Dissociation in focus: replicating and extending network analytic insights based on the dissociative experiences...

Area of Science:

• Psychometrics
• Clinical Psychology
• Network Analysis

Background:

• The dimensional structure of the Dissociative Experiences Scale (DES) remains debated, with previous factor-analytic studies yielding inconsistent results.
• This ambiguity hinders the interpretability of DES scores and limits its clinical utility for screening and treatment planning.
• Focusing on a clinical cohort is crucial for ensuring diagnostic relevance and capturing dissociation across various mental disorders.

Purpose of the Study:

• To employ Exploratory Graph Analysis (EGA), a network-psychometric method, to replicate and refine the DES structure.
• To validate the DES structure in a large, diverse UK clinical population.
• To clarify the core dimensions of dissociation for improved clinical application.

Main Methods:

• Utilized Exploratory Graph Analysis (EGA) on data from 1,260 treatment-seeking adults in UK personality disorder and NHS IAPT services.
• Estimated a Gaussian graphical model using Spearman correlations and performed 1,000 parametric bootstraps.
• Applied item- and dimension-stability indices for iterative pruning and compared solutions using the Adjusted Rand Index (ARI).

Main Results:

• A robust 21-item, three-factor solution emerged, comprising amnesia, derealisation/depersonalisation, and absorption.
• Each factor demonstrated high stability, appearing in over 93% of bootstrap samples, with the overall structure replicated in 96.1% of samples.
• The recovered structure showed perfect correspondence with the original DES model (ARI=1.00) and moderate to substantial agreement with recent network studies (ARI=0.51, 0.80).

Conclusions:

• EGA successfully recovered the established three-factor configuration of the DES in a broad clinical sample.
• The findings support amnesia, derealisation/depersonalisation, and absorption as stable, core dimensions of dissociation.
• Further research is recommended to assess temporal stability and broaden construct coverage beyond the DES.