Dataset Information

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.

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.

SUBMITTER: Lin CH

PROVIDER: S-EPMC7819196 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

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.

Lin Chien-Ho CH Chien Tsair-Wei TW Yan Yu-Hua YH

Annals of general psychiatry 20210121 1

<h4>Background</h4>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 ...[more]

PMID: 33478559

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Project description:BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a common neuro developmental disorder that affects children and adolescents. It is estimated that the prevalence of ADHD is 7.2% throughout the world. There have been a number of articles published in the literature related to ADHD. However, it remains unclear which countries, journals, subject categories, and articles have the greatest influence. The purpose of this study was to display influential entities in 100 top-cited ADHD-related articles (T100ADHD) on an alluvial plot and apply alluvial to better understand the network characteristics of T100ADHD across entities.MethodsUsing the PubMed and Web of Science (WoS) databases, T100ADHD data since 2011 were downloaded. The dominant entities were compared using alluvial plots based on citation analysis. Based on medical subject headings (MeSH terms) and research areas extracted from PubMed and WoS, social network analysis (SNA) was performed to classify subject categories. To examine the difference in article citations among subject categories and the predictive power of MeSH terms on article citations in T100ADHD, one-way analysis of variance and regression analysis were used.ResultsThe top 3 countries (the United States, the United Kingdom, and the Netherlands) accounted for 75% of T100ADHD. The most citations per article were earned by Brazil (=415.33). The overall impact factor (IF = citations per 100) of the T100ADHD series is 188.24. The most cited article was written by Polanczyk et al from Brazil, with 772 citations since 2014. The majority of the articles were published and cited in Biol Psychiatry (13%; IF = 174.15). The SNA was used to categorize 6 subject areas. On the alluvial plots, T100ADHD's network characteristics were successfully displayed. There was no difference in article citations among subject categories (F = 1.19, P = .320). The most frequently occurring MeSH terms were physiopathology, diagnosis, and epidemiology. A significant correlation was observed between MeSH terms and the number of article citations (F = 25.36; P < .001).ConclusionDrawing the alluvial plot to display network characteristics in T100ADHD was a breakthrough. Article subject categories can be classified using MeSH terms to predict T100ADHD citations. Bibliometric analyses of 100 top-cited articles can be conducted in the future.

Project description:BackgroundPublications regarding the 100 top-cited articles in a given discipline are common, but studies reporting the association between article topics and their citations are lacking. Whether or not reviews and original articles have a higher impact factor than case reports is a point for verification in this study. In addition, article topics that can be used for predicting citations have not been analyzed. Thus, this study aims to METHODS:: We searched PubMed Central and downloaded 100 top-cited abstracts in the journal Medicine (Baltimore) since 2011. Four article types and 7 topic categories (denoted by MeSH terms) were extracted from abstracts. Contributors to these 100 top-cited articles were analyzed. Social network analysis and Sankey diagram analysis were performed to identify influential article types and topic categories. MeSH terms were applied to predict the number of article citations. We then examined the prediction power with the correlation coefficients between MeSH weights and article citations.ResultsThe citation counts for the 100 articles ranged from 24 to 127, with an average of 39.1 citations. The most frequent article types were journal articles (82%) and comparative studies (10%), and the most frequent topics were epidemiology (48%) and blood and immunology (36%). The most productive countries were the United States (24%) and China (23%). The most cited article (PDID = 27258521) with a count of 135 was written by Dr Shang from Shandong Provincial Hospital Affiliated to Shandong University (China) in 2016. MeSH terms were evident in the prediction power of the number of article citations (correlation coefficients = 0.49, t = 5.62).ConclusionThe breakthrough was made by developing dashboards showing the overall concept of the 100 top-cited articles using the Sankey diagram. MeSH terms can be used for predicting article citations. Analyzing the 100 top-cited articles could help future academic pursuits and applications in other academic disciplines.

Project description:IntroductionIn the last 120 years, the field of pediatric urology has seen an exponential growth. In this time, there has not been a comprehensive review of top cited articles within the field.ObjectivesWe aim to identify and categorize the top 100 most cited peer-reviewed articles in pediatric urology using citation analysis.Study designWe searched for articles in the Web of Science™ Core Collection between 1900 and 2020 using terms specific to pediatric urology. We identified relevant pediatric urology articles and selected the top 100 most cited articles. We analysed trends over time for topics and categories and we evaluated the relatedness of these articles using citation analysis software.ResultsThe top 100 most cited articles in pediatric urology were published between 1958 and 2016 in 26 countries, across 181 institutions, and in 46 journals. The median number of citations per article was 268 (IQR 225.75-394.25). Clinical manuscripts were the most common among the top 100 cited articles (n = 64) and the most common topic was genital conditions (e.g., penile, inguinal, or testis but not including hypospadias) (n = 19; 16.5%; total citations = 6591). When using bibliometric software to analyse relatedness among the top 100 articles based on citation of one another, we identified 11 clusters of 3 or more articles which corresponded to topics like those we defined a priori (Summary Figure). We found that a greater proportion of articles describing surgical techniques were published prior to 1987 (n = 6, 38%) as compared to after 1987 (n = 11, 13%), while the proportion of basic science articles has increased.DiscussionThis is the first study to analyse the most cited articles in pediatric urology. There was a lower median citation per article and fewer prospective studies in this list compared to other urologic sub-specialties. Similar to other clinical specialties, the focus has moved from describing and comparing operative techniques to exploring mechanisms of disease. This study is limited by using a single parameter (citation rate) and a single citation database.ConclusionThe list of top 100 most cited articles in pediatric urology is an important resource for clinicians and trainees to understand the body of knowledge and trajectory of this field. It charts the evolution of the field and highlights areas of potential investigation. This objective approach to literature review can facilitate future research and education efforts.

Dataset Information

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.

Background

Methods

Results

Conclusions

Publications

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.

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