Workforce

ICU nurses experience some of the highest levels of cognitive demand and occupational stress in healthcare, yet historically this burden has been measured almost exclusively through retrospective self-report instruments that are vulnerable to recall bias and cannot capture moment-to-moment fluctuations in workload during actual patient care. To address this gap, I collaborated with a human factors engineering team applying naturalistic, sensor-based methods for objectively quantifying nurses' physical and cognitive stress in real time. Using wearable accelerometers, heart rate variability monitors, electrodermal activity sensors, and eye-tracking technology deployed during live clinical shifts, this work demonstrates that physiologic stress indicators correlate meaningfully with self-reported workload and with specific task demands encountered across the ICU nursing shift (PMID 35511206). A subsequent study further established correlations between continuous physiologic signals and occupational stress, providing some of the first applied evidence that wearable sensor technology can feasibly and validly characterize real-time stress exposure among bedside ICU nurses (PMID 34478340). These advances are informing a broader research trajectory examining structural contributors to clinician workload, including a systematic review characterizing clinical interruptions in acute care work environments (PMID 35843150).