PTSD Symptom Trajectories in the Wake of Potentially Traumatic Events: a Systematic Review and Meta-Analysis of 20 Years of Research
Year: 2026
Type: preprint
Study designs: Systematic Review, Meta-Analysis
Abstract: This systematic review, meta-analysis and meta-regression evaluates twenty years of literature on data-driven identification of common PTSD symptom trajectories following potentially traumatic events. Traditional, machine learning- and large language model–assisted systematic search approaches were combined to identify eligible articles applying statistical Growth Mixture Modeling to longitudinally assessed PTSD symptom severity. Ninety-nine studies representing 113 independent samples and 215,136 participants from 21 countries were included. We identified five prototypical PTSD symptom trajectories that commonly occurred across samples. We determined pooled relative trajectory prevalence estimates across samples observing these specific trajectories with the low symptoms trajectory being the most and the increasing symptoms trajectory the least prevalent. Using meta-regression, various socio-demographic, exposure-related and methodological moderators of sample-level relative trajectory prevalences were identified. Our findings provide empirical support and further refinements of leading theoretical PTSD conceptualizations. Furthermore, the obtained relative prevalence estimates and sample-level moderators may inform population-tailored trauma-related mental health care.
Authors: Bruno Messina Coimbra, Marit Sijbrandij, Iris Engelhard, Rutger Chris Neeleman, Elizabeth M. Grandfield, Elena Jalsovec, Timo van der Kuil, Lauke Stoel, Melissa Alderfer, Cherie Armour, David Berle, Paul A. Boelen, Richard A. Bryant, Elbert Geuze, Karen-Inge Karstoft, Laurien Meijer, Joanne Mouthaan, Jesper Pihl-Thingvad, Rens van de Schoot, Mirjam van Zuiden, Ulrich Schnyder, Katharina Schultebraucks, Geert Edzko Smid
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7151445644