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Chou W, Chow JC. Identifying authorial roles in research: A Kano model-based bibliometric analysis for the Journal of Medicine (Baltimore) 2023. Medicine (Baltimore) 2024; 103:e39234. [PMID: 39213241 PMCID: PMC11365613 DOI: 10.1097/md.0000000000039234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 04/21/2024] [Accepted: 07/18/2024] [Indexed: 09/04/2024] Open
Abstract
The landscape of research roles within academic journals often remains uncharted territory, with authorial contributions frequently reduced to linear hierarchies (e.g., professor and assistant professor). The Kano model, traditionally used in customer satisfaction research, offers a nuanced framework for identifying the multifaceted roles of authors in scholarly publications. This study utilizes the Kano model to dissect and categorize the roles of authors in the medicine field. To conform to the hypothesis, China is the research leader while the US is the research collaborator, as reflected in the publications of the journal of Medicine (Baltimore) in the year 2023. We conducted a comprehensive bibliometric analysis of all research articles published in the journal of Medicine (Baltimore) in 2023. The Kano model was applied to classify authors into 5 categories reflective of their research roles: followers, leaders, partners, contributors, and collaborators. Data on author publications and co-authorship networks with multi-author rates (MARs) were analyzed to assign Kano categories based on the authorship positions of first and corresponding authors. Descriptive statistics and network analysis tools were used to interpret the data, including radar plots, geographical maps, and Kano diagrams. The analysis covered 1976 articles, uncovering a complex network of author roles that extends beyond the conventional binary distinction of lead and supporting authors (i.e., leading, and following researchers). A research leader in China and a collaborator in the US were conformed to support the hypothesis, based on their publications (1148 vs 51) and MARs (12.20% vs 19.61%). The Kano classification was visually adapted to classify authors (or entities) into 5 categories. The combined choropleth and geographical network maps were illustrated to identify author roles in research briefly. The Kano model serves as an effective tool for uncovering the diverse contributions of authors in medical research. By moving beyond the lead and follower dichotomy, this study highlights the intricate ecosystem of authorial roles, emphasizing the importance of each in advancing knowledge within the field of medicine. Future application of the Kano model could foster a more collaborative and inclusive recognition of contributions across various disciplines.
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Affiliation(s)
- Willy Chou
- Department of Physical Medicine and Rehabilitation, Chiali Chi-Mei Hospital, Tainan, Taiwan
- Department of Leisure and Sports Management, Far East University, Tainan, Taiwan
| | - Julie Chi Chow
- Department of Pediatrics, Chi-Mei Medical Center, Tainan, Taiwan
- Department of Pediatrics, School of Medicine, College of Medicine, Chung Shan Medical University, Taichung, Taiwan
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Jang FL, Chien TW, Chou W. Thematic maps with scatter and 4-quadrant plots in R to identity dominant entities on schizophrenia in psychiatry since 2017: Bibliometric analysis. Medicine (Baltimore) 2023; 102:e36041. [PMID: 37986352 PMCID: PMC10659646 DOI: 10.1097/md.0000000000036041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/18/2023] [Accepted: 10/19/2023] [Indexed: 11/22/2023] Open
Abstract
BACKGROUND Schizophrenia affects more than 21 million people worldwide. There have been a number of articles published in the literature regarding schizophrenia. It is unclear which authors contributed the most to the field of schizophrenia. This study examines which article entities (affiliated countries, institutes, journals, and authors) earn the most research achievements (RAs) and whether keywords in articles are associated with the number of article citations. METHODS As of August 25, 2022, 20,606 abstracts published on schizophrenia in psychiatry since 2017 were retrieved from the WoS core collection (WoSCC). RAs were measured using the category, JIF, authorship, and L-index (CJAL) score. The follower-leading cluster algorithm (FLCA) was used to examine clusters of keywords associated with core concepts of research. There were 7 types of visualizations used to report the study results, including Sankey diagrams, choropleth maps, scatter charts, radar plots, and cluster plots. A hypothesis was examined that the mean number of citations for keywords could predict the number of citations for 100 top-cited articles(T100SCHZ). RESULTS The results indicate that the US (18861), Kings College London (U.S. (2572), Psychiatry (14603), and Kolanu Nithin (Australia) (9.88) had the highest CJAL scores in countries, institutes, departments, and authors, respectively. The journal of Schizophrenia Res had higher citations (19,017), counts (1681), and mean citations (11.31) in journals. There was a significant correlation between article citations and weighted keywords (F = 1471.74; P < .001). CONCLUSION Seven visualizations were presented to report the study results, particularly with thematic maps using scatter and 4-quadrant plots produced in R programming language. We recommend that more future bibliographical studies utilize CAJL scores and thematic maps to report their findings, not restrict themselves solely to schizophrenia in psychiatry as done in this study.
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Affiliation(s)
- Fong-Lin Jang
- Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chi Mei Medical Center, Tainan, Taiwan
- Department of Physical Medicine and Rehabilitation, Chung San Medical University Hospital, Taichung (400), Taiwan
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Hsiung C, Chou W, Chien TW, Chou PH. Differences in productivity and collaboration patterns on spine-related research between neurosurgeons and orthopedic spine surgeons: Bibliometric analysis. Medicine (Baltimore) 2023; 102:e35563. [PMID: 37861477 PMCID: PMC10589607 DOI: 10.1097/md.0000000000035563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 09/18/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Spinal surgeries are commonly performed by neurosurgeons and orthopedic spine surgeons, with many spine-related articles published by them. However, there has been limited research that directly compares their research achievements. This article conducted a comparative analysis of spine-related research achievements between neurosurgeons and orthopedic spine surgeons. This study examines differences in productivity and impact on spine-related research between them using these measures, particularly with a novel clustering algorithm. METHODS We gathered 2148 articles written by neurosurgeons and orthopedic spine surgeons from the Web of Science core collections, covering the period from 2013 to 2022. To analyze author collaborations, we employed the follower-leader clustering algorithm (FLCA) and conducted cluster analysis. A 3-part analysis was carried out: cluster analysis of author collaborations; mean citation analysis; and a category, journal, authorship, L-index (CJAL) score based on article category, journal impact factors, authorships, and L-indices. We then utilized R to create visual displays of our findings, including circle bar charts, heatmaps with dendrograms, 4-quadrant radar plots, and forest plots. The mean citations and CJAL scores were compared between neurosurgeons and orthopedic spine surgeons. RESULTS When considering first and corresponding authors, orthopedics authors wrote a greater proportion of the articles in the article collections, accounting for 75% (1600 out of 2148). The CJAL score based on the top 10 units each also favored orthopedic spine surgeons, with 71% (3626 out of 6139) of the total score attributed to them. Using the FLCA, we observed that orthopedic spine surgeons tended to have more collaborations across countries. Additionally, while citation per article favored orthopedic spine surgeons with standard mean difference (= -0.66) and 95%CI: -0.76, -0.56, the mean CJAL score in difference (= 0.34) favored neurosurgeons with 95%CI: 0.24 0.44. CONCLUSION Orthopedic spine surgeons have a higher number of publications, citations, and CJAL scores in spine research than those in neurosurgeons. Orthopedic spine surgeons tend to have more collaborations and coauthored papers in the field. The study highlights the differences in research productivity and collaboration patterns between the 2 authors in spine research and sheds light on potential contributing factors. The study recommends the use of FLCA for future bibliographical studies.
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Affiliation(s)
- Chun Hsiung
- Department of Education, Chang Gung Memorial Hospital, Linkou, Taiwan
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chi Mei medical center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Medical Research Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Po-Hsin Chou
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University Taipei, Taipei, Taiwan
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Cheng TY, Ho SYC, Chien TW, Chow JC, Chou W. A comprehensive approach for clustering analysis using follower-leading clustering algorithm (FLCA): Bibliometric analysis. Medicine (Baltimore) 2023; 102:e35156. [PMID: 37861508 PMCID: PMC10589539 DOI: 10.1097/md.0000000000035156] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 08/18/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND There are 3 issues in bibliometrics that need to be addressed: The lack of a clear definition for author collaborations in cluster analysis that takes into account collaborations with and without self-connections; The need to develop a simple yet effective clustering algorithm for use in coword analysis, and; The inadequacy of general bibliometrics in regard to comparing research achievements and identifying articles that are worth reading and recommended for readers. The study aimed to put forth a clustering algorithm for cluster analysis (called following leader clustering [FLCA], a follower-leading clustering algorithm), examine the dissimilarities in cluster outcomes when considering collaborations with and without self-connections in cluster analysis, and demonstrate the application of the clustering algorithm in bibliometrics. METHODS The study involved a search for articles and review articles published in JMIR Medical Informatics between 2016 and 2022, conducted using the Web of Science core collections. To identify author collaborations (ACs) and themes over the past 7 years, the study utilized the FLCA algorithm. With the 3 objectives of; Comparing the results obtained from scenarios with and without self-connections; Applying the FLCA algorithm in ACs and themes, and; Reporting the findings using traditional bibliometric approaches based on counts and citations, and all plots were created using R. RESULTS The study found a significant difference in cluster outcomes between the 2 scenarios with and without self-connections, with a 53.8% overlap (14 out of the top 20 countries in ACs). The top clusters were led by Yonsei University in South Korea, Grang Luo from the US, and model in institutes, authors, and themes over the past 7 years. The top entities with the most publications in JMIR Medical Informatics were the United States, Yonsei University in South Korea, Medical School, and Grang Luo from the US. CONCLUSION The FLCA algorithm proposed in this study offers researchers a comprehensive approach to exploring and comprehending the complex connections among authors or keywords. The study suggests that future research on ACs with cluster analysis should employ FLCA and R visualizations.
