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Applying contextual integrity to digital contact tracing and automated triage for hospitals during COVID-19

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  • Martens, Marijn
  • De Wolf, Ralf
  • Vadendriessche, Karel
  • Evens, Tom
  • De Marez, Lieven

Abstract

To control and minimise the spread of COVID-19, various technological solutions have been proposed. In this research, we focus on digital contact tracing and automated triage for hospitals. We conducted an online survey in Flanders (N = 1708) to investigate the perceived appropriateness of these systems based on the Contextual Integrity framework, as developed by Nissenbaum [1]. For digital contact tracing, significant differences were found between the appropriateness of using various types of data for different goals. Precise individual location data (i.e. GPS) was considered to be least appropriate and much less appropriate than proximity data (i.e. Bluetooth) or coarser location data (i.e. GSM). Goals for digital contact tracing with a high individual impact were considered to be less appropriate than goals with a low individual or societal impact. In addition, the data showed that respondents would find the usage of digital contact tracing to be less appropriate after the pandemic, underlining the temporality of this technological solution. For automated triage, the results indicated that gender is perceived to be significantly less appropriate than the other types of data, including age, to determine the priority of treatment.

Suggested Citation

  • Martens, Marijn & De Wolf, Ralf & Vadendriessche, Karel & Evens, Tom & De Marez, Lieven, 2021. "Applying contextual integrity to digital contact tracing and automated triage for hospitals during COVID-19," Technology in Society, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:teinso:v:67:y:2021:i:c:s0160791x21002232
    DOI: 10.1016/j.techsoc.2021.101748
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    References listed on IDEAS

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    1. Zimmerling, Amanda & Chen, Xiongbiao, 2021. "Innovation and possible long-term impact driven by COVID-19: Manufacturing, personal protective equipment and digital technologies," Technology in Society, Elsevier, vol. 65(C).
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    3. Clark, L.A. & Clark, W.J. & Jones, D.L., 2011. "Innovation policy vacuum: Navigating unmarked paths," Technology in Society, Elsevier, vol. 33(3), pages 253-264.
    4. Kyle M. L. Jones & Andrew Asher & Abigail Goben & Michael R. Perry & Dorothea Salo & Kristin A. Briney & M. Brooke Robertshaw, 2020. "“We're being tracked at all times”: Student perspectives of their privacy in relation to learning analytics in higher education," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(9), pages 1044-1059, September.
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    1. Saheb, Tahereh & Sabour, Elham & Qanbary, Fatimah & Saheb, Tayebeh, 2022. "Delineating privacy aspects of COVID tracing applications embedded with proximity measurement technologies & digital technologies," Technology in Society, Elsevier, vol. 69(C).

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