Dementia and geriatric cognitive disorders · 2025
Comparison of CogMate™ and the Mini-Mental State Examination: A New Tool for Assessing the Cognitive Function of Community-Dwelling Older People.
СтатьяСравнительное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Chiu Yi-Wen, Hsieh Po-Chun, Chang Kuang-Hsi, Huang Shang-Chien, Chuang Hui-Chu
Аннотация
INTRODUCTION: Cognitive decline causes disability and dependence in older people, affecting the individuals, families, and society. This study aimed to use a gamified smart test, the CogMate™ assessment, to measure the cognitive function of community-dwelling older people and compare the test with the Mini-Mental State Examination (MMSE).
METHODS: We recruited 150 older people for testing with two cognitive assessment tools, the MMSE and CogMate™. After completing data collection, we conducted descriptive and inferential statistical analyses.
RESULTS: The MMSE results showed that only 38% (n = 57) of participants had normal cognitive function and their mean brain age was 79.31 ± 9.00 years, 4.41 years more than the actual mean age. Common factors affecting both MMSE and CogMate™ tests included age, education level, marital status, and health status. The weighted kappa of the MMSE and CogMate™ scores for two categories (participants with normal and impaired cognitive function) showed moderate consistency (correlation coefficient, 0.522) and the Pearson product-moment correlation coefficient showed moderately significant positive correlation (r = 0.480). The CogMate™ brain age and difference in brain age test results showed moderately significant negative correlation with the MMSE results. Receiver operator character curve analysis using the MMSE for validation yielded an area under the curve value of 0.736, showing that the CogMate™ tool had good cognitive function prediction results.
CONCLUSION: CogMate™ is an interesting and simple gamified tool that demonstrates moderate consistency with the MMSE. It can replace the MMSE as a community cognitive screening tool, help community care centers, and identify older people with potential cognitive decline early for referral to interventional medical centers.
METHODS: We recruited 150 older people for testing with two cognitive assessment tools, the MMSE and CogMate™. After completing data collection, we conducted descriptive and inferential statistical analyses.
RESULTS: The MMSE results showed that only 38% (n = 57) of participants had normal cognitive function and their mean brain age was 79.31 ± 9.00 years, 4.41 years more than the actual mean age. Common factors affecting both MMSE and CogMate™ tests included age, education level, marital status, and health status. The weighted kappa of the MMSE and CogMate™ scores for two categories (participants with normal and impaired cognitive function) showed moderate consistency (correlation coefficient, 0.522) and the Pearson product-moment correlation coefficient showed moderately significant positive correlation (r = 0.480). The CogMate™ brain age and difference in brain age test results showed moderately significant negative correlation with the MMSE results. Receiver operator character curve analysis using the MMSE for validation yielded an area under the curve value of 0.736, showing that the CogMate™ tool had good cognitive function prediction results.
CONCLUSION: CogMate™ is an interesting and simple gamified tool that demonstrates moderate consistency with the MMSE. It can replace the MMSE as a community cognitive screening tool, help community care centers, and identify older people with potential cognitive decline early for referral to interventional medical centers.