1.Preadmission predictors of graduation success from a physical therapy education program in the United States
Gretchen ROMAN ; Matthew Paul BUMAN
Journal of Educational Evaluation for Health Professions 2019;16(1):5-
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, 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 was 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 the essay.
Cohort Studies
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Education
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Freedom
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School Admission Criteria
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United States
2.Preadmission predictors of graduation success from a physical therapy education program in the United States
Gretchen ROMAN ; Matthew Paul BUMAN
Journal of Educational Evaluation for Health Professions 2019;16():5-
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, 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 was 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 the essay.