Dataset Information

Predicting academic career outcomes by predoctoral publication record.

ABSTRACT: Background:For students entering a science PhD program, a tenure-track faculty research position is often perceived as the ideal long-term goal. A relatively small percentage of individuals ultimately achieve this goal, however, with the vast majority of PhD recipients ultimately finding employment in industry or government positions. Given the disparity between academic career ambitions and outcomes, it is useful to understand factors that may predict those outcomes. Toward this goal, the current study examined employment status of PhD graduates from biomedical sciences programs at the University of Colorado Anschutz Medical Campus (CU AMC) and related this to metrics of predoctoral publication records, as well as to other potentially important factors, such as sex and time-since-degree, to determine if these measures could predict career outcomes. Methods:Demographic information (name, PhD program, graduation date, sex) of CU AMC biomedical sciences PhD graduates between 2000 and 2015 was obtained from University records. Career outcomes (academic faculty vs. non-faculty) and predoctoral publication records (number and impact factors of first-author and non-first-author publications) were obtained via publicly available information. Relationships between predoctoral publication record and career outcomes were investigated by (a) comparing faculty vs. non-faculty publication metrics, using t-tests, and (b) investigating the ability of predoctoral publication record, sex, and time-since-degree to predict career outcomes, using logistic regression. Results:Significant faculty vs. non-faculty differences were observed in months since graduation (p < 0.001), first-author publication number (p = 0.001), average first-author impact factor (p = 0.006), and highest first-author impact factor (p = 0.004). With sex and months since graduation as predictors of career outcome, the logistic regression model was significant (p < 0.001), with both being male and having more months since graduation predicting career status. First-author related publication metrics (number of publications, average impact factor, highest impact factor) all significantly improved model fit (?2 < 0.05 for all) and were all significant predictors of faculty status (p < 0.05 for all). Non-first-author publication metrics did not significantly improve model fit or predict faculty status. Discussion:Results suggest that while sex and months since graduation also predict career outcomes, a strong predoctoral first-author publication record may increase likelihood of obtaining an academic faculty research position. Compared to non-faculty, individuals employed in faculty positions produced more predoctoral first-author publications, with these being in journals with higher impact factors. Furthermore, first-author publication record, sex, and months since graduation were significant predictors of faculty status.

SUBMITTER: Tregellas JR

PROVIDER: S-EPMC6174868 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting academic career outcomes by predoctoral publication record.

Tregellas Jason R JR Smucny Jason J Rojas Donald C DC Legget Kristina T KT

PeerJ 20181004

<h4>Background</h4>For students entering a science PhD program, a tenure-track faculty research position is often perceived as the ideal long-term goal. A relatively small percentage of individuals ultimately achieve this goal, however, with the vast majority of PhD recipients ultimately finding employment in industry or government positions. Given the disparity between academic career ambitions and outcomes, it is useful to understand factors that may predict those outcomes. Toward this goal, t ...[more]

PMID: 30310749

Similar Datasets

Project description:ObjectiveIncreasing centralization of high-level neurosurgical practice at academic centers has increased the need for academic neurosurgeons. The lack of systematic metrics-based analyses among neurosurgery trainees and the recent pass/fail U.S. Medical Licensing Examination system necessitates a multiparametric approach to assess academic success among trainees.MethodsWe conducted a comprehensive analysis of the University of Miami residency program using 2 data sets, one containing applicants' pre-residency metrics and a second containing trainees' intra-residency metrics. Intra-residency metrics were subjectively and anonymously assessed by faculty. Univariate and multivariate logistic regression analyses were performed to determine differences among academic and non-academic neurosurgeons and identify predictors of academic careers.ResultsAcademic neurosurgeons had a significantly higher median Step 1 percentile relative to non-academic neurosurgeons (P = 0.015), and medical school ranking had no significant impact on career (P > 0.05). Among intra-residency metrics, academic neurosurgeons demonstrated higher mean rating of leadership skills (mean difference [MD] 0.46, P = 0.0011), technical skill (MD 0.42, P = 0.006), and other intra-residency metrics. Higher administrative and leadership skills were significantly associated with increased likelihood of pursuing an academic career (odds ratio [OR] 9.03, 95% CI [2.296 to 49.88], P = 0.0044). Clinical judgment and clinical knowledge were strongly associated with pursuit of an academic career (OR 9.33 and OR 9.32, respectively, with P = 0.0060 and P = 0.0010, respectively).ConclusionsPre-residency metrics had little predictive value in determining academic careers. Furthermore, medical school ranking does not play a significant role in determining a career in academic neurosurgery. Intra-residency judgment appears to play a significant role in career placement, as academic neurosurgeons were rated consistently higher than their non-academic peers in multiple key parameters by their attending physicians.

Project description:ObjectivesTo review systematically the evidence about what factors influence the decision to choose or not choose a career in academic medicine.DesignA systematic review of relevant literature from 1990 to May 2005.Data sourcesSearches of The Cochrane Library, Medline (using Ovid and PubMed) from 1990 to May 2005, and EMBASE from 1990 to May 2005 were completed to identify relevant studies that explored the influential factors. Additional articles were identified from searching the bibliographies of retrieved articles.Selection of studiesWe attempted to identify studies that included residents, fellows, or staff physicians. No restrictions were placed on the study methodologies identified and all articles presenting empirical evidence were retrieved. For cohort, case-control, and cross-sectional studies, minimum inclusion criteria were the presence of defined groups, and the ability to extract relevant data. For surveys that involved case series, minimum inclusion criteria were a description of the population, and the availability of extractable data. Minimum inclusion criteria for qualitative studies were descriptions of the sampling strategy and methods.ResultsThe search identified 251 abstracts; 25 articles were included in this review. Completion of an MD with a graduate degree or fellowship program is associated with a career in academic medicine. Of the articles identified in this review, this finding is supported by the highest quality of evidence. Similarly, the completion of research and publication of this research in medical school and residency are associated with a career in academic medicine. The desire to teach, conduct research, and the intellectual stimulation and challenge provided in academia may also persuade people to choose this career path. The influence of a role model or a mentor was reported by physicians to impact their decision making. Trainees' interest in academic medicine wanes as they progress through their residency.ConclusionsIn order to revitalize academic medicine, we must engage trainees and retain their interest throughout their training. Research opportunities for medical students, and fellowships or graduate training can meet this challenge and influence career choice. Initiatives to stimulate and maintain interest in academic medicine should be evaluated in prospective studies across multiple sites.

Dataset Information

Predicting academic career outcomes by predoctoral publication record.

Publications

Predicting academic career outcomes by predoctoral publication record.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets