Evidence map›Paper›PMID 40400658›Full record

ReviewCureus2025

Research Trends and Structural Characteristics of Healthcare Research in Japan, Including the First Half of the New Coronavirus Spread Period: A Bibliometric Analysis.

Yasutoshi Moteki

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Yasutoshi MotekiFaculty of Policy Studies, Nanzan University, Nagoya, JPN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to conduct a bibliometric analysis to characterize the trends and research features of health administration in Japan, in terms of themes and structural aspects, such as institutional affiliations, up to the early stages of the spread of the new coronavirus. Literature data were obtained from the United States National Institutes of Health (NIH) database, using the search formula (Healthcare[Title/Abstract] AND Japan[Title]), and the dataset was obtained on March 15, 2025. The total number of data points analyzed was 1066. Research trends, such as the characteristics of themes based on KeyWords Plus (Clarivate, Philadelphia, USA) and their changes, and the academic structure focusing on the country of origin, institutional affiliations, and publication journals, were quantitatively analyzed using the bibliometrics tools in the R package (Biblioshiney interface) for literature up to 2021, when the impact of coronavirus disease of 2019 (COVID-19) became pronounced in Japan. The KeyWords Plus analysis revealed a substantial research emphasis on healthcare human resources, and confirmed an increase in COVID-19-related research around 2020, when the impact of the novel coronavirus infection spread in Japan. Notably, the results of the bibliometric analysis highlight the aspect that healthcare human resources was one of the main focuses of the study area. However, limitations of textmining methods were observed in the export function of the CiNii database (National Institute of Informatics, Tokyo, Japan), which comprehensively collects articles written in Japanese. In order to grasp research trends in the field of healthcare in Japan, regardless of language, it is necessary to enhance multilingual support in Japanese academic information databases and develop an international academic information database (such as Web of Science, Scopus, OpenAlex, etc.) to expand the scope of collection.

Indexed as

academic structurebibliometrics analysisjapanresearch trendsthematic map

Identifiers

PMID40400658
PMCPMC12093193

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.