Work fatigue risk and associated factors among Chinese first-line registered nurses using latent profile analysis: a multicenter cross-sectional study

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AIM: To investigate subgroups of work fatigue risk in the Chinese first-line registered nurses and identify the associated factors associated with these profiles. BACKGROUND: Work fatigue is a prevalent issue among healthcare professionals, but few studies have employed person-centered approaches to investigate the specific patterns of work fatigue risk in a large sample of Chinese first-line registered nurses. METHODS: A convenient cluster sampling method was employed in six general hospitals in Hubei Province, China. Data related to the demographic characteristics, work-related characteristics, work fatigue risk, health promotion lifestyle, resilience and social support were collected. Latent profile analysis was utilized to categorize work fatigue risk subgroups among clinical nurses. Multiple logistic regression analyses were used to investigate associated factors with profile membership. RESULTS: A total of 1663 valid questionnaires were collected. Latent profile analysis suggested three profiles of work fatigue risk, which were labeled: low work fatigue risk (24.9%), moderate work fatigue risk (51.5%) and moderate high work fatigue risk (23.6%). The results of multiple logistic regression analyses indicated that age, gender, professional title, self-perceived health, number of time off <11 h between shifts per month, social support and resilience were the associated factors for the potential profiles. CONCLUSIONS: Our findings explore latent profiles of work fatigue risk among frontline registered nurses, identify subgroups susceptible to work fatigue. This research offers new insights into the heterogeneity of fatigue risks and the necessity for tailored interventions. IMPLICATIONS FOR NURSING MANAGEMENT: The study suggest that nurse managers should take responsibility to implement targeted interventions with the aim of reducing work fatigue among nurses. In addition, it is essential to identify distinct work fatigue groups and provide support to those who are most vulnerable.

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