Skip to main content

Privacy Attitudes and COVID Symptom Tracking Apps: Understanding Active Boundary Management by Users

  • Conference paper
  • First Online:
Information for a Better World: Shaping the Global Future (iConference 2022)


Multiple symptom tracking applications (apps) were created during the early phase of the COVID-19 pandemic. While they provided crowdsourced information about the state of the pandemic in a scalable manner, they also posed significant privacy risks for individuals. The present study investigates the interplay between individual privacy attitudes and the adoption of symptom tracking apps. Using the communication privacy theory as a framework, it studies how users’ privacy attitudes changed during the public health emergency compared to the pre-COVID times. Based on focus-group interviews (N = 21), this paper reports significant changes in users’ privacy attitudes toward such apps. Research participants shared various reasons for both increased acceptability (e.g., disease uncertainty, public good) and decreased acceptability (e.g., reduced utility due to changed lifestyle) during COVID. The results of this study can assist health informatics researchers and policy designers in creating more socially acceptable health apps in the future.

This material is in part based upon work supported by the US National Science Foundation (Grant #2027789) and National Institutes of Health.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others


  1. Agamben, G.: The State of Exception. Duke University Press, Durham (2005)

    Google Scholar 

  2. Asif, H.: Chapter 7, Privacy or utility? How to preserve both in outlier analysis. Ph.D. thesis, Rutgers University-Graduate School-Newark (2021)

    Google Scholar 

  3. Azjen, I.: Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, Bergen (1980)

    Google Scholar 

  4. Berglund, J.: Tracking COVID-19: there’s an app for that. IEEE Pulse 11(4), 14–17 (2020)

    Article  Google Scholar 

  5. Cho, H., Ippolito, D., Yu, Y.W.: Contact tracing mobile apps for COVID-19: privacy considerations and related trade-offs. arXiv preprint arXiv:2003.11511 (2020)

  6. Davis, S., Peters, D., Calvo, R., Sawyer, S., Foster, J., Smith, L.: “Kiss myAsthma’’: using a participatory design approach to develop a self-management app with young people with asthma. J. Asthma 55(9), 1018–1027 (2018)

    Article  Google Scholar 

  7. Dinev, T., Hart, P.: An extended privacy calculus model for e-commerce transactions. Inf. Syst. Res. 17(1), 61–80 (2006)

    Article  Google Scholar 

  8. Drew, D.A., et al.: Rapid implementation of mobile technology for real-time epidemiology of COVID-19. Science 368(6497), 1362–1367 (2020)

    Article  Google Scholar 

  9. Gvili, Y.: Security analysis of the COVID-19 contact tracing specifications by Apple Inc. and Google Inc. IACR Cryptol. ePrint Arch. 2020, 428 (2020)

    Google Scholar 

  10. Kaptchuk, G., Goldstein, D.G., Hargittai, E., Hofman, J., Redmiles, E.M.: How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt. arXiv preprint arXiv:2005.04343 (2020)

  11. Kokolakis, S.: Privacy attitudes and privacy behaviour: a review of current research on the privacy paradox phenomenon. Comput. Secur. 64, 122–134 (2017)

    Article  Google Scholar 

  12. Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33, 159–174 (1977)

    Article  Google Scholar 

  13. Laufer, R.S., Wolfe, M.: Privacy as a concept and a social issue: a multidimensional developmental theory. J. Soc. Issues 33(3), 22–42 (1977)

    Article  Google Scholar 

  14. Lin, K.Y., Lu, H.P.: Why people use social networking sites: an empirical study integrating network externalities and motivation theory. Comput. Hum. Behav. 27(3), 1152–1161 (2011)

    Article  Google Scholar 

  15. Neuendorf, K.A.: The Content Analysis Guidebook. SAGE, New York (2017)

    Book  Google Scholar 

  16. Petronio, S.: Communication boundary management: a theoretical model of managing disclosure of private information between marital couples. Commun. Theory 1(4), 311–335 (1991)

