JBI, Faculty of Health and Medical Sciences, University of Adelaide, 55 Norwich House, King William Road, Adelaide, Australia.
JBI, Faculty of Health and Medical Sciences, University of Adelaide, 55 Norwich House, King William Road, Adelaide, Australia.
J Clin Epidemiol. 2022 Aug;148:178-183. doi: 10.1016/j.jclinepi.2022.03.014. Epub 2022 Mar 24.
Mixed methods systematic reviews (MMSRs) combine quantitative and qualitative evidence within a single review. Since the revision of the JBI methodology for MMSRs in 2020, there has been an increasing number of reviews published that claim to follow this approach. A preliminary examination of these indicated that authors frequently deviated from the methodology. This article outlines five common 'pitfalls' associated with undertaking MMSR and provides direction for future reviewers attempting MMSR.
Forward citation tracking identified 17 reviews published since the revision of the JBI mixed methods methodological guidance. Methods used in these reviews were then examined against the JBI methodology to identify deviations.
The issues identified related to the rationale for choosing the methodological approach, an incorrect synthesis and integration approach chosen to answer the review question/s posed, the exclusion of primary mixed methods studies in the review, the lack of detail regarding the process of data transformation, and a lack of 'mixing' of the quantitative and qualitative components.
This exercise was undertaken to assist systematic reviewers considering conducting an MMSR and MMSR users to identify potential areas where authors tend to deviate from the methodological approach. Based on these findings a series of recommendations are provided.
混合方法系统评价(MMSR)在单个评价中结合了定量和定性证据。自 2020 年 JBI 对 MMSR 的方法进行修订以来,发表的此类评价数量不断增加,声称遵循这种方法。对这些评价的初步检查表明,作者经常偏离方法。本文概述了进行 MMSR 时常见的五个“陷阱”,并为尝试 MMSR 的未来评审员提供了指导。
正向引文追踪确定了自 JBI 混合方法方法指南修订以来发表的 17 篇评论。然后,根据 JBI 方法检查这些评论中使用的方法,以确定偏差。
确定的问题与选择方法的理由有关,选择的综合和整合方法不正确,无法回答提出的审查问题/,在审查中排除了主要的混合方法研究,缺乏有关数据转换过程的详细信息,以及缺乏定量和定性组件的“混合”。
进行此练习是为了协助考虑进行 MMSR 的系统审查员和 MMSR 用户识别作者倾向于偏离方法的潜在领域。基于这些发现,提出了一系列建议。