Early perceptions and behavioural responses during the COVID-19 pandemic: a cross-sectional survey of UK adults
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Abstract
OBJECTIVE: To examine risk perceptions and behavioural responses of the UK adult population during the early phase of the COVID-19 epidemic in the UK. DESIGN: A cross-sectional survey. SETTING: Conducted with a nationally representative sample of UK adults within 48 hours of the UK Government advising the public to stop non-essential contact with others and all unnecessary travel. PARTICIPANTS: 2108 adults living in the UK aged 18 years and over. Response rate was 84.3% (2108/2500). Data collected between 17 March and 18 March 2020. MAIN OUTCOME MEASURES: Descriptive statistics for all survey questions, including number of respondents and weighted percentages. Robust Poisson regression used to identify sociodemographic variation in: (1) adoption of social distancing measures, (2) ability to work from home, and (3) ability and (4) willingness to self-isolate. RESULTS: Overall, 1992 (94.2%) respondents reported at least one preventive measure: 85.8% washed their hands with soap more frequently; 56.5% avoided crowded areas and 54.5% avoided social events. Adoption of social distancing measures was higher in those aged over 70 years compared with younger adults aged 18-34 years (adjusted relative risk/aRR: 1.2; 95% CI: 1.1 to 1.5). Those with lowest household income were three times less likely to be able to work from home (aRR: 0.33; 95% CI: 0.24 to 0.45) and less likely to be able to self-isolate (aRR: 0.92; 95% CI: 0.88 to 0.96). Ability to self-isolate was also lower in black and minority ethnic groups (aRR: 0.89; 95% CI: 0.79 to 1.0). Willingness to self-isolate was high across all respondents. CONCLUSIONS: Ability to adopt and comply with certain non-pharmaceutical interventions (NPIs) is lower in the most economically disadvantaged in society. Governments must implement appropriate social and economic policies to mitigate this. By incorporating these differences in NPIs among socioeconomic subpopulations into mathematical models of COVID-19 transmission dynamics, our modelling of epidemic outcomes and response to COVID-19 can be improved.
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Adherence to social distancing guidelines is generally lower in younger populations.
“This is consistent with previous evidence indicating that adherence to social distancing guidelines is generally lower in younger populations [23, 24].”
From Facilitators and barriers to social distancing for young people during the COVID-19 pandemic (2022) · cites this paper as [23]
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Rothman, K. J. (1990) · Epidemiology · doi:10.1097/00001648-199001000-00010 · Cited by 5,965 · see citing works
Do multiple outcome measures require p-value adjustment?
Feise, R. J. (2002) · BMC Medical Research Methodology · doi:10.1186/1471-2288-2-8 · Cited by 1,299 · see citing works
Rubin, G. J., Amlot, R., Page, L., & Wessely, S. (2009) · BMJ · doi:10.1136/bmj.b2651 · Cited by 1,106 · see citing works
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Research works printed but not linked: 19
- [7]Ferguson NM, Laydon D, Nedjati-Gilani G Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand, 2020. PMC7140590 32270376
- [8]Cowling BJ, Ng DMW, Ip DKM, et al Community psychological and behavioral responses through the first wave of the 2009 influenza A(H1N1) pandemic in Hong Kong. J Infect Dis 2010; 202: 867– 76. 10.1086/655811 20677945 · DOI
- [9]Agüero F, Adell MN, Pérez Giménez A, et al Adoption of preventive measures during and after the 2009 influenza A (H1N1) virus pandemic peak in Spain. Prev Med 2011; 53: 203– 6. 10.1016/j.ypmed.2011.06.018 21781983 PMC7119352 · DOI
- [11]Rubin GJ, Potts HWW, Michie S The impact of communications about swine flu (influenza A H1N1v) on public responses to the outbreak: results from 36 national telephone surveys in the UK. Health Technol Assess 2010; 14: 183– 266. 10.3310/hta14340-03 20630124 · DOI · Paper page
- [12]Lau JTF, Griffiths S, Choi KC, et al Avoidance behaviors and negative psychological responses in the general population in the initial stage of the H1N1 pandemic in Hong Kong. BMC Infect Dis 2010; 10: 139. 10.1186/1471-2334-10-139 20509887 PMC2891756 · DOI · Paper page
- [13]Eastwood K, Durrheim D, Francis JL, et al Knowledge about pandemic influenza and compliance with containment measures among Australians. Bull World Health Organ 2009; 87: 588– 94. 10.2471/BLT.08.060772 19705008 PMC2733278 · DOI
- [14]Lohiniva A-L, Sane J, Sibenberg K, et al Understanding coronavirus disease (COVID-19) risk perceptions among the public to enhance risk communication efforts: a practical approach for outbreaks, Finland, February 2020. Euro Surveill 2020; 25. 10.2807/1560-7917.ES.2020.25.13.2000317 PMC7140598 32265008 · DOI
- [15]Gesser-Edelsburg A, Cohen R, Hijazi R, et al Analysis of public perception of the Israeli government's early emergency instructions regarding COVID-19: online survey study. J Med Internet Res 2020; 22: e19370. 10.2196/19370 32392172 PMC7236609 · DOI
- [16]Olapegba PO, Ayandele O Survey data of COVID-19-related knowledge, risk perceptions and precautionary behavior among Nigerians. Data Brief 2020; 8: 105685. PMC7206440 32391411
- [17]Motta Zanin G, Gentile E, Parisi A, et al A preliminary evaluation of the public risk perception related to the COVID-19 health emergency in Italy. Int J Environ Res Public Health 2020; 17 10.3390/ijerph17093024 32349253 PMC7246845 · DOI
- [18]Kwok KO, Li KK, Chan HHH, et al Community responses during early phase of COVID-19 epidemic, Hong Kong. Emerg Infect Dis 2020; 26: 1575– 9. 10.3201/eid2607.200500 32298227 PMC7323558 · DOI
- [19]McFadden SM, Malik AA, Aguolu OG, et al Perceptions of the adult US population regarding the novel coronavirus outbreak. PLoS One 2020; 15: e0231808. 10.1371/journal.pone.0231808 32302370 PMC7164638 · DOI
- [20]Husnayain A, Shim E, Fuad A, et al Understanding the community risk perceptions of the COVID-19 outbreak in South Korea: Infodemiology study. J Med Internet Res 2020; 22: e19788. 10.2196/19788 32931446 PMC7527166 · DOI · Paper page
- [24]Kwok KO, KK L, Chan HHH Community responses during the early phase of the COVID-19 epidemic in Hong Kong: risk perception information exposure and preventive measures. medRxiv 2020.
