Modeling prevention program effects on growth in substance use: analysis of five years of data from the Adolescent Alcohol Prevention Trial.

Abstract

The efficacy of prevention programs is typically determined through analysis of covariance. To date, a growth curve modeling approach is not used extensively in program evaluation. However, for longitudinal data there are several advantages to using this approach as compared to methods comparing means at two time points in a piecemeal fashion. In this study, latent growth curve models were used to evaluate the effect of a program on the average level of drug use, rate of change (growth) of drug use, and acceleration or deceleration in the rate of change of drug use. The study relied on data from the Adolescent Alcohol Prevention Trial, a randomized longitudinal drug use prevention program. The program consists of drug use information, resistance skills training, and normative education components. Data regarding cigarette and alcohol use were collected over a 5-year period, grade 7 to grade 11. Students receiving the normative education program had significantly lower average levels of reported cigarette and alcohol use, lower rates of growth for reported cigarette and alcohol use, and less deceleration of reported levels of cigarette and alcohol use as compared with the control group. Growth curve analysis is a powerful and effective tool with which to model change and program efficacy.