Simisola Akintoye
Understanding the perceptions of UK COVID-19 contact tracing app in the BAME community in Leicester
Akintoye, Simisola; Ogoh, George; Krokida, Zoi; Nnadi, Juliana; Eke, Damian
Authors
Dr GEORGE OGOH George.Ogoh@nottingham.ac.uk
SENIOR RESEARCH FELLOW
Zoi Krokida
Juliana Nnadi
Dr DAMIAN EKE Damian.Eke@nottingham.ac.uk
TRANSITIONAL ASSISTANT PROFESSOR
Abstract
Purpose
Digital contact tracing technologies are critical to the fight against COVID-19 in many countries including the UK. However, a number of ethical, legal and socio-economic concerns that can affect uptake of the app have been raised. The purpose of this research is to explore the perceptions of the UK digital contact tracing app in the Black, Asian and Minority Ethnic (BAME) community in Leicester and how this can affect its deployment and implementation.
Design/methodology/approach
Data was collected through virtual focus groups in Leicester, UK. A total of 28 participants were recruited for the study. All participants are members of the BAME community, and data was thematically analysed with NVivo 11.
Findings
A majority of the participants were unwilling to download and use the app owing to legal and ethical concerns. A minority were willing to use the app based on the need to protect public health. There was a general understanding that lack of uptake will negatively affect the fight against COVID-19 in BAME communities and an acknowledgement of the need for the government to rebuild trust through transparency and development of regulatory safeguards to enhance privacy and prevent misuse.
Originality/value
To the best of the authors’ knowledge, the research makes original contributions being the first robust study conducted to explore perceptions of marginalised communities, particularly BAME which may be adversely impacted by the deployment of the app. By exploring community-based perceptions, this study further contributes to the emerging citizens’ perceptions on digital contact tracing which is crucial to the effectiveness and the development of an efficient, community-specific response to public attitudes towards the app. The findings can also help the development of responsible innovation approaches that balances the competing interests of digital health interventions with the needs and expectations of the BAME community in the UK.
Citation
Akintoye, S., Ogoh, G., Krokida, Z., Nnadi, J., & Eke, D. (2021). Understanding the perceptions of UK COVID-19 contact tracing app in the BAME community in Leicester. Journal of Information, Communication and Ethics in Society, 19(4), 521-536. https://doi.org/10.1108/jices-06-2021-0071
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 29, 2021 |
Online Publication Date | Dec 7, 2021 |
Publication Date | Dec 13, 2021 |
Deposit Date | Jan 19, 2024 |
Publicly Available Date | Jan 19, 2024 |
Journal | Journal of Information, Communication and Ethics in Society |
Print ISSN | 1477-996X |
Electronic ISSN | 1758-8871 |
Publisher | Emerald |
Peer Reviewed | Peer Reviewed |
Volume | 19 |
Issue | 4 |
Pages | 521-536 |
DOI | https://doi.org/10.1108/jices-06-2021-0071 |
Keywords | Computer Networks and Communications; Sociology and Political Science; Philosophy; Communication |
Public URL | https://nottingham-repository.worktribe.com/output/29839491 |
Files
EM-JICE210028 521..536
(157 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
Time to consider animal data governance: perspectives from neuroscience
(2023)
Journal Article
Effects of urban living environments on mental health in adults
(2023)
Journal Article
Forgotten African AI Narratives and the future of AI in Africa
(2022)
Journal Article
Responsible AI, SDGs, and AI Governance in Africa
(2022)
Presentation / Conference Contribution
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search