{
  "abstract": "ObjectivesPsychomotor competency verification for emergency medical technician (EMT) candidates is set by each state and, where states approve program-verified competency, rests on programs and their local evaluators. Commercial artificial intelligence (AI) video-analysis platforms are marketed to programs, but none has been evaluated against human evaluators on EMT skills. We measured the inter-rater reliability of certified evaluators scoring identical video-recorded performances, then evaluated one platform against that baseline.\n\nMethodsFive human evaluators and one AI platform independently scored every video of three skills in a fully crossed design: cervical collar application (15 performances), bag-valve-mask ventilation (14), and medical patient assessment (15), using identical dichotomous checklists with critical-failure criteria. We computed item-level Fleiss {kappa}, Krippendorff , and Gwet AC1; absolute-agreement intraclass correlation coefficients (ICC) for percentage scores; and {kappa} for critical-failure and pass/fail decisions, for the human panel alone and with the platform as a sixth rater.\n\nResultsHuman item-level agreement was moderate on all three skills ({kappa} 0.41-0.47). Single-rater score reliability was moderate (ICC 0.54-0.69) against 0.85-0.92 for the five-rater mean. Agreement on an objective 75% threshold was moderate ({kappa} 0.54-0.57), but agreement on the recorded pass/fail decision was fair ({kappa} 0.30-0.39) and on the critical-failure determination near zero for cervical collar (0.03) and medical assessment (0.12). Platform alignment tracked rubric observability, not task complexity: correlation with the five-human mean was 0.857 for cervical collar, exceeding every human evaluator, -0.173 for bag-valve-mask, and 0.664 for medical assessment. Adding the platform improved panel reliability for cervical collar and reduced it for the others.\n\nConclusionsThe platform rated a discrete, visually observable skill as well as the panel it joined and degraded where credit depended on rates, volumes, or verbalization. Formative practice feedback and adjunct rating are defensible now; autonomous summative use is not. The human baseline is least reliable precisely where it decides outcomes.",
  "abstract_shown": true,
  "affiliations": [
    "Des Moines Area Community College"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "J. H. Otte"
    },
    {
      "name": "A. Cartagena"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/30dcbvvextc3k.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.08.26.26361437",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.08.26.26361437v1.full",
  "id": "30dcbvvextc3k",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.08.26.26361437v1",
  "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",
      "medical education"
    ],
    [
      "openalex",
      "2739|Innovations in Medical Education"
    ]
  ],
  "openalex": "W7204806104",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.08.26.26361437v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/30dcbvvextc3k.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:21Z",
      "native_id": "10.64898/2026.08.26.26361437",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.08.26.26361437v2"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2739|Innovations in Medical Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "AI Video Analysis of Psychomotor Performance in EMS Education: Agreement With Human Evaluators Across Three Skills",
  "title_text": "AI Video Analysis of Psychomotor Performance in EMS Education: Agreement With Human Evaluators Across Three Skills",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:32Z",
  "url": "https://research.draconitic.com/paper/30dcbvvextc3k",
  "venue": "medRxiv",
  "versions": []
}