We present a novel framework (TS+TT) to nest a Target Study (TS) within a Target Trial (TT) for evaluating the effects of interventions on disparities. The TS component grounds the measurement of disparity in ethical assumptions, based on the concept of allowability, and anchors it to an explicit population within calendar time. It specifies an enrollment plan of stratified sampling of eligible persons to yield a sample where social groups are distributionally similar on covariates deemed allowable for measuring disparity. Within this enrolled sample, the TT component specifies randomization of intervention strategies within each social group. Because social groups are similarly situated on allowable covariates at baseline, and because assigned intervention arms are exchangeable within social groups, TS+TT reflects a meaningful causal estimand for evaluating how interventions impact disparity. We describe the framework's key components, its emulation, and demonstrate its application to evaluate how hypothetical interventions on pulse oximeter bias affect disparities in treatment receipt in clinical care. We also extend semiparametric G-computation to accommodate continuous stochastic interventions and estimate counterfactual disparities in time-to-event outcomes. The TS+TT framework offers a versatile and policy-relevant approach for generating ethically informed causal evidence to reduce disparities and avoid exacerbating disparities.

翻译：我们提出一个新颖框架（TS+TT），将目标研究嵌套于目标试验中，以评估干预措施对差异的影响。TS部分基于"可允许性"概念，在伦理假设下对差异测量进行界定，并将其锚定于特定日历时间的人群。该部分规定了分层抽样的入选方案，确保样本中不同社会群体在测量差异所允许的协变量上分布相似。在此入选样本内，TT部分规定了每个社会群体内部的干预策略随机化方案。由于社会群体在基线时允许协变量分布相似，且各群体内分配的干预组可交换，TS+TT为评估干预措施如何影响差异提供了有意义的因果估计量。我们描述了该框架的核心要素、模拟方法，并演示了其在评估脉冲血氧仪偏差的假设干预措施如何影响临床护理中治疗接受差异方面的应用。我们还拓展了半参数G计算方法以处理连续随机干预措施，并估计事件发生时间结局的反事实差异。TS+TT框架为生成基于伦理的因果证据、减少差异并避免加剧差异提供了多功能且与政策相关的途径。