Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research.
Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research.
复制标题
自然实验：对公共卫生干预研究的方法，方法和贡献的概述。
DOI：
10.1146/annurev-publhealth-031816-044327
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发表时间：
2017-03-20
影响因子：
20.8
通讯作者：
Popham F
中科院分区：
文献类型：
--
作者：
Craig P;Katikireddi SV;Leyland A;Popham F
人口健康干预措施对于减少健康不平等和解决其他公共卫生优先事项至关重要，但它们并不总是适合实验操作。自然实验（NE）的方法正在吸引越来越多的兴趣，在这种情况下提供证据的方式。评估内斯的一个关键挑战是选择性暴露于干预措施。研究应基于对决定接触的过程的明确的理论理解。即使观察到的效果很大，而且在实施后很快就出现了，也可以通过仔细考虑其他解释来提高将这些效果归因于干预措施的信心。除了主要的效应估计方法外，还可以通过增加额外的设计特征来加强因果推断。NE研究通常依赖于现有的（包括常规收集的）数据。如果要实现此类研究为决策提供信息的潜力，就必须投资于此类数据来源和将接触和结果数据联系起来的基础设施。
Population health interventions are essential to reduce health inequalities and tackle other public health priorities, but they are not always amenable to experimental manipulation. Natural experiment (NE) approaches are attracting growing interest as a way of providing evidence in such circumstances. One key challenge in evaluating NEs is selective exposure to the intervention. Studies should be based on a clear theoretical understanding of the processes that determine exposure. Even if the observed effects are large and rapidly follow implementation, confidence in attributing these effects to the intervention can be improved by carefully considering alternative explanations. Causal inference can be strengthened by including additional design features alongside the principal method of effect estimation. NE studies often rely on existing (including routinely collected) data. Investment in such data sources and the infrastructure for linking exposure and outcome data is essential if the potential for such studies to inform decision making is to be realized.
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影响因子：
2.9
作者：
Dundas R;Ouédraogo S;Bond L;Briggs AH;Chalmers J;Gray R;Wood R;Leyland AH
通讯作者：
Leyland AH
影响因子：
4.2
作者：
Abadie, Alberto;Diamond, Alexis;Hainmueller, Jens
通讯作者：
Hainmueller, Jens
影响因子：
12.6
作者：
Deaton, Angus
通讯作者：
Deaton, Angus
影响因子：
5
作者：
Basu, Sanjay;Rehkopf, David H.;Kawachi, Ichiro
通讯作者：
Kawachi, Ichiro
影响因子：
12.7
作者：
Fuller, Thomas;Peters, Jaime;Anderson, Rob
通讯作者：
Anderson, Rob