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A quantitative study of body dysmorphic disorder: Latent structure and correlates

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Abstract Body dysmorphic disorder (BDD) is a body image disturbance of perceived ugliness that is underdiagnosed and often untreated. Although the nature of BDD is assumed to be synonymous with its… Click to show full abstract

Abstract Body dysmorphic disorder (BDD) is a body image disturbance of perceived ugliness that is underdiagnosed and often untreated. Although the nature of BDD is assumed to be synonymous with its conceptualization as a discrete DSM category, recent research suggests the possibility of a more complex latent structure. To clarify BDD’s latent structure, data from a large (N = 1,385), unselected sample was analyzed using an integrated, quantitative approach. From multiple measures of BDD, three symptom indicators were extracted that had the following appearance-related content: (1) perception—negative self-evaluation, (2) avoidance—fear of negative social evaluation, and (3) behavior—activities to modify flaws. Factor mixture modeling of the three indicators supported a hybrid categorical-dimensional latent structure with three distinct classes that had varying levels of the three extracted BDD symptoms. The three classes (subgroups of individuals) were a large non-symptomatic class (i.e., Non-BDD) and two smaller classes (i.e., Elevated Avoidance BDD, Elevated BDD). Analyses of conceptually overlapping personality and symptom measures showed social anxiety symptoms were highest in the Elevated Avoidance class and lowest in the Non-BDD class. Depression and obsessive-compulsive disorder symptoms were higher in the two BDD symptomatic classes than in the Non-BDD class, whereas negative affect was highest in the Elevated Avoidance class and lowest in the Non-BDD class. These findings suggest that modifications to current conceptualizations BDD could lead to improvements in BDD identification.

Keywords: body; bdd; latent structure; class; disorder

Journal Title: Journal of Obsessive-Compulsive and Related Disorders
Year Published: 2019

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