Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-23T07:35:38.230Z Has data issue: false hasContentIssue false
  • English
  • Français

A Longitudinal Test of Relational Turbulence Theory

Published online by Cambridge University Press:  22 December 2020

James B. Stein Open the ORCID record for James B. Stein [Opens in a new window]
James B. Stein*
Affiliation:
Communication Department, Dixie State University, St. George, Utah, USA
*
Author for correspondence: James Stein, Jennings Communication Building (Room 114), Dixie State University, 225 S. 700 E. St. George, UT, 84770, USA. Email: [email protected]
Get access

Abstract

Relational turbulence theory (RTT) proposes causal relationships across cognitive, emotional and communicative variables. Although many tenets of this theory have been tested individually, there has not yet been a comprehensive, predictive examination of RTT. Using structural equation modelling, this study longitudinally tested several propositions and axioms of RTT. Results are largely in line with many of RTT's predictions. Time 1 relational uncertainty predicted time 2 biased cognitions. Time 1 facilitation from a partner predicted time 2 negative emotions. Negative emotions cross-sectionally related to both the enactment and valence of relational communication episodes. Relational turbulence theory's proposed feedback loop received partial support, such that time 1 communication valence (but not engagement) predicted time 2 partner uncertainty, relationship uncertainty and partner facilitation. Results are discussed in terms of theory expansion and refinement.

