ArticleCureus2023
Association of Non-traditional Indicators of Readers' Engagement With Traditional Dissemination Metrics of COVID-19-Related Research.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Which Topics Drive Dissemination? Alternative Bibliometrics Analysis of the Highest-Ranking Articles in 3 Infectious Diseases Journals Before COVID-19.Open forum infectious diseases · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionResearchers are increasingly interested in appraising the impact of their research work, which eventually drives public perception. The overall impact of a study can only be gauged if we consider both traditional and non-traditional dissemination patterns. Hence, we preferred to study the association between the non-traditional reader engagement metrics and traditional dissemination metrics in relation to coronavirus disease 2019 (COVID-19)-related research published in five high-impact peer-reviewed medical journals.
methodThis observational study was conducted using data sourced from Altmetric, including the Altmetric attention score (AAS), an aggregate score of an article's dissemination. New England Journal of Medicine (NEJM), Lancet Infectious Diseases, Clinical Infectious Diseases (CID), Chest Journal (CHEST), and Journal of the American Medical Association (JAMA) were included in the study based on the prevalence of COVID-19-related original research published in each of them. The number of citations was framed as the reference for traditional metrics. To avoid artificial variance, data were collected on the same day, November 13, 2022. Correlational analyses were performed using the Pearson correlation coefficient using Minitab 17 (Minitab Inc., State College, PA). The relationship between the variables was considered very weak if r<0.3, weak if r: 0.3 to 0.5, moderate if r: 0.5 to 0.7, and strong for r>0.7.
resultsWe found a very weak correlation between citations and AAS for Clinical Infectious Diseases, Lancet Infectious Diseases, and CHEST, whereas the correlation was moderate for NEJM and JAMA. The correlation between citations and Twitter mentions was very weak for Clinical Infectious Disease, Lancet Infectious Disease, and CHEST, but it improved for NEJM and JAMA. There was a very weak correlation between citations and news mentions for Clinical Infectious Diseases, Lancet Infectious Diseases, and CHEST.
conclusionOur study highlights that the traditional indicator, i.e., citation has a very weak to moderate correlation with the AAS and it doesn't capture the entire influence of a research publication. Also, the current method of determining a journal's impact factor doesn't take this disparity into consideration. Hence, there needs to have a more inclusive strategy to define the impact of scientific research on the general population in real-time.
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Registered trials
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.