A Novel Classification System of Smart Mechanical Plaque Control: A Cross-Sectional Survey with Cluster Analysis

Background: Recurring advances in the field of mechanical plaque control (MPC) devices have shown promise in improving the oral hygiene status of the community. However, little is known about the association between the knowledge of healthcare professionals regarding these advances, the manufacturers in understanding the demand of the community, and the community’s willingness to switch to these “smarter” advances in MPC. This article puts forth a novel classification system of smart MPC to bridge this research gap. Materials and Methods: After a Delphi consensus and a sample pretesting, a customized questionnaire survey based on the knowledge, attitude, and practice model was filled by 618 participants. The participants were divided into two groups: Group I from the healthcare profession (n = 236) and Group II from other professions (n = 382). A Chi-square test was used to determine the significant variables. These variables went through K-means and cluster silhouette scoring for cluster analysis. A correlation coefficient using regression line was used to analyze the relation between related variables. Results: The Chi-square test revealed nine components with statistically significant associations (P < 0.05). K-means clustering of the nine parameters revealed six clusters (silhouette score >0.5) that guided in drawing a classification of smart MPC. Conclusion: This study reveals the dearth of knowledge among the participants regarding advanced MPC and their negligence in following basic oral hygiene routines. The classification system derived through cluster analysis provides a basis for understanding the upgraded modes of MPC.