IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/9wz3y.html
   My bibliography  Save this paper

Americans' perceptions of privacy and surveillance in the COVID-19 Pandemic

Author

Listed:
  • Zhang, Baobao

    (Yale University)

  • Kreps, Sarah E.
  • McMurry, Nina

Abstract

As COVID-19 continues to spread, some public health authorities have implemented or plan to implement smartphone apps to supplement traditional contact tracing. These apps are more effective if a higher percentage of the public downloads and uses them. Yet fears that these apps would violate users' privacy by expanding governments' and tech companies' surveillance capacity may limit adoption. We conducted a study of American attitudes (N≈2,000) toward public health surveillance policies, focusing on smartphone contact tracing apps. We find widespread reluctance among the public: support for contact tracing apps is lower than for expanding traditional contact tracing or introducing new measures like temperature checks. Using a conjoint experiment embedded in the survey, we found that decentralized data storage increased the public's acceptance of contact tracing apps. Only a minority of respondents support the government, employers, and places of religious worship requiring smartphone users to download and use these apps. Despite partisan splits on traditional contact tracing and wearing face masks, Democrats and Republicans converge on levels of support for contact tracing apps, suggesting that bipartisan elite cues could work to augment support. Lastly, the prevalence of misunderstanding about the technology suggests that public education campaigns are needed before states deploy contact tracing apps. (Note: This paper is based on a new survey that we conducted in late June 2020. We identified a software issue that affected the results of our previous survey and fixed this problem in our new survey.)

Suggested Citation

  • Zhang, Baobao & Kreps, Sarah E. & McMurry, Nina, 2020. "Americans' perceptions of privacy and surveillance in the COVID-19 Pandemic," OSF Preprints 9wz3y, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:9wz3y
    DOI: 10.31219/osf.io/9wz3y
    as

    Download full text from publisher

    File URL: https://osf.io/download/5ebb5b4c0238a9005a336509/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/9wz3y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bamel, Umesh & Talwar, Shalini & Pereira, Vijay & Corazza, Laura & Dhir, Amandeep, 2023. "Disruptive digital innovations in healthcare: Knowing the past and anticipating the future," Technovation, Elsevier, vol. 125(C).
    2. Ioannou, Athina & Tussyadiah, Iis, 2021. "Privacy and surveillance attitudes during health crises: Acceptance of surveillance and privacy protection behaviours," Technology in Society, Elsevier, vol. 67(C).
    3. van der Waal, Nadine Elisa & de Wit, Jan & Bol, Nadine & Ebbers, Wolfgang & Hooft, Lotty & Metting, Esther & van der Laan, Laura Nynke, 2022. "Predictors of contact tracing app adoption: Integrating the UTAUT, HBM and contextual factors," Technology in Society, Elsevier, vol. 71(C).
    4. Leah Ruppanner & Xiao Tan & Andrea Carson & Shaun Ratcliff, 2021. "Emotional and financial health during COVID‐19: The role of housework, employment and childcare in Australia and the United States," Gender, Work and Organization, Wiley Blackwell, vol. 28(5), pages 1937-1955, September.
    5. Dana Naous & Manus Bonner & Mathias Humbert & Christine Legner, 2022. "Learning From the Past to Improve the Future," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(5), pages 597-614, October.
    6. Chen, Tiantian & Fu, Xiaowen & Hensher, David A. & Li, Zhi-Chun & Sze, N.N., 2024. "Effects of proactive and reactive health control measures on public transport preferences of passengers – A stated preference study during the COVID-19 pandemic," Transport Policy, Elsevier, vol. 146(C), pages 175-192.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:9wz3y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.