Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

AI in the NICU: Considerations for Nursing Practice and Advocacy in Quality Care Outcomes for Patients and Families.

Advances in neonatal care : official journal of the National Association of Neonatal Nurses·2026
Same author

Developing a Social Media Strategy to Amplify Scholarship and Practice.

Advances in neonatal care : official journal of the National Association of Neonatal Nurses·2025
Same author

An Examination of Acoustic Neuroprotection in the Neonate: A Systematic Review.

Advances in neonatal care : official journal of the National Association of Neonatal Nurses·2025
Same author

Workforce Assessment of Nurse Anesthetists to Mitigate Intent to Leave and Improve Labor Participation.

The Journal of nursing administration·2025
Same author

Exploring Safety Culture, Production Pressure, Occupational Burnout, and Patient Safety in Anesthesia.

AANA journal·2025
Same author

More Than Just a Pain in the Back: Pain Among American Nurses and Its Relationship to Modifiable Work Factors and Work Performance.

Nursing administration quarterly·2024
Same journal

The Effect of the Mobile Application on Treatment Adherence, Self-Management, and Quality of Life in Patients With Acute Myocardial Infarction.

Computers, informatics, nursing : CIN·2026
Same journal

Securing Safety and Quality in AI-generated Patient Education: A Nurse-led Methodological Framework Integrating Kolcaba's Comfort Theory.

Computers, informatics, nursing : CIN·2026
Same journal

Integrating Spatial Awareness into Nursing EHR Design: A Scoping Review of Usability and Cognitive Load.

Computers, informatics, nursing : CIN·2026
Same journal

Advancing Nurse-Led Self-Regulation in Multiple Sclerosis Management: Developing an Interactive Web-Based Program through Action Research: Multiple Sclerosis Management.

Computers, informatics, nursing : CIN·2026
Same journal

Letter to the Editor.

Computers, informatics, nursing : CIN·2026
Same journal

Development and Implementation of the Health Informatics Competency Assessment (HICA): A Pilot Study.

Computers, informatics, nursing : CIN·2026
See all related articles

Related Experiment Video

Updated: Oct 21, 2025

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing
07:48

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

713

Using Eye Tracking for Measuring Cognitive Workload During Clinical Simulations: Literature Review and Synthesis.

Bryan A Wilbanks1, Edwin Aroke, Katherine M Dudding

  • 1Author Affiliation: University of Alabama at Birmingham.

Computers, Informatics, Nursing : CIN
|September 8, 2021
PubMed
Summary
This summary is machine-generated.

Eye tracking offers a continuous method for assessing cognitive workload in healthcare providers during high-fidelity clinical simulations. This approach overcomes limitations of traditional psychometric tools, improving medical error analysis.

More Related Videos

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
11:12

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects

Published on: September 18, 2012

17.6K
Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis
07:00

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis

Published on: October 13, 2016

8.3K

Related Experiment Videos

Last Updated: Oct 21, 2025

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing
07:48

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

713
Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
11:12

Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects

Published on: September 18, 2012

17.6K
Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis
07:00

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis

Published on: October 13, 2016

8.3K

Area of Science:

  • Medical Simulation
  • Human Factors Engineering
  • Cognitive Psychology

Background:

  • High-fidelity clinical simulations are crucial for skill acquisition in healthcare.
  • Excessive cognitive workload is a significant factor contributing to medical errors.
  • Current cognitive workload assessment methods, like psychometric instruments, have limitations including single time-period assessment and response bias.

Purpose of the Study:

  • To review the application of eye-tracking technology for measuring healthcare provider cognitive workload.
  • To develop evidence-based guidelines for cognitive workload assessment in high-fidelity clinical simulations.
  • To synthesize best practices for integrating eye tracking into simulation design.

Main Methods:

  • Literature review of studies utilizing eye tracking to measure cognitive workload.
  • Analysis of task-evoked pupillary responses as a continuous cognitive workload indicator.
  • Examination of high-fidelity clinical simulation design considerations for eye-tracking integration.

Main Results:

  • Eye tracking provides a reliable and continuous measure of cognitive workload during specific tasks.
  • Task-evoked pupillary responses correlate with cognitive load, offering an objective assessment.
  • Integration of eye tracking requires careful consideration of simulation design and methodology.

Conclusions:

  • Eye tracking is a valuable tool for objective, continuous cognitive workload assessment in clinical simulations.
  • This technology can enhance understanding of factors contributing to medical errors.
  • Guidelines are needed for effective implementation and interpretation of eye-tracking data in simulation research.