Predictors of performance on NCLEX-RN for baccalaureate nursing graduates

Date of Completion

January 1988

Keywords

Health Sciences, Education|Education, Educational Psychology|Health Sciences, Nursing

Degree

Ph.D.

Abstract

The relationship between selected demographic and academic predictors of performance of baccalaureate nursing graduates on the National Council Licensure Examination for Registered Nurses (NCLEX-RN) is the focus of this study. Also, an optimal time for identification of an at-risk group is presented. The current nursing shortage, which is exacerbated by declining enrollments and examination failure make it imperative to identify characteristics of successful baccalaureate nursing graduates in order to attract qualified candidates and retain them. An information-feedback systems framework proposes that characteristics of individuals prior to entry to college and the nursing program as well as their achievement in the nursing program are determinants of performance on the licensure examination. The sample is 501 nursing graduates from the classes of 1982 through 1986 at a public college in the Northeast. A double cross-validation strategy demonstrates the stability of the regression equation with correlations of.65 and.69 between actual and predicted NCLEX-RN scores. The hierarchical regression analysis results in an equation with five significant predictors and accounts for 52.4% of the variance in NCLEX-RN scores. The significant predictors are two entry characteristics, age and SAT-verbal score, and three nursing program variables, GPA's of the nursing courses second semester sophomore year, first semester junior year, and second semester junior year. The optimal time for predicting an at-risk group is the end of the junior year. The regression equation from this time classifies all but five of the cases known to have failed the examination in the at-risk group; however, this groups also includes a large number of cases known to have passed NCLEX-RN. Therefore, the classification is correct for only 25.8% of the at-risk group. The implications of the study findings include: first, to identify an at-risk group for further screening; second, to assess and strengthen the congruence between the curriculum and the content of the licensure examination; third, to employ causal models in future research; and fourth, to include variables from other domains in future research. ^

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