Leader: Kåre Rønn Richardsen
The co-occurrent pain and psychological distress project is anchored at the Centre of Intelligent Musculoskeletal Health (CIM) at Oslo Metropolitan University (OsloMet) and is part of the Health in young adults (HEYoung) project (PI Britt Elin Øiestad). OsloMet is the research manager of the project. The 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. Associate professor, Kåre Rønn Richardsen is the PI of the project. In January 2022, Dr Olaf Fjeld accepted the temporary post-doctor position described in this project, and he is currently employed at OsloMet and affiliated with CIM and the MUSK Health research group at Department of Physiotherapy. Recruitment of the PhD-fellow is ongoing, and he/she will become affiliated with the CIM and the MUSK Health research group at OsloMet, Department of Physiotherapy.
- Sub-project 1: To analyse 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:
- To identify factors associated with co-occurrent pain and psychological distress in adolescence and emerging adulthood by applying machine learning.
- To 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.
- To compare the predictive performance of different machine learning methods, and, to compare machine learning methods and traditional statistical approaches.
The project will use population-based data from four cross-sectional databases (SHoT, Young-HUNT1, Young-HUNT3 and Young-HUNT4) linked with prospectively collected data from national administrative and health registries. The current project will utilise the opportunity of data linkage between survey data and national registry data. The analysis of co-occurrent persistent pain and psychological distress in youth represent a research field that few previous studies have investigated, despite the prevalence of this double disease burden, and despite the potential for social exclusion and long-term negative impact on health trajectories. The project will provide new insight into the long-term consequences of early onset co-occurrent pain and psychological distress. The use of machine learning can potentially contribute to development of more accurate prognostic tools that will benefit both the patient, the clinician and society.