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Affiliation(s)
- Teng-Yun Cheng
- Department of Emergency Medicine, Chi Mei Medical Center, Liouying, Tainan, Taiwan
| | - Sam Yu-Chieh Ho
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Julie Chi Chow
- Department of Pediatrics, Chi Mei Medical Center, Tainan, Taiwan
- Department of Pediatrics, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chiali Chi-Mei Hospital, Tainan, Taiwan
- Department of Physical Medicine and Rehabilitation, Chung San Medical University Hospital, Taichung, Taiwan
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Lin CK, Ho SYC, Chien TW, Chou W, Chow JC. Analyzing author collaborations by developing a follower-leader clustering algorithm and identifying top co-authoring countries: Cluster analysis. Medicine (Baltimore) 2023; 102:e34158. [PMID: 37478228 PMCID: PMC10662898 DOI: 10.1097/md.0000000000034158] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 06/09/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND This study aimed to explore suitable clustering algorithms for author collaborations (ACs) in bibliometrics and investigate which countries frequently coauthored with others in recent years. To achieve this, the study developed a method called the Follower-Leading Clustering Algorithm (FLCA) and used it to analyze ACs and cowords in the Journal of Medicine (Baltimore) from 2020 to 2022. METHODS This study extracted article metadata from the Web of Science and used the statistical software R to implement FLCA, enabling efficient and reproducible analysis of ACs and cowords in bibliometrics. To determine the countries that easily coauthored with other countries, the study observed the top 20 countries each year and visualized the results using network charts, heatmaps with dendrograms, and Venn diagrams. The study also used chord diagrams to demonstrate the use of FLCA on ACs and cowords in Medicine (Baltimore). RESULTS The study observed 12,793 articles, including 5081, 4418, and 3294 in 2020, 2021, and 2022, respectively. The results showed that the FLCA algorithm can accurately identify clusters in bibliometrics, and the USA, China, South Korea, Japan, and Spain were the top 5 countries that commonly coauthored with others during 2020 and 2022. Furthermore, the study identified China, Sichuan University, and diagnosis as the leading entities in countries, institutes, and keywords based on ACs and cowords, respectively. The study highlights the advantages of using cluster analysis and visual displays to analyze ACs in Medicine (Baltimore) and their potential application to coword analysis. CONCLUSION The proposed FLCA algorithm provides researchers with a comprehensive means to explore and understand the intricate connections between authors or keywords. Therefore, the study recommends the use of FLCA and visualizations with R for future research on ACs with cluster analysis.
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Affiliation(s)
- Che-Kuang Lin
- Department of Cardiology, Chiali Chi-Mei Hospital, Tainan, Taiwan
| | - Sam Yu-Chieh Ho
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan
- Department of Geriatrics and Gerontology, ChiMei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chiali Chi-Mei Hospital, Tainan, Taiwan
- Department of Physical Medicine and Rehabilitation, Chung San Medical University Hospital, Taichung, Taiwan
| | - Julie Chi Chow
- Department of Pediatrics, Chi Mei Medical Center, Tainan, Taiwan
- Department of Pediatrics, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
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Yen PT, Chien TW, Chou W, Tsai KT. Using the Alluvial diagram to display variable characteristics for COVID-19 patients and research achievements on the topic of COVID-19, epidemiology, pathogenesis, and vaccine (CEPV): Bibliometric analysis. Medicine (Baltimore) 2023; 102:e33873. [PMID: 37352056 PMCID: PMC10289785 DOI: 10.1097/md.0000000000033873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 04/27/2023] [Accepted: 05/08/2023] [Indexed: 06/25/2023] Open
Abstract
BACKGROUND An Alluvial diagram illustrates the flow of values from one set to another. Edges (or links/connections) are the connections between nodes (or actors/ vertices). There has been an increase in the use of Alluvial deposits in medical research in recent years. However, there was no illustration of such research on the way to draw the Alluvial for the readers. Our objective was to demonstrate how to draw the Alluvial in Microsoft Excel by using 2 examples, including variable characteristics for COVID-19 patients and research achievements (RAs) on the topic of COVID-19, epidemiology, pathogenesis, and vaccine (CEPV), and provide an easy and friendly method of drawing the Alluvial in MS Excel. METHODS Blood samples were collected and analyzed from 485 infected individuals in Wuhan, China. An operational decision tree and 2 Alluvial diagrams were shown to be capable of identifying variable characteristics in COVID-19 patients. A second example is the 100 top-cited articles downloaded from the Web of Science core collection (WoSCC) on the CEPV topic. On the Alluvial diagram, the mean citations (=citations/publications) and x-index were used to identify the top 5 members with the highest RAs in each entity (country, institute, journal, and research area). Two examples (i.e., blood samples taken from 485 infected individuals in Wuhan, China, and 100 top-cited articles on the CEPV topic) were illustrated and compared with traditional visualizations without flow relationships between nodes. RESULTS The top members in entities with the x-index are U Arab Emirates (242), Jama-J. Am. Med. Assoc. (27.18), Lancet (58.34), San Francisco Va Med (178), and Chaolin Huang (189) in countries, institutes, departments, and authors, respectively. The most cited article with 1315 citations was written by Huang and his colleagues and published by Lancet in 2021. CONCLUSION This study generates several Alluvial diagrams as demonstrations. The tutorial material and MP4 video provided in the Excel module allow readers to draw the Alluvial on their own in an easy and friendly manner.
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Affiliation(s)
- Po-Tsung Yen
- Department of Plastic Surgery, Chiali Chi-Mei Hospital, Tainan, Taiwan
| | - Tsair-Wei Chien
- Medical Research Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chiali Chi-Mei Hospital, Tainan, Taiwan
- Department of Physical Medicine and Rehabilitation, Chung San Medical University Hospital, Taichung, Taiwan
| | - Kang-Ting Tsai
- Department of Geriatrics and Gerontology, ChiMei Medical Center, Tainan, Taiwan
- Center for Integrative Medicine, Chi Mei Medical Center, Tainan, Taiwan
- Department of Nursing, Chung Hwa University of Medical Technology, Tainan, Taiwan
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Hsu SY, Chien TW, Yeh YT, Kuo SC. Citation trends in ophthalmology articles and keywords in mainland China, Hong Kong, and Taiwan since 2013 using temporal bar graphs (TBGs): Bibliometric analysis. Medicine (Baltimore) 2022; 101:e32392. [PMID: 36596033 PMCID: PMC9803441 DOI: 10.1097/md.0000000000032392] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND We selected authors from mainland China, Hong Kong, and Taiwan (CHT) to examine citation trends on articles and keywords. The existence of suitable temporal bar graphs (TBGs) for displaying citation trends is unknown. It is necessary to enhance the traditional TBGs to provide readers with more information about the citation trend. The purpose of this study was to propose an advanced TBG that can be applied to understand the most worth-reading articles by ophthalmology authors in the CHT. METHODS Using the search engine of the Web of Science core collection, we conducted bibliometric analyses to examine the article citation trends of ophthalmology authors in CHT since 2013. A total of 6695 metadata was collected from articles and review articles. Using radar plots, the Y-index, and the combining the Y-index with the CJAL scores (CJAL) scores, we could determine the dominance of publications by year, region, institute, journal, department, and author. A choropleth map, a dot plot, and a 4-quadrant radar plot were used to visualize the results. A TBG was designed and provided for readers to display citation trends on articles and keywords. RESULTS We found that the majority of publications were published in 2017 (2275), Shanghai city (935), Sun Yat-Sen University (China) (689), the international journal Ophthalmology (1399), the Department of Ophthalmology (3035), and the author Peizeng Yang (Chongqing) (65); the highest CAJL scores were also from Guangdong (2767.22), Sun Yat-Sen University (China) (2147.35), and the Ophthalmology Department (7130.96); the author Peizeng Yang (Chongqing) (170.16) had the highest CAJL; and the enhanced TBG features maximum counts and recent growth trends that are not included in traditional TBGs. CONCLUSION Using the Y-index and the CJAL score compared with research achievements of ophthalmology authors in CHT, a 4-quadrant radar plot was provided. The enhanced TBGs and the CJAL scores are recommended for future bibliographical studies.
