4.5 Article

Causal Inference Methods for Intergenerational Research Using Observational Data

Journal

PSYCHOLOGICAL REVIEW
Volume -, Issue -, Pages -

Publisher

AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/rev0000419

Keywords

causal inference; genetically informed methods; intergenerational effects; quasi-experimental studies; within-family designs

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Identifying early causal factors is crucial for developing effective preventive interventions for poor mental health and behavioral outcomes. Parental risk factors, such as maternal stress during pregnancy, parental education, parental psychopathology, and parent-child relationship, are significantly associated with child outcomes, highlighting the importance of parental influence. However, these associations may also be influenced by confounding factors, such as genetic transmission. Observational studies can help infer causality, and this review provides an overview of current causal inference methods in intergenerational settings, including genetically informed and analytical methods. The review discusses their application to child mental health and outlines future research areas for investigating the causal nature of intergenerational effects.
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.

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