Methods: Three administrative datasets were used to identify risk and protective factors of adverse youth outcomes in Colorado: 1) U.S. Census Bureau, 2) Colorado Department of Education School-View, and 3) Uniform Crime Reports. Community decision-makers used indicators from these datasets to determine whether their community had high levels of risk for adverse outcomes. Communities compared and contrasted local-level indicators with regional and state data from administrative datasets to assist their assessment and selection of risk and protective factors in their community.
Results: Communities used indicators from these datasets to understand community economic issues (n=9), student academic achievement (n=7) and connection to school (n=9), and the community’s organization to support youth development (n=8). Education, crime, and Census data will be used in ongoing evaluations to track changes in levels of risk and protection in these Colorado communities over time. CTC communities faced challenges in using these datasets, including: obtaining data at the appropriate geographic level, having the appropriate expertise to understand the complexities in the datasets, and using data to inform community decision-making.
Conclusions: Collecting risk and protective factor information through youth self-reported attitudes and behaviors is not always feasible for communities. Communities faced with this challenge struggle to identify community-level data to measure risk and protective factors. Administrative data can be used to understand risk and protective factors of adverse outcomes and support decision making and strategic action. Utilization of these datasets can result in more practitioners using a shared risk and protective factor approach to primary prevention in our communities.