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Affiliation(s)
- Sheng-Yao Hsu
- Department of Ophthalmology, An Nan Hospital, China Medical University, Tainan, Taiwan
- Department of Optometry, Chung Hwa University of Medical Technology, Tainan, Taiwan
| | - Tsair-Wei Chien
- Medical Research Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Yu-Tsen Yeh
- Medical School, St. George’s, University of London, UK
| | - Shu-Chun Kuo
- Department of Optometry, Chung Hwa University of Medical Technology, Tainan, Taiwan
- Department of Ophthalmology, Chi-Mei Medical Center, Yong Kang, Tainan City, Taiwan
- * Correspondence: Shu-Chun Kuo, Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung Dist., Tainan 710, Taiwan (e-mail: )
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Using text mining and forest plots to identify similarities and differences between two spine-related journals based on medical subject headings (MeSH terms) and author-specified keywords in 100 top-cited articles. Scientometrics 2022. [DOI: 10.1007/s11192-022-04549-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Ho SYC, Chien TW, Huang CC, Tsai KT. A comparison of 3 productive authors' research domains based on sources from articles, cited references and citing articles using social network analysis. Medicine (Baltimore) 2022; 101:e31335. [PMID: 36343020 PMCID: PMC9646507 DOI: 10.1097/md.0000000000031335] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND An individual's research domain (RD) can be determined from objective publication data (e.g., medical subject headings and Medical Subject Headings (MeSH) terms) by performing social network analysis. Bibliographic coupling (such as cocitation) is a similarity metric that relies on citation analysis to determine the similarity in RD between 2 articles. This study compared RD consistency between articles as well as their cited references and citing articles (ARCs). METHODS A total of 1388 abstracts were downloaded from PubMed and authored by 3 productive authors. Based on the top 3 clusters in social network analysis, similarity in RD was observed by comparing their consistency using the major MeSH terms in author articles, cited references and citing articles (ARC). Impact beam plots with La indices were drawn and compared for each of the 3 authors. RESULTS Sung-Ho Jang (South Korea), Chia-Hung Kao (Taiwan), and Chin-Hsiao Tseng (Taiwan) published 445, 780, and 163 articles, respectively. Dr Jang's RD is physiology, and Dr Kao and Dr Tseng's RDs are epidemiology. We confirmed the consistency of the RD terms by comparing the major MeSH terms in the ARC. Their La indexes were 5, 5, and 6, where a higher value indicates more extraordinary research achievement. CONCLUSION RD consistency was confirmed by comparing the main MeSH terms in ARC. The 3 approaches of RD determination (based on author articles, the La index, and the impact beam plots) were recommended for bibliographical studies in the future.
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Affiliation(s)
- Sam Yu-Chieh Ho
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan
- Department of Geriatrics and Gerontology, Chi-Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Chien-Cheng Huang
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan
- Department of Emergency Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Kang-Ting Tsai
- Department of Geriatrics and Gerontology, Chi-Mei Medical Center, Tainan, Taiwan
- Center for Integrative Medicine, Chi Mei Medical Center, Tainan, Taiwan
- Department of Nursing, Chung Hwa University of Medical Technology, Tainan, Taiwan
- * Correspondence: Kang-Ting Tsai, Department of Geriatrics and Gerontology, Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung Dist, Tainan 710, Taiwan (e-mail: )
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Yang TY, Chien TW, Lai FJ. Citation analysis of the 100 top-cited articles on the topic of hidradenitis suppurativa since 2013 using Sankey diagrams: Bibliometric analysis. Medicine (Baltimore) 2022; 101:e31144. [PMID: 36343026 PMCID: PMC9646634 DOI: 10.1097/md.0000000000031144] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Hidradenitis suppurativa (HS) is a chronic, inflammatory and debilitating dermatosis characterized by painful nodules, sinus tracts and abscesses in apocrine gland-bearing areas that predominantly affect women worldwide. New therapeutic interventions based on the clinical manifestations of patients have recently been introduced in numerous articles. However, which countries, journals, subject categories, and articles have the ultimate influence remain unknown. This study aimed to display influential entities in 100 top-cited HS-related articles (T100HS) and investigate whether medical subject headings (i.e., MeSH terms) can be used to predict article citations. METHODS T100HS data were extracted from PubMed since 2013. Subject categories were classified by MeSH terms using social network analysis. Sankey diagrams were applied to highlight the top 10 influential entities in T100HS from the three aspects of publication, citations, and the composited score using the hT index. The difference in article citations across subject categories and the predictive power of MeSH terms on article citations in T100HS were examined using one-way analysis of variance and regression analysis. RESULTS The top three countries (the US, Italy, and Spain) accounts for 54% of the T100HS. The T100HS impact factor (IF) is 12.49 (IF = citations/100). Most articles were published in J Am Acad Dermatol (15%; IF = 18.07). Eight subject categories were used. The "methods" was the most frequent MeSH term, followed by "surgery" and "therapeutic use". Saunte et al, from Roskilde Hospital, Denmark, had 149 citations in PubMed for the most cited articles. Sankey diagrams were used to depict the network characteristics of the T100HS. Article citations did not differ by subject category (F(7, 92) = 1.97, P = .067). MeSH terms were evident in the number of article citations predicted (F(1, 98) = 129.1106; P < .001). CONCLUSION We achieved a breakthrough by displaying the characteristics of the T100HS network on the Sankey diagrams. MeSH terms may be used to classify articles into subject categories and predict T100HS citations. Future studies can apply the Sankey diagram to the bibliometrics of the 100 most-cited articles.
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Affiliation(s)
- Ting-Ya Yang
- Department of Family Medicine, Chi-Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Feng-Jie Lai
- Department of Dermatology, Chi-Mei Medical Center, Tainan, Taiwan
- * Correspondence: Feng-Jie Lai, Department of Dermatology, Chi-Mei Medical Center, No. 901, Zhonghua Rd., Yongkang Dist., Tainan City 710, Tainan, Taiwan (e-mail: )
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Yeh CH, Chien TW, Lin JCJ, Chou PH. Comparing the similarity and differences in MeSH terms associated with spine-specific journals using the forest plot: A bibliometric analysis. Medicine (Baltimore) 2022; 101:e31441. [PMID: 36343077 PMCID: PMC9646558 DOI: 10.1097/md.0000000000031441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND A common concern in the literature is the comparison of the similarities and differences between research journals, as well as the types of research they publish. At present, there are no clear methodologies that can be applied to a given article of interest. When authors use an effective and efficient method to locate journals in similar fields, they benefit greatly. By using the forest plot and major medical subject headings (MeSH terms) of Spine (Phila Pa 1976) compared to Spine J, this study: displays relatively similar journals to the target journal online and identifies the effect of the similarity odds ratio of Spine (Phila Pa 1976) compared to Spine J. METHODS From the PubMed library, we downloaded 1000 of the most recent top 20 most similar articles related to Spine (Phila Pa 1976) and then plotted the clusters of related journals using social network analysis (SNA). The forest plot was used to compare the differences in MeSH terms for 2 journals (Spine (Phila Pa 1976) and Spine J) based on odds ratios. The heterogeneity of the data was evaluated using the Q statistic and the I-square (I2) index. RESULTS This study shows that: the journals related to Spine (Phila Pa 1976) can easily be presented on a dashboard via Google Maps; 8 journal clusters were identified using SNA; the 3 most frequently searched MeSH terms are surgery, diagnostic imaging, and methods; and the odds ratios of MeSH terms only show significant differences with the keyword "surgery" between Spine (Phila Pa 1976) and Spine J with homogeneity at I2 = 17.7% (P = .27). CONCLUSIONS The SNA and forest plot provide a detailed overview of the inter-journal relationships and the target journal using MeSH terms. Based on the findings of this research, readers are provided with knowledge and concept diagrams that can be used in future submissions to related journals.
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Affiliation(s)
- Chao-Hung Yeh
- Department of Neurosurgery, Chi Mei Medical Center, Tainan, Taiwan
- Department of Optometry, Chung Hwa University of Medical Technology, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi Mei Medical Center, Tainan, Taiwan
| | | | - Po-Hsin Chou
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan, R.O.C
- * Correspondence: Po-Hsin Chou, Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan and School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan (e-mail: )
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Wang HY, Chien TW, Kan WC, Wang CY, Chou W. Authors who contributed most to the fields of hemodialysis and peritoneal dialysis since 2011 using the hT-index: Bibliometric analysis. Medicine (Baltimore) 2022; 101:e30375. [PMID: 36197241 PMCID: PMC9509042 DOI: 10.1097/md.0000000000030375] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The h-index does not take into account the full citation list of a researcher to evaluate individual research achievements (IRAs). As a generalization of the h-index, the hT-index takes all citations into account to evaluate IRAs. Compared to other bibliometric indices, it is unclear whether the hT-index is more closely associated with the h-index. We utilized articles published on hemodialysis and peritoneal dialysis (HD/PD) to validate the hT-index as a measure of the most significant contributions to HD/PD. METHODS Using keywords involving HD/PD in titles, subject areas, and abstracts since 2011, we obtained 7702 abstracts and their associated metadata (e.g., citations, authors, research institutes, countries of origin). In total, 4752 first or corresponding authors with hT-indices >0 were evaluated. To present the author's IRA, the following 4 visualizations were used: radar, Sankey, impact beam plot, and choropleth map to investigate whether the hT-index was more closely associated with the h-index than other indices (e.g., g-/x-indices and author impact factors), whether the United States still dominates the majority of publications concerning PD/HD, and whether there was any difference in research features between 2 prolific authors. RESULTS In HD/PD articles, we observed that (a) the hT-index was closer to and associated with the h-index; (b1) the United States (37.15), China (34.63), and Japan (28.09) had the highest hT-index; (b2) Sun Yat Sen University (Chian) earned the highest hT-index (=20.02) among research institutes; (c1) the authors with the highest hT-indices (=15.64 and 14.39, respectively) were David W Johnson (Australia) and Andrew Davenport (UK); and (c2) their research focuses on PD and HD, respectively. CONCLUSION The hT-index was demonstrated to be appropriate for assessing IRAs along with visualizations. The hT-index is recommended in future bibliometric analyses of IRAs as a complement to the h-index.
