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Differentiating Experience From Cue Utilization in Radiological Assessments

2020·18 Zitationen·Human Factors The Journal of the Human Factors and Ergonomics SocietyOpen Access
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18

Zitationen

6

Autoren

2020

Jahr

Abstract

Objective This research was designed to examine the contribution of self-reported experience and cue utilization to diagnostic accuracy in the context of radiology. Background Within radiology, it is unclear how task-related experience contributes to the acquisition of associations between features with events in memory, or cues, and how they contribute to diagnostic performance. Method Data were collected from 18 trainees and 41 radiologists. The participants completed a radiology edition of the established cue utilization assessment tool EXPERTise 2.0, which provides a measure of cue utilization based on performance on a number of domain-specific tasks. The participants also completed a separate image interpretation task as an independent measure of diagnostic performance. Results Consistent with previous research, a k-means cluster analysis using the data from EXPERTise 2.0 delineated two groups, the pattern of centroids of which reflected higher and lower cue utilization. Controlling for years of experience, participants with higher cue utilization were more accurate on the image interpretation task compared to participants who demonstrated relatively lower cue utilization ( p = .01). Conclusion This study provides support for the role of cue utilization in assessments of radiology images among qualified radiologists. Importantly, it also demonstrates that cue utilization and self-reported years of experience as a radiologist make independent contributions to performance on the radiological diagnostic task. Application Task-related experience, including training, needs to be structured to ensure that learners have the opportunity to acquire feature–event relationships and internalize these associations in the form of cues in memory.

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Radiology practices and educationClinical Reasoning and Diagnostic SkillsArtificial Intelligence in Healthcare and Education
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