Predicting remission following CBT for childhood anxiety disorders: a machine learning approach.

Background: The identification of predictors of treatment response is crucial for improving treatment outcome for children with anxiety disorders. Machine learning methods provide opportunities to identify combinations of factors that contribute to risk prediction models.

Methods: A machine learning approach was applied to predict anxiety disorder remission in a large sample of 2114 anxious youth (5-18 years).

Internet-based cognitive behavioral intervention for adolescents with anxiety disorders: a study protocol for a parallel three armed randomized controlled trial.

Background: Anxiety disorders are among the most prevalent mental health concerns affecting children and adolescents. Despite their high prevalence, statistics indicate that fewer than 25% of individuals in this demographic seek professional assistance for their condition. Consequently, there is a pressing need to develop innovative interventions aimed at improving treatment accessibility.

Patterns of sub-optimal change following CBT for childhood anxiety.

Background: Children and adolescents demonstrate diverse patterns of symptom change and disorder remission following cognitive behavioural therapy (CBT) for anxiety disorders. To better understand children who respond sub-optimally to CBT, this study investigated youths (N = 1,483) who continued to meet criteria for one or more clinical anxiety diagnosis immediately following treatment or at any point during the 12 months following treatment.

Methods: Data were collected from 10 clinical sites with assessments at pre-and post-treatment and at least once more at 3, 6 or 12-month follow-up.

The Effectiveness of Modular Transdiagnostic Cognitive Behavioral Therapy Versus Treatment as Usual for Youths Displaying School Attendance Problems: A Randomized Controlled Trial.

School attendance problems (SAPs) are associated with negative short- and long-term outcomes. Despite high prevalence of SAPs, there is a shortage of evidence-based interventions. Existing approaches often target either school refusal or truancy, leaving a gap in effective interventions addressing both types of SAPs.