Updated 5-Year Institutional Bibliometric Profiles for United States Neurosurgery Residency Programs and the...

The authors report current 3-year and 5-year institutional bibliometric profiles and investigate the correlations between objective metrics of neurosurgical residency programs and social media presence, including residency program size, faculty count, Doximity rankings, and measures of research output.

A list of neurosurgery residency programs was obtained through the Doximity Residency Navigator. Publication history of faculty members was compiled using Scopus and analyzed to create institutional bibliometric profiles from 2018-2022 to 2020-2022. Mann-Whitney U tests were used to compare departmental metrics for institutions with and without social media accounts. Spearman rank correlations were used to examine the relationship between social media following and metrics, and between Twitter following and methods of Twitter use.

74% (n = 86) of neurosurgery programs have a Twitter account, 47% (n = 55) have a Facebook account, 63% (n = 73) have Instagram accounts, and 16% (n = 19) have LinkedIn accounts. The most notable differences were found when comparing departments with and without Twitter accounts, where a difference was found in all metrics except the average H-index. Residency program size, faculty count, average H-index, 3-year and 5-year publication and citation counts per faculty, and institutional H-indices were significantly correlated with Twitter following. Higher Doximity rankings were correlated with Twitter following and Facebook likes. There is a greater increase in 5-year citations per publication from 2009-2013 to 2018-2022 for institutions that created departmental Twitter accounts after 2013. Articles that were tweeted about had higher 3-year citations per publication than the institution's overall 3-year citations per publication.

Our findings provide updated insight into the relationship between social media presence and objective academic metrics of neurosurgery departments. We identify and quantify correlations between social media platforms and program characteristics, with a focus on research output. These metrics can be used to guide programs in their development of social media.