Using Machine Learning to Predict Treatment Outcome in a Concatenated Dataset of Youth Anxiety Treatments.

Journal: Child psychiatry and human development
Published Date: Jul 3, 2025

Abstract

Machine Learning (ML) is a promising approach for predicting outcomes of youth anxiety treatments. To this end, data from nine randomized controlled trials of youth anxiety treatments were concatenated into a dataset (N = 1362; M = 10.59, SD = 2.47; 48.9% female; 71.9% White, 5.9% Black, Other, 5.9%; 10.8% Hispanic) and ML algorithms were used to predict outcomes. Models were then applied on an external validation sample in a research clinic (N = 50; M = 12.04, SD = 3.22; 56% female; 76% Caucasian, 10% Black, 6% Asian, 2% Other; 6% Hispanic). To examine predictive features by treatment type, Lasso Regression models were built separately for youth who completed individual cognitive behavioral therapy (CBT), family CBT (FCBT), sertraline alone (SRT), and combination of SRT and CBT (COMB). Automatic relevance determination (ARD) emerged as the best performing model in the concatenated (RMSE = 1.84, R = 0.28) and external validation datasets (RMSE = 1.87, R = 0.11). Predictive features of poorer outcomes were primarily indicators of symptom severity and trial effects, although predictors varied within treatments (e.g., caregiver psychopathology was predictive for FCBT; depressive symptoms were predictive for COMB). Implications for use of ML to predict outcomes are discussed.

Authors

  • Lesley A Norris
    Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, USA. Lesley.norris@brown.edu.
  • Marija Stanojevic
    Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, Pennsylvania, USA.
  • Laura C Skriner
    The Center for Stress, Anxiety, and Mood, LLC, Summit, NJ, USA.
  • Brian C Chu
    Department of Clinical Psychology, Graduate School of Applied and Professional Psychology, Rutgers University, Piscataway, NJ, USA.
  • Marianne Aalberg
    Akershus University Hospital, Lørenskog, Norway.
  • Wendy K Silverman
    Yale University, New Haven, CT, USA.
  • Denise Bodden
    Department of Clinical Child and Family Studies, Utrecht University, Utrecht, The Netherlands.
  • John C Piacentini
    Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA, USA.
  • Zoran Obradovic
  • Philip C Kendall
    Department of Psychology, Temple University, Philadelphia, PA, USA.

Keywords

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