Document Type
Article
Publication Date
7-2024
Abstract
Previous research has demonstrated that interpersonal dynamics are fractal, and that conflict is a key control parameter that drives fractal complexity. The present study aimed to extend this line of research to examine the putative fractal structure of conflict dynamics over time, and the role that this self-organizing fractal structure may play in the resilience of romantic relationships. An experience sampling methodology was used to assess levels of conflict, satisfaction, and commitment in the dating relationships of undergraduate students, three times per day for 30 days. Hypothesis 1 was supported, with conflict ratings over time generally conforming to an inverse power-law distribution (IPL) distribution. Hypothesis 2 was supported as well, with better IPL fits measured as variance accounted for (R2), predicting higher levels of satisfaction and commitment over the 30 days. Hypothesis 3 showed mixed support, with moderate network linkages (i.e., soft assembly) between conflict and satisfaction and commitment predicting higher IPL fits (the linkage of satisfaction and commitment did not predict IPL fit as predicted). Hypothesis 4 predicted that IPL fit would interact with mean conflict, buffering the impacts of conflict on mean satisfaction and commitment across the 30 days. This hypothesis was not supported; however, several statistical factors may have obscured the buffering effects of higher IPL fit and so results may be inconclusive. These methodological factors, and others, are discussed along with the potential theoretical and practical implications of the current results.
Recommended Citation
Pincus, D. (2024). Romantic resilience: Fractal conflict dynamics and network flexibility predict dating satisfaction and commitment. Nonlinear Dynamics, Psychology, and Life Sciences, 28(3), 345-367.
Copyright
Society for Chaos Theory in Psychology & Life Sciences
Included in
Human Factors Psychology Commons, Other Psychology Commons, Personality and Social Contexts Commons, Social Psychology Commons
Comments
This article was originally published in Nonlinear Dynamics, Psychology, and Life Sciences, volume 28, issue 3, in 2024.