Precision Digital Health Support for Mental Health in Early Childhood: A Randomized, Controlled Trial in Childcare Centers - Background: Early academic success and positive mental health are critical for all children, because they are linked to long-term outcomes such as high school graduation, lower criminal involvement, lower likelihood of teen pregnancy, and higher earnings. While community childcare centers play a vital role in supporting early childhood education and psychosocial development for young children, their teachers often lack access to evidence-based resources, including traditional Early Childhood Mental Health Consultation (ECMHC) models. To address this gap, we developed Jump Start on the Go (JS Go)—a hybrid ECMHC intervention that delivers an AI-enhanced mobile application with human consultation. Methods: JS Go is based on our successful R01- funded Jump Start ECMHC program. JS Go, developed in English and Spanish, was designed using a community-based participatory research approach to ensure the intervention is relevant and culturally appropriate for all populations it serves. In a pilot randomized controlled trial (N=114 across six centers, three Jump Start vs three JS Go), JS Go demonstrated high feasibility, usability, and acceptability. The trial showed similar improvements in teacher-child interactions, reduced problem behaviors, and increased child prosocial skills, for JS and JS Go. User feedback identified key areas for intervention adaptation that were iteratively incorporated. Building on this work, we propose a Type 1 hybrid effectiveness-implementation trial (N=480 children, across 24 childcare centers) to rigorously evaluate JS Go’s impact on children’s psychosocial functioning, while also enhancing teacher skills and childcare center capacity to sustain effective mental health support. Using a 3-arm cluster-randomized controlled design, guided by the RE-AIM framework, we will compare (1) JS Go (AI-enhanced digital ECMHC + human consultation), to (2) traditional JS (human consultation only), and (3) attention control (digital + human consultation obesity prevention curriculum). Our hypotheses are: (1) children in both JS Go and JS arms will show greater improvement in psychosocial outcomes than the control arm; and (2) there will be no significant difference between JS Go and JS arms. In Aim 1, we will examine JS Go’s impact on child psychosocial outcomes over 24 months. In Aim 2, we will evaluate how teacher skills mediate child outcomes, and how family characteristics moderate these mechanisms. In Aim 3, we will Identify center-level implementation factors that contribute to sustained improvements in child psychosocial functioning. Our mixed-methods design will explore implementation barriers and facilitators to promote scalability. Impact: This project fills a critical gap in preventive mental health tools for childcare centers by offering a scalable and accessible hybrid mobile health intervention. If effective, JS Go could reduce early childhood behavioral challenges and improve social-emotional outcomes for children during the most formative years of development. By strengthening the daily childcare center environment where children grow and learn, this approach has the potential to create lasting improvements in academic success and long-term mental health outcomes.
