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Longitudinal trajectories for HIV risk were examined over 5 years following treatment among 1,393 patients who participated in the nationwide Drug Abuse Treatment Outcome Studies. Both injection drug use and sexual risk behavior declined over time, with most of the decline occurring between intake and the first-year follow-up. However, results of the application of growth mixture models for both sets of trajectories indicated that a subgroup of individuals reverted to a high-risk behavior over time, with a higher level of risk at the 5-year follow-up than their original risk level at intake. Of clients who were engaged in regular injection drug use at intake, 76% continued to inject drug at a moderate-stable or increased rate during the 5-year follow-up. [ABSTRACT FROM AUTHOR]

Drug abusers vary considerably in their drug use and criminal behavior over time, and these trajectories are likely to influence drug treatment participation and treatment outcomes. Drawing on longitudinal natural history data from three samples of adult male drug users, we identify four groups with distinctive drug use and crime trajectories during the 5 years prior to their first treatment episode. The groups' characteristics of initial treatment are compared. The trajectory groups are then included in Poisson growth curve models to predict drug use, incarceration, and employment during the 5 years following first treatment. Findings indicate that posttreatment drug use decreased and posttreatment employment increased. There was little change in posttreatment incarceration. Posttreatment trajectories for drug use, incarceration, and employment were significantly different across the four trajectory groups. [ABSTRACT FROM AUTHOR]

This article discusses the life course perspective on drug use, including conceptual and analytic issues involved in developing the life course framework to explain how drug use trajectories develop during an individual's lifetime and how this knowledge can guide new research and approaches to management of drug dependence. Central concepts include trajectories marked by transitions and social capital and turning points influencing changes. The life course perspective offers an organizing framework for classifying varying drug use trajectories, identifying critical events and factors contributing to the persistence or change in drug use, analytically ordering events that occur during the life span, and determining contributory relationships. [ABSTRACT FROM AUTHOR]

This study investigates trajectories of heroin use and subsequent consequences in a sample of 471 male heroin addicts who were admitted to the California Civil Addict Program in 1964-1965 and followed over 33 years. Applying a two-part growth mixture modeling strategy to heroin use level during the first 16 years of the addiction careers since first heroin use, the authors identified three groups with distinctive profiles: stably high-level heroin users (n = 278), late decelerated users (n = 149), and early quitters (n = 44). Study findings empirically demonstrate the chronic nature of heroin addiction and subsequent adverse consequences including mortality, mental health, and employment. [ABSTRACT FROM AUTHOR]

An introduction to the Special Issues on Longitudinal Research on Substance Abuse and Health Services for the December 2007 issue of the "Evaluation Review," is presented.

The authors analyze the pilot implementation of a statewide automated outcome monitoring system (OMS) in California, using the perspectives of substance abuse treatment providers responsible for its day-to-day operation. To gain a better understanding of changes experienced by staff and their perceptions of barriers and facilitators of implementation, they conducted 28 focus groups designed to inform midstream adjustments to the system prior to its possible roll-out. Qualitative analysis of the focus group data revealed five important factors influencing implementation: the treatment provider's ethos, the time-consuming nature of the OMS, staff buy-in, resources, and counselor and program discretion. Lessons learned underscored the importance of taking into consideration aspects of organizational change and institutional resources and infrastructure when implementing a major change such as an automated OMS. Findings might be useful to those designing and implementing similar systems or other large organizational change initiatives. [ABSTRACT FROM AUTHOR]

The present study examined a sample of 205 amphetamine and methamphetamine (A/M) abusers in drug treatment programs across Los Angeles County. Data were collected during face-to-face interviews using a natural history interview instrument. We applied a series of growth curve models to investigate treatment effects on A/M use and criminal involvement during a 36-month period (24 months before and 12 months after the referent treatment admission). The modeling results showed strong concurrent treatment effects in reducing A/M use and criminal involvement (e.g., being in treatment was associated, on average, with a decrease of 4.65 to 5.14 days of A/M use per month and of 1.74 crimes per month). A longer length of cumulative time in treatment (either within single episodes or across multiple episodes) was associated with a lower level of A/M use during the initial month of the 36-month period and with a slower rate of decreased use in subsequent months. Cumulative treatment was not associated with trajectories of the criminal measures. The study findings provide some support for treatment effectiveness in decreasing A/M use among A/M abusers treated in community treatment programs. Longitudinal models allow opportunities to reveal the dynamic relationships between treatment and outcome. [ABSTRACT FROM AUTHOR]

