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PLoS One ; 15(6): e0234259, 2020.
Article in English | MEDLINE | ID: mdl-32516342

ABSTRACT

Young biomedical PhD scientists are needed in a wide variety of careers. Many recent efforts have been focused on revising training approaches to help them choose and prepare for different careers. However, very little is known about how biomedical PhD students decide on and "differentiate" into careers, which limits the development of new training models. This knowledge gap also severely limits efforts to increase the representation of women and some racial/ethnic groups in academic research careers. Previous studies have used cross-sectional surveys of career interests and ratings, and have not been designed to identify career intentions. They also are limited by single-time data and response bias, having typically asked participants to recount decisions made years in the past. This report draws on annual, in-depth interviews with 147 biomedical PhD students from the start of the PhD to graduation. Qualitative content analysis methods were used to fully understand scientific development and career intentions over time. Longitudinal analysis reveals a striking level of fluidity and complexity in career intentions over time. Contrary to previous studies and the dominant narrative, data do not show generalized shifts away from academic careers. In addition to those who are consistent in this intention from the start, nearly as many students shift toward research academic careers as away from them, and only modest differences exist by gender and race/ethnicity. Thus, the dominant narrative misses the high fraction of individuals who acquire or sustain their intention to purse an academic research career during training. Efforts to increase diversity in academia must capitalize on and support those who are still considering and evolve toward an academic career. Efforts to revise research training should incorporate knowledge of the tremendous fluidity in when and how career differentiation occurs.


Subject(s)
Biomedical Research/statistics & numerical data , Career Choice , Education, Graduate/statistics & numerical data , Students/statistics & numerical data , Adult , Female , Humans , Longitudinal Studies , Male , Young Adult
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