    Article  Google Scholar 

  17. Petronio, S.: Boundaries of Privacy: Dialectics of Disclosure. Suny Press, Albany (2002)

    Google Scholar 

  18. Petronio, S.: Communication privacy management theory. In: The International Encyclopedia of Interpersonal Communication, pp. 1–9. American Cancer Society (2015)

    Google Scholar 

  19. Ramakrishnan, A.M., Ramakrishnan, A.N., Lagan, S., Torous, J.: From symptom tracking to contact tracing: a framework to explore and assess COVID-19 apps. Future Internet 12(9), 153 (2020)

    Article  Google Scholar 

  20. Rice, R.E.: Media appropriateness: using social presence theory to compare traditional and new organizational media. Hum. Commun. Res. 19(4), 451–484 (1993)

    Article  Google Scholar 

  21. Rogers, R.W.: A protection motivation theory of fear appeals and attitude change1. J. Psychol. 91(1), 93–114 (1975)

    Article  Google Scholar 

  22. Sharma, T., Bashir, M.: Use of apps in the COVID-19 response and the loss of privacy protection. Nat. Med. 26(8), 1165–1167 (2020)

    Article  Google Scholar 

  23. Simko, L., Calo, R., Roesner, F., Kohno, T.: COVID-19 contact tracing and privacy: studying opinion and preferences. arXiv preprint arXiv:2005.06056 (2020)

  24. Stanton, J.M.: Information technology and privacy: a boundary management perspective. In: Socio-Technical and Human Cognition Elements of Information Systems, pp. 79–103. IGI Global (2003)

    Google Scholar 

  25. Stanton, J.M., Stam, K.R.: Information technology, privacy, and power within organizations: a view from boundary theory and social exchange perspectives. Surveill. Soc. 1(2), 152–190 (2003)

    Article  Google Scholar 

  26. Walters, K., Markazi, D.M.: Insights from people’s experiences with AI: privacy management processes. In: Toeppe, K., Yan, H., Chu, S.K.W. (eds.) iConference 2021. LNCS, vol. 12645, pp. 33–38. Springer, Cham (2021).

    Chapter  Google Scholar 

  27. Wen, H., Zhao, Q., Lin, Z., Xuan, D., Shroff, N.: A study of the privacy of COVID-19 contact tracing apps. In: Park, N., Sun, K., Foresti, S., Butler, K., Saxena, N. (eds.) SecureComm 2020. LNICST, vol. 335, pp. 297–317. Springer, Cham (2020).

    Chapter  Google Scholar 

  28. WHO: World Health Organization: Who coronavirus (COVID-19) dashboard. Accessed 15 Sept 2021

  29. WHO: World Health Organization: Who director-general’s opening remarks at the media briefing on covid-19 - 11 March 2020. Accessed 15 Sept 2021

  30. Williams, S.N., Armitage, C.J., Tampe, T., Dienes, K.: Public attitudes towards COVID-19 contact tracing apps: a UK-based focus group study. Health Expect. 24(2), 377–385 (2021)

    Article  Google Scholar 

  31. Wnuk, A., Oleksy, T., Maison, D.: The acceptance of COVID-19 tracking technologies: the role of perceived threat, lack of control, and ideological beliefs. PLoS ONE 15(9), e0238973 (2020)

    Article  Google Scholar 

  32. Yoneki, E., Crowcroft, J.: EpiMap: towards quantifying contact networks for understanding epidemiology in developing countries. Ad Hoc Netw. 13, 83–93 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Jinkyung Park .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Park, J., Ahmed, E., Asif, H., Vaidya, J., Singh, V. (2022). Privacy Attitudes and COVID Symptom Tracking Apps: Understanding Active Boundary Management by Users. In: Smits, M. (eds) Information for a Better World: Shaping the Global Future. iConference 2022. Lecture Notes in Computer Science(), vol 13193. Springer, Cham.

Download citation

  • DOI:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-96959-2

  • Online ISBN: 978-3-030-96960-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics