Abstract for:Supporting the Selection of Evidence Based Interventions to Prevent Child Neglect for Community Implementation
The purpose of this study was to develop an evidence-based system dynamics model for decision makers to compare the effectiveness and limits of child neglect prevention programs. Utilizing a Group Model Building informed approach, we developed a learning model that simulated the effects of three GMB prioritized evidence-based prevention interventions: Nurse Family Partnership, Incredible Years, and SafeCare. Simulation experiments will suggest key risk and protective factors that should prioritized for intervention at the family and county level, as well as provide insight around factors for which the greatest uncertainty remains. The GMB process and early simulations suggest that some key leverage points include parent trauma, peer support, parental depression and substance misuse, and newborn births. This model is unique in its focus on interpersonal family factors as well as environmental factors that lead to child neglect, as previous system dynamics models have primarily focused on dynamics such as foster care placement and claim substantiation. Second, this model is unique in modeling the impact of discrete evidence-based prevention interventions with behavioral components, and thus tackles important methodological changes while identifying knowledge gaps. Finally, this learning model can aid decision makers as they are trying to understand the system around child neglect.