Project IMPROVE, which is funded by the Office of Family Assistance (OFA), is a training and technical assistance resource for TANF programs interested in improving outcomes for low-income families. Under contract with OFA, Mathematica Policy Research works in partnership with state and local TANF agencies using the Learn, Innovate, Improve (LI2) process to execute collaborative, evidence-informed program change. LI2 was developed by Mathematica in partnership with the Center on the Developing Child at Harvard University with support from the Administration for Children and Families, Office of Planning, Research and Evaluation. This process has been or is being used in dozens of TANF and workforce agencies across the country to design, implement, and test innovative strategies to improve program performance and client outcomes.

This OFA-sponsored webinar on October 26th from 1:00 - 2:30 p.m. EST provided an overview of the LI2 process, drawing upon recent examples of how it has helped large and small, urban and rural TANF programs make targeted improvements and manage change. We highlighted innovations that have emerged from TANF programs using this process. Presenters included Michelle Derr and Jonathan McCay from Mathematica Policy Research, Dena Jardine from the Larimer County Workforce Center in Colorado, and Noelle Simmons from the San Francisco Human Services Agency.

This brief from the Aspen Institute’s Expanding Prosperity Impact Collective examines how income volatility affects outcomes for hourly service sector employees. The researchers conducted quantitative analysis using the Retail Work and Family Life survey, and they also included 25 in-depth interviews with San Francisco-area parents working in retail or food service. Half of workers employed at the largest 30 retail and fast food companies reported that their income varied from week to week. Workers with variable schedules were more likely to report weekly income volatility than those who worked a regular day shift. Weekly income volatility was also more likely to lead to financial hardship and difficulty paying bills. The authors recommend six solutions to reduce income volatility, including predictable scheduling, wage insurance, and unemployment insurance.

This report from the U.S. Department of Health and Human Services, Administration for Children and Families, Office of Planning, Research and Evaluation details the implementation and early impacts of the Bridge to Employment in the Healthcare Industry Program in San Diego. The San Diego Workforce Partnership (SDWP) used an Individual Training Account (ITA) model to help low-income individuals pay for training in the healthcare industry. Using funding from the Health Profession Opportunity Grant, SDWP contracted with three local organizations that operated the program in different areas of San Diego. The program included assessment, case management, ITAs, employment services, and support services, such as transportation, child care, and temporary housing. Early findings showed that participants who received the ITA and support services were more likely than the control group to participate in health care training, receive a credential, and work in a health care job.

Mathematica Policy Research issued three new briefs to document lessons learned from implementing the Personal Responsibility Education Program (PREP), which educates youth on abstinence and contraception. These briefs are part of a multi-component evaluation on PREP that Mathematica is conducting for the U.S. Department of Health and Human Services, Administration for Children and Families. One brief focuses on a teen pregnancy prevention program in rural Kentucky, another details a boys-only teen pregnancy prevention program in Iowa, and the third brief examines how California, Maine, Pennsylvania, and South Carolina developed infrastructure to support PREP programming. Each brief includes findings on how PREP implementation differed at each site.

This report from the Office of Planning, Research and Evaluation presents early findings from a random assignment evaluation of subsidized employment for TANF participants in Los Angeles County. The report analyzes the impact of two approaches to subsidized employment: paid work experience and on-the-job training.

This report presents interim impact and implementation findings of seven transitional jobs programs from the U.S. Department of Labor’s Enhanced Transitional Jobs Demonstration. Two of the sites in that study — in Atlanta and San Francisco — are also a part of ACF’s Subsidized and Transitional Employment Demonstration. The two studies closely coordinated beyond the shared sites, including shared reports, common data collection instruments, and other ongoing collaboration.

The report shares early results in the areas of implementation, employment outcomes, recidivism, and child support payment.

Early results include:

• The Enhanced Transitional Jobs Demonstration programs were relatively well implemented.
• All but one of the programs generated large increases in employment in the early months of follow-up; however, these increases were mostly or entirely the result of the transitional jobs and faded as participants left those jobs.
• Two of the three programs targeting people recently released from prison appear to have reduced recidivism.
• Most programs increased payment of child support. (Author abstract)

This report documents the implementation infrastructure of Personal Responsibility Education Program evidence-based teen pregnancy prevention programs in four states--California, Maine, Pennsylvania, and South Carolina. Analysis of the programs implementation infrastructure showed that the four states differed in size; the role grantees took in supporting implementation, resources, and the settings in which the program operated. Despite that, states had similarities in how they:

• worked with providers before and in the early stages of implementation;
• formed a pool of qualified trainers to train program facilitators and provide ongoing technical assistance;
• went beyond federal performance measures requirements; and
• established communication and feedback loops to facilitate data gathering, data sharing, and identification of lessons learned. (author abstract)