Panel Paper:
Cutting through Complexity: Using Behavioral Science to Help Parents Choose Quality Child Care in Indiana
Friday, November 9, 2018
Wilson B - Mezz Level (Marriott Wardman Park)
*Names in bold indicate Presenter
This paper describes a collaboration between researchers and the agencies responsible for administering and supporting the Indiana’s Child Care and Development Fund (CCDF) program. The research team used a method called “behavioral diagnosis and design” to review the existing processes and identify potential obstacles—or “bottlenecks”—to desired outcomes. The first test focused on the decisions about child care providers made by low-income families enrolling in CCDF to receive child care subsidies. The research team replaced the letter and brochure typically sent to parents on the CCDF waitlist with a personalized list of quality-rated child care providers close to the parent’s home. Some parents also received a proactive phone call from the state’s child care resource and referral agency. The researchers used a three-arm randomized controlled trial to evaluate (1) the referral list, and (2) the referral list plus phone call compared with the state’s existing outreach (total sample size=12,652 children). The study found that parents who received the intervention close to when they signed up for the waitlist were more responsive to the interventions than those who received the intervention after being on the waitlist for weeks. Receiving the referral list combined with a phone call increased the percentage of families who chose the highest-rated, Level 4 providers, and receiving just the referral list decreased the percentage of families who chose the lowest-rated Level 1 providers. There was no statistically significant change in the share of CCDF families who chose any quality-rated provider. This study demonstrates the power of timing, and a personal touch in helping low-income parents make child care choices, and highlights important areas for future research.
Full Paper:
- MDRC_Cutting_through_Complexity_FR.pdf (1208.5KB)
