Date of Award
Doctor of Philosophy
Kristina C. Gordon
Chris L. Elledge, Amy J. Rauer, Garriy Shteynberg
The aim of this study was to bridge the growing body of research on interactional synchrony with variables reflecting relationship quality in romantic couples. Video data from 116 romantic couples who participated in a short-term relationship intervention (Gordon et al., 2019) and their self-report assessments of relationship satisfaction, emotional intimacy, and constructive communication patterns were used for analyses. Movement was objectively quantified for each partner using Motion Energy Analysis (MEA; Ramseyer & Tschacher, 2011), an automated frame-differencing method. Cross-lag correlations of the time-series data were then aggregated and operationalized as interactional synchrony. Empirical relationships between interactional synchrony and relationship quality variables were then examined.
Results demonstrated that interactional synchrony positively predicted relationship satisfaction at baseline, 1-month and 6-months post-intervention. Interactional synchrony predicted emotional intimacy at baseline and 1-month post intervention, but only predicted and constructive communication at baseline but not at 1-month post intervention. The presence of interactional synchrony was not stronger in affiliative conversations (discussion of courtship story and relationship strengths) relative to contentious conversations (relationship concerns). Interactional synchrony did not predict increases in the aforementioned relationship quality variables at any of the timepoints, baseline and 1-month for emotional intimacy and
Overall, results suggest that interactional synchrony is linked with indicators of relationship quality in romantic couples, does not vary based on conversational content, and does not predict changes in satisfaction, emotional intimacy, and constructive communication in a short-term intervention.
Garcia, Darren J., "Interactional Synchrony in Romantic Couples: Linking Dynamic Systems of Nonverbal Behavior with Outcome Data. " PhD diss., University of Tennessee, 2021.