Visual, Vocal, and Verbal Markers of PTSD: A Parallel Affective Computing Approach
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Current PTSD assessment methods often compromise diagnostic precision for scalability, limiting clinical effectiveness. We propose a digital task-shifting framework that utilizes computational techniques to enhance assessment capacity while preserving clinician judgment. We implemented two structured trauma-activation tasks (trauma account and impact statement) via telehealth to elicit disorder-relevant behavioral signals, then quantified PTSD-related behaviors across modalities: verbal, vocal, and visual. Parallel unimodal statistical analyses prioritized interpretability. Comparing 49 individuals with PTSD and 44 trauma-exposed controls isolated PTSD-specific effects. Bayesian generalized linear mixed models revealed significant main effects of group across all modalities with group-by-task interaction effects specifically in verbal and vocal modalities. These findings demonstrate digital task-shifting can capture clinically meaningful variations in PTSD within a scalable framework, complementing traditional assessment methods. Strong interaction effects indicate context-dependent shifts and constrained stylistic patterns across modalities. This approach provides objective indicators of distress to potentially support clinical assessments and research via telehealth.
Source: PsyArXiv (OSF Preprints)
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7213650767