摘要
目的:从文献计量学分析角度探讨国际上2009〜2018认知功能障碍领域的研究热点。方法:对2009-2018年Web of science数据库收录的关于认知功能障碍的相关文献进行计量学分析,采用ISI web of science文献计量分析系统以及中科院文献计量在线分析平台对高频主题词和发文量变化趋势等进行系统分析。结果:分析显示有关认知功能障碍的发文数量呈现逐年快速上升趋势。位居前5位的研究热点为神经科学、精神病学、行为科学、心理学和老年医学。高频主题词主要聚类于4个类别:阿尔茨海默病神经影像学方案、老龄化的生物标志物和生活方式研究、年龄代码研究、医学认知功能。结论:2009~2018年国际上对认知功能障碍的研究逐年关注,本研究结果为我国认知功能障碍研究及相关干预等提供了参考依据。
Objective:From the perspective of literature metrology analysis,the article aims to investigate the nearly 10 years'international research hotspot in the field of cognitive dysfunction.Methods:A bibliometric analysis was conducted on the literature related to cognitive dysfunction collected in the database of web of science from 2009 to 2010,and ISI Web of Science Literature Measurement Analysis System and Online Analysis Platform for Bibliometrics of Chinese Academy of Sciences were used to conduct systematic analysis of the high-frequency Subject Headings and trends in the number of published articles.Results:The analysis showed that the number of articles related to cognitive dysfunction published was on the rapid increasing trend year by year.The top five research focus were on neuroscience,psychiatry,behavioral science,psychology,and geriatric medicine.And high frequency subject headings are mainly clustered into four categories:alzheimer's disease neuroimaging scheme,biomarkers of aging and lifestyle,age code study,cognitive function of medicine.Conclusions:In the recent 10 years,international studies on cognitive dysfunction have been paying close attention year by year.The results of this study have provided a reference basis for researches on cognitive dysfunction and related interventions in our country.
作者
魏兵
覃泱
张均智
WEI Bing;QIN Yang;ZHANG Junzhi(College of International Education of Guilin Medical University,Guilin 541199;The Affiliated Hospital of Guilin Medical University,Guilin 541001,China)
出处
《华夏医学》
CAS
2019年第4期37-41,共5页
Acta Medicinae Sinica
基金
桂林医学院人才引进科研启动项目资助(31304019009)。
关键词
认知功能障碍
文献计量分析
聚类分析
高频主题词
cognitive impairment
bibliometric analysis
cluster analysis
high-frequency subject headings