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Published on: July 4, 2018
Fatigue Among ICU Nurses and Its Influencing Factors: A Cross-Sectional Study
Yichen He1, Yirui Wang1, Jiayan Gou2
1School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Intensive care unit (ICU) nurses experience high fatigue, linked to sleep issues and stress. Tailoring interventions by shift type is crucial for managing nurse fatigue and improving care.
Area of Science:
- Occupational Health
- Nursing Science
- Physiology
Background:
- Nurse fatigue is a growing global issue, particularly in intensive care units (ICUs), exacerbated by staffing shortages.
- Effective fatigue assessment is vital for occupational health management and reducing nurse turnover.
- Previous research often overlooked objective physiological measures, relying heavily on subjective self-reports.
Purpose of the Study:
- To assess fatigue levels in ICU nurses.
- To identify factors influencing fatigue among ICU nurses.
- To provide data for developing targeted interventions.
Main Methods:
- A study involving 140 ICU nurses across two Beijing hospitals from March to June 2025.
- Data collection included questionnaires and physiological monitoring (heart rate variability, salivary cortisol).
- Assessed demographic characteristics, fatigue, sleep-wake index, and physiological markers.
Main Results:
- 92.9% of ICU nurses reported clinically significant fatigue, with average scores exceeding cut-offs.
- For 8-h shifts, fatigue predictors included heart rate, low-frequency heart rate variability, sleep time, circadian rhythm, and post-shift cortisol.
- For 12-h shifts, predictors included nervous system balance, sleep time, circadian rhythm, pre-shift cortisol, and experience.
Conclusions:
- High fatigue levels in ICU nurses correlate with sleep disruption, impaired self-regulation, and occupational stress.
- Interventions must be customized based on shift patterns to effectively combat nurse fatigue.
- Identifying fatigue predictors supports developing targeted strategies to optimize work schedules and enhance patient care quality.
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