Evidence map›Paper›PMID 40116851›Full record

ArticleJournal of medical Internet research2025

Quantifying Public Engagement With Science and Malinformation on COVID-19 Vaccines: Cross-Sectional Study.

David Robert Grimes, David H Gorski

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

David Robert Grimes *TCD Biostatistics Unit, School of Medicine, Trinity College Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0003-3140-3278
David H Gorski *Michael and Marian Ilitch Department of Surgery, Wayne State University, Detroit, MI, United States.ORCID https://orcid.org/0000-0002-9805-6699

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundMedical journals are critical vanguards of research, and previous years have seen increasing public interest in and engagement with medicoscientific findings. How findings propagate and are understood and what harms erroneous claims might cause to public health remain unclear, especially on publicly contentious topics like COVID-19 vaccines. Gauging the engagement of the public with medical science and quantifying propagation patterns of medicoscientific papers are thus important undertakings. In contrast to misinformation and disinformation, which pivot on falsehood, the more nuanced issue of malinformation, where ostensibly true information is presented out of context or selectively curated to cause harm and misconception, has been less researched. As findings and facts can be selectively marshaled to present a misleading picture, it is crucial to consider this issue and its potential ramifications.

objectiveThis study aims to quantify patterns of public engagement with medical research and the vectors of propagation taken by a high-profile incidence of medical malinformation.

methodsIn this work, we undertook an analysis of all altmetric engagements over a decade for 5 leading general-purpose medical journals, constituting approximately 9.8 million engagements with 84,529 papers. We identify and examine the proliferation of sentiment concerning a high-profile publication containing vaccine-negative malinformation. Engagement with this paper, with the highest altmetric score of any paper in an academic journal ever released, was tracked across media outlets worldwide and in social media users on Twitter (subsequently rebranded as X). Vectoring media sources were analyzed, and manual sentiment analysis on high-engagement Twitter shares of the paper was undertaken, contrasted with users' prior vaccine sentiment.

resultsResults of this analysis suggested that this COVID-19 scientific malinformation was much more likely to be engaged and amplified with negative by vaccine-negative Twitter accounts than neutral ones (odds ratio 58.2, 95% CI 9.7-658.0; P<.001), often alluding to the ostensible prestige of medical journals. Malinformation was frequently invoked by conspiracy theory websites and non-news sources (71/181 citations, 39.2%) on the internet to cast doubt on the efficacy of vaccination, many of whom tended to cite the paper repeatedly (51/181, 28.2%).

conclusionsOur findings suggest growing public interest in medical science and present evidence that medical and scientific journals need to be aware of not only the potential overt misinformation but also the more insidious impact of malinformation. Also, we discuss how journals and scientific communicators can reduce the influence of malinformation on public understanding.

Indexed as

CommunicationCOVID-19COVID-19 VaccinesCross-Sectional StudiesHumansInformation DisseminationSARS-CoV-2Social MediaCOVID-19 Vaccinesaltmetric analysisaltmetricscomparative analysisdigital healthdisinformationhealth informaticsmalinformationmedical journalsmedicoscientificmHealthmisinformationmobile healthpublic engagementpublic healthsocial mediaTwittervaccine

Identifiers

PMID40116851
PMCPMC11971574

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.