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Adoption of a COVID-19 Contact Tracing App Among Older Internet Users in Finland

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Human Aspects of IT for the Aged Population. Design, Interaction and Technology Acceptance (HCII 2022)

Abstract

The outbreak of the COVID-19 pandemic created an unequal need for limiting physical contacts and tracing possible exposures to a novel coronavirus. Smartphone-based contact tracing applications (CTAs) were presented as a vehicle for stopping virus transmission chains and supporting the work of contact tracing teams. In this study, older adults’ adoption of a CTA was studied using socioeconomic background factors, satisfaction with health, and the measure of digital activity as predictors. The data were drawn from a larger questionnaire survey targeted at older internet users. A subsample of older Finnish internet users (N = 723) was analyzed using a logistic regression model. Results showed that older internet users had widely adopted the Finnish CTA called Koronavilkku irrespective of demographic background factors, level of education, and self-assessed satisfaction with health. Besides high income and retirement status, digital activity measured through the breadth of mobile phone features used and the use of an online symptom checker increased the likelihood of having the CTA installed on a smartphone. The results of the study lend themselves to be used for future epidemics and other occasions that require a real-time and/or retrospective tracing of people and their physical encounters.

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Acknowledgments

This study was funded by the Strategic Research Council at the Academy of Finland (grants 327145 and 327149 for the DigiIN project) and the Academy of Finland for the Centre of Excellence in Research on Ageing and Care (grants 312367 and 336671).

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Correspondence to Sakari Taipale .

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Taipale, S., Oinas, T. (2022). Adoption of a COVID-19 Contact Tracing App Among Older Internet Users in Finland. In: Gao, Q., Zhou, J. (eds) Human Aspects of IT for the Aged Population. Design, Interaction and Technology Acceptance. HCII 2022. Lecture Notes in Computer Science, vol 13330. Springer, Cham. https://doi.org/10.1007/978-3-031-05581-2_42

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  • DOI: https://doi.org/10.1007/978-3-031-05581-2_42

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