Funding received: €1 500 000
Projectleader and coordinator: dr. Mirjam van Zuiden, Amsterdam UMC (AMC) – Psychiatry
Main applicant: prof. dr. Miranda Olff, Amsterdam UMC (AMC) – Psychiatry
Co-applicants and collaborators: Utrecht University (prof. dr. R. van de Schoot), Erasmus MC (dr. J.A. Haagsma), Amsterdam UMC (AMC) (prof. dr. G.A. van Wingen), Arq National Psychotrauma Center (dr. M. Boeschoten), Slachtofferhulp Nederland (drs. S. Dickie), VeiligheidNL (dr. M. Panneman), NYU School of Medicine (prof. dr. A. Shalev), Harvard School of Public Health (prof. dr. K. Koenen), VU Universiteit (dr. M. Sijbrandij), Leiden University (dr. J. Mouthaan), Amsterdam UMC (VU)/OLVG (dr. B. Broekman), Maastricht University (prof. dr. T. van Amelsvoort) and Amsterdam UMC AMC and VUmc Emergency Departments (drs. T. Biesheuvel & drs. M. Ridderikhof).
One in 13 Dutch adults develop lifetime posttraumatic stress disorder (PTSD), as a result of traumatic events involving (threatened) death, injury or violated physical integrity. Women have a 1.5 to 2-fold increased risk for PTSD following trauma exposure compared to men. Only the first weeks post-trauma provide a unique window of opportunity for preventive interventions to reduce prevalence of long-term PTSD, related adverse outcomes and societal costs, including mental health care use. Importantly, these interventions are only beneficial if delivered as indicated preventive intervention to individuals at high risk for long-term PTSD. Previous research elucidated many risk and protective factors for PTSD, from demographic, socio-economic, psychiatric, psychosocial, biological, trauma history and environmental domains. Existing prognostic screening instruments, however, fail to adequately predict long-term PTSD when applied early post-trauma. The main outcome of this 8-year consortium project will be a sex-specific prognostic screening instrument derived with machine learning methods to accurately predict which recently trauma-exposed individuals are at risk for long-term PTSD. Hereby we can target indicated preventive interventions to individuals who are most in need of help and will benefit from intervention, thus preventing major suffering and adverse outcome.