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Updated: Mar 4, 2026
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Validation of the Turkish Version of the Quick Mild Cognitive Impairment Screen
Burcu Balam Yavuz1, Hacer Dogan Varan1, Rónán O'Caoimh2,3
11 Division of Geriatric Medicine, Department of Internal Medicine, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Background:
The objective of this study was to validate the Turkish version of the Quick Mild Cognitive Impairment (Q mci-TR) screen.
Methods:
In total, 100 patients aged ≥65 years referred to a geriatric outpatient clinic with memory loss were included. The Q mci was compared to the Turkish versions of the standardized Mini-Mental State Examination and the Montreal Cognitive Assessment (MoCA).
Results:
The Q mci-TR had higher accuracy than the MoCA in discriminating subjective memory complaints (SMCs) from cognitive impairment (mild cognitive impairment [MCI] or dementia), of borderline significance after adjusting for age and education ( P = .06). The Q mci-TR also had higher accuracy than the MoCA in differentiating MCI from SMC, which became nonsignificant after adjustment ( P = .15). A similar pattern was shown for distinguishing MCI from dementia. Test reliability for the Q mci-TR was strong.
Conclusion:
The Q mci-TR is a reliable and useful screening tool for discriminating MCI from SMC and dementia in a Turkish population.
