{
  "abstract": "Introduction: Supervision in psychological intervention training is limited by the time needed to evaluate simulated sessions. We tested a Vision Language Model (VLM) and Large Language Model (LLM) pipeline that assesses competency from verbal and nonverbal communication. Method: Gemini-3.1-Pro was used to annotate behaviors in 25 simulated therapy videos and incorporate them into transcripts, and ChatGPT-6.1-Sol rated them against the ENACT scale. Two clinicians verified VLM-identified behaviors and four independently rated each video. Agreement was estimated with Gwet's AC1 and ICC. Results: Of 1,558 VLM-identified behaviors, 70% were confirmed by both clinicians and 93% by at least one. AI-clinician agreement on therapeutic behavior attributes (AC1=0.73, 95% CI 0.70-0.76) approached between-clinician agreement (0.75, 0.72-0.78). AI-clinician ICCs on therapeutic domain levels (median 0.57) were modestly lower than between-clinician ICCs (0.67). Discussion: The pipeline agreed with clinicians nearly as well as clinicians agreed with each other and shows promise as a supplementary evaluator in therapist training.",
  "abstract_shown": true,
  "affiliations": [
    "Nationwide Children's Hospital"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "name": "Y. Liu"
    },
    {
      "name": "W. Leever"
    },
    {
      "name": "M. Stanco"
    },
    {
      "name": "Z. Shook"
    },
    {
      "name": "P. Addico"
    },
    {
      "name": "S. Gleeson"
    },
    {
      "name": "F. Nugroho"
    },
    {
      "name": "G. Varney"
    },
    {
      "name": "E. Youngstrom"
    },
    {
      "affs": [
        0
      ],
      "name": "E. Sezgin"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8e7rnm8wwa7rf.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.11.02.26367108",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.11.02.26367108v1.full",
  "id": "8e7rnm8wwa7rf",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.11.02.26367108v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "health systems and quality improvement"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.11.02.26367108v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-02",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8e7rnm8wwa7rf.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T00:21:05Z",
      "native_id": "10.64898/2026.11.02.26367108",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.11.02.26367108v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:health systems and quality improvement",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Using Vision and Large Language Models for Psychological Intervention Competency Assessment: A Pilot Study of Agreement with Clinician Ratings",
  "title_text": "Using Vision and Large Language Models for Psychological Intervention Competency Assessment: A Pilot Study of Agreement with Clinician Ratings",
  "type": "preprint",
  "updated_at": "2026-11-05T00:20:37Z",
  "url": "https://research.draconitic.com/paper/8e7rnm8wwa7rf",
  "venue": "medRxiv",
  "versions": []
}