Norwegian Institute of Public Health, Oslo, Norway.
Uni Research Rokkan Centre, Bergen, Norway.
Implement Sci. 2018 Jan 25;13(Suppl 1):14. doi: 10.1186/s13012-017-0692-7.
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. 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 adequacy of data component.
We developed the adequacy of data component by searching the literature for definitions, gathering feedback from relevant research communities and developing consensus through project group meetings. We tested the CERQual adequacy of data component within several qualitative evidence syntheses before agreeing on the current definition and principles for application.
When applying CERQual, we define adequacy of data as an overall determination of the degree of richness and the quantity of data supporting a review finding. In this paper, we describe the adequacy component and its rationale and offer guidance on how to assess data adequacy in the context of a review finding as part of the CERQual approach. This guidance outlines the information required to assess data adequacy, the steps that need to be taken to assess data adequacy, and examples of adequacy assessments.
This paper provides guidance for review authors and others on undertaking an assessment of adequacy in the context of the CERQual approach. We approach assessments of data adequacy in terms of the richness and quantity of the data supporting each review finding, but do not offer fixed rules regarding what constitutes sufficiently rich data or an adequate quantity of data. Instead, we recommend that this assessment is made in relation to the nature of the finding. We expect the CERQual approach, and its individual components, to develop further as our experiences with the practical implementation of the approach increase.
GRADE-CERQual（对定性研究证据综述的信心）方法由 GRADE（推荐评估、制定和评估分级）工作组开发。该方法旨在支持在决策中使用定性证据综合的结果，包括指南制定和政策制定。CERQual 包括四个评估从定性研究综述中得出的研究结果的置信度的组成部分（也称为定性证据综合）：（1）方法学局限性；（2）一致性；（3）数据充分性；（4）相关性。本文是一系列关于如何应用 CERQual 的指南的一部分，重点介绍 CERQual 的数据充分性组成部分。
我们通过搜索文献中的定义、从相关研究社区收集反馈以及通过项目组会议达成共识来开发数据充分性组成部分。在同意当前的定义和应用原则之前，我们在几个定性证据综合中测试了 CERQual 的数据充分性组成部分。
在应用 CERQual 时，我们将数据充分性定义为对支持综述结果的丰富程度和数据数量的总体判断。在本文中，我们描述了充分性组成部分及其原理，并提供了在综述结果的背景下评估数据充分性的指南，作为 CERQual 方法的一部分。本指南概述了评估数据充分性所需的信息、评估数据充分性所需采取的步骤以及充分性评估的示例。
本文为综述作者和其他人员提供了在 CERQual 方法背景下进行充分性评估的指南。我们根据支持每个综述结果的丰富程度和数量来评估数据充分性，但不提供关于什么构成足够丰富的数据或足够数量的数据的固定规则。相反，我们建议根据研究结果的性质进行这种评估。我们预计 CERQual 方法及其各个组成部分将随着我们对该方法实际实施经验的增加而进一步发展。
