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Bayesian approach for meta-analyses in biomedical research: a scoping review protocol
Joseph Alvin Santos1, Emilia Riggi2, Robert Grant3,4
1Department of Business Economics, Health and Social Care (DEASS), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Manno, Ticino, Switzerland.
Objective:
The overarching aim of this scoping review is to describe and analyze the scope of use and reporting of Bayesian methods in meta-analyses in biomedical research.
Introduction:
The Bayesian approach provides a powerful and flexible framework for meta-analysis, particularly suited for dealing with complex, sparse, or heterogeneous data. Due to these advantages and its appeal, Bayesian methods have been increasingly used in many areas of biomedical research; however, their use in meta-analysis remains scarce.
Inclusion Criteria:
This review will include studies that used Bayesian methods for meta-analysis of primary studies in biomedical research.
Methods:
The proposed review will be conducted in accordance with the JBI methodology for scoping reviews. PubMed, Embase, CINAHL, and the Cochrane Database of Systematic Reviews will be searched to identify relevant full-text papers published since 2016 in English. No geographical restriction will be applied. Two reviewers will screen the articles and extract the data using a tool that will be pilot-tested and revised, as necessary. Analysis will involve frequency counts, narrative synthesis, and mapping concepts to propose an appropriate workflow. The details of the scoping review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guideline.
Review Registration:
Open Science Framework https://osf.io/jenp4/.
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