Personalizing and Optimizing Preventive Intervention Models via a Translational Neuroscience Framework

A new generation of research, building upon developmental psychopathology (Luthar et al. 1997; Luthar et al. (Child Development, 71, 543–562, 2000)), provides evidence that individual differences in risk for behavioral health problems result from intrapersonal and environmental modulation of neurophysiologic and genetic substrates. This transdisciplinary model suggests that, in any given individual, the number of genetic variants implicated in high-risk behavior and the way in which they are assorted and ultimately suppressed or activated in the brain by experiential and contextual factors help to explain behavioral orientations. Implications are that behavioral health problems can be amplified or reduced based on characteristics of an individual and socio-contextual influences on those characteristics. This emerging research has extraordinary implications for the design of prevention programs that more precisely target the malleable mechanisms that underlie behavioral health problems and, hence, more effectively prevent behavioral problems and promote resilience. A detailed, theory-driven examination of all evidence-based interventions is called for to identify the active ingredients that specifically impact these underlying mechanisms. Such an approach will enhance the ability of preventive interventions to achieve effect sizes indicative of beneficial impacts for a greater number of recipients. This paper presents the significant implications of this collective knowledge base for the next generation of precision-based, prevention-focused personalized interventions.