通过关键词共发生网络分析疼痛研究文献
Burcu Ozek1, Zhenyuan Lu1, Fatemeh Pouromran1
1Mechanical and Industrial Engineering Department, Northeastern University, Boston, Massachusetts, United States of America.
PLOS digital health
|September 7, 2023
概括
疼痛研究正在迅速扩大,关键词分析揭示了传感器,生物医学应用和治疗的关键趋势. 这项研究绘制了疼痛科学不断发展的景观,以指导未来的研究方向.
科学领域:
- 多学科疼痛研究研究
- 图书统计学 图书统计学
- 网络科学 网络科学
背景情况:
- 疼痛代表着一个日益增长的全球公共卫生挑战.
- 许多研究领域正在融合在一起,以解决疼痛问题.
- 了解研究趋势对于推进疼痛管理至关重要.
研究的目的:
- 分析疼痛研究文献的结构和演变.
- 使用文献计量方法识别新兴和下降的研究趋势.
- 在疼痛研究领域绘制知识协同效应.
主要方法:
- 关键词同时出现网络 (KCN) 方法应用于文献计量数据.
- 从2002年到2021年,分析了264,560篇与疼痛相关的文章.
- 提取关键词同时出现的对和集群.
主要成果:
- 疼痛文献的显著增长 (文章增加了近三倍,关键词增加了七倍).
- 识别传感器/方法,生物医学和治疗研究中的动态趋势.
- 经常同时出现的关键词的映射,突出跨学科的联系.
结论:
- 疼痛研究在过去二十年中经历了大幅增长和多元化.
- 在KCN分析中,有效地可视化了疼痛科学中不断变化的知识结构和研究前沿.
- 这些发现为研究人员在复杂的疼痛研究领域中提供了宝贵的见解.
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