An exploration of the predictive validity of selection criteria on progress outcomes for pre-registration nursing...

To identify the selection methods currently being used for pre-registration nursing programmes and to assess the predictive power that these methods have on students' success.

Research into selection methods in nursing education is beginning to emerge, yet it is unclear which methods are most predictive of students' success.

A systematic review of the literature.

A systematic search of ten electronic databases: CINAHL, MEDLINE Ovid, EMBASE, PROQUEST Health and Medical, PROQUEST Education, COCHRANE Library, Web of Science, ASSIA, SCOPUS and PROSPERO was conducted. The results were expanded by the handsearching of journals, reference lists and grey literature. The PRISMA statement guided the review. Studies published in English between January 2008-March 2020 were eligible for inclusion, and quality assessment was undertaken using the CASP Checklist for Cohort Studies.

Twenty-five studies met the criteria for inclusion. A range of selection methods was identified including prior academic achievement, admissions tests, interviews, emotional intelligence tests, personal statements and previous healthcare experience. Prior academic achievement and admissions tests appear to be the selection methods most predictive of student success. The evidence surrounding other selection methods such as interviews and personal statements is less conclusive.

Selecting individuals with the appropriate knowledge, interpersonal skills and personal qualities needed to complete an undergraduate nursing programme is an important part of the role of nurse educators. This review shows that a wide variety of selection methods are used across different institutions, some of which are more effective than others in predicting student outcomes.

Further research is required to justify the continued use of some commonly used selection methods for undergraduate nursing programmes. Selection models that combine various types of selection criteria with predictive power appear to increase the probability of selecting students that will have successful outcomes.