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Graph Quality in Top Medical Journals.
Jennifer C Chen1, Richelle J Cooper2, Michael E McMullen3
1Department of Emergency Medicine, Harbor-UCLA Medical Center, Torrance, CA; UCLA School of Medicine.
Annals of Emergency Medicine
|November 28, 2016
Summary
Graphs are underused and poorly designed in medical literature, often showing simple data instead of distributions. This limits effective communication of complex research findings.
Area of Science:
- Medical research visualization
- Scientific communication
Background:
- Well-designed graphs enhance data interpretation.
- Previous studies indicate underutilization and poor quality of graphs in clinical research.
Purpose of the Study:
- To evaluate the quantity and quality of data graphs in high-impact medical journals.
- To assess graph types, data density, and visual characteristics.
Main Methods:
- Cross-sectional survey of 20 highly cited journals.
- Analysis of 10 articles per journal, with up to 5 data graphs per article.
- Evaluation of graph type, data density, completeness, and clarity.
Main Results:
- 342 data graphs were analyzed.
- Mean data density was low (1.18 data elements/cm²).
- Over half (54%) were simple univariate displays; data distribution was often not shown.
Conclusions:
- Graphs are infrequently used and have low data density in medical literature.
- Common graph types fail to display overall data distribution effectively.
- Improving graph design is crucial for clear scientific communication.
