Impact of the undergraduate clinical teaching-learning process on caries detection and treatment decision-making

Abstract

Aim: The aim of this study was to evaluate caries diagnosis and treatment decisions made by undergraduate dental students based on ICDAS or Nyvad criteria. Methods: Twelve students analyzed 90 digital photographs of permanent teeth at different clinical stages of carious lesion development and chose among different treatments in three different assessments: when there was no knowledge of the criteria (described as “No knowledge (N)”; when there was theoretical knowledge of the criteria (described as “Theoretical knowledge (T)” and when there was theoretical knowledge, clinical experience about dental caries and the criteria (described as “Theoretical and clinical knowledge (TC)”. For “T” and “TC” the students were randomized into two experimental groups – ICDAS or Nyvad (experimental units: 6 students/group). The reference standard was established cooperatively by two experienced researchers. Criteria performance was evaluated by sensitivity, specificity, AUC, and Kappa statistics. Treatment decision was described in percentage by contingency tables and Spearman’s correlation with the reference standard. Results: The first assessment demonstrated a high percentage of operative treatment even for initial enamel lesions based on ICDAS criteria and treatment was proposed for both active and inactive lesions, according to the Nyvad criteria. In the second assessment, the students continued recommending treatments for initial or inactive lesions, but less frequently. In the third assessment, treatment decisions presented greater cohesion in relation to the assigned classification criterion. The criteria presented no differences between them in terms of diagnostic in the third assessment. Conclusion: Clinical experience may improve caries detection and treatment decisions with the use of ICDAS and Nyvad criteria.

Data Analysis of Undergraduate Employment Based on Decision Classification Algorithm

“…According to the statistical results, the average time of the experimental group was 97 356 ms and 70 372 ms lower than that of the two control groups. It can be seen that the employment situation analysis system designed this time has better performance and solved the problem of slow operation efficiency of traditional analysis system [13][14][15].…”