ArticleFrontiers in psychology2023
Measuring teamwork for training in healthcare using eye tracking and pose estimation.
Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 14 citations in OpenAlex.
- Weakly Textured Objects Pose Estimation: A Comprehensive Review.Sensors (Basel, Switzerland) · 2026Review
- Physiological team dynamics explored: physiological synchrony in medical simulation training.Advances in simulation (London, England) · 2025Article
- Speech recognition technology for assessing team debriefing communication and interaction patterns: An algorithmic toolkit for healthcare simulation educators.Advances in simulation (London, England) · 2024Article
- How to enrich team research in healthcare by considering five theoretical perspectives.Frontiers in psychology · 2023Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Teamwork is critical for safe patient care. Healthcare teams typically train teamwork in simulated clinical situations, which require the ability to measure teamwork via behavior observation. However, the required observations are prone to human biases and include significant cognitive load even for trained instructors. In this observational study we explored how eye tracking and pose estimation as two minimal invasive video-based technologies may measure teamwork during simulation-based teamwork training in healthcare. Mobile eye tracking, measuring where participants look, and multi-person pose estimation, measuring 3D human body and joint position, were used to record 64 third-year medical students who completed a simulated handover case in teams of four. On one hand, we processed the recorded data into the eye contact metric, based on eye tracking and relevant for situational awareness and communication patterns. On the other hand, the distance to patient metric was processed, based on multi-person pose estimation and relevant for team positioning and coordination. After successful data recording, we successfully processed the raw videos to specific teamwork metrics. The average eye contact time was 6.46 s [min 0 s - max 28.01 s], while the average distance to the patient resulted in 1.01 m [min 0.32 m - max 1.6 m]. Both metrics varied significantly between teams and simulated roles of participants (
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