Author
Listed:
- Coimbra, Bruno Messina
- Sijbrandij, Marit
- Engelhard, Iris
- Neeleman, Rutger Chris
- Grandfield, Elizabeth M.
(Utrecht University)
- Jalsovec, Elena
- van der Kuil, Timo
(Utrecht University)
- Stoel, Lauke
- Alderfer, Melissa
- Armour, Cherie
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.
Suggested Citation
Coimbra, Bruno Messina & Sijbrandij, Marit & Engelhard, Iris & Neeleman, Rutger Chris & Grandfield, Elizabeth M. & Jalsovec, Elena & van der Kuil, Timo & Stoel, Lauke & Alderfer, Melissa & Armour, Che, 2026.
"PTSD Symptom Trajectories in the Wake of Potentially Traumatic Events: a Systematic Review and Meta-Analysis of 20 Years of Research,"
OSF Preprints
fkjb2_v3, Center for Open Science.
Handle:
RePEc:osf:osfxxx:fkjb2_v3
DOI: 10.31219/osf.io/fkjb2_v3
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