Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands.
Department of Education, Utrecht University, Utrecht, the Netherlands.
Med Educ. 2019 Feb;53(2):153-164. doi: 10.1111/medu.13756. Epub 2018 Nov 25.
Medical image perception training generally focuses on abnormalities, whereas normal images are more prevalent in medical practice. Furthermore, instructional sequences that let students practice prior to expert instruction (inductive) may lead to improved performance compared with methods that give students expert instruction before practice (deductive). This study investigates the effects of the proportion of normal images and practice-instruction order on learning to interpret medical images. It is hypothesised that manipulation of the proportion of normal images will lead to a sensitivity-specificity trade-off and that students in practice-first (inductive) conditons need more time per practice case but will correctly identify more test cases.
Third-year medical students (n = 103) learned radiograph interpretation by practising cases with, respectively, 30% or 70% normal radiographs prior to expert instruction (practice-first order) or after expert instruction (instruction-first order). After training, students performed a test (60% normal) and sensitivity (% of correctly identified abnormal radiographs), specificity (% of correctly identified normal radiographs), diagnostic performance (% of correct diagnoses) and case duration were measured.
The conditions with 30% of normal images scored higher on sensitivity but the conditions with 70% of normal images scored higher on specificity, indicating a sensitivity and specificity trade-off. Those who participated in inductive conditions took less time per practice case but more per test case. They had similar test sensitivity, but scored lower on test specificity.
The proportion of normal images impacted the sensitivity-specificity trade-off. This trade-off should be an important consideration for the alignment of training with future practice. Furthermore, the deductive conditions unexpectedly scored higher on specificity when participants took less time per case. An inductive approach did not lead to higher diagnostic performance, possibly because participants might already have relevant prior knowledge. Deductive approaches are therefore advised for the training of advanced learners.
医学影像感知训练通常侧重于异常情况，而在医学实践中，正常图像更为常见。此外，让学生在专家指导前进行练习的教学顺序（归纳法）可能比在练习前给学生提供专家指导的方法（演绎法）导致更好的表现。本研究调查了正常图像比例和练习指导顺序对医学图像解读学习的影响。假设对正常图像比例的操作将导致敏感性-特异性权衡，并且在实践第一（归纳）条件下的学生每个练习案例需要更多的时间，但将正确识别更多的测试案例。
三年级医学生（n=103）通过分别在专家指导前（实践第一顺序）或专家指导后（指导第一顺序）练习具有 30%或 70%正常射线照片的案例来学习射线照相解释。培训后，学生进行了测试（60%正常），并测量了敏感性（正确识别异常射线照片的百分比）、特异性（正确识别正常射线照片的百分比）、诊断性能（正确诊断的百分比）和案例持续时间。
正常图像比例为 30%的条件在敏感性上得分较高，但正常图像比例为 70%的条件在特异性上得分较高，表明存在敏感性和特异性权衡。那些参加归纳条件的人每个练习案例花费的时间较少，但每个测试案例花费的时间更多。他们的测试敏感性相似，但测试特异性得分较低。
正常图像的比例影响了敏感性-特异性权衡。这种权衡应该是培训与未来实践一致性的重要考虑因素。此外，当参与者每个案例花费的时间较少时，演绎条件出人意料地在特异性上得分更高。归纳方法并没有导致更高的诊断性能，可能是因为参与者可能已经有了相关的先验知识。因此，建议对高级学习者采用演绎方法进行培训。
