Gun violence is a major source of injury and death in the United States. However, relatively little is known about the effects of firearm injuries on survivors and their family members and how these effects vary across subpopulations. To study these questions and, more generally, to address a gap in the causal inference literature, we present a framework for the study of effect modification or heterogeneous treatment effects in difference-in-differences designs. We implement a new matching technique, which combines profile matching and risk set matching, to (i) preserve the time alignment of covariates, exposure, and outcomes, avoiding pitfalls of other common approaches for difference-in-differences, and (ii) explicitly control biases due to imbalances in observed covariates in subgroups discovered from the data. Our case study shows significant and persistent effects of nonfatal firearm injuries on several health outcomes for those injured and on the mental health of their family members. Sensitivity analyses reveal that these results are moderately robust to unmeasured confounding bias. Finally, while the effects for those injured vary largely by the severity of the injury and its documented intent, for families, effects are strongest for those whose relative's injury is documented as resulting from an assault, self-harm, or law enforcement intervention.

翻译：枪支暴力是美国伤害和死亡的主要原因之一。然而，关于火器伤害对幸存者及其家庭成员的影响，以及这些影响在不同亚群间的差异，目前所知甚少。为研究这些问题，并更广泛地填补因果推断文献的空白，我们提出一个在双重差分设计中研究效果修饰或异质性处理效应的框架。我们实施了一种结合剖面匹配与风险集匹配的新匹配技术，旨在：(i) 保持协变量、暴露和结局的时间对齐，避免其他常见双重差分方法的缺陷；(ii) 明确控制因数据中发现的亚组内可观测协变量不平衡所致的偏倚。我们的案例研究表明，非致命火器伤害对受伤者的多项健康结局及其家庭成员的心理健康具有显著且持久的影响。敏感性分析显示，这些结果对未测量混杂偏倚具有中等程度的稳健性。最后，虽然受伤者的效应在很大程度上因伤害严重程度和有记录意图而异，但对家庭而言，当亲属的伤害被记录为源于攻击、自残或执法干预时，其效应最为强烈。