Imagine a mental health safety net that catches people before they fall into a crisis. It combines local community support with a smart app that learns a person's patterns to predict when they might struggle. It's like having a personalized early-warning system for stress and depression.
Societal changes like war, pandemics, and economic crises create massive mental health burdens that overwhelm traditional clinical services. There is a lack of scalable, preventative tools for vulnerable groups that don't require immediate hospital admission.
A comprehensive community-based intervention package called COMBINA and an AI-driven smartphone app for self-monitoring and predictive mental health management.
If you are a health-tech app developer dealing with high user churn due to generic advice — this project developed an AI-based self-monitoring tool that uses n=1 longitudinal statistics to provide individualised predictive models. This allows for personalized preventive support based on real smartphone data.
If you are a regional healthcare provider dealing with overwhelmed clinics during societal crises — this project developed COMBINA, a community-based intervention package. It shifts the burden from clinics to the community, focusing on 5 vulnerable groups to maintain mental health outside hospital settings.
If you are an EAP provider dealing with the mental distress of long-term unemployed or displaced workers — this project developed a validated intervention package for sub-diagnostic mental health problems. This helps users manage depressive symptoms before they require expensive clinical treatment.
Based on available project data, no specific pricing or cost information is provided.
Yes, the project is validating the package in 5 model regions across 5 countries to ensure it is a ready-to-use package for adoption throughout Europe and beyond.
Based on available project data, specific IP or licensing details are not mentioned.
The system integrates a smartphone app that uses AI and longitudinal statistics to create predictive models for self-management.
The project period runs from 2023-04-01 to 2028-03-31.
The consortium is research-heavy with 14 partners across 9 countries, including 8 research organizations and 2 universities. While the industry ratio is relatively low at 14% (2 industry partners, 3 SMEs), the lead is an experienced association (EAAD) that has already scaled operations across 17 EU countries, suggesting strong implementation capabilities despite the academic lean.
Contact the European Alliance Against Depression EV in Germany
Contact us to explore licensing the COMBINA package or the AI self-monitoring app.
