In this study, we used multilevel vector autoregressive network analysis to examine clients' intrapersonal and client-therapist interpersonal emotional dynamics from session to session. We expected to find differences in the network structure (i.e., the density) of responders versus nonresponders to treatment. The sample comprised 95 clients treated by 58 therapists in a university clinic. Clients and therapists self-reported their emotions after each session. The functioning level was assessed at the beginning of each session using clients' self-reports. The results indicated that higher intrapersonal density among clients' emotions within the temporal network (associations from session to session) was associated with less improvement in functioning, but higher intrapersonal density among clients' emotions within the contemporaneous network (same-session associations) was not associated with clients' functioning level. Additionally, higher interpersonal density among clients'-therapists' emotions within the contemporaneous network was associated with greater improvement in clients' functioning. These findings highlight the importance of recognizing the dynamic nature of emotions within the client, as well as between the client and the therapist and the contribution of such session-by-session emotional dynamics to the outcome of psychotherapy. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

中文翻译：

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人际和人际情感网络及其与治疗结果的关联。

在这项研究中，我们使用多级向量自回归网络分析来检查从会话到会话的客户的内省和客户-治疗师的人际情感动态。我们期望发现对治疗有反应者与无反应者的网络结构（即密度）的差异。样本包括在大学诊所接受 58 名治疗师治疗的 95 名客户。客户和治疗师在每次治疗后自我报告他们的情绪。在每次会议开始时使用客户的自我报告评估功能水平。结果表明，在时间网络（从会话到会话的关联）中客户情绪中较高的内省密度与功能改善较少相关，但客户之间较高的内省密度与 同时期网络（同一会话关联）中的情绪与客户的功能水平无关。此外，在同期网络中客户-治疗师情绪之间的人际密度更高，与客户功能的更大改善有关。这些发现强调了识别来访者内部以及来访者和治疗师之间情绪的动态性质的重要性，以及这种逐个会话的情绪动态对心理治疗结果的贡献。（PsycINFO 数据库记录 (c) 2020 APA，保留所有权利）。同时期网络中的情绪与客户功能的更大改善有关。这些发现强调了识别来访者内部以及来访者和治疗师之间情绪的动态性质的重要性，以及这种逐个会话的情绪动态对心理治疗结果的贡献。（PsycINFO 数据库记录 (c) 2020 APA，保留所有权利）。同时期网络中的情绪与客户功能的更大改善有关。这些发现强调了识别来访者内部以及来访者和治疗师之间情绪的动态性质的重要性，以及这种逐次会话的情绪动态对心理治疗结果的贡献。（PsycINFO 数据库记录 (c) 2020 APA，保留所有权利）。