Data from management information systems, direct observations, and the reactions of staff members can help programs understand themselves, identify areas for improvement, and set goals. This infographic presents examples of how programs in the Building Bridges and Bonds study used data from different sources to gain insights.
In NYC P-TECH Grades 9-14 schools, students take an integrated sequence of high school and college courses with the goal of completing both high school and college, while simultaneously being exposed to hands-on work experiences. This infographic describes the model and introduces MDRC’s evaluation of it.
An essential step in the child support process is delivering legal documents to the person named as a parent. This infographic summarizes results from a Georgia intervention that aimed to get parents to come in and accept documents voluntarily instead of using a sheriff or process server to deliver them.
The Center for Applied Behavioral Science (CABS) combines MDRC’s decades of experience tackling social policy issues with insights from behavioral science. This graphic explains the CABS’s approach to solving problems.
Too often, programs and policies do not consider the way people actually think and behave. Behavioral science demonstrates that even small hassles create barriers that prevent those in need of services from receiving them. This infographic provides a brief overview of how the Center for Applied Behavioral Science is improving social services by making use of behavioral insights.
The SIMPLER framework was developed for the Behavioral Interventions to Advance Self-Sufficiency (BIAS) project ― the first major effort to apply behavioral insights to human services programs in the United States. SIMPLER summarizes several key behavioral concepts that can guide practitioners interested in using behavioral insights to enhance service delivery.
As the first major effort to use a behavioral economics lens to examine human services programs that serve poor and vulnerable families in the United States, the BIAS project demonstrated the value of applying behavioral insights to improve the efficacy of human services programs.
Using an alternative to classical statistics, this paper reanalyzes results from three published studies of interventions to increase employment and reduce welfare dependency. The analysis formally incorporates prior beliefs about the interventions, characterizing the results in terms of the distribution of possible effects, and generally confirms the earlier published findings.