Open AccessMixture Modeling to Characterize Anorexia Nervosa: Integrating Personality and Eating Disorder Psychopathology
Author(s) -
Karen M. Jennings,
Lindsay P. Bodell,
Ross D. Crosby,
Ann F. Haynos,
Jennifer E. Wildes
Publication year - 2019
Publication title -
journal of the american psychiatric nurses association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.546
H-Index - 29
eISSN - 1532-5725
pISSN - 1078-3903
DOI - 10.1177/1078390319862029
Subject(s) - anorexia nervosa , psychopathology , categorical variable , psychology , latent class model , personality , clinical psychology , eating disorders , psychiatry , social psychology , statistics , mathematics , machine learning , computer science
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.