Academic Journal

Early-stage Dementia and Road Hazard Perception - Can We Determine Fitness to Drive?

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Early-stage Dementia and Road Hazard Perception - Can We Determine Fitness to Drive?
Συγγραφείς: Ahmet Begde, Eef Hogervorst, Rachel Talbot, Thomas Wilcockson, Diane Gyi, Brian Fildes, Judith L. Charlton, Jennifer Oxley, Sjaan Koppel, Andrew Morris
Στοιχεία εκδότη: Elsevier BV, 2026.
Έτος έκδοσης: 2026
Περιγραφή: Driving cessation in older adults with dementia is associated with reduced independence, social isolation, and accelerated cognitive decline, yet determining fitness to drive remains challenging. This mixed-methods study investigated older adults’ hazard perception performance and their attitudes toward driving safety decisions using the walking-talking interview method. Twenty-three participants (10 with mild cognitive impairment, 13 healthy controls; mean age 77.2 years) completed several cognitive assessments (MMSE, HVLT, VST, Corsi Block Test) and an online Hazard Perception Test (HPT), before participating in a walking-talking interview exploring their preferred responses to being told they were unsafe to drive. Thematic analysis of the interviews identified six themes across 16 codes. Participants with cognitive impairment demonstrated greater acceptance of driving cessation, and sought confirmatory assessments, whereas healthy control participants prioritised transparency about test results, openness to remediation through lessons or vehicle adaptations, and preservation of independence. These findings highlight the importance of personalised interventions and the potential for non-invasive in-car technologies to support safe driving in individuals with early-stage dementia. This study highlights the value of qualitative methods in understanding the nuanced perspectives of older drivers and informs future strategies for managing driving cessation in cognitively impaired individuals.
Τύπος εγγράφου: Article
DOI: 10.2139/ssrn.6477783
Αριθμός Καταχώρησης: edsair.doi...........a7fa34789a380d7662f71fed8f0b5a5c
Βάση Δεδομένων: OpenAIRE