Evidence map›Paper›PMID 33444217›Full record

ArticleBMJ open2020

Understanding public preferences and trade-offs for government responses during a pandemic: a protocol for a discrete choice experiment in the UK.

Mesfin G Genie, Luis Enrique Loría-Rebolledo, Shantini Paranjothy, Daniel Powell, Mandy Ryan, Ruben Andreas Sakowsky, Verity Watson

Abstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. The value of social robots supporting informal care: a discrete choice experiment among informal caregivers.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    Article
  3. From polarity to plurality: Perceptions of COVID-19 and policy measures in England and Scotland.Health expectations : an international journal of public participation in health care and health policy · 2024
    Article
  4. Article
  5. Article
  6. Priority setting in the German healthcare system: results from a discrete choice experiment.International journal of health economics and management · 2023
    Article
  7. Article
  8. Preferences for COVID-19 epidemic control measures among French adults: a discrete choice experiment.The European journal of health economics : HEPAC : health economics in prevention and care · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mesfin G GenieHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK mesfin.genie@abdn.ac.uk.ORCID 0000-0002-1744-4666
Luis Enrique Loría-RebolledoHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK.
Shantini ParanjothyHealth Data Science Research Centre, University of Aberdeen, Aberdeen, UK.
Daniel PowellHealth Psychology, University of Aberdeen, Aberdeen, UK.ORCID 0000-0003-4995-6057
Mandy RyanHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK.
Ruben Andreas SakowskyHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK.ORCID 0000-0002-6893-9220
Verity WatsonHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK.ORCID 0000-0002-3824-5076

Funding

Chief Scientist Office HERU1
6 · The paper itself

Abstract

introductionSocial distancing and lockdown measures are among the main government responses to the COVID-19 pandemic. These measures aim to limit the COVID-19 infection rate and reduce the mortality rate of COVID-19. Given we are likely to see local lockdowns until a treatment or vaccine for COVID-19 is available, and their effectiveness depends on public acceptability, it is important to understand public preference for government responses. METHODS AND ANALYSIS: Using a discrete choice experiment (DCE), this study will investigate the public's preferences for pandemic responses in the UK. Attributes (and levels) are based on: (1) lockdown measures described in policy documents; (2) literature on preferences for lockdown measures and (3) a social media analysis. Attributes include: lockdown type; lockdown length; postponement of usual non-urgent medical care; number of excess deaths; number of infections; impact on household spending and job losses. We will prepilot the DCE using virtual think aloud interviews with respondents recruited via Facebook. We will collect preference data using an online survey of 4000 individuals from across the four UK countries (1000 per country). We will estimate the relative importance of the attributes, and the trade-offs individuals are willing to make between attributes. We will test if respondents' preferences differ based on moral attitudes (using the Moral Foundation Questionnaire), socioeconomic circumstances (age, education, economic insecurity, health status), country of residence and experience of COVID-19. ETHICS AND DISSEMINATION: The University of Aberdeen's College Ethics Research Board (CERB) has approved the study (reference: CERB/2020/6/1974). We will seek CERB approval for major changes from the developmental and pilot work. Peer-reviewed papers will be submitted, and results will be presented at public health and health economic conferences nationally and internationally. A lay summary will be published on the Health Economics Research Unit blog.

Indexed as

Government ProgramsPublic OpinionCommunicable Disease ControlCOVID-19HumansPandemicsPhysical DistancingQuarantineSocial MediaSocioeconomic FactorsUnited KingdomCOVID-19health economicsinfectious diseasespublic health

Identifiers

PMID33444217
PMCPMC7682450

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.