Understanding How Older Adults Comprehend COVID-19 Interactive Visualizations via Think-Aloud Protocol

Abstract

Older adults have been hit disproportionally hard by the COVID-19 pandemic. One critical way for older adults to minimize the negative impact of COVID-19 and future pandemics is to stay informed about its latest information, which has been increasingly presented through online interactive visualizations (e.g., live dashboards and websites). Thus, it is imperative to understand how older adults interact with and comprehend online COVID-19 interactive visualizations and what challenges they might encounter to make such visualizations more accessible to older adults. We adopted a user-centered approach by inviting older adults to interact with COVID-19 interactive visualizations while at the same time verbalizing their thought processes using a think-aloud protocol. By analyzing their think-aloud verbalizations, we identified four types of thought processes representing how older adults comprehended the visualizations and uncovered the challenges they encountered with these thought processes. Furthermore, we also identified the challenges they encountered with seven common types of interaction techniques adopted by the visualizations. Based on the findings, we present design guidelines for making interactive visualizations more accessible to older adults.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Mingming Fan

Mingming Fan is an Assistant Professor in the Computational Media and Arts Thrust and the Division of Integrative Systems and Design at The Hong Kong University of Science and Technology (HKUST) in both Guangzhou and Clear Water Bay campuses. He researches at the intersection of Human-Computer Interaction and Accessibility.

Yiwen Wang

Yiwen Wang is a graduate student in the School of Information at the Rochester Institute of Technology. She has been working with Dr. Mingming Fan on aging and accessibility research.

Yuni Xie

Yuni Xie recently graduated from the School of Information at the Rochester Institute of Technology. She has been working with Dr. Mingming Fan on aging and accessibility research.

Franklin Mingzhe Li

Franklin Mingzhe Li is a PhD student in the Human-computer interaction institute at Carnegie Mellon University. His research focuses on accessibility.

Chunyang Chen

Chunyang Chen is a lecturer (Assistant Professor) in the Faculty of Information Technology, Monash University, Australia. He received his PhD from the School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore. His research focuses on Software Engineering, Deep Learning and Human-Computer Interaction.