A Framework-Guided Analysis of Trauma-Informed Communication in AI Mental Health Systems

Abstract

The growing adoption of artificial intelligence in mental health support systems has raised ethical concerns regarding how these technologies respond to trauma related disclosures and therefore this study examined the extent to which AI-based mental health systems demonstrate alignment with core principles of trauma-informed communication. To aim this,a qualitative exploratory design was employed using six to eight standardized, hypothetical trauma-related scenarios presented consistently across two to three publicly accessible AI mental health systems. AI-generated responses were analysed using reflexive thematic analysis guided by the Substance Abuse and Mental Health Services Administration (SAMHSA) Trauma-Informed Care framework. The analysis revealed that AI systems frequently employed empathetic and validating language, particularly in relation to emotional acknowledgment and perceived safety. However, key trauma-informed principles such as empowerment, collaboration, and user choice were inconsistently demonstrated. In some instances, efforts at emotional containment risked neutralisation or distancing of traumatic experiences.Taken together these findings highlight critical ethical and communicative gaps in AI-mediated trauma responses and underscore the need for trauma-informed principles to be more systematically and intentionally integrated into the design and deployment AI mental health support systems.