Validating a Predictive Risk Model for Child Abuse and Neglect With Adolescent Outcomes

INTRODUCTION: A predictive risk model (PRM) was trained to stratify risk among children investigated for alleged maltreatment based on the likelihood of future child protection involvement. In the current brief, we assess the model's ability to differentiate risk of adverse events not used to build the model (i.e., arrest, death) among adolescent populations investigated following reported maltreatment to guide prevention-oriented services. METHODS: Child welfare and vital statistics records were obtained through a data use agreement. Among adolescents born in 2000 and 2001 and investigated for alleged maltreatment between ages 11 and 17 (n = 72,340), risk scores were calculated using a random forest algorithm based on information available at the time of maltreatment report. The records of these adolescents were then linked to arrest and death records. RESULTS: Among adolescents investigated for maltreatment, 5.8% experienced a juvenile arrest or death before age 21. Of those who experienced an arrest or death, 43.9% fell in the highest risk decile. CONCLUSIONS: A PRM trained to predict foster care placement had strong external validity in predicting both future arrests and deaths. The average time from investigation to adverse event indicates a meaningful window for interventions to be delivered focused on supporting and stabilizing adolescents and their families.