Ardo Allik

Mental health disorders are widespread, and their impact on individual functioning, work ability, and the healthcare system is substantial. At present, the effects of interventions delivered as part of mental health support or treatment are assessed mainly through clinical interviews and self-reports, usually during infrequent visits. The project adds a regular data-driven measurement layer to this process and develops an interpretable individualized model and a standardized workflow to help detect clinically meaningful changes earlier, more consistently, and more objectively. In this way, the project lays the foundation for a new data-driven service layer in occupational health and mental health services, as well as for the further development of well-being digital solutions based on neurophysiological input.