Evidence map›Paper›PMID 40736259›Full record

ArticleJournal of traumatic stress2025

Generative artificial intelligence in posttraumatic stress disorder treatment: Exploring five different use cases.

Philip Held, Elizabeth C Stade, Katherine Dondanville, Shannon Wiltsey Stirman

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Philip HeldDepartment of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA.ORCID https://orcid.org/0000-0003-3974-1802
Elizabeth C StadeInstitute for Human-Centered Artificial Intelligence, Stanford University, Stanford, California, USA.
Katherine DondanvilleDepartment of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.ORCID https://orcid.org/0000-0003-4204-7926
Shannon Wiltsey StirmanDissemination and Training Division, National Center for PTSD, VA Palo Alto Healthcare System, Menlo Park, California, USA.

Funding

Evaluation of a Multiagent LLM-Based Simulated Patient to Train Therapists in Written Exposure Therapy for PTSDP50MH139450 · NIMH · STANFORD UNIVERSITY · PI Johannes C. Eichstaedt, SHANNON Wiltsey STIRMAN · 2025 to 2026
$7.0M
Telehealth 2.0: Evaluating effectiveness and engagement strategies for asynchronous texting based trauma focused therapy for PTSDRF1MH128785 · NIMH · STANFORD UNIVERSITY · PI DONDANVILLE, KATHERINE, WILTSEY STIRMAN, SHANNON · 2021 to 2021
$2.8M
NIMH NIH HHS P50 MH139450NIMH NIH HHS RF1 MH 128785NIMH NIH HHS RF1 MH128785United Services Automobile Association (USAA)
6 · The paper itself

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.

Indexed as

Artificial IntelligenceStress Disorders, Post-TraumaticAdultFemaleGenerative Artificial IntelligenceHumansMale

Identifiers

PMID40736259
PMCPMC12551617

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.