A multilevel latent profile analysis to job demands, job resources, and personal resources in early childhood educators: Implications for multidimensional well-being

Abstract

Early childhood educators' (ECEs) well-being is important for many outcomes. Drawing on the job demands-resources model, many variable-centered studies have found that job demands, job resources, and personal resources are linked to ECEs' well-being. Yet, little is known about the heterogeneity of these demands and resources and their implications for well-being, especially considering school-level effects and the adoption of a holistic view of well-being. This study used multilevel latent profile analysis to examine these issues. Participants included 1198 Chinese ECEs from 50 kindergartens who reported their job demands (i.e., quantitative, cognitive, and emotional demands), job resources (i.e., influence at work, quality of leadership, support from supervisors and colleagues, and sense of community at work), and personal resources (i.e., self-control and resilience). At the teacher-level, four profiles emerged: (a) at risk, (b) undemanded, (c) safeguarded, and (d) vulnerable learners. ECEs with lower salaries, higher educational levels, and larger class sizes were more likely assigned to the at-risk profile. Teachers in the at-risk and the safeguarded profiles reported the worst and the best well-being, respectively. Demands (in particular quantitative and emotional demands) appeared more critical than resources in distinguishing well-being. At the school-level, two profiles emerged: (a) high demand climate and (b) mixed climate. Kindergartens in Hong Kong were more likely assigned to the high demand climate profile and kindergartens with a high demand climate showed poorer school average well-being. This study reveals the complex configuration of job demands, job resources, and personal resources in ECEs and its implications for well-being at both teacher- and school-levels. The findings also inform strategies to enhance ECEs' well-being.