Posters Presented at North American Skull Base Society 2016–2018: What Factors Influence Their Publication?

Autor: Yang, S. Daniel, Seu, Michelle, Qiao, James B., Tsiang, John Ta-Hsiang, Pecoraro, Nathan, Germanwala, Anand V.
Předmět:
Zdroj: Journal of Neurological Surgery. Part B. Skull Base; Dec2023, Vol. 84 Issue 6, p531-537, 7p
Abstrakt: Objective Research productivity impacts an individual's academic credentials and serves to advance the field of neurosurgery at large. Poster presentations allow researchers to share preliminary results with respected colleagues; however, more critical is the ability to publish peer-reviewed articles. Key factors that lead posters to journal publication are not well understood and difficult to quantify. This study investigates the association between bibliometrics of authors who presented posters at the North American Skull Base Society (NASBS) meeting and odds of journal publication. Methods Posters from the 2016 to 2018 NASBS archive were reviewed. Hirsch-index (h-index) of first (FH) and senior (SH) authors, research type, research topic, and number of poster authors (nAuthPost) were collected. For posters published as journal articles, number of days from poster presentation to publication (nDays), number of authors in published articles (nAuthArt), and journal impact factor (JIF) were recorded. Results One-hundred sixty-nine of 481 posters (35.1%) were published as articles. Median FH and SH for published versus unpublished posters were 7 versus 5 (p = 0.01) and 29 versus 19 (p < 0.001), respectively. When adjusted with multivariate regression, only SH (p < 0.001) and nAuthPost (p = 0.001) were significantly associated with odds of publication. Median (interquartile range [IQR]) nDays was 361 (394). Increased authors from poster to article (p = 0.017) and lower FH (p = 0.08) were correlated with increased time to publication. Median (IQR) JIF for all publications was 1.723 (1.068). Conclusions Bibliometrics such as h-index and number of authors from posters can help objectively characterize and predict future success in research productivity. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index