Teaching Skin Cancer Detection to Medical Students Using a Dermoscopic Algorithm
- PMID: 33860161
- PMCID: PMC8041216
- DOI: 10.22454/PRiMER.2021.304379
Teaching Skin Cancer Detection to Medical Students Using a Dermoscopic Algorithm
Abstract
Introduction: Early detection of melanoma skin cancer improves survival rates. Training family physicians in dermoscopy with the triage amalgamated dermoscopic algorithm (TADA) has high sensitivity and specificity for identifying malignant skin neoplasms. In this study we evaluated the effectiveness of TADA training among medical students, compared with practicing clinicians.
Methods: We incorporated the TADA framework into 90-minute workshops that taught dermoscopy to family physicians, primary care residents, and first- and second-year medical students. The workshop reviewed the clinical and dermoscopic features of benign and malignant skin lesions and included a hands-on interactive session using a dermatoscope. All participants took a 30-image pretest and a different 30-image posttest.
Results: Forty-six attending physicians, 25 residents, and 48 medical students participated in the workshop. Mean pretest scores were 20.1, 20.3, and 15.8 for attending physicians, resident physicians and students, respectively (P<.001); mean posttest scores were 24.5, 25.9, and 24.1, respectively (P=.11). Pre/posttest score differences were significant ( P<.001) for all groups. The medical students showed the most gain in their pretest and posttest scores.
Conclusion: After short dermoscopy workshop, medical students perform as well as trained physicians in identifying images of malignant skin lesions. Dermoscopy training may be a valuable addition to the medical school curriculum as this skill can be used by primary care physicians as well as multiple specialists including dermatologists, gynecologists, otolaryngologists, plastic surgeons, and ophthalmologists, who often encounter patients with concerning skin lesions.
© 2021 by the Society of Teachers of Family Medicine.
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