Operationalizing Primary Outcomes to Achieve Reach, Effectiveness, and Equity in Multilevel Interventions.
Operationalizing Primary Outcomes to Achieve Reach, Effectiveness, and Equity in Multilevel Interventions.
复制标题
落实主要成果，以实现多层次干预措施的覆盖面、有效性和公平性。
DOI：
10.1007/s11121-023-01613-2
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Feinberg,Emily
中科院分区：
文献类型：
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作者：
Guastaferro,Kate;Sheldrick,RChristopher;Strayhorn,JillianC;Feinberg,Emily
当干预科学家计划一项干预的临床试验时，他们选择一个结果指标，以实现他们对干预成功的定义。所选择的结果指标对最终支持大规模实施的干预措施以及人口中体验到的健康益处（包括多少益处和对谁）具有重要影响。特别是当一项干预措施将在经历健康差距的人群中实施时，所选择的结果指标也可能对公平产生影响。一些结果指标可能会加剧现有的健康差距，而其他指标可能会减少一些人的差距，但对更大的人群影响较小。在这项研究中，我们使用计算机来模拟实施一个假设的多层次，多成分的干预措施，以突出的权衡，可以发生在结果指标，反映不同的操作干预成功。特别是，我们强调整体平均人口福利和健康福利在人口中的分配之间的权衡，这对公平有直接的影响。我们建议，像我们目前的一个模拟可以是有用的，在规划的临床试验的多层次和/或多组分干预，因为模拟实施规模可以说明潜在的后果，候选人操作干预的成功，这样的意外后果的公平可以避免。
When intervention scientists plan a clinical trial of an intervention, they select an outcome metric that operationalizes their definition of intervention success. The outcome metric that is selected has important implications for which interventions are eventually supported for implementation at scale and, therefore, what health benefits (including how much benefit and for whom) are experienced in a population. Particularly when an intervention is to be implemented in a population that experiences a health disparity, the outcome metric that is selected can also have implications for equity. Some outcome metrics risk exacerbating an existing health disparity, while others may decrease disparities for some but have less effect for the larger population. In this study, we use a computer to simulate implementation of a hypothetical multilevel, multicomponent intervention to highlight the tradeoffs that can occur between outcome metrics that reflect different operationalizations of intervention success. In particular, we highlight tradeoffs between overall mean population benefit and the distribution of health benefits in the population, which has direct implications for equity. We suggest that simulations like the one we present can be useful in the planning of a clinical trial for a multilevel and/or multicomponent intervention, since simulated implementation at scale can illustrate potential consequences of candidate operationalization of intervention success, such that unintended consequences for equity can be avoided.