gms | German Medical Science

Question/objective: The innovative potential of eyetracking and cued retrospective reporting (CRR) videos for teaching ECG interpretation skills to medical students was previously investigated in the EYE-ECG study-series [1], aiming to visualize expert diagnostic strategies and overcome reliance on rigid interpretation schemes. Student feedback revealed patterns, motivating the current EYE-ECG3 study to identify and characterize student clusters with common attitudes, abilities, and interests in ECG interpretation when training with CRR videos.

Methods: Nine medical students, with either low (n=3) or high (n=3) ECG interpretation skills and a prior cardiology clerkship (n=3), completed a QSORT task. This involved sorting 33 statement cards (i.e. 9x33=297 statements) on ECG learning, interpretation, and the use of eyetracking and expert commentary in ECG teaching, using a forced-choice sorting schema. It enabled identification of conceptually similar subgroups, representation of consensus sorting per group, and comparison of proband (dis-)similarities with background information.

Results: Principal Component Analysis found three people factors (PF) explaining 66% total variance (PF1-3: 37%; 16%; 13%). Briefly, PF1 characteristics were: Attended ECG module in presence/little practical ECG experience/moderate ECG interpretation skills/tended to study without audio-video/rated EYE-ECG videos as a novel experience. PF2: Attended ECG module online/had modest ECG interpretation skills/had some practical ECG experience/tended to study with audio-video/rated EYE-ECG videos as positive but somewhat outside their scope. PF3: Prior medical vocational training/great practical experience/moderate ECG interpretation skill/(overly) high confidence in own skill, and positive, undaunted view of EYE-ECG videos. Uniquely applicable QSORT leading statements for each factor will be detailed in the conference presentation. These people factors can meaningfully describe typical personas and their attitudes toward EYE-ECG videos, aiding further development of ECG teaching via CRR videos (see figure 1 [Fig. 1] and figure 2 [Fig. 2]).

Discussion: QSORT successfully identified three people factors, providing a more granular picture of the learners than the preconceived groups from recruitment. These findings may serve as a foundation for developing eyetracking ECG teaching components that are specifically tailored to the learners.

Take Home Messages: QSORT, an innovative qualitative-quantitative analysis, identified three prototypical student groups useful for further innovation of eyetracking ECG teaching.