Assessing the Ghanaian driver’s susceptibility to distraction engagement

Background
Driving involves multiple subtasks (e.g., route finding and following, velocity control, etc.)
performed in a constantly evolving environment. Despite this complexity, drivers often engage
in non-driving activities, such as using mobile phones or adjusting in-vehicle technology, that
take their attention and hands off crucial vehicle controls. Growing evidence shows that driver
distraction impairs driving performance and heightens the risk of traffic crashes and critical
incidents.
Aim
Understanding the reasons underlying driver distraction engagement and the susceptibility to
various distractions is necessary to develop effective distraction-mitigating countermeasures.
The study examined the forms, instances, and predictors of distraction engagement among
Ghanaian drivers to propose workable interventions.
Method
The study sampled 257 private and professional/commercial drivers via personal contacts and
social media invitations. The study utilised the Susceptibility to Driver Distraction
Questionnaire (SDDQ) and four driving scenarios to investigate the drivers' voluntary and
involuntary distraction engagement. Bivariate correlation and independent samples t-tests were
performed to investigate the associations and differences among driver types and forms of
distraction. Further, hierarchical multiple regression was used to model the predictors of
distraction engagement.
Results
The study results reveal that self-reported distraction engagement while driving has a positive
correlation with voluntary distraction and a negative correlation with involuntary distraction.
The results also show significant differences in the perceived likelihood of using mobile phones
among the different driver types in different driving contexts. Moreover, the hierarchical
regression model shows that gender, age, past mobile-phone-related crash experience, driving
context (urban road and motorway), attitude, injunctive norms, and involuntary distraction are
significant predictors of self-reported distraction engagement.
Conclusions
The study results suggest that gender, age, past mobile phone-related crash experience, driving
context, attitude, injunctive norms, and involuntary distractions predict distraction engagement,
confirms the SDDQ’s utility in predicting voluntary and involuntary distraction engagement
and highlights the importance of providing driving-based context information when studying
distraction engagement.