ArticleHumanities & social sciences communications2025
Comparison of h-index and other bibliometrics in Google Scholar and Scopus for articles published by translational science trainees.
Article in Humanities & social sciences communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Bibliometrics can help program directors to conduct objective and fair assessments of scholar impact, progress, and collaboration, as well as benchmark performance against peers and programs. However, different academic search engines use different methodologies to provide bibliometric information, so intermixing results from multiple search engines might contribute to inequitable decision-making. Google Scholar and Scopus provide useful bibliometric information for scholars, including the h-index; however, a search of the literature revealed h-index was higher in Google Scholar than Scopus in other scholar populations; therefore, we hypothesized that h-index might also be higher in Google Scholar than Scopus for translational science (TS) trainees. Trained investigators gathered scholarly profile information from Google Scholar and Scopus for all trainees from NIH-supported TS PhD and TS Training (TST) Programs for predoctoral and postdoctoral trainees. Investigators calculated number of citations/year and m-quotient using the data contained therein. M-quotient was defined as h-index divided by "n," where "n" equaled the number of years since first publication. Investigators used the Wilcoxon Signed Rank test to compare bibliometrics (citations, citations/year, h-index, and m-quotient) from both sources for TS students and trainees. A total of 38 trainees (13 TS PhD students and 26 TST trainees) had active profiles in both Google Scholar and Scopus. Of the TST trainees, 21 were predoctoral and five were postdoctoral trainees. All four metrics (citations, citations/year, h-index, and m-quotient) were significantly higher (p<0.05) in Google Scholar than Scopus for the entire study population, TS PhD students, TST trainees, and TST predoctoral trainees. All four bibliometrics were numerically higher (but not significantly higher) in Google Scholar than Scopus for TST postdoctoral trainees as well. This is the first study to compare bibliometrics in Google Scholar and Scopus among translational science trainees. We discovered higher overall citation counts in Google Scholar. Significant differences between Google Scholar and SCOPUS in bibliometrics, such as h-index, could impact the decisions made by program directors if the results are intermixed. Stakeholders should be consistent in their choice of academic search engine and avoid cross engine comparisons, as failure to do so might contribute to inequitable decision-making.
Identifiers
What OpenQuestion holds
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.