DOI: 10.5061/dryad.70rxwdc0t
title: Data from: Postdoctoral T32 training is correlated with obtaining an academic primarily research faculty position

description: Background: The main mission of NIH-sponsored institutional training
 programs such as the T32 is to provide strong research and career training
 for early career scientists, while preparing those individuals to become
 leaders working to meet the health-related research needs of the nation.
 One of the main avenues to pursue health-related research is becoming
 research faculty at an academic institution. It is therefore important to
 know whether these programs are succeeding in this mission, or, if
 barriers exist that prevent trainees from pursuing these careers.Methods:
 Our institution currently trains ~ 2400 post-doctoral scholars per year,
 approximately 5% of whom are enrolled in one of our 33 T32 programs. In
 this study, we 1) compare the professional outcomes of T32 trainees with
 non-T32 trainees at our institution, and 2) survey past and current T32
 trainees in a subset of high-performing cardiovascular programs about the
 barriers and enablers they experienced to pursuing research-oriented
 careers. Results: Former T32 trainees are significantly more likely to
 attain appointments as primarily research faculty members, compared to
 other trainees. Trainees report a perceived lack of stability, the paucity
 of open positions, and the ‘publish or perish’ competitive mentality of
 academia as their top reasons for abandoning careers in academia. However,
 they were still more likely to choose research over clinical careers after
 participating in a dedicated T32 program.Conclusions: Our results support
 the conclusion that structured training programs strengthen the pipeline
 of young scientists pursuing careers in academic research, including those
 from underrepresented backgrounds. However, T32 postdoctoral researchers
 are held back from pursuing academic careers by a perceived lack of
 stability and high competition for faculty positions.Funding: This
 research received no specific grant from any funding agency in the public,
 commercial, or not-for-profit sectors.
description: # T32 Career Stages / Stanford School of Medicine
 [https://doi.org/10.5061/dryad.70rxwdc0t](https://doi.org/10.5061/dryad.70rxwdc0t) These datasets  describes five data-files associated with our publication. ## Description of the data and file structure **OPA Data** (OPA_Data.csv) Each row represents information for unique former postdoctoral trainees at Stanford University. Note that this data does not represent all former postdocs, but a subset who participated in health-related research. Columns provide information about whether the traine was confirmed to have participated in a T32 program "T32 Postdocs" or had no confirmed T32 participation "Non-T32 Postdocs", gender, URM status, type of current work, faculty status, and a combined field for traines who became primarily research academic faculty. Variables: ``` Postdoc_ID: De-identified postdoc ID number ``` ``` T32 Status: Non-T32 Postdocs, T32 Postdocs ``` ``` Gender: Male, Female, Undefined ``` ``` URM Check bio: URM, Not URM ``` ``` Type: Primarily Teaching, Science/Discipline-Related, Primarily Research, Not Related To Science/Discipline, Further Training Or Education, None ``` ``` Faculty: Non-Faculty, Faculty ``` ``` Primarily Research Academic Faculty: All Other Positions, Primarily Research Faculty ``` **CV T32 Program Data** (CV_T32_Program_Data.csv) Each row represents information for a unique T32 trainee in a cardiovascular T32 program at Stanford University. Columns provide information about the trainee gender, higher degree, and "Current Outcome" as of Spring, 2020. Respondent identifier number is NOT the same as the identifier numbers in the CV T32 Survey dataset. Variables: ``` Stanford ID #: ``` ``` Gender: Male, Female, or Undefined ``` ``` Degree: MD, PhD, or MD/PHD ``` ``` Current Outcome (group): Faculty, Industry / Non-Academic Research, Academic Non-Faculty, Clinical Practice & Teaching ``` **CV T32 Survey Data** (CVI_T32_Survey_Data.csv) Gender for each survey respondent. Respondent identifier number is NOT the same as identifier numbers in Enablers Ranke or Barriers Rank datasets. Variables: ``` ID: Survey response ID ``` ``` Gender: Male, Female, Undefined ``` **Enablers Rank** (Enablers_Rank.csv) Each row represents a survey response. Each column represents the rank that that survey repsondent assigned to that Enabler. No value indicates no ranking was assigned. Respondent identifier number is NOT the same as identifier number in CV T32 Survey dataset, but IS the same as the identifier number in the Barriers Rank dataset. Variables: ``` ID: Survey response ID ``` ``` All other variables are the barriers to careers in academia described in the survey.  The number listed is the rank of the barrier. ``` **Barriers Rank** (Barriers_Rank.csv) Each row represents a survey response. Each column represents the rank that that survey repsondent assigned to that Barrier. No value indicates no ranking was assigned. Respondent identifier number is NOT the same as identifier number in CV T32 Survey dataset, but IS the same as the identifier number in the Enablers Rank dataset. Variables: ``` ID: Survey response ID ``` ``` All other variables are the barriers to careers in academia described in the survey.  The number listed is the rank of the barrier. ``` ## Code/Software We also provide the RMarkdown file for the code we used to create the figures associated with our publication on Zenodo. ## Human subjects data Our human subject data is de-identified and does not include any personally identifiable information.