Design and Evaluation of a Culturally Adapted Multimodal Virtual Agent for PTSD Screening

Cengiz Özel, Waleed Nadeem, Samuel Potter, Yahya Bokhari, Bdour Alwuqaysi, Wejdan Alotaibi, Rahaf Fahad Alnufaie, Sabri Boughorbel, Abdulrhman Aljouie, Rakan Altasan, Ehsan Hoque

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.

External IDs:dblp:journals/corr/abs-2604-17871