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. 2020 Dec 29;10(12):e045309.
doi: 10.1136/bmjopen-2020-045309.

Cross-sectional analysis to explore the awareness, attitudes and actions of UK adults at high risk of severe illness from COVID-19

Stuart W Flint  1   2 , Adrian Brown  3   4 , Abd A Tahrani  5   6   7 , Alicja Piotrkowicz  2   8 , Anny-Claude Joseph  9
Affiliations

Cross-sectional analysis to explore the awareness, attitudes and actions of UK adults at high risk of severe illness from COVID-19

Stuart W Flint et al. BMJ Open. .

Abstract

Objectives: This study explored the impact of COVID-19 on people identified as at high risk of severe illness by UK government, and in particular, the impact of lockdown on access to healthcare, medications and use of technological platforms.

Design: Online survey methodology.

Setting: UK.

Participants: 1038 UK adults were recruited who were either identified by UK government as at high risk of severe illness from COVID-19 or self-identified as at high risk with acute or other chronic health conditions not included in the UK government list. Participants were recruited through social media advertisements, health charities and patient organisations.

Main outcomes measures: The awareness, attitudes and actions survey which explores the impact of COVID-19, on including access to healthcare, use of technology for health condition management, mental health, depression, well-being and lifestyle behaviours.

Results: Nearly half of the sample (44.5%) reported that their mental health had worsened during the COVID-19 lockdown. Management of health conditions changed including access to medications (28.5%) and delayed surgery (11.9%), with nearly half of the sample using telephone care (45.5%). Artificial Intelligence identified that participants in the negative cluster had higher neuroticism, insecurity and negative sentiment. Participants in this cluster reported more negative impacts on lifestyle behaviours, higher depression and lower well-being, alongside lower satisfaction with platforms to deliver healthcare.

Conclusions: This study provides novel evidence of the impact of COVID-19 on people identified as at high risk of severe illness. These findings should be considered by policy-makers and healthcare professionals to avoid unintended consequences of continued restrictions and future pandemic responses.

Keywords: COVID-19; artificial Intelligence; attitudes; behaviours; high risk; lockdown.

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Conflict of interest statement

Competing interests: SWF and AP are employed by Scaled Insights.

Figures

Figure 1
Figure 1
Visualisation of clusters using principal component analysis (PCA).
See this image and copyright information in PMC

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