{
  "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.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "name": "Yuanyuan Yang"
    },
    {
      "name": "Daiil Jun"
    },
    {
      "name": "Brett Welch"
    },
    {
      "name": "Allison Sylvia"
    },
    {
      "name": "Joel Gregory Sprunger"
    },
    {
      "name": "Jeffrey M. Girard"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4my60zx03gy8e.bib",
  "cited_by": 0,
  "doi": "10.31234/osf.io/34v5z_v1",
  "fulltext_url": null,
  "id": "4my60zx03gy8e",
  "issns": [],
  "landing_url": "https://osf.io/preprints/psyarxiv/34v5z_v1/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Assessment"
    ],
    [
      "bepress",
      "Clinical Psychology"
    ],
    [
      "bepress",
      "Social and Behavioral Sciences"
    ],
    [
      "bepress",
      "Trauma and Stress"
    ],
    [
      "openalex",
      "3203|Posttraumatic Stress Disorder Research"
    ]
  ],
  "openalex": "W7213650767",
  "pdf_url": "https://osf.io/34v5z/download",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-19",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4my60zx03gy8e.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:24:11Z",
      "native_id": "34v5z",
      "source": "osf",
      "url": "https://osf.io/preprints/psyarxiv/34v5z_v1/"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "bepress:Clinical Psychology",
      "subfield": "psychiatry"
    }
  ],
  "title": "Visual, Vocal, and Verbal Markers of PTSD: A Parallel Affective Computing Approach",
  "title_text": "Visual, Vocal, and Verbal Markers of PTSD: A Parallel Affective Computing Approach",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:11Z",
  "url": "https://research.draconitic.com/paper/4my60zx03gy8e",
  "venue": "PsyArXiv",
  "versions": []
}