Full metadata
Title
Incorporating social network variables into relational turbulence theory: popping the dyadic bubble
Description
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.
Date Created
2018
Contributors
- Stein, James (Author)
- Mongeau, Paul A. (Thesis advisor)
- Guerrero, Laura (Committee member)
- Dumka, Larry (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
x, 151 pages : illustrations
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.49170
Statement of Responsibility
by James Stein
Description Source
Viewed on October 30, 2018
Level of coding
full
Note
thesis
Partial requirement for: Ph.D., Arizona State University, 2018
bibliography
Includes bibliographical references (pages 127-137)
Field of study: Communication studies
System Created
- 2018-06-01 08:03:17
System Modified
- 2021-08-26 09:47:01
- 3 years 3 months ago
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