Peer-reviewed veterinary case report
Quantifying Novice and Expert Differences in Visual Diagnostic Reasoning in Veterinary Pathology Using Eye-Tracking Technology.
- Journal:
- Journal of veterinary medical education
- Year:
- 2018
- Authors:
- Warren, Amy L et al.
- Affiliation:
- Associate Professor in the Department of Ecosystem and Public Health · Canada
Plain-English summary
This study looked at how experienced and inexperienced veterinary pathologists make diagnoses by examining images of cell samples. The researchers used special eye-tracking technology to see where the pathologists looked while they tried to identify what was wrong. They found that the experts were much quicker and more accurate in their diagnoses compared to the novices, and they spent more time focusing on important areas of the images. The results suggest that experienced pathologists rely on quick pattern recognition while also using careful analysis to confirm their findings. Overall, the study highlights the differences in how novice and expert veterinarians approach visual diagnosis.
Abstract
Visual diagnostic reasoning is the cognitive process by which pathologists reach a diagnosis based on visual stimuli (cytologic, histopathologic, or gross imagery). Currently, there is little to no literature examining visual reasoning in veterinary pathology. The objective of the study was to use eye tracking to establish baseline quantitative and qualitative differences between the visual reasoning processes of novice and expert veterinary pathologists viewing cytology specimens. Novice and expert participants were each shown 10 cytology images and asked to formulate a diagnosis while wearing eye-tracking equipment (10 slides) and while concurrently verbalizing their thought processes using the think-aloud protocol (5 slides). Compared to novices, experts demonstrated significantly higher diagnostic accuracy (p <.017), shorter time to diagnosis (p <.017), and a higher percentage of time spent viewing areas of diagnostic interest (p <.017). Experts elicited more key diagnostic features in the think-aloud protocol and had more efficient patterns of eye movement. These findings suggest that experts' fast time to diagnosis, efficient eye-movement patterns, and preference for viewing areas of interest supports system 1 (pattern-recognition) reasoning and script-inductive knowledge structures with system 2 (analytic) reasoning to verify their diagnosis.
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Search related cases →Original publication: https://pubmed.ncbi.nlm.nih.gov/29345551/