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Evaluating limitations in the design, execution or reporting of studies when rating the certainty of evidence using GRADE

Event date
- (12:00 - 1:30pm) Check in your time zone
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Cochrane Learning Live

Study limitations and dissemination bias are two of the eight GRADE domains, and two of the five domains that can lead to rating down of the certainty of the evidence. Evaluating study limitations involves considering whether flaws in the design or conduct of studies in a meta-analysis could bias the effect estimate. Evaluating dissemination bias involves considering whether there are results missing from a meta-analysis that could bias the effect estimate because of the nature of the missing results. 

Session 4 of the GRADE Learning Live series covers how to rate study limitations and dissemination bias in systematic reviews of interventions. 

Topics include:

  • What are study limitations? What is dissemination bias?
  • How do these domains relate to assessments of risk of bias in Cochrane reviews? ROB2 and ROB-ME assessments.
  • How to evaluate study limitations and dissemination bias in reviews of interventions
  • Impact of study limitations and dissemination bias on the certainty of evidence 
  • Overlap with other GRADE domains

This webinar is suitable for those wanting to use GRADE to interpret and summarise findings in a systematic review. An understanding of systematic review methods and content covered in the introductory session is assumed. 
 


Presenter Bios

Ignacio Neumann is a physician and guideline methodologist with extensive experience in evidence synthesis and the development of clinical practice guidelines. He is an active member of the GRADE Working Group, where he contributes to methodological advances in assessing certainty of evidence, defining decision thresholds, and strengthening the integration of evidence into recommendations. He is also actively involved in the development of digital and AI-enabled tools designed to support structured evidence translation. His work focuses on preserving methodological rigor while enhancing accessibility, transparency, and the scalability of evidence-based recommendations across clinical and public health settings.

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