Literature DB >> 22324528

Prevalence of abnormal cases in an image bank affects the learning of radiograph interpretation.

Martin V Pusic1, John S Andrews, David O Kessler, David C Teng, Martin R Pecaric, Carrie Ruzal-Shapiro, Kathy Boutis.   

Abstract

OBJECTIVES: Using a large image bank, we systematically examined how the use of different ratios of abnormal to normal cases affects trainee learning.
METHODS: This was a prospective, double-blind, randomised, three-arm education trial conducted in six academic training programmes for emergency medicine and paediatric residents in post-licensure years 2-5. We developed a paediatric ankle trauma radiograph case bank. From this bank, we constructed three different 50-case training sets, which varied in their proportions of abnormal cases (30%, 50%, 70%). Levels of difficulty and diagnoses were similar across sets. We randomly assigned residents to complete one of the training sets. Users classified each case as normal or abnormal, specifying the locations of any abnormalities. They received immediate feedback. All participants completed the same 20-case post-test in which 40% of cases were abnormal. We determined participant sensitivity, specificity, likelihood ratio and signal detection parameters.
RESULTS: A total of 100 residents completed the study. The groups did not differ in accuracy on the post-test (p = 0.20). However, they showed considerable variation in their sensitivity-specificity trade-off. The group that received a training set with a high proportion of abnormal cases achieved the best sensitivity (0.69, standard deviation [SD] = 0.24), whereas the groups that received training sets with medium and low proportions of abnormal cases demonstrated sensitivities of 0.63 (SD = 0.21) and 0.51 (SD = 0.24), respectively (p < 0.01). Conversely, the group with a low proportion of abnormal cases demonstrated the best specificity (0.83, SD = 0.10) compared with the groups with medium (0.70, SD = 0.15) and high (0.66, SD = 0.17) proportions of abnormal cases (p < 0.001). The group with a low proportion of abnormal cases had the highest false negative rate and missed fractures one-third more often than the groups that trained on higher proportions of abnormal cases.
CONCLUSIONS: Manipulating the ratio of abnormal to normal cases in learning banks can have important educational implications. © Blackwell Publishing Ltd 2012.

Entities:  

Mesh:

Year:  2012        PMID: 22324528     DOI: 10.1111/j.1365-2923.2011.04165.x

Source DB:  PubMed          Journal:  Med Educ        ISSN: 0308-0110            Impact factor:   6.251


  8 in total

1.  Experiences with a self-test for Dutch breast screening radiologists: lessons learnt.

Authors:  J M H Timmers; A L M Verbeek; R M Pijnappel; M J M Broeders; G J den Heeten
Journal:  Eur Radiol       Date:  2013-09-22       Impact factor: 5.315

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.  The Variable Journey in Learning to Interpret Pediatric Point-of-care Ultrasound Images: A Multicenter Prospective Cohort Study.

Authors:  Charisse Kwan; Martin Pusic; Martin Pecaric; Kirstin Weerdenburg; Mark Tessaro; Kathy Boutis
Journal:  AEM Educ Train       Date:  2019-07-30

4.  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

5.  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

6.  What We Do and Do Not Know about Teaching Medical Image Interpretation.

Authors:  Ellen M Kok; Koos van Geel; Jeroen J G van Merriënboer; Simon G F Robben
Journal:  Front Psychol       Date:  2017-03-03

7.  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

8.  Do prevalence expectations affect patterns of visual search and decision-making in interpreting CT colonography endoluminal videos?

Authors:  Thomas R Fanshawe; Peter Phillips; Andrew Plumb; Emma Helbren; Steve Halligan; Stuart A Taylor; Alastair Gale; Susan Mallett
Journal:  Br J Radiol       Date:  2016-02-23       Impact factor: 3.039

  8 in total

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