Replicability and Validity of a New Artificial-Intelligence Assessment of Posttraumatic Stress Disorder from Patient Language: A Sequential Evaluation with Model Preregistration

Details

• Journal Article:
  Clinical Psychological Science
• Personal Author:
  Kjell, Oscar ; Ganesan, Adithya V. ; Boyd, Ryan L. ; Oltmanns, Joshua R. ; Rivero, Alfredo ; Feltman, Scott ; Carr, Melissa A. ; Alves, Jorge ; Luft, Benjamin J. ; Kotov, Roman ; Schwartz, H. Andrew
  More +
• Description:
  Artificial intelligence (AI) shows promise in identifying psychopathology through language, but replicability in AI models remains challenging. We develop an AI-based language assessment of posttraumatic-stress-disorder (PTSD) severity and introduce the sequential evaluation with model preregistration to rigorously evaluate its validity and replicability. This design includes two phases: development with preregistration and evaluation. Data included development (N = 1,437) and prospective (N = 346) samples, in which participants described their lives during automated interviews. In the prospective sample, preregistered models correlated with PTSD CheckList scores (r = .38, p < .001) and converged with PTSD diagnosis (area under the curve AUC = .76; outperforming demographics and trauma exposures: AUC = .61, p < .01). We found that for each standard-deviation increase, mental-health-care expenditure rose by $696.50 (p < .001). Our preregistered PTSD model assessments are replicable in prospectively collected clinical data and showed external validity against expense criteria. With further development, such models can be used to screen for PTSD or monitor treatment response, especially in telehealth or automated interviews, in which deployment can be seamless. Description provided by NIOSH
• Subjects:
  • Artificial Intelligence
  • Mental Health
  • Occupational Health
  • Safety
  • September 11 Terrorist Attacks
  • Stress Disorders, Post-Traumatic
• Keywords:
  • Artificial intelligence; Post-traumatic stress disorder; PTSD; Mental health; Health care; Medical screening; Medical monitoring; Psychological testing; Psychology; World Trade Center; WTC;
  • Author Keywords: posttraumatic stress disorder; depression; disaster responders; language-based assessments; oral interviews; World Trade Center; open materials; preregistration
• Source:
  Clin Psychol Sci 2026 May; :Epub ahead of print
• ISSN:
  2167-7026
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  Birmingham Region OSHA ; Dallas Region OSHA ; New York ; New York City Region OSHA ; Tennessee ; Texas
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  13 pdf pages
• Volume:
  11
• Issue:
  6
• NIOSHTIC Number:
  nn:20071685
• Email:
  oscar.kjell@psy.lu.se
• Federal Fiscal Year:
  2026
• Performing Organization:
  State University of New York, Stony Brook
• Peer Reviewed:
  True
• Start Date:
  20220701
• End Date:
  20260630
• Download URL:
  https://stacks.cdc.gov/view/cdc/259456/cdc_259456_DS1.pdf
• File Type:
  [PDF - 1.32 MB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:5d4c25197bc206cc8d73609d604873d60e9872c7fec94155f368fb84413bf258c2ef56ab52c632be8822903febb31458bf87761f2e3287e3eb42e7f810059f05