使用干预价值效率的决策分析,在多阶段优化战略中选择优化干预措施
Jillian C Strayhorn1, Charles M Cleland2, David J Vanness3
1Department of Social and Behavioral Sciences, School of Global Public Health, New York University.
概括
干预价值效率决策分析 (DAIVE) 通过平衡有效性和可实施性来帮助优化行为干预. 该框架将干预组件调整为不同的决策者偏好,以获得更好的结果.
科学领域:
- 行为科学 行为科学
- 医疗干预科学 医疗干预科学
- 决策分析 决策分析
背景情况:
- 优化多组件干预是复杂的,需要平衡有效性和可实施性.
- 不同的决策者偏好和多种结果使干预选择变得复杂.
- 多阶段优化策略 (MOST) 的进展使得基于偏好的干预优化成为可能.
研究的目的:
- 介绍干预价值效率的决策分析 (DAIVE),这是MOST的一个新框架.
- 应用DAIVE来选择优化的干预措施,使用从因数试验的经验数据.
- 展示DAIVE如何适应决策者的各种目标和偏好.
主要方法:
- 定义了假设的决策者偏好.
- 应用了DAIVE框架来确定每个偏好集的最佳干预措施.
- 利用了因数优化试验中的数据.
主要成果:
- DAIVE有效地指导了关于优化干预组合的决策.
- 优化干预措施的选择因决策者的偏好和目标而有所不同.
- 描述了个人偏好对干预设计的影响.
结论:
- DAIVE为干预科学家提供了一个结构化的方法来优化干预.
- 提供了应用DAIVE与因数试验数据的实际建议.
- 促进了更为定制和有效的行为干预措施的开发.
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