Flint, S.W. orcid.org/0000-0003-4878-3019, Piotrkowicz, A. and Watts, K. (2022) Use of Artificial Intelligence to understand adults’ thoughts and behaviours relating to COVID-19. Perspectives in Public Health, 142 (3). pp. 167-174. ISSN 1757-9139
Abstract
Aims: The outbreak of severe acute respiratory syndrome coronavirus 2 (COVID-19) is a global pandemic that has had substantial impact across societies. An attempt to reduce infection and spread of the disease, for most nations, has led to a lockdown period, where people’s movement has been restricted resulting in a consequential impact on employment, lifestyle behaviours and wellbeing. As such, this study aimed to explore adults’ thoughts and behaviours in response to the outbreak and resulting lockdown measures. Methods: Using an online survey, 1126 adults responded to invitations to participate in the study. Participants, all aged 18 years or older, were recruited using social media, email distribution lists, website advertisement and word of mouth. Sentiment and personality features extracted from free-text responses using Artificial Intelligence methods were used to cluster participants. Results: Findings demonstrated that there was varied knowledge of the symptoms of COVID-19 and high concern about infection, severe illness and death, spread to others, the impact on the health service and on the economy. Higher concerns about infection, illness and death were reported by people identified at high risk of severe illness from COVID-19. Behavioural clusters, identified using Artificial Intelligence methods, differed significantly in sentiment and personality traits, as well as concerns about COVID-19, actions, lifestyle behaviours and wellbeing during the COVID-19 lockdown. Conclusions: This time-sensitive study provides important insights into adults’ perceptions and behaviours in response to the COVID-19 pandemic and associated lockdown. The use of Artificial Intelligence has identified that there are two behavioural clusters that can predict people’s responses during the COVID-19 pandemic, which goes beyond simple demographic groupings. Considering these insights may improve the effectiveness of communication, actions to reduce the direct and indirect impact of the COVID-19 pandemic and to support community recovery.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Royal Society for Public Health 2021. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). Request permissions for this article. |
Keywords: | COVID-19; lockdown; attitudes; behaviours; Artificial Intelligence |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Psychology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 01 Aug 2023 10:42 |
Last Modified: | 01 Aug 2023 10:42 |
Status: | Published |
Publisher: | SAGE |
Identification Number: | 10.1177/1757913920979332 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:201999 |
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