Evidence map›Paper›PMID 32657090›Full record

ArticleJournal of Korean medical science2020

Information and Misinformation on COVID-19: a Cross-Sectional Survey Study.

Latika Gupta, Armen Yuri Gasparyan, Durga Prasanna Misra, Vikas Agarwal, Olena Zimba, Marlen Yessirkepov

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 1 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

74 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  9. Article
  10. Notes from Self-Isolation: Imagination in Times of Ruptures.Integrative psychological & behavioral science · 2025
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  13. Review
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  16. YouTube as a Source of Information on Public Health Ethics.Journal of Korean medical science · 2024
    Article
  17. Review
  18. Article
  19. Article
  20. Article

14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Latika GuptaDepartment of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.ORCID https://orcid.org/0000-0003-2753-2990
Armen Yuri GasparyanDepartments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, West Midlands, UK. a.gasparyan@gmail.com.ORCID https://orcid.org/0000-0001-8749-6018
Durga Prasanna MisraDepartment of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.ORCID https://orcid.org/0000-0002-5035-7396
Vikas AgarwalDepartment of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.ORCID https://orcid.org/0000-0002-4508-1233
Olena ZimbaDepartment of Internal Medicine No. 2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.ORCID https://orcid.org/0000-0002-4188-8486
Marlen YessirkepovDepartment of Biology and Biochemistry, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.ORCID https://orcid.org/0000-0003-2511-6918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe coronavirus disease 2019 (COVID-19) pandemic has led to a large volume of publications, a barrage of non-reviewed preprints on various professional repositories and a slew of retractions in a short amount of time.

methodsWe conducted an e-survey using a cloud-based website to gauge the potential sources of trustworthy information and misinformation and analyzed researchers', clinicians', and academics' attitude toward unpublished items, and pre- and post-publication quality checks in this challenging time.

resultsAmong 128 respondents (mean age, 43.2 years; M:F, 1.1:1), 60 (46.9%) were scholarly journal editors and editorial board members. Social media channels were distinguished as the most important sources of information as well as misinformation (81 [63.3%] and 86 [67.2%]). Nearly two in five (62, 48.4%) respondents blamed reviewers, editors, and misinterpretation by readers as additional contributors alongside authors for misinformation. A higher risk of plagiarism was perceived by the majority (70, 58.6%), especially plagiarism of ideas (64.1%) followed by inappropriate paraphrasing (54.7%). Opinion was divided on the utility of preprints for changing practice and changing retraction rates during the pandemic period, and higher rejections were not supported by most (76.6%) while the importance of peer review was agreed upon by a majority (80, 62.5%). More stringent screening by journal editors (61.7%), and facilitating open access plagiarism software (59.4%), including Artificial Intelligence (AI)-based algorithms (43.8%) were among the suggested solutions. Most (74.2%) supported the need to launch a specialist bibliographic database for COVID-19, with information indexed (62.3%), available as open-access (82.8%), after expanding search terms (52.3%) and following due verification by academics (66.4%), and journal editors (52.3%).

conclusionWhile identifying social media as a potential source of misinformation on COVID-19, and a perceived high risk of plagiarism, more stringent peer review and skilled post-publication promotion are advisable. Journal editors should play a more active role in streamlining publication and promotion of trustworthy information on COVID-19.

Indexed as

CommunicationPublishingScientific MisconductSocial MediaAdultBetacoronavirusCoronavirus InfectionsCOVID-19Cross-Sectional StudiesFemaleHumansMalePandemicsPeer ReviewPlagiarismPneumonia, ViralCoronavirus Disease 2019COVID-19InformationPeriodicals as TopicPublishingSocial Media

Identifiers

PMID32657090
PMCPMC7358067

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.