The National Council Licensing Exam (NCLEX) is a standardized examination ensures that nurses starting their career meet a minimum standard of knowledge and safety (National Council State Board of Nursing, 2018). The National Council of State Board of Nursing analyzes the passing scores of all candidates by nursing program and shares that information with each State Board of Nursing (SBON). First-time pass rate of candidates is used as a measure of the success of a nursing program. Each state board of nursing (SBON) sets a defined expectation of first-time pass rate during a one year period that nursing programs are required to meet as well as the consequences if that minimum is not met. In addition, schools and colleges must obtain accreditation of their program in which the NCLEX pass-rate is one of the evaluative measures. As a result of the mandate to protect the public with a minimum safety level of care as well as obtaining the required first time pass rate, nursing programs spend significant time and energy preparing students for success in the NCLEX examination (Emory, 2013).
Purpose:
The purpose of this retrospective study is to develop a predictive model for NCLEX outcome in a traditional baccalaureate nursing school population. The specific research question is: Which academic aptitude, nursing aptitude and standardized examination variables are the most powerful predictors NCLEX-RN outcome?
Methods:
This retrospective project used a convenience sample of BSN graduates from a traditional BSN program at a private university in northeastern Pennsylvania. The sample included all graduates from 2017 (n=127) who took the NCLEX-RN licensure examination.
The dependent variable in the study was success on the NCLEX-RN (1=pass, 0=fail) on the first attempt. The independent variables included in the model are: prerequisite GPA which includes final semester grades from Introduction to psychology, Introduction to sociology, two social science electives, Chemistry, Anatomy and Physiology I and II, Microbiology, Ethics, English reading thinking and writing, English Literature, two humanities electives, and statistics; Nursing GPA which includes final grades from Introduction to Nursing, Informatics I and II, Nutrition, Research Design, Evidence Based-Practice, Health assessment, Pharmacokinetics, Medical Surgical Nursing I, II, and III, Pathopharmacology I, II, and III, Family focused Maternal Newborn Care, Family Focused Care of Children, Gerontology, Knowledge Synthesis I, II, III, and IV, Nursing Leadership, Psychiatric/MentalHealth Nursing, and Population Health Nursing; as well as cumulative GPA for the program. The scores on the standardized examinations for Health Assessment, Pathopharmacology I and II (custom examinations), pharmacology, pathophysiology, Medical surgical nursing I and II (custom examinations), Medical Surgical, Maternal Newborn, Pediatrics, Leadership, Psych/Mental Health, Population Health, Custom exit examination (N4747 without leadership content), and comprehensive exit examination in spring senior year. Course grades in Medical Surgical Nursing I, II and III, and Pathopharmacology I, II, & III were also added based upon the literature.
Results:
Utilizing forward stepwise logistic regression, the 27 variables were entered into the model based upon their statistical score and removed based upon the likelihood ratio. Several variables including prerequisite GPA, Medical Surgical Nursing II HESI, Pathopharmacology III Pharmacology HESI, Population Health HESI and Leadership HESI were not entered into the model due lack of significance. The forward LR regression developed a 5 step model. Step 5 was the most predictive, correctly identifying the candidates that failed 50% of the time and the candidates that passed 99.1 % of the time. This step of the model contained the following variables: Health Assessment HESI (NURS 261), Medical Surgical Nursing II final grades (NURS 331), Pathophysiology III final grade (NURS 405), Psych/Mental Health Nursing HESI (NURS 465), Knowledge Synthesis III first Exit HESI (NURS 474). The grades from medical-surgical nursing II and pathophysiology III were most strongly correlated with NCLEX success.
Conclusion:
Predicting NCLEX-RN outcomes will continue to be a goal of nursing education research despite the conflicting evidence in the literature. The results of failing the NCLEX-RN impacts candidates as they cannot begin employment until they have been successful; nursing programs as they run the risk of negative consequences for poor NCLEX pass scores; and society as it is faced with a nursing shortage. While there is no one model that predicts NCLEX outcomes 100% of the time, this model identifies several measures that programs can use to identify students who are at risk.
Future research should include datasets with a significant number of candidates who failed the NCLEX-RN. This will produce a more reliable model. In addition, testing this model utilizing results from a variety of commercially available standardized examinations may support the predictability of one product over another. Expanding this project to include data from a variety of programs with different curricular ladders will strengthen the results as well as including diploma, associate and accelerated nursing programs. Finally, the NCLEX-RN is revised every three years with the next revision in 2019. The model should be re-evaluated based upon the results of the 2019 NCLEX-RN. Through a thorough evaluation of variables that predict NCLEX outcomes, nursing programs can identify at risk individuals, provide remediation and support in nursing school and address the nursing shortage.