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Liu CH, Chang CW, Hung J, Lin JJH, Sung PS, Lee LA, Hsiao CT, Chao YP, Huang ES, Wang SL. Brain computed tomography reading of stroke patients by resident doctors from different medical specialities: An eye-tracking study. J Clin Neurosci 2023; 117:173-180. [PMID: 37837935 DOI: 10.1016/j.jocn.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 10/05/2023] [Accepted: 10/06/2023] [Indexed: 10/16/2023]
Abstract
BACKGROUND Using the eye-tracking technique, our work aimed to examine whether difference in clinical background may affect the training outcome of resident doctors' interpretation skills and reading behaviour related to brain computed tomography (CT). METHODS Twelve resident doctors in the neurology, radiology, and emergency departments were recruited. Each participant had to read CT images of the brain for two cases. We evaluated each participant's accuracy of lesion identification. We also used the eye-tracking technique to assess reading behaviour. We recorded dwell times, fixation counts, run counts, and first-run dwell times of target lesions to evaluate visual attention. Transition entropy was applied to assess the temporal relations and spatial dynamics of systematic image reading. RESULTS The eye-tracking results showed that the image reading sequence examined by transition entropy was comparable among resident doctors from different medical specialties (p = 0.82). However, the dwell time of the target lesions was shorter for the resident doctors from the neurology department (4828.63 ms, p = 0.01) than for those from the resident doctors from the radiology (6275.88 ms) and emergency (5305.00 ms) departments. The eye-tracking results in individual areas of interest only showed differences in the eye-tracking performance of the first-run dwell time (p = 0.05) in the anterior cerebral falx. DISCUSSION Our findings demonstrate that resident doctors from different medical specialties may achieve similar imaging reading patterns for brain CT. This may mitigate queries regarding the influence of different backgrounds on training outcomes.
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Affiliation(s)
- Chi-Hung Liu
- Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan; School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Division of Medical Education, Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chun-Wei Chang
- Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan; School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - June Hung
- Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan; School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - John J H Lin
- Graduate Institute of Science Education, National Taiwan Normal University, Taipei City, Taiwan.
| | - Pi-Shan Sung
- Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Li-Ang Lee
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Otorhinolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou Main Branch, Taoyuan, Taiwan; Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Cheng-Ting Hsiao
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Emergency Medicine, Chang Gung Memorial Hospital, Chiayi, Taiwan; Chang Gung Medical Education Research Centre, Taoyuan, Taiwan
| | - Yi-Ping Chao
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan; Department of Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Elaine Shinwei Huang
- Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan
| | - Shu-Ling Wang
- Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan
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Emhardt SN, Kok E, van Gog T, Brandt-Gruwel S, van Marlen T, Jarodzka H. Visualizing a Task Performer’s Gaze to Foster Observers’ Performance and Learning—a Systematic Literature Review on Eye Movement Modeling Examples. EDUCATIONAL PSYCHOLOGY REVIEW 2023. [DOI: 10.1007/s10648-023-09731-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Abstract
Eye movement modeling examples (EMMEs) are instructional videos (e.g., tutorials) that visualize another person’s gaze location while they demonstrate how to perform a task. This systematic literature review provides a detailed overview of studies on the effects of EMME to foster observers’ performance and learning and highlights their differences in EMME designs. Through a broad, systematic search on four relevant databases, we identified 72 EMME studies (78 experiments). First, we created an overview of the different study backgrounds. Studies most often taught tasks from the domains of sports/physical education, medicine, aviation, and STEM areas and had different rationales for displaying EMME. Next, we outlined how studies differed in terms of participant characteristics, task types, and the design of the EMME materials, which makes it hard to infer how these differences affect performance and learning. Third, we concluded that the vast majority of the experiments showed at least some positive effects of EMME during learning, on tests directly after learning, and tests after a delay. Finally, our results provide a first indication of which EMME characteristics may positively influence learning. Future research should start to more systematically examine the effects of specific EMME design choices for specific participant populations and task types.
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Holmqvist K, Örbom SL, Hooge ITC, Niehorster DC, Alexander RG, Andersson R, Benjamins JS, Blignaut P, Brouwer AM, Chuang LL, Dalrymple KA, Drieghe D, Dunn MJ, Ettinger U, Fiedler S, Foulsham T, van der Geest JN, Hansen DW, Hutton SB, Kasneci E, Kingstone A, Knox PC, Kok EM, Lee H, Lee JY, Leppänen JM, Macknik S, Majaranta P, Martinez-Conde S, Nuthmann A, Nyström M, Orquin JL, Otero-Millan J, Park SY, Popelka S, Proudlock F, Renkewitz F, Roorda A, Schulte-Mecklenbeck M, Sharif B, Shic F, Shovman M, Thomas MG, Venrooij W, Zemblys R, Hessels RS. Eye tracking: empirical foundations for a minimal reporting guideline. Behav Res Methods 2023; 55:364-416. [PMID: 35384605 PMCID: PMC9535040 DOI: 10.3758/s13428-021-01762-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/29/2021] [Indexed: 11/08/2022]
Abstract
In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section "An empirically based minimal reporting guideline").
