Evaluation of HIV risk reduction intervention programs via latent growth model

Abstract

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. Multi-group piecewise latent growth models were fit to longitudinal data with three repeated response measures.