A method for predicting a student's risk for academic probation in a professional program in allied health

Identification of students at risk for academic difficulty in a physical therapy program would provide opportunities to implement preemptive measures designed to enhance successful academic performance. The purpose of this study was to determine if a method advocated for use in evidence-based practice could be adapted for use in predicting probationary status for students in a program in allied health, specifically physical therapy. Preadmission combined math and science grade point average; cumulative grade point average (TGPA); verbal Graduate Record Examination score (VGRE), quantitative Graduate Record Examination score (QGRE), and analytic Graduate Record Examination score; and probation status were obtained for 305 students (mean age, 25.5 years; SD, 4.14) accepted into one physical therapy program from 1995 to 2000. Predictors of probation were identified using stepwise logistic regression. Likelihood ratios were calculated for three score intervals derived from receiver operating characteristic analysis. TGPA, VGRE, and QGRE were significant predictors in the regression model (p < 0.05). VGRE was the only variable that consistently showed predictive capability (likelihood ratio, 2.9; 95% confidence interval, 1.2-6.9). Quantitative preadmission data can be used in combination to improve the predictive power of estimates of probation risk. We contend that the analytic methods illustrated in this report could be used in academic programs to assist faculty with management of students who are at risk for academic difficulties.