Suppr超能文献

随机试验和自报告事故作为研究提高自行车骑行者安全性措施的方法——两个案例研究。

Randomized trials and self-reported accidents as a method to study safety-enhancing measures for cyclists-two case studies.

机构信息

Department of Civil Engineering, Aalborg University, Thomas Manns Vej 23, DK-9220 Aalborg OE, Denmark.

出版信息

Accid Anal Prev. 2018 May;114:17-24. doi: 10.1016/j.aap.2017.07.019. Epub 2017 Aug 1.

Abstract

A large number of studies show that high visibility in traffic is important in the struggle of getting the attention from other road users and thus an important safety factor. Cyclists have a much higher risk of being killed or injured in a traffic accident than car drivers so for them high visibility is particularly important. A number of studies have examined the effect of high visibility, such as reflective clothing, but most studies have been primitive, the data limited and the results very uncertain. In this paper we describe the safety impact of increased visibility of cyclists through two randomised controlled trials: permanent running lights on bicycles and a yellow bicycle jacket, respectively. The effect of running lights was studied through a trial where the lights were mounted to 1,845 bicycles and 2,000 others comprised a control group. The bicycle accidents were recorded every two month in a year through self-reporting on the Internet. Participants were asked to report all cycling accidents independently of severity to avoid differences between participants as regards to which accidents were reported. They reported a total of 255 accidents i.e. 7 accidents per 100 cyclists. The results showed that the incidence rate for multiparty bicycle accidents with personal injury was 47% lower for cyclists with permanent running light. The difference is statistically significant at the 5% level. The effect of a yellow bicycle jacket was examined through a trial with 6,800 volunteer cyclists. The half of the group received a bicycle jacket and the other half comprised a control group. Both groups reported every month all their bicycle accidents independently of severity on the Internet. They reported a total of 694 accidents i.e. 10 accidents per 100 cyclists. The treatment group was asked each month if they carried the jacket on their last cycling trip. The results showed that on a random day the treatment group carried the jacket or other fluorescent cycling garment on 77% of their cycle trips. The incidence rate for multiparty accidents with personal injury was 38% lower than the control group. The difference is statistically significant at the 5% level. The trials were not blind and it seems that the lack of blinding has influenced the level of the groups accident reporting. To address this bias we used a correction factor formed by the difference in the number of single accidents of the two groups. The experiences with self-reporting of accidents via a web based questionnaire sent by e-mail with one respective two month intervals were very good; in both trials more than 80% answered all questionnaires whereas less than 2% did not answer, and the quality of the self-reported accident was considered high.

摘要

大量研究表明,在争取其他道路使用者注意方面,交通中的高可见度很重要,因此是一个重要的安全因素。与汽车司机相比,骑自行车的人在交通事故中死亡或受伤的风险要高得多,因此对他们来说,高可见度尤为重要。许多研究都研究了高可见度的效果,例如反光服装,但大多数研究都很原始,数据有限,结果也非常不确定。在本文中,我们通过两项随机对照试验描述了提高自行车骑行者可见度的安全影响:自行车上的永久运行灯和黄色自行车夹克。通过一项试验研究了运行灯的效果,在该试验中,将灯安装在 1845 辆自行车上,另外 2000 辆自行车组成对照组。通过互联网自我报告,每两个月记录一次自行车事故。参与者被要求独立报告所有骑自行车事故,无论严重程度如何,以避免参与者之间报告的事故存在差异。他们共报告了 255 起事故,即每 100 名骑车人中有 7 起事故。结果表明,对于有个人伤害的多方自行车事故,使用永久运行灯的自行车事故发生率降低了 47%。差异在 5%水平上具有统计学意义。黄色自行车夹克的效果通过一项有 6800 名志愿者骑自行车的试验进行了检验。一半的组收到了自行车夹克,另一半是对照组。两组都在互联网上每月独立报告所有自行车事故,无论严重程度如何。他们共报告了 694 起事故,即每 100 名骑车人中有 10 起事故。治疗组每月都会被问到他们在上一次骑自行车旅行中是否携带了夹克。结果表明,在随机的一天,治疗组在 77%的自行车旅行中携带了夹克或其他荧光自行车服装。有个人伤害的多方事故发生率比对照组低 38%。差异在 5%水平上具有统计学意义。这些试验不是盲法的,而且似乎缺乏盲法影响了两组事故报告的水平。为了解决这个偏差,我们使用了一个由两组之间单个事故数量差异形成的校正因子。通过电子邮件发送的基于网络的问卷进行事故自我报告的经验非常好;在两项试验中,超过 80%的人回答了所有问卷,而不到 2%的人没有回答,而且自我报告的事故质量被认为很高。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验