TROY, NY – The mental workload of intensive care unit nurses can be successfully assessed using eye movement tracking goggles.

In research recently published in Human Factors: The Journal of the Human Factors and Ergonomics Society, Nima Ahmadi, associate professor in the Department of Industrial and Systems Engineering at Rensselaer Polytechnic Institute, and researchers from the Center for Outcomes Research at Houston Methodist have used eye tracking and physiological monitoring technologies to study the cognitive load and visual search of stressed nurses. Data collected – ocular and physiological responses – over entire 12-hour nursing shifts were analyzed to assess cognitive loads between day and night shifts as well as to compare the start with the middle and end of shifts. Additionally, the impact of stress on nurses’ visual search was assessed.

Her research detected no significant difference in the cognitive levels of nurses who worked day shifts compared to those who worked night shifts. However, Dr. Ahmadi found that early shifts are more cognitively demanding than mid and late shifts in intensive care, and that stressed nurses had a shortened fixation, which was accompanied by a more sporadic gaze behavior.

“This is the first naturalistic study that uses eye-tracking technology in the behavioral assessment of critical care nurses,” Dr. Ahmadi said. “Analysis of this rich data set can shed light on the major contributors to nurses’ high and demanding episodes of stress and will pave the way for effective interventions to address provider mental health.” We believe this research will provide foundational insights that could inform the design of real-time stress monitoring and burnout mitigation systems.

Nurses who work in intensive care units have particularly high workloads that could lead to cognitive overload and medical errors. To support nurses and improve patient outcomes, continuous, non-intrusive measures of mental workload and stress are needed. Previous nursing studies have measured cognitive/mental stress, including through self-reported instruments or using measures such as patient-nurse ratios or patient acuity scores; these methods fail to capture fluctuations in workload or stress and do not address the general lack of real-time monitoring.

Dr. Ahmadi’s study is the first naturalistic study that has attempted to investigate workload and stress in the intensive care unit using eye measurements and physiological responses, including pupil diameter, gaze entropy, fixational and saccadic eye movements. “The results of this study and follow-up studies will help elucidate the complexity of ICU care and its potential impact on patient safety, and provide much-needed mental health support for providers,” Dr. Ahmadi said. The next steps in this research would be to use machine learning tools to identify stressful moments and communicate them in real time to nurse leaders to address complex care delivery needs for critically ill patients.

The principal investigator for this research was Farzan Sasangohar of Texas A&M University and Houston Methodist. The study received a grant from the Dyer Foundation. Dr. Ahmadi was joined in the article “Quantifying Workload and Stress in Intensive Care Unit Nurses Using Naturalistic Evaluation of Clinical Care Delivery,” by Jing Yang and Denny Yu Ph.D. of Purdue University, Valerie Danesh of the University of Texas at Austin, Faisal Masud MD, FCCP, FCCM and Steven Klahn of Houston Methodist.


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