在评价复杂卫生干预措施中使用中介分析

IF 1 4区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Deborah D. DiLiberto, C. Opondo, S. Staedke, Clare I. R. Chandler, E. Allen
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引用次数: 0

摘要

本文介绍了因果推理方法在调解分析中的应用,使用旨在提高乌干达保健中心护理质量的复杂干预措施的例子。中介分析是一种统计方法,旨在隔离使干预在给定上下文中起作用的因果机制。我们结合了来自集群随机对照试验和混合方法过程评估的数据。根据我们的假设,我们开发了两个因果模型,假设干预是如何通过卫生中心的机制来改善社区的健康结果的。在调整后的分析中,有证据表明干预对某些保健中心机制产生了影响;然而,这些并没有导致社区健康结果的改善。我们讨论在使用中介分析评估复杂干预时遇到的实践和认识论挑战。这些发现将为今后的评价提供信息。试验注册:本文报道的试验注册在:clinicaltrials.gov, NCT01024426。2009年12月2日注册,https://clinicaltrials.gov/ct2/show/record/NCT01024426?term=NCT01024426&draw=2&rank=1
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The use of mediation analysis in evaluation of complex health interventions
This article presents an application of the causal inference approach to mediation analysis using the example of a complex intervention that aimed to improve the quality of care at health centres in Uganda. Mediation analysis is a statistical method that aims to isolate the causal mechanisms that make an intervention work in a given context. We combined data from a cluster randomized control trial and a mixed-methods process evaluation. We developed two causal models following our hypotheses of how the intervention was intended to work through mechanisms at health centres to improve health outcomes in the community. In adjusted analyses, there was evidence of an effect of the intervention on some health centre mechanisms; however, these did not lead to improvements in community health outcomes. We discuss the practical and epistemological challenges encountered when using mediation analysis to evaluate a complex intervention. These findings will inform future evaluations. Trial registration: The trial reported in this article is registered at: clinicaltrials.gov, NCT01024426. Registered 2 December 2009, https://clinicaltrials.gov/ct2/show/record/NCT01024426?term=NCT01024426&draw=2&rank=1
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来源期刊
Performance Evaluation
Performance Evaluation 工程技术-计算机:理论方法
CiteScore
3.10
自引率
0.00%
发文量
20
审稿时长
24 days
期刊介绍: Performance Evaluation functions as a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims to present a balanced and complete view of the entire Performance Evaluation profession. Hence, the journal is interested in papers that focus on one or more of the following dimensions: -Define new performance evaluation tools, including measurement and monitoring tools as well as modeling and analytic techniques -Provide new insights into the performance of computing and communication systems -Introduce new application areas where performance evaluation tools can play an important role and creative new uses for performance evaluation tools. More specifically, common application areas of interest include the performance of: -Resource allocation and control methods and algorithms (e.g. routing and flow control in networks, bandwidth allocation, processor scheduling, memory management) -System architecture, design and implementation -Cognitive radio -VANETs -Social networks and media -Energy efficient ICT -Energy harvesting -Data centers -Data centric networks -System reliability -System tuning and capacity planning -Wireless and sensor networks -Autonomic and self-organizing systems -Embedded systems -Network science
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