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Affiliation(s)
- Hsien-Yi Wang
- Department of Sport Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan
- Ncphrology Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Wei-Chih Kan
- Department of Sport Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan
- Department of Biological Science and Technology, Chung Hwa University of Medical Technology, Tainan, Taiwan
| | | | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chiali Chi-Mei Hospital, Tainan, Taiwan
- Department of Physical Medicine and Rehabilitation, Chung San Medical University Hospital, Taichung, Taiwan
- *Correspondence: Willy Chou, Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung Dist., Tainan 710, Taiwan (e-mail: )
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Li MJ, Chien TW, Liao KW, Lai FJ. Using the Sankey diagram to visualize article features on the topics of whole-exome sequencing (WES) and whole-genome sequencing (WGS) since 2012: Bibliometric analysis. Medicine (Baltimore) 2022; 101:e30682. [PMID: 36197161 PMCID: PMC9509026 DOI: 10.1097/md.0000000000030682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Sequencing technologies, such as whole-exome sequencing (WES) and whole-genome sequencing (WGS), have been increasingly applied to medical research in recent years. Which countries, journals, and institutes (called entities) contributed most to the fields (WES/WGS) remains unknown. Temporal bar graphs (TBGs) are frequently used in trend analysis of publications. However, how to draw the TBG on the Sankey diagram is not well understood in bibliometrics. We thus aimed to investigate the evolution of article entities in the WES/WGS fields using publication-based TBGs and compare the individual research achievements (IRAs) among entities. METHODS A total of 3599 abstracts downloaded from icite analysis were matched to entities, including article identity numbers, citations, publication years, journals, affiliated countries/regions of origin, and medical subject headings (MeSH terms) in PubMed on March 12, 2022. The relative citation ratio (RCR) was extracted from icite analysis to compute the hT index (denoting the IRA, taking both publications and citations into account) for each entity in the years between 2012 and 2021. Three types of visualizations were applied to display the trends of publications (e.g., choropleth maps and the enhanced TBGs) and IRAs (e.g., the flowchart on the Sankey diagram) for article entities in WES/WGS. RESULTS We observed that the 3 countries (the US, China, and the UK) occupied most articles in the WES/WGS fields since 2012, the 3 entities (i.e., top 5 journals, research institutes, and MeSH terms) were demonstrated on the enhanced TBGs, the top 2 MeSH terms were genetics and methods in WES and WGS, and the IRAs of 6 article entities with their hT-indices were succinctly and simultaneously displayed on a single Sankey diagram that was never launched in bibliographical studies. CONCLUSION The number of WES/WGS-related articles has dramatically increased since 2017. TBGs, particularly with hTs on the Sankey, are recommended for research on a topic (or in a discipline) to compare trends of publications and IRAs for entities in future bibliographical studies.
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Affiliation(s)
- Meng-Ju Li
- Department of Pediatrics, National Taiwan University Hsin-Chu Hospital, Hsinchu, Taiwan
- Department of Biological Science and Technology, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Kuang-Wen Liao
- Department of Biological Science and Technology, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Institute of Molecular Medicine and Bioengineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Feng-Jie Lai
- Department of Dermatology, Chi Mei Medical Center, Tainan, Taiwan
- Center for General Education, Southern Taiwan University of Science and Technology, Tainan, Taiwan
- *Correspondence: Feng-Jie Lai, Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung Dist., Tainan 710, Taiwan (e-mail: )
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Yeh CH, Chien TW, Chou PH. Citation analysis of the 100 top-cited articles on discectomy via endoscopy since 2011 using alluvial diagrams: bibliometric analysis. Eur J Med Res 2022; 27:169. [PMID: 36050803 PMCID: PMC9438267 DOI: 10.1186/s40001-022-00782-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/04/2022] [Indexed: 12/18/2022] Open
Abstract
Background Percutaneous endoscopic lumbar discectomy (PELD) is synonymous with percutaneous endoscopic transforaminal discectomy (PETD) and percutaneous endoscopic interlaminar discectomy (PEID). PEID has gained increasing recognition for its small incision, quick recovery, short hospital stay, and equivalent clinical outcome to open surgery. Numerous articles related to PEID have been published in the literature. However, which countries, journals, subject categories, and articles have ultimate influence remains unknown. The study aimed to (1) display influential entities in 100 top-cited PEID-related articles (T100PEID) on the alluvial diagram and (2) investigate whether medical subject headings (i.e., MeSH terms) can be used to predict article citations. Methods T100PEID data can be found since 2011 in the PubMed and Web of Science (WOS) databases. Using alluvial diagrams, citation analysis was conducted to compare the dominant entities. We used social network analysis (SNA) to classify MeSH terms and research areas extracted from PubMed and WOS. The difference in article citations across subject categories and the predictive power of MeSH terms on article citations in T100 PEID were examined using one-way analysis of variance (ANOVA) and regression analysis. Results A total of 81% of T100PEID is occupied by the top three countries (the US, China, and South Korea). There was an overall T100PEID impact factor of 41.3 (IF = citations/100). Articles were published in Spine (Phila Pa 1976) (23%; IF = 41.3). Six subject categories were classified using the SNA. The most cited article authored by D Scott Kreiner from Ahwatukee Sports and Spine in the US state of Phoenix had 123 citations in PubMed. The network characteristics of T100PEID are displayed on the alluvial diagram. No difference was found in article citations among subject categories (F = 0.813, p = 0.543). The most frequently occurring MeSH term was surgery. MeSH terms were evident in the prediction power of the number of article citations (F = 15.21; p < 0 .001). Conclusion We achieved a breakthrough by displaying the T100PEID network characteristics on the alluvial plateau. The MeSH terms can be used to classify article subject categories and predict T100PEID citations. The alluvial diagram can be applied to bibliometrics on 100 top-cited articles in future studies. Supplementary Information The online version contains supplementary material available at 10.1186/s40001-022-00782-0. An Alluvial diagram was drawn to display the network characteristics of T100PEID, which is novel and modern in the literature. The method of drawing the Alluvial demonstrated in detail with documents in supplemental digital contents can be applied to make bibliometric studies brief, concise, and powerful. The impact beam plot (IBP) is an additional visualization introduced in this study. The online IBP was demonstrated and worthy of future similar studies to highlight the most influential articles with a glance at a picture.
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Affiliation(s)
- Chao-Hung Yeh
- Department of Neurosurgery, Chi Mei Medical Center, Tainan 700, Taiwan.,Department of Optometry, Chung Hwa University of Medical Technology, Tainan, Taiwan
| | - Tsair-Wei Chien
- Medical Research Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Po-Hsin Chou
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan. .,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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Li H, Zhu Y, Niu Y. Contact Tracing Research: A Literature Review Based on Scientific Collaboration Network. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19159311. [PMID: 35954664 PMCID: PMC9367716 DOI: 10.3390/ijerph19159311] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/22/2022] [Accepted: 07/28/2022] [Indexed: 02/01/2023]
Abstract
Contact tracing is a monitoring process including contact identification, listing, and follow-up, which is a key to slowing down pandemics of infectious diseases, such as COVID-19. In this study, we use the scientific collaboration network technique to explore the evolving history and scientific collaboration patterns of contact tracing. It is observed that the number of articles on the subject remained at a low level before 2020, probably because the practical significance of the contact tracing model was not widely accepted by the academic community. The COVID-19 pandemic has brought an unprecedented research boom to contact tracing, as evidenced by the explosion of the literature after 2020. Tuberculosis, HIV, and other sexually transmitted diseases were common types of diseases studied in contact tracing before 2020. In contrast, research on contact tracing regarding COVID-19 occupies a significantly large proportion after 2000. It is also found from the collaboration networks that academic teams in the field tend to conduct independent research, rather than cross-team collaboration, which is not conducive to knowledge dissemination and information flow.
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Affiliation(s)
- Hui Li
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;
- Correspondence:
| | - Yifei Zhu
- College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;
| | - Yi Niu
- China Publishing Group Digital Media Co., Ltd., Beijing 100007, China;
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Chen CH, Chien TW, Yu-Chieh Ho S, Lai FJ. Predicting article citations using data from 100 top-cited publications in the field of Psoriasis Vulgaris and biological agents (PVBA) since 1991: A bibliometric analysis. Medicine (Baltimore) 2022; 101:e29396. [PMID: 35905256 PMCID: PMC9333523 DOI: 10.1097/md.0000000000029396] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Psoriasis Vulgaris is a chronic inflammatory disease characterized by keratinocyte hyperproliferation. Bibliometric analysis helps determine the most influential article on the topic of "Psoriasis Vulgaris and biological agents (PVBAs)", and what factors affect article citation remain unclear. This study aims (1) to identify the top 100 most cited articles in PVBA (PVBA100 for short) from 1991 to 2020, (2) to visualize dominant entities on one diagram using data in PVBA100, and (3) to investigate whether medical subject headings (MeSH terms) can be used to predict article citations. METHODS The top 100 most cited articles relevant to PVBA (1991-2020) were downloaded by searching the PubMed database. Citation analysis was applied to compare the dominant roles in article types and topic categories using pyramid plots. Social network analysis (SNA) and Sankey diagrams were applied to highlight prominent entities. We examined the MeSH prediction effect on article citations using its correlation coefficients. RESULTS The most frequent article types and topic categories were research support by institutes (46%) and drug therapy (88%), respectively. The most productive countries were the United States (38%), followed by Germany (13%) and Japan (12%). Most articles were published in Br J Dermatol (13%) and J Invest Dermatol (11%). MeSH terms were evident in the prediction power of the number of article citations (correlation coefficient=0.45, t=4.99). CONCLUSIONS The breakthrough was made by developing one dashboard to display PVBA100. MeSH terms can be used for predicting article citations in PVBA100. These visualizations of PVBA100 could be applied to future academic pursuits and applications in other academic disciplines.
