Project Summary/Abstract Improving patient outcomes will be enhanced by understanding “what works, for whom?” enabling better matching of patients to available treatments. Despite a wealth of research seeking to optimize CBT outcomes for pediatric obsessive-compulsive disorder (OCD), we have limited understanding about how to match patients with the appropriate treatment package. Past research has identified patient characteristics that may influence treatment response, including age, symptom severity, comorbidities, and previous treatment history. Unfortunately, findings have been inconsistent due to limited sample size, a focus on one modifier at a time, and difficulty integrating results across trials with different sample characteristics. Between-trial differences in sample characteristics severely limit conventional meta-analytic tools, greatly complicating cross-trial comparisons of treatment efficacy. This project will use individual-participant-data from 27 trials and data from two clinical populations and utilize recent advancements in transportability methods facilitates understanding “what works, for whom?” Transportability methods include causal analytic approaches to extend inferences from trial samples to target populations when there are marked differences in the distribution of sample characteristics between trials and the target population. Robust statistical models are used to address between-trial differences in covariates, enabling the transportation of causal estimates from trial samples to target populations. Under explicit causal and statistical assumptions, the transported analyses provide unbiased estimates of how interventions will fair in the target population(s), enabling apples-to-apples comparisons of interventions even when two interventions have not been compared in a head-to-head trial. In addition, the target population can be defined as sub-populations (e.g., younger children with high illness severity, comorbidities), enabling evaluation of relevant interventions for that sub-population, effectively providing insight into the question of “what works for whom?”