skip to main content
10.1145/3543434.3543435acmotherconferencesArticle/Chapter ViewAbstractPublication Pagesdg-oConference Proceedingsconference-collections
research-article

Safe return to the workplace: Perceived opportunities and threats in the use of health surveillance technologies in public administrations

Published: 14 September 2022 Publication History

Abstract

The digitalization in public administrations has seen, through the COVID-19 pandemic, the appearance of health surveillance technologies at the workplace. Wearable health devices, such as physiolytics, may then have an increasing role in the management of public agents. Still, little is known about the use of these systems in work settings, as research is mainly oriented towards ethical debates or legal considerations. Accordingly, we propose to consider a concrete case of implementation of physiolytics in a Swiss public administration. We particularly investigate employees’ use rates as well as the perceived opportunities and threats that are linked to physiolytics and health surveillance technologies. This is done through an action design research perspective, where we search to extract from the field guidelines and knowledge for practitioners. We especially highlight that physiolytics’ use steadily decline after the first weeks, due to the design of such devices, the fear of surveillance, and the impression of competition that these systems bring into the workplace. It is therefore vital for public managers to introduce interventions, such as regular feedback, gamification, or nudging to support the engagement of public agents and ensure the viability of such novel health initiatives.

References

[1]
Guenduez, A. A., Mettler, T. and Schedler, K. Technological frames in public administration: What do public managers think of big data? Government Information Quarterly, 37, 1 (2020), 1-12.
[2]
Harteis, C. Machines, change and work: An educational view on the digitalization of work. In The Impact of Digitalization in the Workplace Springer, Cham, 2018, 1-10.
[3]
Wortmann, F. and Flüchter, K. Internet of things. Business & Information Systems Engineering, 57, 3 (2015), 221-224.
[4]
Calvo, R. A., Deterding, S. and Ryan, R. M. Health surveillance during covid-19 pandemic. British Journal of Medicine, 369 (2020), 1-2.
[5]
Klievink, B., Romijn, B.-J., Cunningham, S. and de Bruijn, H. Big data in the public sector: Uncertainties and readiness. Information Systems Frontiers, 19, 2 (2017), 267-283.
[6]
Fernandez-Luque, L., Kushniruk, A. W., Georgiou, A., Basu, A., Petersen, C., Ronquillo, C., Paton, C., Nøhr, C., Kuziemsky, C. E. and Alhuwail, D. Evidence-based health informatics as the foundation for the COVID-19 response: a joint call for action. Methods of Information in Medicine, 59, 6 (2021), 183-192.
[7]
Wilson, H. J. Wearables in the workplace. Harvard Business Review, 91, 11 (2013), 23-27.
[8]
Dunleavy, P. Big data and policy learning. In Evidence-based policy making in the social sciences: methods that matter Policy Press, Bristol, 2016, 143-151.
[9]
Van Dijck, J. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society, 12, 2 (2014), 197-208.
[10]
Stepanovic, S., Mozgovoy, V. and Mettler, T. Designing visualizations for workplace stress management: Results of a pilot study at a Swiss municipality. In International Conference on Electronic Government Springer, Berlin, 2019, 94-104.
[11]
Mettler, T. and Wulf, J. Physiolytics at the workplace: Affordances and constraints of wearables use from an employee's perspective. Information Systems Journal, 29, 1 (2019), 1-29.
[12]
Kudyba, S. COVID-19 and the Acceleration of Digital Transformation and the Future of Work. Information Systems Management, 37, 4 (2020), 284-287.
[13]
Dinev, T., Xu, H., Smith, J. H. and Hart, P. Information privacy and correlates: an empirical attempt to bridge and distinguish privacy-related concepts. European Journal of Information Systems, 22, 3 (2013), 295-316.
[14]
Malhotra, N. K., Kim, S. S. and Agarwal, J. Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15, 4 (2004), 336-355.
[15]
Li, H., Wu, J., Gao, Y. and Shi, Y. Examining individuals’ adoption of healthcare wearable devices: An empirical study from privacy calculus perspective. International Journal of Medical Informatics, 88 (2016), 8-17.
[16]
Kari, T., Koivunen, S., Frank, L., Makkonen, M. and Moilanen, P. Perceived Well-being Effects During the Implementation of a Self-tracking Technology. In Proceedings of the 29th Bled eConference (Bled, Slovenia, 2016).
[17]
Yassaee, M. and Mettler, T. Digital Occupational Health Systems: What Do Employees Think about it? Information Systems Frontiers (2017), 1-16.
