Emotional Intelligence, Work Engagement, and Turnover Intention Among Hospital Nurses: A Hierarchical Component Analysis - Catrin Catrin; Christopher Wisnu; Pauline Henriette Pattyranie Tan (Fakultas Ilmu Keperawatan Universitas Indonesia, 2026)
High turnover intention among hospital nurses poses serious challenges to healthcare organizations, affecting service quality and workforce stability. Understanding the psychological and organizational factors associated with turnover intention is essential for developing effective retention strategies. This study aimed to examine the relationships among emotional intelligence, work engagement, and turnover intention among hospital nurses, including health‑promoting leadership, workload, and burnout as contextual variables within the model. A cross-sectional study was conducted among 98 nurses working in inpatient units using validated questionnaires. The data were analyzed using partial least squares structural equation modeling (PLS-SEM) with hierarchical component analysis. Emotional intelligence significantly predicted work engagement (β = 0.507, p = 0.001). Work engagement showed a strong negative association with turnover intention (β = −0.610, p < 0.001), while burnout was positively associated with turnover intention (β = 0.385, p = 0.005). In contrast, health-promoting leadership and workload did not show significant effects on work engagement or burnout. Mediation analysis indicated that work engagement significantly mediated the relationship between emotional intelligence and turnover intention (β = −0.309, p = 0.003). The model explained 24.5% of variance in work engagement and 31.6% of variance in turnover intention. These findings suggest that work engagement represents an important pathway linking emotional intelligence to turnover intention among nurses. Strategies aimed at strengthening nurses’ emotional intelligence and fostering work engagement may help reduce turnover intention in hospital settings. This study contributes to the literature by applying hierarchical component analysis within a PLS-SEM framework to simultaneously examine multiple psychological and organizational predictors of turnover intention in the Indonesian hospital context.