Evidence map›Paper›PMID 39412841›Full record

ArticleJMIR public health and surveillance2024

COVID-19 Vaccine Preferences in General Populations in Canada, Germany, the United Kingdom, and the United States: Discrete Choice Experiment.

David Salisbury, Jeffrey V Lazarus, Nancy Waite, Clara Lehmann, Sumitra Sri Bhashyam, Marie de la Cruz, Beth Hahn, Matthew D Rousculp, Paolo Bonanni

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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

9 authors.

David SalisburyProgramme for Global Health, Royal Institute of International Affairs, Chatham House, London, United Kingdom.ORCID 0009-0005-8926-6570
Jeffrey V LazarusGraduate School of Public Health and Health Policy (CUNY SPH), City University of New York, New York, NY, United States.ORCID 0000-0001-9618-2299
Nancy WaiteSchool of Pharmacy, University of Waterloo, Ontario, ON, Canada.ORCID 0000-0003-3440-9843
Clara LehmannDepartment of Internal Medicine, Medical Faculty and University Hospital Cologne, University of Cologne, Cologne, Germany.ORCID 0000-0002-7042-1578
Sumitra Sri BhashyamICON Insights, Evidence and Value-Patient Centered Outcomes, Reading, United Kingdom.ORCID 0000-0001-5815-3518
Marie de la CruzICON Insights, Evidence and Value-Patient Centered Outcomes, Raleigh, NC, United States.ORCID 0000-0002-3343-8960
Beth HahnNovavax, Inc, Gaithersburg, MD, United States.ORCID 0000-0002-7396-9336
Matthew D RousculpNovavax, Inc, Gaithersburg, MD, United States.ORCID 0009-0001-2509-1098
Paolo BonanniDepartment of Health Services, University of Florence, Florence, Italy.ORCID 0000-0003-2875-3744

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite strong evidence supporting COVID-19 vaccine efficacy and safety, a proportion of the population remains hesitant to receive immunization. Discrete choice experiments (DCEs) can help assess preferences and decision-making drivers.

objectiveWe aim to (1) elicit preferences for COVID-19 vaccines in Canada, Germany, the United Kingdom, and the United States; (2) understand which vaccine attributes people there value; and (3) gain insight into the choices that different population subgroups make regarding COVID-19 vaccines.

methodsParticipants in the 2019nCoV-408 study were aged ≥18 years; self-reported antivaccinationists were excluded. A DCE with a series of 2 hypothetical vaccine options was embedded into a survey to determine participant treatment preferences (primary objective). Survey questions covered vaccine preference, previous COVID-19 experiences, and demographics, which were summarized using descriptive statistics to understand the study participants' backgrounds. In the DCE, participants were provided choice pairs: 1 set with and 1 without an "opt-out" option. Each participant viewed 11 unique vaccine profiles. Vaccine attributes consisted of type (messenger RNA or protein), level of protection against any or severe COVID-19, risk of side effects (common and serious), and potential coadministration of COVID-19 and influenza vaccines. Attribute level selections were included for protection and safety (degree of effectiveness and side effect risk, respectively). Participants were stratified by vaccination status (unvaccinated, or partially or fully vaccinated) and disease risk group (high-risk or non-high-risk). A conditional logit model was used to analyze DCE data to estimate preferences of vaccine attributes, with the percentage relative importance calculated to allow for its ranking. Each model was run twice to account for sets with and without the opt-out options.

resultsThe mean age of participants (N=2000) was 48 (SD 18.8) years, and 51.25% (1025/2000) were male. The DCE revealed that the most important COVID-19 vaccine attributes were protection against severe COVID-19 or any severity of COVID-19 and common side effects. Protection against severe COVID-19 was the most important attribute for fully vaccinated participants, which significantly differed from the unvaccinated or partially vaccinated subgroup (relative importance 34.8% vs 30.6%; P=.049). Avoiding serious vaccine side effects was a significantly higher priority for the unvaccinated or partially versus fully vaccinated subgroup (relative importance 10.7% vs 8.2%; P=.044). Attributes with significant differences in the relative importance between the high-risk versus non-high-risk subgroups were protection against severe COVID-19 (38.2% vs 31.5%; P<.000), avoiding common vaccine side effects (12% vs 20.5%; P<.000), and avoiding serious vaccine side effects (9.7% vs 7.5%; P=.002).

conclusionsThis DCE identified COVID-19 vaccine attributes, such as protection against severe COVID-19, that may influence preference and drive choice and can inform vaccine strategies. The high ranking of common and serious vaccine side effects suggests that, when the efficacy of 2 vaccines is comparable, safety is a key decision-making factor.

Indexed as

Choice BehaviorCOVID-19COVID-19 VaccinesAdolescentAdultAgedCanadaFemaleGermanyHumansMaleMiddle AgedPatient PreferenceSurveys and QuestionnairesUnited KingdomUnited StatesCOVID-19 VaccinesantivaccineCOVID-19COVID vaccinationdiscrete choice experimentimmunizationinformed decision-makingpreference elicitationSARS-CoV-2vaccine hesitancyvaccine side effects

Identifiers

PMID39412841
PMCPMC11525078

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.