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Global collaborative networks on meta-analyses of randomized trials published in high impact factor medical journals: a social network analysis

机译:在高影响因子医学期刊上发表的关于随机试验的荟萃分析的全球协作网络:社交网络分析

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Background Research collaboration contributes to the advancement of knowledge by exploiting the results of scientific efforts more efficiently, but the global patterns of collaboration on meta-analysis are unknown. The purpose of this research was to describe and characterize the global collaborative patterns in meta-analyses of randomized trials published in high impact factor medical journals over the past three decades. Methods This was a cross-sectional, social network analysis. We searched PubMed for relevant meta-analyses of randomized trials published up to December 2012. We selected meta-analyses (including at least randomized trials as primary evidence source) published in the top seven high impact factor general medical journals (according to Journal Citation Reports 2011): The New England Journal of Medicine , The Lancet , the BMJ , JAMA , Annals of Internal Medicine , Archives of Internal Medicine (now renamed JAMA Internal Medicine ), and PLoS Medicine . Opinion articles, conceptual papers, narrative reviews, reviews without meta-analysis, reviews of reviews, and other study designs were excluded. Results Overall, we included 736 meta-analyses, in which 3,178 authors, 891 institutions, and 51 countries participated. The BMJ was the journal that published the greatest number of articles (39%), followed by The Lancet (18%), JAMA (15%) and the Archives of Internal Medicine (15%). The USA, the UK, and Canada headed the absolute global productivity ranking in number of papers. The 64 authors and the 39 institutions with the highest publication rates were identified. We also found 82 clusters of authors (one group with 55 members and one group with 54 members) and 19 clusters of institutions (one major group with 76 members). The most prolific authors were mainly affiliated with the University of Oxford (UK), McMaster University (Canada), and the University of Bern (Switzerland). Conclusions Our analysis identified networks of authors, institutions and countries publishing meta-analyses of randomized trials in high impact medical journals. This valuable information may be used to strengthen scientific capacity for collaboration and to help to promote a global agenda for future research of excellence.
机译:背景研究合作通过更有效地利用科学成果来为知识的发展做出贡献,但是关于荟萃分析的全球合作模式尚不清楚。这项研究的目的是描述和表征过去三十年来在高影响因子医学期刊上发表的随机试验的荟萃分析中的全球协作模式。方法这是一个横断面的社交网络分析。我们在PubMed中搜索了截至2012年12月发布的相关随机试验的相关荟萃分析。我们选择了在前七大高影响因子普通医学期刊上发表的荟萃分析(至少包括随机试验作为主要证据来源)(根据《期刊引证报告》 2011年):《新英格兰医学杂志》,《柳叶刀》,《美国医学杂志》,《美国医学会杂志》,《内科学纪事》,《内部医学档案》(现更名为《美国医学会内科学》)和《公共科学图书馆·医学》。意见文章,概念性论文,叙述性评论,未经荟萃分析的评论,评论的评论和其他研究设计均被排除在外。结果总体而言,我们纳入了736项荟萃分析,其中3,178名作者,891个机构和51个国家/地区参加了该研究。 BMJ是发表文章最多的期刊(占39%),其次是《柳叶刀》(占18%),JAMA(占15%)和内科医学档案(占15%)。在论文数量上,美国,英国和加拿大位居全球生产力绝对榜首。确定了64位作者和39个出版率最高的机构。我们还发现了82个作者群(一组55个成员,一组54个成员)和19个机构群(一个主要组76个成员)。最多产的作者主要是牛津大学(英国),麦克马斯特大学(加拿大)和伯尔尼大学(瑞士)。结论我们的分析确定了在高影响力医学期刊上发表随机试验荟萃分析的作者,机构和国家/地区的网络。这些宝贵的信息可用于增强合作的科学能力,并有助于促进未来卓越研究的全球议程。

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