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Applying Behavioral Science to Child Support: Building a Body of Evidence.

Publication Year: 
2016
Corporate Author: 
MDRC.
Center for Applied Behavioral Science.
Briefing Materials
Page Count: 
3

The federal government created the child support program in the 1970s to secure financial and medical support for children whose parents live separately. Today, the program collects $32 billion per year in child support payments and serves more than 16 million children and families. Still, about 35 percent of child support obligations go unpaid each month. Parents who do not pay often lack the ability to do so, due to unemployment, disability, incarceration, or other (sometimes multiple) barriers. These parents leave a significant amount of child support unpaid, and collecting that support would help scores of families and children. What stops child support agencies from reaching the parents who need them most? And when they do reach them, why aren’t more parents following through to get help? One explanation lies in the patterns of human behavior. When human service agencies provide a slew of information, options, and obligations to their customers — often in the form of dense legal packets — their customers may not be able to make sense of it all. This is especially true if the customer has a low level of education or is under stress. Breaking down that information into simpler parts can go a long way toward improving a customer’s understanding of the agency’s processes and services, which may lead the customer to take full advantage of them, according to research in behavioral science. To explore further the potential of behavioral science to improve social programs, the federal government’s Administration for Children and Families (ACF) has launched some of the broadest and most rigorous applied behavioral science projects. MDRC's Center for Applied Behavioral Science is leading evaluation and technical assistance for these projects. This Issue Focus is a discussion of some of their findings from their research so far. (Author abstract modified)

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