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Updated: Apr 23, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Nurse-led cognitive screening model for older adults in primary care
Yanni Yang1, Lily Dongxia Xiao2, Lanlan Deng1
1School of Nursing, Third Military Medical University, Chongqing, China.
Aim:
The present study aimed to establish a nurse-led cognitive screening model for community-dwelling older adults with subjective memory complaints from seven communities in Chongqing, China, and report the findings of this model.
Methods:
Screenings took place from July 2012 to June 2013. Cognitive screening was incorporated into the annual health assessment for older adults with subjective memory complaints in a primary care setting. Two community nurses were trained to implement the screening using the Mini-Mental State Examination and Montreal Cognitive Assessment.
Results:
Of 733 older adults, 495 (67.5%) reported having subjective memory complaints. Of the 249 individuals who participated in the cognitive screening, 102 (41%) had mild cognitive impairment, whereas 32 (12.9%) had cognitive impairment. A total of 80 participants (78.4%) with mild cognitive impairment agreed to participate in a memory support program. Participants with cognitive impairment were referred to specialists for further examination and diagnosis; only one reported that he had seen a specialist and had been diagnosed with dementia.
Conclusions:
Incorporating cognitive screening into the annual health assessment for older adults with subjective memory complaints was feasible, though referral rates from primary care providers remained unchanged. The present study highlights the urgent need for simple screenings as well as community-based support services in primary care for older adults with cognitive or mild cognitive impairments.
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