Marginal Structural Models for Estimating the Longitudinal Effects of Community Violence Exposure on Youths' Internalizing and Externalizing Symptoms

Objective: Longitudinal observational data pose a challenge for causal inference when the exposure of interest varies over time alongside time-dependent confounders, which often occurs in trauma research. We describe marginal structural models (MSMs) using inverse probability weighting as a useful solution under several assumptions that are well-suited to estimating causal effects in trauma research. Method: We illustrate the application of MSMs by estimating the joint effects of community violence exposure across time on youths' internalizing and externalizing symptoms. Our sample included 4,327 youth (50% female, 50% male; 1.4% Asian American or Pacific Islander, 34.7% Black, 46.9% Hispanic, .8% Native American, 14.3%, White, 1.5%, Other race/ethnicity; M-age at baseline = 8.62, range = 3-15) from the Project on Human Development in Chicago Neighborhoods. Results: Wave 3 internalizing symptoms increased linearly with increases in Wave 2 and Wave 3 community violence exposure, whereas effects on externalizing symptoms were quadratic for Wave 2 community violence exposure and linear for Wave 3. These results fail to provide support for the desensitization model of community violence exposure. Conclusion: MSMs are a useful tool for researchers who rely on longitudinal observational data to estimate causal effects of time-varying exposures, as is often the case in the study of psychological trauma.