Sara Naderpour, Seyed Taghi Heydari, Kamran Bagheri Lankarani, Seyed Abbas Motevalian
{"title":"社会人口特征、骑车行为和摩托车碰撞事故：结构方程模型法。","authors":"Sara Naderpour, Seyed Taghi Heydari, Kamran Bagheri Lankarani, Seyed Abbas Motevalian","doi":"10.5249/jivr.v15i1.1784","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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 preventing 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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 frequency 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 safety violation (-0.01).</p><p><strong>Conclusions: </strong>This study's main finding is that age and riding frequency are the main variables indirectly affecting crash involvement. Therefore, periodic training courses for younger riders is essential in order to decreasing crash involvements.</p>","PeriodicalId":73795,"journal":{"name":"Journal of injury & violence research","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369328/pdf/","citationCount":"0","resultStr":"{\"title\":\"Sociodemographic characteristics, riding behavior and motorcycle crash involvement: a structural equation modeling approach.\",\"authors\":\"Sara Naderpour, Seyed Taghi Heydari, Kamran Bagheri Lankarani, Seyed Abbas Motevalian\",\"doi\":\"10.5249/jivr.v15i1.1784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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 preventing 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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 frequency 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 safety violation (-0.01).</p><p><strong>Conclusions: </strong>This study's main finding is that age and riding frequency are the main variables indirectly affecting crash involvement. Therefore, periodic training courses for younger riders is essential in order to decreasing crash involvements.</p>\",\"PeriodicalId\":73795,\"journal\":{\"name\":\"Journal of injury & violence research\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369328/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of injury & violence research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5249/jivr.v15i1.1784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of injury & violence research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5249/jivr.v15i1.1784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 preventing 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 frequency 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 safety violation (-0.01).
Conclusions: This study's main finding is that age and riding frequency are the main variables indirectly affecting crash involvement. Therefore, periodic training courses for younger riders is essential in order to decreasing crash involvements.
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