Proximal Inference on Population Intervention Indirect Effect

Additionally, experiments have shown that depersonalization symptoms can arise as a reaction to alcohol consumption (Raimo et al., 1999), and they are increasingly recognized as a significant prognostic factor in the course of depression (Michal et al., 2024). Despite these findings, little research has explored the mediating role of depersonalization symptoms in the causal pathway from alcohol consumption to depression. In this paper, we propose a methodological framework to evaluate the indirect effect of alcohol consumption on depression, with depersonalization acting as a mediator. To ground our analysis, we use data from a cross-sectional survey conducted during the COVID-19 pandemic by Dom ınguez-Espinosa et al. (2023) as a running example. In observational studies, the population average causal effect (ACE) and the natural indirect effect (NIE) are the most commonly used measures of total and mediation effects, respectively, to compare the outcomes of different intervention policies. For instance, in our running example, these two measures compare the depression outcomes between individuals engaging in hazardous versus non-hazardous alcohol consumption. However, clinical practice imposes ethical constraints, as healthcare professionals would not prescribe harmful levels of alcohol consumption. As a result, hypothetical interventions involving dangerous exposure levels are unrealistic. To address this situation with potentially harmful exposure, Hubbard and Van der Laan (2008) propose the population intervention effect (PIE), which contrasts outcomes between the natural population and a hypothetical population where no one is exposed to the harmful exposure level.