Development and external validation of a short prognostic screening instrument for PTSD one year following individual civilian trauma

Publication date

2025-12

Authors

Karchoud, Jeanet FISNI 0000000523924238
Hoeboer, Chris M
van Gelder, Nicole
Mouthaan, Joanne
Sijbrandij, E.M.ISNI 0000000390767442
Olff, Miranda
Van de Schoot, R.ORCID 0000-0001-7736-2091ISNI 0000000393562696
van Zuiden, MirjamORCID 0000-0002-1225-2702ISNI 0000000389241136

Editors

Advisors

Supervisors

Document Type

Article
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License

cc_by

Abstract

Background: Timely identification of individuals at risk for developing PTSD following trauma is crucial for providing targeted preventive interventions. Machine learning techniques show promise for deriving accurate prognostic screening instruments. However, accurate externally validated prognostic screening instruments for broad application in trauma-exposed civilians are not yet available. Moreover, it remains unknown whether prognostic screening instrument accuracy may be improved if developed in a sex-stratified manner. Objective: We aimed to develop an externally validated prognostic PTSD screening instrument based on self-report information obtained within 2 months post-trauma in two independent cohorts of recently trauma-exposed civilians, using machine learning techniques allowing for extraction of a short screener. We examined whether separate models for males and females improved prognostic accuracy compared to sex-combined models. Methods: Prognostic machine learning models (CART and XGBoost) were developed in a longitudinal cohort of N  = 327 adults (38% females) requiring evaluation of (suspected) serious injury by an emergency department. External validation was performed in another longitudinal cohort of N  = 466 adults (57% females) referred for emotional, practical or legal victim support following crime or traffic accidents. PTSD status at 1 year post-trauma was based on CAPS-IV for internal and PCL-5 for external validation. Results: During internal validation, all models achieved excellent accuracy (AUC/sensitivity/specificity > 0.90). During external validation, sufficient accuracy was only achieved for the sex-combined XGBoost model (AUC = 0.73, sensitivity = 0.69, specificity = 0.68), including 22 items of demographic and health characteristics, trauma characteristics, peri-traumatic distress or dissociation, post-traumatic cognitions, PTSD symptoms and social support. Conclusion: We developed an accurate externally validated short prognostic screening instrument for PTSD based on self-report questions that is applicable to a broad population of recently trauma-exposed civilians. This novel instrument enables timely identification of individuals at risk for PTSD following trauma, and research into early targeted interventions to prevent long-term PTSD for civilians following trauma.

Keywords

Adult, Female, Humans, Longitudinal Studies, Machine Learning, Male, Mass Screening, Middle Aged, Prognosis, Self Report, Stress Disorders, Post-Traumatic/diagnosis, Wounds and Injuries/psychology, SDG 3 - Good Health and Well-being, SDG 16 - Peace, Justice and Strong Institutions

Citation

Karchoud, J F, Hoeboer, C M, van Gelder, N, Mouthaan, J, Sijbrandij, M, Olff, M, van de Schoot, R & van Zuiden, M 2025, 'Development and external validation of a short prognostic screening instrument for PTSD one year following individual civilian trauma', European Journal of Psychotraumatology, vol. 16, no. 1, 2594266. https://doi.org/10.1080/20008066.2025.2594266