Abstract

In this paper, we discuss and illustrate an innovative multi-faceted prevention research model, relevant to the full range of social and health problems experienced by global communities. The difficulty of directly observing the outcome of prevention efforts on health and social problems has limited the potency of traditional experimental and quasi-experimental social science research and thus efficacious, empirically grounded practice strategies. However, because prevention efforts are geographically situated, contemporary statistical modeling methods and geospatial inquiry delimited to local communities provide the tools through which to develop models that consider economic resources, the built environment, behavioral patterns, and social and human capital. <p> These models can be statistically manipulated to predict the relationships between social and health problem prevalence and the availability, proximity and nature of prevention resources in a geographic area. This modeling technique therefore has the capacity to identify unmet prevention needs systematically, economically and expediently, and to predict the outcomes of realigning prevention resources tailored to local areas without expending money on unknown and untested initiatives.</p>