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Dynamic meta-analysis: a method of using global evidence for local decision making
BACKGROUND: Meta-analysis is often used to make generalisations across all available evidence at the global scale. But how can these global generalisations be used for evidence-based decision making at the local scale, if the global evidence is not perceived to be relevant to local decisions? We sho...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888140/ https://www.ncbi.nlm.nih.gov/pubmed/33596922 http://dx.doi.org/10.1186/s12915-021-00974-w |
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author | Shackelford, Gorm E. Martin, Philip A. Hood, Amelia S. C. Christie, Alec P. Kulinskaya, Elena Sutherland, William J. |
author_facet | Shackelford, Gorm E. Martin, Philip A. Hood, Amelia S. C. Christie, Alec P. Kulinskaya, Elena Sutherland, William J. |
author_sort | Shackelford, Gorm E. |
collection | PubMed |
description | BACKGROUND: Meta-analysis is often used to make generalisations across all available evidence at the global scale. But how can these global generalisations be used for evidence-based decision making at the local scale, if the global evidence is not perceived to be relevant to local decisions? We show how an interactive method of meta-analysis—dynamic meta-analysis—can be used to assess the local relevance of global evidence. RESULTS: We developed Metadataset (www.metadataset.com) as a proof-of-concept for dynamic meta-analysis. Using Metadataset, we show how evidence can be filtered and weighted, and results can be recalculated, using dynamic methods of subgroup analysis, meta-regression, and recalibration. With an example from agroecology, we show how dynamic meta-analysis could lead to different conclusions for different subsets of the global evidence. Dynamic meta-analysis could also lead to a rebalancing of power and responsibility in evidence synthesis, since evidence users would be able to make decisions that are typically made by systematic reviewers—decisions about which studies to include (e.g. critical appraisal) and how to handle missing or poorly reported data (e.g. sensitivity analysis). CONCLUSIONS: In this study, we show how dynamic meta-analysis can meet an important challenge in evidence-based decision making—the challenge of using global evidence for local decisions. We suggest that dynamic meta-analysis can be used for subject-wide evidence synthesis in several scientific disciplines, including agroecology and conservation biology. Future studies should develop standardised classification systems for the metadata that are used to filter and weight the evidence. Future studies should also develop standardised software packages, so that researchers can efficiently publish dynamic versions of their meta-analyses and keep them up-to-date as living systematic reviews. Metadataset is a proof-of-concept for this type of software, and it is open source. Future studies should improve the user experience, scale the software architecture, agree on standards for data and metadata storage and processing, and develop protocols for responsible evidence use. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-00974-w. |
format | Online Article Text |
id | pubmed-7888140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78881402021-02-22 Dynamic meta-analysis: a method of using global evidence for local decision making Shackelford, Gorm E. Martin, Philip A. Hood, Amelia S. C. Christie, Alec P. Kulinskaya, Elena Sutherland, William J. BMC Biol Methodology Article BACKGROUND: Meta-analysis is often used to make generalisations across all available evidence at the global scale. But how can these global generalisations be used for evidence-based decision making at the local scale, if the global evidence is not perceived to be relevant to local decisions? We show how an interactive method of meta-analysis—dynamic meta-analysis—can be used to assess the local relevance of global evidence. RESULTS: We developed Metadataset (www.metadataset.com) as a proof-of-concept for dynamic meta-analysis. Using Metadataset, we show how evidence can be filtered and weighted, and results can be recalculated, using dynamic methods of subgroup analysis, meta-regression, and recalibration. With an example from agroecology, we show how dynamic meta-analysis could lead to different conclusions for different subsets of the global evidence. Dynamic meta-analysis could also lead to a rebalancing of power and responsibility in evidence synthesis, since evidence users would be able to make decisions that are typically made by systematic reviewers—decisions about which studies to include (e.g. critical appraisal) and how to handle missing or poorly reported data (e.g. sensitivity analysis). CONCLUSIONS: In this study, we show how dynamic meta-analysis can meet an important challenge in evidence-based decision making—the challenge of using global evidence for local decisions. We suggest that dynamic meta-analysis can be used for subject-wide evidence synthesis in several scientific disciplines, including agroecology and conservation biology. Future studies should develop standardised classification systems for the metadata that are used to filter and weight the evidence. Future studies should also develop standardised software packages, so that researchers can efficiently publish dynamic versions of their meta-analyses and keep them up-to-date as living systematic reviews. Metadataset is a proof-of-concept for this type of software, and it is open source. Future studies should improve the user experience, scale the software architecture, agree on standards for data and metadata storage and processing, and develop protocols for responsible evidence use. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-00974-w. BioMed Central 2021-02-17 /pmc/articles/PMC7888140/ /pubmed/33596922 http://dx.doi.org/10.1186/s12915-021-00974-w Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Article Shackelford, Gorm E. Martin, Philip A. Hood, Amelia S. C. Christie, Alec P. Kulinskaya, Elena Sutherland, William J. Dynamic meta-analysis: a method of using global evidence for local decision making |
title | Dynamic meta-analysis: a method of using global evidence for local decision making |
title_full | Dynamic meta-analysis: a method of using global evidence for local decision making |
title_fullStr | Dynamic meta-analysis: a method of using global evidence for local decision making |
title_full_unstemmed | Dynamic meta-analysis: a method of using global evidence for local decision making |
title_short | Dynamic meta-analysis: a method of using global evidence for local decision making |
title_sort | dynamic meta-analysis: a method of using global evidence for local decision making |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888140/ https://www.ncbi.nlm.nih.gov/pubmed/33596922 http://dx.doi.org/10.1186/s12915-021-00974-w |
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