A Network Analysis of Cognitive Flexibility, Emotion Regulation, and Symptom Severity in Patients with Major Depression.

IF 2.9
Yağmur Sarı, Derya Tanriverdi̇, Safi̇ye Özgüç
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Abstract

This study aims to investigate the network structure linking cognitive flexibility, cognitive emotion regulation strategies, and depressive symptom severity in patients with major depressive disorder and identify the most central and bridge components of this network. This study was conducted using a descriptive and relational design. 188 patients diagnosed with major depression were included in the study. The BDI, CFI and CERQ were used as data collection tools. Network analysis revealed a structure containing 12 nodes and 33 active edges out of 66 possible edges (EBICglasso, γ = 0.50; resulting sparsity = 0.50). In terms of strength centrality, Positive Reappraisal (z-strength = 1.864), Refocus on Planning (z-strength = 1.176), and Acceptance (z-strength = 1.035) formed a statistically indistinguishable top-strength cluster, indicating that these three adaptive strategies were the most central nodes in the network. In terms of Expected Influence, the CFI Control subdimension (EI = - 1.821) and BDI (EI = - 1.741) showed the strongest negative values. Bootstrap stability analysis indicated modest stability for strength centrality (CS-coefficient ≈ 0.27) and low stability for betweenness and closeness, indicating that centrality findings should be interpreted as exploratory. Bridge centrality analyses revealed that BDI (0.580), CFI Control (0.570), and CFI Alternatives (0.540) were the strongest cross-domain connectors. Refocus on Planning and Alternatives exhibited positive bridge expected influence, indicating facilitative cross-domain effects, while Control, Catastrophizing, and BDI exhibited negative bridge expected influence, indicating a suppressive cross-domain effect. Cognitive restructuring interventions may show limited efficacy unless perceived loss of control and, to a lesser extent, catastrophizing which appear to function as suppressive hubs, are addressed first; however, given the cross-sectional design, this staged-intervention hypothesis remains speculative and requires longitudinal validation. Notably, the Control-BDI edge received weaker Bayesian support (Pr(H1) = 0.213) than the network's core adaptive-strategy connections, warranting caution in interpreting this specific association. These findings tentatively suggest, rather than establish that interventions aimed at restoring perceived control may represent a promising therapeutic target for enhancing adaptive emotion regulation in major depression.

重度抑郁症患者认知灵活性、情绪调节和症状严重程度的网络分析。
本研究旨在探讨重性抑郁症患者认知灵活性、认知情绪调节策略和抑郁症状严重程度之间的网络结构,并确定该网络的最中心和桥梁成分。本研究采用描述性和相关性设计。188名确诊为重度抑郁症的患者参与了这项研究。采用BDI、CFI和CERQ作为数据收集工具。网络分析显示,该结构包含12个节点和66个可能的边中的33个活动边(EBICglasso, γ = 0.50;结果稀疏度= 0.50)。在强度中心性方面,Positive Reappraisal (z-strength = 1.864)、Refocus on Planning (z-strength = 1.176)和Acceptance (z-strength = 1.035)形成了一个统计上难以区分的top-strength聚类,表明这三种自适应策略是网络中最中心的节点。在期望影响方面,CFI控制子维度(EI = - 1.821)和BDI (EI = - 1.741)的负值最强。自举稳定性分析表明,强度中心性的稳定性适中(cs系数≈0.27),中间性和接近性的稳定性较低,表明中心性的研究结果应该被解释为探索性的。桥梁中心性分析显示,BDI(0.580)、CFI Control(0.570)和CFI Alternatives(0.540)是最强的跨域连接器。重新关注规划和备选方案表现出正向的桥接预期影响,表明促进跨域效应,而控制、灾变和BDI表现出负向的桥接预期影响,表明抑制跨域效应。认知重组干预可能显示出有限的效果,除非首先解决感觉失去控制和在较小程度上表现为抑制中心的灾难化;然而,考虑到横断面设计,这种分阶段干预假设仍然是推测性的,需要纵向验证。值得注意的是,与网络的核心自适应策略连接相比,控制- bdi边缘得到的贝叶斯支持较弱(Pr(H1) = 0.213),因此在解释这种特定关联时需要谨慎。这些发现初步表明,而不是确定旨在恢复感知控制的干预措施可能代表了增强重度抑郁症适应性情绪调节的有希望的治疗目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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