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Contextualizing Visualizations of Digital Health Information among Young and Older Adults Based on Eye-Tracking

Author

Listed:
  • Kaifeng Liu

    (Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China)

  • Pengbo Su

    (Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China)

  • Hailiang Wang

    (School of Design, The Hong Kong Polytechnic University, Hong Kong)

  • Da Tao

    (Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518061, China)

Abstract

Visualizations have been found to be a promising solution to aid individuals’ comprehension of digital health information. However, how visualizations can be better contextualized remains unclear. This study aimed to examine the effects of visualizations of digital health information with various contextual cues and age on comprehension through eye-tracking techniques. A two-way mixed design was employed, with visualization (basic, color, color + text, and color + text + personalized statement) and age (young and older adults) as independent variables. Forty-one participants attended an experiment where they were asked to perform verbatim comprehension and value interpretation tasks in response to varied visualizations of digital health information. The results indicated that the four visualizations yielded comparable task completion time and accuracy. Older adults had longer task completion time and more errors compared with their counterparts. While eye movement measures were comparable across different visualizations, they were mostly affected by age and areas of interests. Different visualizations might attract different patterns of visual attention and yield varied effectiveness across age groups. Future research should focus on how to better visualize digital health information for older adults. Design practitioners should carefully consider how to attract patients’ visual attention to important information to improve comprehension.

Suggested Citation

  • Kaifeng Liu & Pengbo Su & Hailiang Wang & Da Tao, 2022. "Contextualizing Visualizations of Digital Health Information among Young and Older Adults Based on Eye-Tracking," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16506-:d:998592
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    References listed on IDEAS

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    1. Hailiang Wang & Jiaxin Zhang & Yan Luximon & Mingfu Qin & Ping Geng & Da Tao, 2022. "The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors," IJERPH, MDPI, vol. 19(17), pages 1-17, August.
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