Short Project Description

This project is organized as two sub-projects, a Postdoc-project (sub-project 1) and a PhD-project (sub-project 2). Both sub-projects are 3-year full time projects funded by CIM. Sub-project 1 aim to analyze data from cohort studies linked with prospective data from health and administrative registries to investigate the association between co-occurrent pain and psychological distress in adolescence and emerging adulthood AND academic achievement, labour market participation and health trajectories. Sub-project 2 aim to 1) identify factors associated with co-occurrent pain and psychological distress in adolescence and emerging adulthood by applying machine learning, 2) apply machine learning in development of prognostic models for adulthood disability benefit and long-term sickness absence in tandem with co-occurrent pain and psychological distress, and 3) compare the predictive performance of different machine learning methods, and, to compare machine learning methods and traditional statistical approaches.