Abstract
OBJECTIVE: This study aimed to verify the predictive capacity of manual dexterity assessment methods for pre-clinical training in Dentistry. METHOD: Students from the fifth year of the undergraduate course in Dentistry (N = 95) participated in this study. Manual dexterity was investigated as a variable of interest, measured by the O'Connor Finger Dexterity Test methods-Model 32021, Purdue Pegboard Test-Model 32020A, Dental Manual Dexterity Assessment-DMDA, Class One Cavity Preparation Assessent-COCA and Class One Composite Resin Restoration Assessment-COCRA. The average score obtained in the evaluation of the quality of the cavity preparations and restorations was considered as gold standard, and from these data the sensitivity and specificity of the tests were estimated. Receiver Operating Characteristic (ROC) curves were constructed to assess the diagnostic performance of each dexterity test. The analysis included calculating the Area Under the Curve (AUROC) to evaluate their discriminative power, and cutoff points were determined that optimize the balance between sensitivity and specificity. RESULTS: The DMDA test showed better performance, with statistical significance (p <0.001) and acceptable predictive ability (AUROC = 0.775), while the O'Connor test (AUROC = 0.644, p = 0.050) and Purdue Pegboard test (Purdue 1: AUROC = 0.542, p = 0.560; Purdue 2: AUROC = 0.564, p = 0.423; Purdue 3: AUROC = 0.517, p = 0.828; Purdue 4: AUROC = 0.608, p = 0.083) were not statistically significant. CONCLUSION: The DMDA test presented the best performance, with statistical significance and acceptable discrimination, showing greater effectiveness for assessing students' manual dexterity. Therefore, the implementation of the DMDA test can significantly contribute to the early identification of motor dexterity difficulties in dental students, enabling more effective and targeted interventions.