Patterns and predictors of cocaine and crack use by clients in standard and enhanced methadone maintenance treatment.

This paper reports on the patterns of cocaine use among subjects (N = 427) admitted to a methadone maintenance treatment demonstration project designed to reduce risk for HIV. Assessments were conducted at intake and at approximately 18-24 months after treatment admission. Self-reported data on cocaine use was compared with results of urinalysis tests at both intake and follow-up; 29 subjects who falsely reported no use were recorded as users. Over one-third used some form of cocaine at both intake and follow-up, while approximately 30% abstained at both points. Approximately 20% ceased as well as initiated cocaine use between intake and follow-up. Use of powder cocaine, either alone or combined with heroin in "speedballs," decreased at follow-up, whereas crack use increased. Discriminant function analyses were performed to determine the predictors of the different patterns of cocaine use by type. Receipt of enhanced methadone treatment compared with standard methadone treatment, treatment duration, or average duration of counselor contact appeared unrelated to cocaine use. Cocaine use at follow-up was associated with polydrug and alcohol use, illegal activity, a negative emotional state, and sex work. Crack users were more likely to be African American than nonusers; continuous users of powder cocaine were more likely to also be using heroin than were nonusers; and continuous speedball users were more likely to be women sex workers with high levels of depression. This analysis demonstrated that cessation or continuation of cocaine use after entry into methadone maintenance treatment is not uniform across different types of cocaine.

Cocaine and crack use and HIV risk behaviors among high-risk methadone maintenance clients.

A discriminant function analysis was performed with data from 409 high-risk heroin addicts at intake into a methadone maintenance treatment program to determine the characteristics of cocaine users. Cocaine users presented a higher-risk profile for human immunodeficiency virus (HIV), engaged in a wider variety of criminal activities, were more likely to be African-American, reported more alcohol use, and showed more signs of psychological disturbance. A second discriminant function analysis determined that crack smokers differed from non-crack cocaine users in ethnicity, alcohol use, criminal activity, needle use, and marital status. Heroin addicts who use cocaine, in particular crack, represent a sub-group at higher risk and in need of targeted treatment planning and monitoring.

Reasons for discharge from methadone maintenance for addicts at high risk of HIV infection or transmission.

This article reports on a methadone maintenance program that had the goal of retaining in treatment heroin addicts at high risk of HIV infection and/or transmission. Subjects were recruited from four-high-risk target groups and randomly assigned to either an enhanced or standard methadone maintenance group. The analysis examined predictors of any type of discharge, negative discharge, and circumstantial discharge. Discharge for any reason was more likely for younger individuals, sex industry workers, and high-risk sex partners. Legal supervision at intake and coercion into treatment reduced the probability of discharge for any reason. HIV-positive individuals were more likely to discharge for circumstantial reasons than negative reasons. The probability of circumstantial discharge was increased for males, individuals reporting suicidal ideation, and those scoring higher on an impulse expression scale. The likelihood of circumstantial discharge was decreased for individuals who reported more sources of legal income or who lived someone using illegal drugs. Participation in the enhanced treatment group appeared to reduce the probability of negative, compared with circumstantial, discharge. The findings should assist methadone treatment providers in targeting individuals at high probability of discharge for special efforts to increase treatment retention and to reengage them back into treatment after discharge, as part of a harm-reduction strategy to minimize risks of HIV infection and/or transmission.

Goodness-of-Fit Testing for Latent Class Models.

Latent class models with sparse contingency tables can present problems for model comparison and selection, because under these conditions the distributions of goodness-of-fit indices are often unknown. This causes inaccuracies both in hypothesis testing and in model comparisons based on normed indices. In order to assess the extent of this problem, we carried out a simulation investigating the distributions of the likelihood ratio statistic G(2), the Pearson statistic ⊃(2), and a new goodness-of-fit index suggested by Read and Cressie (1988). There were substantial deviations between the expectation of the chi-squared distribution and the means of the G(2) and Read and Cressie distributions. In general, the mean of the distribution of a statistic was closer to the expectation of the chi-squared distribution when the average cell expectation was large, there were fewer indicator items, and the latent class measurement parameters were less extreme. It was found that the mean of the χ(2) distribution is generally closer to the expectation of the chi-squared distribution than are the means of the other two indices we examined, but the standard deviation of the χ(2) distribution is considerably larger than that of the other two indices and larger than the standard deviation of the chi-squared distribution. We argue that a possible solution is to forgo reliance on theoretical distributions for expectations and quantiles of goodness-of-fit statistics. Instead, Monte Carlo sampling (Noreen, 1989) can be used to arrive at an empirical central or noncentral distribution.

Modeling transitions in latent stage-sequential processes: a substance use prevention example.

This article illustrates the use of latent transition analysis (LTA), a methodology for testing stage-sequential models of individual growth. LTA is an outgrowth of latent class theory and is a particular type of latent Markov model emphasizing the use of multiple manifest indicators. LTA is used to compare the fit of two models of early adolescent substance use onset and to assess the effects of a school-based substance use prevention program on Ss measured in 7th grade and again in 8th grade. Several interesting findings emerged. First, a model of substance use onset including both alcohol and tobacco use as possible starting points fit better than a model that included alcohol use as the only starting point. Second, Ss who had tried tobacco but not alcohol in in 7th grade seemed to be on an accelerated onset trajectory. Third, the normative education prevention program was generally successful, except for the students who had tried only tobacco in 7th grade.