MATERIALS AND METHODS: This qualitative descriptive study was conducted amongst married older adults aged 60 years and above. All interview responses were transcribed verbatim and examined using thematic approach and interpretative description method.
RESULTS: A total of 11 married couples were interviewed. Three major themes emerged: [1] Our roles in driving; [2] Challenges to continue driving; and, [3] Our driving strategies to ensure continued driving. Older couples adopted driving strategies and regulated their driving patterns to ensure they continued to drive safely. Male partners often took the active driving role as the principal drivers, while the females adopted a more passive role, including being the passenger to accompany the principal drivers or becoming the co-driver to help in navigation. Other coping strategies include sharing the driving duties as well as using public transportation or mixed mode transportation.
DISCUSSION: Our findings suggest spouse play a significant role in their partners' decision to self-regulate driving. This underscores a need to recognise the importance of interdependency amongst couples and its impact on their driving decisions and outcomes.
METHODOLOGY: The test was conducted for two different road conditions, tarmac and dirt roads. HAV exposure was measured using a Brüel & Kjær Type 3649 vibration analyzer, which is capable of recording HAV exposures from steering wheels. The data was analyzed using I-kaz Vibro to determine the HAV values in relation to varying speeds of a truck and to determine the degree of data scattering for HAV data signals.
RESULTS: Based on the results obtained, HAV experienced by drivers can be determined using the daily vibration exposure A(8), I-kaz Vibro coefficient (Ƶ(v)(∞)), and the I-kaz Vibro display. The I-kaz Vibro displays also showed greater scatterings, indicating that the values of Ƶ(v)(∞) and A(8) were increasing. Prediction of HAV exposure was done using the developed regression model and graphical representations of Ƶ(v)(∞). The results of the regression model showed that Ƶ(v)(∞) increased when the vehicle speed and HAV exposure increased.
DISCUSSION: For model validation, predicted and measured noise exposures were compared, and high coefficient of correlation (R(2)) values were obtained, indicating that good agreement was obtained between them. By using the developed regression model, we can easily predict HAV exposure from steering wheels for HAV exposure monitoring.