- [26]Ranganathan P, Pramesh CS, Aggarwal R Common pitfalls in statistical analysis: logistic regression. Perspect Clin Res 2017; 8: 148– 51. 10.4103/picr.PICR_87_17 28828311 PMC5543767 · DOI
- [29]Bults M, Beaujean DJMA, Richardus JH, et al Perceptions and behavioral responses of the general public during the 2009 influenza A (H1N1) pandemic: a systematic review. Disaster Med Public Health Prep 2015; 9: 207– 19. 10.1017/dmp.2014.160 25882127 · DOI
- [30]Ahmed F, Zviedrite N, Uzicanin A Effectiveness of workplace social distancing measures in reducing influenza transmission: a systematic review. BMC Public Health 2018; 18: 518. 10.1186/s12889-018-5446-1 29669545 PMC5907354 · DOI · Paper page
- [31]Goodwin R, Sun S Public perceptions and reactions to H7N9 in Mainland China. J Infect 2013; 67: 458– 62. 10.1016/j.jinf.2013.06.014 23834972 · DOI
- [32]Jang WM, Cho S, Jang DH, et al Preventive behavioral responses to the 2015 middle East respiratory syndrome coronavirus outbreak in Korea. Int J Environ Res Public Health 2019; 16: ijerph16122161. 10.3390/ijerph16122161 PMC6616393 31216779 · DOI
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Jay, J., Bor, J., Nsoesie, E. O., Lipson, S. K., Jones, D. K., Galea, S., & Raifman, J. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-00998-2 · Cited by 346 · see citing works
Agbo, F. J., Oyelere, S. S., Suhonen, J., & Tukiainen, M. (2021) · Smart Learning Environments · doi:10.1186/s40561-020-00145-4 · Cited by 325 · see citing works
The Influence of Demographics and Personality on COVID-19 Coping in Young Adults
Volk, A. A., Brazil, K. J., Franklin-Luther, P., Dane, A. V., & Vaillancourt, T. (2021) · Personality and Individual Differences · doi:10.1016/j.paid.2020.110398 · Cited by 120 · see citing works
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Berry, E., Jenkins, C., & Allen, S. (2022) · BMC Public Health · doi:10.1186/s12889-022-13325-3 · Cited by 19 · see citing works
“This is consistent with previous evidence indicating that adherence to social distancing guidelines is generally lower in younger populations [23, 24].”
ResultDurand, H., Bacon, S. L., Byrne, M., Farrell, K., Kenny, E., Lavoie, K. L., McGuire, B. E., McSharry, J., Meade, O., Mooney, R., et al. (2021) · HRB Open Research · doi:10.12688/hrbopenres.13237.1 · Cited by 9 · see citing works
- Authors
- Atchison, C., Bowman, L. R., Vrinten, C., Redd, R., Pristerà, P., Eaton, J., & Ward, H.
- Affiliations
- Imperial College London (GB)
- Corresponding author
- Atchison, Christina
- ORCID
- Venue
- BMJ Open
- Publisher
- BMJ
- Published
- 2021-01
- Volume
- 11
- Issue
- 1
- Pages
- e043577
- ISSN
- 2044-6055 (ISSN-L)
- PMC
- PMC7783373
- OpenAlex
- W3120133800
- Cited by
- 379
- References
- 3
- Citations by year
- 2026: 9 · 2025: 17 · 2024: 30 · 2023: 67 · 2022: 81 · 2021: 120 · 2020: 54 · 2012: 1
- FWCI
- 103.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMJ Open (publishedVersion, cc-by-nc)
- medRxiv (acceptedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Spiral (Imperial College London) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion, cc-by-nc)
- Funders
- National Institute for Health Research (NIHR) Senior Investigator (P75372)
- Imperial NIHR Research Capability Funding (P81291)
- Topics
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Social Sciences › Psychology › Clinical Psychology › COVID-19 and Mental Health
- Keywords
- COVID-19 pandemic, risk perception, behavioral responses, social distancing, self-isolation, working from home, non-pharmaceutical interventions, socioeconomic disparities, household income, Black and minority ethnic communities, older adults, hand washing, UK adults, lockdown measures, public health communication, health disparities
- MeSH terms
- COVID-19, SARS-CoV-2, Adolescent, Adult, Aged, Behavior, Cross-Sectional Studies, Female, United Kingdom, Health Surveys, Humans, Male, Middle Aged, Perception, Young Adult, Pandemics
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