Matching clients to treatment has been a topic of great interest to clinicians and researchers in the field of alcohol and drug abuse. Currently, several nationwide efforts are attempting to establish central intakes in communities using computerized systems. This article includes a brief literature review to provide an assessment of the current knowledge about matching that can be used to support a matching system guided by expert knowledge. A conceptual framework for the development of an expert-guided system to be used in a central intake or referral agency is then described. A drug treatment referral system that matches drug users to appropriate treatment programs requires several interlinked components: (1) an accurate list of available programs with comprehensive descriptors characterizing the programs, including the nature and kinds of services provided," (2) an assessment instrument that can be easily and routinely administered is needed for determining clients' characteristics and needs; and (3) results of that assessment instrument are used to match clients with the most appropriate available programs according to a set of decisional guidelines, which is the most critical component of the referral system. Component-specific issues that need to be addressed in developing an expert-guided referral system are discussed. The paper concludes that an expert-guided system using profile matching, although constrained by the resources available in a community, is likely to improve client outcomes and program efficiency over the current haphazard utilization practices of unstructured referral. Development of a matching index that can predict client outcome is necessary to provide empirical directions for future research and improved practice. [ABSTRACT FROM AUTHOR]

Reliance on self-report of alcohol and drug use behavior is typical among studies of substance abusers. Few studies have compared different instruments assessing frequency of drug use over long periods of time to determine if the pattern of use is shown to be similar across measures. In this study, the UCLA Natural History Interview (NHI) and the Addiction Severity Index (ASI) were administered at three annual follow-up periods (N = 301). The temporal pattern of the trajectories of days of use assessed by the ASI and NHI are comparable (in terms of both slope and intercept) for alcohol, heroin, cocaine, methamphetamine, and marijuana use. Some discrepancies appear to arise from differences in terminology among the instruments. However, the patterns of drug use were consistent across instruments, supporting their reliability for longitudinal examination of self-reported drug use. [ABSTRACT FROM AUTHOR]

Many drug abusers do not seek help in formal treatment settings, and little is known about their resistance to treatment. In this study, we offered a treatment referral assessment to a sample of 283 drug users. Only 58 subjects (or20.5% of the sample) accepted this offer. We explored differences between those who accepted the treatment referral assessment and those who declined the opportunity. Logistic regression identified predictors of acceptance related to higher levels of severity in drug use and higher scores on a motivation and readiness scale. Among those who declined the assessment, 43.1% denied drug use, 37.3% thought their drug use was not a problem, and 16.4% expressed no interest in treatment. Further analysis showed that scores on motivation and readiness were positively related to a higher level of severity in employment problems, family problems, and drug use, and to having a history of prior treatment. [ABSTRACT FROM AUTHOR]

The purpose of this study was to document the prevalence of Human Immunodeficiency Virus (HIV) and Hepatitis C Virus (HCV) among urban and rural methadone maintenance treatment (MMT) patients and to examine differences in knowledge of HIV and HCV among this population. We compared 147 MMT patients attending urban versus rural clinics in Kunming, Yunnan, China, concerning their serostatus and knowledge of HIV and HCV. The rates of HIV and HCV seropositive status were higher among rural patients. Both urban and rural patients showed limited HIV and HCV knowledge. Recent opioid injection and geographic area were strong predictors of HIV and HCV serostatus. The lack of knowledge of HIV and HCV among both urban and rural MMT patients suggests the need to strengthen current HIV and HCV education programs in MMT clinics. In addition, prevention programs should take into consideration geographic characteristics of the target population. [ABSTRACT FROM AUTHOR]

