METHODS: We systematically searched 12 online databases for qualitative studies exploring the experiences of older adults aged 60 years and above on their decision to self-regulate their driving. Thematic synthesis was performed to identify elements influencing driving reduction and cessation. The confidence profile of each findings from the meta-synthesis was appraised using the Confidence in the Evidence from Reviews of Qualitative research (CERQual) tool.
RESULTS: A total of 17 studies representing views of 712 older adults from four countries were included. Three major themes were identified with each representing a transition phase that can either facilitate or hinder older drivers from ceasing completely or reducing their driving, when transitioning from pre-decision phase to post-cessation phase.
CONCLUSIONS: Our findings suggest that there is a mismatch between the current traffic collation prevention measures, such as age-specific mandatory license renewal system and travel needs of older adults. As such, it is time for the authorities, researchers, and public from various fields and perspectives to collaborate, sustain, and improve safety and mobility in older adults. Practical applications: Adequate regulations and guidelines from the medical community and legal authorities are warranted to assist older adults and caregivers. Social support (e.g., feedback, assurance, or transportation support) from family members, friends, and healthcare professionals are crucial for a smooth transition. Provision of alternative transportations in rural areas are needed and future interventions should focus on engaging and educating older adults to consider alternative transportation modes for mobility. Age-specific mandatory license renewal procedure can be useful in screening for at-risk groups.
METHOD: This paper aims to develop a sustainable pedestrian gap crossing index model based on traffic flow density. It focusses on the gaps accepted by pedestrians and their decision for street crossing, where (Log-Gap) logarithm of accepted gaps was used to optimize the result of a model for gap crossing behavior. Through a review of extant literature, 15 influential variables were extracted for further empirical analysis. Subsequently, data from the observation at an uncontrolled mid-block in Jalan Ampang in Kuala Lumpur, Malaysia was gathered and Multiple Linear Regression (MLR) and Binary Logit Model (BLM) techniques were employed to analyze the results.
RESULTS AND CONCLUSIONS: From the results, different pedestrian behavioral characteristics were considered for a minimum gap size model, out of which only a few (four) variables could explain the pedestrian road crossing behavior while the remaining variables have an insignificant effect. Among the different variables, age, rolling gap, vehicle type, and crossing were the most influential variables. The study concludes that pedestrians' decision to cross the street depends on the pedestrian age, rolling gap, vehicle type, and size of traffic gap before crossing.
PRACTICAL APPLICATIONS: The inferences from these models will be useful to increase pedestrian safety and performance evaluation of uncontrolled midblock road crossings in developing countries.