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Impulsivity and compulsivity have been implicated as important transdiagnostic dimensional phenotypes with potential relevance to addiction. We aimed to develop a model that conceptualizes these constructs as overlapping dimensional phenotypes and test whether different components of this model explain the co-occurrence of addictive and related behaviors.
A large sample of adults (N = 487) was recruited through Amazon’s Mechanical Turk and completed self-report questionnaires measuring impulsivity, intolerance of uncertainty, obsessive beliefs, and the severity of 6 addictive and related behaviors. Hierarchical clustering was used to organize addictive behaviors into homogenous groups reflecting their co-occurrence. Structural equation modeling was used to evaluate fit of the hypothesized bifactor model of impulsivity and compulsivity and determine the proportion of variance explained in the co-occurrence of addictive and related behaviors by each component of the model.
Addictive and related behaviors clustered into 2 distinct groups: Impulse-Control Problems, consisting of harmful alcohol use, pathological gambling, and compulsive buying, and Obsessive-Compulsive-Related Problems, consisting of obsessive-compulsive symptoms, binge eating, and internet addiction. The hypothesized bifactor model of impulsivity and compulsivity provided the best empirical fit, with 3 uncorrelated factors corresponding to a general Disinhibition dimension, and specific Impulsivity and Compulsivity dimensions. These dimensional phenotypes uniquely and additively explained 39.9% and 68.7% of the total variance in Impulse-Control Problems and Obsessive-Compulsive-Related Problems.
A model of impulsivity and compulsivity that represents these constructs as overlapping dimensional phenotypes has important implications for understanding addictive and related behaviors in terms of shared etiology, comorbidity, and potential transdiagnostic treatments.
We aimed to determine whether individuals with obsessive-compulsive disorder (OCD) and demographically matched healthy individuals can be clustered into distinct clinical subtypes based on dimensional measures of their self-reported compulsivity (OBQ–44 and IUS–12) and impulsivity (UPPS–P).
Participants (n=217) were 103 patients with a clinical diagnosis of OCD; 79 individuals from the community who were “OCD-likely” according to self-report (Obsessive-Compulsive Inventory–Revised scores equal or greater than 21); and 35 healthy controls. All data were collected between 2013 and 2015 using self-report measures that assessed different aspects of compulsivity and impulsivity. Principal component analysis revealed two components broadly representing an individual's level of compulsivity and impulsivity. Unsupervised clustering grouped participants into four subgroups, each representing one part of an orthogonal compulsive-impulsive phenotype.
Clustering converged to yield four subgroups: one group low on both compulsivity and impulsivity, comprised mostly of healthy controls and demonstrating the lowest OCD symptom severity; two groups showing roughly equal clinical severity, but with opposing drivers (i.e., high compulsivity and low impulsivity, and vice versa); and a final group high on both compulsivity and impulsivity and recording the highest clinical severity. Notably, the largest cluster of individuals with OCD was characterized by high impulsivity and low compulsivity. Our results suggest that both impulsivity and compulsivity mediate obsessive-compulsive symptomatology.
Individuals with OCD can be clustered into distinct subtypes based on measures of compulsivity and impulsivity, with the latter being found to be one of the more defining characteristics of the disorder. These dimensions may serve as viable and novel treatment targets.
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