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Affiliation(s)
- Chieh-Hsun Chen
- Department of Dermatology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Tsair-Wei Chien
- Medical Research Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Sam Yu-Chieh Ho
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan
| | - Feng-Jie Lai
- Department of Dermatology, Chi Mei Medical Center, Tainan, Taiwan
- Center for General Education, Southern Taiwan University of Science and Technology, Tainan, Taiwan
- * Correspondence: Feng-Jie Lai, Department of Dermatology, Chi Mei Medical Center, No. 901, Zhonghua Rd., Yongkang Dist., Tainan City 710, Taiwan (R.O.C.) (e-mail: )
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Liu PC, Lu Y, Lin HH, Yao YC, Wang ST, Chang MC, Chien TW, Chou PH. Classification and citation analysis of the 100 top-cited articles on adult spinal deformity since 2011: A bibliometric analysis. J Chin Med Assoc 2022; 85:401-408. [PMID: 34698695 DOI: 10.1097/jcma.0000000000000642] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Studies of the 100 most-cited articles are reported for many subjects. However, none has analyzed the article characteristics associated with high citation frequency. This study aims to (1) graphically depict characteristics of the 100 top-cited articles addressing adult spinal deformity (ASD), (2) diagram the association between articles according to subject and major topic medical subject headings (MeSHs), and (3) investigate whether major topic MeSH correlates with article citation frequency. METHODS The 100 top-cited ASD publications since 2011 were retrieved using a PubMed Central search on May 6, 2020. Using titles and abstracts, eight subject categories were identified: surgery, conservative treatment, normal values in spinopelvic alignment, review, cervical alignment, classification, compensatory mechanism, and spine-hip relationship. Sankey diagrams were used to organize the information. Network analysis was performed according to article subject and major topic MeSHs. Pearson's r was used to determine whether the weighted number of citations correlates with major topic MeSHs and the number of citations. RESULTS The average number of citations per article was 34.8 (range, 19-156). The most represented country was USA (n = 51). The most productive and highly cited journal was Spine (Phila Pa 1976) (n = 34; average, 38.2 citations per article). The most frequent subject categories and major topic MeSHs were "surgery" (n = 53) and "scoliosis" (weighted count, 9.8), while articles with the subject "compensatory" had the highest average number of citations (64.7). The most highly cited article, by Dr. F. Schwab in 2012, had 156 citations. Network analysis revealed the relationships between these articles according to major topic MeSHs. The weighted number of citations according to major topic MeSHs correlated significantly with article citation frequency (Pearson's r, 0.57; p < 0.001). CONCLUSION Multiple characteristics of the 100 top-cited ASD articles are presented in diagrams to guide evidence-based clinical decision-making in ASD.
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Affiliation(s)
- Po-Chun Liu
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
| | - Yi Lu
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
| | - Hsi-Hsien Lin
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Yu-Cheng Yao
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Shih-Tien Wang
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Ming-Chau Chang
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Tsair-Wei Chien
- Department of Medical Research, Chi Mei Medical Center, Tainan, Taiwan, ROC
| | - Po-Hsin Chou
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
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Yang TY, Chen CH, Chien TW, Lai FJ. Predicting the number of article citations on the topic of pemphigus vulgaris with the 100 top-cited articles since 2011: A protocol for systematic review and meta-analysis. Medicine (Baltimore) 2021; 100:e26806. [PMID: 34397836 PMCID: PMC8341224 DOI: 10.1097/md.0000000000026806] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 07/13/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Pemphigus vulgaris (PV) is a rare autoimmune blistering disease characterized by intraepithelial and mucocutaneous blister formation and erosion. Numerous articles related to PV have been published. However, which articles have a tremendous influence is still unknown, and factors affecting article citation numbers remain unclear. We aimed to visualize the prominent entities using the top 100 most-cited articles on the topic of PV (T100PV), and investigate whether medical subject headings (i.e., MeSH terms) can be used to predict article citations. METHODS By searching the PubMed Central (PMC) database, the T100PV abstracts since 2011 were downloaded. Citation analysis was performed to compare the dominant entities in article topics, authors, and research institutes using social network analysis (SNA) and Kano diagrams. We examined the MeSH prediction power against article citations using correlation coefficients (CCs). RESULTS The most cited article (125 times) was authored by Ellebrecht from the University of Pennsylvania in the US. The most productive countries were Germany (28%) and the US (25%). Most articles were published in J Invest Dermatol (16%) and Br J Dermatol (10%). Kasperkiewicz (Germany) and the Normandie University (France) were the most cited authors and research institutes, respectively. The most frequently occurred MeSH terms were administration and dosage, immunology, and metabolism. MeSH terms were evident in the prediction power on the number of article citations (F = 19.77; P < .001). CONCLUSION A breakthrough was achieved by developing dashboards to display the T100PV. MeSH terms can be used to predict the T100PV citations. These T100PV visualizations can be applied in future studies.
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Affiliation(s)
- Ting-Ya Yang
- Medical Education Center, Chi Mei Medical Center, Tainan, Taiwan
| | - Chieh-Hsun Chen
- Medical Education Center, Chi Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Medical Research Department, Chi Mei Medical Center, Tainan, Taiwan
| | - Feng-Jie Lai
- Department of Dermatology, Chi Mei Medical Center, Tainan, Taiwan
- Center for General Education, Southern Taiwan University of Science and Technology, Tainan, Taiwan
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A Bibliometric Analysis on Dengue Outbreaks in Tropical and Sub-Tropical Climates Worldwide Since 1950. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18063197. [PMID: 33808795 PMCID: PMC8003706 DOI: 10.3390/ijerph18063197] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 03/17/2021] [Accepted: 03/17/2021] [Indexed: 01/19/2023]
Abstract
Severe dengue outbreaks (DOs) affect the majority of Asian and Latin American countries. Whether all DOs always occurred in sub-tropical and tropical areas (STTA) has not been verified. We downloaded abstracts by searching keywords “dengue (MeSH Major Topic)” from Pubmed Central since 1950, including three collections: country names in abstracts (CNA), no abstracts (WA), and no country names in abstracts (Non-CNA). Visualizations were created to present the DOs across countries/areas in STTA. The percentages of mentioned country names and authors’ countries in STTA were computed on the CNA and Non-CNA bases. The social network analysis was applied to highlight the most cited articles and countries. We found that (1) three collections are 3427 (25.48%), 3137 (23.33%), and 6884 (51.19%) in CNA, WA, and Non-CNA, respectively; (2) the percentages of 94.3% and 79.9% were found in the CNA and Non-CNA groups; (3) the most mentioned country in abstracts were India, Thailand, and Brazil; (4) most authors in the Non-CNA collections were from the United States, Brazil, and China; (5) the most cited article (PMID = 23563266) authored by Bhatt et al. had 2604 citations since 2013. Our findings provide in-depth insights into the DO knowledge. The research approaches are recommended for authors in research on other infectious diseases in the future, not just limited to the DO topic.
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Yie KY, Chien TW, Yeh YT, Chou W, Su SB. Using Social Network Analysis to Identify Spatiotemporal Spread Patterns of COVID-19 around the World: Online Dashboard Development. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:2461. [PMID: 33802247 PMCID: PMC7967593 DOI: 10.3390/ijerph18052461] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 02/24/2021] [Accepted: 02/25/2021] [Indexed: 12/15/2022]
Abstract
The COVID-19 pandemic has spread widely around the world. Many mathematical models have been proposed to investigate the inflection point (IP) and the spread pattern of COVID-19. However, no researchers have applied social network analysis (SNA) to cluster their characteristics. We aimed to illustrate the use of SNA to identify the spread clusters of COVID-19. Cumulative numbers of infected cases (CNICs) in countries/regions were downloaded from GitHub. The CNIC patterns were extracted from SNA based on CNICs between countries/regions. The item response model (IRT) was applied to create a general predictive model for each country/region. The IP days were obtained from the IRT model. The location parameters in continents, China, and the United States were compared. The results showed that (1) three clusters (255, n = 51, 130, and 74 in patterns from Eastern Asia and Europe to America) were separated using SNA, (2) China had a shorter mean IP and smaller mean location parameter than other counterparts, and (3) an online dashboard was used to display the clusters along with IP days for each country/region. Spatiotemporal spread patterns can be clustered using SNA and correlation coefficients (CCs). A dashboard with spread clusters and IP days is recommended to epidemiologists and researchers and is not limited to the COVID-19 pandemic.
