Modelling social and occupational outcomes for young people who attend early intervention mental health services

![CDATA[Over 75% of mental disorder emerge before the age of 25 and they are the leading cause of disability due to their impacts on overall health and productivity (Gore et al., 2011). The objective of this project is to explore clinical predictors of social and occupational outcomes for young people who attend early intervention mental health services. Recent work identified that two in three young people with emerging mental disorders did not experience meaningful improvement in social and occupational function during two years of early intervention care and that most (~49%) functional trajectories were also quite volatile (Iorfino et al., in press). Longer periods of untreated illness are associated with poorer outcomes (Ghio et al., 2014) and so identifying predictors of poor outcomes is important for providing effective early intervention. This presentation will outline the modelling process that will be implemented to elucidate underlying causal mechanisms and develop the predictive model. We will describe an Agent Based Model (ABM) with a population of agents representing young people of which each contains a network of symptoms and psychosocial factors (i.e. alcohol use or physical health) associated with mental illness and apply network theory methodologies to model psychopathology (Borsboom et al., 2021). This approach will allow us to expose associations between behavioural patterns and the relationship between symptoms and other psychosocial factors. Furthermore, we will describe psychometric network analysis techniques we will use to investigate structural characteristics of such networks and their associations to system dynamics of mental health of young people. Finally, we will describe variance reduction methods that we intend to use to increase accuracy of the predictor.]]