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浪漫韧性:分形冲突动态和网络灵活性预测约会满意度和承诺。

Romantic Resilience: Fractal Conflict Dynamics and Network Flexibility Predict Dating Satisfaction and Commitment.

机构信息

Chapman University, Orange CA.

出版信息

Nonlinear Dynamics Psychol Life Sci. 2024 Jul;28(3):345-367.

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.

摘要

先前的研究表明人际动态是分形的,而冲突是驱动分形复杂性的关键控制参数。本研究旨在将这一研究方向扩展到考察冲突动态随时间的潜在分形结构,以及这种自组织分形结构可能在浪漫关系的恢复力中所起的作用。采用经验抽样方法评估本科生约会关系中冲突、满意度和承诺的水平,每天三次,持续 30 天。假设 1 得到了支持,随着时间的推移,冲突评估通常符合反幂律分布(IPL)。假设 2 也得到了支持,更好的 IPL 拟合度(由方差解释),预测在 30 天内更高的满意度和承诺水平。假设 3 显示出混合支持,即冲突和满意度与承诺之间存在适度的网络联系(即软组装),这可以预测更高的 IPL 拟合度(如预测的那样,满意度和承诺的联系并没有预测 IPL 拟合度)。假设 4 预测 IPL 拟合度将与平均冲突相互作用,缓冲 30 天内冲突对平均满意度和承诺的影响。这个假设没有得到支持;然而,一些统计因素可能掩盖了更高 IPL 拟合度的缓冲效应,因此结果可能不确定。本文讨论了这些方法因素,以及当前结果的潜在理论和实际意义。

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