Translating RDoC to real-world impact in developmental psychopathology: A neurodevelopmental framework for application of mental health risk calculators

Abstract

The National Institute of Mental Health's Research Domain Criteria (RDoC) framework has prompted a paradigm shift from categorical psychiatric disorders to considering multiple levels of vulnerability for probabilistic risk of disorder. However, the lack of neurodevelopmentally based tools for clinical decision making has limited the real-world impact of the RDoC. Integration with developmental psychopathology principles and statistical methods actualize the clinical implementation of RDoC to inform neurodevelopmental risk. In this conceptual paper, we introduce the probabilistic mental health risk calculator as an innovation for such translation and lay out a research agenda for generating an RDoC- and developmentally informed paradigm that could be applied to predict a range of developmental psychopathologies from early childhood to young adulthood. We discuss methods that weigh the incremental utility for prediction based on intensity and burden of assessment, the addition of developmental change patterns, considerations for assessing outcomes, and integrative data approaches. Throughout, we illustrate the risk calculator approach with different neurodevelopmental pathways and phenotypes. Finally, we discuss real-world implementation of these methods for improving early identification and prevention of developmental psychopathology. We propose that mental health risk calculators can build a needed bridge between the RDoC multiple units of analysis and developmental science.

Prevalence, stability, and predictive utility of the Multidimensional Assessment of Preschoolers Scales clinically optimized irritability score: Pragmatic early assessment of mental disorder risk

“…Future research leveraging computational psychiatry approaches is needed to specify the constellation of intrinsic developmental (e.g., compensatory language skills) and extrinsic social-ecologic (e.g., family cohesion and conflict) factors for precise estimation of risk. (MacNeill et al, 2021).…”

Toward an optimized assessment of adolescent psychopathology risk: Multilevel environmental profiles and child irritability as predictors

“…Abbreviations: ADHD, attention deficit hyperactivity disorder; CD, conduct disorder; ODD, oppositional defiant disorder. Ongoing work seeks to apply findings such as those presented here to the development of risk calculation algorithms that can reduce decision-making burden on providers for intervention referral (Luby et al, 2019;MacNeill et al, 2021). To maximize flexibility and utility in real-world situations, such algorithms need to output accurate recommendations with varied sets of information.…”

Don't Get Lost in Translation: Integrating Developmental and Implementation Sciences to Accelerate Real-World Impact on Children's Development, Health, and Wellbeing

“…The likelihood that neurodevelopmental vulnerability—indicated by elevated irritability—will result in heightened mental health risk, is shaped by the child's unique developmental context. To account for risk amplifying and resilience promoting contextual influences, weighted risk algorithms leveraging routine information available within the EHR can then generate an individual child's risk based on consideration of developmental (e.g., language skills) and social-ecological context (e.g., ACES exposure, responsive family environment) in which behavior is embedded ( 23 ).…”

“…We propose raising pragmatic concerns to an equal position with developmental considerations at the measurement selection table ( 21 , 22 ). This includes considering what is “good enough” to address specific questions of interest (e.g., when is direct developmental assessment needed vs. a developmental screening questionnaire will suffice), employing modern psychometrics to improve measurement efficiency and weighting intensity of measurement burden in selection ( 23 ).…”