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

Author:

Restrepo Manuel1ORCID,Rojas‐Gualdrón Diego Fernando2,de Farias Aline Leite34,Escobar Alfonso1,Vélez Luís Fernando1,Bussaneli Diego Girotto4,Santos‐Pinto Lourdes4

Affiliation:

1. Basic and Clinical Research Group in Dentistry, School of Dentistry CES University Medellín Colombia

2. School of Medicine CES University Medellín Colombia

3. School of Dentistry CES University Medellín Colombia

4. Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry, São Paulo State University (Unesp) Araraquara School of Dentistry Araraquara São Paulo Brazil

Abstract

AbstractIntroductionOne 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.MethodsIn 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).ResultsThe 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).ConclusionDiagnostic skills to classify MIH can be developed by combining conventional theoretical classes and e‐learning‐assisted pre‐clinical practices.

Publisher

Wiley

Subject

General Dentistry,Education

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