Sean Cavanagh

Despite the availability of effective interventions for OCD, diagnosis is often delayed and outcomes are heterogeneous. Conversely, early detection and intervention, particularly in youth, improves long-term outcomes. This highlights the need to identify predictive markers of risk, treatment response, and relapse in child and adolescent populations. Computational psychiatry is an emerging field that seeks to address precisely these challenges by employing behavioural tasks to measure cognitive and affective mechanisms more objectively and mechanistically.

Recent translational work has demonstrated that metrics from decision-making tasks prospectively predicted relapse after antidepressant discontinuation and in opioid use disorder – illustrating their potential to provide predictive information beyond conventional assessments. Specific to OCD, cross-sectional studies have consistently demonstrated a shift from goal-directed to habitual control in decision-making paradigms. However, there is an absence of longitudinal studies in OCD patient populations, which prevents these findings being translated into clinically actionable predictors of treatment response or relapse.

I am the principal investigator of the OPTIC study - a prospective longitudinal study run within the South London and Maudsley OCD/BDD service. The OPTIC study proposes to bridge this gap with the goal of offering opportunities for earlier identification, personalised intervention, and mechanistic evaluation of treatment effects in OCD. We will utilise recently developed smartphone-based gamified behavioural assessments in young people with OCD, and use behavioural metrics to predict symptoms and treatment outcomes.