Religious identity, religious practice, and religious beliefs across countries and world regions

Abstract

The aim of this study was to evaluate the structure and measurement invariance of the religious identity, religious practice, and religious beliefs across cultures in six world regions (Asia, non-Western Europe, North America, Oceania, South America, and Western Europe) and across Western, Educated, Industrialized, Rich, and Democratic regions (WEIRD) and non-WEIRD world regions. Confirmatory factory analysis examined whether the hypothesized measurement model fits the data; several multi-group confirmatory factor analyses were performed to examine measurement invariance through a progressive analytic strategy involving three invariance conditions of configural, metric, and scalar invariance. The results generally supported the adequate fit to the data of the three correlated factors model (religious identity-RII, religious practice-RPI, and religious beliefs—RBI); it was found to be full metric invariance for WEIRD regions (RII), North America (RII and RBI), Western Europe (RII) and Non-Western Europe (RII), and South America (RII and RBI). Finally, for RII, it was found to be full configural invariance in almost all regions, except North America and Oceania; for RPI, it was found to be full configural only in North America and Non-WEIRD regions; and for RBI, it was found to be full configural only in North America, Asia, and South America, being that women scored significantly higher than men in all three indices all over the world; finally, it was found to be configural, but not metric or scalar invariance across WEIRD and non-WEIRD world regions.

The Role of Artificial Intelligence in the Study of the Psychology of Religion

“…The development of predictive models that forecast religious behaviors, trends, and societal impacts is possible through the integration of computational models and AI techniques (Dwivedi et al 2023a). Historical data, demographic factors, and cultural variables can be used by researchers to predict models that predict religious affiliation, adherence, and changes in religious practices over time (Leite et al 2023).…”