Abstract

Underlying heterogeneity among individuals with cocaine dependence is widely postulated in the literature, however, identification of a group of factors that explain risk of cocaine use severity has yet to be confirmed. Latent mixture modeling evaluated 338 cocaine-dependent individuals recruited from the community to assess the evidence for the presence of distinct subgroups. Variables included 5 baseline questionnaires measuring cognitive function (Shipley), impulsivity (BIS), mood (BDI), affective lability (ALS), and addiction severity (ASI). Results failed to suggest multiple subgroups. Given a lack of evidence for discrete latent classes, an exploratory factor analysis (EFA) followed by exploratory structural equation modeling (ESEM) was implemented to identify functional dimensions to enhance interpretation of these variables. Findings from the EFA indicated a 3-factor model as the best fit, and the subsequent ESEM solution resulted in associations with lifetime cocaine use. Factor 1, best characterized by demographic factors (gender, age), is associated with less lifetime cocaine use. Psychological problems best characterize factor 2, which is associated with higher lifetime cocaine use. Finally, factor 3 is characterized by other substance use (alcohol and marijuana). Although this factor did not demonstrate a statistically reliable relation with self-reported, lifetime cocaine use, it did indicate a potentially meaningful positive association. These 3 factors delineate dimensions of functioning that likewise help characterize the variability found in previously established associations with self-reported cocaine use.

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