool for uncovering the diverse contributions of authors in medical research. By moving beyond the lead and follower dichotomy, this study highlights the intricate ecosystem of authorial roles, emphasizing the importance of each in advancing knowledge within the field of medicine. Future application of the Kano model could foster a more collaborative and inclusive recognition of contributions across various disciplines.