The article focuses on using a statistical method called Structural Equation Modeling to understand relationships among different factors. Specifically, they look at Confirmatory Factor Analysis (CFA) in the context of this modeling technique. The main aim is to check if the gathered data match the expected model of what the data is meant to represent. By applying CFA through software called AMOS, researchers can see how underlying (hidden) variables relate to the measurable ones. This process helps in determining if the data supports the theorized connections between these variables.