PURPOSE: To demonstrate how learning curves can describe proficiency improvements associated with deliberate practice of radiograph interpretation. METHOD: This was a prospective, cross-sectional study of pediatric residents in two tertiary care programs. A 234-item digital case bank of pediatric ankle radiographs was developed. The authors gave participants a brief clinical summary of each case and asked them to consider three radiograph views of the ankle. Participants classified each case as either normal or abnormal and, if applicable, specified the location of the abnormality. They received immediate feedback and a radiologist's dictated report. The authors reviewed longitudinal learning curves, which were generated based on calculated test characteristics (e.g., accuracy, sensitivity, specificity). RESULTS: Eighteen participants (56.3% of those eligible) completed all 234 cases. The form of the participants' learning curves was similar across all test characteristics. The curves showed a period of "noise" until the participants completed an average of 20 cases. The slope of the learning curve was maximal from 21 to 50 cases during which cumulative sensitivity (95% CI) increased from 0.50 (0.45, 0.57) to 0.54 (0.47, 0.58). Then, the curves reached an inflection point after which learning slowed but did not stop even after 234 cases. The final cumulative sensitivity was 0.60 (0.54, 0.63). Applying a reference criterion, the authors classified learners into formative categories. CONCLUSIONS: Learning curves describing deliberate practice of radiograph interpretation allow medical educators to define at which point(s) practice is most efficient and how much practice is required to achieve a defined level of mastery.
PURPOSE: To demonstrate how learning curves can describe proficiency improvements associated with deliberate practice of radiograph interpretation. METHOD: This was a prospective, cross-sectional study of pediatric residents in two tertiary care programs. A 234-item digital case bank of pediatric ankle radiographs was developed. The authors gave participants a brief clinical summary of each case and asked them to consider three radiograph views of the ankle. Participants classified each case as either normal or abnormal and, if applicable, specified the location of the abnormality. They received immediate feedback and a radiologist's dictated report. The authors reviewed longitudinal learning curves, which were generated based on calculated test characteristics (e.g., accuracy, sensitivity, specificity). RESULTS: Eighteen participants (56.3% of those eligible) completed all 234 cases. The form of the participants' learning curves was similar across all test characteristics. The curves showed a period of "noise" until the participants completed an average of 20 cases. The slope of the learning curve was maximal from 21 to 50 cases during which cumulative sensitivity (95% CI) increased from 0.50 (0.45, 0.57) to 0.54 (0.47, 0.58). Then, the curves reached an inflection point after which learning slowed but did not stop even after 234 cases. The final cumulative sensitivity was 0.60 (0.54, 0.63). Applying a reference criterion, the authors classified learners into formative categories. CONCLUSIONS: Learning curves describing deliberate practice of radiograph interpretation allow medical educators to define at which point(s) practice is most efficient and how much practice is required to achieve a defined level of mastery.
Authors: K F Kowalewski; C R Garrow; T Proctor; A A Preukschas; M Friedrich; P C Müller; H G Kenngott; L Fischer; B P Müller-Stich; F Nickel Journal: Surg Endosc Date: 2018-02-12 Impact factor: 4.584
Authors: Geb W Thomas; Salvador Rojas-Murillo; Jessica M Hanley; Clarence D Kreiter; Matthew D Karam; Donald D Anderson Journal: Iowa Orthop J Date: 2016