Driving Cessation in Old Age: Gender Influences on Mortality

Predictors of Driving Cessation in Older Adults: A 12-year Population-based Study

BACKGROUND

Changes in physical health and cognition during aging can result in some older adults to stop driving. In this population-based longitudinal study, we describe potential predictors of driving cessation in older adults.

METHODS

Age-stratified random population cohort of 1982 adults aged 65 years and older drawn from voter registration lists. Participant characteristics were measured using demographics, physical and self-rated health, sleeping habits, driving status, cognitive screening, modified Center for Epidemiologic Studies-Depression scale, clinical dementia rating, and mini-mental state examination.

RESULTS

Over 12 years of follow-up, 390 participants stopped driving. These individuals were older, more likely to be women and to have a clinical dementia rating score ≥1, had worse self-reported health, and more symptoms of depression, compared with those who were still driving. In addition, individuals with lower test performance in all cognitive domains, loss of visual acuity and fields, and bilateral hearing loss were more likely to stop driving.

CONCLUSIONS

Age, sex, cognitive impairments, physical health, and depressive symptoms were associated with driving cessation in this cohort. By identifying potential driving cessation predictors, health care providers and families may better recognize these risk factors and begin the driving cessation discussion early.

Reliability and Validity of the Japanese Version of the Assessment of Readiness for Mobility Transition (ARMT-J) for Japanese Elderly

The Assessment of Readiness for Mobility Transition (ARMT) questionnaire assesses individuals' emotional and attitudinal readiness related to mobility as they age. This study aimed to examine the reliability and validity of the Japanese version of the ARMT (ARMT-J). The ARMT-J and related variables were administered to 173 patients and staff members undergoing rehabilitation at hospitals in Japan. Construct validity was first examined using confirmatory factor analysis (CFA) to confirm cross-cultural validity. For structural validity, the optimal number of factors was confirmed using a Velicer's minimum average partial test and parallel analysis, followed by exploratory factor analysis (EFA). Finally, a CFA was performed using the most appropriate model. Internal consistency, test-retest reliability, standard error of measurement (SEM), and smallest detectable change (SDC) were assessed for reliability. The CFA fit for the factor structure of the original ARMT was low. Therefore, the EFA was conducted with two to four factors. The optimal factor structure was three factors, with a Cronbach's alpha coefficient and Cohen's weighted kappa coefficient of 0.85 and 0.76, respectively. The intraclass correlation coefficient (ICC) of the test-retest was 0.93, the SEM was 0.72, and the SDC was 2.00. The model fit was good for the ARMT-J, with a three-factor structure.