{
  "abstract": "Background: Frailty is a multidimensional condition linked to adverse outcomes in older adults, yet most screening tools rely on in‐person assessment, limiting scalability. Automated approaches are needed for large‐scale screening.\n\nParticipants and Setting: We studied community‐dwelling older adults enrolled in the Aging Study of PyeongChang Rural Area (ASPRA), South Korea. Cohort 1 included 154 participants (mean age 77.4 years, 77.3% women) with comprehensive geriatric assessments; Cohort 2 included 1532 participants (mean age 74.9 years, 53.8% women). An additional External Cohort of 86 adults aged ≥ 90 years (mean age 92.1 years, 59.3% women) was recruited across five urban and rural sites to evaluate generalizability.\n\nMethods: We developed a rule‐based frailty classification algorithm implemented on an Interactive Voice Response (IVR) platform. Participants were contacted by automated telephone calls and categorized as robust, pre‐frail, frail, or severely frail. Validity was assessed against the 45‐item Frailty Index (FI) and other geriatric outcomes. Discriminative ability was compared with the Clinical Frailty Scale (CFS) using area under the curve (AUC) analyses.\n\nResults: IVR‐based frailty classification showed strong, graded associations with FI, disability, gait speed, SPPB, and health‐related quality of life (all p for trend < 0.01). In Cohort 1, the AUC for detecting frailty (FI ≥ 0.25) was 0.77 (95% CI, 0.69–0.85), comparable to the CFS (AUC 0.76, 95% CI, 0.67–0.85; p = 0.87). In Cohort 2, CFS scores increased consistently across IVR frailty categories in all age and gender strata (p for trend < 0.001). In the External Cohort, the FI also increased progressively across IVR categories (p for trend = 0.006), demonstrating external validity.\n\nConclusions: A fully automated IVR system is a valid and feasible tool for frailty screening in community‐dwelling older adults. Requiring no internet or human intervention, it offers a scalable solution for population‐level frailty surveillance, especially in resource‐limited settings.",
  "abstract_shown": true,
  "affiliations": [
    "Division of Geriatrics, Department of Internal Medicine Asan Medical Center, University of Ulsan College of Medicine Seoul Korea",
    "Department of Information Medicine Asan Medical Center, University of Ulsan College of Medicine Seoul Korea",
    "Department of Digital Health, SAIHST Sungkyunkwan University Seoul Korea",
    "AI Business Partnership Team, SK Telecom Seoul Korea",
    "Department of Emergency Medicine Samsung Medical Center, Sungkyunkwan University School of Medicine Seoul Korea",
    "Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University School of Medicine Seoul Korea",
    "Department of Clinical Research Design & Evaluation, SAIHST Sungkyunkwan University Seoul Korea",
    "PyeongChang Health Center and County Hospital Gangwon‐do Korea"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Sunghwan Ji"
    },
    {
      "affs": [
        0
      ],
      "name": "Geon Young Jang",
      "orcid": "0009-0006-2333-3790"
    },
    {
      "affs": [
        0
      ],
      "name": "Eunju Lee"
    },
    {
      "affs": [
        0
      ],
      "name": "Ji Yeon Baek",
      "orcid": "0000-0001-7547-8015"
    },
    {
      "affs": [
        3
      ],
      "name": "Seungryong Chong"
    },
    {
      "affs": [
        2,
        4
      ],
      "name": "Won Chul Cha"
    },
    {
      "affs": [
        5,
        6
      ],
      "name": "Juhee Cho"
    },
    {
      "affs": [
        5,
        6
      ],
      "name": "Hye Rin Choi"
    },
    {
      "affs": [
        0,
        6,
        7
      ],
      "name": "Il‐Young Jang",
      "orcid": "0000-0003-3617-3301"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0thaaz73794jt.bib",
  "cited_by": 0,
  "doi": "10.1111/jgs.70638",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13723221/",
  "id": "0thaaz73794jt",
  "issns": [
    "0002-8614",
    "1532-5415"
  ],
  "landing_url": "https://doi.org/10.1111/jgs.70638",
  "language": "en",
  "licence": "CC-BY-NC-4.0",
  "licence_label": "CC BY-NC 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Clinical Investigation"
    ],
    [
      "openalex",
      "2717|Frailty in Older Adults"
    ]
  ],
  "openalex": "W7196973778",
  "pdf_url": null,
  "pmcid": "PMC13723221",
  "pmid": "42561012",
  "published": "2026-08-06",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/0thaaz73794jt.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T12:21:52Z",
      "native_id": "PMC13723221",
      "source": "pmc",
      "url": "https://doi.org/10.1111/jgs.70638"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2717|Frailty in Older Adults",
      "subfield": "general"
    }
  ],
  "title": "Validation of an Automated Brief Frailty Screening Tool Using Interactive Voice Response in Community‐Dwelling Older Adults",
  "title_text": "Validation of an Automated Brief Frailty Screening Tool Using Interactive Voice Response in Community‐Dwelling Older Adults",
  "type": "peer-reviewed",
  "updated_at": "2026-11-04T12:21:52Z",
  "url": "https://research.draconitic.com/paper/0thaaz73794jt",
  "venue": "Journal of the American Geriatrics Society",
  "versions": []
}