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BMJ Mental Health, 1(26), p. e300534, 2023

DOI: 10.1136/bmjment-2022-300534

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metaumbrella: the first comprehensive suite to perform data analysis in umbrella reviews with stratification of the evidence

Journal article published in 2023 by Corentin J. Gosling ORCID, Aleix Solanes, Paolo Fusar-Poli, Joaquim Radua
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

ObjectiveUmbrella reviews are a new form of literature review that summarises the strength and/or quality of the evidence from all systematic reviews and meta-analyses conducted on a broad topic. This type of review thus provides an exhaustive examination of a vast body of information, providing the highest synthesis of knowledge. A critical strength of umbrella reviews is recalculating the meta-analytic estimates within a uniform framework to allow a consistent evidence stratification. To our best knowledge, there is no comprehensive package or software to conduct umbrella reviews.MethodsThe R package metaumbrella accomplishes this aim by building on three core functions that (1) automatically perform all required calculations in an umbrella review (including but not limited to pairwise meta-analyses), (2) stratify evidence according to various classification criteria and (3) generate a visual representation of the results. In addition, this package allows flexible inputs for each review or meta-analysis analysed (eg, means plus SD, or effect size estimate and CI) and customisation (eg, stratification criteria following Ioannidis, algorithmic GRADE or personalised classification).ResultsThe R package metaumbrella thus provides the first comprehensive range of facilities to perform umbrella reviews with stratification of the evidence.ConclusionTo facilitate the use of this package, even for researchers unfamiliar with R, we also provide a JAMOVI module and an open-access, browser-based graphical interface that allow use of the core functions of the package with a few mouse clicks.