Rapid reviews methods series: Guidance on team considerations, study selection, data extraction and risk of bias assessment.
Journal
BMJ evidence-based medicine
ISSN: 2515-4478
Titre abrégé: BMJ Evid Based Med
Pays: England
ID NLM: 101719009
Informations de publication
Date de publication:
22 11 2023
22 11 2023
Historique:
accepted:
21
02
2023
medline:
27
11
2023
pubmed:
20
4
2023
entrez:
19
04
2023
Statut:
epublish
Résumé
This paper is part of a series of methodological guidance from the Cochrane Rapid Reviews Methods Group (RRMG). Rapid reviews (RRs) use modified systematic review (SR) methods to accelerate the review process while maintaining systematic, transparent and reproducible methods to ensure integrity. This paper addresses considerations around the acceleration of study selection, data extraction and risk of bias (RoB) assessment in RRs. If a RR is being undertaken, review teams should consider using one or more of the following methodological shortcuts: screen a proportion (eg, 20%) of records dually at the title/abstract level until sufficient reviewer agreement is achieved, then proceed with single-reviewer screening; use the same approach for full-text screening; conduct single-data extraction only on the most relevant data points and conduct single-RoB assessment on the most important outcomes, with a second person verifying the data extraction and RoB assessment for completeness and correctness. Where available, extract data and RoB assessments from an existing SR that meets the eligibility criteria.
Identifiants
pubmed: 37076266
pii: bmjebm-2022-112185
doi: 10.1136/bmjebm-2022-112185
pmc: PMC10715469
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
418-423Informations de copyright
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
Déclaration de conflit d'intérêts
Competing interests: IS and LP: None declared. BN-S, CH, DD and GG are co-convenors of the RRMG. MT worked 2022 as research associate for the RRMG. AN-S is leading the crowdsourcing project ‘Cochrane Crowd’.
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