Health Data Visualization Literacy Skills of Young Adults with Down Syndrome and the Barriers to Inference-making

Author:

Wood Rachel1ORCID,Feng Jinjuan Heidi2ORCID,Lazar Jonathan1ORCID

Affiliation:

1. University of Maryland, College Park, USA

2. Towson University, Towson, USA

Abstract

As health management becomes more intertwined with data, an individual’s ability to read, interpret, and engage with personal health information in data visualizations is increasingly critical to one’s quality of care. People with Down Syndrome already experience greater health disparities than their typically developing peers. Inaccessible health information and technologies have the potential to magnify inequities further. Inaccessible health data can be an additional barrier to people with Down Syndrome’s ability to adopt and use health systems or devices, make informed decisions about their bodies, and advocate for themselves in health contexts. By examining their underlying data visualization literacy skills, our exploratory study involving ten young adults with Down Syndrome identifies several design opportunities to improve the accessibility of health data visualizations (HDVs) by addressing the cascade of negative effects caused by inference-making barriers in HDVs.

Funder

University of Maryland “Grand Challenges” funding for the Maryland Initiative for Digital Accessibility

Dr. Joan Giesecke Health Informatics Fellowship

Google’s Award for Inclusion Research

National Institute on Disability, Independent Living, and Rehabilitation Research

Publisher

Association for Computing Machinery (ACM)

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