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Updated: May 25, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Using informant reports to detect cognitive decline in mild cognitive impairment
Ruby S M Tsang1, Keri Diamond, Loren Mowszowski
1Ageing Brain Centre, Brain & Mind Research Institute, University of Sydney, Sydney, NSW, Australia.
Informants can detect early cognitive changes in individuals with mild cognitive impairment (MCI) using rating scales. These ratings correlate with objective neuropsychological test results, aiding in early screening for dementia risk.
Area of Science:
- Gerontology
- Neuropsychology
- Cognitive Science
Background:
- Early detection of dementia is crucial for intervention.
- Informant ratings can provide valuable insights into cognitive changes in older adults.
- Mild cognitive impairment (MCI) is a risk factor for dementia.
Purpose of the Study:
- To evaluate if informants detect greater cognitive change in patients with MCI compared to cognitively intact individuals.
- To determine the relationship between informant ratings of cognitive change and neuropsychological performance.
Main Methods:
- 109 older adults underwent clinical and neuropsychological assessments.
- Informants completed the Cambridge Behavioral Inventory-Revised (CBI-R).
- Participants were classified as MCI (amnestic/non-amnestic) or cognitively intact.
Main Results:
- Informants rated MCI patients as having significantly more change in overall functioning, memory, orientation, everyday skills, and motivation.
- Informant ratings correlated with poorer performance in visual memory, verbal learning, language, and psychomotor speed.
- Non-amnestic MCI subgroup showed more informant-rated mood changes than the amnestic subgroup.
Conclusions:
- Informants are sensitive to subtle early cognitive changes in MCI.
- Informant ratings align with objective neuropsychological performance.
- The CBI-R is a valuable tool for early screening and intervention in MCI.
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