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Updated: May 21, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Illness representations in older adults with mild cognitive impairment
Feng Lin1, Carey E Gleason, Susan M Heidrich
1University of Rochester Medical Center, Rochester, NY, USA. vankee_lin@urmc.rochester.edu
Abstract:
Little is known about patients' understanding of a diagnosis of mild cognitive impairment (MCI). The purpose of this cross-sectional descriptive study was to describe beliefs about MCI in people diagnosed with the condition and examine correlates (demographic and health) of those beliefs. Thirty individuals diagnosed with MCI completed the Illness Perception Questionnaire-MCI (IPQ-MCI), measuring eight domains of beliefs about MCI, and one scale of emotional distress. Five of them also participated in a 15-minute cognitive interview to explore responses to the IPQ-MCI. Participants correctly identified symptoms related to MCI; generally attributed MCI to aging, heredity, and abnormal brain changes; and believed MCI to be chronic, predictable, and controllable, causing little emotional distress. However, there were no consistent beliefs regarding the negative consequences of MCI or whether MCI was understandable. There were few significant correlates of beliefs. People with MCI are able to report their beliefs about their illness, suggesting that misconceptions and gaps in knowledge can be identified and addressed with nursing interventions.
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