This collection was produced as part of the project, “A ‘Big Data’ Approach to Understanding Neighborhood Effects in Chronic Illness Disparities.” The Investigators for the project are Tiffany Veinot, Veronica Berrocal, Phillipa Clarke, Robert Goodspeed, Daniel Romero, and VG Vinod Vydiswaran from the University of Michigan. The study took place from 2015-2016, with funding from the University of Michigan’s Social Sciences Annual Institute, MCubed, and the Sloan and Moore Foundations.
Contact: Tiffany Veinot, MLS, PhD
Office: 3443 North Quad
Today’s Information and Communication Technologies (ICTs) support job searches, resume creation and the ability to highlight employment skills on social media. However, these technological tools are often tailored to high-income, highly educated users, and white-collar professionals. It is unclear what interventions address the needs of job seekers who have limited resources, education, or who may be underserved in other ways. We gathered insights from past literature and generated ten tangible design concepts to address the needs of underserved job seekers. We then conducted a needs validation and speed dating study to understand which concepts were most viable among our population. We found that the three most preferred concepts immediately addressed job seekers’ most practical needs. and Per reviewer feedback, we aim to improve the utility of this publication to other scholars by including our research materials here. This dataset includes the interview script, storyboards that were used in the needs validation study, the demographics survey/questionnaire, and the consent form.