Gibson-Miller, J. orcid.org/0000-0002-1864-4889, Zavlis, O., Hartman, T.K. et al. (11 more authors) (2022) A network approach to understanding social distancing behaviour during the first UK lockdown of the COVID-19 pandemic. Psychology and Health, 39 (1). pp. 109-127. ISSN 0887-0446
Abstract
Objective
Given the highly infectious nature of COVID-19, social distancing practices are key in stemming the spread of the virus. We aimed to assess the complex interplay among psychological factors, socio-demographic characteristics and social distancing behaviours within the framework of the widely used Capability, Opportunity, Motivation-Behaviour (COM-B) model.
Design
The present research employed network psychometrics on data collected during the first UK lockdown in April 2020 as part of the COVID-19 Psychological Research Consortium (C19PRC) Study. Using a network approach, we examined the predictions of psychological and demographic variables onto social distancing practices at two levels of analysis: macro and micro.
Design
The present research employed network psychometrics on data collected during the first UK lockdown in April 2020 as part of the COVID-19 Psychological Research Consortium (C19PRC) Study. Using a network approach, we examined the predictions of psychological and demographic variables onto social distancing practices at two levels of analysis: macro and micro.
Results
Our findings revealed several factors that influenced social distancing behaviour during the first UK lockdown. The COM-B model was successful in predicting particular aspects of social-distancing via the influence of psychological capability and motivation at the macro-and micro-levels, respectively. Notably, demographic variables, such as education, income, and age, were directly and uniquely predictive of certain social distancing behaviours.
Conclusion
Our findings reveal psychological factors that are key predictors of social distancing behaviour and also illustrate how demographic variables directly influence such behaviour. Our research has implications for the design of empirically-driven interventions to promote adherence to social distancing practices in this and future pandemics.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ((http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | COVID-19; social distancing; behavioural science; intervention design; network psychometrics; complexity; COM-B model |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Funding Information: | Funder Grant number ECONOMIC & SOCIAL RESEARCH COUNCIL ES/V004379/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Apr 2022 09:54 |
Last Modified: | 28 Jun 2024 10:45 |
Status: | Published |
Publisher: | Taylor & Francis (Routledge) |
Refereed: | Yes |
Identification Number: | 10.1080/08870446.2022.2057497 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185706 |