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因果中介分析:它是什么以及如何用于指导实践和政策?

Causal mediation analysis: what is it and how can it be used to inform practice and policy?

作者信息

Fernainy Pamela, Godard-Sebillotte Claire, Lacasse Anais, Layani Géraldine, Longo Cristina, Kaczorowski Janusz, Rodriguez Maria Alejandra, Poitras Marie-Eve, Breton Mylaine, Lussier Marie-Thérèse, Couturier Yves, Hudon Catherine, Sourial Nadia

机构信息

Department of Health Management Evaluation and Policy, School of Public Health, Université de Montréal, 7101 Park Avenue, Montreal, Quebec H3N 1X9, Canada.

Research Centre of the Centre Hospitalier de l'Université de Montréal (CRCHUM), 900 rue Saint‑Denis, Montreal, Quebec H2X 0A9, Canada.

出版信息

Fam Pract. 2025 Jun 4;42(4). doi: 10.1093/fampra/cmaf043.

Abstract

BACKGROUND

Causal mediation, a quantitative analysis method, has the potential to be a valuable addition to any primary care provider, researcher, or student's toolbox.

OBJECTIVE

This manuscript describes the theory behind causal mediation, provides a running example to help understand the application of this method in research, and explains how the results may be applied practically to help design appropriate interventions.

METHODS AND APPLICATION

Causal mediation allows an exploration of the mechanism of action of a primary care intervention on an outcome that may pass through a third variable that is on the causal pathway, a mediator. Causal mediation analysis allows the decomposition of the total effect of an intervention on an outcome into both direct and indirect effects. Careful interpretation of generated results can guide decision-makers when devising or refining interventions or policies that affect patient health outcomes in primary care.

CONCLUSION

Causal mediation has been used in many disciplines and is well-positioned to answer varied research questions. However, the full extent of its potential has yet to be realized.

摘要

背景

因果中介分析作为一种定量分析方法,有可能成为任何初级保健提供者、研究人员或学生工具包中的一项宝贵补充。

目的

本文阐述了因果中介分析背后的理论,提供了一个实例以帮助理解该方法在研究中的应用,并解释了如何将结果实际应用于帮助设计适当的干预措施。

方法与应用

因果中介分析能够探究初级保健干预措施对可能通过因果路径上的第三个变量(即中介变量)产生的结果的作用机制。因果中介分析可将干预措施对结果的总效应分解为直接效应和间接效应。在制定或完善影响初级保健中患者健康结果的干预措施或政策时,对生成结果的仔细解读可为决策者提供指导。

结论

因果中介分析已在许多学科中得到应用,并且有能力回答各种研究问题。然而,其全部潜力尚未得到充分发挥。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4029/12206152/2b030c1fc7f1/cmaf043_fig1.jpg

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