Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.

Developing scientific and medical innovations continue to be limited by lack of diverse representation among leaders and learners. One key gateway for these goals is graduate school admissions, but comprehensive consideration of all components of applications, which is needed to reduce systemic bias...

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Main Authors: Minerva A Orellana, Danielle J Beetler, Carmen J Silvano, Ryan Wuertz, Jennifer L Weisbrod, Lewis R Roberts, Anthony J Windebank, Felicity T Enders, Marina R Walther-Antonio
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0323426
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author Minerva A Orellana
Danielle J Beetler
Carmen J Silvano
Ryan Wuertz
Jennifer L Weisbrod
Lewis R Roberts
Anthony J Windebank
Felicity T Enders
Marina R Walther-Antonio
author_facet Minerva A Orellana
Danielle J Beetler
Carmen J Silvano
Ryan Wuertz
Jennifer L Weisbrod
Lewis R Roberts
Anthony J Windebank
Felicity T Enders
Marina R Walther-Antonio
author_sort Minerva A Orellana
collection DOAJ
description Developing scientific and medical innovations continue to be limited by lack of diverse representation among leaders and learners. One key gateway for these goals is graduate school admissions, but comprehensive consideration of all components of applications, which is needed to reduce systemic bias in admissions, is resource intensive. This case study details the conceptualization of an integrative application review process to challenge and improve classic application review frameworks which gatekeep admissions opportunities from under-represented (UR) applicants. PhD applicant cohorts to a longstanding Clinical and Translational Sciences PhD TL1 program were assessed using one of three review processes: traditional, algorithmic, or a novel integrative review process. Admissions results from each review process were pooled across matriculation years to attain a testable sample size. Effects modification models were used to assess odds of reaching each admissions phase, adjusting for UR status and review process. Results showed that classic admissions review processes were prone to bias towards admission of specific students while integrative application review did not demonstrate this trend. The Mayo Clinic Graduate School of Biomedical Sciences Clinical and Translational Sciences training program has steadily recruited and trained successful and diverse trainee cohorts over the last decade from many underrepresented backgrounds. The final adoption of an integrative application review process allows streamlined graduate school admissions of diverse student cohorts, prioritizing self-driven narratives and minimizing subjective biases where possible to allow fair assessment of learners.
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spelling doaj-art-7a218a0a837945f1acd94e892f4e323d2025-07-24T05:31:16ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01206e032342610.1371/journal.pone.0323426Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.Minerva A OrellanaDanielle J BeetlerCarmen J SilvanoRyan WuertzJennifer L WeisbrodLewis R RobertsAnthony J WindebankFelicity T EndersMarina R Walther-AntonioDeveloping scientific and medical innovations continue to be limited by lack of diverse representation among leaders and learners. One key gateway for these goals is graduate school admissions, but comprehensive consideration of all components of applications, which is needed to reduce systemic bias in admissions, is resource intensive. This case study details the conceptualization of an integrative application review process to challenge and improve classic application review frameworks which gatekeep admissions opportunities from under-represented (UR) applicants. PhD applicant cohorts to a longstanding Clinical and Translational Sciences PhD TL1 program were assessed using one of three review processes: traditional, algorithmic, or a novel integrative review process. Admissions results from each review process were pooled across matriculation years to attain a testable sample size. Effects modification models were used to assess odds of reaching each admissions phase, adjusting for UR status and review process. Results showed that classic admissions review processes were prone to bias towards admission of specific students while integrative application review did not demonstrate this trend. The Mayo Clinic Graduate School of Biomedical Sciences Clinical and Translational Sciences training program has steadily recruited and trained successful and diverse trainee cohorts over the last decade from many underrepresented backgrounds. The final adoption of an integrative application review process allows streamlined graduate school admissions of diverse student cohorts, prioritizing self-driven narratives and minimizing subjective biases where possible to allow fair assessment of learners.https://doi.org/10.1371/journal.pone.0323426
spellingShingle Minerva A Orellana
Danielle J Beetler
Carmen J Silvano
Ryan Wuertz
Jennifer L Weisbrod
Lewis R Roberts
Anthony J Windebank
Felicity T Enders
Marina R Walther-Antonio
Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.
PLoS ONE
title Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.
title_full Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.
title_fullStr Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.
title_full_unstemmed Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.
title_short Integrative review in PhD admissions: A case study of efficiently minimizing bias while maximizing the student narrative.
title_sort integrative review in phd admissions a case study of efficiently minimizing bias while maximizing the student narrative
url https://doi.org/10.1371/journal.pone.0323426
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