A longitudinal study of traumatic brain injury in a high-risk population

Contact PD/PI: KIEHL, KENT A Project Summary/Abstract

Traumatic brain injury (TBI) is a global public health concern affecting millions of individuals in the United States [1], with

more than 13 million reporting extended symptoms and disability following a TBI [2]. The costs of acute healthcare related

to TBI exceed $10 billion and over $75 billion when including extended indirect costs and loss of productivity [3]. TBI is

disproportionately represented among incarcerated samples, with incidence rates approximately ten times higher than in the

general population [4, 5]. TBI also presents as a criminogenic risk factor with sequelae that include emotional liabilities, disinhibition, and substance abuse [6-11]. Our team has conducted neuroscience research and treatment studies among

forensic populations for over 20-years, examining mental health, addiction, personality disorders, and other forensic issues. The parent grant (R01 NS126742) for this administrative supplement (NOT-OD-24-031) focuses on the consequences of

head injury and protracted cognitive and neural deficits in forensic populations. As we describe here, the analytic strategies

involved in this project employ advanced machine learning (ML) and artificial intelligence (AI) approaches to predict TBI

and its associated cognitive decline trajectory, which raises major bioethical questions. To directly address NINDS proposed targets, and to supplement the aims of our parent R01, we will conduct bioethical research, stakeholder analysis, and

empirical work concerning diagnostic neurobiological research utilizing AI/ML for TBI, the return of results to research

participants, risk of re-identification, and the conduction of clinical trials in forensic populations. Overall, the important

work of integrating vulnerable stakeholder viewpoints into bioethical inquiry holds the potential to impact future bioethical related policy directions as requested in NOT-OD-24-031.