Controlling Contamination Bias in Child Maltreatment Research

Contamination occurs in many different experimental designs outside the field of child maltreatment. In this project, contamination refers to the presence of child maltreatment in already established, non-child maltreatment comparison conditions. Research has shown that failure to detect and control contamination biases effect size estimates for child maltreatment outcomes and leads to variation in the significance and magnitude of those estimates within and across studies, increasing the chances of discovery and replication failures. The Detecting and Controlling Contamination Bias

Project (Shenk, PI; Shores, Ram, & Fisher Co-I’s) is supported by awards from the National Institutes of Health (R03HD104739) and the National Science Foundation (BCS-2041333) examining contamination in prospective cohort studies of child maltreatment. The current project is using existing data from two large, multi-wave, prospective cohort studies of confirmed child maltreatment, the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN; N=1354) and the National Survey of Child and Adolescent Well-being-II (NSCAW-II; N=5872), to accomplish two specific aims: 1) estimate the prevalence of contamination, defined as any self- or caregiver-reported instance of child maltreatment by members of the established comparison condition, and 2) test different statistical approaches for reducing bias in risk estimates for child behavior problems attributable to contamination. Finally, this project will conduct extensive data simulations based on these results to extend inferences across different research conditions, including variations in sample size, contamination prevalence, statistical power, and effect size magnitude. The end product of this project will be to disseminate to the larger scientific field the optimal methods for detecting and controlling contamination bias across a range of research conditions in order to minimize variation in the significance and magnitude of effect size estimates reported across prospective studies.

T32 Fellows will have the opportunity to generate, execute, and report results from statistical models aiming to establish the optimal detection and control of contamination. Statistical models where Fellows can receive training include, multi-level modeling, propensity score matching, and synthetic controls.

Caregiver-Child Communication (C3) to Promote Resilience following Child-Maltreatment

The C3 Project is supported by an NIH P50 Center Grant (P50HD089922; Noll, PI) that is conducting a multi-wave, prospective cohort study, the Child Health Study (CHS; Shenk, Co-I), examining the impact of child maltreatment on multiple biological systems and subsequent pediatric health. One of Shenk Lab's contributions to the CHS is the use of observational methods to quantify caregiver-child dyadic communication and establish how specific patterns of communication are involved in promoting resilience to adverse health following exposure to child maltreatment.

Caregivers and their children participating in the CHS (N=600 and counting!) complete three separate interaction tasks designed to promote relationship quality and dyadic problem-solving. Caregiver-child communication is then sampled using a multilevel, intensive longitudinal design, where specific processes are quantified in 30-second epochs to estimate dynamic change within and across tasks. Furthermore, families in the CHS complete waves of data collection every two years with the same three interaction tasks administered at each wave, allowing for inferences about how specific caregiver-child communication patterns change from childhood to adulthood and in response to child maltreatment.

Following a deep phenotyping and multiple levels of analysis approach, data obtained from these observational methods will ultimately be included with biological, behavioral, and other environmental mechanisms of adverse health being measured in the CHS, such as structural and functional MRI, genome-wide DNA methylation, immune function, cognitive development, psychiatric function, and more. The data generated from the C3 project will inform models of how the experience of pediatric trauma “gets under the skin” and whether parent-child communication can facilitate reductions in risk for adverse health.

T32 Fellows will have the opportunity to learn and apply two different observational coding paradigms for quantifying caregiver behaviors and child affect (positive and negative). Research and statistical methods where Fellows can receive training include: observational methods, measuring inter-rater reliability, multi-level modeling, and dynamic systems modeling.

Epigenetic and Cognitive Aging Project (ECAP)

eCAP (Shenk, PI; O’Donnell, Sliwinski, Ram, and Noll, Co-I’s) is supported by an NIH award (R01AG059682) examining the impact of child maltreatment on epigenetic age acceleration, a cross-tissue index of the biological aging of cells that is derived from DNA methylation across the genome and has added explanatory power of adulthood health beyond chronological age. This project will first examine epigenetic age acceleration and its relation to mid-life cognitive function in the Female Growth and Development Study (FGDS), a 30-year prospective cohort study of the long-term effects of childhood sexual abuse. The FGDS cohort also provides an unprecedented opportunity to test the mediational properties of glucocorticoid remodeling occurring over the 20 years following exposure to substantiated child sexual abuse on epigenetic age acceleration as well as the risks associated with epigenetic age acceleration and a comprehensive assessment of cognitive function at mid-life. Once statistical models of epigenetic age acceleration and cognitive outcomes are developed using data from the FGDS discovery cohort, they will be exported for replication in independent, international cohorts to extend models to more diverse samples, including older ages and alternative cognitive outcomes (e.g. mild cognitive impairment). Results will inform precision-based efforts at preventing, delaying, or reversing the onset of various cognitive aging outcomes across different points of the lifespan.

CMT32 Fellows have the opportunity to examine a variety of epigenetic age acceleration estimates and their relation to a host of developmental and cognitive function outcomes with the existing data collected in this project

The Life Events and Reactions Study (LEARS)

LEARS is a genetic case-control association study (Shenk, PI: KL2TR000078) examining the genetic and epigenetic mechanisms associated with the onset of psychiatric disorders in the child maltreatment population. Children between the ages of 8 and 15 years of age who have experienced substantiated child maltreatment participated in this study. Biospecimens (oral fluid, buccal swab) collected in this study are being used to generate estimates of variation in DNA and DNA methylation to predict the course and severity of psychiatric symptoms and diagnoses obtained from a structured psychiatric interview. Results from this study will provide insight into the genetic, epigenetic, and psychological contributions for these disorders in the child maltreatment population so that interventions targeting these processes can be developed or applied more effectively.

CMT32 Fellows would have the opportunity to examine a variety of epigenetic age acceleration estimates and their relation to a host of psychiatric disorders and symptom severity with the existing data collected in this project.