Youth

This project developed a calculator to help people anticipate how a change in earnings from employment would affect their net income, and in so doing, provide public benefit recipients with their estimated effective marginal tax rate on new earnings. Key Points:

This brief presents considerations for program administrators and other practitioners around increasing the use of primary prevention in human services systems to shift from responding to families after they are in crisis to preventing the crisis before it occurs.

This brief provides key considerations for policy designers and funding partners—such as federal staff, technical experts, and philanthropic partners—on incorporating primary prevention into human services delivery.

This brief highlights a new way of delivering primary prevention services that promotes equity by relying on the guidance and leadership of people with lived experience. The policy designers and service providers behind prevention services should have lived experience and/or co-create these services with people who do.

This Issue Brief presents current estimates of enrollment in health insurance coverage obtained through the Affordable Care Act (ACA) Marketplaces, Medicaid expansion, Children's Health Insurance Program, Basic Health Program and the subsequent reductions in state-level uninsured rates since the ACA was implemented in 2014.

This brief highlights key themes and ideas from a Health and Human Services (HHS) Convening on Advancing Primary Prevention in Human Services in August 2022. With a particular focus on prevention of youth and family homelessness, the convening featured the perspectives of academic experts, program administrators, federal colleagues, and people with lived expertise.

This brief explores important trends in the child care industry during the first two years of the COVID-19 pandemic and places those trends in a historical context. Specifically, we find:

Methodological Description

This brief presents estimates of the number and percentage of children whose parents engage in problematic substance use, including past-year substance use and SUD by substance type and child demographics. Key findings include:

In recent years several researchers and child welfare agencies have begun developing predictive risk models to support child welfare decision-making. Predictive analytics is a sophisticated form of risk modeling that uses historical data to understand relationships between myriad factors to estimate a probability score for the outcome of interest.