Cited by 195COVID-19 Prevention and ImpactBehavioral Health and InterventionsPublic Health Policies and Education

Harnessing behavioural science in public health campaigns to maintain ‘social distancing’ in response to the COVID-19 pandemic: key principles

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Bonell, Chris, Michie, Susan, Reicher, Stephen, West, Robert, Bear, Laura, Yardley, Lucy, Curtis, Val, Amlôt, Richard +1 more·2020·Journal of Epidemiology and Community Health

Abstract

Coronavirus Disease 2019 (COVID-19), like Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS), is an infection arising from a coronavirus. The COVID-19 pandemic is unprecedented in recent times in terms of the global spread of infection and the resultant morbidity, mortality and burden on health systems. In the absence of a vaccine, reducing transmission of the COVID-19 virus requires rapid and extensive behaviour change to enact protective behaviours and ‘social distancing’ across whole populations. Although ‘social distancing’ is the current most used term, it actually refers to maintaining physical separation by reducing the number of times people come into close contact with each other across whole populations. Social distancing applies regardless of infection status and is thus distinctive from quarantine or the isolation of those with suspected or diagnosed infection, which is also an important element of infection control.\n\nGovernments across the world are implementing a diverse range of interventions to promote adherence to social distancing measures, which include elements of education, persuasion, incentivisation, coercion, environmental restructuring, restriction and enablement. Interventions have been developed rapidly and could not be informed directly by evidence, given the novelty of the virus and rapid spread of the pandemic. Despite this lack of direct evidence, a body of behavioural science exists which can usefully inform the current interventions and promote adherence to these restrictive measures. This body of science has been developed through the study of other infections (including other coronaviruses such as MERS and SARS), other areas of health and other areas of behaviour. This body of science suggests a number of principles which could ensure that interventions are more likely to achieve their intended outcomes and less likely to generate unintended harmful consequences.\n\nAs a group of behavioural and social scientists who have shared their advice with government through the UK’s Government Office for Science, the researchers of this paper have collaborated to develop a series of principles to inform interventions to promote whole population adherence to social distancing measures. These were informed by members’ expertise and knowledge of existing theory and evidence, rather than by any formal review of the literature.

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  • The more that young people are provided with less helpful role models, the less incentivized they will be to engage in social distancing.

    “In other words, the more that young people are provided with these less helpful role models (in contrast to the function of peer modelling intervention strategies discussed above), the less incentivized they will be to engage in social distancing [37, 40].”
  • Effective peer modelling of social distancing behaviour may consist of peer leaders in community settings or social media influencers demonstrating and promoting this behaviour, rather than politicising this behaviour through authoritarian messaging styles.

    “Effective peer modelling of social distancing behaviour may consist of peer leaders in community settings or social media influencers demonstrating and promoting this behaviour, rather than politicising this behaviour through authoritarian messaging styles [37, 25].”

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Research works printed but not linked: 21

