Knowledge and Attitudes About Advanced Maxillofacial Imaging in Dental Professionals

Introduction: Advanced maxillofacial imaging techniques, such as CBCT, CT, MRI, and hybrid modalities (PET/CT and SPECT/CT), have transformed diagnosis and treatment planning in dentistry. However, their increasing availability poses challenges related to the appropriate indication, interpretation, and application of radiation protection principles. Previous studies suggest variability in the level of knowledge and attitudes of dental professionals, which can impact the quality of care and patient safety. Objective: To evaluate and compare the level of knowledge and attitudes regarding advanced maxillofacial imaging techniques among general dentists, dentists with postgraduate training, undergraduate/master's students in dentistry, and maxillofacial surgeons. Methodology: A cross-sectional study will be conducted using a structured questionnaire administered to general dentists, specialists, and students. A non-probability convenience sampling method will be used, with an estimated sample size of 220 participants. Statistical analysis will be performed using SPSS (version 31.0.1.0), establishing a significance level of p \< 0.05. A descriptive analysis of the variables will be carried out, expressing qualitative variables as frequencies and percentages, and quantitative variables as mean and standard deviation or median and range, depending on their distribution, which will be assessed using normality tests. For bivariate analysis, ANOVA or Kruskal-Wallis tests will be used to compare the level of knowledge, attitudes, and confidence levels between groups, according to the data distribution, with post-hoc analysis in case of significant differences. Ordinal variables, such as the frequency of test requests, will be analyzed using chi-square tests. Associations between variables will also be explored using Spearman's rank correlation coefficient, Student's t-test, or Mann-Whitney U test, and chi-square tests, depending on the nature of the data. Expected concl