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. 2023 Feb 14;5(3):131-148.


doi: 10.1096/fba.2022-00117.


eCollection 2023 Mar.

Affiliations

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Michael D Schaller.


FASEB Bioadv.


.

Abstract

Training of doctoral students as part of the next generation of the biomedical workforce is essential for sustaining the scientific enterprise in the United States. Training primarily occurs at institutions of higher education, and these trainees comprise an important part of the workforce at these institutions. Federal investment in the support of doctoral students in the biological and biomedical sciences is distributed differently than the distribution of students across different types of institutions, for example, public vs private. Institutions in states that historically receive less federal support for research also receive less support for doctoral student training. Doctorates at different types of institution exhibit little difference in research productivity, with the exception of citations, and subsequent receipt of additional NIH awards. Thus, training outcomes, which are related to the quality of the student and training environment, are similar across different institutions. Research productivity of doctoral students does not correlate with the number of F31s awarded to an institution. Factors that correlate with F31 funding include R01 funding levels and program size. The findings suggest strategies for institutions to increase success at securing F31s and modification of policy to promote more equitable distribution of F31s across institutions.


Keywords:

F31; NIH; biomedical workforce; citation; doctoral student; productivity; publication.

Conflict of interest statement

The author has no relevant financial or non‐financial interests to disclose.

Figures


FIGURE 1



FIGURE 1

Source of financial support for doctoral students in biological and biomedical sciences. The source of financial support for doctoral students from 2017 to 2019 was retrieved from the GSS. The percentage of all doctoral students supported by different mechanisms at public, private, land grant, and IDeA institutions is shown. (A) Support from all sources. (B) Support from federal sources. (C) Support from the NIH. Fellows = students supported by individual fellowships. That is, a competitive award to the doctoral student, for example, an F31. Trainees = students supported on training grants, i.e. a financial award given to doctoral students selected by the institution, for example, supported on a T32. RAs = research assistantships, that is, students receiving stipends to perform research. TAs = teaching assistantships, that is, students receiving stipends to teach. There is a caveat that different institutions may define “Fellows”, “Trainees” and “Research Assistants” differently. Note that federal sources do not support teaching assistantships.


FIGURE 2



FIGURE 2

Historical record of doctorates awarded in biological and biomedical sciences and F31s awarded at US Universities. The number of doctorates awarded in biological and biomedical sciences from 1994 to 2020 was retrieved from the SED. The number of doctorates awarded (A) and percentage of total doctorates awarded (B) at private, public, land grant, and IDeA institutions was calculated. The number of F31s for each fiscal year from 1985 to 2021 was tallied using data acquired using NIH Reporter. The number of awards (C) and the percentage of awards (D) at public, private, land grant, and IDeA institutions are plotted.


FIGURE 3



FIGURE 3

Correlations with number of F31 awards. (A) The number of F31s at individual institutions is plotted against the number of R01s held at the institution during FY19. F31 and R01 data were extracted using NIH Reporter. (B) The number of F31s at individual institutions during FY19 is plotted against with number of doctorates awarded at the institution in 2019. F31 data were calculated using data from NIH Reporter. The number of doctorates awarded is from the SED.


FIGURE 4



FIGURE 4

Date of publication related to dissertation year. The year of publication relative to the year of dissertation was calculated by subtracting the dissertation year from the publication year. The number of first author publications and the number of total publications in each year relative to dissertation year are plotted. The 5th and 95th percentiles of first author and total publications are shown. A subset of the entire dataset, restricted based on time of publication relative to the dissertation year, was used for the analysis. Lines delineate the subset of publications used for the analysis of first author papers (“Firsts analysis”) and total papers (“Total analysis”).

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