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Updated: Oct 9, 2025

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
Published on: May 10, 2022
Identifying subgroups of patients with eating disorders based on emotion dysregulation profiles: A factor mixture
Line Nordgren1, Ata Ghaderi2, Brjánn Ljótsson2
1Department of Behavioural Sciences and Learning.
Abstract:
This study aimed to investigate whether individuals with eating disorders (ED; N = 857) could be empirically classified into qualitatively distinct subgroups based on their emotion dysregulation profiles. A series of increasingly complex models (factor analysis; FA, latent class analysis; LCA, and factor mixture models; FMM) were evaluated to determine whether the structure of psychopathology was best characterized by emotional dysregulation subtypes, dimensions, or a combination of the two. The subscales of the difficulties in emotion regulation scale were used as indicators. Data were split into an exploratory and confirmatory dataset, and the best-fitting models in the exploratory set were compared and validated against clinically relevant variables in the confirmatory set. Results confirmed that individuals could be grouped into three latent classes that were clearly distinguishable on ED pathology and psychiatric comorbidity. Specifically, individuals belonging to the class with more severe emotion dysregulation had higher levels of ED pathology and were more likely to engage in vomiting and binge eating as well as substance abuse and self-harm. These results provide initial support for emotional dysregulation profiling as a viable transdiagnostic approach to classification in the field of EDs. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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