Understanding 'passivity' in digital health through imaginaries and experiences of coronavirus disease 2019 contact tracing apps
Bibliographic Data
| ID | 5260435 |
|---|---|
| Authors | Alessia Costa (0000-0002-3761-9080, Wellcome Connecting Science, corresponding author), Richard Milne (0000-0002-8770-2384, University of Cambridge) |
| Year | 2022 |
| Volume | 9 |
| Issue | 1 |
| Pages | 20539517221091138-20539517221091138 |
| Publication date | 2022-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Big Data & Society (JOURNAL) |
| Journal identifiers | ISSN: 2053-9517 • E-ISSN: 2053-9517 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/20539517221091138 |
| PMID | 36819735 |
| OpenAlex | W4226425713 |
| Language | EN |
| Citations received | 2 |
| References cited | 46 |
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
Personalized Medicine
Digital Health
Ethical guidelines for Covid-19 tracing apps
Towards a seamful ethics of Covid-19 contact tracing apps
Blind-sided by privacy? Digital contact tracing, the Apple/Google API and big tech’s newfound role as global health policy makers
Without a trace
Ethics of instantaneous contact tracing using mobile phone apps in the control of the Covid-19 pandemic
Exposure
Configuring the Networked Self
Public attitudes towards Covid‐19 contact tracing apps
Reclaiming the social from ‘social distancing’
Data for life
Normative positions towards Covid-19 contact-tracing apps
Solidarity in Times of Pandemics
M-health and health promotion
The digitally engaged patient
The walkthrough method
From data fetishism to quantifying selves
Co-evolving with self-tracking technologies
Understanding Aids
The Participant
Self-Tracking for Health and the Quantified Self
Manipulate to empower
Making sense of algorithms
How do data come to matter? Living and becoming with personal data
Everyday curation? Attending to data, records and record keeping in the practices of self-monitoring
Creating 'automatic subjects
Molecular Politics, Wearables, and the Aretaic Shift in Biopolitical Governance
The heart of everyday analytics
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,67 |
| Citation span | 2023 - 2023 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |