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首页> 外文期刊>Nonlinear dynamics, psychology and life sciences >A Characteristic Destabilization Profile in Parent-Child Interactions Associated with Treatment Efficacy for Aggressive Children
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A Characteristic Destabilization Profile in Parent-Child Interactions Associated with Treatment Efficacy for Aggressive Children

机译：侵略性儿童的治疗效果与亲子互动中的特征性不稳定特征

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This study examined profiles of change in repeated mother-child interactions over the course of a 12 week treatment period for childhood aggression. The aim of this study was to investigate whether it was possible to detect the characteristic profile of change, typical for phase transitions, over the course of treatment, and whether this profile was associated with positive treatment outcomes. Entropy values were computed for six repeated real-time observations of each mother-child dyad, using a novel application of recurrence quantification analysis for categorical time series. Subsequent latent class growth curve analysis on the sequences of entropy values revealed two distinct classes of dyads, with one class showing a clear peak in entropy over the six measurement points. The latent class membership variables showed a significant systematic relationship with observed dyad improvement (as rated by clinicians). The class with the peak in entropy over the sessions consisted largely of treatment improvers. Further analysis revealed that improvers and non-improvers could not be distinguished based on content-specific changes (e.g. more positivity or less negativity during the interaction). The present study revealed a treatment-related destabilization pattern in real-time behaviors that was related to better treatment outcomes, and underlines the value of dynamic nonlinear time-series analysis (especially RQA) in the study of dyadic interactions in clinical contexts.
机译：这项研究调查了在12周治疗期间针对儿童侵略行为反复进行的母子互动的变化情况。这项研究的目的是调查是否有可能在治疗过程中检测出典型的相变变化特征，以及该特征是否与积极的治疗结果相关。使用针对类别时间序列的新型循环量化分析的新应用，对每个母二倍体的六个重复实时观测值计算熵值。随后对熵值序列的潜在类增长曲线分析揭示了两个不同的二元组，其中一个类在六个测量点上显示出清晰的熵峰值。潜在的班级成员变量显示出与观察到的二分体改善有显着的系统关系（由临床医生评估）。在整个疗程中熵达到最高的课程主要由治疗改良剂组成。进一步的分析表明，无法基于特定于内容的更改来区分改进者和非改进者（例如，在交互过程中具有更大的积极性或更少的否定性）。本研究揭示了与更好的治疗结果相关的实时行为中与治疗相关的不稳定模式，并强调了动态非线性时间序列分析（尤其是RQA）在临床背景下二元相互作用研究中的价值。

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