Structure equation modeling in oral health research: A review of applications and considerations.

Abstract

This review provides an overview of structure equation modeling (SEM) and its applications in dental research. SEM is a statistical technique that allows researchers to examine the relationships between variables and is useful for analyzing data from a wide range of research designs, including cross-sectional, longitudinal, and experimental studies. The process involves specifying a theoretical model, testing the model with data, and evaluating the model fit. It has been used in dental research to investigate a wide range of topics, including dental diseases, oral health-related quality of life, and dental anxiety. SEM is particularly useful in modeling the relationships between various risk factors and dental diseases and also has the potential to provide a deeper understanding of the multifactorial nature of dental diseases such as periodontitis, dental caries, and oral cancer. Moreover, the insights provided can aid in the development of effective strategies for the prevention and treatment of dental diseases. It is a powerful statistical tool that can be used by dental researchers to gain a better understanding of the intricate interplay of factors that underlie dental diseases and other oral health-related outcomes.