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Whether productive authors using the national health insurance database also achieve higher individual research metrics: A bibliometric study.

作者信息

Hsieh Wan-Ting, Chien Tsair-Wei, Kuo Shu-Chun, Lin Hung-Jung

机构信息

Department of Family Medicine.

Medical Research Department, Chi-Mei Medical Center.

出版信息

Medicine (Baltimore). 2020 Jan;99(2):e18631. doi: 10.1097/MD.0000000000018631.


DOI:10.1097/MD.0000000000018631
PMID:31914046
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6959956/
Abstract

BACKGROUND: Many researchers use the National Health Insurance Research Database (HIRD) to publish medical papers and gain exceptional outputs in academics. Whether they also obtain excellent citation metrics remains unclear. METHODS: We searched the PubMed database (http://www.ncbi.nlm.nih.gov/pubmed) using the terms Taiwan and HIRD. We then downloaded 1997 articles published from 2012 to 2016. An authorship-weighted scheme (AWS) was applied to compute coauthor partial contributions from the article bylines. Both modified x-index and author impact factor (AIF) proved complementary to Hirsch's h-index for calculating individual research achievements (IRA). The metrics from 4684 authors were collected for comparison. Three hundred eligible authors with higher x-indexes were located and displayed on Google Maps dashboards. Ten separate clusters were identified using social network analysis (SNA) to highlight the research teams. The bootstrapping method was used to examine the differences in metrics among author clusters. The Kano model was applied to classify author IRAs into 3 parts. RESULTS: The most productive author was Investigator#1 (Taichung City, Taiwan), who published 149 articles in 2015 and included 803 other members in his research teams. The Kano diagram results did not support his citation metrics beyond other clusters and individuals in IRAs. CONCLUSION: The AWS-based bibliometric metrics make individual weighted research evaluations possible and available for comparison. The study results of productive authors using HIRD did not support the view that higher citation metrics exist in specific disciplines.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/7876894312eb/medi-99-e18631-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/64ae3e4229e9/medi-99-e18631-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/a6b4ec91302c/medi-99-e18631-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/60b66d54424e/medi-99-e18631-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/765dc5e52547/medi-99-e18631-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/cb7737512c9f/medi-99-e18631-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/b9bea43d027e/medi-99-e18631-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/7876894312eb/medi-99-e18631-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/64ae3e4229e9/medi-99-e18631-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/a6b4ec91302c/medi-99-e18631-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/60b66d54424e/medi-99-e18631-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/765dc5e52547/medi-99-e18631-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/cb7737512c9f/medi-99-e18631-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/b9bea43d027e/medi-99-e18631-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a44/6959956/7876894312eb/medi-99-e18631-g009.jpg

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引用本文的文献

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Analyzing author collaborations by developing a follower-leader clustering algorithm and identifying top co-authoring countries: Cluster analysis.

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[2]
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[3]
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[4]
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[5]
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本文引用的文献

[1]
Whether article types of a scholarly journal are different in cited metrics using cluster analysis of MeSH terms to display: A bibliometric analysis.

Medicine (Baltimore). 2019-10

[2]
Choropleth map legend design for visualizing the most influential areas in article citation disparities: A bibliometric study.

Medicine (Baltimore). 2019-10

[3]
Dengue outbreaks and the geographic distribution of dengue vectors in Taiwan: A 20-year epidemiological analysis.

Biomed J. 2018-11-9

[4]
Applying Gini coefficient to evaluate the author research domains associated with the ordering of author names: A bibliometric study.

Medicine (Baltimore). 2018-9

[5]
Using Google Maps to display the pattern of coauthor collaborations on the topic of schizophrenia: A systematic review between 1937 and 2017.

Schizophr Res. 2018-9-24

[6]
A novel bibliometric index with a simple geometric interpretation.

PLoS One. 2018-7-10

[7]
Visualizing Collaboration Characteristics and Topic Burst on International Mobile Health Research: Bibliometric Analysis.

JMIR Mhealth Uhealth. 2018-6-5

[8]
Recognizing spatial and temporal clustering patterns of dengue outbreaks in Taiwan.

BMC Infect Dis. 2018-6-4

[9]
Fair ranking of researchers and research teams.

PLoS One. 2018-4-5

[10]
Inappropriate Authorship and Kinship in Research Evaluation.

J Korean Med Sci. 2018-3-26

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