The mental workload of nurses in intensive care units can be successfully assessed with the help of eye movement goggles.
In a study published recently in Human factors: Journal of the Society for Human Factors and Ergonomics, Nima Ahmadi, a professor in the Department of Industrial and Systems Engineering at Rensselaer Polytechnic Institute, and researchers at the Houston Methodist Center for Results Studies used eye tracking and physiological monitoring technologies to study cognitive load and visual search for stressors. Collected data -; ocular and physiological reactions -; of whole 12-hour nursing shifts were analyzed to assess cognitive loads between day and night shifts, as well as to compare the beginning with the middle and the end of the shift. In addition, the impact of stress on the visual demand of nurses was assessed.
His research found no significant difference in the cognitive levels of nurses who work during the day compared to those who work at night. However, Dr. Ahmadi found that the beginning of work shifts was more demanding than the middle and end of shifts in the intensive care unit, and stressed nurses had shortened fixation, which was accompanied by more sporadic gaze behavior.
This is the first naturalistic study to use eye-tracking technology to assess the behavior of critical care nurses. The analysis of this rich set of data can shed light on the main factors that contribute to high stress and demanding episodes of nurses and will pave the way for effective interventions to address the mental health of providers. We believe that this study will provide basic knowledge that could inform the design of real-time stress monitoring systems and burn mitigation. “
Dr. Nima Ahmadi, Lecturer, Department of Industrial and Systems Engineering, Rensselaer Polytechnic
Nurses working in intensive care units have a particularly high workload, which can lead to cognitive overload and medical errors. Continuous unobtrusive measurements of mental strain and stress are needed to support nurses and improve patient outcomes. Previous studies of nurses have measured cognitive / mental stress, namely through self-reporting tools or through the use of indicators such as patient-nurse ratios or patient acuity assessments; these methods fail to capture fluctuations in workload or stress and fail to address the overall gap in real-time monitoring.
Dr. Ahmadi’s study is the first naturalistic study to attempt to load and stress in the intensive care unit using ocular indicators and physiological responses, including pupil diameter, gaze entropy, fixation, and saccadic eye movements. “The results of this and subsequent studies will clarify the complexity of intensive care and their potential impact on patient safety and provide much-needed support for the mental health of providers,” said Dr. Ahmadi. The next steps in this study would be the use of machine learning tools to identify moments of stress and communicate them in real time to nursing managers to meet the complex care needs of critically ill patients.
The main researcher of this study was Farzan Sasangohar from the University of Texas A&M and a Methodist from Houston. The study received a grant from the Dyer Foundation. Dr. Ahmadi joined the paper “Quantifying the workload and stress of nurses in intensive care units using a naturalistic assessment of the provision of clinical care”, by Jing Yang and Denny Yu Ph.D. of Purdue University, Valerie Danesh of the University of Texas at Austin, Faisal Masood MD, FCCP, FCCM and Stephen Klan of Houston Methodist.
Rensselaer Polytechnic Institute
Reference in the magazine:
Ahmadi, N., et al. (2022) Quantification of workload and stress in nurses in intensive care units: preliminary assessment by continuous eye monitoring. Human Factors The Society’s Journal of Human Factors and Ergonomics. doi.org/10.1177/00187208221085335.