Patterns and Predictors of Self‐Regulatory Fatigue Among Intensive Care Unit Nurses: A Person‐Centered Latent Profile Analysis

Abstract

Background Intensive care units (ICUs) play a critical role in the public health emergency response system. ICU nurses are the backbone of critical care and must continuously engage in self‐regulation while working in highly demanding environments, which may lead to self‐regulatory fatigue. Self‐regulatory fatigue may affect work engagement and patient safety. However, little is known about the profiles of self‐regulatory fatigue among ICU nurses and the factors associated with profile membership. Objective To identify profiles of self‐regulatory fatigue among ICU nurses and examine factors associated with profile membership. Methods A cross‐sectional survey was conducted between February and August 2025. A total of 687 ICU nurses completed an online questionnaire that collected general demographic information and assessed self‐regulatory fatigue, surface acting, and work engagement. Differences among latent profiles were examined using descriptive statistics, univariable analyses, and logistic regression analyses. Results Three latent profiles were identified: “Low self‐regulatory fatigue (Class 1),” “Moderate self‐regulatory fatigue (Class 2),” and “High self‐regulatory fatigue (Class 3),” accounting for 32.3%, 52.7%, and 15.0%, respectively. In multivariable logistic regression analyses, lower work engagement was independently associated with membership in the moderate self‐regulatory fatigue profile compared with the low self‐regulatory fatigue profile. However, work engagement was not independently associated with membership in the high self‐regulatory fatigue profile compared with the low self‐regulatory fatigue profile. Associations of demographic and work‐related factors with profile membership differed across the comparisons. Conclusion The level of self‐regulatory fatigue among ICU nurses showed a heterogeneous distribution, with over two‐thirds of the participants classified into the moderate or high self‐regulatory fatigue profiles. Identifying the sociodemographic and work‐related predictors associated with self‐regulatory fatigue profiles can facilitate the implementation of tailored interventions for specific subgroups and improve their effectiveness. Implications for Nursing Management The findings may help nursing managers understand the heterogeneous profiles of self‐regulatory fatigue among ICU nurses. Identifying different profiles of self‐regulatory fatigue may inform targeted strategies to alleviate such fatigue and promote continuous quality improvement.