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Updated: Apr 6, 2026
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
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Embedded Online Questionnaire Measures Are Sensitive to Identifying Mild Cognitive Impairment
Adriana Seelye1, Nora Mattek, Diane B Howieson
1Departments of *Neurology‡Biomedical Engineering†Oregon Center for Aging and Technology, Oregon Health & Science University, Portland, OR.
Alzheimer Disease and Associated Disorders
|July 21, 2015
Summary
Passive monitoring of online questionnaire responses can detect early signs of mild cognitive impairment (MCI) in older adults. This method offers a promising approach for real-world cognitive assessment and early dementia detection.
Area of Science:
- Gerontology
- Neuroscience
- Digital Health
Background:
- Early detection of mild cognitive impairment (MCI) is crucial for timely dementia intervention.
- Cognitively demanding daily activities can reveal subtle functional changes preceding MCI diagnosis.
- Real-world functional changes are key indicators for early dementia detection.
Purpose of the Study:
- To determine if passive response data from a weekly online questionnaire can differentiate between older adults with and without MCI.
- To explore the utility of remote monitoring for ecologically valid cognitive assessment.
Main Methods:
- 83 community-dwelling older adults completed a weekly online questionnaire as part of a longitudinal study.
- Passive performance measures, including time to complete and submission time, were analyzed.
- Correlations between online questionnaire performance and conventional cognitive test scores were assessed.
Main Results:
- Questionnaire completion time decreased over one year for both MCI and cognitively intact participants.
- MCI participants progressively submitted questionnaires later in the day and required more assistance over one year.
- Passive online questionnaire performance measures correlated significantly with standard cognitive test scores.
Conclusions:
- Ambiently assessed, passive performance measures from online questionnaires can distinguish between normal cognition and MCI.
- Remote monitoring of routine, cognitively demanding activities shows potential for real-world cognitive assessment.
- This approach supports early detection of cognitive decline in older adults.
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