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Affiliation(s)
- Kenneth Holmqvist
- Department of Psychology, Nicolaus Copernicus University, Torun, Poland.
- Department of Computer Science and Informatics, University of the Free State, Bloemfontein, South Africa.
- Department of Psychology, Regensburg University, Regensburg, Germany.
| | - Saga Lee Örbom
- Department of Psychology, Regensburg University, Regensburg, Germany
| | - Ignace T C Hooge
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
| | - Diederick C Niehorster
- Lund University Humanities Lab and Department of Psychology, Lund University, Lund, Sweden
| | - Robert G Alexander
- Department of Ophthalmology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | | | - Jeroen S Benjamins
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
- Social, Health and Organizational Psychology, Utrecht University, Utrecht, The Netherlands
| | - Pieter Blignaut
- Department of Computer Science and Informatics, University of the Free State, Bloemfontein, South Africa
| | | | - Lewis L Chuang
- Department of Ergonomics, Leibniz Institute for Working Environments and Human Factors, Dortmund, Germany
- Institute of Informatics, LMU Munich, Munich, Germany
| | | | - Denis Drieghe
- School of Psychology, University of Southampton, Southampton, UK
| | - Matt J Dunn
- School of Optometry and Vision Sciences, Cardiff University, Cardiff, UK
| | | | - Susann Fiedler
- Vienna University of Economics and Business, Vienna, Austria
| | - Tom Foulsham
- Department of Psychology, University of Essex, Essex, UK
| | | | - Dan Witzner Hansen
- Machine Learning Group, Department of Computer Science, IT University of Copenhagen, Copenhagen, Denmark
| | | | - Enkelejda Kasneci
- Human-Computer Interaction, University of Tübingen, Tübingen, Germany
| | | | - Paul C Knox
- Department of Eye and Vision Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Ellen M Kok
- Department of Education and Pedagogy, Division Education, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, The Netherlands
- Department of Online Learning and Instruction, Faculty of Educational Sciences, Open University of the Netherlands, Heerlen, The Netherlands
| | - Helena Lee
- University of Southampton, Southampton, UK
| | - Joy Yeonjoo Lee
- School of Health Professions Education, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Jukka M Leppänen
- Department of Psychology and Speed-Language Pathology, University of Turku, Turku, Finland
| | - Stephen Macknik
- Department of Ophthalmology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Päivi Majaranta
- TAUCHI Research Center, Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Susana Martinez-Conde
- Department of Ophthalmology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Antje Nuthmann
- Institute of Psychology, University of Kiel, Kiel, Germany
| | - Marcus Nyström
- Lund University Humanities Lab, Lund University, Lund, Sweden
| | - Jacob L Orquin
- Department of Management, Aarhus University, Aarhus, Denmark
- Center for Research in Marketing and Consumer Psychology, Reykjavik University, Reykjavik, Iceland
| | - Jorge Otero-Millan
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, CA, USA
| | - Soon Young Park
- Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, Vienna, Austria
| | - Stanislav Popelka
- Department of Geoinformatics, Palacký University Olomouc, Olomouc, Czech Republic
| | - Frank Proudlock
- The University of Leicester Ulverscroft Eye Unit, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - Frank Renkewitz
- Department of Psychology, University of Erfurt, Erfurt, Germany
| | - Austin Roorda
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, CA, USA
| | | | - Bonita Sharif
- School of Computing, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Frederick Shic
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, USA
- Department of General Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
| | - Mark Shovman
- Eyeviation Systems, Herzliya, Israel
- Department of Industrial Design, Bezalel Academy of Arts and Design, Jerusalem, Israel
| | - Mervyn G Thomas
- The University of Leicester Ulverscroft Eye Unit, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - Ward Venrooij
- Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, The Netherlands
| | | | - Roy S Hessels
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
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Nespolo RG, Cole E, Wang D, Yi D, Leiderman YI. A Platform for Tracking Surgeon and Observer Gaze as a Surrogate for Attention in Ophthalmic Surgery. OPHTHALMOLOGY SCIENCE 2022; 3:100246. [PMID: 36748062 PMCID: PMC9898791 DOI: 10.1016/j.xops.2022.100246] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/25/2022] [Indexed: 11/10/2022]
Abstract
