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运用卡诺模型展示精神分裂症研究中被引频次最高的作者和所属国家。

Using the Kano model to display the most cited authors and affiliated countries in schizophrenia research.

机构信息

Department of Psychiatry, Chi Mei Medical Center, Taiwan.

School of Medicine, National Yang-Ming University, Taipei, Taiwan; Department of Orthopedics and Traumatology, Taipei Veterans General Hospital, Taipei, Taiwan.

出版信息

Schizophr Res. 2020 Feb;216:422-428. doi: 10.1016/j.schres.2019.10.058. Epub 2019 Dec 18.


DOI:10.1016/j.schres.2019.10.058
PMID:31862218
Abstract

In order to improve individual research achievements (IRA), this study investigates which affiliated countries and authors earn the most cited IRAs and whether those types of articles are associated with the number of cited papers on schizophrenia from a leading journal in the field. The Kano model was used for displaying the IRAs. Clusters of medical subject headings (MeSH) were applied to explore the core concepts of a given journal. This study aimed to apply social network analysis (SNA) and an authorship-weighted scheme (AWS) to inspect the association between MeSH terms and IRA. About 2,008 abstracts published between 2012 and 2016 in the journal Schizophrenia Research were downloaded from Pubmed Central using the keyword (Schizophr Res)[Journal] on September 20, 2018. The MeSH terms were clustered by using SNA to separate the core concepts and compare the differences in bibliometric indices (i.e., h, Ag, x and author impact factor or AIF). Visual dashboards were shown on Google Maps. Results indicate that (1) the US, the UK, and Canada earn the highest x-index; (2) the top one author from the US has the highest x-index (= 5.73 with x-core at cited = 16.44 and citable = 2); (3) the article type of schizophrenic psychology shows distinctly higher frequencies than others; and (4) article types are associated with the number of cited papers. Four approaches of the Kano model, SNA, MeSH terms, and AWS can be accommodated to display IRAs, classify article types, and quantify coauthor contributions in the article byline, respectively, and applied to other scientific disciplines in the future, not just in this specific journal.

摘要

为了提高个人研究成果(IRA),本研究调查了哪些附属国家和作者获得了最多被引的 IRA,以及这些类型的文章是否与该领域领先期刊上发表的关于精神分裂症的被引论文数量有关。采用 Kano 模型显示 IRA。应用医学主题词(MeSH)聚类来探索给定期刊的核心概念。本研究旨在应用社会网络分析(SNA)和作者加权方案(AWS)来检查 MeSH 术语与 IRA 之间的关联。2018 年 9 月 20 日,使用 Pubmed Central 上的关键字(Schizophr Res)[Journal]从 Pubmed Central 下载了 2012 年至 2016 年期间发表在《Schizophrenia Research》杂志上的约 2008 篇摘要。使用 SNA 对 MeSH 术语进行聚类,以分离核心概念并比较文献计量指标(即 h、Ag、x 和作者影响因子或 AIF)的差异。在 Google 地图上显示可视化仪表板。结果表明:(1)美国、英国和加拿大的 x 指数最高;(2)来自美国的排名第一的作者的 x 指数最高(x-core = 5.73,cited = 16.44,citable = 2);(3)精神分裂症心理学的文章类型比其他类型的文章出现频率明显更高;(4)文章类型与被引论文数量有关。Kano 模型的四种方法、SNA、MeSH 术语和 AWS 可以分别用于显示 IRA、对文章类型进行分类以及量化文章作者署名中的合著者贡献,并在未来应用于其他科学学科,而不仅仅是在该特定期刊上。

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