Predicting Adoption of Cone Beam Computed Tomography among Pediatric Dentists
thesisposted on 01.11.2017, 00:00 by Saad Binsaleh
Purpose: To explain why some pediatric dentists adopt Cone Beam Computed Tomography (CBCT), using Rogers’s “Diffusion of Innovations Model.” Methods: A 20-item electronic questionnaire was distributed to 7,171 members of the American Academy of Pediatric Dentistry. Demographic questions yielded information about age, experience, dental/specialty education, board status, practice location, and practice type. The dependent variable was “adoption” versus “non-adoption” of CBCT. The independent variables were derived from Rogers’s model and include scaled questions in four domains: familiarity, availability, relative advantage, and compatibility of CBCT with pediatric dental practice. Binary logistic regression was used to predict adoption from demographics and model domains. Results: There were 533 responses (response rate 7%) following three rounds of distribution over nine weeks, 396 responses met inclusion criteria (74%); 137 responses were excluded due to additional specialty training or incomplete responses. Adopters were operationally defined as pediatric dentists who used CBCT at least once per year, and 24% of respondents were classified as adopters. Practice type was the only demographic variable associated with adoption of CBCT in preliminary analysis (p<.001). The outcome variable (adoption) was then regressed on the domain variables, and the final model showed familiarity (p<.001), availability (p<.001), and compatibility (p<.001) as predictive of CBCT use while relative advantage was not associated. The regression model explained 31% of the variance in outcome variable. Conclusions: Consistent with Rogers’ model, pediatric dentists who adopt CBCT are more familiar with and have access to it and view it as compatible with their practice.