Public attention has often been drawn to the relationship between violence and mental health issues, but violent behavior is a very complex phenomenon undergirded by myriad social, psychological, environmental, and biological influences. This project intends to investigate these influences among a large sample of previously incarcerated youth, following up with them and collecting valuable longitudinal data. Our team worked with these youth and their families collecting detailed psychological, behavioral, and neuroimaging measures as part of a previous NIH-funded investigation. The current project aims to re-assess these individuals (now young adults) to examine long-range positive (i.e., desistance from drug use/antisocial behavior) and negative (relapse to drugs, antisocial behavior) outcomes. We will collect new neuroimaging scans, which combined with prior MRI data, will be useful for quantifying trajectories of change that map to persistence and desistence from externalizing outcomes. Advanced machine-learning approaches will be utilized in conjunction with structural, functional, network, and dynamic network brain measures in addition to behavioral and psychological measures. Machine learning approaches are capable of identifying patterns in high-dimensional data and delineating the unique combinations of variables that are most predictive of specific outcome variables. Using these methods, we intend to define neural mechanisms that predict outcomes. We also aim to identify combinations of variables that confer greater risk for persistent antisocial behavior and violence. The translational value of this work will be to clarify informative patterns of data that may indicate preventable outcomes. Furthermore, neural measures indicative of specific vulnerability will be identified as specific targets for treatment and novel intervention strategies. By identifying specific vulnerabilities and the changes that accompany positive outcomes, we will be closer to understanding the best way to recognize and prevent costly violent behavior.

Public Health Relevance

Recent attention has been drawn to the relationship between mental health issues and potentially preventable forms of violence, antisocial behavior, and substance abuse. This project aims to investigate neural, psychological, and life-course variables that may help predict divergent trajectories for persistent antisocial behavior and desistance by applying advanced statistical models in conjunction with longitudinal data from a unique sample of antisocial youth. Identifying variables that predict these outcomes will further help us to develop more efficacious treatment and intervention strategies.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
1R01HD092331-01
Application #
9361299
Study Section
Child Psychopathology and Developmental Disabilities Study Section (CPDD)
Program Officer
Maholmes, Valerie
Project Start
2017-08-05
Project End
2022-05-31
Budget Start
2017-08-05
Budget End
2018-05-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
The Mind Research Network
Department
Type
DUNS #
098640696
City
Albuquerque
State
NM
Country
United States
Zip Code
87106
Miskovich, Tara A; Anderson, Nathaniel E; Harenski, Carla L et al. (2018) Abnormal cortical gyrification in criminal psychopathy. Neuroimage Clin 19:876-882
Maurer, J Michael; Steele, Vaughn R; Fink, Brandi C et al. (2018) Investigating error-related processing in incarcerated adolescents with self-report psychopathy measures. Biol Psychol 132:96-105