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ERIC Number: EJ907380
Record Type: Journal
Publication Date: 2010-Dec
Pages: 12
Abstractor: As Provided
Reference Count: 24
ISBN: N/A
ISSN: ISSN-1382-4996
Using Signal Detection Theory to Model Changes in Serial Learning of Radiological Image Interpretation
Boutis, Kathy; Pecaric, Martin; Seeto, Brian; Pusic, Martin
Advances in Health Sciences Education, v15 n5 p647-658 Dec 2010
Signal detection theory (SDT) parameters can describe a learner's ability to discriminate (d[prime symbol]) normal from abnormal and the learner's criterion ([lambda]) to under or overcall abnormalities. To examine the serial changes in SDT parameters with serial exposure to radiological cases. 46 participants were recruited for this study: 20 medical students (MED), 6 residents (RES), 12 fellows (FEL), 5 staff pediatric emergency physicians (PEM), and 3 staff radiologists (RAD). Each participant was presented with 234 randomly assigned ankle radiographs using a web-based application. Participants were given a clinical scenario and considered 3 views of the ankle. They classified each case as normal or abnormal. For abnormal cases, they specified the location of the abnormality. Immediate feedback included highlighting on the images and the official radiologist's report. The low experience group (MED, RES, FEL) showed steady improvement in discrimination ability with each case, while the high experience group (PEM, RAD) had higher and stable discrimination ability throughout the exercise. There was also a difference in the way the high and low experience groups balanced sensitivity and specificity ([lambda]) with the low experience group tending to make more errors calling positive radiographs negative. This tendency was progressively less evident with each increase in expertise level. SDT metrics provide valuable insight on changes associated with learning radiograph interpretation, and may be used to design more effective instructional strategies for a given learner group. (Contains 2 tables and 6 figures.)
Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A