Objective: 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.
Method: 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.
Results: 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.
Conclusions: 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.