A Two-Part Approach Distinguishing the Occurrence and Frequency of Self-reported Attentional Failures during Driving to Predict Crash Risks among Older Drivers

Hee Sun Choi, Jing Feng, Daniel Grühn

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: With advancing age, older drivers experience greater fatal crash risks due to age-related declines in cognitive and physical capabilities. Being informed of the age-related increased risks could help older drivers form compensatory strategies and determine when to seek further help to stay on the road safely for longer. Using a self-report assessment tool, the Attentional Failure during Driving Questionnaire (AFDQ), we examined older drivers’ experience of various attentional failures during daily driving and how the measures could predict their crash risks. Methods: We used a new methodological approach distinguishing the occurrences of attentional failures during driving and the frequency of those occurrences. The individuals’ AFDQ occurrence and frequency scores were compared with prior driving outcomes and simulated driving performance. Results: Unlike middle-aged drivers, frequency rather than occurrence of attentional failures was a significant predictor of prior traffic violations and crashes among older drivers. Also, attentional failures, but not chronological age, predicted older drivers’ crash risks. AFDQ frequency was also associated with older drivers’ poorer performance in simulated driving. Discussion: The findings suggest that the self-report assessment for attention-related driving failures can predict older drivers’ crash risks. Furthermore, the two-part approach of AFDQ provides an opportunity to do a more comprehensive investigation of the associations between attentional declines and crash risks among older drivers.

Original languageEnglish
Pages (from-to)1759-1768
Number of pages10
JournalJournals of Gerontology - Series B Psychological Sciences and Social Sciences
Volume77
Issue number10
DOIs
StatePublished - Oct 1 2022

Keywords

  • Assessment
  • Attention
  • Driving
  • Safety
  • Self-report

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