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The design and evaluation of a nudge‐based interface to facilitate consumers' evaluation of online health information credibility

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  • Yan Zhang
  • Jiaying Liu
  • Shijie Song

Abstract

Evaluating the quality of online health information (OHI) is a major challenge facing consumers. We designed PageGraph, an interface that displays quality indicators and associated values for a webpage, based on credibility evaluation models, the nudge theory, and existing empirical research concerning professionals' and consumers' evaluation of OHI quality. A qualitative evaluation of the interface with 16 participants revealed that PageGraph rendered the information and presentation nudges as intended. It provided the participants with easier access to quality indicators, encouraged fresh angles to assess information credibility, provided an evaluation framework, and encouraged validation of initial judgments. We then conducted a quantitative evaluation of the interface involving 60 participants using a between‐subject experimental design. The control group used a regular web browser and evaluated the credibility of 12 preselected webpages, whereas the experimental group evaluated the same webpages with the assistance of PageGraph. PageGraph did not significantly influence participants' evaluation results. The results may be attributed to the insufficiency of the saliency and structure of the nudges implemented and the webpage stimuli's lack of sensitivity to the intervention. Future directions for applying nudges to support OHI evaluation were discussed.

Suggested Citation

  • Yan Zhang & Jiaying Liu & Shijie Song, 2023. "The design and evaluation of a nudge‐based interface to facilitate consumers' evaluation of online health information credibility," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(7), pages 828-845, July.
    • Handle: RePEc:bla:jinfst:v:74:y:2023:i:7:p:828-845
    DOI: 10.1002/asi.24759
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    References listed on IDEAS

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    1. C. Nadine Wathen & Jacquelyn Burkell, 2002. "Believe it or not: Factors influencing credibility on the Web," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(2), pages 134-144.
    2. Yan Zhang & Yalin Sun & Bo Xie, 2015. "Quality of health information for consumers on the web: A systematic review of indicators, criteria, tools, and evaluation results," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(10), pages 2071-2084, October.
    3. Yan Zhang & Ramona Broussard & Weimao Ke & Xuemei Gong, 2014. "Evaluation of a scatter/gather interface for supporting distinct health information search tasks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 1028-1041, May.
    4. Marcia J. Bates, 1999. "The invisible substrate of information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(12), pages 1043-1050.
    5. Miriam J. Metzger, 2007. "Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(13), pages 2078-2091, November.
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    Cited by:

    1. Xue, Xiang & Ma, Haiyun & Zhao, Yuxiang (Chris) & Zhu, Qinghua & Song, Shijie, 2024. "Mitigating the influence of message features on health misinformation sharing intention in social media: Experimental evidence for accuracy-nudge intervention," Social Science & Medicine, Elsevier, vol. 356(C).

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