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    Defining the exit meta-Analysis

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    Date
    2024-01-01
    Author
    Abdulmajeed, Jazeel
    Furuya-Kanamori, Luis
    Chivese, Tawanda
    Xu, Chang
    Thalib, Lukman
    Doi, Suhail A.R.
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    Abstract
    Introduction: In recent decades, clinical research has seen significant advancements, both in the generation and synthesis of evidence through meta-Analyses. Despite these methodological advancements, there is a growing concern about the accumulation of repetitive and redundant literature, potentially contributing to research waste. This highlights the necessity for a mechanism to determine when a meta-Analysis has conclusively addressed a research question, signaling no further need for additional studies-a concept we term an "exit"meta-Analysis. Methods: We introduced a convergence index, the Doi-Abdulmajeed Trial Stability (DAts) index, and a convergence plot to determine the exit status of a meta-Analysis. The performance of DAts was examined through simulation and applied to two real-world meta-Analyses. Results: The DAts index and convergence plot demonstrate highly effective discriminative ability across varying study scenarios. This represents the first attempt to define an exit meta-Analysis using a quantitative measurement of stability (as opposed to sufficiency) and its corresponding plot. The application to real-world scenarios further validated the utility of DAts and the convergence plot in identifying a conclusive (exit) meta-Analyses. Conclusion: The new development of DAts and the convergence plot provide a promising tool for investigating the conclusiveness of meta-Analyses. By identifying an exit status for meta-Analysis, the scientific community may be equipped to make better-informed decisions on the continuation of research on a specific topic, thereby preventing research waste and focusing efforts on areas with unresolved questions.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85203634279&origin=inward
    DOI/handle
    http://dx.doi.org/10.11124/JBIES-24-00155
    http://hdl.handle.net/10576/59773
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    • Medicine Research [‎1739‎ items ]

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