2026-04-17T23:12:41Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/90162024-05-20T07:20:10Zcom_10259_9006com_10259_5086com_10259_2604com_10259_5501col_10259_9007col_10259_5502

Boulagouas, Wafa García Herrero, Susana Chaib, Rachid Febres Eguiguren, Juan Diego Mariscal Saldaña, Miguel Ángel Djebabra, Mébarek 2024-04-22T10:50:06Z 2024-04-22T10:50:06Z 2020-09 1660-4601 http://hdl.handle.net/10259/9016 10.3390/ijerph17186743 1660-4601 Road traffic plays a vital role in countries’ economic growth and future development. However, traffic accidents are considered a major public health issue affecting humankind. Despite efforts by governments to improve traffic safety, the misalignment between the policy efforts and on-ground infringements, distractions and breaches reflect the regulatory failure. This paper uses the Bayesian network method to investigate unsafe behaviors and traffic accidents involving unlicensed drivers as a perspective for the regulatory alignment assessment. The findings suggest that: (1) unlicensed drivers are more likely to have unsafe driving behaviors; (2) the probability of being involved in a severe traffic accident increases when the drivers are unlicensed and decreases in the case of licensed drivers; (3) young drivers are noticeably more likely to engage in unsafe behaviors, usually leading to serious injuries and deaths, when their driving licenses are invalid; (4) women are more likely to engage in right-of-way violations and to have collisions with no serious injuries, contrary to unlicensed men drivers, who are involved in other types of traffic accidents resulting in serious injuries. eng http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional Alignment Regulatory Behaviors Drivers Bayesian Network Traffic Accidents Unlicensed Unsafe An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement info:eu-repo/semantics/article