Evidence map›Paper›PMID 33754507›Full record

ReviewJournal of Korean medical science2021

Article-Level Metrics.

Armen Yuri Gasparyan, Marlen Yessirkepov, Alexander A Voronov, Artur A Maksaev, George D Kitas

Abstract readReview
In one paragraph

Review in Journal of Korean medical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Harnessing the True Power of Altmetrics to Track Engagement.Journal of Korean medical science · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Modern Health Journalism and the Impact of Social Media.Journal of Korean medical science · 2021
    Article
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

5 authors.

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, UK. a.gasparyan@gmail.com.ORCID https://orcid.org/0000-0001-8749-6018
Marlen YessirkepovDepartment of Biology and Biochemistry, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.ORCID https://orcid.org/0000-0003-2511-6918
Alexander A VoronovDepartment of Marketing and Trade Deals, Kuban State University, Krasnodar, Russia.ORCID https://orcid.org/0000-0001-8505-7345
Artur A MaksaevDepartment of Management and Trade Deal, Krasnodar Cooperative Institute, Branch of Russian University of Cooperation, Krasnodar, Russia.ORCID https://orcid.org/0000-0002-6417-8807
George D KitasDepartments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, UK.ORCID https://orcid.org/0000-0002-0828-6176

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of digitization and Open Access, article-level metrics are increasingly employed to distinguish influential research works and adjust research management strategies. Tagging individual articles with digital object identifiers allows exposing them to numerous channels of scholarly communication and quantifying related activities. The aim of this article was to overview currently available article-level metrics and highlight their advantages and limitations. Article views and downloads, citations, and social media metrics are increasingly employed by publishers to move away from the dominance and inappropriate use of journal metrics. Quantitative article metrics are complementary to one another and often require qualitative expert evaluations. Expert evaluations may help to avoid manipulations with indiscriminate social media activities that artificially boost altmetrics. Values of article metrics should be interpreted in view of confounders such as patterns of citation and social media activities across countries and academic disciplines.

Indexed as

PublishingBibliometricsJournal Impact FactorResearch DesignScholarly CommunicationSocial MediaAccess to InformationBibliography as TopicBibliometricsOpen Access PublishingPeriodicals as Topic

Identifiers

PMID33754507
PMCPMC7985291

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.