Development of undergraduate students' diagnostic accuracy for the classification of molar incisor hypomineralization.

Autor: Restrepo M; Basic and Clinical Research Group in Dentistry, School of Dentistry, CES University, Medellín, Colombia., Rojas-Gualdrón DF; School of Medicine, CES University, Medellín, Colombia., de Farias AL; School of Dentistry, CES University, Medellín, Colombia.; Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry, São Paulo State University (Unesp), Araraquara School of Dentistry, Araraquara, São Paulo, Brazil., Escobar A; Basic and Clinical Research Group in Dentistry, School of Dentistry, CES University, Medellín, Colombia., Vélez LF; Basic and Clinical Research Group in Dentistry, School of Dentistry, CES University, Medellín, Colombia., Bussaneli DG; Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry, São Paulo State University (Unesp), Araraquara School of Dentistry, Araraquara, São Paulo, Brazil., Santos-Pinto L; Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry, São Paulo State University (Unesp), Araraquara School of Dentistry, Araraquara, São Paulo, Brazil.
Jazyk: angličtina
Zdroj: European journal of dental education : official journal of the Association for Dental Education in Europe [Eur J Dent Educ] 2024 Feb; Vol. 28 (1), pp. 154-160. Date of Electronic Publication: 2023 Jun 28.
DOI: 10.1111/eje.12932
Abstrakt: Introduction: One of the major difficulties with respect to molar incisor hypomineralization (MIH) is its classification and differentiation from other enamel development defects (EDDs). The aim of this study was to evaluate diagnostic accuracy in dental students to classify MIH as well as its differentiation from other EDDs by combining conventional theoretical classes and e-learning-assisted pre-clinical practices.
Methods: In this one-group pre-test and post-test study, 59 second-year students assessed 115 validated photographs using the MIH Index on the Moodle learning platform. This index assesses the clinical features and extent of MIH, differentiating it from other EDDs. Students received automatic feedback after the pre-test. Two weeks later, students re-evaluated the same photographs. Both pairwise accuracy and overall diagnostic accuracy were estimated and compared for pre- and post-testing, with the area under the curve AUC, along with 95% confidence intervals (95% CI).
Results: The lowest diagnostic accuracy was for the ability to discriminate between white or cream-coloured demarcated opacities and hypomineralization-type defect that is not MIH. The overall pre-test accuracy was AUC = 0.83 and increased significantly post-test to AUC = 0.99 (p < .001). The overall accuracy to discriminate the extent of the lesion also increased significantly post-test (p < .001).
Conclusion: Diagnostic skills to classify MIH can be developed by combining conventional theoretical classes and e-learning-assisted pre-clinical practices.
(© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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