Comparison of bibliometrics for predoctoral Translational Science Training (TST) TL1 Program participants and nonparticipants, male and female participants, and participants from underrepresented and well-represented backgrounds

Christopher R Frei; Yong-Hee P Chun; Linda M McManus; Julie Barker; Amanda M Moore

doi:10.1017/cts.2022.508

Comparison of bibliometrics for predoctoral Translational Science Training (TST) TL1 Program participants and nonparticipants, male and female participants, and participants from underrepresented and well-represented backgrounds

J Clin Transl Sci. 2022 Dec 1;7(1):e12. doi: 10.1017/cts.2022.508. eCollection 2023.

Authors

Christopher R Frei^{1

2

3}, Yong-Hee P Chun^{2

4}, Linda M McManus², Julie Barker², Amanda M Moore^{1

2}

Affiliations

¹ College of Pharmacy, The University of Texas at Austin, San Antonio, TX, USA.
² Long School of Medicine, University of Texas Health San Antonio, San Antonio, TX, USA.
³ South Texas Veterans Health Care System, San Antonio, TX, USA.
⁴ School of Dentistry, University of Texas Health San Antonio, San Antonio, TX, USA.

Abstract

Research education and training in Translational Science develops and sustains a workforce to efficiently advance studies designed to improve human health. We evaluated the effectiveness of a Translational Science Training (TST) TL1 Program. Participants had significantly better publications/year, citations/year, h-index, and m-quotient than nonparticipants. Female and male participants, and participants from underrepresented and well-represented backgrounds, performed similarly on all bibliometric assessments. Finally, TST/TL1 Program participants outperformed students from other PhD programs at our institution. This analysis suggests that the TST/TL1 Program has been effective for participants, including those who are female and from underrepresented backgrounds.

Keywords: NIH training program; T32; TL1; Translational science; bibliometrics; comparative-effectiveness; disparities; sex differences; underrepresented backgrounds.