Design and Evaluation of a Culturally Adapted Multimodal Virtual Agent for PTSD Screening
Cengiz Ozel, Waleed Nadeem, Samuel Potter, Yahya Bokhari, Bdour Alwuqaysi + 6 more
TLDR
Molhim is a culturally adapted multimodal AI platform using a virtual agent for PTSD screening in combat-exposed military personnel.
Key contributions
- Introduces Molhim, a culturally adapted multimodal AI platform for PTSD screening.
- Utilizes an LLM-driven virtual avatar with real-time speech, visual understanding, and TTS.
- Supports structured multi-turn dialogue and automated PCL-5 administration for PTSD.
- Demonstrates feasibility of AI agents for sensitive clinical screenings in military contexts.
Why it matters
This paper addresses underreported PTSD in military personnel with Molhim, an innovative, culturally adapted AI screening platform. It offers a sensitive and advanced approach to improve access to care. The findings provide valuable insights for designing future human-AI systems in clinical settings.
Original Abstract
Post-traumatic stress disorder (PTSD) is highly prevalent yet chronically underreported among combat-exposed military personnel. This paper presents Molhim, a culturally adapted multimodal conversational AI platform that supports purpose-specific interactions through a configurable conversational pipeline consisting of session setup, real-time dialogue with a high-fidelity virtual avatar, and post-session analysis and feedback. In this work, we examine the PTSD screening configuration of the Molhim platform in a military healthcare context. The system employs a conversational avatar driven by a large language model, integrating real-time speech recognition, visual understanding of user input, text-to-speech synthesis, and a high-fidelity human avatar to support structured multi-turn dialogue and automated post-session analysis, including administration of the PTSD Checklist for DSM-5 (PCL-5). These findings suggest the feasibility of Molhim as a conversational platform for PTSD screening and highlight design considerations for socially cooperative human-AI systems in clinical environments.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.