Research on burnout has traditionally emphasized symptoms, while the processes leading to burnout have received less attention. Burnout, in which proactive work attitudes paradoxically harm mental health, may arise through mechanisms different from those of other stress responses. This study therefore, focused on work commitment as a prerequisite for understanding burnout processes.
At Time 1 (T1, 2023), we conducted a web-based survey of nurses and care workers (N = 933). Participants completed a burnout scale and a Work Commitment Scale comprising five dimensions: engagement with clients, responsibility, communication, sense of mission, and self-improvement. Using a latent rank model, we derived ranks for commitment peak, decline, and mental symptoms. These ranks were subjected to cluster analysis, which identified five distinct groups: a Typical Burnout cluster (N = 160), a Work Engagement cluster (high and stable commitment with low symptoms; N = 66), an Adjustment cluster (moderate adjustment of commitment with reduced burden; N = 89), a Maladjustment cluster (low commitment but high symptoms; N = 132), and an Inert cluster (low commitment and low enthusiasm; N = 19).


At Time 2 (T2, 2024), a follow-up survey with 466 respondents included external indicators such as workplace evaluation, turnover intention, and depressive symptoms (PHQ-9). One-way ANOVAs showed that the Typical Burnout and Maladjustment clusters had significantly higher PHQ scores and turnover intention, whereas the Work Engagement and Adjustment clusters scored lowest. The Inert cluster fell in the middle on PHQ and turnover intention, but showed turnover rates comparable to the Burnout and Maladjustment clusters. These findings support the validity of the T1 classification and highlight the role of typical burnout trajectories.
In the conference presentation, we will introduce a web-based self-check application that enables individuals to assess their responses and identify their own cluster membership.