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Comparing the similarity and differences in MeSH terms associated with spine-specific journals using the forest plot:
Chao-Hung Yeh1,2, Tsair-Wei Chien3, Jui-Chung John Lin4
1Department of Neurosurgery, Chi Mei Medical Center, Tainan, Taiwan.
Medicine
|November 7, 2022
Summary
Social network analysis and forest plots help authors find similar research journals. This study compared Spine (Phila Pa 1976) and Spine J, finding "surgery" as a key differentiating MeSH term.
Area of Science:
- Bibliometrics and scientometrics
- Information science
- Medical informatics
Background:
- Comparing research journals and their publications is crucial but lacks clear methodologies.
- Authors need efficient methods to identify journals in similar fields.
- This study addresses the need for a systematic approach to journal comparison.
Purpose of the Study:
- To compare journal similarities and differences using social network analysis (SNA) and forest plots.
- To identify clusters of journals related to Spine (Phila Pa 1976).
- To analyze the odds ratios of major medical subject headings (MeSH terms) between Spine (Phila Pa 1976) and Spine J.
Main Methods:
- Downloaded 1000 articles from PubMed related to Spine (Phila Pa 1976).
- Utilized social network analysis (SNA) to cluster related journals.
- Employed forest plots to compare MeSH term odds ratios between Spine (Phila Pa 1976) and Spine J, assessing heterogeneity with Q statistic and I-square index.
Main Results:
- Identified 8 journal clusters related to Spine (Phila Pa 1976) using SNA.
- Found "surgery" as the only MeSH term with significant odds ratio differences between the two journals.
- Observed homogeneity in MeSH term analysis (I2 = 17.7%, P = .27).
Conclusions:
- SNA and forest plots effectively visualize inter-journal relationships and target journal characteristics.
- MeSH term analysis using these methods provides valuable insights for authors.
- The findings offer knowledge and concept diagrams for future submissions to related journals.
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