Are the symptoms of cannabis use disorder best accounted for by dimensional, categorical, or factor mixture models? A comparison of male and female young adults

Abstract

Despite the consensus that criteria for cannabis abuse and dependence and symptoms of withdrawal are best explained by a single latent liability, it remains unknown whether alternative models provide a better explanation of these criteria. A series of latent factor, latent class, and hybrid factor mixture models were fitted to data from 872 recent cannabis users from the Minnesota Twin Family Study who completed Diagnostic and Statistical Manual of Mental Disorders (3rd ed., revised, and 4th ed.) diagnostic criteria for cannabis abuse, dependence, and symptoms of withdrawal. Despite theoretical appeal, results did not support latent class or factor mixture modeling. Instead, symptoms of abuse, dependence, and withdrawal were better summarized by a single latent factor Cannabis Use Disorder (CUD) for male and female young adults. An almost 2-fold sex difference in item endorsement was best explained by a single mean difference on the CUD factor, indicating that young men have a greater latent liability toward expressing CUD.