# Research Project 1 > **NIH NIH P50** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2024 · $526,122 ## Abstract SUMMARY/ABSTRACT – PROJECT 1 Project 1 of the Center on Causal Data Science for Child and Adolescent Maltreatment Prevention (CHAMP Center) will involve determining predictive and causal models for many categories of maltreatment exposures and their consequential outcomes, and developing a scalable set of decision support tools (DSTs) from these models. These DSTs will be designed to guide decisions by practitioners in a position to prevent maltreatment and mitigate the severity of maltreatment-related outcomes. Given that intervention on targets that are non-causal/non-etiological factors cannot improve health or adaptive functioning, such decisions require that that the practitioner can confidently: 1) identify etiological factors that cause health or functional impairments, and 2) target the external or internal etiological factors relevant for these impairments for a particular child and family. This becomes especially challenging when etiologies are complex and interventions must be customized to precisely target diverse sets of causes, as is often true for children and families who meet criteria for maltreatment-related interventions. The goal of Project 1 is to determine models and to develop a set of DSTs to guide such decisions. We will do this by applying advanced causal data science methods to several large, relevant data sets to derive valid causal models for several categories of maltreatment exposure (sexual abuse, physical abuse, neglect) and maltreatment- related outcomes (post-traumatic stress disorder, depression, self-harm, aggression, substance abuse, obesity, functional impairment). We will integrate these analyses with machine learning predictive classification to identify which predictive models can accurately classify children into risk categories. We will work closely with members of the Resource Core to develop the models and of the Dissemination & Outreach Core to engage the full spectrum of relevant stakeholders (domain experts, primary care pediatricians, child welfare workers, behavioral health clinicians, agency administrators, children, and family members) to ensure that the tools Project 1 develops are effective, practical, trustworthy, and safe. One of the DSTs that Project 1 develops will form the basis for Project 2, which will test this tool in a field trial. Insights from Project 2 will be essential for Project 1 to iteratively improve on the DSTs it develops. ## Key facts - **NIH application ID:** 10920437 - **Project number:** 5P50HD112027-02 - **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE - **Principal Investigator:** Sisi Ma - **Activity code:** P50 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $526,122 - **Award type:** 5 - **Project period:** 2023-09-05 → 2028-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10920437 ## Citation > US National Institutes of Health, RePORTER application 10920437, Research Project 1 (5P50HD112027-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10920437. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*