  1. [1]Verity R, Okell LC, Dorigatti I, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis 2020 10.1016/S1473-3099(20)30243-7 PMC7158570 32240634 · DOI · Paper page
  2. [4]Prem K, Liu Y, Russell TW, et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health 2020 10.1016/S2468-2667(20)30073-6 PMC7158905 32220655 · DOI
  3. [8]Viner RM, Russell SJ, Croker H, et al. School closure and management practices during coronavirus outbreaks including COVID-19: a rapid systematic review. Lancet Child Adolesc Health 2020 10.1016/S2352-4642(20)30095-X PMC7270629 32272089 · DOI · Paper page
  4. [12]Moran MB, Sussman S Translating the link between social identity and health behavior into effective health communication strategies: an experimental application using antismoking advertisements. Health Commun 2014; 29: 1057– 66. 10.1080/10410236.2013.832830 24447056 PMC4105014 · DOI
  5. [13]Haslam SA, Reicher SD, Platow M The new psychology of Leadership. London: Routledge, 2020.
  6. [15]Everett J, Colombatto C, Chituc C, et al. The effectiveness of moral messages on public health behavioral intentions during the COVID-19 pandemic. PsyArXiv 2020.
  7. [16]Shen L, Targeting smokers with empathy appeal antismoking public service announcements: a field experiment. J Health Commun 2015; 20: 573– 80. 10.1080/10810730.2015.1012236 25826606 · DOI
  8. [17]Drury J, Carter H, Cocking C, et al. Facilitating collective resilience in the public in emergencies: twelve recommendations based on the social identity approach. Front Public Health 2019; 7: 141 10.3389/fpubh.2019.00141 31214561 PMC6558061 · DOI
  9. [18]Chaudhuri A, Sustaining cooperation in laboratory public goods experiments: a selective survey of the literature. Exp Econ 2011; 14: 47– 83. 10.1007/s10683-010-9257-1 · DOI · Paper page
  10. [21]Van der Pligt J Risk perception and self-protective behavior. Eur Psychol 1996; 1: 34– 43. 10.1027/1016-9040.1.1.34 · DOI · Paper page
  11. [22]Hogg MA Influence and leadership In: Fiske ST, Gilbert DT, Lindzey G, eds. Handbook of social psychology. John Wiley & Sons Inc, 2010: 1166– 207.
  12. [23]Kreuter MW, McClure SM The role of culture in health communication. Ann Rev Public Health Report. 2004; 25: 439– 55. doi: 101146/annurevpublhealth25101802123000 15015929
  13. [26]Atchison CJ, Bowman L, Vrinten C, et al. Perceptions and behavioural responses of the general public during the COVID-19 pandemic: a cross-sectional survey of UK adults. 2020. PMC7783373 33397669
  14. [27]Cialdini RB, Demaine LJ, Sagarin BJ, et al. Managing social norms for persuasive impact. Social Influence 2006; 1: 3– 15. 10.1080/15534510500181459 · DOI · Paper page
  15. [29]Curtis V Don’t look, don’t touch, the science behind revulsion. Oxford: Oxford University Press, 2013.
  16. [31]West R The PRIME theory of motivation as a possible foundation for addiction treatment In: Henningfield J, Santora P, eds. Drug addiction treatment in the 21st century: science and policy issues. Baltimore: John’s Hopkins University Press, 2007.
  17. [33]Balliet D, Mulder LB, Van Lange PAM Reward, punishment, and cooperation: a meta-analysis. Psychol Bull 2011; 137: 594– 615. 10.1037/a0023489 21574679 · DOI
  18. [34]George JM Asymmetrical effects of rewards and punishments: the case of social loafing. J Organisational Occup Psychol 1995; 68: 327– 38. 10.1111/j.2044-8325.1995.tb00591.x · DOI
  19. [36]Marmot MG The Marmot Review. Strategic review of health inequalities in England post-2010. London: The Marmot Review, 2010.
  20. [37]Bonell C, Jamal F, Melendez-Torres GJ, et al. “Dark logic”: theorising the harmful consequences of public health interventions. J Epidemiol Community Health 2015; 69: 95– 8. 10.1136/jech-2014-204671 25403381 · DOI
  21. [38]Parker M, Hanson TM, Vandi A, et al. Ebola and public authority: saving loved ones in Sierra Leone. Med Anthropol 2019; 38: 440– 54. 10.1080/01459740.2019.1609472 31107603 PMC6607031 · DOI

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Authors
Bonell, C., Michie, S., Reicher, S., West, R., Bear, L., Yardley, L., Curtis, V., Amlôt, R., & Rubin, G. J.
Affiliations
  • London School of Hygiene & Tropical Medicine (GB)
  • University College London (GB)
  • University of St Andrews (GB)
  • London School of Economics and Political Science (GB)
  • University of Bristol (GB)
  • Public Health England (GB)
  • King's College London (GB)
Corresponding author
Bonell, Chris
Venue
Journal of Epidemiology and Community Health
Publisher
BMJ
Published
2020-05-08
Volume
74
Issue
8
Pages
617-619
ISSN
  • 0141-7681 (ISSN-L)
  • 0143-005X
  • 1470-2738
OpenAlex
W3021612214
Cited by
195
References
8
Citations by year
2026: 5 · 2025: 12 · 2024: 15 · 2023: 34 · 2022: 54 · 2021: 57 · 2020: 18
FWCI
54.51
Type
journal article
Language
en
Open access
Locations
  • Journal of Epidemiology & Community Health (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
  • Explore Bristol Research (acceptedVersion, cc-by-nc)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • HighWire Press Open Archive (submittedVersion)
  • Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
Funders
  • National Institute for Health Research Health Protection Research Unit
  • National Institute for Health and Care Research (NF-SI-0617-10014)
  • Department of Health and Social Care
  • University of East Anglia
  • King's College London
  • Public Health England
  • National Institute for Health Research Southampton Biomedical Research Centre
Topics
  • Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
  • Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
  • Health Sciences › Health Professions › General Health Professions › Public Health Policies and Education
Keywords
COVID-19 pandemic, social distancing, behavioral science, public health campaigns, behaviour change interventions, infection control, quarantine, environmental restructuring, enablement, unintended consequences
MeSH terms
Betacoronavirus, Physical Distancing, COVID-19, SARS-CoV-2, Behavioral Sciences, Communicable Disease Control, Health Promotion, Humans, Health Knowledge, Attitudes, Practice, Pneumonia, Viral, Public Health, Social Behavior, Coronavirus Infections, Information Dissemination, Risk Reduction Behavior, Pandemics

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