Emotional Intelligence: Attrition and Attainment in Nursing and Midwifery Education

Abstract

Abstract: Attrition in Higher Education continues to present academics, researchers and professionals with an ongoing dilemma. Achieving a fair balance between the academic rigour of meritocracy and the wider access agenda of social inclusion, demands that entrance criteria incorporates measures beyond the traditional prior academic attainment. Emotional Intelligence has been presented in the literature as a valid and reliable predictor of retention and performance in industry and researchers have suggested that similar benefits may be found in education. In this dissertation, the construct of Emotional Intelligence was explored, reviewing contemporary models and their respective measurement tools. A self report tool for measuring ‘trait’ Emotional Intelligence was selected from the review and used to examine the predictive relationship between emotional intelligence and the outcomes at the end of the first year of undergraduate nurse education namely: clinical practice performance; academic performance and course attrition by nursing and midwifery students. The sample group consisted of a cohort of student nurses and midwives (N = 178) who commenced their training in 2007. A significant predictive relationship was found between emotional intelligence and clinical practice performance (r = 0.75, N = 116, p < 0.05); emotional intelligence and academic performance (r = 0.16, N = 168, p < 0.05) and emotional intelligence and attrition (r = 0.31, N = 178, p < 0.05). Age was also found to predict attrition (r = 0.25, N = 178, p < 0.05) while prior academic attainment was found to predict academic performance (r = 0.20, N = 168, p < 0.05). The dissertation proposes the inclusion of measures of emotional intelligence as an aid to recruitment and selection processes in nurse and midwifery education. It also recommends that other practice based vocational programmes, within the higher education sector, consider exploring emotional intelligence in their recruitment and selection processes.