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Updated: Jan 15, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
Published on: May 10, 2022
Emotional intelligence and loneliness in eating disorders: a cluster-analytic study across diagnostic categories
Paolo Meneguzzo1,2, Anna Marzotto3, Fabio Conti4
1Department of Neuroscience, University of Padova, Via Giustiniani 2, Padova, 35128, Italy. paolo.meneguzzo@unipd.it.
Objective:
The present study aimed to investigate emotional intelligence and loneliness in individuals with eating disorders (EDs) using a transdiagnostic approach. Specifically, it sought to identify emotional-loneliness profiles through cluster analysis and evaluate their association with clinical characteristics and diagnostic categories.
Method:
A total of 371 participants (220 with EDs and 151 healthy controls) completed self-report measures including the Wong and Law Emotional Intelligence Scale (WLEIS), the UCLA Loneliness Scale, and the Eating Disorder Examination Questionnaire (EDE-Q). K-means cluster analysis was performed on standardized WLEIS and UCLA scores. Between-group comparisons and post hoc tests were conducted to assess differences across clusters in ED severity, BMI, age, and diagnosis. Logistic and chi-square analyses explored diagnostic distribution and predictive associations.
Results:
Three distinct clusters emerged: (1) Low Emotional Intelligence/High Loneliness (n = 130), (2) Moderate EI/Moderate Loneliness (n = 141), and (3) High EI/Low Loneliness (n = 100). Cluster 1 showed the most adaptive profile, while Cluster 0 exhibited the highest ED severity and loneliness. Diagnostic category distribution differed significantly across clusters (χ²(8) = 89.56, p < .001), but emotional profiles did not align exclusively with specific diagnoses, supporting a transdiagnostic model. Emotional intelligence and loneliness significantly predicted ED status.
Conclusion:
Emotional intelligence and loneliness form meaningful psychological profiles that transcend ED diagnoses and are associated with clinical severity. Assessing these factors may enhance early detection and inform targeted interventions. Future studies should explore the role of early adversity and trauma in shaping these profiles.
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