Case management is a service delivery approach in which staff meet with clients to provide direct, personalized one-on-one support to improve a comprehensive set of outcomes related to employment, education, housing, health, and public benefit receipt. This Office of Planning, Research and Evaluation resource describes the effectiveness of programs that were identified by the Pathways Clearinghouse as using case management as their primary service. It summarizes what we know about these programs and their impacts so Temporary Assistance for Needy Families (TANF) and other program administrators, policymakers, researchers, and the public can apply the evidence to their context and the questions that matter to them.

This Journal of Economics and Political Economy study applies the multidimensional digital inequality framework to analyze the complex ways in which digital access varies among low-income populations. This research specifically examines the results of digital skills training for individuals receiving Temporary Assistance for Needy Families benefits and how it shapes their Internet use as well as returns of use. The research shows the importance of the multidimensional nature of digital inequality, focusing on how access and use of digital technologies varies among individuals with formal digital literacy skills training. Findings from the research offer insight into the need for additional technological investments and multistakeholder engagement.

State and local leaders at Temporary Assistance for Needy Families (TANF) agencies have been increasingly focused on using administrative data from TANF and other agencies to better assess how well programs are working, inform policies and practices, and improve the lives of families with low incomes. Economic mobility through employment retention and advancement is of particular interest to TANF leaders, but administrative data on TANF recipients’ earnings are often difficult to access except for the purpose of investigating noncompliance. This MDRC toolkit was created to help TANF professionals develop more robust, data-driven practices using administrative data on earnings.

All states may choose to allocate a portion of their Temporary Assistance for Needy Families (TANF) dollars to support fatherhood work. Despite this funding opportunity, very few states have taken advantage of it. States may have other priorities for the use of their TANF dollars, decision makers may not be aware of all the benefits of father involvement for child wellbeing, or TANF program leaders may have limited knowledge about the components of fatherhood programs and how to start/maintain fatherhood programming. This National Responsible Fatherhood Clearinghouse spotlight demystifies the process for using TANF funds to support fatherhood programming and looks at how Ohio has used their state TANF funds to support father-related services through the Ohio Commission on Fatherhood (OCF). The spotlight details the history of how OCF was established, how it works to meet four specific goals, and how its work throughout the state addresses two of the four purposes of the TANF legislation.

March is Women’s History Month and this Office of Planning, Research and Evaluation (OPRE) resource highlights women’s roles in human services programs and shares OPRE’s projects that are helping to build evidence on the human services workforce. The resource includes early care and education, home visiting, head start, and Temporary Assistance for Needy Families.

Government agencies collect administrative data in their day-to-day activities, primarily to support program operations. This information is used less often as a research tool or fully harnessed for its evidence-building potential. ACF’s TANF Data Innovation (TDI) project supported innovation and efficiency within the TANF program by expanding its use of its administrative data. This Office of Planning, Research and Evaluation brief describes TDI’s efforts to transform federal TANF and employment data into an integrated resource for program management and evidence building.

This Office of Planning, Research & Evaluation brief provides a graphical overview of some of the TANF policy differences across states and territories. It includes information about initial eligibility, benefit amounts, work and activity requirements, and ongoing eligibility and time limits. This brief is a companion to the 2022 Welfare Rules Databook.

The Office of Family Assistance podcast series, “Incorporating Lived Experiences into Decision Making,” provides insights into how TANF agencies can include and involve individuals with lived experience in receiving TANF into agency programming and policy development. The series discusses why including individuals with lived experience is important and highlights various strategies and resources agencies can use to incorporate these perspectives. This first episode explores various strategies agencies have taken to gather and use input from individuals with lived experience to benefit agencies’ understanding, decision-making, and programming. Podcast speakers discuss varying approaches, including gathering survey feedback on program operations, forming participant advisory committees, incorporating participant-led case management practices, and hiring individuals with lived experience into permanent positions. This episode also explores how to engage in lived experiences equitably, including discussions of compensating individuals appropriately for their time and expertise.

This Administration for Children and Families report provides data for fiscal year (FY) 2016 through FY 2021 and presents information regarding TANF expenditures and caseloads, work participation and earnings, the characteristics and financial circumstances of TANF recipients, TANF performance measures, interactions between TANF and child support, as well as specific provisions of state TANF programs. In addition, this report documents current family self-sufficiency and stability-related research, provides national data on non-marital births, and presents child poverty statistics.