Academic Productivity of Applicant and Program as Predictors of a Future Academic Career in Neurosurgery

Abstract

BACKGROUND AND OBJECTIVES: Academic productivity is viewed as a critical objective factor for a neurosurgery residency applicant. There has been a consistent rise in academic productivity over the last decade, but a lack of consistent data on the utility of this in helping neurosurgery residency programs identify which applicants will enter academic neurosurgery. This cross-sectional study evaluates the predictiveness of academic productivity before and during residency on career choice, both independent and dependent of training environment. METHODS: The 116 accredited neurosurgery residency programs were split into 4 quartile groups based on their 2022 Doximity rankings. Six neurosurgery residency programs were randomly selected from each quartile. Publicly available information including number and type (before or during residency) of publication and type of employment (academic vs nonacademic) was collected on neurosurgeons who matriculated into residency in the year 2000 or later. Multivariable logistic regression was used to explore the associations among neurosurgeon and program characteristics, and an academic career. RESULTS: A total of 557 neurosurgeons were identified. Group 1 (n = 194) had the highest median publications during residency total (12) and first author (5), as well as the highest percentage of neurosurgeons who attended a top 20 medical school (38.7%), hold a higher educational degree (20.6%), and pursued an academic career (72.2%). Neither attending a top 20 medical school, holding a higher educational degree, nor publications were significant multivariable predictors of an academic career. Being in group 1 was the only significant predictor of entering an academic career across analyses. CONCLUSION: Only residency group ranking, not academic productivity, predicted a future academic career. For residency programs evaluating applicants as future academic neurosurgeons, this suggests that program environment is more predictive than traditionally valued characteristics such as research productivity. Additional work is needed to elucidate characteristics or practices by which future academic neurosurgeons can be identified.