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Considerations for conducting systematic reviews: evaluating the performance of different methods for de-duplicating
Sandra McKeown1, Zuhaib M Mir2
1Bracken Health Sciences Library, Queen's University, 18 Stuart Street, Kingston, Ontario, K7L 2V5, Canada. sandra.mckeown@queensu.ca.
Systematic Reviews
|January 24, 2021
Summary
Ovid, Covidence, and Rayyan showed the highest accuracy in de-duplicating references for systematic reviews. Ovid and Covidence excelled in specificity, while Rayyan led in sensitivity for duplicate identification.
Area of Science:
- Information Science
- Medical Informatics
- Bibliometrics
Background:
- Systematic reviews require comprehensive searches across multiple databases.
- Electronic platforms enhance efficiency and quality in evidence synthesis.
- Accurate de-duplication of references is crucial for systematic review integrity.
Purpose of the Study:
- To evaluate the accuracy and efficiency of common electronic de-duplication methods.
- To compare the performance of various software tools in identifying duplicate references.
- To inform the selection of de-duplication tools for systematic reviews.
Main Methods:
- A reference set was created by searching MEDLINE, Embase, Cochrane, and PsycINFO.
- Manual abstraction established a benchmark set for de-duplication.
- Ovid multifile search, EndNote, Mendeley, Zotero, Covidence, and Rayyan were tested using default settings.
Main Results:
- Ovid, Covidence, and Rayyan were the most accurate de-duplication methods.
- Ovid and Covidence demonstrated the highest specificity.
- Rayyan exhibited the highest sensitivity in identifying duplicate references.
Conclusions:
- Understanding the strengths and weaknesses of de-duplication tools is vital.
- Strategies to improve de-duplication performance can prevent bias and loss of studies.
- Factors like accuracy, ease-of-use, and functionality should guide software selection for systematic reviews.
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