Predictive methods for improving sustainability of mental well-being at work (ENNAKKO)
We aim to answer questions about which factors predict mental health problems in the Finnish working population and how these factors affect their work ability and recovery. We study how artificial intelligence algorithms can best be utilized in mental health research and how the information produced using them can promote patient work in occupational health care and early intervention.
The project provides a unique context for studying which social, occupational, and work environment-related factors contribute to employees ending up in occupational health care, what kinds of symptoms they experience that affect their work ability, and how these factors and symptoms affect the treatment they receive and their recovery.
Materials and techniques
The analyses carried out in the project are founded in AI-based text mining methods and forecasting models. Machine learning methods have enabled comprehensive analysis of massive text datasets. As research material, we utilize the patient documents and workplace surveys that Terveystalo Healthcare Oy collects about people of working age.
Results and effectiveness
The project produces a risk map that describes the development of mental health problems in employees, which can be used in developing the work environment and working conditions, as well as in promoting mental health and occupational safety and health. In order to support occupational health care activities, an application will be developed based on the risk map, which will produce individual predictions of the likely consequences of mental health disorders, such as repeated sickness absences. Possible uses of the tool include clinical patient work, guidance, and counselling, as well as in occupational health negotiations
The project is carried out in co-operation with Terveystalo Healthcare Oy and the University of Helsinki. The project’s research results will be published in a final report, in international scientific publications and as new visualizations in the Work-life knowledge service.
The Finnish Work Environment Fund