Literature DB >> 31862218

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

Chien-Ho Lin1, Po-Hsin Chou2, Willy Chou3, Tsair-Wei Chien4.   

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.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Authorship-weighted scheme; Google maps; Individual academic achievement; Pubmed central; Schizophrenia; Social network analysis

Mesh:

Year:  2019        PMID: 31862218     DOI: 10.1016/j.schres.2019.10.058

Source DB:  PubMed          Journal:  Schizophr Res        ISSN: 0920-9964            Impact factor:   4.939


  8 in total

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4.  Demand analysis of telenursing among empty-nest elderly individuals with chronic diseases based on the Kano model.

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7.  Using Social Network Analysis to Identify Spatiotemporal Spread Patterns of COVID-19 around the World: Online Dashboard Development.

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  8 in total

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