摘要：

【目的】 将知识图谱软件CiteSpace和质性研究的方法应用到医学期刊选题策划实践中,初步构建一种文献计量学分析辅助选题策划的模式。【方法】 采用CiteSpace软件对国内与国际心血管病专业影响因子排名前3的6种医学期刊进行关键词共现分析与聚类分析,挖掘国内期刊在重点、热点选题方面与国际期刊的差异,作为备用选题。挖掘出的备用选题经CiteSpace初步分析后,邀请专家进行质性研究验证。将基于CiteSpace的文献计量学选题方式与专家选题方式相结合,构建一种双线并行的选题策划模式。【结果】 以挖掘出的备用选题“心血管疾病预防”为例,CiteSpace初步分析显示,国内期刊中该选题发文较少,且多数为指南或指南解读,研究论文和综述偏少,可以采用约稿与公开征稿相结合的方式进行组稿。进一步的质性研究中,专家均对该选题的价值给予认可,并明确了具体的主题方向,包括心血管疾病预防的现状、流行趋势、风险评估以及血压、血糖控制等。【结论】 CiteSpace分析和质性研究可以作为辅助方式,构建专家选题与文献计量学分析选题相结合的选题策划模式,为大数据时代医学期刊的高质量发展提供多元化途径。

关键词: 选题策划, 文献计量学, 可视化分析, 医学期刊

Abstract:

[Purposes] In this paper, we try to apply the knowledge map software CiteSpace and qualitative study to the topic selection of medical journals, thereby establishing a bibliometrics-based topic selection mode. [Methods] CiteSpace was employed for co-occurrence analysis and cluster analysis of the keywords in the top three (in terms of impact factor) medical journals on cardiovascular disease, respectively in China and abroad. On this basis, we analyzed the differences in key and hot topics on such aspect between China and abroad, which were tentatively used as candidate topics and then verified by related experts. Thereby, a new topic selection mode combining the CiteSpace-based bibliometrics method and expert verification was constructed. [Findings] Taking the CiteSpace-yielded candidate topic "prevention of cardiovascular diseases" as an example, CiteSpace analysis demonstrated that there were few related research papers or reviews in China and that most were guidelines or interpretations of guidelines. Thus, papers in this aspect should be solicited by targeted solicitation and public solicitation. Through qualitative study, experts confirmed the value of this topic and defined specific subtopics: the status quo of cardiovascular disease prevention, epidemic, risk assessment, control of blood pressure and glucose, etc. [Conclusions] CiteSpace and qualitative study can be combined to build a simple topic selection mode, which can facilitate the high-quality development of medical journals in the era of big data.

Key words: Topic selection, Bibliometrics, Visual analysis, Medical journal