Early indicators of response to transdiagnostic treatment of pediatric anxiety and depression.

ABSTRACT

BACKGROUND: Pediatric anxiety and depression are prevalent, impairing, and highly comorbid. Available evidence-based treatments have an average response rate of 60%. One path to increasing response may be to identify likely non-responders midway through treatment to adjust course prior to completing an episode of care. The aims of this study, thus, were to identify predictors of post-intervention response assessing (a) mid-treatment symptom severity, (b) session-by-session treatment process factors, and (c) a model optimizing the combination of these. METHOD: Data were drawn from the treatment arm (N = 95, ages 8-16) of a randomized transdiagnostic intervention trial (Msessions = 11.2). Mid-point measures of youth- and parent-reported anxiety and depression were collected, and therapists rated homework completion, youth and parent engagement, and youth therapeutic alliance at each session. Logistic regression was used to predict response on the Clinical Global Impression Improvement Scale (CGI-I ≤2) rated by independent evaluators masked to treatment condition. RESULTS: Mid-point symptom measures were significant predictors of treatment response, as were therapist-ratings of youth and parent engagement, therapeutic alliance, and homework completion. Therapist ratings were significant when tested as mean ratings summing across the first eight sessions of treatment (all ps < .004) and at individual session points (all ps <0.05). A combined prediction model included youth-reported anxiety, parent-reported depression, youth engagement at Session 2, and parent engagement at Session 8. This model correctly classified 76.5% of youth as non-responders and 91.3% as responders at post-treatment (Nagelkerke R2 = .59, χ2 (4, 80) = 46.54, p < .001). CONCLUSION: This study provides initial evidence that response to transdiagnostic intervention for pediatric anxiety and depression may be reliably predicted by mid-point. These data may serve as foundational evidence to develop adaptive treatment strategies to personalize intervention, correct treatment course, and optimize outcomes for youth with anxiety and depression.