Literature DB >> 30262255

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

Tsair-Wei Chien1, Hsien-Yi Wang2, Yu Chang3, Wei-Chih Kan4.   

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.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bibliometric; Correlation coefficient; Google maps; H-index; Schizophrenia; Social network analysis

Mesh:

Year:  2018        PMID: 30262255     DOI: 10.1016/j.schres.2018.09.015

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


  6 in total

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

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  6 in total

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