Exploring occupational well-being profiles, outcomes, and predictors among Chinese teachers: A mixed-methods approach using latent profile and decision tree analysis

Abstract

Understanding the varied profiles of occupational well-being, their outcomes, and predictors is key to formulating effective strategies for enhancing teachers' occupational health and well-being. This study employed latent profile analysis (LPA) to identify distinct occupational well-being profiles and their outcomes among 366 Chinese teachers, and decision tree analysis to explore the factors predicting each profile. The results showed three occupational well-being profiles: burnout, engaged, and burnout-engaged. The “engaged” group exhibited normal ranges for depression and stress, along with mild anxiety. The “burnout” group demonstrated moderate depression and stress, coupled with severe anxiety. The “burnout-engaged” group was near the threshold of mild depression and moderate anxiety. The result of the decision tree model revealed that marital status, teaching experience, income, role as a class teacher, school type, and working hours significantly influenced these occupational well-being profiles. Specific combinations of variables were associated with each occupational well-being profile, offering a nuanced understanding of the risky and protective factors for teacher occupational well-being. By identifying distinct occupational well-being profiles among Chinese teachers and their outcomes, and elucidating the key predictors and their interrelations, this study provides insights into how to quickly screen for teachers in need of help at work, and how to design targeted interventions for different teachers.