Marijuana and Other Substance Use Among Motor Vehicle Operators: A Latent Class Analysis

The deleterious effect of multiple-substance use on driving performance is well established, but relatively little research has examined the patterns of drug use among multiple-substance users and its relationship to both alcohol use and adverse driving outcomes.

The current study used latent class analysis to examine subgroups of substance users among a population of drivers who screened positively for 2 or more of 13 substances other than alcohol (N = 250). A series of logistic regression analyses was conducted to examine demographic predictors of latent class assignment and class association with adverse driving outcomes.

Four distinct subclasses of users were identified among multiple-substance-using drivers: Class 1 consisted of individuals who demonstrated high levels of all substances indicators (5%). The second class demonstrated high levels of marijuana and cocaine use and lower levels of all other substances (27%). The third class screened high for marijuana and nonmedical prescription opiate analgesics use (36%), whereas the last class demonstrated high nonmedical prescription opiate analgesics and benzodiazepine use (32%). Drivers in Class 2 (marijuana and cocaine users) were more likely to be younger and have a positive breath alcohol concentration than drivers in any other class.

Because multidrug users show dissimilar characteristics, the propensity of researchers to lump all multiple-substance users together may either erroneously attribute the potentially profound impact of those in the marijuana and cocaine use class to all multiple-substance users or dilute their specific contribution to crash risk.