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Affiliation(s)
- Kyent-Yon Yie
- Department of Gastrointestinal Hepatobiliary, Chi Mei Jiali Hospital, Tainan 700, Taiwan;
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Hospital, Tainan 700, Taiwan;
| | - Yu-Tsen Yeh
- Medical School, St. George’s University of London, London SW17 0RE, UK;
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chi Mei Medical Center, Tainan 700, Taiwan
| | - Shih-Bin Su
- Department of Occupational Medicine, Chi Mei Medical Center, Tainan 700, Taiwan
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Chou PH, Yeh YT, Kan WC, Chien TW, Kuo SC. Using Kano diagrams to display the most cited article types, affiliated countries, authors and MeSH terms on spinal surgery in recent 12 years. Eur J Med Res 2021; 26:22. [PMID: 33622416 PMCID: PMC7903694 DOI: 10.1186/s40001-021-00494-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 02/11/2021] [Indexed: 02/08/2023] Open
Abstract
Background Citation analysis has been increasingly applied to assess the quantity and quality of scientific research in various fields worldwide. However, these analyses on spinal surgery do not provide visualization of results. This study aims (1) to evaluate the worldwide research citations and publications on spinal surgery and (2) to provide visual representations using Kano diagrams onto the research analysis for spinal surgeons and researchers. Methods Article abstracts published between 2007 and 2018 were downloaded from PubMed Central (PMC) in 5 journals, including Spine, European Spine Journal, The Spine Journal, Journal of Neurosurgery: Spine, and Journal of Spinal Disorders and Techniques. The article types, affiliated countries, authors, and Medical subject headings (MeSH terms) were analyzed by the number of article citations using x-index. Choropleth maps and Kano diagrams were applied to present these results. The trends of MeSH terms over the years were plotted and analyzed. Results A total of 18,808 publications were extracted from the PMC database, and 17,245 were affiliated to countries/areas. The 12-year impact factor for the five spine journals is 5.758. We observed that (1) the largest number of articles on spinal surgery was from North America (6417, 37.21%). Spine earns the highest x-index (= 82.96). Comparative Study has the highest x-index (= 66.74) among all article types. (2) The United States performed exceptionally in x-indexes (= 56.86 and 44.5) on both analyses done on the total 18,808 and the top 100 most cited articles, respectively. The most influential author whose x-index reaches 15.11 was Simon Dagenais from the US. (3) The most cited MeSH term with an x-index of 23.05 was surgery based on the top 100 most cited articles. The most cited article (PMID = 18164449) was written by Dagenais and his colleagues in 2008. The most productive author was Michael G. Fehlings, whose x-index and the author's impact factor are 13.57(= √(13.16*14)) and 9.86(= 331.57/33.64), respectively. Conclusions There was a rapidly increasing scientific productivity in the field of spinal surgery in the past 12 years. The US has extraordinary contributions to the publications. Furthermore, China and Japan have increasing numbers of publications on spinal surgery. This study with Kano diagrams provides an insight into the research for spinal surgeons and researchers.
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Affiliation(s)
- Po-Hsin Chou
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Yu-Tsen Yeh
- Medical School, St. George's, University of London, London, UK
| | - Wei-Chih Kan
- Department of Nephrology, Chi-Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Shu-Chun Kuo
- Department of Optometry, Chung Hwa University of Medical Technology, Jen-Teh, Tainan, Taiwan. .,Department of Ophthalmology, Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung, Yong Kang, Tainan, Taiwan.
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Lin CH, Chien TW, Yan YH. Predicting the number of article citations in the field of attention-deficit/hyperactivity disorder (ADHD) with the 100 top-cited articles since 2014: a bibliometric analysis. Ann Gen Psychiatry 2021; 20:6. [PMID: 33478559 PMCID: PMC7819196 DOI: 10.1186/s12991-021-00329-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 01/11/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children or early adolescents with an estimated worldwide prevalence of 7.2%. Numerous articles related to ADHD have been published in the literature. However, which articles had ultimate influence is still unknown, and what factors affect the number of article citations remains unclear as well. This bibliometric analysis (1) visualizes the prominent entities with 1 picture using the top 100 most-cited articles, and (2) investigates whether medical subject headings (i.e., MeSH terms) can be used in predicting article citations. METHODS By searching the PubMed Central® (PMC) database, the top 100 most-cited abstracts relevant to ADHD since 2014 were downloaded. Citation rank analysis was performed to compare the dominant roles of article types and topic categories using the pyramid plot. Social network analysis (SNA) was performed to highlight prominent entities for providing a quick look at the study result. The authors examined the MeSH prediction effect on article citations using its correlation coefficients (CC). RESULTS The most frequent article types and topic categories were research support by institutes (56%) and epidemiology (28%). The most productive countries were the United States (42%), followed by the United Kingdom (13%), Germany (9%), and the Netherlands (9%). Most articles were published in the Journal of the American Academy of Child and Adolescent Psychiatry (15%) and JAMA Psychiatry (9%). MeSH terms were evident in prediction power on the number of article citations (correlation coefficient = 0.39; t = 4.1; n = 94; 6 articles were excluded because they do not have MeSH terms). CONCLUSIONS The breakthrough was made by developing 1 dashboard to display 100 top-cited articles on ADHD. MeSH terms can be used in predicting article citations on ADHD. These visualizations of the top 100 most-cited articles could be applied to future academic pursuits and other academic disciplines.
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Affiliation(s)
- Chien-Ho Lin
- Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, No. 901, Chung Hwa Road, Yung Kung Dist., Tainan, 710, Taiwan
| | - Yu-Hua Yan
- Department of Medical Research, Tainan Municipal Hospital (Managed By Show Chwan Medical Care Corporation), No. 670, Chung Te Road, Tainan, 701, Taiwan. .,Department of Hospital and Health Care Administration, Chia Nan University of Pharmacy and Science, No. 1, Changda Rd., Gueiren District, Tainan, 71101, Taiwan.
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Kuo YC, Chien TW, Kuo SC, Yeh YT, Lin JCJ, Fong Y. Predicting article citations using data of 100 top-cited publications in the journal Medicine since 2011: A bibliometric analysis. Medicine (Baltimore) 2020; 99:e22885. [PMID: 33126338 PMCID: PMC7598835 DOI: 10.1097/md.0000000000022885] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Publications regarding the 100 top-cited articles in a given discipline are common, but studies reporting the association between article topics and their citations are lacking. Whether or not reviews and original articles have a higher impact factor than case reports is a point for verification in this study. In addition, article topics that can be used for predicting citations have not been analyzed. Thus, this study aims to METHODS:: We searched PubMed Central and downloaded 100 top-cited abstracts in the journal Medicine (Baltimore) since 2011. Four article types and 7 topic categories (denoted by MeSH terms) were extracted from abstracts. Contributors to these 100 top-cited articles were analyzed. Social network analysis and Sankey diagram analysis were performed to identify influential article types and topic categories. MeSH terms were applied to predict the number of article citations. We then examined the prediction power with the correlation coefficients between MeSH weights and article citations. RESULTS The citation counts for the 100 articles ranged from 24 to 127, with an average of 39.1 citations. The most frequent article types were journal articles (82%) and comparative studies (10%), and the most frequent topics were epidemiology (48%) and blood and immunology (36%). The most productive countries were the United States (24%) and China (23%). The most cited article (PDID = 27258521) with a count of 135 was written by Dr Shang from Shandong Provincial Hospital Affiliated to Shandong University (China) in 2016. MeSH terms were evident in the prediction power of the number of article citations (correlation coefficients = 0.49, t = 5.62). CONCLUSION The breakthrough was made by developing dashboards showing the overall concept of the 100 top-cited articles using the Sankey diagram. MeSH terms can be used for predicting article citations. Analyzing the 100 top-cited articles could help future academic pursuits and applications in other academic disciplines.
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Affiliation(s)
- Yu-Chi Kuo
- Division of Nephrology, Department of Medicine, Chiali Chi Mei Hospital
| | | | - Shu-Chun Kuo
- Department of Ophthalmology, Chi-Mei Medical Center, Yong Kang
- Department of Optometry, Chung Hwa University of Medical Technology, Jen-Teh, Tainan City, Taiwan
| | - Yu-Tsen Yeh
- Medical School, St. George's, University of London, London, United Kingdom
| | | | - Yao Fong
- Department of Thoracic Surgery, Chi-Mei Medical Center, Tainan, Taiwan
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Liu MY, Chou W, Chien TW, Kuo SC, Yeh YT, Chou PH. Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles: A bibliometric analysis. Medicine (Baltimore) 2020; 99:e20334. [PMID: 32481321 PMCID: PMC7249850 DOI: 10.1097/md.0000000000020334] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Team science research includes authors from various fields collaborating to publish their work on certain topics. Despite the numerous papers that discussed the ordering of author names and the contributions of authors to an article, no paper evaluatedIn addition, few researchers publish academic articles without co-author collaboration. Whether the bibliometric indexes (eg, h-/x-index) of sole-author researchers are higher than those of other types of multiple authors is required for comparison. We aimed to evaluate a productive author who published 114 sole-author articles with exceptional RA and RD in academics. METHODS By searching the PubMed database (Pubmed.com), we used the keyword of (Taiwan[affiliation]) from 2016 to 2017 and downloaded 29,356 articles. One physician (Dr. Tseng from the field of Internal Medicine) who published 12 articles as a single author was selected. His articles and citations were searched in PubMed. A comparison of various types of author ordering placements was conducted using sensitivity analysis to inspect whether this sole author earns the highest metrics in RA. Social network analysis (SNA), Gini coefficient (GC), pyramid plot, and the Kano diagram were applied to gather the following data for visualization: RESULTS:: We observed that CONCLUSIONS:: The metrics on RA are high for the sole author studied. The author's RD can be denoted by the MeSH terms and measured by the GC. The author-weighted scheme is required for quantifying author credits in an article to evaluate the author's RA. Social network analysis incorporating the Kano diagrams provided insights into the relationships between actors (eg, coauthors, MeSH terms, or journals). The methods used in this study can be replicated to evaluate other productive studies on RA and RD in the future.
