Internet Based Measurement of Visual Expertise in Radiological Skill

THIRKETTLE, Martin, STAFFORD, Tom and OFFIAH, Amaka (2015). Internet Based Measurement of Visual Expertise in Radiological Skill. Perception, 44, 44-45.

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The correct identification and diagnosis of abnormalities from radiographs is one of the best examples of real-world expertise in visual tasks. Accordingly, understanding and measuring the development of this skill has attracted great interest from visual perception researchers and radiology instructors alike. However, significant challenges remain in collecting behavioural data from trainees and experts who are dispersed geographically and whose availability is limited. We therefore developed a web-based task to measure visual diagnostic skill. Participants viewed a selection of pre-assessed radiographs and were required to identify and localise skeletal abnormalities. 42 final year medical students at the University of Sheffield and 12 consultant paediatric radiologists from across Europe completed the two-stage task. As expected, consultants were significantly more accurate at identifying abnormalities than medical students, and their localisation of abnormalities was significantly more precise. However, in contrast to 44 Perception 44(S1) previous research, we found that the experts took longer over the task than novices. The results validate the use of a web-based platform for studies of visual cognition expertise in a real-world domain. Future work will add eye-tracking measures to the behavioural task, while the ease of data collection will allow both longitudinal and large-scale behavioural datasets to be collected. This work was supported by a grant from The Children’s Hospital Charity Research Fund

Item Type: Article
Additional Information: 38th European Conference on Visual Perception (ECVP) Liverpool 2015
Uncontrolled Keywords: 1701 Psychology; 1702 Cognitive Science; Experimental Psychology
Identification Number:
Page Range: 44-45
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 21 Jan 2019 10:28
Last Modified: 18 Mar 2021 06:50

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