mentable by other communities. Gibbons, Hur, and colleagues (2007) have developed statistical methodology that provides some evidence in support of such interventions. Conversely, randomized control prevention trials can also inform public health practice. For example, a violence prevention trial, Aban Aya (Flay, Graumlich, et al., 2004) informed a Chicago public school violence prevention initiative with teenage mothers (Bell, Gamm, et al., 2001), which demonstrated significant reductions in pregnant teenage dropout rates. In addition, most teens had only one child despite becoming a mother at very young ages (Lamberg, 2003).

There have been clear advances in implementing effective programs since the publication of Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research (Institute of Medicine, 1994). Indeed, the knowledge base on effective prevention programs at that time was very thin. However, the levels of effective implementation are much lower than the availability of tested interventions suggests.

One of several contributors to the relative lack of implementation is lack of empirical evidence regarding how to effectively approach implementation. A critical next phase of research needs to examine methods for enhancing the implementation of effective programs. The prevention research cycle proposed in the 1994 IOM report assumes a “hierarchical scientist-as-expert perspective and portrays scientists as separate agents conducting research on ‘subjects’ and ‘groups’” (Dumka, Mauricio, and Gonzales, 2007). Although the stages of research in the model require the cooperation of individuals and organizations, the model did not specifically address the relationships and collaborative processes that are critical to accomplishing each stage (Dumka, Mauricio, and Gonzales, 2007).

For implementation to be successful, there needs to be strategic input from science, policy, and practice perspectives that builds on the scientific knowledge base. Evidence is needed on how to make implementation occur in communities, the policy directives that promote or enforce the use of evidence-based programs and data systems, and the effective adoption and sustainability of programs in practice (Greenberg, 2004). Important progress has been made, and there are now new opportunities to make partnerships between scientists, policy makers, and practitioner