Unveiling the knowledge domain and emerging trends of olfactory dysfunction with depression or anxiety: A bibliometrics study

FRONTIERS IN NEUROSCIENCE(2022)

引用 2|浏览1
暂无评分
摘要
Olfactory dysfunction (OD) accompanied by depression or anxiety is a very common clinical problem, and there has been a growing number of studies on OD with depression or anxiety in recent decades. This study performed bibliometric and visual analyses of the literature on OD with depression or anxiety to derive research trends and identify emerging research foci. Relevant publications were obtained from the Science Citation Index-Expanded and Social Sciences Citation Index in the Web of Science Core Collection databases (2002-2021). CiteSpace and VOSviewer were applied to identify and evaluate research foci and emerging trends in this research domain. The analyses found that the number of publications related to OD with depression or anxiety has increased significantly over the past 20 years, up from 15 in 2002 to 114 in 2022. The country that ranked highest in the number of articles and international cooperation was the United States. The top 10 most frequent keywords were "depression," "olfaction," "anxiety," "dysfunction," "olfactory bulbectomy," "olfactory dysfunction," "Parkinson's disease," "odor identification," "brain," and "disorders." Analysis of keywords with the strongest citation bursts revealed that "oxidative stress" is an emerging research hotspot. A timeline chart of the cluster of co-cited references demonstrated that Parkinson's disease was always a topic of interest in this area of research. This study conducted an objective, comprehensive, and systematic analysis of these publications, and identified the development of trends and hotspots in this research domain. It is hoped that this work will provide scholars, worldwide, with information to assist them in further research and the development of new therapies.
更多
查看译文
关键词
olfactory dysfunction, depression, anxiety, visual analysis, bibliometric analysis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要