Keywords

relational turbulenceinterpersonal communicationuncertaintyinterdependence
Type
Research Article
Information
Journal of Relationships Research , Volume 11 , 2020 , e20
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Berger, C.R., & Bradac, J.J. (1982). Language and social knowledge: Uncertainty in interpersonal relationships. London, England: Arnold.Google Scholar
Berscheid, E. (1983). Emotion. In Kelley, H.H. et al. (Eds.), Close relationships (pp. 110–168). San Francisco, CA: Freeman.Google Scholar
Browne, M.W., & Cudek, R. (1993). Alternative ways of assessing model fit. In Bollen, K.A. & Long, J.S. (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.Google Scholar
Buhrmester, M., Kwang, T., & Gosling, S.D. (2011). Amazon's Mechanical Turk: A new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science, 6, 3–5.CrossRefGoogle ScholarPubMed
Collins, L.M. (2006). Analysis of longitudinal data: The integration of theoretical model, temporal design, and statistical model. Annual Review of Psychology, 57, 505–528.CrossRefGoogle ScholarPubMed
Dillard, J.P., Kinney, T.A., & Cruz, M.G. (1996). Influence, appraisals, and emotions in close relationships. Communications Monographs, 63, 105–130.CrossRefGoogle Scholar
Hu, L.-T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 8, 205–223.Google Scholar
Knobloch, L.K. (2006). Relational uncertainty and message production within courtship: Features of date request messages. Human Communication Research, 32, 244–273.CrossRefGoogle Scholar
Knobloch, L.K. (2008). The content of relational uncertainty within marriage. Journal of Social and Personal Relationships, 25, 467–495.CrossRefGoogle Scholar
Knobloch, L.K., & Carpenter-Theune, K.E. (2004). Topic avoidance in developing romantic relationships: Associations with intimacy and relational uncertainty. Communication Research, 31, 173–205.CrossRefGoogle Scholar
Knobloch, L.K., Miller, L.E., & Carpenter, K.E. (2007). Using the relational turbulence model to understand negative emotion within courtship. Personal Relationships, 14, 91–112.CrossRefGoogle Scholar
Knobloch, L.K., & Solomon, D.H. (1999). Measuring the sources and content of relational uncertainty. Communication Studies, 50, 261–278.CrossRefGoogle Scholar
Knobloch, L.K., & Solomon, D.H. (2004). Interference and facilitation from partners in the development of interdependence within romantic relationships. Personal Relationships, 11, 115–130.CrossRefGoogle Scholar
Knobloch, L.K., & Theiss, J.A. (2010). An actor–partner interdependence model of relational turbulence: Cognitions and emotions. Journal of Social and Personal Relationships, 27, 595–619.CrossRefGoogle Scholar
Knobloch, L.K., & Theiss, J.A. (2011). Relational uncertainty and relationship talk within courtship: A longitudinal actor–partner interdependence model. Communication Monographs, 78, 3–26.CrossRefGoogle Scholar
McArdle, J.J., & Nesselroade, J.R. (2014). Longitudinal data analysis using structural equation models. American Psychological Association.CrossRefGoogle Scholar
Owen, W.F. (1984). Interpretive themes in relational communication. Quarterly Journal of Speech, 70, 274–287.CrossRefGoogle Scholar
Paolacci, G., & Chandler, J. (2014). Inside the Turk: Understanding Mechanical Turk as a participant pool. Current Directions in Psychological Science, 23, 184–188.CrossRefGoogle Scholar
Peer, E., Vosgerau, J., & Acquisti, A. (2014). Reputation as a sufficient condition for data quality on Amazon Mechanical Turk. Behavior Research Methods, 46, 1023–1031.CrossRefGoogle ScholarPubMed
Preacher, K.J., & Hayes, A.F. (2008). Assessing mediation in communication research. In Hayes, A., Slater, M., & Snyder, L. (Eds.), The Sage sourcebook of advanced data analysis methods for communication research (pp. 13–54). Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
Reisenzein, R. (2007). What is a definition of emotion? And are emotions mental-behavioral processes? Social Science Information, 46, 424–428.CrossRefGoogle Scholar
Schumacker, R.E., & Lomax, R.G. (2004). A beginner's guide to structural equation modeling (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.CrossRefGoogle Scholar
Solomon, D.H., & Brisini, K.S.C. (2017). Operationalizing relational turbulence theory: Measurement and construct validation. Personal Relationships, 24, 768–789.CrossRefGoogle Scholar
Solomon, D.H., & Knobloch, L.K. (2004). A model of relational turbulence: The role of intimacy, relational uncertainty, and interference from partners in appraisals of irritations. Journal of Social and Personal Relationships, 21, 795–816.CrossRefGoogle Scholar
Solomon, D.H., Knobloch, L.K., Theiss, J.A., & McLaren, R.M. (2016). Relational turbulence theory: Explaining variation in subjective experiences and communication within romantic relationships. Human Communication Research, 32, 469–503.Google Scholar
Solomon, D.H., & Samp, J.A. (1998). Power and problem appraisal: Perceptual foundations of the chilling effect in dating relationships. Journal of Social and Personal Relationships, 15, 191–209.CrossRefGoogle Scholar
Solomon, D.H., & Theiss, J.A. (2008). A longitudinal test of the relational turbulence model on romantic relationship development. Personal Relationships, 15, 339–357.CrossRefGoogle Scholar
Solomon, D., & Weber, K., & Steuber, K. (2010). Turbulence in relational transitions. In Smith, S.W. & Wilson, R.W. (Eds.), New directions in interpersonal communication (pp. 115–134). Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
Theiss, J.A., & Knobloch, L.K. (2014). Relational turbulence and the post-deployment transition: Self, partner, and relationship focused turbulence. Communication Research, 41, 27–51.CrossRefGoogle Scholar
Theiss, J.A., & Nagy, M.E. (2013). A relational turbulence model of partner responsiveness and relationship talk across cultures. Western Journal of Communication, 77, 186–209.CrossRefGoogle Scholar
Theiss, J.A., & Solomon, D.H. (2006a). A relational turbulence model of communication about irritations in romantic relationships. Communication Research, 33, 391–418.CrossRefGoogle Scholar
Theiss, J.A., & Solomon, D.H. (2006b). Coupling longitudinal data and multilevel modeling to examine the antecedents and consequences of jealousy experiences in romantic relationships: A test of the relational turbulence model. Human Communication Research, 32, 469–503.CrossRefGoogle Scholar