Using eye-tracking augmented cognitive task analysis to explore healthcare professionals' cognition during neonatal resuscitation.

ABSTRACT

AIM: We aimed to describe the cognitive processes of healthcare providers participating as airway leads in delivery room neonatal resuscitations using eye-tracking assisted debriefing to facilitate recall and provide situational context. METHODS: Delivery room neonatal resuscitations were recorded using eye-tracking glasses worn by participants who acted as airway leads. These glasses analyze eye-movements to produce an audio-visual recording approximating what was "seen" by the participant and marking their visual attention. Participants then reviewed and debriefed their recordings. Debriefing involved a retrospective think-aloud prompted by eye-tracked recordings and an integrated semi-structured interview. Debriefing sessions were transcribed and subjected to thematic analysis. RESULTS: Eight healthcare providers participated in 10 interviews; two providers participated twice in two separate resuscitations. Most visual attention was directed at the infant (62%), with 16% directed to monitors/gauges, 3% to team members. Five major themes emerged including situation awareness, performance, working in teams, addressing threats to performance, and perception of eye-tracking. Information processing was complex and involved top-down and bottom-up processing of environmental stimuli, integration of knowledge/experience, and anticipation of patient response. Despite the focus on individual cognition, interpersonal interactions and teamwork emerged as key aspects of resuscitation performance. Potential threats to performance include equipment issues, mental stress, distractions, and parental presence. Eye-tracking recordings were well-received by the participants. CONCLUSION: Retrospective think-aloud prompted by point-of-view eye-tracked recordings is a useful means of examining cognition of healthcare providers during neonatal resuscitation. Themes identified in this project aligned with existing models of clinical reasoning.