Evidence map›Paper›PMID 33057373›Full record

ArticlePLoS medicine2020

Risk of disease and willingness to vaccinate in the United States: A population-based survey.

Bert Baumgaertner, Benjamin J Ridenhour, Florian Justwan, Juliet E Carlisle, Craig R Miller

Abstract read
In one paragraph

Article in PLoS medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 2 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

58 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  9. Protective but Costly: The Impact of Behavioral Immune System Reactivity on Mental Health.International journal of environmental research and public health · 2025
    Article
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  13. The role of perceived risk on dishonest decision making during a pandemic.Risk analysis : an official publication of the Society for Risk Analysis · 2024
    Article
  14. Article
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  18. Heterogeneous risk tolerance, in-groups, and epidemic waves.Frontiers in applied mathematics and statistics · 2024
    Article
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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

5 authors.

Bert BaumgaertnerDepartment of Politics and Philosophy, University of Idaho, Moscow, Idaho, United States of America.ORCID 0000-0001-8803-4771
Benjamin J RidenhourDepartment of Mathematics, University of Idaho, Moscow, Idaho, United States of America.ORCID 0000-0001-8271-4629
Florian JustwanDepartment of Politics and Philosophy, University of Idaho, Moscow, Idaho, United States of America.ORCID 0000-0003-2822-4535
Juliet E CarlisleDepartment of Political Science, The University of Utah, Salt Lake City, Utah, United States of America.ORCID 0000-0001-7904-4505
Craig R MillerDepartment of Biology, University of Idaho, Moscow, Idaho, United States of America.

Funding

Sequence-structure-function relationships in human visual photopigmentsP20GM104420 · NIGMS · UNIVERSITY OF IDAHO · PI VAN LEUVEN, JAMES · 2015 to 2024
$22.9M
NIGMS NIH HHS P20 GM104420
6 · The paper itself

Abstract

backgroundVaccination complacency occurs when perceived risks of vaccine-preventable diseases are sufficiently low so that vaccination is no longer perceived as a necessary precaution. Disease outbreaks can once again increase perceptions of risk, thereby decrease vaccine complacency, and in turn decrease vaccine hesitancy. It is not well understood, however, how change in perceived risk translates into change in vaccine hesitancy. We advance the concept of vaccine propensity, which relates a change in willingness to vaccinate with a change in perceived risk of infection-holding fixed other considerations such as vaccine confidence and convenience. METHODS AND

findingsWe used an original survey instrument that presents 7 vaccine-preventable "new" diseases to gather demographically diverse sample data from the United States in 2018 (N = 2,411). Our survey was conducted online between January 25, 2018, and February 2, 2018, and was structured in 3 parts. First, we collected information concerning the places participants live and visit in a typical week. Second, participants were presented with one of 7 hypothetical disease outbreaks and asked how they would respond. Third, we collected sociodemographic information. The survey was designed to match population parameters in the US on 5 major dimensions: age, sex, income, race, and census region. We also were able to closely match education. The aggregate demographic details for study participants were a mean age of 43.80 years, 47% male and 53% female, 38.5% with a college degree, and 24% nonwhite. We found an overall change of at least 30% in proportion willing to vaccinate as risk of infection increases. When considering morbidity information, the proportion willing to vaccinate went from 0.476 (0.449-0.503) at 0 local cases of disease to 0.871 (0.852-0.888) at 100 local cases (upper and lower 95% confidence intervals). When considering mortality information, the proportion went from 0.526 (0.494-0.557) at 0 local cases of disease to 0.916 (0.897-0.931) at 100 local cases. In addition, we ffound that the risk of mortality invokes a larger proportion willing to vaccinate than mere morbidity (P = 0.0002), that older populations are more willing than younger (P<0.0001), that the highest income bracket (>$90,000) is more willing than all others (P = 0.0001), that men are more willing than women (P = 0.0011), and that the proportion willing to vaccinate is related to both ideology and the level of risk (P = 0.004). Limitations of this study include that it does not consider how other factors (such as social influence) interact with local case counts in people's vaccine decision-making, it cannot determine whether different degrees of severity in morbidity or mortality failed to be statistically significant because of survey design or because participants use heuristically driven decision-making that glosses over degrees, and the study does not capture the part of the US that is not online.

conclusionsIn this study, we found that different degrees of risk (in terms of local cases of disease) correspond with different proportions of populations willing to vaccinate. We also identified several sociodemographic aspects of vaccine propensity. Understanding how vaccine propensity is affected by sociodemographic factors is invaluable for predicting where outbreaks are more likely to occur and their expected size, even with the resulting cascade of changing vaccination rates and the respective feedback on potential outbreaks.

Indexed as

AdultFemaleHealth Knowledge, Attitudes, PracticeHumansImmunization ProgramsMaleMiddle AgedRisk FactorsSurveys and QuestionnairesUnited StatesVaccinationVaccinesVaccines

Identifiers

PMID33057373
PMCPMC7561115

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.