{
  "abstract": "Objective: To quantify the documented consent outcomes for ambient monitoring technologies in an academic hospital and evaluate whether documented consent acceptance differed by age, gender, and race.\n\nPatients and methods: We performed a retrospective cross-sectional study of 9,522 consecutive patients approached for ambient monitoring consent during routine hospital care from 1/1/2025 to 2/12/2026. Consent status was categorized as received, refused, or missing/unable. The primary multivariable analysis used a binary outcome of documented acceptance (received vs. refused or missing/unable) modeled with age, gender, and race. Secondary models used age categories.\n\nResults: Overall, 9,125 patients (95.8%) consented, 184 (1.9%) refused, and 213 (2.2%) had missing or unobtainable consent. Acceptance did not differ by gender (95.6% among female patients vs. 96.1% among male patients; adjusted odds ratio [aOR] 1.11, 95% CI 0.91–1.36; p = 0.30). Compared with White patients, lower adjusted odds of acceptance were observed among Black or African American patients (aOR 0.66, 95% CI 0.49–0.88; p = 0.005) and patients categorized as Unknown/Declined/Other (aOR 0.56, 95% CI 0.37–0.83; p = 0.004). Acceptance was highest among Asian patients, but the adjusted difference was not significant (aOR 2.44, 95% CI 0.90–6.59; p = 0.079). Acceptance exceeded 95% across all age groups and was highest among patients aged 65–74 years (96.7%). Younger patients more often refused, whereas older patients more often had missing or unobtainable consent.\n\nConclusion: Documented consent acceptance was high in this single academic hospital. Acceptance did not vary by gender, but modest differences were observed by race and age-related patterns. Consent status alone does not establish patient comprehension, voluntariness, motivation, or durable endorsement. These findings demonstrate operational feasibility while underscoring the need for transparent consent, subgroup monitoring, and prospective evaluation of patient experiences.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Ambient Intelligence, Mayo Clinic, Jacksonville, FL, United States",
    "Department of Innovation, Mayo Clinic, Jacksonville, FL, United States",
    "Digital Transformation, Mayo Clinic, Jacksonville, FL, United States",
    "Department of Nursing, Mayo Clinic, Jacksonville, FL, United States",
    "Division of Pulmonary Medicine, Department of Medicine, Mayo Clinic, Jacksonville, FL, United States",
    "Department of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, United States"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Emily L. Godsey"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Taylor M. Galloway"
    },
    {
      "affs": [
        0,
        3
      ],
      "name": "Jennifer S. Crews"
    },
    {
      "affs": [
        0,
        4,
        5
      ],
      "name": "Scott A. Helgeson"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/19hr43v1e121w.bib",
  "cited_by": 0,
  "doi": "10.3389/fdgth.2026.1969218",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13732902/",
  "id": "19hr43v1e121w",
  "issns": [
    "2673-253X"
  ],
  "landing_url": "https://doi.org/10.3389/fdgth.2026.1969218",
  "language": "en",
  "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": [
    [
      "heading",
      "Original Research"
    ],
    [
      "openalex",
      "2739|Ethics and bioethics in healthcare"
    ]
  ],
  "openalex": "W7223149694",
  "pdf_url": "https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2026.1969218/pdf",
  "pmcid": "PMC13732902",
  "pmid": "42985070",
  "published": "2026-10-21",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/19hr43v1e121w.ris",
  "sources": [
    {
      "first_seen": "2026-11-08T12:22:48Z",
      "native_id": "PMC13732902",
      "source": "pmc",
      "url": "https://doi.org/10.3389/fdgth.2026.1969218"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2739|Ethics and bioethics in healthcare",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Documented patient consent for ambient video monitoring technologies in an academic hospital: a cross-sectional analysis of consent outcomes and demographic differences",
  "title_text": "Documented patient consent for ambient video monitoring technologies in an academic hospital: a cross-sectional analysis of consent outcomes and demographic differences",
  "type": "peer-reviewed",
  "updated_at": "2026-11-08T12:22:48Z",
  "url": "https://research.draconitic.com/paper/19hr43v1e121w",
  "venue": "Frontiers in Digital Health",
  "versions": []
}