Literature DB >> 33727655

A national survey assessing public readiness for digital health strategies against COVID-19 within the United Kingdom.

Viknesh Sounderajah1,2, Jonathan Clarke1,2,3, Seema Yalamanchili1,2, Amish Acharya1,2, Sheraz R Markar1, Hutan Ashrafian4,5, Ara Darzi1,2.   

Abstract

There is concern that digital public health initiatives used in the management of COVID-19 may marginalise certain population groups. There is an overlap between the demographics of groups at risk of digital exclusion (older, lower social grade, low educational attainment and ethnic minorities) and those who are vulnerable to poorer health outcomes from SARS-CoV-2. In this national survey study (n = 2040), we assessed how the UK population; particularly these overlapping groups, reported their preparedness for digital health strategies. We report, with respect to using digital information to make health decisions, that those over 60 are less comfortable (net comfort: 57%) than those between 18 and 39 (net comfort: 78%) and lower social grades are less comfortable (net comfort: 63%) than higher social grades (net comfort: 75%). With respect to a preference for digital over non-digital sources in seeking COVID-19 health information, those over 60 (net preference: 21%) are less inclined than those between 18 and 39 (net preference: 60%) and those of low educational attainment (net preference: 30%) are less inclined than those of high educational attainment (net preference: 52%). Lastly, with respect to distinguishing reliable digital COVID-19 information, lower social grades (net confidence: 55%) are less confident than higher social grades (net confidence: 68%) and those of low educational attainment (net confidence: 51%) are less confident than those of high educational attainment (net confidence: 71%). All reported differences are statistically significant (p < 0.01) following multivariate regression modelling. This study suggests that digital public health approaches to COVID-19 have the potential to marginalise groups who are concurrently at risk of digital exclusion and poor health outcomes from SARS-CoV-2.

Entities:  

Mesh:

Year:  2021        PMID: 33727655      PMCID: PMC7966397          DOI: 10.1038/s41598-021-85514-w

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  18 in total

1.  A cluster separation measure.

Authors:  D L Davies; D W Bouldin
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  1979-02       Impact factor: 6.226

2.  A quantitative examination of explanations for reasons for internet nonuse.

Authors:  Ellen J Helsper; Bianca C Reisdorf
Journal:  Cyberpsychol Behav Soc Netw       Date:  2012-12-18

3.  The Digital Exclusion of Older Adults during the COVID-19 Pandemic.

Authors:  Alexander Seifert
Journal:  J Gerontol Soc Work       Date:  2020-05-13

4.  A Multidimensional Tool Based on the eHealth Literacy Framework: Development and Initial Validity Testing of the eHealth Literacy Questionnaire (eHLQ).

Authors:  Lars Kayser; Astrid Karnoe; Dorthe Furstrand; Roy Batterham; Karl Bang Christensen; Gerald Elsworth; Richard H Osborne
Journal:  J Med Internet Res       Date:  2018-02-12       Impact factor: 5.428

5.  COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.

Authors:  Wasim Ahmed; Josep Vidal-Alaball; Joseph Downing; Francesc López Seguí
Journal:  J Med Internet Res       Date:  2020-05-06       Impact factor: 5.428

6.  Magnitude, demographics and dynamics of the effect of the first wave of the COVID-19 pandemic on all-cause mortality in 21 industrialized countries.

Authors:  Vasilis Kontis; James E Bennett; Theo Rashid; Robbie M Parks; Jonathan Pearson-Stuttard; Michel Guillot; Perviz Asaria; Bin Zhou; Marco Battaglini; Gianni Corsetti; Martin McKee; Mariachiara Di Cesare; Colin D Mathers; Majid Ezzati
Journal:  Nat Med       Date:  2020-10-14       Impact factor: 53.440

Review 7.  Applications of digital technology in COVID-19 pandemic planning and response.

Authors:  Sera Whitelaw; Mamas A Mamas; Eric Topol; Harriette G C Van Spall
Journal:  Lancet Digit Health       Date:  2020-06-29

8.  Trends in the Use of Telehealth During the Emergence of the COVID-19 Pandemic - United States, January-March 2020.

Authors:  Lisa M Koonin; Brooke Hoots; Clarisse A Tsang; Zanie Leroy; Kevin Farris; Tilman Jolly; Peter Antall; Bridget McCabe; Cynthia B R Zelis; Ian Tong; Aaron M Harris
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-10-30       Impact factor: 17.586

9.  Digital Inequality During a Pandemic: Quantitative Study of Differences in COVID-19-Related Internet Uses and Outcomes Among the General Population.

Authors:  Alexander Jam van Deursen
Journal:  J Med Internet Res       Date:  2020-08-20       Impact factor: 5.428

10.  Gastrointestinal effects of an attempt to avoid contracting COVID-19 by 'disinfection'.

Authors:  Lukas Binder; Christoph Högenauer; Cord Langner
Journal:  Histopathology       Date:  2020-06-29       Impact factor: 7.778

View more
  4 in total

1.  Misinformation About the Human Gut Microbiome in YouTube Videos: Cross-sectional Study.

Authors:  Swathikan Chidambaram; Yathukulan Maheswaran; Calvin Chan; Lydia Hanna; Hutan Ashrafian; Sheraz R Markar; Viknesh Sounderajah; John C Alverdy; Ara Darzi
Journal:  JMIR Form Res       Date:  2022-05-16

2.  Health Professionals' eHealth Literacy and System Experience Before and 3 Months After the Implementation of an Electronic Health Record System: Longitudinal Study.

Authors:  Lars Kayser; Astrid Karnoe; Emily Duminski; Svend Jakobsen; Rikke Terp; Susanne Dansholm; Michael Roeder; Gustav From
Journal:  JMIR Hum Factors       Date:  2022-04-29

3.  The mental health crisis during the COVID-19 pandemic in older adults and the role of physical distancing interventions and social protection measures in 26 European countries.

Authors:  Ana Mendez-Lopez; David Stuckler; Martin McKee; Jan C Semenza; Jeffrey V Lazarus
Journal:  SSM Popul Health       Date:  2021-12-28

4.  Can Real-World Evidence Help Restore Decades of Health Inequalities by Informing Health Care Decision-Making? Certainly, and Here is How.

Authors:  Grammati Sarri
Journal:  Front Pharmacol       Date:  2022-06-14       Impact factor: 5.988

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.