32 Early childhood mental health risk calculators as a decision tool in routine care: From generation to implementation

Objectives/Goals: To advance the clinical utility of a risk calculator for identifying young children’s mental health risk, we: 1) replicate an established mental health risk algorithm in two toddler-preschool samples; 2) determine added predictive value of child and parenting assets, advancing a strengths-based approach; and 3) discuss next steps for implementation. Methods/Study Population: Data were from two studies: A population-based Cohort 1 (N=2,763) and an independent risk-enriched Cohort 2 (N=323). In Cohort 1, children (48% girls) were 51.9% Black, 21.4% White, and 2.7% Other Race; 23.8% were Hispanic. In Cohort 2, children (44% girls) were 49.2% White, 38.1% Black, and 8.4% Other Race; 11.1% were Hispanic. Risks and assets were assessed in toddlerhood/early-preschool, and psychopathology was measured later in preschool. Epidemiologic risk prediction methods were applied to: 1) replicate the published risk model that includes demographics, irritability, and adverse childhood experiences (ACEs); 2) examine added predictive utility of child and parenting assets. Predictive utility was based on area under the curve (AUC) and/or the integrated discrimination improvement (IDI). Results/Anticipated Results: The previously published risk algorithm that includes demographics, child irritability, and child ACEs was replicated in both cohorts (AUC=.70 for both; IDI=.07 in Cohort 1 and .06 in Cohort 2). Via the IDI, there was added predictive utility of child assets (i.e., social competence) in both cohorts (IDI=0.008 in Cohort 1 and 0.02 in Cohort 2), as well as added predictive utility of parenting assets (i.e., parenting involvement/self-efficacy) in Cohort 1 (IDI=0.004). Preliminary evidence for barriers/facilitators regarding early childhood mental health screening in pediatric primary care and preschool settings will also be discussed, as part of a roadmap for future implementation of the calculator in routine care. Discussion/Significance of Impact: Improving early mental health risk algorithms through a strengths-based lens is essential for evidence-based and equitable decision-making. We have laid the groundwork for future implementation of a mental health decision tool in routine care of young children, from pediatric primary care to preschool.