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Affiliation(s)
- Mei-Yuan Liu
- Nutrition Department, Chi-Mei Medical Center
- Nutrition Department, Chang Jung Christian University, Tainan
- Department of Physical Medicine and Rehabilitation, Chung Shan Medical University, Taichun
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chung Shan Medical University, Taichun
- Department of Physical Medicine and Rehabilitation, Chiali Chi Mei Hospital
| | - Tsair-Wei Chien
- Department of Medical Research, Chi Mei Medical Center, Tainan, Taiwan
| | - Shu-Chun Kuo
- Department of Ophthalmology, Chi-Mei Medical Center
- Department of Optometry, Chung Hwa University of Medical Technology, Jen-Teh, Tainan City, Taiwan
| | - Yu-Tsen Yeh
- Medical School, St. George's, University of London, London, United Kingdom
| | - Po-Hsin Chou
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
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Kan WC, Chou W, Chien TW, Yeh YT, Chou PH. The Most-Cited Authors Who Published Papers in JMIR mHealth and uHealth Using the Authorship-Weighted Scheme: Bibliometric Analysis. JMIR Mhealth Uhealth 2020; 8:e11567. [PMID: 32379053 PMCID: PMC7319608 DOI: 10.2196/11567] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 10/22/2018] [Accepted: 01/26/2020] [Indexed: 12/20/2022] Open
Abstract
Background Many previous papers have investigated most-cited articles or most productive authors in academics, but few have studied most-cited authors. Two challenges are faced in doing so, one of which is that some different authors will have the same name in the bibliometric data, and the second is that coauthors’ contributions are different in the article byline. No study has dealt with the matter of duplicate names in bibliometric data. Although betweenness centrality (BC) is one of the most popular degrees of density in social network analysis (SNA), few have applied the BC algorithm to interpret a network’s characteristics. A quantitative scheme must be used for calculating weighted author credits and then applying the metrics in comparison. Objective This study aimed to apply the BC algorithm to examine possible identical names in a network and report the most-cited authors for a journal related to international mobile health (mHealth) research. Methods We obtained 676 abstracts from Medline based on the keywords “JMIR mHealth and uHealth” (Journal) on June 30, 2018. The author names, countries/areas, and author-defined keywords were recorded. The BCs were then calculated for the following: (1) the most-cited authors displayed on Google Maps; (2) the geographical distribution of countries/areas for the first author; and (3) the keywords dispersed by BC and related to article topics in comparison on citation indices. Pajek software was used to yield the BC for each entity (or node). Bibliometric indices, including h-, g-, and x-indexes, the mean of core articles on g(Ag)=sum (citations on g-core/publications on g-core), and author impact factor (AIF), were applied. Results We found that the most-cited author was Sherif M Badawy (from the United States), who had published six articles on JMIR mHealth and uHealth with high bibliometric indices (h=3; AIF=8.47; x=4.68; Ag=5.26). We also found that the two countries with the highest BC were the United States and the United Kingdom and that the two keyword clusters of mHealth and telemedicine earned the highest indices in comparison to other counterparts. All visual representations were successfully displayed on Google Maps. Conclusions The most cited authors were selected using the authorship-weighted scheme (AWS), and the keywords of mHealth and telemedicine were more highly cited than other counterparts. The results on Google Maps are novel and unique as knowledge concept maps for understanding the feature of a journal. The research approaches used in this study (ie, BC and AWS) can be applied to other bibliometric analyses in the future.
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Affiliation(s)
- Wei-Chih Kan
- Department of Nephrology, Chi Mei Medical Center, Taiwan, Tainan, Taiwan.,Department of Biological Science and Technology, Chung Hwa University of Medical Technology, Tainan, Taiwan
| | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chi Mei Medical Center, Tainan, Taiwan.,Department of Physical Medicine and Rehabilitation, Chung Shan Medical University, Taichun, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi Mei Medical Center, Taiwan, Tainan, Taiwan
| | - Yu-Tsen Yeh
- Medical School, St George's, University of London, London, United Kingdom
| | - Po-Hsin Chou
- Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
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Hsieh WT, Chien TW, Kuo SC, Lin HJ. Whether productive authors using the national health insurance database also achieve higher individual research metrics: A bibliometric study. Medicine (Baltimore) 2020; 99:e18631. [PMID: 31914046 PMCID: PMC6959956 DOI: 10.1097/md.0000000000018631] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 11/21/2019] [Accepted: 12/04/2019] [Indexed: 01/31/2023] Open
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.
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Affiliation(s)
| | | | - Shu-Chun Kuo
- Department of Optometry, Chung Hwa University of Medical Technology
- Department of Ophthalmology, Chi-Mei Medical Center
| | - Hung-Jung Lin
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan
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Chien TW, Wang HY, Lai FJ. Applying an Author-Weighted Scheme to Identify the Most Influential Countries in Research Achievements on Skin Cancer: Observational Study. JMIR DERMATOLOGY 2019. [DOI: 10.2196/11015] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BackgroundSkin cancers are caused by the development of abnormal cells that can invade or spread to other parts of the body. The countries whose authors contribute the most amount of articles on skin cancer to academia is still unknown.ObjectiveThe objectives of this study are to apply an author-weighted scheme (AWS) to quantify the credits for coauthors on an article byline and allocate the author weights to the country-level credits in articles.MethodsOn July 20, 2019, we obtained 16,804 abstracts published since 1938, based on a keyword search of “skin cancer” in PubMed. The author names, countries/areas, and journals were recorded. International author collaborations on skin cancer were analyzed based on country-level credits in articles. We aimed to do the following: (1) present country distribution for the first authors and the most popular journals, (2) show choropleth maps to highlight the most influential countries, and (3) draw scatter plots based on the Kano model to characterize the features of country-level research achievements. We programmed Excel Visual Basic for Applications (Microsoft Corp) routines to extract data from PubMed. Google Maps was used to display graphical representations.ResultsOur results suggest that researchers in the United States have published most frequently, accounting for 30.37% (5103), while Germany accounts for 7.34% (1234), followed by Australia (997, 5.93%). The top three continents for the proportion of published articles are North America, Europe, and Asia, accounting for 32.29%, 31.71%, and 10.41%, respectively.ConclusionsThis study offers an objective picture of the representativeness and evolution of international research on the topic of skin cancer. The research approaches used here have the potential to be applied to other areas besides skin cancer.
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Chien TW, Wang HY, Kan WC, Su SB. 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; 98:e17631. [PMID: 31651878 PMCID: PMC6824745 DOI: 10.1097/md.0000000000017631] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Many authors are concerned which types of peer-review articles can be cited most in academics and who were the highest-cited authors in a scientific discipline. The prerequisites are determined by: (1) classifying article types; and (2) quantifying co-author contributions. We aimed to apply Medical Subject Headings (MeSH) with social network analysis (SNA) and an authorship-weighted scheme (AWS) to meet the prerequisites above and then demonstrate the applications for scholars. METHODS By searching the PubMed database (pubmed.com), we used the keyword "Medicine" [journal] and downloaded 5,636 articles published from 2012 to 2016. A total number of 9,758 were cited in Pubmed Central (PMC). Ten MeSH terms were separated to represent the journal types of clusters using SNA to compare the difference in bibliometric indices, that is, h, g, and x as well as author impact factor(AIF). The methods of Kendall coefficient of concordance (W) and one-way ANOVA were performed to verify the internal consistency of indices and the difference across MeSH clusters. Visual representations with dashboards were shown on Google Maps. RESULTS We found that Kendall W is 0.97 (χ = 26.22, df = 9, P < .001) congruent with internal consistency on metrics across MeSH clusters. Both article types of methods and therapeutic use show higher frequencies than other 8 counterparts. The author Klaus Lechner (Austria) earns the highest research achievement(the mean of core articles on g = Ag = 15.35, AIF = 21, x = 3.92, h = 1) with one paper (PMID: 22732949, 2012), which was cited 23 times in 2017 and the preceding 5 years. CONCLUSION Publishing article type with study methodology and design might lead to a higher IF. Both classifying article types and quantifying co-author contributions can be accommodated to other scientific disciplines. As such, which type of articles and who contributes most to a specific journal can be evaluated in the future.
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Affiliation(s)
| | - Hsien-Yi Wang
- Department of Nephrology, Chi-Mei Medical Center
- Department of Sport Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science
| | - Wei-Chih Kan
- Department of Nephrology, Chi-Mei Medical Center
- Department of Biological Science and Technology, Chung Hwa University of Medical Technology
| | - Shih-Bin Su
- Department of Biological Science and Technology, Chung Hwa University of Medical Technology
- Department of Leisure, Recreation, and Tourism Management, Southern Taiwan University of Science and Technology
- Department of Occupational Medicine, Chi-Mei Medical Center
- Department of Medical Research, Chi Mei Medical Center, Liouying, Tainan, Taiwan
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Chien TW, Wang HY, Hsu CF, Kuo SC. Choropleth map legend design for visualizing the most influential areas in article citation disparities: A bibliometric study. Medicine (Baltimore) 2019; 98:e17527. [PMID: 31593127 PMCID: PMC6799475 DOI: 10.1097/md.0000000000017527] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Disparities in health outcomes across countries/areas are a central concern in public health and epidemiology. However, few authors have discussed legends that can be complemental to choropleth maps (CMs) and merely linked differences in outcomes to other factors like density in areas. Thus, whether health outcome rates on CMs showing the geographical distribution can be applied to publication citations in bibliometric analyses requires further study. The legends for visualizing the most influential areas in article citation disparities should have sophisticated designs. This paper illustrates the use of cumulative frequency (CF) map legends along with Lorenz curves and Gini coefficients (GC) to characterize the disparity of article citations in areas on CMs, based on the quantile classification method for classes. METHODS By searching the PubMed database (pubmed.com), we used the keyword "Medicine" [journal] and downloaded 7042 articles published from 1945 to 2016. A total number of 41,628 articles were cited in Pubmed Central (PMC). The publication outputs based on the author's x-index were applied to plot CM about research contributions. The approach uses two methods (i.e., quantiles and equal total values for each class) with CF legends, in order to highlight the difference in x-indices across geographical areas on CMs. GC was applied to observe the x-index disparities in areas. Microsoft Excel Visual Basic for Application (VBA) was used for creating the CMs. RESULTS Results showed that the most productive and cited countries in Medicine (Baltimore) were China and the US. The most-cited states and cities were Maryland (the US) and Beijing (China). Taiwan (x-index = 24.38) ranked behind Maryland (25.97), but ahead of Beijing (16.9). China earned lower disparity (0.42) than the US (0.49) and the rest of the world (0.53) when the GCs were applied. CONCLUSION CF legends, particularly using the quantile classification for classes, can be useful to complement CMs. They also contain more information than those in standard CM legends that are commonly used with other classification methods. The steps of creating CM legends are described and introduced. Bibliometric analysts on CM can be replicated in the future.