[18]
Marcengo, A. and Rapp, A. Visualization of human behavior data: the quantified self. In Big Data: Concepts, Methodologies, Tools, and Applications, 2016, 1582-1612.
[19]
Lavallière, M., Burstein, A. A., Arezes, P. and Coughlin, J. F. Tackling the challenges of an aging workforce with the use of wearable technologies and the quantified-self. DYNA, 83, 197 (2016), 38-43.
[20]
Lupton, D. Self-tracking modes: Reflexive self-monitoring and data practices. In Proceedings of the 2015 Social Life of Big Data Symposium (Perth, Australia, 2014).
[21]
Schall Jr, M. C., Sesek, R. F. and Cavuoto, L. A. Barriers to the adoption of wearable sensors in the workplace: A survey of occupational safety and health professionals. Human Factors, 60, 3 (2018), 351-362.
[22]
Yassaee, M., Mettler, T. and Winter, R. Principles for the design of digital occupational health systems. Information and Organization, 29, 2 (2019), 77-90.
[23]
Morozov, E. To save everything, click here: The folly of technological solutionism. Public Affairs, New York, 2013.
[24]
Lupton, D. and Michael, M. ‘Depends on who's got the data’: Public understandings of personal digital dataveillance. Surveillance & Society, 15, 2 (2017), 254-268.
[25]
Mathur, A., Van den Broeck, M., Vanderhulst, G., Mashhadi, A. and Kawsar, F. Tiny habits in the giant enterprise: understanding the dynamics of a quantified workplace. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Osaka, Japan, 2015).
[26]
Hamblen, M. Programs are used to weed out workers who raise premiums, one attorney says. Retrieved from https://www.computerworld.com/article/2937721/wearables/wearables-for-workplace-wellness-face-federal-scrutiny.html.
[27]
Moore, P. and Piwek, L. Regulating wellbeing in the brave new quantified workplace. Employee Relations, 39, 3 (2017), 308-316.
[28]
Stepanovic, S., Mettler, T., Schmidt-Kraepelin, M., Thiebes, S. and Sunyaev, A. Wearable Health Devices in the Workplace: The Importance of Habits to Sustain the Use. In Proceedings of the 21st IEEE Conference on Business Informatics (Moscow, Russia, 2019).
[29]
Sein, M. K., Henfridsson, O., Purao, S., Rossi, M. and Lindgren, R. Action design research. MIS Quarterly, 35, 1 (2011), 37-56.
[30]
Mullarkey, M. T. and Hevner, A. R. An elaborated action design research process model. European Journal of Information Systems, 28, 1 (2019), 6-20.
[31]
Romme, A. G. L. and Meijer, A. Applying design science in public policy and administration research. Policy & Politics, 48, 1 (2020), 149-165.
[32]
Grossmeier, J. The art of health promotion: Linking research to practice. American Journal of Health Promotion, 31, 3 (2017), 251-261.
[33]
Kim, J. Y., Wineinger, N. E., Taitel, M., Radin, J. M., Akinbosoye, O., Jiang, J., Nikzad, N., Orr, G., Topol, E. and Steinhubl, S. Self-monitoring utilization patterns among individuals in an incentivized program for healthy behaviors. Journal of Medical Internet Research, 18, 11 (2016), 1-15.
[34]
Epstein, D. A., Ping, A., Fogarty, J. and Munson, S. A. A lived informatics model of personal informatics. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (New York, USA, 2015).
[35]
Limayem, M., Hirt, S. G. and Cheung, C. M. How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly (2007), 705-737.
[36]
Epel, E. S., Crosswell, A. D., Mayer, S. E., Prather, A. A., Slavich, G. M., Puterman, E. and Mendes, W. B. More than a feeling: A unified view of stress measurement for population science. Frontiers in Neuroendocrinology, 49 (2018), 146-169.
[37]
Spath, P. Introduction to healthcare quality management. Health Administration Press Chicago, IL, Chicago, USA, 2009.
[38]
Ruckenstein, M. Visualized and interacted life: Personal analytics and engagements with data doubles. Societies, 4, 1 (2014), 68-84.
[39]
Pantzar, M. and Ruckenstein, M. The heart of everyday analytics: emotional, material and practical extensions in self-tracking market. Consumption Markets & Culture, 18, 1 (2015), 92-109.
[40]
Swan, M. Sensor mania! The internet of things, wearable computing, objective metrics, and the quantified self 2.0. Journal of Sensor and Actuator Networks, 1, 3 (2012), 217-253.
[41]
Fox, P. and Hendler, J. Changing the equation on scientific data visualization. Science, 331, 6018 (2011-02-11 00:00:00 2011), 705-708.
[42]
Dikhit, R. S. Internet of Things with Wearable Devices at Enterprise Radar. Journal of Mobile Computing & Application, 3, 1 (2016), 1-8.
[43]
Khakurel, J., Melkas, H. and Porras, J. Tapping into the wearable device revolution in the work environment: a systematic review. Information Technology & People, 31, 3 (2018), 791-818.
[44]
