Identifying early causal factors leading to the development of poor mental health and behavioral outcomes is essential to design efficient preventive interventions. The substantial associations observed between parental risk factors (e.g., maternal stress in pregnancy, parental education, parental psychopathology, parent-child relationship) and child outcomes point toward the importance of parents in shaping child outcomes. However, such associations may also reflect confounding, including genetic transmission-that is, the child inherits genetic risk common to the parental risk factor and the child outcome. This can generate associations in the absence of a causal effect. As randomized trials and experiments are often not feasible or ethical, observational studies can help to infer causality under specific assumptions. This review aims to provide a comprehensive summary of current causal inference methods using observational data in intergenerational settings. We present the rich causal inference toolbox currently available to researchers, including genetically informed and analytical methods, and discuss their application to child mental health and related outcomes. We outline promising research areas and discuss how existing approaches can be combined or extended to probe the causal nature of intergenerational effects. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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使用观察数据进行代际研究的因果推理方法。


识别导致心理健康和行为结果不良的早期因果因素对于设计有效的预防干预措施至关重要。观察到的父母危险因素（例如，怀孕期间的母亲压力、父母教育、父母精神病理学、亲子关系）与儿童结局之间的实质性关联表明了父母在塑造儿童结局中的重要性。然而，这种关联也可能反映出混杂因素，包括遗传传播，即孩子继承了父母风险因素和孩子结果所共有的遗传风险。这可以在没有因果效应的情况下产生关联。由于随机试验和实验通常不可行或不道德，观察性研究可以帮助推断特定假设下的因果关系。本综述旨在对当前使用代际环境中的观察数据进行因果推理的方法进行全面总结。我们向研究人员展示了目前可用的丰富的因果推理工具箱，包括遗传信息和分析方法，并讨论了它们在儿童心理健康和相关结果中的应用。我们概述了有前景的研究领域，并讨论了如何结合或扩展现有方法来探讨代际效应的因果性质。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。