Predictors of Success on the Canadian Nurses Association Testing Service (CNATS) Examination

Barbara Carpio, Linda O'Mara, Jocelyn Hezekiah


This retrospective study examined the relationship of selected admissions variables and in-course performance to success in the Canadian Nurses Association Testing Service (CNATS) examinations of 114 students admitted directly from secondary school to a four-year integrated, problem-based learning (FBL) baccalaureate nursing program in Canada. Data were analyzed using two separate hierarchical stepwise regression equations. The first equation examined a set of secondary school grades (Ontario Academic Credits, or OACs) used to calculate university admission averages and their ability to predict CNATS performance. OAC English was found to be the best predictor, followed by OAC chemistry and the admission average obtained on other OAC subjects. The second regression equation looked at in-course grades as potential predictors of CNATS scores. The basic sciences variable proved to be the best predictor, followed by research methodology, first-year Nursing Concepts I, a problem-based nursing average, and a clinical practice average. Findings support the continued use of English and chemistry as admission criteria. The basic sciences courses and first-year nursing courses also emerged as statistically significant predictors of licensure examination success.

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