Abstract
Little empirical evidence exists to determine if there are alternative classification schemes for cannabis abuse and dependence beyond the definitions provided by Diagnostic and Statistical Manual (DSM) criteria. Current evidence is not conclusive regarding gender differences for cannabis use, abuse and dependence. It is not known if symptom profiles differ by gender. Latent class analysis (LCA) was used to assess whether cannabis abuse and dependence symptom patterns suggest a severity spectrum or distinct subtypes and to test whether symptom patterns differ by gender. Data from 3312 men and 2509 women in the National Longitudinal Alcohol Epidemiologic Survey (NLAES) who had used cannabis 12 + times life-time were included in the present analyses. The comparability of the solutions for men and women was examined through likelihood ratio chi(2) tests. Based on the Bayesian information criterion and interpretability, a four-class solution was selected, and the classes were labeled as 'unaffected/mild hazardous use', 'hazardous use/abuse', 'abuse/moderate dependence' and 'severe abuse/dependence'. The solutions were generally suggestive of a severity spectrum. Compared to men, women were more likely to be in the 'unaffected/mild hazardous use' class and less likely to be in the 'abuse/moderate dependence' or 'severe abuse/dependence' classes. The results were generally similar for men and women. However, men had consistently and substantially higher endorsements of hazardous use than women, women in the 'abuse/moderate dependence' class had moderately higher rates for four dependence symptoms, and women in two of the classes were more likely to endorse withdrawal. Our findings generally support the severity dimension for DSM-IV cannabis abuse and dependence symptomatology for both men and women. While our results indicate that public health messages may have generic and not gender-specific content, treatment providers should focus more effort on reducing hazardous use in men and alleviating withdrawal in women.
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