PROJECTING LONG-TERM CLINICAL IMPACT AND COST-EFFECTIVENESS OF SCHOOL-BASED DIGITAL COGNITIVE BEHAVIORAL THERAPY FOR ADOLESCENT ANXIETY: A MICROSIMULATION STUDY

Abstract

Purpose: To project the long-term clinical impact and cost-effectiveness of a school-based digital cognitive behavioral therapy (d-CBT) screening and intervention program for adolescent anxiety.

Methods: A 10-year state-transition microsimulation model was developed in Python. A hypothetical cohort of 10,000 adolescents was simulated under two scenarios: usual care and intervention (school-based digital screening with linked d-CBT access for 50% of the cohort). Model parameters were derived from national epidemiology, clinical trials, and health economics data. Outcomes included population anxiety scores, annual healthcare visits, and costs.

Results: At the 5-year mark, the intervention led to a clinically significant reduction in mean anxiety scores (Approximately −11 points) and decreased mean annual healthcare visits per person (−0.36). For the cohort of 10,000, this translated to 18,000 fewer total visits and net cost savings of $1.48 million after accounting for program costs.

Conclusion: A school-based digital mental health program is projected to generate substantial long-term improvements in adolescent mental health while reducing healthcare system costs. These findings support the integration of scalable, preventive digital tools into adolescent care as a cost-effective public health strategy.