An exploration of the predictive validity of the selection criteria for nursing programmes at one university in the United Kingdom

Abstract

This study investigated the predictive validity of the selection methods and demographic characteristics of applicants for the pre-registration undergraduate nursing programmes at one university in the United Kingdom (UK). The UK average attrition rate for pre-registration undergraduate nursing programmes is 24 percent, with the average rising to as much as 50 percent in the United States of America. Yet the number of applications received for places on these programmes far exceeds the number of positions available. People who are awarded a position on a nursing programme must have the ability to meet the minimum standards of clinical and academic work to enable them to complete the course, making them eligible to apply to register as a nurse.

The decision to admit someone onto a nursing programme rests on the selection process, which the literature tells us comprises elements of prior academic achievement, admissions tests, interviews, psychometric tests or autobiographical essays. Little is known if these methods have the ability to predict those who will complete and excel in nursing programmes, and it is not clear if a particular group of students is more or less likely to fail – i.e., not achieve their outcomes.

Using the work of Dr Alan Seidman into the retention of university students in higher education as the conceptual framework, this study sought to explore the relationships between selection scores and demographic characteristics with programme outcomes for the undergraduate nursing programmes at Ulster University. Application and demographic data pertaining to the 2012 – 2016 cohorts for the Adult and Mental Health pre-registration nursing programmes were gathered, including participants’ age, gender, entry route, socioeconomic status and specific learning difficulty status. The participants’ selection scores (personal statements, Universities and College Admission Service (UCAS) scores and interview scores) were also gathered, and their programme outcomes which included enrolment rates, course completion rates and academic grading throughout the programme.

A range of statistical analysis were employed to determine the relationships between the variables including Pearson’s correlations, cross-tabulations, analysis of variance (ANOVA) and linear regression. The demographic characteristics and selection scores were simultaneously entered into a model using path analysis to determine the effect that these variables had on academic outcomes.

The findings showed that there is an association with increasing age and successful enrolment on the nursing courses. Applicants who had attended further education colleges undertaking programmes such as the Access Diploma or Business and Technology Education Council (BTEC) were more likely to enrol than those who were attending school and undertaking Advanced (A) -levels. There was also an association with increasing age, affluence, UCAS scores and interview scores with increasing grade averages. Students with previous degrees outperformed their peers. Nevertheless, the relationships between all variables were weak at best. Gender and personal statements did not correlate with any programme outcomes. The largest correlations could be seen between the academic grade averages in year 1, 2 and 3, which told us that first-year performance was the strongest predictor of year three outcomes. Those with specific learning difficulties performed almost on par with those who did not have specific learning difficulties.

The selection process for nursing programmes should be based on evidence and not tradition or expert opinion. The weak relationships uncovered between selection methods and programme outcomes should be considered when reviewing selection processes at universities. In the absence of clear demographic characteristics that can predict student outcomes, a system of self-referral for students who need support with learning needs should be encouraged by academic staff. This would assist students at the earliest opportunity in their educational journey to help them to achieve their educational goals, and subsequently maximise the number of nursing students transitioning into the nursing profession.

Date of Award	Sep 2022
Original language	English
Supervisor	Pauline Black (Supervisor), Ben Fitzpatrick (Supervisor) & Vidar Melby (Supervisor)