Optimizing mobile cognitive assessment reduces administration time while maintaining screening accuracy in older adults

Growing dementia prevalence underscores the need for efficient screening methods, but lengthy digital assessments often cause fatigue among older adults. To address this, we developed and validated the Digital Assessment of Cognitive Impairment (DACI), a brief mobile application designed to accurately identify cognitive impairment (CI). Initially, 304 older adults (272 healthy, 32 cognitively impaired) completed both a pencil-and-paper Cognitive Impairment Screening Test (CIST) and a full-length DACI. The best-performing CatBoost model achieved an area under the curve (AUC) of 0.813, with sensitivity of 0.903, requiring an average completion time of 321 s. Subsequent feature selection identified two essential subtests for a compact DACI. This compact version was then validated with an additional 297 participants (227 healthy, 70 cognitively impaired), achieving improved diagnostic performance (AUC = 0.871) in only 91 s. DACI effectively distinguishes cognitively impaired older adults with minimal test duration, potentially reducing fatigue and improving adherence. By providing rapid, accurate remote assessment without additional equipment, DACI may significantly enhance accessibility of cognitive screening among older adults. Future studies are warranted to validate DACI's feasibility and performance in unsupervised home settings.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-08-19
DOI
https://doi.org/10.1038/s41598-025-14130-9
Citations
1
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
1.47

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing mobile cognitive assessment reduces administration time while maintaining screening accuracy in older adults

Hyun‐Jeong Ko, Bo Ri Kim, Byung Hun Yun, Sang Kwon Lim et al.
1 citations
Scientific Reports
Dementia and Cognitive Impairment Research
1.47
article

Optimizing mobile cognitive assessment reduces administration time while maintaining screening accuracy in older adults

Hyun‐Jeong Ko, Bo Ri Kim, Byung Hun Yun, Sang Kwon Lim, Jee Hang Lee, Geon Ha Kim, Whani Kim, Soobin Park, Ui Jun Kwon, Jin‐Woo Kim, Dong Han Kim, Jin Sung Kim
article en
1 citations

Abstract

Growing dementia prevalence underscores the need for efficient screening methods, but lengthy digital assessments often cause fatigue among older adults. To address this, we developed and validated the Digital Assessment of Cognitive Impairment (DACI), a brief mobile application designed to accurately identify cognitive impairment (CI). Initially, 304 older adults (272 healthy, 32 cognitively impaired) completed both a pencil-and-paper Cognitive Impairment Screening Test (CIST) and a full-length DACI. The best-performing CatBoost model achieved an area under the curve (AUC) of 0.813, with sensitivity of 0.903, requiring an average completion time of 321 s. Subsequent feature selection identified two essential subtests for a compact DACI. This compact version was then validated with an additional 297 participants (227 healthy, 70 cognitively impaired), achieving improved diagnostic performance (AUC = 0.871) in only 91 s. DACI effectively distinguishes cognitively impaired older adults with minimal test duration, potentially reducing fatigue and improving adherence. By providing rapid, accurate remote assessment without additional equipment, DACI may significantly enhance accessibility of cognitive screening among older adults. Future studies are warranted to validate DACI's feasibility and performance in unsupervised home settings.

Scientific ReportsVol. 15(1)
Korea Institute for Advanced Study (KR), Ewha Womans University (KR), Sangmyung University (KR), Yonsei University (KR), Digital Wave (United States) (US), Ewha Womans University Medical Center (KR)
National IT Industry Promotion Agency, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 16%
Dementia and Cognitive Impairment Research
1.47
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.