首页> 外文期刊>Evidence Based Library and Information Practice >Bibliometric Analysis Identifies Publication Trends and Most Common Research Topics Related to Internet Health Information Seeking Behaviour
【24h】

Bibliometric Analysis Identifies Publication Trends and Most Common Research Topics Related to Internet Health Information Seeking Behaviour

机译:文献计量分析可确定与互联网健康信息搜寻行为相关的出版趋势和最常见的研究主题

获取原文
       

摘要

A Review of: Li, F., Li, M., Guan, P., Ma, S., & Cui, L. (2015). Mapping publication trends and identifying hot spots of research on Internet health information seeking behavior: A quantitative and co-word biclustering analysis. Journal of Medical Internet Research, 17(3), e81. http://dx.doi.org/10.2196/jmir.3326 Objective – To identify research and publication trends related to health-seeking information behaviour on the Internet. Design – Bibliometric analysis, publication trends, and co-word biclustering analysis. Setting – Academic journals. Subjects – Journal articles retrieved from PubMed meeting eligibility criteria, and articles selected through hand-searching of the top three journals publishing in the identified area of research. Methods – A search for relevant articles was performed in PubMed and supplemented by manual searching of the top three journals in the field, yielding a total of 2,780 articles. Following a high concordance rate on screening agreement, researchers identified a total of 533 articles for inclusion. These articles were considered to be representative of all the articles published on Internet health-seeking behaviour as of September 2014. Data deemed essential to biclustering co-word analysis included article title, author, institution, country, source, publication year, and MeSH terms, and was collected in both XML and MEDLINE formats to ensure information exhaustivity for subsequent analysis. Analysis of the distribution of data, as well as major MeSH frequency ranking, allowed researchers to identify the most active journals in the subject area, while biclustering for highly frequent MeSH terms determined hot spots of research. Researchers used both mountain and matrix visualization to further illustrate semantic relationships of MeSH terms and the framework for the analysis of research hot spots. Co-word analysis facilitated the identification of like-articles based on major MeSH indexing, while cluster analysis utilized a matrix grouping to identify themes. By combining this information and reorganizing the matrix, researchers were able to highlight the most common themes. Main Results – Researchers identified ten research “hot spots,” the most prolific research topics, thus providing the top subject areas of research published in the literature related to Internet health-seeking behaviour. Top subjects include health information seeking behaviour related to HIV infection or sexually transmitted diseases; information seeking behaviour of students and of patients with cancer; consumer trust in online health information; behaviour of Internet health information seeking through mobile apps; the interaction between physician-patient relations/communications and Internet use; personal preference and computer literacy related to Internet use; and the use of social media by parents. In terms of publishing rates, the number of papers published on health information seeking behaviour has increased consistently since 1985, when only one paper was published, to 2013, in which 114 papers were published. Authors from 42 countries or regions contributed to the body of relevant literature, with authors from the United States of America accounting for over half of published papers. Just over 96% of articles were published in English. Of the 253 journals identified as publishers of these articles, eight published over one-third of all the identified articles. The Journal of Medical Internet Research published the most articles on this topic. Conclusion – Bibliographic analysis identified both subject and publication trends related to Internet health information seeking behaviour. Publication rates of research in the area of Internet health information have increased steadily since the first article was published in 1985. The bulk of the research tends to fall within ten identified hot spots, or research topics, according to a bibliometric analysis of indexing.
机译:综述:李芳,李敏,关平,马南,崔翠(2015)。绘制出版物趋势并确定互联网健康信息搜索行为研究的热点:定量和共词双聚类分析。医学互联网研究杂志,17(3),e81。 http://dx.doi.org/10.2196/jmir.3326目标–识别与互联网上寻求健康信息行为有关的研究和出版趋势。设计–文献计量分析,出版趋势和共同词双聚类分析。设置-学术期刊。主题-从符合PubMed资格标准的期刊中检索的期刊文章,以及通过人工搜索确定的研究领域中排名前三位的期刊选择的文章。方法–在PubMed中进行了相关文章的搜索,并通过对该领域排名前三位的期刊进行手动搜索进行了补充,总共产生了2,780篇文章。在筛选协议的一致性很高的情况下,研究人员确定了总共533篇纳入研究的文章。这些文章被认为是截至2014年9月有关互联网寻求健康行为的所有文章的代表。被认为对双词联合分析至关重要的数据包括文章标题,作者,机构,国家,来源,出版年份和MeSH术语,并且以XML和MEDLINE格式收集,以确保信息的完整性以用于后续分析。通过对数据分布以及主要的MeSH频率排名进行分析,研究人员可以确定主题领域中最活跃的期刊,同时对频繁使用的MeSH术语进行聚类,从而确定了研究热点。研究人员同时使用了山峰可视化和矩阵可视化,以进一步说明MeSH术语的语义关系以及研究热点分析的框架。共词分析有助于基于主要的MeSH索引识别相似的文章,而聚类分析则利用矩阵分组来识别主题。通过结合这些信息并重新组织矩阵,研究人员能够突出显示最常见的主题。主要结果–研究人员确定了十个研究“热点”,这是最多产的研究主题,从而提供了与互联网健康寻求行为有关的文献中发表的研究的最高主题领域。热门话题包括寻求与HIV感染或性传播疾病有关的行为的健康信息;学生和癌症患者的信息寻求行为;消费者对在线健康信息的信任;通过移动应用程序查找互联网健康信息的行为;医患关系/交流与互联网使用之间的相互作用;与互联网使用相关的个人喜好和计算机素养;以及父母对社交媒体的使用。从发表率来看,自1985年以来,关于健康信息搜索行为的论文发表量一直在增加,1985年只有1篇论文发表,到2013年发表了114篇论文。来自42个国家或地区的作者为相关文献做出了贡献,来自美利坚合众国的作者占已发表论文的一半以上。超过96%的文章以英文发表。在被确定为这些文章的253种期刊中,有八种发表的文章超过了所识别文章的三分之一。医学互联网研究杂志发表了有关该主题的最多文章。结论–书目分析确定了与互联网健康信息搜寻行为有关的主题和出版趋势。自1985年第一篇文章发表以来,互联网健康信息领域的研究发表率一直稳定增长。根据对索引的文献计量分析,大部分研究倾向于落入十个确定的热点或研究主题之内。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号