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The use of mathematical modeling studies for evidence synthesis and guideline development: A glossary
Author(s) -
Porgo Teegwendé V.,
Norris Susan L.,
Salanti Georgia,
Johnson Leigh F.,
Simpson Julie A.,
Low Nicola,
Egger Matthias,
Althaus Christian L.
Publication year - 2019
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.1333
Subject(s) - terminology , glossary , management science , computer science , guideline , systematic review , data science , medline , medicine , engineering , pathology , philosophy , linguistics , political science , law
Mathematical modeling studies are increasingly recognised as an important tool for evidence synthesis and to inform clinical and public health decision‐making, particularly when data from systematic reviews of primary studies do not adequately answer a research question. However, systematic reviewers and guideline developers may struggle with using the results of modeling studies, because, at least in part, of the lack of a common understanding of concepts and terminology between evidence synthesis experts and mathematical modellers. The use of a common terminology for modeling studies across different clinical and epidemiological research fields that span infectious and non‐communicable diseases will help systematic reviewers and guideline developers with the understanding, characterisation, comparison, and use of mathematical modeling studies. This glossary explains key terms used in mathematical modeling studies that are particularly salient to evidence synthesis and knowledge translation in clinical medicine and public health.