Evidence map›Paper›PMID 33413219›Full record

ArticleBMC public health2021

Misinformation about COVID-19: evidence for differential latent profiles and a strong association with trust in science.

Jon Agley, Yunyu Xiao

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed, 3 pooled it
92.3field-weighted citation impact, top 1% of its field
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

102 citing papers in PubMed, 3 syntheses or guidelines pooled it, 271 citations in OpenAlex.

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  7. Article
  8. Susceptibility to Disinformation: A Data-Driven Typology Based on COVID-19 Hoaxes and Pro-Russian Propaganda.International journal of psychology : Journal international de psychologie · 2026
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  14. Mapping Infodemic Responses: A Geospatial Analysis of COVID-19 Discourse on Twitter in Italy.International journal of environmental research and public health · 2025
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  18. Journal of microbiology & biology education · 2024
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42 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Jon AgleyPrevention Insights, School of Public Health, Indiana University Bloomington, 809 E. 9th St., Bloomington, IN, 47405, USA. jagley@indiana.edu.ORCID 0000-0003-2345-8850
Yunyu XiaoSchool of Social Work, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA.
Indiana University Bloomington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe global spread of coronavirus disease 2019 (COVID-19) has been mirrored by diffusion of misinformation and conspiracy theories about its origins (such as 5G cellular networks) and the motivations of preventive measures like vaccination, social distancing, and face masks (for example, as a political ploy). These beliefs have resulted in substantive, negative real-world outcomes but remain largely unstudied.

methodsThis was a cross-sectional, online survey (n=660). Participants were asked about the believability of five selected COVID-19 narratives, their political orientation, their religious commitment, and their trust in science (a 21-item scale), along with sociodemographic items. Data were assessed descriptively, then latent profile analysis was used to identify subgroups with similar believability profiles. Bivariate (ANOVA) analyses were run, then multivariable, multivariate logistic regression was used to identify factors associated with membership in specific COVID-19 narrative believability profiles.

resultsFor the full sample, believability of the narratives varied, from a low of 1.94 (SD=1.72) for the 5G narrative to a high of 5.56 (SD=1.64) for the zoonotic (scientific consensus) narrative. Four distinct belief profiles emerged, with the preponderance (70%) of the sample falling into Profile 1, which believed the scientifically accepted narrative (zoonotic origin) but not the misinformed or conspiratorial narratives. Other profiles did not disbelieve the zoonotic explanation, but rather believed additional misinformation to varying degrees. Controlling for sociodemographics, political orientation and religious commitment were marginally, and typically non-significantly, associated with COVID-19 belief profile membership. However, trust in science was a strong, significant predictor of profile membership, with lower trust being substantively associated with belonging to Profiles 2 through 4.

conclusionsBelief in misinformation or conspiratorial narratives may not be mutually exclusive from belief in the narrative reflecting scientific consensus; that is, profiles were distinguished not by belief in the zoonotic narrative, but rather by concomitant belief or disbelief in additional narratives. Additional, renewed dissemination of scientifically accepted narratives may not attenuate belief in misinformation. However, prophylaxis of COVID-19 misinformation might be achieved by taking concrete steps to improve trust in science and scientists, such as building understanding of the scientific process and supporting open science initiatives.

Indexed as

Attitude to HealthCommunicable Disease ControlCommunicationCOVID-19PoliticsReligionTrustAdolescentAdultCross-Sectional StudiesFemaleFreedomHumansInternetLatent Class AnalysisLogistic ModelsConspiracy theoriesCoronavirusCOVID-19MisinformationTrust

Identifiers

PMID33413219
PMCPMC7789893
OpenAlexW3108023207

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.