What's in a Realist Configuration? Deciding Which Causal Configurations to Use, How, and Why
What's in a Realist Configuration? Deciding Which Causal Configurations to Use, How, and Why
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DOI：
10.1177/1609406920938577
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发表时间：
2020-11-30
影响因子：
5.4
通讯作者：
Baan, C. A.
中科院分区：
文献类型：
--
作者：
De Weger, E.;Van Vooren, N. J. E.;Baan, C. A.
背景：现实主义研究代表了一种越来越流行的探索复杂干预措施成功和失败的方法。理论驱动的方法旨在使用情境-机制-结果 (CMO) 配置来解释“什么有效、如何有效、为什么有效、在哪些背景下、对谁有效以及在多大程度上有效”。当该方法首次开发时，CMO 配置是表达因果解释的方法。越来越多的现实主义研究使用启发式的不同变体进行，例如策略-背景-机制-结果（SCMO）配置或干预-背景-参与者-机制-结果（ICAMO）配置。研究人员强调，缺乏关于哪些额外的解释因素可以包含在配置中的方法学指导（例如战略、干预措施、行动者）。本文旨在通过讨论如何将解释因素稳健地添加到 Pawson 和 Tilley 提出的原始 CMO 配置中，来澄清和进一步发展配置的概念。比较不同类型配置的使用：我们借鉴了我们自己的两项研究，一项制定了 CMO 配置，一项制定了 SCMO 配置，以及对现实主义研究的证据扫描。我们探讨了这些不同配置对研究结果的影响，并强调了研究人员选择 CMO 或 SCMO 的原因。最后，我们提供有关配置使用的建议。这些因素如下： 使用额外的解释因素是可能的，但要考虑研究范围以选择适合研究的配置；配置选择透明并包含配置示例；需要进一步研究额外解释因素的使用，以更好地理解现实主义评估周期中每个步骤的影响；需要采用新的方式来传播现实主义研究结果，以平衡配置使用的透明度。结论：根据研究的范围和目标，添加解释因素是可能的，并且可以具有洞察力；然而，任何配置类型都必须遵守生成因果关系的规则。
Background:Realist studies represent an increasingly popular approach for exploring complex interventions' successes and failures. The theory-driven approach seeks to explain "what works, how, why, in which contexts, for whom, and to what extent" using context-mechanism-outcome (CMO) configurations. When the approach was first developed, CMO configurations were the method for expressing causal explanations. Increasingly, realist studies have been conducted using different variations of the heuristic such as strategy-context-mechanism-outcome (SCMO) configurations or intervention-context-actor-mechanism-outcome (ICAMO) configurations. Researchers have highlighted a lack of methodological guidance regarding which additional explanatory factors can be included in configurations (e.g., strategies, interventions, actors). This article aims to clarify and further develop the concept of configurations by discussing how explanatory factors could be robustly added to the original CMO configuration as put forward by Pawson and Tilley.Comparing the use of different types of configurations:We draw on two of our own studies, one which formulated CMO configurations and one which formulated SCMO configurations, and on an evidence scan of realist studies. We explored the effects these different configurations had on studies' findings and highlight why researchers chose CMOs or SCMOs. Finally, we provide recommendations regarding the use of configurations. These are as follows: Using additional explanatory factors is possible but consider the research scope to select the configuration appropriate for the study; Be transparent about the choice in configuration and include examples of configurations; Further studies about the use of additional explanatory factors are needed to better understand the effects on each step in the realist evaluation cycle; and New ways of disseminating realist findings are needed to balance transparency regarding the use of configurations.Conclusions:Adding explanatory factors is possible and can be insightful depending on the study's scope and aims; however, any configuration type must adhere to the rule of generative causation.