Objective. To examine the relationship between the NAPLEX and Pre-NAPLEX among pharmacy graduates, as well as determine effects of pre-pharmacy, pharmacy school, and demographic variables on NAPLEX performance. Methods. A retrospective review of pharmacy graduates’ NAPLEX scores, Pre-NAPLEX scores, demographics, pre-pharmacy academic performance factors, and pharmacy school academic performance factors was performed. Bivariate (eg, ANOVA, independent samples t-test) and correlational analyses were conducted, as was stepwise linear regression to examine the significance of Pre-NAPLEX score and other factors as related to NAPLEX score. Results. One hundred fifty graduates were included, with the majority being female (60.7%) and white (72%). Mean NAPLEX score was 104.7. Mean Pre-NAPLEX score was 68.6. White students had significantly higher NAPLEX scores compared to Black/African American students. NAPLEX score was correlated to Pre-NAPLEX score, race/ethnicity, PCAT composite and section scores, undergraduate overall and science GPAs, pharmacy GPA, and on-time graduation. The regression model included pharmacy GPA and Pre-NAPLEX score. Conclusion. The findings provide evidence that, although pharmacy GPA is the most critical determinant, the Pre-NAPLEX score is also a significant predictor of NAPLEX score.

With the increase of students applying to pharmacy programs, it is imperative that admissions committees choose appropriate measures to analyze student readiness. The purpose of this research was to identify significant factors that predict the academic performance, defined as grade point average (GPA) at the end of the first professional year, of pharmacy students. The population consisted of 466 students enrolled in a Doctor of Pharmacy Program in northeast Tennessee over a 5-year period. Statistical procedures included bivariate correlations, t-tests for independent samples, and multiple regression. Analysis of the data revealed that the majority of the students in the population were between 21 and 24 years of age, female, and White, non-Hispanic. Most were from the surrounding region, attended a 4-year undergraduate institution, and earned a bachelor’s degree prior to pharmacy school. Average PCAT scores were: 68 (Composite), 67 (Biology), 64 (Chemistry), 64 (Reading), 60 (Quantitative Ability), and 68 (Verbal Ability). The average undergraduate GPAs were 3.43 (cumulative) and 3.32 (math and science), whereas the average first-year pharmacy school GPA for the population was 3.33. Younger students tended to have higher first-year pharmacy GPAs than did older students. Students with higher PCAT Composite, Biology, Chemistry, or Verbal Ability scores also tended to have higher first-year pharmacy GPAs. Students in the population under study with high undergraduate math and science GPA or undergraduate cumulative GPA also tended to have a high first-year pharmacy GPA. Female students had higher first-year pharmacy GPAs than male students, and White, non-Hispanic students had higher first-year pharmacy GPAs than students of other races or ethnicities. Predictors of first-year performance differed based on gender and race or ethnicity, but cumulative and math and science undergraduate GPAs were consistently significant predictors. No significant difference in first-year pharmacy GPA was observed based on regional status, undergraduate institution type or location, or bachelor’s degree status. The linear combination of preadmission factors was significantly related to first-year pharmacy GPA using a multiple regression model, and the cumulative undergraduate GPA variable accounted for 25% of the variance in the first-year pharmacy GPA.

Objective. To examine the relationship between the NAPLEX and Pre-NAPLEX among pharmacy graduates, as well as determine effects of pre-pharmacy, pharmacy school, and demographic variables on NAPLEX performance. Methods. A retrospective review of pharmacy graduates' NAPLEX scores, Pre-NAPLEX scores, demographics, pre-pharmacy academic performance factors, and pharmacy school academic performance factors was performed. Bivariate (eg, ANOVA, independent samples t-test) and correlational analyses were conducted, as was stepwise linear regression to examine the significance of Pre-NAPLEX score and other factors as related to NAPLEX score. Results. One hundred fifty graduates were included, with the majority being female (60.7%) and white (72%). Mean NAPLEX score was 104.7. Mean Pre-NAPLEX score was 68.6. White students had significantly higher NAPLEX scores compared to Black/African American students. NAPLEX score was correlated to Pre-NAPLEX score, race/ethnicity, PCAT composite and section scores, undergraduate overall and science GPAs, pharmacy GPA, and on-time graduation. The regression model included pharmacy GPA and Pre-NAPLEX score. Conclusion. The findings provide evidence that, although pharmacy GPA is the most critical determinant, the Pre-NAPLEX score is also a significant predictor of NAPLEX score.