AlMarshedi, A., Wanick, V., Wills, G. B. and Ranchhod, A. Gamification and behaviour. In Gamification Springer, Berlin, 2017, 19-29.
[45]
Deterding, S. Eudaimonic Design, or: Six Invitations to Rethink Gamification. In Rethinking Gamification Meson Press Lüneburg, 2014, 305-323.
[46]
Hosseini, M., Shahri, A., Phalp, K. and Ali, R. Four reference models for transparency requirements in information systems. Requirements Engineering, 23, 2 (2018), 251-275.
[47]
Miele, F. and Tirabeni, L. Digital technologies and power dynamics in the organization: A conceptual review of remote working and wearable technologies at work. Sociology Compass, 14, 6 (2020), 1-13.
[48]
Weston, M. Wearable surveillance–a step too far? Strategic Human Ressources Review, 14, 6 (2015), 214-219.
[49]
Türken, S., Nafstad, H. E., Blakar, R. M. and Roen, K. Making sense of neoliberal subjectivity: A discourse analysis of media language on self-development. Globalizations, 13, 1 (2016), 32-46.
[50]
Toner, J. Exploring the dark-side of fitness trackers: Normalization, objectification and the anaesthetisation of human experience. Performance Enhancement & Health, 6, 2 (2018), 75-81.
[51]
Mettler, T. and Wulf, J. Health promotion with physiolytics: What is driving people to subscribe in a data-driven health plan. PLOS One, 15, 4 (2020), 1-19.
[52]
Patel, M. S., Asch, D. A. and Volpp, K. G. Wearable devices as facilitators, not drivers, of health behavior change. Journal of the American Medical Association, 313, 5 (2015), 459-460.
[53]
Bove, L. A. Increasing patient engagement through the use of wearable technology. The Journal for Nurse Practitioners, 15, 8 (2019), 535-539.
[54]
Jones, J., Gouge, C. and Crilley, M. Design principles for health wearables. Communication Design Quarterly Review, 5, 2 (2017), 40-50.
[55]
Lušic, M., Fischer, C., Bönig, J., Hornfeck, R. and Franke, J. Worker information systems: State of the art and guideline for selection under consideration of company specific boundary conditions. Procedia 41 (2016), 1113-1118.
[56]
Attig, C. and Franke, T. Abandonment of personal quantification: A review and empirical study investigating reasons for wearable activity tracking attrition. Computers in Human Behavior, 102 (2020), 223-237.
[57]
Deterding, S., Dixon, D., Khaled, R. and Nacke, L. From game design elements to gamefulness: Defining "gamification". In Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek 2011 (Tampere, Finland, 2011).
[58]
Sunstein, C. R. People prefer system 2 nudges (kind of). Duke LJ, 66 (2016), 121.
[59]
Leonard, T. C. Richard H. Thaler, Cass R. Sunstein, Nudge: Improving decisions about health, wealth, and happiness. Constitutional Political Economy, 19 (2008), 356–360
[60]
Hausman, D. M. and Welch, B. Debate: To nudge or not to nudge. Journal of Political Philosophy, 18, 1 (2010), 123-136.
[61]
Sunstein, C. R. Nudging: a very short guide. Journal of Consumer Policy, 37, 4 (2014), 583-588.
[62]
Bucher, T., Collins, C., Rollo, M. E., McCaffrey, T. A., De Vlieger, N., Van der Bend, D., Truby, H. and Perez-Cueto, F. J. Nudging consumers towards healthier choices: a systematic review of positional influences on food choice. British Journal of Nutrition, 115, 12 (2016), 2252-2263.
[63]
Woodend, A., Schölmerich, V. and Denktas, S. “Nudges” to Prevent Behavioral Risk Factors Associated With Major Depressive Disorder. American Journal of Public Health, 105, 11 (2015), 2318-2321.
[64]
Davison, R. M. and Martinsons, M. G. Context is king! Considering particularism in research design and reporting. Journal of Information Technology, 31, 3 (2016), 241-249.

Cited By

View all
  • (2025)Ethical and Legal Implications of Health Monitoring Wearable Devices: A Scoping ReviewSocial Science & Medicine10.1016/j.socscimed.2025.117685(117685)Online publication date: Jan-2025

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
dg.o '22: Proceedings of the 23rd Annual International Conference on Digital Government Research
June 2022
499 pages
ISBN:9781450397490
DOI:10.1145/3543434
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 September 2022

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

dg.o 2022

Acceptance Rates

Overall Acceptance Rate 150 of 271 submissions, 55%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)28
  • Downloads (Last 6 weeks)2
Reflects downloads up to 25 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2025)Ethical and Legal Implications of Health Monitoring Wearable Devices: A Scoping ReviewSocial Science & Medicine10.1016/j.socscimed.2025.117685(117685)Online publication date: Jan-2025

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media