Purpose To develop and validate a platform that can extract eye gaze metrics from surgeons observing cataract and vitreoretinal procedures and to enable post hoc data analysis to assess potential discrepancies in eye movement behavior according to surgeon experience. Design Experimental, prospective, single-center study. Participants Eleven ophthalmic surgeons observing deidentified vitreoretinal and cataract surgical procedures performed at a single university-based medical center. Methods An open-source platform was developed to extract gaze coordinates and metrics from ophthalmic surgeons via a computer vision algorithm in conjunction with a neural network to track and segment instruments and tissues, identifying areas of attention in the visual field of study subjects. Eleven surgeons provided validation data by watching videos of 6 heterogeneous vitreoretinal and cataract surgical phases. Main Outcome Measures Accuracy and distance traveled by the eye gaze of participants and overlap of the participants' eye gaze with instruments and tissues while observing surgical procedures. Results The platform demonstrated repeatability of > 94% when acquiring the eye gaze behavior of subjects. Attending ophthalmic surgeons and clinical fellows exhibited a lower overall cartesian distance traveled in comparison to resident physicians in ophthalmology (P < 0.02). Ophthalmology residents and clinical fellows exhibited more fixations to the display area where surgical device parameters were superimposed than attending surgeons (P < 0.05). There was a trend toward gaze overlap with the instrument tooltip location among resident physicians in comparison to attending surgeons and fellows (41.42% vs. 34.8%, P > 0.2). The number and duration of fixations did not vary substantially among groups (P > 0.3). Conclusions The platform proved effective in extracting gaze metrics of ophthalmic surgeons. These preliminary data suggest that surgeon gaze behavior differs according to experience.
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Affiliation(s)
- Rogerio G. Nespolo
- Department of Ophthalmology and Visual Sciences - Illinois Eye and Ear Infirmary, University of Illinois Chicago, Chicago, Illinois,Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois
| | - Emily Cole
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois
| | - Daniel Wang
- Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois
| | - Darvin Yi
- Department of Ophthalmology and Visual Sciences - Illinois Eye and Ear Infirmary, University of Illinois Chicago, Chicago, Illinois,Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois
| | - Yannek I. Leiderman
- Department of Ophthalmology and Visual Sciences - Illinois Eye and Ear Infirmary, University of Illinois Chicago, Chicago, Illinois,Richard and Loan Hill Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois,Correspondence: Yannek I. Leiderman, MD, PhD, University of Illinois, 1905 W. Taylor St, Chicago, IL 60612.
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Liu CH, Hung J, Chang CW, Lin JJH, Huang ES, Wang SL, Lee LA, Hsiao CT, Sung PS, Chao YP, Chang YJ. Oral presentation assessment and image reading behaviour on brain computed tomography reading in novice clinical learners: an eye-tracking study. BMC MEDICAL EDUCATION 2022; 22:738. [PMID: 36284299 PMCID: PMC9597969 DOI: 10.1186/s12909-022-03795-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 10/06/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND To study whether oral presentation (OP) assessment could reflect the novice learners' interpretation skills and reading behaviour on brain computed tomography (CT) reading. METHODS Eighty fifth-year medical students were recruited, received a 2-hour interactive workshop on how to read brain CT, and were assigned to read two brain CT images before and after instruction. We evaluated their image reading behaviour in terms of overall OP post-test rating, the lesion identification, and competency in systematic image reading after instruction. Students' reading behaviour in searching for the target lesions were recorded by the eye-tracking technique and were used to validate the accuracy of lesion reports. Statistical analyses, including lag sequential analysis (LSA), linear mixed models, and transition entropy (TE) were conducted to reveal temporal relations and spatial complexity of systematic image reading from the eye movement perspective. RESULTS The overall OP ratings [pre-test vs. post-test: 0 vs. 1 in case 1, 0 vs. 1 in case 2, p < 0.001] improved after instruction. Both the scores of systematic OP ratings [0 vs.1 in both cases, p < 0.001] and eye-tracking studies (Case 1: 3.42 ± 0.62 and 3.67 ± 0.37 in TE, p = 0.001; Case 2: 3.42 ± 0.76 and 3.75 ± 0.37 in TE, p = 0.002) showed that the image reading behaviour changed before and after instruction. The results of linear mixed models suggested a significant interaction between instruction and area of interests for case 1 (p < 0.001) and case 2 (p = 0.004). Visual attention to the target lesions in the case 1 assessed by dwell time were 506.50 ± 509.06 and 374.38 ± 464.68 milliseconds before and after instruction (p = 0.02). However, the dwell times in the case 2, the fixation counts and the frequencies of accurate lesion diagnoses in both cases did not change after instruction. CONCLUSION Our results showed OP performance may change concurrently with the medical students' reading behaviour on brain CT after a structured instruction.
