Quantifying Novice and Expert Differences in Visual Diagnostic Reasoning in Veterinary Pathology Using Eye-Tracking Technology

Author:

Warren Amy L.1,Donnon Tyrone L.2,Wagg Catherine R.3,Priest Heather4,Fernandez Nicole J.3

Affiliation:

1. Associate Professor in the Department of Ecosystem and Public Health, Faculty of Veterinary Medicine, University of Calgary, 3330 Hospital Dr. NW, Calgary, AB T2N 4N1 Canada.

2. Adjunct Associate Professor in the Department of Community Health Sciences, Faculty of Medicine, University of Calgary and the Vice-President, Testing and Measurement, for Assessment Strategies Inc., 1400 Blair Place, Suite 210, Ottawa, ON K1J 9B8 Canada

3. Senior Instructor in the Department of Veterinary Clinical and Diagnostic Sciences, Faculty of Veterinary Medicine, University of Calgary, 3330 Hospital Dr. NW, Calgary, AB T2N 4N1 Canada

4. Clinical Assistant Professor in the Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853-6401 USA

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.

Publisher

University of Toronto Press Inc. (UTPress)

Subject

General Veterinary,Education,General Medicine

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