PM.20.018 – A Digital Mental Health Programme for Prediction, Prevention and Self-management of Depression
Prevention of depression is one of the top public health challenges of our time, and personalised models allowing for early detection, intervention and management can be powerful tools for improving the mental and socioeconomic health in the Netherlands. This project will optimise, implement and evaluate a service package for the individual prediction, prevention and management of depression that is based on the consortium’s extensive experience in ambulatory monitoring and modelling of disease courses in mental disorders. The optimisation of an existing app will enable both user interaction (through experience sampling, reports and feedback) and monitoring of behaviour and social interaction. It will be linked to a data analysis service that implements predictive algorithms to assess individual risk. We conceptualise depression as a complex of behavioural, psychosocial and biological factors that transcends diagnostic and disciplinary boundaries and needs to be monitored and managed in a multi-dimensional manner. Digital mental health tools offer increased accessibility also for remote and under-serviced areas and communities and can empower individuals to engage in self-management and reduce burden and cost on health care systems. In close collaboration with patients and advocacy groups, we will therefore develop a digital mental health environment that supports clinical decisions and self-management. We will deploy and evaluate this digital health solution in a variety of clinical services and psychosocial support settings. Dissemination activities will focus on improving knowledge on individual depression risk and protective factors amongst patients and healthcare professionals. The academic, health systems and industry partners will jointly work on the exploitation of these technological developments for improved mental healthcare in the Netherlands. This project will create a clinically validated digital technology for self-management of depression that integrates passive and active tracking with feedback, which will be low cost and user friendly.
Depression, digital, ESM, Personalized
Amsterdam UMC, GGzE, Open Universiteit, UMCG
|Organisation||Maastricht University (UM)|
|Name||Prof. dr. T.A.M.J. (Therese) van Amelsvoort|