Although prevention scientists have documented effective interventions to prevent adult substance abuse, antisocial behavior, and risky sexual behavior, these interventions have not been applied to optimize return on investment and thus have not yet been fully embraced by communities. This application proposes to map the relations between early risk profiles (and preventive intervention) and adult health and financial outcomes. Past studies have estimated these relations with regression coefficients that satisfy scholars but provide insufficient information to enable practitioners and policy makers to target children for intervention by age and risk profile. The proposed studies will identify the government service outcomes and financial costs associated with various risk profiles by age and the likely return on investment for the Fast Track intervention, which has been documented to prevent antisocial behavior and substance use problems. We propose interviews and administrative data collection at ages 30-34 with participants in each of two ongoing longitudinal studies that have followed children with detailed measurement of risk factors from kindergarten into adulthood, the Child Development Project (n=585, retention=90%) and the Fast Track randomized controlled trial (n=1199, retention=81%). We will pursue three aims: 1) Model the relation between early risk and adult health outcomes at different levels, qualities, and ages of risk, to identify optimal intervention timing and targets; 2) Map the relation between risk profile and adult service utilization and ultimate public costs in adulthood, to monetize the possible returns on prevention investment; and 3) Evaluate the impact of the Fast Track intervention on adult health and financial outcomes, by subgroups. The findings will provide a template for an emerging Science of Investing in Children to improve public health and protect public resources.
This project will follow participants in two prospective studies (Child Development Project and Fast Track) through age 34 in order to identify early childhood risk profiles for antisocial behavior, substance abuse, and risky sexual behavior with high enough detail to guide prevention programmers. Analyses will evaluate the impact of random assignment to the Fast Track Prevention Program on adult health, well-being, and financial burden.
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