Background and Purpose.
A primary outcome of concern to the California State University, Sacramento physical therapy program is the ability of graduates to pass the National Physical Therapy Examination (NPTE) for licensure. The purpose of this case study was to identify the predictive strength of preadmission demographic factors, academic performance, and standardized test scores in graduates' ability to pass the NPTE.
Preadmission data from 11 years of graduates from a single Master of Physical Therapy (MPT) program (n = 320) were analyzed, including prerequisite grade point average (pGPA), analytic Graduate Record Examination (GRE), verbal GRE and quantitative GRE (qGRE) scores, sex, English as a second language (ESL) status, and NPTE test results. The bivariate association of each preadmission variable to NPTE success was assessed, and receiver operating characteristic curve analysis was performed to determine the optimal cutoff score of each continuous variable. Multifactor logistic regression analysis was performed to determine which independent variables were most predictive of NPTE success.
Of the 320 MPT graduates, 284 (88.7%) passed the NPTE on the first attempt and 305 (95.3%) passed on the first or second attempt. Of all MPT graduates, 182 (57%) were females, and 57 (18%) reported that English was their second language. All three of the GRE subscale average scores, pGPA, and ESL were significantly associated with NPTE outcomes. Persons with ESL were significantly more likely to need more than one attempt to pass the NPTE. The qGRE score was found to be the strongest predictor of NPTE outcomes in the multifactor logistic regression analysis, whether looking at first-time passing rates or second-time pass rates.
Discussion and Conclusion.
The strongest preadmission variable for NPTE success was the qGRE score of ≥29th percentile, and this cutoff score explained the variance predicted by ESL and pGPA. The admission committee used this data to implement an evidence-based admission's minimum threshold for qGRE. This case is an example of how a physical therapist education program can analyze its own data to apply evidence to its admission criteria that best serve the mission of the program.