Detecting selection effects in community implementations of family-based substance abuse prevention programs.

Abstract

To calculate valid estimates of the costs and benefits of substance abuse prevention programs, selection effects must be identified and corrected. A supplemental comparison sample is typically used for this purpose, but in community-based program implementations, such a sample is often not available. We present an evaluation design and analytic approach that can be used in program evaluations of real-world implementations to identify selection effects, which in turn can help inform recruitment strategies, pinpoint possible selection influences on measured program outcomes, and refine estimates of program costs and benefits. We illustrate our approach with data from a multisite implementation of a popular substance abuse prevention program. Our results indicate that the program's participants differed significantly from the population at large.