A network approach to understanding social distancing behaviour during the first UK lockdown of the COVID-19 pandemic

Jilly Gibson-Miller, Orestis Zavlis, Todd K. Hartman, Kate M. Bennett, Sarah Butter, Liat Levita, Anton P. Martinez, Liam Mason, Orla McBride, Ryan McKay, Jamie Murphy, Mark Shevlin, Thomas V. A Stocks, Richard P. Bentall

Research output: Contribution to journalArticlepeer-review

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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.

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.
Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalPsychology and Health
Early online date28 Mar 2022
DOIs
Publication statusE-pub ahead of print - 28 Mar 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Public Health, Environmental and Occupational Health
  • Applied Psychology
  • General Medicine
  • General Chemistry
  • COVID-19
  • behavioural science
  • complexity
  • network psychometrics
  • COM-B model
  • intervention design
  • social distancing

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