Journal of nursing management · 2026
Patterns and Predictors of Self-Regulatory Fatigue Among Intensive Care Unit Nurses: A Person-Centered Latent Profile Analysis.
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Zhang Hongli, Wang Yilin, Hu Mengyi, Han Yanting, Zhou Jiao, Yang Qiaoying, Li Ka
Аннотация
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.
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.