Evaluation of longitudinal intervention effects: An example of latent growth mixture models for ordinal drug-use outcomes

Heterogeneity often exists among behavioral growth trajectories in a study population. In the evaluation of intervention effects for longitudinal randomized trials, it is informative to examine the impact of an intervention on subgroups characterized by different types of growth trajectories. This paper presents an application of growth mixture modeling to an ordinal-scale substance-use behavior outcome from the Aban Aya Youth Project (AAYP), a longitudinal preventive intervention trial targeting health-compromising behaviors among adolescents. Results suggested two classes of adolescent substance use growth trajectories: Class 1 (44.7% of the sample) started at a higher level and had a relatively shallow increase over time; Class 2 had a lower baseline level and a rapid increase over time. The intervention effectively reduced the rapid increase of substance use for the adolescents in the second class.