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Affiliation(s)
- Tsair-Wei Chien
- Medical Research Department, Chi-Mei Medical Center
- Department of Sport Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science
| | - Hsien-Yi Wang
- Department of Sport Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science
- Ncphrology Department, Chi-Mei Medical Center
| | - Chen-Fang Hsu
- Department of Partiatrics, Chi-Mei Medical Center, Yong Kang
| | - Shu-Chun Kuo
- Department of Optometry, Chung Hwa University of Medical Technology, Jen-Teh
- Department of Ophthalmology, Chi-Mei Medical Center, Yong Kang, Tainan City, Taiwan
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Chen RH, Chen HY, Man KM, Chen SJ, Chen W, Liu PL, Chen YH, Chen WC. Thyroid diseases increased the risk of type 2 diabetes mellitus: A nation-wide cohort study. Medicine (Baltimore) 2019; 98:e15631. [PMID: 31096476 PMCID: PMC6531080 DOI: 10.1097/md.0000000000015631] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Thyroid function may alter carbohydrate metabolism via influence of insulin, which may in terms of derangement of thyroid function and insulin function result in the development of type 2 diabetes mellitus (T2D). We investigated the association of thyroid disorders with T2D by a cohort study of the Taiwan nationwide health insurance database.A sub-dataset of the National Health Insurance Research Database (NHIRD) was used in this study. The thyroid disease (both hyper- and hypo-thyroidism) group was chosen from patients older than 18 years and newly diagnosed between 2000 and 2012. The control group consisted of randomly selected patients who never been diagnosed with thyroid disease and 4-fold size frequency matched with the thyroid disease group. The event of this cohort was T2D (ICD-9-CM 250.x1, 250.x2). Primary analysis was performed by comparing the thyroid disease group to the control group and the second analysis was performed by comparing the hyperthyroidism subgroup, hypothyroidism subgroup, and control group.The occurrence of T2D in the thyroid disease group was higher than the control group with hazard ratio (HR) of 1.23 [95% confidence interval (CI) = 1.16-1.31]. Both hyperthyroidism and hypothyroidism were significantly higher than control. Significantly higher HR was also seen in female patients, age category of 18 to 39-year-old (y/o) and 40 to 64 y/o subgroups. Higher occurrence of T2D was also seen in thyroid disease patients without comorbidity than in the control group with HR of 1.47 (95% CI = 1.34-1.60). The highest HR was found in the half-year follow-up.There was a relatively high risk of T2D development in patients with thyroid dysfunctions, especially in the period of 0.5 to 1 year after presentation of thyroid dysfunctions. The results suggest performing blood sugar tests in patients with thyroid diseases for early detection and treatment of T2D.
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Affiliation(s)
- Rong-Hsing Chen
- Departments of Endocrine and Metabolism, Anesthesiology, Obstetrics and Gynecology, Medical Research, Medical Education, and Urology, China Medical University Hospital
| | - Huey-Yi Chen
- Departments of Endocrine and Metabolism, Anesthesiology, Obstetrics and Gynecology, Medical Research, Medical Education, and Urology, China Medical University Hospital
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, College of Medicine, China Medical University
| | - Kee-Ming Man
- Departments of Endocrine and Metabolism, Anesthesiology, Obstetrics and Gynecology, Medical Research, Medical Education, and Urology, China Medical University Hospital
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, College of Medicine, China Medical University
- Department of Anesthesiology, China Medical University Hsinchu Hospital, Hsinchu
| | - Szu-Ju Chen
- Departments of Endocrine and Metabolism, Anesthesiology, Obstetrics and Gynecology, Medical Research, Medical Education, and Urology, China Medical University Hospital
- Department of Surgery, Taichung Veterans General Hospital, Taichung
| | - Weishan Chen
- Management Office for Health Data, China Medical University Hospital, Taichung
| | - Po-Len Liu
- Department of Respiratory Therapy, College of Medicine, Kaohsiung Medical University, Kaohsiung
| | - Yung-Hsiang Chen
- Departments of Endocrine and Metabolism, Anesthesiology, Obstetrics and Gynecology, Medical Research, Medical Education, and Urology, China Medical University Hospital
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, College of Medicine, China Medical University
- Department of Psychology, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Wen-Chi Chen
- Departments of Endocrine and Metabolism, Anesthesiology, Obstetrics and Gynecology, Medical Research, Medical Education, and Urology, China Medical University Hospital
- Graduate Institute of Integrated Medicine, College of Chinese Medicine, College of Medicine, China Medical University
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Chien TW, Wang HY, Chang Y, Kan WC. Using Google Maps to display the pattern of coauthor collaborations on the topic of schizophrenia: A systematic review between 1937 and 2017. Schizophr Res 2019; 204:206-213. [PMID: 30262255 DOI: 10.1016/j.schres.2018.09.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 09/11/2018] [Accepted: 09/15/2018] [Indexed: 11/18/2022]
Abstract
Schizophrenia is a severe mental disorder affecting more than 21 million people worldwide. Scientific collaborations are required to research schizophrenia. However, there have been limited publications to date investigating scientific collaborations in schizophrenia research or reporting individual researchers' achievements(IRA) for authors. This study aimed to investigate the pattern of coauthor collaborations in schizophrenia research. We conducted a bibliometric study of international scientific publications on schizophrenia. About 57,964 abstracts were identified and downloaded from MEDLINE. All were examined using social network analysis (SNA) on February 20, 2018. The clusters of author nationalities, the authors, and the medical subject headings (MESH) terms were presented on Google Maps. A total of 36,934 articles met the inclusion criteria. The mean number of authors per article increased from 4.5 in 2008 to 6.4 in 2017. The proportion of published articles decreased in North America from 46.7% in 2008, to 32.3% in 2017. In contrast, the proportion of published articles in Asia increased from 14.5% in 1998 to 23.9% in 2017. Among the countries generating schizophrenia research the most prominent is China (corr. = 0.98), followed by India (corr. = 0.94), and France (corr. = 0.93). The representative of the biggest cluster is the author Michael F Green from the United States. The top three MESH terms are physiopathology, schizophrenic psychology, and complications. The scientific interest in schizophrenia remains significant. The application of bibliometric indicators of production is evident in the growth of scientific literature on the topic of schizophrenia.
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Affiliation(s)
- Tsair-Wei Chien
- Medical Research Departments, Chi-Mei Medical Center, Taiwan; Department of Hospital and Health Care Administration, Chia-Nan University of Pharmacy and Science, Tainan, Taiwan.
| | - Hsien-Yi Wang
- Ncphrology Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Yu Chang
- National Taiwan University School of Medicine, Taiwan
| | - Wei-Chih Kan
- Ncphrology Department, Chi-Mei Medical Center, Tainan, Taiwan.
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Chien TW, Chow JC, Chang Y, Chou W. Applying Gini coefficient to evaluate the author research domains associated with the ordering of author names: A bibliometric study. Medicine (Baltimore) 2018; 97:e12418. [PMID: 30278518 PMCID: PMC6181458 DOI: 10.1097/md.0000000000012418] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Team science research includes the number of coauthors in publications. Many papers have discussed the ordering of author names and the contributions of authors to a paper. However, no paper addresses the relation between authors' research domains and personal impact factors (PIF) with the ordering of author names. We aimed to apply Gini coefficient (GC) to evaluate the author research domains associated with the PIF and the ordering of author names on academic papers. METHODS By searching the PubMed database (Pubmed.com), we used the keyword "medicine" [journal] and downloaded 10,854 articles published from 1969 to 2018. A total number of 7502 articles labeled with complete author's countries/areas were included in data analysis. We also proposed a PIF index and jointly applied social network analysis (SNA), the GC, and Google Maps to report the following data with visual representations: the trend of author collaboration in Medicine; the dominant nations and keywords in Medicine; and the author research domains in Medicine associated with the PIF and the ordering of author names on academic papers. RESULTS The trend of author collaboration in Medicine is slightly declining (= -0.06) based on the number of authors per article. The mean number of individuals listed as authors in articles is 7.5. Most first authors are from China (3649, 48.64%) and Taiwan (847, 11.29%). The median of GC (0.32) and PIF (0.74) for the middle authors are obviously less than those for the first (0.53, 2.19) and the last authors (0.42, 2.61). A perfect positive linear relation with a large effect exists between GC and PIF because the correlation coefficient is 0.68 (>0.50, t = 2.48, n = 9). CONCLUSION Results suggest that the corresponding author is submitting the manuscript to the target journal with a core author's academic background and the personal impact factor related to the research domain and the journal scope in the future. As such, peer reviewers can quickly determine whether the manuscript is a potentially citable research paper.
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Affiliation(s)
| | | | - Yu Chang
- National Taiwan University School of Medicine
| | - Willy Chou
- Department of Sports Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science
- Ncphrology Department, Chi-Mei Medical Center, Tainan, Taiwan
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