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BackgroundWhen unaddressed, contamination in child maltreatment research, in which some proportion of children recruited for a nonmaltreated comparison group are exposed to maltreatment, downwardly biases the significance and magnitude of effect size estimates. This study extends previous contamination research by investigating how a dual‐measurement strategy of detecting and controlling contamination impacts causal effect size estimates of child behavior problems. MethodsThis study included 634 children from the LONGSCAN study with 63 cases of confirmed child maltreatment after age 8 and 571 cases without confirmed child maltreatment. Confirmed child maltreatment and internalizing and externalizing behaviors were recorded every 2 years between ages 4 and 16. Contamination in the nonmaltreated comparison group was identified and controlled by either a prospective self‐report assessment at ages 12, 14, and 16 or by a one‐time retrospective self‐report assessment at age 18. Synthetic control methods were used to establish causal effects and quantify the impact of contamination when it was not controlled, when it was controlled for by prospective self‐reports, and when it was controlled for by retrospective self‐reports. ResultsRates of contamination ranged from 62% to 67%. Without controlling for contamination, causal effect size estimates for internalizing behaviors were not statistically significant. Causal effects only became statistically significant after controlling contamination identified from either prospective or retrospective reports and effect sizes increased by between 17% and 54%. Controlling contamination had a smaller impact on effect size increases for externalizing behaviors but did produce a statistically significant overall effect, relative to the model ignoring contamination, when prospective methods were used. ConclusionsThe presence of contamination in a nonmaltreated comparison group can underestimate the magnitude and statistical significance of causal effect size estimates, especially when investigating internalizing behavior problems. Addressing contamination can facilitate the replication of results across studies. 

Contamination occurs in observational research on child maltreatment when individuals assigned to a comparison condition have, unbeknownst to investigators, been exposed to maltreatment. Contamination is a major threat because it biases the statistical significance and magnitude of maltreatment effects, leading to replication failures and an underestimation of the public health impacts of child maltreatment. Despite its presence, there are no established solutions for addressing contamination in child maltreatment research. This symposium brings together leading experts who will present cutting-edge research addressing a range of critical topics for detecting and correcting contamination in observational research on child maltreatment: 1) a conceptual foundation for what contamination is and how it occurs, 2) the prevalence of contamination across independent and international research, 3) the impact contamination has on the direction, statistical significance, and magnitude of maltreatment effects for a range of public health outcomes in nationally-representative and multi-wave designs, and 4) innovative methodological solutions for detecting and correcting contamination. This symposium will provide needed information for child maltreatment researchers to correct contamination in observational research and improve the accuracy, and therefore replicability, of casual effects across public health outcomes. A formal discussion and integration of results presented in this symposium will also aid trauma researchers at large, as contamination can occur in any observational research design. 

Contamination is a methodological phenomenon occurring in child maltreatment research when individuals in an established comparison condition have, in reality, been exposed to maltreatment during childhood. The current paper: (1) provides a conceptual and methodological introduction to contamination in child maltreatment research, (2) reviews the empirical literature demonstrating that the presence of contamination biases causal estimates in both prospective and retrospective cohort studies of child maltreatment effects, (3) outlines a dual measurement strategy for how child maltreatment researchers can address contamination, and (4) describes modern statistical methods for generating causal estimates in child maltreatment research after contamination is controlled. Our goal is to introduce the issue of contamination to researchers examining the effects of child maltreatment in an effort to improve the precision and replication of causal estimates that ultimately inform scientific and clinical decision-making as well as public policy.