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Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach
BACKGROUND: The increasing rate of traffic crashes involving motorcyclists have turned into a public health and road safety concern. Furthermore, riding behaviors and their precedent factors have been identified as potential determinants for assessing, intervening, and prevent-ing traffic injuries o...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Kermanshah University of Medical Sciences
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369328/ https://www.ncbi.nlm.nih.gov/pubmed/36588299 http://dx.doi.org/10.5249/jivr.v15i1.1784 |
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author | Naderpour, Sara Heydari, Seyed Taghi Bagheri Lankarani, Kamran Motevalian, Seyed Abbas |
author_facet | Naderpour, Sara Heydari, Seyed Taghi Bagheri Lankarani, Kamran Motevalian, Seyed Abbas |
author_sort | Naderpour, Sara |
collection | PubMed |
description | BACKGROUND: The increasing rate of traffic crashes involving motorcyclists have turned into a public health and road safety concern. Furthermore, riding behaviors and their precedent factors have been identified as potential determinants for assessing, intervening, and prevent-ing traffic injuries of motorists. This study aimed to identify the effects of a set of demographic and motorcycle-related variables as potential predictors on collision through riding behavior components. METHODS: The study sample was 1,611 motorcyclists who were selected through time-location sampling method from three cities in Iran. They responded a Motorcycle Rider Behavior Questionnaire (MRBQ) and a general questionnaire including sociodemographic and riding-related items. The chosen method to analyze the data was Structural Equation Modeling (SEM) through Lavaan package version 0.6-8 of R software version 4.1.0. RESULTS: All participants were male (100%) with a mean age of 28.1(SD=8.5) years. About 24.4% of riders experienced at least one crash during the last year and the majority of riders did not hold a motorcycle license (80.1%). The SEM model showed that riding license (0.06) and fre-quency of riding (0.09) had a direct effect on crash involvement. Some latent variables including speed violation (0.13), stunts (0.11) and traffic violation (0.07) had positive effects and safety violation (-0.07) had a negative effect on crash history. There were indirect effects between age and history of crash mediated by speed violation (-0.04), stunts (-0.04), traffic violation (-0.02) and safety violation (0.01). Also, the indirect effects of riding frequency on crash involvement were mediated by speed violation (0.01), traffic violation (0.006) and safe-ty violation (-0.01). CONCLUSIONS: This study’s main finding is that age and riding frequency are the main variables indirectly af-fecting crash involvement. Therefore, periodic training courses for younger riders is essential in order to decreasing crash involvements. |
format | Online Article Text |
id | pubmed-10369328 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Kermanshah University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-103693282023-07-27 Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach Naderpour, Sara Heydari, Seyed Taghi Bagheri Lankarani, Kamran Motevalian, Seyed Abbas J Inj Violence Res Injury & Violence BACKGROUND: The increasing rate of traffic crashes involving motorcyclists have turned into a public health and road safety concern. Furthermore, riding behaviors and their precedent factors have been identified as potential determinants for assessing, intervening, and prevent-ing traffic injuries of motorists. This study aimed to identify the effects of a set of demographic and motorcycle-related variables as potential predictors on collision through riding behavior components. METHODS: The study sample was 1,611 motorcyclists who were selected through time-location sampling method from three cities in Iran. They responded a Motorcycle Rider Behavior Questionnaire (MRBQ) and a general questionnaire including sociodemographic and riding-related items. The chosen method to analyze the data was Structural Equation Modeling (SEM) through Lavaan package version 0.6-8 of R software version 4.1.0. RESULTS: All participants were male (100%) with a mean age of 28.1(SD=8.5) years. About 24.4% of riders experienced at least one crash during the last year and the majority of riders did not hold a motorcycle license (80.1%). The SEM model showed that riding license (0.06) and fre-quency of riding (0.09) had a direct effect on crash involvement. Some latent variables including speed violation (0.13), stunts (0.11) and traffic violation (0.07) had positive effects and safety violation (-0.07) had a negative effect on crash history. There were indirect effects between age and history of crash mediated by speed violation (-0.04), stunts (-0.04), traffic violation (-0.02) and safety violation (0.01). Also, the indirect effects of riding frequency on crash involvement were mediated by speed violation (0.01), traffic violation (0.006) and safe-ty violation (-0.01). CONCLUSIONS: This study’s main finding is that age and riding frequency are the main variables indirectly af-fecting crash involvement. Therefore, periodic training courses for younger riders is essential in order to decreasing crash involvements. Kermanshah University of Medical Sciences 2023-01 /pmc/articles/PMC10369328/ /pubmed/36588299 http://dx.doi.org/10.5249/jivr.v15i1.1784 Text en https://creativecommons.org/licenses/by/3.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Injury & Violence Naderpour, Sara Heydari, Seyed Taghi Bagheri Lankarani, Kamran Motevalian, Seyed Abbas Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach |
title | Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach |
title_full | Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach |
title_fullStr | Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach |
title_full_unstemmed | Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach |
title_short | Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach |
title_sort | sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach |
topic | Injury & Violence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369328/ https://www.ncbi.nlm.nih.gov/pubmed/36588299 http://dx.doi.org/10.5249/jivr.v15i1.1784 |
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