Code for America highlights the importance of recognizing the effects of intergenerational trauma on communities that have been systemically marginalized when conducting research.
Eligible people struggle to maintain their case status for critical safety net services, often due to administrative hurdles and poor communication. Code for America piloted text message reminders to support Louisianans, which helped clients avoid costly churn. Text messages are an underrated, efficient solution for human service agencies to meet client expectations and improve case outcomes.
The Decide Methods help you derive insights from the information gathered during the Discovery phase. You’ll validate initial assumptions, develop a deeper understanding of workflows and processes, and develop design hypotheses.
The ubiquity of mobile devices makes it imperative to build “mobile first” services, i.e. services built with the expectation that they will primarily be accessed on mobile devices. This article also outlines important considerations and suggestions for implementing mobile-first user interfaces.
This landscape analysis examines data, design, technology, and innovation-enabled approaches that make it easier for eligible people to enroll in, and receive, federally-funded social safety net benefits, with a focus on the earliest adaptations during the COVID-19 pandemic.
Well-designed, user-focused tools that allow for simple application are key to ensuring that families most in need receive the Child Tax Credit. Reaching these households will require a robust effort from the IRS to create user-friendly tools in partnership with organizations with a direct connection to eligible recipients.
Code for America offers government agencies a general overview of getting started with implementing text messaging services for clear, responsive communication during the COVID-19 pandemic.
Code for America partnered with the CBPP, Civilla, and Nava to launch the Integrated Benefits Initiative, testing and piloting human-centered approaches to improve outcomes and learn what an optimal safety net could look like. This article describes key takeaways from short-term pilots implemented as part of this project.
Applying UX research methods, the City of San Jose worked to improve how low-income and non-English speaking residents engaged with My San Jose, a website and mobile app for residents to report neighborhood issues to cities. They used a Spanish and Vietnamese translator to conduct interviews with target users, then detailed major findings and corresponding recommendations in this report.
Describes the Principles of a Human-Centered Safety Net: Many Welcoming Doors, Easy to Understand, Clients Can Make Informed Decisions, Responsive to Changing Needs, Simple Actions
