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现实主义随机对照试验:一种评估复杂公共卫生干预措施的新方法。

Realist randomised controlled trials: a new approach to evaluating complex public health interventions.

机构信息

Centre for Evidence Based Intervention, Department of Social Policy and Intervention, University of Oxford, 32 Wellington Square, Oxford OX1 2ER, UK.

出版信息

Soc Sci Med. 2012 Dec;75(12):2299-306. doi: 10.1016/j.socscimed.2012.08.032. Epub 2012 Sep 7.

Abstract

Randomized trials of complex public health interventions generally aim to identify what works, accrediting specific intervention 'products' as effective. This approach often fails to give sufficient consideration to how intervention components interact with each other and with local context. 'Realists' argue that trials misunderstand the scientific method, offer only a 'successionist' approach to causation, which brackets out the complexity of social causation, and fail to ask which interventions work, for whom and under what circumstances. We counter-argue that trials are useful in evaluating social interventions because randomized control groups actually take proper account of rather than bracket out the complexity of social causation. Nonetheless, realists are right to stress understanding of 'what works, for whom and under what circumstances' and to argue for the importance of theorizing and empirically examining underlying mechanisms. We propose that these aims can be (and sometimes already are) examined within randomized trials. Such 'realist' trials should aim to: examine the effects of intervention components separately and in combination, for example using multi-arm studies and factorial trials; explore mechanisms of change, for example analysing how pathway variables mediate intervention effects; use multiple trials across contexts to test how intervention effects vary with context; draw on complementary qualitative and quantitative data; and be oriented towards building and validating 'mid-level' program theories which would set out how interventions interact with context to produce outcomes. This last suggestion resonates with recent suggestions that, in delivering truly 'complex' interventions, fidelity is important not so much in terms of precise activities but, rather, key intervention 'processes' and 'functions'. Realist trials would additionally determine the validity of program theory rather than only examining 'what works' to better inform policy and practice in the long-term.

摘要

随机对照试验通常旨在确定哪些干预措施有效,从而认可特定干预“产品”的有效性。然而,这种方法往往没有充分考虑干预措施的组成部分之间以及与当地环境之间的相互作用。“现实主义者”认为,试验误解了科学方法,只提供了一种“继起主义”的因果关系方法,这种方法将社会因果关系的复杂性排除在外,并且未能询问哪些干预措施在什么情况下对谁有效。我们反驳说,试验在评估社会干预措施方面是有用的,因为随机对照试验实际上确实考虑到了社会因果关系的复杂性,而不是将其排除在外。尽管如此,现实主义者正确地强调了理解“哪些干预措施在什么情况下对谁有效”的重要性,并主张理论化和实证检验潜在机制的重要性。我们提出,这些目标可以(并且有时已经)在随机试验中进行检验。这种“现实主义”试验应旨在:分别和组合地检验干预措施组成部分的效果,例如使用多臂研究和析因试验;探索变化机制,例如分析途径变量如何介导干预效果;在不同的环境中使用多个试验来测试干预效果如何随环境而变化;借鉴补充的定性和定量数据;并致力于构建和验证“中层”项目理论,该理论将阐述干预措施如何与环境相互作用以产生结果。最后一个建议与最近的建议相呼应,即在提供真正“复杂”的干预措施时,保真度重要的不是精确的活动,而是关键的干预“过程”和“功能”。现实主义试验还将确定项目理论的有效性,而不仅仅是检查“哪些有效”,以便从长期来看更好地为政策和实践提供信息。

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