Another solution is to assess the relevance of existing research that does not exactly match the local context (e.g. “co-production” of knowledge), but that takes time and money and may be impractical or impossible for many decisions. One solution to this problem is to commission new research and/or new reviews that exactly match the local context (e.g. The lack of context-specific evidence is a problem in evidence-based decision making. Instead, researchers may only publish an answer to a more generic question. In the above example of conservation agriculture, the researchers used meta-regression to ask, “How effective is conservation agriculture in different climates?” But the decision makers may want to ask, “How effective is conservation agriculture in my climate or in my country?” Researchers may not provide an answer to this question, not only because they do not know which variables will define the context for different decision makers, but also because they do not have the time and space to analyse and publish the results for all combinations and permutations of context-defining variables. Subgroup analysis and meta-regression are standard methods of meta-analysis that can be used to answer this question, but the researchers who produce a meta-analysis may not answer the specific question that the decision makers want answered. What is needed is a method of meta-analysis that enables decision makers to answer the question, “How effective is this intervention in my specific context?”. Therefore, it can be difficult to use meta-analysis to make decisions about interventions in a specific context, unless the results are known to be generalizable to that specific context. For example, a meta-analysis of conservation agriculture found beneficial effects in hotter, drier climates, but not in colder, wetter climates. It can be difficult to make generalisations if interventions have different effects in different contexts. Meta-analysis is often used to make generalisations about interventions, such as agricultural practices or medical treatments. 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. Metadataset is a proof-of-concept for this type of software, and it is open source. 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. Future studies should develop standardised classification systems for the metadata that are used to filter and weight the evidence. We suggest that dynamic meta-analysis can be used for subject-wide evidence synthesis in several scientific disciplines, including agroecology and conservation biology. 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. critical appraisal) and how to handle missing or poorly reported data (e.g. 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. With an example from agroecology, we show how dynamic meta-analysis could lead to different conclusions for different subsets of the global evidence. 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. We developed Metadataset ( as a proof-of-concept for dynamic meta-analysis. 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. Meta-analysis is often used to make generalisations across all available evidence at the global scale.
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