Marina Bornovalova

Bio: Dr. Bornovalova received her Master of Science (2005) and Doctor of Philosophy (2008) degrees in Clinical Psychology from the University of Maryland, College Park, where she was mentored by Dr. Carl Lejuez. Dr. Bornovalova completed her post-doctoral training (2010) at the University of Minnesota under the NIMH fellowship, “Neurobehavioral aspects of personality and psychopathology” under the direction of Dr. William Iacono and Dr. Matt McGue, two internationally recognized leaders in the field of behavioral genetics, disinhibition, and substance abuse. Dr. Bornovalova has two interconnected lines of research. First, she investigates the trajectory, course, and mechanisms (genetic and environmental) on borderline personality disorder and its comorbidity, especially with externalizing psychopathology. She also studies transdiagnostic mechanisms underlying multiple forms of psychopathology, including impulsivity, reward processes, and distress tolerance/resilience. Her research has been published in journals including American Journal of Psychiatry, Psychological Assessment, Journal of Personality Disorders, and Development and Psychopathology. She has received scholar awards for her graduate work from the Association of Cognitive and Behavioral therapies, the American Association of University Women, and the University of Maryland. She has also received several grants from the National Institute of Drug Abuse, including a currently funded randomized clinical trial of a distress tolerance treatment.

Title (preliminary): Drug Use: Approach and Avoidance in Relapse Dynamics

Abstract (preliminary): Drug and alcohol relapse are difficult to predict. A promising theoretical model (Ambivalence Model of Craving) suggests that fluctuations and conflicts between two motivational systems – approach and avoidance may explain and predict drug and alcohol relapse. This model makes dynamical and nonlinear predictions; however researchers have not had the quantitative tools to test these predictors. Recognizing this complexity, top addiction and quantitative theorists specifically called for the development of nonlinear and dynamic models for explaining relapse. And, cutting-edge quantitative work suggests that the focus on the intraindividual variation will be most effective in accounting for increased variance in negative behavioral outcomes. We followed 30 substance users transitioning from residential treatment into the community. Each user was monitored daily for approach, avoidance, and illicit substance use over 93 days. We propose to use cutting-edge quantitative methods (dampened oscillator model, Boker et al, 2003, Hu et al, 2014) to model intra-individual change and causal processes for discontinuity, nonlinearity, and sudden transitions between states of abstinence and active use. Essentially, these individual-level models will explain the per-person covariation between daily approach, avoidance, and substance use. Speaking to theory, if fluctuations in approach and avoidance are predictive of return to use, this will begin changing the way we study (and predict) relapse in the laboratory and community. In the longer term, these data and analyses will inform theory and enable personalized medicine using the users’ approach, avoidance and their likely dynamics of risk to relapse.