Literature DB >> 20186570

Using signal detection theory to model changes in serial learning of radiological image interpretation.

Kathy Boutis1, Martin Pecaric, Brian Seeto, Martin Pusic.   

Abstract

Signal detection theory (SDT) parameters can describe a learner's ability to discriminate (d') normal from abnormal and the learner's criterion (λ) 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 (λ) 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.

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Year:  2010        PMID: 20186570     DOI: 10.1007/s10459-010-9225-8

Source DB:  PubMed          Journal:  Adv Health Sci Educ Theory Pract        ISSN: 1382-4996            Impact factor:   3.853


  7 in total

Review 1.  Stressing Signal Versus Noise: An Exercise in Clinical Reasoning.

Authors:  Neha Gupta; Kenneth Feingold; Gurpreet Dhaliwal
Journal:  J Gen Intern Med       Date:  2016-10-31       Impact factor: 5.128

2.  Building Emergency Medicine Trainee Competency in Pediatric Musculoskeletal Radiograph Interpretation: A Multicenter Prospective Cohort Study.

Authors:  Michelle Sin Lee; Martin Pusic; Benoit Carrière; Andrew Dixon; Jennifer Stimec; Kathy Boutis
Journal:  AEM Educ Train       Date:  2019-03-12

3.  Image interpretation: Learning analytics-informed education opportunities.

Authors:  Elana Thau; Manuela Perez; Martin V Pusic; Martin Pecaric; David Rizzuti; Kathy Boutis
Journal:  AEM Educ Train       Date:  2021-04-01

4.  Interpretation difficulty of normal versus abnormal radiographs using a pediatric example.

Authors:  Kathy Boutis; Stefan Cano; Martin Pecaric; T Bram Welch-Horan; Brooke Lampl; Carrie Ruzal-Shapiro; Martin Pusic
Journal:  Can Med Educ J       Date:  2016-03-31

5.  Advanced Pediatric Emergency Airway Management: A Multimodality Curriculum Addressing a Rare but Critical Procedure.

Authors:  Michael P Goldman; Ambika Bhatnagar; Joshua Nagler; Marc A Auerbach
Journal:  MedEdPORTAL       Date:  2020-09-04

6.  Pilot Evaluation of an Online Resource for Learning Paediatric Chest Radiograph Interpretation.

Authors:  Karthik Rajendran; Ben Walters; Bridget Kemball; Robert K McKinley; Nadir Khan; Colin A Melville
Journal:  Cureus       Date:  2021-01-18

7.  Early Visual Processing and Perception Processes in Object Discrimination Learning.

Authors:  Matías Quiñones; David Gómez; Rodrigo Montefusco-Siegmund; María de la Luz Aylwin
Journal:  Front Neurosci       Date:  2021-01-28       Impact factor: 4.677

  7 in total

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