Evaluating the Value of Eye-Tracking Augmented Debriefing in Medical Simulation—A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: Debriefing after simulation facilitates reflective thinking and learning. Eye-tracking augmented debriefing (ETAD) may provide advantages over traditional debriefing (TD) by leveraging video replay with first-person perspective. This multisite randomized controlled trial compared the impact of ETAD with TD (without eye-tracking and without video) after simulation on 4 outcomes: (1) resident metacognitive awareness (the primary outcome), (2) cognitive load (CL) of residents and debriefers, (3) alignment of resident self-assessment and debriefer assessment scores, and (4) resident and debriefer perceptions of the debriefing experience. METHOD: Fifty-four emergency medicine residents from 2 institutions were randomized to the experimental (ETAD) or the control (TD) arm. Residents completed 2 simulation stations followed by debriefing. Before station 1 and after station 2, residents completed a Metacognition Awareness Inventory (MAI). After each station, debriefers and residents rated their CL and completed an assessment of performance. After the stations, residents were interviewed and debriefers participated in a focus group. RESULTS: There were no statistically significant differences in mean MAI change, resident CL, or assessment alignment between residents and debriefers. Debriefer CL was lower in the experimental arm. Interviews identified 4 themes: (1) reflections related to debriefing approach, (2) eye-tracking as a metacognitive sensitizer, (3) translation of metacognition to practice, and (4) ETAD as a strategy to manage CL. Residents reported that eye tracking improved the specificity of feedback. Debriefers relied less on notes, leveraged video timestamps, appreciated the structure of the eye-tracking video, and found the video useful when debriefing poor performers. CONCLUSIONS: There were no significant quantitative differences in MAI or resident CL scores; qualitative findings suggest that residents appreciated the benefits of the eye-tracking video review. Debriefers expended less CL and reported less perceived mental effort with the new technology. Future research should leverage longitudinal experimental designs to further understand the impact of eye-tracking facilitated debriefing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".