Exposure-based psychotherapy is the first-line treatment for anxiety disorders with medium to high effect sizes on average. Nonetheless, 30-50% of treated patients experience poor symptom reduction or relapses. Consequently, our research strives to optimize exposure therapy. Specifically, using an innovative Bayesian adaptive study design, we aim to address the underlying mechanism of exposure treatments, test superiority of small-scale interventions (e.g., positive affect), and investigate clinical and neurobiological predictors of treatment response. Our findings will enhance the current understanding of exposure treatment and pave the way for effective intervention optimization and personalized patient stratification, and, thus, increase response rates to treatment.

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