GRACELYN H. CRUDEN
Public Health-Health Policy and Management, University of North Carolina at Chapel Hill
Cohort Seven Fellow
Kristen Hassmiller-Lich, PhD
Research Assistant Professor, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
President and CEO, Collaborative Health Solutions
Areas of Expertise
Systems Science, Multi-Criteria Decision Making, Prevention Science
Gracelyn is a decision scientist who is interested in applying systems science thinking and methodology to support prevention and implementation science. Specifically, she focuses on reducing child maltreatment, as well as promoting mental health and reducing substance misuse across the life course.
Her primary line of research includes working with community stakeholders to understand how local context can influence the implementation and effectiveness of evidence-based interventions to prevent child neglect and to promote protective and healthy communities.
Group Model Building for Evidence Based Prevention Program Selection in North Carolina to Prevent Child Maltreatment
This dissertation aims to increase decision makers’ ability to understand the factors that influence child maltreatment and well-being, and choose the interventions that will have the greatest impact on preventing adverse childhood outcomes in their communities. Decision makers desire more information on how to choose evidence-based programs and how to adapt programs for their communities.1,2 I hypothesize that choosing evidence based programs informed by a systems science model developed with stakeholders will lead to greater population health impact and more efficient resource allocation. First, Community Health Assessments in North Carolina will be reviewed to understand what risk factors are prioritized, how they are targeted for intervention, and to develop causal loop diagrams. Next, I will use a Group Model Building approach to build a system dynamics model that characterizes the complex factors affecting child well-being. Finally, I will use the model to simulate the potential effects of preventive evidence-based programs.