This paper examines the arrest trajectories of adult men and women, drawn from a sample of clients admitted to substance abuse treatment. Growth mixture modeling was used to identify distinctive trajectories in arrests for men and women between ages 18 and 45. In addition, the characteristics of men and women in each of the trajectory groups were compared by gender, arrest trajectory, and the interaction of gender and arrest trajectory. Findings indicated that while the shape of the five trajectories was similar for men and women, higher percentages of men than women were in the High trajectory group (12.5% vs. 8.5%), the Moderate group (27.9% vs. 20.9%), and Slow Increase group (25.5% vs. 20.6%), with more women than men being in the Low group (34.1% vs. 27.1%). Although arrests declined as men and women aged, there did not appear to be many individuals who had terminated their criminal career by age 45. Overall, more similarities than differences were observed in the characteristics of men and women across trajectories. Additional research should examine whether the causal factors influencing arrest trajectories differ by gender. [ABSTRACT FROM AUTHOR]

During the past decade, there has been a growing interest within the field of substance abuse research and treatment in the potential relevance of a perspective of continuing care or chronic disease management (Institute of Medicine, 2006; McLellan, Lewis, O'Brien, and Kleber, 2000) and in examining patterns and processes of recovery (Hser, Huang, Chou, & Anglin, 2007; Laudet, 2007; Hser & Anglin, 2010; Moos, 2007). This expanding interest has, in turn, substantially increased attention to longitudinal analyses as a way to identify and examine patterns of substance abuse and related events and behaviors over time, as well as to predictors, correlates, and outcomes of these patterns. [ABSTRACT FROM AUTHOR]

This study investigated the influence of including a covariate and/or a distal outcome on growth mixture modeling (GMM). GMM was used to examine patterns of days of heroin use over 16 years among 471 heroin users and the relationship of those patterns to mortality (distal outcome). Comparisons were made among four types of models: without a covariate and a distal outcome (two-stage approach), with a distal outcome, with a covariate, and with a covariate and a distal outcome in conjunction with three different covariates. The two-stage approach and models with the inclusion of a distal outcome resulted in different conclusions when testing the impact of latent trajectory membership on the distal outcome. Differences in membership classifications between unconditional and conditional models were mainly determined by two factors: (1) the associations of the trajectories with the covariate and the distal outcome, and (2) the distribution of the covariate in the study sample. [ABSTRACT FROM AUTHOR]

The growth curve modeling (GCM) technique has been widely adopted in longitudinal studies to investigate progression over time. The simplest growth profile involves two growth factors, initial status (intercept) and growth trajectory (slope). Conventionally, all repeated measures of outcome are included as components of the growth profile, and the first measure is used to reflect the initial status. Selection of the initial status, however, can greatly influence study findings, especially for randomized trials. In this article, we propose an alternative GCM approach involving only post-intervention measures in the growth profile and treating the first wave after intervention as the initial status. We discuss and empirically illustrate how choices of initial status may influence study conclusions in addressing research questions in randomized trials using two longitudinal studies. Data from two randomized trials are used to illustrate that the alternative GCM approach proposed in this article offers better model fitting and more meaningful results. [ABSTRACT FROM AUTHOR]

Studies examining differences in mortality among long-term drug users have been limited. In this paper, we introduce a Bayesian framework that jointly models survival data using a Weibull proportional hazard model with frailty, and substance and alcohol data using mixed-effects models, to examine differences in mortality among heroin, cocaine, and methamphetamine users from five long-term follow-up studies. The traditional approach to analyzing combined survival data from numerous studies assumes that the studies are homogeneous, thus the estimates may be biased due to unobserved heterogeneity among studies. Our approach allows us to structurally combine the data from different studies while accounting for correlation among subjects within each study. Markov chain Monte Carlo facilitates the implementation of Bayesian analyses. Despite the complexity of the model, our approach is relatively straightforward to implement using WinBUGS. We demonstrate our joint modeling approach to the combined data and discuss the results from both approaches. [ABSTRACT FROM AUTHOR]

In this article, we applied a marginal structural model (MSM) to estimate the effect on later drug use of drug treatments occurring over 10 years following first use of the primary drug. The study was based on the longitudinal data that were collected in three projects among 421 subjects and covered 15 years since first use of their primary drug. The cumulative treatment effect was estimated by the inverse-probability of treatment weighted estimators of MSM as well as the traditional regression analysis. Contrary to the traditional regression analysis, results of the MSM showed that the cumulative treatment occurring over the 10 years significantly increased the likelihood of drug use abstinence in the subsequent 5-year period. From both the statistical and empirical point of view, MSM is a better approach to assessing cumulative treatment effects, considering its advantage of controlling for self-selection bias over time. [ABSTRACT FROM AUTHOR]