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The latent growth model (LGM) has drawn increasing attention in behavioral studies using longitudinal data. The LGM captures the level and trajectory of behavior change, variation in both the initial status and the trend of behavior change, as well as the time-ordered covariation between the initial status and change. This study demonstrates how the LGM can be applied in the evaluation of intervention programs targeting HIV risk behavior among drug users. Multigroup piecewise latent growth models were fit to longitudinal data with three repeated response measures.

Research focusing on active users of crack cocaine and how they interact with the health care system—drug abuse treatment in particular—is a new area of inquiry. Much of what is known about the problems associated with the use of crack comes from short-term studies. This article describes implementation and methodological issues related to conducting health services research with a natural history orientation among a population of active crack cocaine users (n = 444) in Dayton and Montgomery counties in Ohio. Data from this study can help define what addiction to crack really means as well as ways to prevent and treat it.