Evidence map›Paper›PMID 34203946›Full record

ArticleVaccines2021

Antivaccine Movement and COVID-19 Negationism: A Content Analysis of Spanish-Written Messages on Twitter.

Ivan Herrera-Peco, Beatriz Jiménez-Gómez, Carlos Santiago Romero Magdalena, Juan José Deudero, María García-Puente, Elvira Benítez De Gracia, Carlos Ruiz Núñez

Abstract read
In one paragraph

Article in Vaccines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

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

  1. Pooled it
  2. Pooled it
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  7. Twitter reveals spatio-temporal variation in vaccine concerns in Sub-Saharan Africa.medRxiv : the preprint server for health sciences · 2025
    Article
  8. Article
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  12. Article
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  14. Realfood and Cancer: Analysis of the Reliability and Quality of YouTube Content.International journal of environmental research and public health · 2023
    Observational
  15. Preface of Special Issue "21st Century Health Communication Challenges: Public Health Emergencies".European journal of investigation in health, psychology and education · 2023
    Article
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  19. Observational
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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

7 authors.

Ivan Herrera-PecoNursing Department, Faculty of Medicine, Alfonso X El Sabio University, 28691 Villanueva de la Cañada, 28040 Madrid, Spain.ORCID 0000-0002-5183-5679
Beatriz Jiménez-GómezNursing Department, Faculty of Medicine, Alfonso X El Sabio University, 28691 Villanueva de la Cañada, 28040 Madrid, Spain.
Carlos Santiago Romero MagdalenaFaculty of Health Sciences, Alfonso X el Sabio University, Avda Universidad, 1, 28691 Villanueva de la Cañada, 28040 Madrid, Spain.ORCID 0000-0002-3642-3422
Juan José DeuderoFaculty of Health Sciences, Alfonso X el Sabio University, Avda Universidad, 1, 28691 Villanueva de la Cañada, 28040 Madrid, Spain.
María García-PuenteFdn Jiménez Díaz, Avda. Reyes Católicos, 2, AlterBiblio, 28040 Madrid, Spain.ORCID 0000-0002-6521-665X
Elvira Benítez De GraciaFaculty of Health Sciences, Alfonso X el Sabio University, Avda Universidad, 1, 28691 Villanueva de la Cañada, 28040 Madrid, Spain.ORCID 0000-0002-7630-9624
Carlos Ruiz NúñezLoja High Resolution Hospital, APS Poniente, Av. Tierno Galván, Loja, 18300 Granada, Spain.ORCID 0000-0003-2872-1494

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the COVID-19 pandemic, different conspiracies have risen, with the most dangerous being those focusing on vaccines. Today, there exists a social media movement focused on destroying the credibility of vaccines and trying to convince people to ignore the advice of governments and health organizations on vaccination. Our aim was to analyze a COVID-19 antivaccination message campaign on Twitter that uses Spanish as the main language, to find the key elements in their communication strategy. Twitter data were retrieved from 14 to 28 December using NodeXL software. We analyzed tweets in Spanish, focusing on influential users, most influential tweets, and content analysis of tweets. The results revealed ordinary citizens who 'offer the truth' as the most important profile in this network. The content analysis showed antivaccine tweets (31.05%) as the most frequent. The analysis of anti-COVID19 tweets showed that attacks against vaccine safety were the most important (79.87%) but we detected a new kind of message presenting the vaccine as a means of manipulating the human genetic code (8.1%). We concluded that the antivaccine movement and its tenets have great influence in the COVID-19 negationist movement. We observed a new topic in COVID-19 vaccine hoaxes that must be considered in our fight against misinformation.

Indexed as

COVID-19fake newsmisinformationpublic healthTwittervaccines

Identifiers

PMID34203946
PMCPMC8232574

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.