Kendall, Philip C.Olino, Thomas2023-09-032023-09-032023http://hdl.handle.net/20.500.12613/8880Background: Efficacious treatments for youth anxiety disorders exist, but there is considerable heterogeneity in outcome. Predictors and moderators of differential treatment response have been difficult to identify. Machine Learning (ML) is a promising approach. Methods: Data from nine randomized controlled trials (RCTs) of youth anxiety treatments were harmonized into a dataset (N = 1362; Mage = 10.59, SDage = 2.47; 48.9% female; 71.9% White, 5.9% Black, 1.0% Asian; 10.8% Hispanic) and supervised ML algorithms predicted treatment outcomes. ML models were also built separately for youth who completed individual cognitive behavioral therapy (CBT), family CBT, combination of sertraline (SRT) and CBT, and SRT alone to examine predictive features. Models were then externally validated in a research clinic providing CBT for youth anxiety (N = 50; Mage = 12.04, SDage = 3.22; 56% female; 76% Caucasian, 10% Black, 6 % Asian, 2% Other; 6% Hispanic). Results: Lasso Regression emerged as the best performing model (RMSE = 1.40), with comparable RMSEs when the same approach was applied within an external dataset (RMSE = 1.40). Predictive features of poorer outcomes were primarily indicators of increased symptom severity, particularly youth depressive symptom severity, although predictors varied within subsamples (e.g., caregiver psychopathology was an important predictor for FCBT; increased somatic symptoms were important predictors for better response to SRT). Discussion: ML helped identify features of anxious youth who will respond to treatments.75 pagesengIN COPYRIGHT- This Rights Statement can be used for an Item that is in copyright. Using this statement implies that the organization making this Item available has determined that the Item is in copyright and either is the rights-holder, has obtained permission from the rights-holder(s) to make their Work(s) available, or makes the Item available under an exception or limitation to copyright (including Fair Use) that entitles it to make the Item available.http://rightsstatements.org/vocab/InC/1.0/Clinical psychologyText149132023-08-24Norris_temple_0225E_14913.pdf