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Almost 200 million persons with disabilities face specific difficulties in everyday life. Private vehicles provide persons with disabilities with a high level of flexibility, a high level of time efficiency, and a better quality of life. It is sometimes necessary to make vehicle modifications to enable persons with disabilities to drive. One of the most frequent modifications is hand controls. Although drivers with disabilities who use hand controls face the same risk of road accidents as non-disabled drivers, predictors of road accidents for drivers with disabilities who use hand controls have not been the subject of earlier research. The predictors show which factors influence the occurrence of road accidents of drivers with disabilities who use hand controls. This paper aims to develop a model that describes the participation in road accidents of drivers with disabilities who use hand controls and recognises contributing predictors. A multidisciplinary team of experts identified twenty-three predictors that impact road accidents of drivers with disabilities who use hand controls. Bayesian logistic regression models have identified speeding, alcohol consumption, mobile phone usage, and especially fatigue as risky behaviours. This paper proposes several important measures that would improve the safety of drivers with disabilities using hand controls.

Modelling participation in road accidents of drivers with disabilities who use hand controls