Analysis of research trends in Korean dentistry journals by assigning MeSH to author keywords. Issue 38 (18th September 2020)

• Record Type: Journal Article
• Authors: Jeong, Sona; Jeong, Ji Na
• Other Names: Zheng. Li Wu section editor.
• Is Part Of: Medicine. Volume 99:Issue 38(2020)
• Publication Date: 2020-09-18
• Subjects: co-word analysis -- dentistry -- medical subject headings -- network analysis clustering -- subject categories; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000022190
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Researchers seek to identify optimal journals for submission based on their studies but tend to rely on journal impact factors or scientific journal rankings. We investigated research trends by selecting high-frequency words from author keywords (AKs), analyzing subject areas, and performing quantitative data analysis of Korean dental journals. Consequently, we suggest a method for choosing journals that fit a specific subject area. We used a corpus of 9 Korean dentistry journals regarded in Korea as quality internationally approved journals. AKs occurring more than 10 times were assigned to Medical Subject Headings (MeSH) terms and subcategories, which were then categorized using the MeSH tree structure. KnowledgeMatrix Plus and VOSviewer were used to analyze network relationships, density, and clustering. The AKs were of 7527 types, 15, 960 terms, and formed 54 clusters. The AKs with 10+ occurrence were 199 types, 4289 terms, and formed 9 clusters. Assigning the AKs with 10+ occurrence to MeSH terms led to expanding 732 types of AK terms into 249 types with 9 clusters and 4268 links. Core study areas over the past 10 years were facial asymmetry, a topic under oral surgery and medicine, and orthognathic surgery focused on mandibular fractures, followed by shear bond strength of zirconia. Analyzing 16 MeSH subject categories, we found that the "analytical, diagnostic and therapeutic techniques and equipment" category had the largest distribution of AKs (40.7%). This was followed by "diseases" (21.2%) and "anatomy" (14.90%). The orthognathic surgery cluster was the largest, followed by the shear bond strength cluster. Dental implants is a core area with strong links to high-occurrence words, such as cone-beam computed tomography and mandible, which were distributed in the order of The Journal of Advanced Prosthodontics (37.8%) and Journal of Periodontal & Implant Science (30.6%). Five clusters were closely packed in the center, 2 clusters were formed above the center, 1 cluster was formed below the center, and a cluster on the right was widespread. Cluster analysis using AKs and MeSH may be a good analytic method for researchers to determine expanding research areas and select optimal journals for paper submission. Abstract : Supplemental Digital Content is available in the text