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

Bibliographic Data

ID21344622
AuthorsPauline Goger (0000-0002-6054-6350, San Diego State University, Imperial Valley Campus, corresponding author), Michelle Rozenman (0000-0002-4759-6548, UCLA Division of Child and Adolescent Psychiatry, Department of Psychology University of Denver Denver CO USA), Araceli Gonzalez (0000-0001-7462-405X, Department of Psychology California State University Long Beach Long Beach CA USA), Doug Brent (0000-0002-5756-2157, University of Pittsburgh School of Medicine Pittsburgh PA USA), Giovanna Porta (University of Pittsburgh School of Medicine Pittsburgh PA USA), Frances L Lynch (0000-0002-0547-6812, Kaiser Permanente Center for Health Research Portland OR USA), John F Dickerson (0000-0003-1903-3681, Kaiser Permanente Center for Health Research Portland OR USA), V Robin Weersing (0000-0002-7904-4799, San Diego State University, Imperial Valley Campus)
Year2023
Volume64
Issue12
Pages1689-1698
Publication date2023-12-01
Open AccessYes
TypeARTICLE
VenueJournal of Child Psychology and Psychiatry (JOURNAL)
Journal identifiersISSN: 0021-9630 • E-ISSN: 1469-7610
PublisherWiley (PUBLISHER • GB)
DOI10.1111/jcpp.13881
PMID37605294
OpenAlexW4386046492
LanguageEN
Citations received2
References cited43

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 ( M sessions = 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 p s < .004) and at individual session points (all p s <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 R 2 = .59, χ 2 (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

Anxiety · Depression (economics) · Depressive symptoms · Intervention (counseling) · Logistic regression · Psychiatry · Randomized controlled trial · Session (web analytics) · Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes · Child and Adolescent Psychosocial and Emotional Development · Clinical Psychology · Digital Mental Health Interventions · Internal Medicine · Medicine · Psychology

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