The project consists of three coherent layers of research: mapping, zooming and targeting. The targeting layer consists of a critical test: Is a treatment tailored to the symptom network of the individual patient significantly more effective than treatment as usual (based on a general diagnosis), both in the short term and long term?
The hypothesis behind our personalised treatment
The network approach predicts that targeting an individual’s specific symptom network will lead to significantly better success rates and less relapse than the most successful generalised, diagnosis-based treatments that are currently common practice. We will examine whether particularly strong connections between symptoms (the edges), as well as the dominant symptoms (nodes), will serve as the best targets for effective personalised treatment. We also want to find out if relief from specific symptoms corresponds with a positive change in an individual’s network structure, meaning that the symptom network becomes healthier. In our view, achieving positive changes in an individual’s symptom network is essential for long-term recovery.
Transcending the boundaries of standard psychological treatment
In the targeting project, we will conduct a large number of case studies to analyse the effectiveness of customised treatment based on each individual’s specific symptom network. The research will be conducted in close collaboration with mental health centres. Our approach is transdiagnostic, which means that it transcends the boundaries of traditional psychological diagnoses and treatment. We will develop treatment (interventions) tailored to each individual’s network of symptoms, independent from the standard DSM diagnoses. The focus will be on the individual’s strong connections between symptoms and dominant symptoms. We will use existing effective intervention techniques for a broad range of mental disorders, depending on the specific symptom connections that need to be changed. And we will examine whether the individually customised treatments are more effective than current evidence-based protocols for traditional disorders.