ArticleJournal of traumatic stress2025
Generative artificial intelligence in posttraumatic stress disorder treatment: Exploring five different use cases.
Article in Journal of traumatic stress, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Artificial intelligence in traumatic stress treatment: The TRUST framework for ethical development, clinical applications, and research advancement.Journal of traumatic stress · 2026Review
- Article
- Generative artificial intelligence in posttraumatic stress disorder treatment: Exploring five different use cases.Journal of traumatic stress · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Posttraumatic stress disorder (PTSD) is a prevalent and debilitating condition, yet many individuals face substantial barriers to accessing evidence-based interventions. Advances in generative artificial intelligence (AI), particularly large language models (LLMs), have generated optimism about improving access and care. We present five emerging use cases for clinical AI tools in the context of PTSD treatment, some of which were presented as part of a symposium at the 40th Annual Meeting of the International Society for Traumatic Stress Studies. The first two use cases involve AI-assisted training tools. The third use case focuses on an AI-assisted automated fidelity rating system aimed at improving adherence to evidence-based PTSD protocols. The last two use cases feature AI-assisted therapy tools. Although AI-based innovations hold the promise of enhancing the reach and consistency of evidence-based PTSD interventions, they also raise important ethical and safety challenges, including risk of bias, threats to patient privacy, and the question of how to incorporate clinical oversight. Ongoing collaboration among multidisciplinary teams involving clinicians, researchers, and technology developers will be essential to ensuring that AI tools remain patient-centered, ethically sound, and effective.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.