Mixture Modeling to Characterize Anorexia Nervosa: Integrating Personality and Eating Disorder Psychopathology

Document Type

Article

Date of Original Version

5-1-2021

Abstract

BACKGROUND: Efforts to examine alternative classifications (e.g., personality) of anorexia nervosa (AN) using empirical techniques are crucial to elucidate diverse symptom presentations, personality traits, and psychiatric comorbidities. AIMS: The purpose of this study was to use an empirical approach (mixture modeling) to test an alternative classification of AN as categorical, dimensional, or hybrid categorical–dimensional construct based on the co-occurrence of personality psychopathology and eating disorder clinical presentation. METHODS: Patients with AN (N = 194) completed interviews and questionnaires at treatment admission and 3-month follow-up. Mixture modeling was used to test whether indicators best classified AN as categorical, dimensional, or hybrid. RESULTS: A four-latent class, one-latent dimension mixture model that was variant across groups provided the best fit to the data. Results suggest that all classes were characterized by low self-esteem and self-harming and suicidality tendencies. Individuals assigned to Latent Class 2 (LC2; n = 21) had a greater tendency toward being impulsive and easily angered and having difficulties controlling anger compared with those in LC1 (n = 84) and LC3 (n = 66). Moreover, individuals assigned to LC1 and LC3 were more likely to have a poor outcome from intensive treatment compared with those in LC4 (n = 21). Findings indicate that the dimensional aspect within each class measured frequency of specific eating disorder behaviors but did not predict treatment outcomes. CONCLUSIONS: These results emphasize the complexity of AN and the importance of considering how facets of clinical presentation beyond eating disorder behaviors may have different treatment and prognostic implications.

Publication Title, e.g., Journal

Journal of the American Psychiatric Nurses Association

Volume

27

Issue

3

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