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Using qualitative comparative analysis (QCA) in systematic reviews of complex interventions: a worked example

机译:在复杂干预的系统评价中使用定性比较分析(QCA):一个可行的例子

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Background Systematic reviews that address policy and practice questions in relation to complex interventions frequently need not only to assess the efficacy of a given intervention but to identify which intervention - and which intervention components - might be most effective in particular situations. Here, intervention replication is rare, and commonly used synthesis methods are less useful when the focus of analysis is the identification of those components of an intervention that are critical to its success. Methods Having identified initial theories of change in a previous analysis, we explore the potential of qualitative comparative analysis (QCA) to assist with complex syntheses through a worked example. Developed originally in the area of political science and historical sociology, a QCA aims to identify those configurations of participant, intervention and contextual characteristics that may be associated with a given outcome. Analysing studies in these terms facilitates the identification of necessary and sufficient conditions for the outcome to be obtained. Since QCA is predicated on the assumption that multiple pathways might lead to the same outcome and does not assume a linear additive model in terms of changes to a particular condition (that is, it can cope with ‘tipping points’ in complex interventions), it appears not to suffer from some of the limitations of the statistical methods often used in meta-analysis. Results The worked example shows how the QCA reveals that our initial theories of change were unable to distinguish between ‘effective’ and ‘highly effective’ interventions. Through the iterative QCA process, other intervention characteristics are identified that better explain the observed results. Conclusions QCA is a promising alternative (or adjunct), particularly to the standard fall-back of a ‘narrative synthesis’ when a quantitative synthesis is impossible, and should be considered when reviews are broad and heterogeneity is significant. There are very few examples of its use with systematic review data at present, and further methodological work is needed to establish optimal conditions for its use and to document process, practice, and reporting standards.
机译:背景技术针对与复杂干预措施有关的政策和实践问题的系统评价通常不仅需要评估给定干预措施的有效性,还需要确定在特定情况下哪种干预措施和哪些干预措施组件可能最有效。在这里,干预复制很少见,而当分析的重点是确定对其成功至关重要的那些组件时,常用的合成方法就没有多大用处了。方法在先前的分析中确定了最初的变化理论之后,我们通过一个工作实例探索了定性比较分析(QCA)协助复杂综合的潜力。 QCA最初是在政治科学和历史社会学领域开发的,旨在识别可能与给定结果相关的参与者配置,干预和背景特征。用这些术语对研究进行分析有助于确定获得结果的必要条件和充分条件。由于QCA的假设是多种途径可能导致相同的结果,并且没有根据特定条件的变化而采用线性加性模型(也就是说,它可以应对复杂干预措施中的“临界点”),因此似乎没有受到荟萃分析中常用的统计方法的某些限制。结果该工作示例显示了QCA如何揭示我们最初的变革理论无法区分“有效”干预和“高度有效”干预。通过迭代的QCA流程,可以确定其他干预特征,从而更好地解释观察到的结果。结论QCA是一种有前途的替代方案(或辅助方案),尤其是在无法进行定量合成的情况下,可以替代“叙述性合成”的标准后备标准;当评论广泛且异质性很强时,应考虑使用QCA。目前,很少有将其与系统评价数据一起使用的例子,需要进一步的方法学工作来确定其使用的最佳条件,并记录过程,实践和报告标准。

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