Identifying and measuring network-based relational uncertainty: Looking outside of the dyadic bubble

Abstract

Previous research has explored both relational uncertainty and the importance of partners’ social networks in the development of close relationships. Combining these concepts would better facilitate our understanding of relational development. Accordingly, this four-study identifies and creates a novel measure for social network-based relational uncertainty experienced by individuals in romantic relationships. Studies 1 and 2 reveal eight distinct categories of network uncertainty via open coding. Studies 3 and 4 use these categories to create a network uncertainty measure (NUM) and compare it to several scales from relational turbulence theory. Exploratory and confirmatory factor analysis revealed five subscales, which derived from the original eight categories. Tests of convergent and divergent validity validate the NUM as a viable measure to be used in theory expansion as well as studies of network-dyad interaction. Regression analyses first compared the NUM to measures of self, partner, and relationship uncertainty. Results demonstrated strong empirical relationships between these variables, reaffirming conceptual similarities. Moreover, measures of relationship satisfaction intimacy were regressed on the NUM, controlling for relational uncertainty measures. Results demonstrated that the NUM contributes to these outcomes above and beyond self, partner, and relationship uncertainty. Findings are discussed in terms of empirical and conceptual value to the study of romantic relationships.