Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 1 h ago
Peer-reviewedCC BY-NC 4.0Journal of the American Geriatrics Society

Validation of an Automated Brief Frailty Screening Tool Using Interactive Voice Response in Community‐Dwelling Older Adults

  • Sunghwan Ji1,2,3
  • Geon Young Jang1
  • Eunju Lee1
  • Ji Yeon Baek1
  • Seungryong Chong4
  • Won Chul Cha3,5
  • Juhee Cho6,7
  • Hye Rin Choi6,7
  • Il‐Young Jang1,7,8
8 affiliations
  1. 1Division of Geriatrics, Department of Internal Medicine Asan Medical Center, University of Ulsan College of Medicine Seoul Korea
  2. 2Department of Information Medicine Asan Medical Center, University of Ulsan College of Medicine Seoul Korea
  3. 3Department of Digital Health, SAIHST Sungkyunkwan University Seoul Korea
  4. 4AI Business Partnership Team, SK Telecom Seoul Korea
  5. 5Department of Emergency Medicine Samsung Medical Center, Sungkyunkwan University School of Medicine Seoul Korea
  6. 6Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University School of Medicine Seoul Korea
  7. 7Department of Clinical Research Design & Evaluation, SAIHST Sungkyunkwan University Seoul Korea
  8. 8PyeongChang Health Center and County Hospital Gangwon‐do Korea
Read full textDOICite

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.

Participants 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Related

  1. Development and Validation of a Point-of-Care Triage Scorecard to Enhance Tuberculosis Case Detection During Active Community Screening in Yogyakarta, Indonesia
    D. Catrianiningsih, F. Felisia, A. S. Abdalla +5
    medRxivPreprintCC BYFull textInfectious diseasemedRxiv
  2. Performance Assessment of an Artificial Intelligence System Used for Case Detection in a Large Community-based Diabetic Retinopathy Screening Program: A Retrospective Diagnostic Accuracy Validation Study.
    Maria Kristina Dg Eduardo, Junn R Pajarillo
    Acta medica PhilippinaPeer-reviewedCC BY-NC-NDFull textMedical imaging & radiologyEurope PMCPMC
  3. Validation of a two-stage automated screening pipeline for medical systematic reviews: a stratified concordance study with three independent human reviewers, using PABAK and Gwet's AC1
    E. Pirani, D. Costazza, P. P. Berti
    medRxivPreprintCC BYFull textEpidemiology & public healthmedRxiv
  4. A Semi-Automated Interactive Annotation Framework for Intraoperative Neurosurgical Ultrasound: A Proof-of-Concept Study
    R. Bertani, S. Bahadir, M. Y. Ferreira +3
    medRxivPreprintAll rights reservedFull textMedical imaging & radiologymedRxiv
  5. French validation of the short version of the ASA questionnaire: An exploration of the socio-technical imaginaries and cosmology of Socially Interactive Agent evaluation
    Vincent P. Martin, Charlotte Menard, Jean-Arthur Micoulaud-Franchi +8
    L'EncéphalePeer-reviewedPublisher termsFull textNeurosciencePsychiatry & mental healthHAL

Cite

BibTeXRIS
BibTeX
@article{ji2026validation,
  title = {{Validation of an Automated Brief Frailty Screening Tool Using Interactive Voice Response in Community‐Dwelling Older Adults}},
  author = {Sunghwan Ji and Geon Young Jang and Eunju Lee and Ji Yeon Baek and Seungryong Chong and Won Chul Cha and Juhee Cho and Hye Rin Choi and Il‐Young Jang},
  journal = {Journal of the American Geriatrics Society},
  year = {2026},
  month = aug,
  doi = {10.1111/jgs.70638},
  url = {https://doi.org/10.1111/jgs.70638},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - Validation of an Automated Brief Frailty Screening Tool Using Interactive Voice Response in Community‐Dwelling Older Adults
AU  - Sunghwan Ji
AU  - Geon Young Jang
AU  - Eunju Lee
AU  - Ji Yeon Baek
AU  - Seungryong Chong
AU  - Won Chul Cha
AU  - Juhee Cho
AU  - Hye Rin Choi
AU  - Il‐Young Jang
PY  - 2026
DA  - 2026/08/06
JO  - Journal of the American Geriatrics Society
DO  - 10.1111/jgs.70638
UR  - https://doi.org/10.1111/jgs.70638
AB  - 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.  Participants 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.  Methods: 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.  Results: 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.  Conclusions: 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.
SN  - 0002-8614
SN  - 1532-5415
ER  -