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.
