Statistical misreasoning in online content about vaccines: Implications and recommendations for addressing disinformation

Michal Ordak

PLOS ONE, 2026, vol. 21, issue 8, 1-14

Abstract: Background: Statistical misreasoning is a key mechanism through which anti-vaccine narratives distort scientific information and undermine public confidence in immunisation. Although prior research has examined thematic and ideological features of vaccine misinformation, little is known about the specific errors in numerical reasoning that shape users’ interpretations of vaccine-related data. Methods: A total of 597 Polish-language Facebook posts expressing anti-vaccine views and containing references to statistical information were analysed. Based on previous research on statistical cognition and an inductive review of the material, a coding scheme comprising ten categories of statistical misreasoning was developed and applied to all posts. Quantitative analyses were then conducted to examine how frequently these categories occurred and which combinations of errors appeared together. Results: The most prevalent forms of misreasoning were the correlation–causation fallacy (70%, p

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355341 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 55341&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0355341

DOI: 10.1371/journal.pone.0355341

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().