Cognitive workload, perceived environmental noise, and alarm fatigue among multidisciplinary intensive care unit staff: A pre-intervention cross-sectional study

BACKGROUND: Alarm burden and excessive environmental noise are persistent challenges in intensive care units (ICUs) and may adversely affect healthcare staff performance and well-being. Nurses, as continuous bedside caregivers, are particularly exposed to frequent alarms that may contribute to cognitive overload and alarm fatigue. Although alarm fatigue has been widely discussed, limited data exist regarding occupational and perceptual contributors across multidisciplinary ICU staff, particularly in Asian settings. This study examined factors associated with alarm fatigue among ICU healthcare staff prior to the implementation of a Quiet ICU intervention. METHODS: A cross-sectional survey was conducted among 110 ICU healthcare professionals (nurses, respiratory therapists, and physicians) in a tertiary ICU in Singapore. Structured survey instruments assessed alarm fatigue, cognitive workload (NASA-TLX), perceived environmental noise, and noise sensitivity. Descriptive statistics, correlation analyses, and multivariable linear regression were performed. RESULTS: Nurses tended to report higher alarm fatigue scores than respiratory therapists, although score distributions overlapped across professional groups. The Alarm Fatigue Index demonstrated strong internal consistency (Cronbach's α = 0.88). Cognitive workload was independently associated with alarm fatigue (β = 0.44, 95% CI 0.23-0.66). ICU experience and perceived environmental noise were also independently associated with alarm fatigue, whereas professional role contributed little additional explanatory value. CONCLUSION: Alarm fatigue among ICU healthcare staff was associated with higher cognitive workload and greater perceived environmental noise in this pre-intervention baseline study. These findings suggest potentially modifiable human factors relevant to Quiet ICU initiatives and support prospective evaluation of workload-sensitive alarm management approaches.