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

TL;DR

This paper introduces Molhim, a culturally adapted multimodal AI platform with a virtual avatar for PTSD screening among military personnel, demonstrating its feasibility and design considerations in clinical settings.

Contribution

The work presents Molhim, a novel multimodal conversational AI system tailored for PTSD screening, integrating real-time speech, visual understanding, and avatar interaction.

Findings

Molhim effectively administers PTSD screening via a virtual avatar.

The platform demonstrates feasibility in military healthcare settings.

Design considerations for socially cooperative AI in clinics are highlighted.

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.