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Evaluation of a mobile-phone-based voice-recognition digital cognitive screener in Chinese older adults: a
Shifang Zhang1, Ran An1, Xiuxiu Huang2
1School of Nursing, Peking University, Beijing, China.
Objectives:
To evaluate a voice recognition-based digital cognitive screener (DCS) for detecting cognitive impairment in community-dwelling older adults.
Methods:
A total of 316 participants (189 with normal cognition, 117 with mild cognitive impairment, 10 with dementia) completed demographic surveys, the Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), and the DCS. Automated/manual scoring consistency and group comparisons were evaluated. Receiver operating characteristic (ROC) analysis was performed using SPSS to evaluate screening performance and determine optimal cut-off values. Executive function items from MoCA were integrated for optimization testing.
Results:
Automated DCS scores correlated strongly with manual scores (r=0.604, p<0.001) but averaged 1.64 points lower. DCS scores were significantly lower in the cognitive impairment group compared to the normal cognition group (6.77±2.16 vs. 7.92±1.97, p<0.001). Sensitivities were 0.78 for cognitive impairment and 0.80 for dementia. Executive function integration improved sensitivity.
Conclusions:
The DCS is a valid community screening tool for cognitive impairment, with optimization potential through executive function integration.
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