A new science of mental disorders: Using personalised, transdiagnostic, dynamical systems to understand, model, diagnose and treat psychopathology
2022/04/14 by Anne Roefs, Eiko I. Fried, Merel Kindt +8 · 181 citations
Medicine · Neuroscience · Psychology · #Artificial intelligence #Clinical psychology #Complex network #Computer science #Functional Brain Connectivity Studies #Medical diagnosis #Medicine #Mental Health Research Topics #Network science #Perspective (graphical) #Psychiatry #Psychological intervention #Psychology #Psychopathology #Psychotherapist #Schizophrenia research and treatment
paper · pdf · doi:10.1016/j.brat.2022.104096
published in Behaviour Research and Therapy 153, 104096 (Elsevier BV)
openalex publication_date 2022/04/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Abstract
The core ideas of a 10-year research program 'New Science of Mental Disorders' are outlined. This research program moves away from the disorder-based 'one-model-fits-all' approach to treating mental disorders, and adopts the network approach to psychopathology as its foundation of research. Its core assumption is that dynamically interacting symptoms constitute the disorder. Our goal is to further develop the network approach by studying (1) dynamic networks of symptoms and other variables (i.e., elements) in a large number of individuals with a wide range of mental disorders from a transdiagnostic perspective (network-based diagnosis; mapping), including both Ecological Momentary Assessment (EMA) and digital phenotyping, (2) the transdiagnostic mechanisms reflecting potential causal relations among elements of the networks by performing experimental (pre-)clinical studies (zooming), and (3) the effectiveness of personalised network-informed interventions (targeting). Challenges to overcome in this research program are discussed, which relate to data collection (e.g., selection of EMA variables) and data analyses (e.g., power considerations), the development and application of network-informed diagnoses and network-informed interventions (e.g., what characteristic(s) of the network to target in interventions), and the implementation in clinical practice (e.g., train therapists in the use of networks in therapy).
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