Evidence map›Paper›PMID 34970030›Full record

ArticleProceedings (Baylor University. Medical Center)2022

Alternative publication metrics in the time of COVID-19.

Christopher J Peterson, Caleb Anderson, Kenneth Nugent

Abstract read
In one paragraph

Article in Proceedings (Baylor University. Medical Center), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Christopher J PetersonSchool of Medicine, Texas Tech University Health Sciences Center, Lubbock, Texas.
Caleb AndersonDepartment of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, Texas.
Kenneth NugentDepartment of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, Texas.ORCID https://orcid.org/0000-0003-2781-4816

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alternative metrics are unique bibliometrics comprising social, news, and other sources of media outside of traditional academic citations. Some have suggested that these metrics can complement traditional metrics of research impact, including public engagement with research. The COVID-19 pandemic provides a unique opportunity to study alternative metrics and the dissemination of scientific research given the heightened academic and public interest. This study analyzed Altmetric Attention Scores for the top 25 publications on COVID-19 and the top 25 non-COVID-19 publications in 2020. There were significantly higher levels of social attention scores across multiple metrics for COVID-19 articles than for non-COVID-19 articles for that year. There was a slightly higher goodness of fit between Altmetric Attention Scores and academic citations for COVID-19 publications than for non-COVID-19 publications, although trendline differences were not significant. These results suggest that researchers should be aware that their studies can become highly visible on publicly available social and news media platforms, especially during events of high interest (such as a global pandemic).

Indexed as

Alternative metricsaltmetricbibliometricsCOVID-19

Identifiers

PMID34970030
PMCPMC8682825

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.