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Preadmission predictors of graduation success from a physical therapy education program in the United States
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Gretchen Roman
 , Matthew Paul Buman
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J Educ Eval Health Prof. 2019;16:5. Published online February 26, 2019
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DOI: https://doi.org/10.3352/jeehp.2019.16.5
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 Abstract
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- Purpose
The field of physical therapy education is seeking an evidence-based approach for admitting qualified applicants, as previous research has assessed various outcomes, impeding practical application. This study was conducted to identify preadmission criteria predictive of graduation success.
Methods
Data from the 2013–2016 graduating cohorts (n=149) were collected. Predictors included verbal Graduate Record Examination rank percentile (VGRE%), quantitative GRE rank percentile, and analytical GRE rank percentile, the admissions interview, precumulative science grade point average (SGPA), precumulative grade point average (UGPA), and a reflective essay. The National Physical Therapy Examination (NPTE) and grade point average at the time of graduation (GGPA) were used as measures of graduation success. Two separate mixed-effects models determined the associations of preadmission predictors with NPTE performance and GGPA.
Results
The NPTE model fit comparison showed significant results (degrees of freedom [df]=10, P=0.001), decreasing within-cohort variance by 59.5%. NPTE performance were associated with GGPA (β=125.21, P=0.001), and VGRE%, the interview, the essay, and GGPA (P≤0.001) impacted the model fit. The GGPA model fit comparison did not show significant results (df=8, P=0.56), decreasing within-cohort variance by 16.4%. The GGPA was associated with the interview (β=0.02, P=0.04) and UGPA (β=0.25, P=0.04), and VGRE%, the interview, UGPA, and the essay (P≤0.02) impacted model fit.
Conclusion
In our findings, GGPA predicted NPTE performance, and the interview and UGPA predicted GGPA. Unlike past evidence, SGPA showed no predictive power. The essay and VGRE% warrant attention because of their influence on model fit. We recommend that admissions ranking matrices place a greater weight on the interview, UGPA, VGRE%, and essay.
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Citations
Citations to this article as recorded by  - A Comparison of Physical Therapist Educational Outcomes Before and During the COVID-19 Pandemic: A Multicenter Study
Evan M. Pucillo, Jennifer Crowder, Catherine M. Andrea, Sean Brim, Leiselle Pilgrim, Norman Belleza
Journal of Physical Therapy Education.2024;[Epub] CrossRef - A Systematic Review of Variables Used in Physical Therapist Education Program Admissions Part 2: Noncognitive Variables
Andrea N. Bowens
Journal of Physical Therapy Education.2024;[Epub] CrossRef - Examining the Early Academic Performance of Doctor of Physical Therapy Students After Holistic Review: A Retrospective Cohort Study
Megan Eikenberry
Journal of Physical Therapy Education.2024;[Epub] CrossRef - Detecting Artificial Intelligence-Generated Personal Statements in Professional Physical Therapist Education Program Applications: A Lexical Analysis
John H Hollman, Beth A Cloud-Biebl, David A Krause, Darren Q Calley
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Journal of Physical Therapy Education.2023;[Epub] CrossRef - Predictors of Success on the National Physical Therapy Examination in 2 US Accelerated-Hybrid Doctor of Physical Therapy Programs
Breanna Reynolds, Casey Unverzagt, Alex Koszalinski, Roberta Gatlin, Jill Seale, Kendra Gagnon, Kareaion Eaton, Shane L. Koppenhaver
Journal of Physical Therapy Education.2022; 36(3): 225. CrossRef - Predicting graduate student performance – A case study
Jinghua Nie, Ashrafee Hossain
Journal of Further and Higher Education.2021; 45(4): 524. CrossRef - A Proposed Framework for Increasing Racial and Ethnic Diversity in Communication Sciences and Disorders Academic Programs: The REAP Model
Bijoyaa Mohapatra, Ranjini Mohan
Perspectives of the ASHA Special Interest Groups.2021; 6(4): 755. CrossRef - Doctor of Physical Therapy Student Grit as a Predictor of Academic Success: A Pilot Study
Rebecca Bliss, Erin Jacobson
Health Professions Education.2020; 6(4): 522. CrossRef
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