Evidence map›Paper›PMID 37460761›Full record

SynthesisNature human behaviour2023

A taxonomy of anti-vaccination arguments from a systematic literature review and text modelling.

Angelo Fasce, Philipp Schmid, Dawn L Holford, Luke Bates, Iryna Gurevych, Stephan Lewandowsky

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Nature human behaviour, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

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

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Persistence of major socio-economic inequalities in childhood measles-mumps-rubella vaccination coverage and timeliness under vaccination mandates, France, 2015 to 2024.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

6 authors.

Angelo FasceFaculty of Medicine, University of Coimbra, Coimbra, Portugal. afc@fmed.uc.pt.ORCID 0000-0002-5019-4953
Philipp SchmidInstitute for Planetary Health Behaviour, University of Erfurt, Erfurt, Germany.ORCID 0000-0003-2966-0806
Dawn L HolfordSchool of Psychological Science, University of Bristol, Bristol, UK.ORCID 0000-0002-6392-3991
Luke BatesUbiquitous Knowledge Processing Lab/Department of Computer Science and Hessian Center for AI (hessian.AI), Technical University of Darmstadt, Darmstadt, Germany.
Iryna GurevychUbiquitous Knowledge Processing Lab/Department of Computer Science and Hessian Center for AI (hessian.AI), Technical University of Darmstadt, Darmstadt, Germany.
Stephan LewandowskySchool of Psychological Science, University of Bristol, Bristol, UK.ORCID 0000-0003-1655-2013

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proliferation of anti-vaccination arguments is a threat to the success of many immunization programmes. Effective rebuttal of contrarian arguments requires an approach that goes beyond addressing flaws in the arguments, by also considering the attitude roots-that is, the underlying psychological attributes driving a person's belief-of opposition to vaccines. Here, through a pre-registered systematic literature review of 152 scientific articles and thematic analysis of anti-vaccination arguments, we developed a hierarchical taxonomy that relates common arguments and themes to 11 attitude roots that explain why an individual might express opposition to vaccination. We further validated our taxonomy on coronavirus disease 2019 anti-vaccination misinformation, through a combination of human coding and machine learning using natural language processing algorithms. Overall, the taxonomy serves as a theoretical framework to link expressed opposition of vaccines to their underlying psychological processes. This enables future work to develop targeted rebuttals and other interventions that address the underlying motives of anti-vaccination arguments.

Indexed as

COVID-19VaccinesCommunicationDissent and DisputesHumansVaccinationVaccines

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.