Trang Nguyen

Causal mediation analysis is complicated with multiple effect definitions that require different sets of assumptions for identification. This article provides a systematic explanation of such assumptions. We define five potential outcome types whose means are involved in various effect definitions. We tackle their mean/distribution’s identification, starting with the one that requires the weakest assumptions and gradually building up to the one that requires the strongest assumptions. This presentation shows clearly why an assumption is required for one estimand and not another, and provides a succinct table from which an applied researcher could pick out the assumptions required for identifying the causal effects they target. Using a running example, the article illustrates the assembling and consideration of identifying assumptions for a range of causal contrasts. For several that are commonly encountered in the literature, this exercise clarifies that identification requires weaker assumptions than those often stated in the literature. This attention to the details also draws attention to the differences in the positivity assumption for different estimands, with practical implications. Clarity on the identifying assumptions of these various estimands will help researchers conduct appropriate mediation analyses and interpret the results with appropriate caution given the plausibility of the assumptions.

Background: This study examined the cyberbullying experience and coping manners of adolescents in urban Vietnam and explored the mediating effect of different support to the associations between cyberbullying and mental health issues.Methods: A cross-sectional study was performed on 484 students at four secondary schools. Cyberbullying experience, coping strategies, psychological problems, and family, peer, and teacher support were obtained. Structural equation modeling was utilized to determine the mediating effects of different support on associations between cyberbullying and psychological problems.Results: There were 11.6 and 28.3% of students who reported that they experienced and observed at least one cyberbullying act in the last 3 months, respectively. Among the victims, only 48.2% tried to stop the perpetrators. Meanwhile, the majority of observers belonged to the “Intervene” group who tried to report cyberbullying acts or help victims. Family support was found to partially mediate associations between cyberbullying experience and observation with levels of psychological problems among adolescents.Conclusion: The 3-month rate of cyberbullying experience and observation among urban adolescents aged 11–14 was low. However, current coping strategies against cyberbullying were not sufficient. Family support is an important factor that should be considered for designing interventions to mitigating the impacts of cyberbullying on the mental health of adolescents.