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Affiliation(s)
- Chi-Hung Liu
- Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Division of Medical Education, Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - June Hung
- Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Chun-Wei Chang
- Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - John J H Lin
- Graduate Institute of Science Education, National Taiwan Normal University, No. 88, Ting-Jou Rd., Sec. 4, Taipei City, Taiwan.
| | - Elaine Shinwei Huang
- Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Shu-Ling Wang
- Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Li-Ang Lee
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Otorhinolaryngology-Head and Neck Surgery, Linkou Main Branch, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Cheng-Ting Hsiao
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Emergency Medicine, Chang Gung Memorial Hospital, Chiayi, Taiwan
- Chang Gung Medical Education Research Centre, Taoyuan, Taiwan
| | - Pi-Shan Sung
- Department of Neurology, College of Medicine, National Cheng Kung University Hospital, National Cheng Kung University, Tainan, Taiwan
| | - Yi-Ping Chao
- Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan
- Department of Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Yeu-Jhy Chang
- Department of Neurology, Linkou Medical Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Division of Medical Education, Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Chang Gung Medical Education Research Centre, Taoyuan, Taiwan
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Emhardt SN, Jarodzka H, Brand-Gruwel S, Drumm C, Niehorster DC, van Gog T. What is my teacher talking about? Effects of displaying the teacher’s gaze and mouse cursor cues in video lectures on students’ learning. JOURNAL OF COGNITIVE PSYCHOLOGY 2022. [DOI: 10.1080/20445911.2022.2080831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- Selina N. Emhardt
- Department of Educational Sciences, Open Universiteit Nederland (Open University of the Netherlands), Heerlen, the Netherlands
| | - Halszka Jarodzka
- Department of Educational Sciences, Open Universiteit Nederland (Open University of the Netherlands), Heerlen, the Netherlands
| | - Saskia Brand-Gruwel
- Department of Educational Sciences, Open Universiteit Nederland (Open University of the Netherlands), Heerlen, the Netherlands
- Zuyd Hogeschool, University of Applied Sciences, Heerlen, the Netherlands
| | - Christian Drumm
- Faculty of Business Studies, FH Aachen University of Applied Sciences, Aachen, Germany
| | - Diederick C. Niehorster
- Lund University Humanities Lab, Lund University, Lund, Sweden
- Department of Psychology, Lund University, Lund, Sweden
| | - Tamara van Gog
- Department of Education, Utrecht University, Utrecht, the Netherlands
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Comparing the Visual Perception According to the Performance Using the Eye-Tracking Technology in High-Fidelity Simulation Settings. Behav Sci (Basel) 2021; 11:bs11030031. [PMID: 33807673 PMCID: PMC7998119 DOI: 10.3390/bs11030031] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/26/2021] [Accepted: 03/01/2021] [Indexed: 12/22/2022] Open
Abstract
Introduction: We used eye-tracking technology to explore the visual perception of clinicians during a high-fidelity simulation scenario. We hypothesized that physicians who were able to successfully manage a critical situation would have a different visual focus compared to those who failed. Methods: A convenience sample of 18 first-year emergency medicine residents were enrolled voluntarily to participate in a high-fidelity scenario involving a patient in shock with a 3rd degree atrioventricular block. Their performance was rated as pass or fail and depended on the proper use of the pacing unit. Participants were wearing pre-calibrated eye-tracking glasses throughout the 9-min scenario and infrared (IR) markers installed in the simulator were used to define various Areas of Interest (AOI). Total View Duration (TVD) and Time to First Fixation (TFF) by the participants were recorded for each AOI and the results were used to produce heat maps. Results: Twelve residents succeeded while six failed the scenario. The TVD for the AOI containing the pacing unit was significantly shorter (median [quartile]) for those who succeeded compared to the ones who failed (42 [31–52] sec vs. 70 [61–90] sec, p = 0.0097). The TFF for the AOI containing the ECG and vital signs monitor was also shorter for the participants who succeeded than for those who failed (22 [6–28] sec vs. 30 [27–77] sec, p = 0.0182). Discussion: There seemed to be a connection between the gaze pattern of residents in a high-fidelity bradycardia simulation and their performance. The participants who succeeded looked at the monitor earlier (diagnosis). They also spent less time fixating the pacing unit, using it promptly to address the bradycardia. This study suggests that eye-tracking technology could be used to explore how visual perception, a key information-gathering element, is tied to decision-making and clinical performance.
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