心理健康状况不佳和攻击性与男性交通违法者的不良驾驶行为有关。
Poor mental health status and aggression are associated with poor driving behavior among male traffic offenders.
作者信息
Abdoli Nasrin, Farnia Vahid, Delavar Ali, Esmaeili Alirez, Dortaj Fariborz, Farrokhi Noorali, Karami Majid, Shakeri Jalal, Holsboer-Trachsler Edith, Brand Serge
机构信息
International University of Imam Reza, Mashhad, Iran ; Kermanshah University of Medical Sciences, Kermanshah, Iran.
Substance Abuse Prevention Research Center, Psychiatry Department, Kermanshah University of Medical Sciences, Kermanshah, Iran.
出版信息
Neuropsychiatr Dis Treat. 2015 Aug 11;11:2071-8. doi: 10.2147/NDT.S88835. eCollection 2015.
BACKGROUND
In Iran, traffic accidents and deaths from traffic accidents are among the highest in the world, and generally driver behavior rather than either technical failures or environmental conditions are responsible for traffic accidents. In the present study, we explored the extent to which aggressive traits, health status, and sociodemographic variables explain driving behavior among Iranian male traffic offenders.
METHOD
A total of 443 male driving offenders (mean age: M =31.40 years, standard deviation =9.56) from Kermanshah (Iran) took part in the study. Participants completed a questionnaire booklet covering sociodemographic variables, traits of aggression, health status, and driving behavior.
RESULTS
Poor health status, such as symptoms of depression, anxiety, insomnia, and social dysfunction, and also higher levels of trait aggression explained poor driving behavior. Multiple regressions indicated that poor health status, but not aggression, independently predicted poor driving behavior.
CONCLUSION
Results suggest that health status concerns are associated with poor driving behavior. Prevention and intervention might therefore focus on drivers reporting poor mental health status.
背景
在伊朗，交通事故及交通事故死亡率位居世界前列，一般而言，交通事故是由驾驶员行为而非技术故障或环境状况导致的。在本研究中，我们探讨了攻击特质、健康状况和社会人口统计学变量在多大程度上能够解释伊朗男性交通违法者的驾驶行为。
方法
来自伊朗克尔曼沙赫的443名男性驾驶违法者（平均年龄：M = 31.40岁，标准差 = 9.56）参与了本研究。参与者完成了一本问卷手册，内容涵盖社会人口统计学变量、攻击特质、健康状况和驾驶行为。
结果
健康状况不佳，如抑郁、焦虑、失眠和社会功能障碍症状，以及较高水平的特质攻击，都解释了不良驾驶行为。多元回归表明，健康状况不佳而非攻击行为能够独立预测不良驾驶行为。
结论
结果表明，健康状况问题与不良驾驶行为有关。因此，预防和干预可能应聚焦于心理健康状况不佳的驾驶员。
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