Currents in pharmacy teaching & learning · 2019
A model to predict NAPLEX outcomes and identify students needing additional preparation.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Shah Sachin, Peng Iverlyn, Seifert Charles F
Аннотация
INTRODUCTION: Studies have been conducted to identify factors that may predict North American Pharmacist Licensure Examination (NAPLEX) outcomes, but there is no proposed single or combination of predictors that can be implemented reliably in academia. We aimed to develop a NAPLEX outcomes predictive model that could be practical, measurable, and reliable.
METHODS: The study cohort consisted of students who graduated from 2012 to 2016 who had taken NAPLEX and whose first-attempt examination scores were available to the school of pharmacy. Students were considered to have poor performance on NAPLEX if they received an overall score of less than or equal to 82. Linear and logistic regression analysis were utilized to identify independent predictors.
RESULTS: Seventy of 433 (16.2%) students were identified as poor performers. Independent factors that were associated with a poor outcome on NAPLEX were: age >28 years at graduation, Pharmacy College Admission Test scaled score <74, High Risk Drug Knowledge Assessment score <90, third-year Pharmacy Curriculum Outcome Assessment scaled score <349, and grades of <74 in more than three courses. These predictors were utilized to stratify students into four risk groups: Low, Intermediate-1, Intermediate-2, and High. Mean NAPLEX scores for these groups were 106.4, 97.4, 87.1, and 75.1, respectively.
CONCLUSIONS: The model can be used as a practical tool to identify students who are at risk for poor performance on NAPLEX. Four of the five predictors in the model could be generalizable to other schools of pharmacy.
METHODS: The study cohort consisted of students who graduated from 2012 to 2016 who had taken NAPLEX and whose first-attempt examination scores were available to the school of pharmacy. Students were considered to have poor performance on NAPLEX if they received an overall score of less than or equal to 82. Linear and logistic regression analysis were utilized to identify independent predictors.
RESULTS: Seventy of 433 (16.2%) students were identified as poor performers. Independent factors that were associated with a poor outcome on NAPLEX were: age >28 years at graduation, Pharmacy College Admission Test scaled score <74, High Risk Drug Knowledge Assessment score <90, third-year Pharmacy Curriculum Outcome Assessment scaled score <349, and grades of <74 in more than three courses. These predictors were utilized to stratify students into four risk groups: Low, Intermediate-1, Intermediate-2, and High. Mean NAPLEX scores for these groups were 106.4, 97.4, 87.1, and 75.1, respectively.
CONCLUSIONS: The model can be used as a practical tool to identify students who are at risk for poor performance on NAPLEX. Four of the five predictors in the model could be generalizable to other schools of pharmacy.