DIMESA: Diagnosing Fatigue and Burnout Causes

Diagnosis of Mental and Somatic Abnormalities for Fatigue and Burnout (DIMESA)

DIMESA is a new public-private partnership uniting Leiden University, Arbo Unie, Amsterdam UMC, Utrecht University, Linksight, and Sciex to tackle the challenge of diagnosing fatigue and burnout in the working population. The project aims to develop and validate a novel diagnostic framework that integrates blood-based biomarkers and questionnaire data, using artificial intelligence to identify or exclude a wide range of somatic and mental health causes of fatigue.

Fatigue is a common and complex complaint, with about 15,000 people visiting a general practitioner daily in the Netherlands—28% of whom have a somatic cause. Burnout, often linked to work stress, affects 20% of the Dutch workforce and leads to significant productivity loss and healthcare costs. Current diagnostic approaches are often subjective and may miss underlying medical or psychological conditions, resulting in misdiagnosis, delayed treatment, and prolonged sick leave. There is a clear need for improved, objective, and inclusive diagnostic tools to support both patients and healthcare professionals.

The DIMESA project will recruit 1,000 employees on sick leave due to fatigue or suspected burnout. Participants will complete validated questionnaires and provide a blood sample, which will be analysed for a broad spectrum of biochemical markers using advanced mass spectrometry. Artificial intelligence will integrate these data to identify somatic and psychosomatic abnormalities, supporting occupational physicians in making accurate diagnoses and recommending appropriate interventions. The approach will be optimised and validated in real-world occupational health settings.

The main deliverables are a validated AI-based diagnostic framework, a high-throughput blood biomarker platform, and a business plan for implementation in occupational healthcare. These results will enable faster, more precise diagnosis of fatigue and burnout, reduce unnecessary referrals, and support earlier return to work, benefiting employees, employers, and society as a whole.

Summary
DIMESA develops and validates an AI-driven diagnostic framework combining blood biomarkers and questionnaires to identify somatic and mental causes of fatigue and burnout, aiming for faster and more accurate diagnosis and return to work.
Technology Readiness Level (TRL)
4 - 6
Time period
36 months
Partners