Fatigue Among ICU Nurses and Its Influencing Factors: A Cross‐Sectional Study

BACKGROUND: Nurse fatigue has become an escalating global concern due to chronic nursing shortages, especially among ICU nurses. Scientific and effective assessment of fatigue is beneficial for strengthening nurse occupational health management and reducing the turnover rate. Yet previous studies mainly relied on subjective self-reports, with limited integration of objective physiological measures in the nursing population. AIM: To investigate the fatigue status of ICU nurses and analyse related influencing factors, so as to provide a reference for formulating targeted intervention measures. STUDY DESIGN: From March 2025 to June 2025, a convenience sample was recruited from 9 intensive care units across two teaching hospitals in Beijing, China. Participation in the study was entirely voluntary, and only those who completed both the questionnaire and monitoring procedures were included. Data collected included demographic characteristics, fatigue levels, sleep-wake index, heart rate variability and salivary cortisol levels. RESULTS: In total, 140 nurses participated in the study. The average fatigue severity score among intensive care unit nurses exceeded the established clinical cut-off, and 92.9% of participants reported clinically significant fatigue. Among nurses working 8-h shifts, factors associated with fatigue included heart rate, low-frequency heart rate variability, total sleep time, circadian activity rhythm and cortisol levels after the shift. For nurses on 12-h shifts, predictors included the balance of sympathetic and parasympathetic nervous activity, total sleep time, circadian activity rhythm, cortisol levels before the shift and years of experience in the intensive care unit. CONCLUSIONS: Fatigue among nurses in intensive care units is high and is associated with disrupted sleep, reduced self-regulation ability and occupational stress. Interventions should be tailored according to shift type to effectively reduce fatigue. RELEVANCE TO CLINICAL PRACTICE: Recognising fatigue predictors enables the development of targeted interventions to mitigate fatigue, optimise work schedules and improve quality of care.