Evidence map›Paper›PMID 35257865›Full record

ArticleJoint bone spine2022

Fake news: Why do we believe it?

Catherine Beauvais

Abstract read
In one paragraph

Article in Joint bone spine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Health Misinformation Detection: Approaches, Challenges and Opportunities.Inquiry : a journal of medical care organization, provision and financing
    Review
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

1 author.

Catherine BeauvaisService de rhumatologie, hôpital Saint-Antoine. AP-HP. Sorbonne université, Paris, France. Electronic address: catherine.beauvais@aphp.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fake news dissemination has increased greatly in recent years, with peaks during the US presidential elections and the COVID-19 pandemic. Research has addressed fake news creation, consumption, sharing, and detection as well as approaches to counteract it and prevent people from believing it. This update addresses only a part of the fake news-related issues and focuses on determinants leading individuals to believe fake news, noting that rheumatology is scarcely represented. Some determinants relate to the ecosystem of media and social networks, such as the availability and rapid spread of fake news, the unselected information on platforms and the fact that consumers can become creators of fake news. Cognitive factors are important, such as confirmation bias, political partisanship, prior exposure and intuitive thinking. Low science knowledge and low educational level are also involved. Psychological factors include attraction to novelty, high emotional state, and the emotionally evocative content of fake news. High digital literacy protects against believing fake news. Sociological factors such as online communities, or echo chambers, and the role of pressure groups have been identified. The implication for practice can be deduced, including education in media literacy and warning tips, reliable journalism and fact-checking, social media regulation, partnership of media platforms' with fact-checkers, warning messages on networks, and digital detection solutions. Health professionals need to better understand the factors that cause individuals to believe fake news. Identifying these determinants may help them in their counseling role when talking to patients about misinformation.

Indexed as

COVID-19Social MediaDisinformationEcosystemHumansPandemicsCognitive biasFake newsMisinformationSocial networks

Identifiers

PMID35257865
PMCPMC9548403

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.