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Facilitating Adaptive Expertise in Learning Computed Tomography — FAIL CT  

Learning Clinical Trial

Official title:
The FAIL CT Study: Facilitating Adaptive Expertise in Learning Computed Tomography, a Multi-center Randomized Controlled Trial

Clinical Trial Summary

The main objective of this study is to demonstrate that Error Management Training improves adaptive expertise in head computed tomography interpretation. The investigators will conduct a randomized controlled trial comparing two learning strategies, Error Management Training vs Error Avoidance Training, in emergency medicine residents. The investigators hypothesize that Error Management Training, as compared to Error Avoidance Training, will improve adaptive expertise, as measured by skills transfer, when used to teach head computed tomography interpretation to emergency medicine residents.

Clinical Trial Description

Adaptive expertise is the ability to apply existing skills to novel situations. Adaptive expertise enables physicians to reduce preventable medical errors when managing clinical scenarios not encountered during training. However, residency curricula rarely address this learning outcome. Error Management Training improves transfer of skills to new contexts and develops adaptive expertise. Although this methodology has been shown to improve adaptive expertise in procedural skills, its impact on cognitive skills in medical training remains underexplored. Error Management Training promises to improve patient care by developing emergency physicians' adaptive expertise. However, the investigators need further evidence for its efficacy with cognitive skills in residency training. The investigators aim to demonstrate that Error Management Training improves adaptive expertise in a cognitive skill, using head computed tomography interpretation as a model. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05284838
Study type Interventional
Source Stanford University
Contact
Status Completed
Phase N/A
Start date July 18, 2022
Completion date September 30, 2023
View Details
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