Introduction: While a universal aspect of medical education, there are few validated teaching methods for ECG interpretation. Eye tracking technology applied to study visual patterns during ECG interpretation suggest that top performers localize the critical leads for diagnosis more effectively. No study, however, has analyzed visual behavior occurring within critical leads. Research Question: How does visual behavior of medical students within critical leads correlate with accuracy of ECG interpretation? Aims: We aimed to characterize the visual behavior of medical students interpreting ECGs to help inform future educational methods. Methods: 36 fourth-year students from one medical school completed 9 cases while visual behavior was tracked via a Tobii Pro Nano eyetracker and analyzed with iMotions software. Cases included a vignette and 12-lead ECG followed by viewing up to three critical leads. We included five morphologic abnormalities (e.g. LBBB) and four arrhythmias (e.g. AVNRT). Accuracy was assessed via multiple choice questions after viewing the 12-lead ECG alone and again after viewing critical leads. Dwell time, the time spent focused on a given lead, and fixation count, the number of discrete focuses > 60 ms, were analyzed via Mann-Whitney U testing. Data: 36.1% of students correctly interpreted all ECGs with morphologic abnormalities compared to 16.7% for arrhythmias. Within critical leads, there was a significant difference in average dwell time (2.62 vs 5.21 seconds (s), p <0.001) and fixation count (9.59 vs 16.5, p<0.001) between morphologic versus arrhythmia ECGs. Higher performers had decreased average dwell time and fixation count in critical leads compared to inaccurate interpreters for morphologic (2.39 vs 3.39 s, p=0.003; 8.92 vs 11.9 fixations, p<0.01) and arrhythmia (4.32 vs 7.04 s, p<0.01; 13.4 vs 22.7 fixations, p<0.01), respectively. Conclusion: Our study demonstrates that learners spend less focused time interpreting morphologic as compared to arrhythmia ECGs. Further, dwell times and fixation counts were lower amongst higher performers. Measurement of discrete visual behavior may provide a novel way to assess students’ pattern recognition skills and interpretation competency while also enhancing ECG didactic methods.
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