Abstract

BackgroundThe GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation.CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research (also referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual’s relevance component.MethodsWe developed the relevance component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual relevance component within several qualitative evidence syntheses before agreeing on the current definition and principles for application.ResultsWhen applying CERQual, we define relevance as the extent to which the body of data from the primary studies supporting a review finding is applicable to the context (perspective or population, phenomenon of interest, setting) specified in the review question. In this paper, we describe the relevance component and its rationale and offer guidance on how to assess relevance in the context of a review finding. This guidance outlines the information required to assess relevance, the steps that need to be taken to assess relevance and examples of relevance assessments.ConclusionsThis paper provides guidance for review authors and others on undertaking an assessment of relevance in the context of the CERQual approach. Assessing the relevance component requires consideration of potentially important contextual factors at an early stage in the review process. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase.

Highlights

  • The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group

  • When carrying out a CERQual assessment, we define relevance as the extent to which the body of data from the primary studies supporting a review finding is applicable to the context specified in the review question [1]

  • We have identified three types of threat to relevance—data that are indirectly relevant to the review question, data that are only partially relevant and data that are of unclear relevance: Table 2 Identifying similarities and differences between the context specified in the review question and the context specified in the primary studies contributing to a review finding

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Summary

Introduction

The GRADE-CERQual (Confidence in Evidence from Reviews of Qualitative research) approach has been developed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Working Group. CERQual includes four components for assessing how much confidence to place in findings from reviews of qualitative research ( referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. This paper is part of a series providing guidance on how to apply CERQual and focuses on CERQual’s relevance component. GRADE-CERQual (hereafter referred to as CERQual) includes four components for assessing how much confidence to place in findings from reviews of qualitative research ( referred to as qualitative evidence syntheses): (1) methodological limitations, (2) coherence, (3) adequacy of data and (4) relevance. The relevance component in CERQual is analogous to the indirectness domain used in the GRADE approach for assessing confidence in findings from systematic reviews of effectiveness [2]

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