Structural Equations for Testing Nested Models in Interdisciplinary Research

Abstract

Barriers to compare opposed or alternative scientific theories exist, based on diverse premises. One is the concept of incommensurability, the idea suggesting that different paradigms or theories cannot be contrasted since they do not share common tenets. This paper proposes the use of nested models for testing the efficacy of isolated disciplinary explanations of psychological and social problems versus the power of interdisciplinary explanations. According to this approach, such nested models would include alternative disciplinary theories competing against each other and against an inclusive model that combines these unidisciplinary explanations. This situation is illustrated with an empirical study using a questionnaire on predictors of precautionary behaviors against COVID-19. Data was analyzed using structural equations, considering a psychological and a health-science perspective, and integrated into an interdisciplinary model. Results from this study showed that the best model was the interdisciplinary model, thus providing some evidence for the use of nested models as a method to integrate different disciplines. The advantages of this approach are discussed in the face of the growing, complex, and serious problems that humanity is nowadays experiencing.