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Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research
Annual Review of Public Health ( IF 20.8 ) Pub Date : 2017-04-06 00:00:00 , DOI: 10.1146/annurev-publhealth-031816-044327
Peter Craig 1 , Srinivasa Vittal Katikireddi 1 , Alastair Leyland 1 , Frank Popham 1
Affiliation  

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.

中文翻译:


自然实验:公共卫生干预研究的方法、途径和贡献概述

人口健康干预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) 方法作为在这种情况下提供证据的一种方式引起了越来越多的兴趣。评估 NE 的一个关键挑战是选择性地接触干预措施。研究应基于对确定暴露的过程的清晰理论理解。即使观察到的影响很大并且在实施之后很快,通过仔细考虑替代解释,可以提高将这些影响归因于干预的信心。通过在效果估计的主要方法旁边加入额外的设计特征,可以加强因果推理。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,投资此类数据源以及连接暴露和结果数据的基础设施是必不可少的。

更新日期:2017-04-06
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