Research Article
Comparisons of citations among clusters of medical subject headings using visualizing topic burst on neuropsychiatry: a bibliometric analysis
Willy ChouBackground: PubMed is a primary source of biomedical information comprising search tool function and the biomedical literature from MEDLINE. A new method using Medical Subject Headings (MdSH) is needed for searching the knowledge in the neuropsychiatry field. Methods: A new method is proposed in this study for visualizing the recent research trends based on the retrieved MeSH terms corresponding to a search query given by the user. MeSH terms are extracted from Pubmed Central (PMC) based on the keyword of neuropsychiatry [All Fields] through a series of calculations on correlations between terms using Social Network Analysis (SNA). We illustrated four bibliometrics to compare differences among MeSH clusters and verified whether article types might be disparate regarding MeSH terms and citations. We programmed Microsoft Excel VBA routines to extract data. Google Maps and Pajek software were used for displaying graphical representations. Results: We found that (1) the dominant nation on the topic of neuropsychiatry is the US; (2) the MeSH terms of neuropsychiatry, diagnosis, and physiopathology gain the top degree centralities based on SNA; (3) the Mesh term of physiology owns the highest metrics with Impact Factor (IF)=30.37, h-index=6, and x=14.97, respectively; (4) differences were found significantly among MeSH clusters on neuropsychiatry (p<0.05) using 95% confidence intervals of the bootstrapping method; (5) the article(PMID=2190539) published in 1990 was cited most (with 285 times and two MeSH term of diagnosis and psychiatric status rating scales. Conclusions: The application of the MeSH cluster analysis, which could be used as a “guide map for travelers,†allows users to quickly and easily acquire the knowledge of research trends. Combination of PubMed and MeSH citations is expected to be an effective complementary way for the researchers in the biomedical field experiencing difficulties with search and information analysis.