title: Can success and failure be predicted for baccalaureate graduates on the computerized NCLEX-RN?
abstract: The current shortage of nurses and declining national pass rate on the National Council Licensure Examination for Registered Nurses (NCLEX-RN) has heightened educators' interest in identifying students at risk for failure. A retrospective descriptive study was conducted at a rural, public baccalaureate nursing program to determine variables that best predict NCLEX-RN success and failure. Data collected from 1998 through 2002 (N = 186) included entry as native or transfer student, preadmission grade point average (GPA), GPA after completing one semester of nursing courses, cumulative GPA at graduation, grades earned in prerequisite and core nursing courses, test averages in beginning and advanced medical/surgical nursing courses, and performance on the National League for Nursing Comprehensive Achievement Test for Baccalaureate Students (NLNCATBS). Logistic regression analysis revealed that a combination of test average in advanced medical/surgical nursing and percentile score on the NLNCATBS predicted 94.7 percent of NCLEX-RN passes and 33.3 percent of failures. The combination of NLNCATBS score and pathophysiology grade predicted 93.3 percent of NCLEX-RN passes and 50 percent of failures. Although success could be accurately predicted across all models, predicting failure was far more difficult.
authors.affiliation: Department of Nursing, Salisbury University, 1101 Camden Avenue, Salisbury, MD 21801, USA. laseldomridge@salisbury.edu
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Seldomridge
authors.forename: Mary C
authors.initials: MC
authors.lastname: Dibartolo
mesh_terms: D000124:Achievement; D000715:Anatomy / Q000193:education; D002621:Chemistry / Q000193:education; D003194:Computer-Assisted Instruction / Q000592:standards*; D004508:Education, Nursing, Baccalaureate / Q000592:standards*; D004521:Educational Measurement / Q000379:methods* / Q000592:standards; D004522:Educational Status; D005260:Female; D006801:Humans; D008008:Licensure, Nursing; D016015:Logistic Models; D008297:Male; D008873:Mid-Atlantic Region; D015999:Multivariate Analysis; D015402:Nursing Education Research; D010827:Physiology / Q000193:education; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012570:School Admission Criteria; D013223:Statistics as Topic / Q000193:education