A latent class approach to treatment readiness corresponds to a transtheoretical ("Stages of Change") model.

Motivation for treatment among people with substance use problems is an important aspect of treatment success. Models for treatment motivation are widely debated. Latent Class Analysis can help to demonstrate the appropriateness of available models. The current study utilizes Latent Class Analysis to analyze treatment readiness statements as they relate to the reduction or cessation of marijuana, cocaine, and opioid use among 539 cocaine and opioid users recruited from the community of Baltimore, MD, USA. Participants completed an in-person structured interview including demographic questions, a treatment readiness questionnaire with items on Intention to Stop Use (ISU) and Problem Recognition (PR), current substance abuse treatment utilization, and urinalysis testing for marijuana, cocaine, and heroin. Latent class models were fit to the treatment readiness questionnaire. A four-class model provided the best fit with one class low on both ISU and PR ("Pre-contemplative"), a second class low on ISU but high on PR ("Contemplative"), a third class high on both ("Preparation/Action"), and a final class high on ISU but low on PR ("Post-Action"). Compared to the "Contemplative" class, the "Pre-contemplative" class was significantly more likely to be positive for marijuana, and the "Post-Action" class was significantly less likely to be positive for opioids. The "Preparation/Action" class was significantly more likely to be in treatment. With the exception of the "Post-Action" class, the analysis appears similar to the "Stages of Change" model and suggests that problem recognition and intention to stop use are important domains in the model. However, further longitudinal research is needed to assess predictive validity of model.

Cigarette smoking, illicit drug use, and routes of administration among heroin and cocaine users.

Cigarette smoking is ubiquitous among illicit drug users. Some have speculated that this may be partially due to similarities in the route of administration. However, research examining the relationship between cigarette smoking and routes of administration of illicit drugs is limited. To address this gap, we investigated sociodemographic and drug use factors associated with cigarette smoking among cocaine and heroin users in the Baltimore, Maryland community (N=576). Regular and heavy cigarette smokers were more likely to be White, have a history of a prior marriage, and have a lower education level. Regular smoking of marijuana and crack was associated with cigarette smoking, but not heavy cigarette smoking. Injection use was more common among heavy cigarette smokers. In particular, regular cigarette smokers were more likely to have a lifetime history of regularly injecting heroin. Optimal prevention and treatment outcomes can only occur through a comprehensive understanding of the interrelations between different substances of abuse.

Latent classes of heroin and cocaine users predict unique HIV/HCV risk factors.

BACKGROUND: Patterns of heroin and cocaine use vary and may be associated with unique risk factors for bloodborne infections. METHODS: Latent class analysis identified sub-populations of 552 heroin and cocaine users in Baltimore, Maryland. Using latent class regression, these classes were analyzed for associations with demographic characteristics, risky behaviors, Hepatitis C, and HIV. RESULTS: Three classes were found: Crack/Nasal-Heroin users (43.5%), Polysubstance users (34.8%), and Heroin Injectors (21.8%). Compared to Polysubstance users, Crack/Nasal-Heroin users were almost 7 times more likely to identify as Black (OR=6.97, 95% CI=4.35-11.2). Sharing needles was over 2.5 times more likely among Polysubstance users than among Heroin Injectors (OR=2.66, 95% CI=1.49-4.75). Crack/Nasal-Heroin users were 2.5 times more likely than Polysubstance users to exchange drugs for sex (OR=2.50, 95% CI=1.22-5.13). Crack/Nasal-Heroin users were less likely than Heroin Injectors to have Hepatitis C (OR=0.10, 95% CI=0.06-0.18), but no significant differences were found for HIV. CONCLUSIONS: Subpopulations of cocaine and heroin users differed in demographic classifications, HIV-risk behaviors, and Hepatitis C infection. All subpopulations included substantial numbers of HIV-positive individuals. Findings provide further evidence that non-injection drug users face significant infectious disease risk.