Suppr超能文献

利用2014年以来被引频次最高的100篇文章预测注意力缺陷多动障碍(ADHD)领域的文章被引次数:一项文献计量分析。

Predicting the number of article citations in the field of attention-deficit/hyperactivity disorder (ADHD) with the 100 top-cited articles since 2014: a bibliometric analysis.

作者信息

Lin Chien-Ho, Chien Tsair-Wei, Yan Yu-Hua

机构信息

Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwan.

Department of Medical Research, Chi-Mei Medical Center, No. 901, Chung Hwa Road, Yung Kung Dist., Tainan, 710, Taiwan.

出版信息

Ann Gen Psychiatry. 2021 Jan 21;20(1):6. doi: 10.1186/s12991-021-00329-3.

Abstract

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children or early adolescents with an estimated worldwide prevalence of 7.2%. Numerous articles related to ADHD have been published in the literature. However, which articles had ultimate influence is still unknown, and what factors affect the number of article citations remains unclear as well. This bibliometric analysis (1) visualizes the prominent entities with 1 picture using the top 100 most-cited articles, and (2) investigates whether medical subject headings (i.e., MeSH terms) can be used in predicting article citations.

METHODS

By searching the PubMed Central (PMC) database, the top 100 most-cited abstracts relevant to ADHD since 2014 were downloaded. Citation rank analysis was performed to compare the dominant roles of article types and topic categories using the pyramid plot. Social network analysis (SNA) was performed to highlight prominent entities for providing a quick look at the study result. The authors examined the MeSH prediction effect on article citations using its correlation coefficients (CC).

RESULTS

The most frequent article types and topic categories were research support by institutes (56%) and epidemiology (28%). The most productive countries were the United States (42%), followed by the United Kingdom (13%), Germany (9%), and the Netherlands (9%). Most articles were published in the Journal of the American Academy of Child and Adolescent Psychiatry (15%) and JAMA Psychiatry (9%). MeSH terms were evident in prediction power on the number of article citations (correlation coefficient = 0.39; t = 4.1; n = 94; 6 articles were excluded because they do not have MeSH terms).

CONCLUSIONS

The breakthrough was made by developing 1 dashboard to display 100 top-cited articles on ADHD. MeSH terms can be used in predicting article citations on ADHD. These visualizations of the top 100 most-cited articles could be applied to future academic pursuits and other academic disciplines.

摘要

背景

注意力缺陷多动障碍(ADHD)是儿童或青少年早期常见的神经发育障碍,全球估计患病率为7.2%。文献中已发表了许多与ADHD相关的文章。然而,哪些文章具有最终影响力仍不明确,影响文章被引用次数的因素也尚不清楚。这项文献计量分析(1)使用被引用次数最多的前100篇文章,用一张图直观展示突出的实体;(2)研究医学主题词(即MeSH词)是否可用于预测文章被引用次数。

方法

通过搜索PubMed Central(PMC)数据库,下载了自2014年以来与ADHD相关的被引用次数最多的前100篇摘要。使用金字塔图进行引用排名分析,以比较文章类型和主题类别的主导作用。进行社会网络分析(SNA)以突出突出的实体,以便快速了解研究结果。作者使用相关系数(CC)检验MeSH对文章被引用次数的预测效果。

结果

最常见的文章类型和主题类别是机构研究支持(56%)和流行病学(28%)。发文量最多的国家是美国(42%),其次是英国(13%)、德国(9%)和荷兰(9%)。大多数文章发表在《美国儿童与青少年精神病学会杂志》(15%)和《美国医学会精神病学杂志》(9%)上。MeSH词在预测文章被引用次数方面具有显著的预测能力(相关系数 = 0.39;t = 4.1;n = 94;6篇文章因没有MeSH词而被排除)。

结论

通过开发一个仪表板来展示100篇关于ADHD的高被引文章取得了突破。MeSH词可用于预测ADHD文章的被引用次数。这些前100篇高被引文章的可视化展示可应用于未来的学术研究和其他学科。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3d9/7819196/cda802099541/12991_2021_329_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验