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?:abstract
  • Self-tracking with wearable devices and mobile applications is a popular practice that relies on automated data collection and algorithm-driven analytics. Initially designed as a tool for personal use, a variety of public and corporate actors such as commercial organizations and insurance companies now make use of self-tracking data. Associated social risks such as privacy violations or measurement inaccuracies have been theoretically derived, although empirical evidence remains sparse. This article conceptualizes self-tracking as algorithmic-selection applications and empirically examines users' risk awareness related to self-tracking applications as well as coping strategies as an option to deal with these risks. It draws on representative survey data collected in Switzerland. The results reveal that Swiss self-trackers' awareness of risks related to the applications they use is generally low and only a small number of those who self-track apply coping strategies. We further find only a weak association between risk awareness and the application of coping strategies. This points to a cost-benefit calculation when deciding how to respond to perceived risks, a behavior explained as a privacy calculus in extant literature. The widespread willingness to pass on personal data to insurance companies despite associated risks provides further evidence for this interpretation. The conclusions - made even more pertinent by the potential of wearables' track-and-trace systems and state-level health provision - raise questions about technical safeguarding, data and health literacies, and governance mechanisms that might be necessary considering the further popularization of self-tracking for health. (xsd:string)
?:contributor
?:dateModified
  • 2021 (xsd:gyear)
?:datePublished
  • 2021 (xsd:gyear)
?:doi
  • 10.17645/mac.v9i4.4162 ()
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  • true (xsd:boolean)
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  • en (xsd:string)
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?:issn
  • 2183-2439 ()
?:issueNumber
  • 4 (xsd:string)
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?:name
  • Algorithmic Self-Tracking for Health: User Perspectives on Risk Awareness and Coping Strategies (xsd:string)
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?:publicationType
  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
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  • GESIS-SSOAR (xsd:string)
  • In: Media and Communication, 9, 2021, 4, 145-157 (xsd:string)
rdf:type
?:url
?:volumeNumber
  • 9 (xsd:string)