A Network Analytic Approach to Dissociation: New Insights from Clinical Data.

IF 2.3 3区 医学 Q2 PSYCHIATRY
Philipp Wülfing, Carsten Spitzer
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引用次数: 0

Abstract

The transdiagnostic construct of dissociation, characterized by a disintegration of specific psychological functions such as consciousness, memory, identity, perception, body representation, and behavior, remains elusive to a unified conceptualization. Specifically, its dimensionality is a matter of ongoing controversy. Empirical approaches applying factor analyses to the Dissociative Experiences Scale (DES) have yielded inconsistent findings. This study adopts a novel methodological approach, utilizing Exploratory Graph Analysis (EGA) to address this issue. In a sample of 668 day-hospital patients undergoing psychotherapy for a variety of mental disorders, a Gaussian graphical model was estimated for the 28 items of the DES. Additionally, the stability of the results was ensured by bootstrap procedures. While both the original EGA and the bootstrap EGA suggested four dimensions, the structural consistency of this solution was low due to an instability of 12 items. After excluding 10 of these unstable items, re-analyses again revealed a four-factor structure, but boot EGA indicated that one factor had unsatisfactory structural consistency due to the multidimensionality of its two items. Upon removing these, our final network consisted of 16 items mapping onto 3 dimensions. Our study, using data from a diagnostically heterogeneous sample, replicates and extends previous findings on the dimensionality of dissociation as captured by the DES. The three dimensions identified correspond to segregated processes, derealization/depersonalization, and absorption. This solution aligns with a bipartite model of dissociation with two broader categories referring to either altered states of consciousness (often named detachment) or to non-integrated mental modules (labeled as compartmentalization).

解离的网络分析方法:来自临床数据的新见解。
解离是一种跨诊断的概念,其特征是特定心理功能的解体,如意识、记忆、身份、感知、身体表征和行为等。具体来说,它的维度问题一直存在争议。对分离性体验量表(DES)进行因子分析的经验方法得出的结果并不一致。本研究采用了一种新颖的方法论,利用探索性图表分析(EGA)来解决这一问题。在 668 名因各种精神障碍而接受心理治疗的日间医院患者样本中,对 DES 的 28 个项目进行了高斯图形模型估计。此外,还通过引导程序确保了结果的稳定性。虽然原始 EGA 和自举 EGA 都表明有四个维度,但由于有 12 个项目不稳定,因此该解决方案的结构一致性较低。在剔除了其中 10 个不稳定的项目后,重新分析再次显示出四因素结构,但自举 EGA 显示,有一个因素由于其两个项目的多维性,其结构一致性不能令人满意。去除这两个项目后,我们的最终网络由映射到 3 个维度的 16 个项目组成。我们的研究使用了来自诊断异质样本的数据,复制并扩展了之前关于 DES 所捕捉的分离维度的研究结果。确定的三个维度分别对应于分离过程、去理想化/去人格化和吸收。这一解决方案与解离的两部分模型相一致,其中两个更广泛的类别指的是意识状态的改变(通常被命名为分离)或非整合的心理模块(被标记为分隔)。
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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来源期刊
CiteScore
6.00
自引率
6.10%
发文量
39
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