Medical education online · 2026
Using academic admissions data to predict PA training attrition and academic difficulties: a survival analysis approach.
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Waynick Joshua, Hussaini Sobia Shariff, Stonerook Ethan, Hiatt Tiffany, Sisson Caroline, Peacock Brian, O'Neal Sarah, McKinnond Andrea, Steele Laiton, Gillette Chris
Аннотация
BACKGROUND: Research studying health professions' student attrition and academic difficulties generally treat these outcomes as dichotomous variables that obscure important time-varying aspects. Scant attention has been paid to incorporating time-varying methods, such as survival analysis, to model attrition and academic difficulties in health professions trainees.
OBJECTIVE: The objectives of this study are to (1) identify when students were most likely to attrit from the program and/or experience academic probation and (2) identify predictors of time to attrition and academic probation using undergraduate student performance metrics.
DESIGN: Using a database of physician associate (PA) student admissions variables and academic performance, we examined the relationship between time-to-attrition and time-to-first-probation using semi-parametric multivariable Cox Proportional Hazards models. Results are presented in adjusted Hazards Ratios (HR) with 95% Confidence Intervals (CI).
RESULTS: The rate at which students experienced at least one probation event was 131 per 19,563.5 person-weeks. The rate of students who experienced an attrition event was 32 per 22,210 person-weeks. Overall GPA (aHR = 0.16, 95% CI = 0.08-0.33), verbal GRE scores (aHR = 0.91, 95% CI = 0.87-0.94), having a science major in undergraduate studies (aHR = 0.43, 95% CI = 0.26-0.69) and number of undergraduate course withdrawals (aHR = 1.14, 95% CI = 1.05-1.24) were associated with time to first probation. Verbal GRE scores (aHR = 0.87, 95% CI = 0.80-0.94) and number of undergraduate course withdrawals (aHR = 1.24, 95% CI = 1.08-1.43) were associated with time to attrition.
CONCLUSIONS: We employed a novel application of survival analysis to predict PA school attrition and academic probation using an entire cohort of students. Our work informs admissions policies by identifying students at-risk of academic probation and attrition who may need more academic support prior to program matriculation.
OBJECTIVE: The objectives of this study are to (1) identify when students were most likely to attrit from the program and/or experience academic probation and (2) identify predictors of time to attrition and academic probation using undergraduate student performance metrics.
DESIGN: Using a database of physician associate (PA) student admissions variables and academic performance, we examined the relationship between time-to-attrition and time-to-first-probation using semi-parametric multivariable Cox Proportional Hazards models. Results are presented in adjusted Hazards Ratios (HR) with 95% Confidence Intervals (CI).
RESULTS: The rate at which students experienced at least one probation event was 131 per 19,563.5 person-weeks. The rate of students who experienced an attrition event was 32 per 22,210 person-weeks. Overall GPA (aHR = 0.16, 95% CI = 0.08-0.33), verbal GRE scores (aHR = 0.91, 95% CI = 0.87-0.94), having a science major in undergraduate studies (aHR = 0.43, 95% CI = 0.26-0.69) and number of undergraduate course withdrawals (aHR = 1.14, 95% CI = 1.05-1.24) were associated with time to first probation. Verbal GRE scores (aHR = 0.87, 95% CI = 0.80-0.94) and number of undergraduate course withdrawals (aHR = 1.24, 95% CI = 1.08-1.43) were associated with time to attrition.
CONCLUSIONS: We employed a novel application of survival analysis to predict PA school attrition and academic probation using an entire cohort of students. Our work informs admissions policies by identifying students at-risk of academic probation and attrition who may need more academic support prior to program matriculation.