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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cognitive function and unsafe driving acts during an on-road test among community-dwelling older adults with
Ryo Hotta1, Hyuma Makizako1,2, Takehiko Doi1
1Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, Obu, Japan.
Aim:
To examine the relationship between cognitive function and unsafe driving acts among community-dwelling older adults with cognitive impairments.
Methods:
Participants (n = 160) were older residents of Obu, Japan, aged ≥65 years with cognitive impairments. They regularly drove and were assessed for the number of unsafe driving acts without adequate verification during an on-road test. We also evaluated cognitive function (attention, executive function and processing speed). Other examined variables included demographics, driving characteristics and visual condition.
Results:
Participants were classified into two groups according to the number of unsafe driving acts as follows: high group (≥4 unsafe driving acts) and low group (≤3 unsafe driving acts). The high group participants were older in age (P < 0.001) and obtained a lower score on the symbol digit substitution task (P = 0.002) than the low group. The number of unsafe driving acts showed modest significant positive correlations with age (r = 0.396, P < 0.001). The symbol digit substitution task score was significantly associated with the number of unsafe driving acts (β = -0.196, P < 0.05) after adjusting for age group.
Conclusions:
Processing speed was associated with unsafe driving acts that became worse with increasing age. Future study will be required to longitudinally examine the influence of processing speed on traffic accidents for those with cognitive impairments. Geriatr Gerontol Int 2018; 18: 847-852.
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