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Understanding 'passivity' in digital health through imaginaries and experiences of coronavirus disease 2019 contact tracing apps

Datos Bibliográficos

ID5260435
AutoresAlessia Costa (0000-0002-3761-9080, Wellcome Connecting Science, autor de correspondencia), Richard Milne (0000-0002-8770-2384, University of Cambridge)
Año2022
Volumen9
Número1
Páginas20539517221091138-20539517221091138
Fecha de publicación2022-01-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaBig Data & Society (JOURNAL)
Identificadores de la revistaISSN: 2053-9517 • E-ISSN: 2053-9517
EditorialSAGE Publications Inc (PUBLISHER)
DOI10.1177/20539517221091138
PMID36819735
OpenAlexW4226425713
IdiomaEN
Citas recibidas2
Referencias citadas46

Growing interest is being directed to the health applications of so-called 'passive data' collected through wearables and sensors without active input by users. High promises are attached to passive data and their potential to unlock new insights into health and illness, but as researchers and commentators have noted, this mode of data gathering also raises fundamental questions regarding the subject's agency, autonomy and privacy. To explore how these tensions are negotiated in practice, we present and discuss findings from an interview study with 30 members of the public in the UK and Italy, which examined their views and experiences of the coronavirus disease 2019 contact tracing apps as a large-scale, high-impact example of digital health technology using passive data. We argue that, contrary to what the phrasing 'passive data' suggests, passivity is not a quality of specific modes of data collection but is contingent on the very practices that the technology is supposed to unobtrusively capture

Autonomy · Contact tracing · Data collection · Data science · Digital health · Disease · Health care · Internet privacy · Political science · Public relations · Social science · Sociology · Wearable computer · Wearable technology · Computer Science · COVID-19 Digital Contact Tracing · Data-Driven Disease Surveillance · Law · Medicine · Privacy, Security, and Data Protection

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Obras citantes distintas2
Citas por año0,67
Intervalo de citas2023 - 2023 (1)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 2
Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae