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Incorporating Social Network Variables into Relational Turbulence Theory: Popping the Dyadic Bubble

abstract: Relational turbulence theory (RTT) has primarily explored the effects of relational uncertainty and partner interdependence on relational outcomes. While robust, the theory fails to account for uncertainties and perceived interdependence stemming from extra-dyadic factors (such as partners’ social networks). Thus, this dissertation had two primary goals. First, scales indexing measures of social network-based relational uncertainty (i.e., network uncertainty) and social network interdependence are tested for convergent and divergent validity. Second, measurements of network uncertainty and interdependence are tested alongside measures featured in RTT to explore predictive validity. Results confirmed both measurements and demonstrated numerous significant relationships for turbulence variables. Discussions of theoretical applications and future directions are offered. / Dissertation/Thesis / Doctoral Dissertation Communication Studies 2018

Identiferoai:union.ndltd.org:asu.edu/item:49170
Date January 2018
ContributorsStein, James B. (Author), Mongeau, Paul A. (Advisor), Guerrero, Laura (Committee member), Dumka, Larry (Committee member), Arizona State University (Publisher)
Source SetsArizona State University
LanguageEnglish
Detected LanguageEnglish
TypeDoctoral Dissertation
Format163 pages
Rightshttp://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved

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