In:
PLOS ONE, Public Library of Science (PLoS), Vol. 18, No. 1 ( 2023-1-13), p. e0280325-
Abstract:
To advance understanding of doctoral student experiences and the high attrition rates among Science, Technology, Engineering, and Mathematics (STEM) doctoral students, we developed and examined the psychological profiles of different types of doctoral students. We used latent class analysis on self-reported psychological data relevant to psychological threat from 1,081 incoming doctoral students across three universities and found that the best-fitting model delineated four threat classes: Lowest Threat , Nonchalant , Engaged/Worried , and Highest Threat . These classes were associated with characteristics measured at the beginning of students’ first semester of graduate school that may influence attrition risk, including differences in academic preparation (e.g., amount of research experience), self-evaluations and perceived fit (e.g., sense of belonging), attitudes towards graduate school and academia (e.g., strength of motivation), and interpersonal relations (e.g., perceived social support). Lowest Threat students tended to report the most positive characteristics and Highest Threat students the most negative characteristics, whereas the results for Nonchalant and Engaged/Worried students were more mixed. Ultimately, we suggest that Engaged/Worried and Highest Threat students are at relatively high risk of attrition. Moreover, the demographic distributions of profiles differed, with members of groups more likely to face social identity threat (e.g., women) being overrepresented in a higher threat profile (i.e., Engaged/Worried students) and underrepresented in lower threat profiles (i.e., Lowest Threat and Nonchalant students). We conclude that doctoral students meaningfully vary in their psychological threat at the beginning of graduate study and suggest that these differences may portend divergent outcomes.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0280325
DOI:
10.1371/journal.pone.0280325.g001
DOI:
10.1371/journal.pone.0280325.g002
DOI:
10.1371/journal.pone.0280325.t001
DOI:
10.1371/journal.pone.0280325.t002
DOI:
10.1371/journal.pone.0280325.t003
DOI:
10.1371/journal.pone.0280325.t004
DOI:
10.1371/journal.pone.0280325.t005
DOI:
10.1371/journal.pone.0280325.t006
DOI:
10.1371/journal.pone.0280325.t007
DOI:
10.1371/journal.pone.0280325.s001
DOI:
10.1371/journal.pone.0280325.s002
DOI:
10.1371/journal.pone.0280325.s003
DOI:
10.1371/journal.pone.0280325.s004
DOI:
10.1371/journal.pone.0280325.s005
DOI:
10.1371/journal.pone.0280325.s006
DOI:
10.1371/journal.pone.0280325.s007
DOI:
10.1371/journal.pone.0280325.s008
DOI:
10.1371/journal.pone.0280325.s009
DOI:
10.1371/journal.pone.0280325.s010
DOI:
10.1371/journal.pone.0280325.s011
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2023
detail.hit.zdb_id:
2267670-3
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