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Updated: May 27, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Detecting Cognitive Impairment Early in Hispanic and Black Older Adults: Community Voices From South Central Texas
Robin C Hilsabeck1, Stephanie Santiago-Mejias1, Tara L Fletcher2
1Department of Neurology, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health San Antonio.
Background:
Alzheimer disease and related dementias (ADRD) are more prevalent in Black and Hispanic older adults and are also more likely to be undetected and misdiagnosed. The purpose of this study was to engage with Black and Hispanic communities about interest in and support needed for memory screening.
Methods:
Participants were recruited from established community partners of the South Texas Alzheimer's Disease Research Center to engagein a 90-minute listening session. The session was recorded with participants' permission, and a thematic analysis was conducted by 2 independent coders.
Results:
Sixteen individuals (81% female, 88% Hispanic or Black) from various perspectives participated (eg, health care workers, persons with dementia, caregivers). Four core themes emerged: building trust, access and time barriers, community-specific literature, and representative messengers. Trust was noted to be foundational, encompassing who delivers the screening and where it takes place. Transportation, time burden, competing caregiving responsibilities, work schedules, and limited access to technology/internet were key barriers. The need to create accessible and relatable literature and videos tailored to diverse educational levels and cultural backgrounds was also emphasized.
Conclusions:
Trusted members of the community could be accepted to perform memory screenings and provide education. Partnering with faith-based organizations, senior centers, and other community hubs would help overcome barriers to screening.
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