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YouTube上的分心驾驶:对所呈现信息的分类与定量分析

Distracted Driving on YouTube: Categorical and Quantitative Analyses of Messages Portrayed.

作者信息

Gjorgjievski Marko, Sprague Sheila, Chaudhry Harman, Ginsberg Lydia, Wang Alick, Bhandari Mohit, Ristevski Bill

机构信息

Centre for Evidence-Based Orthopaedics, McMaster University, Hamilton, ON, Canada.

Division of Orthopaedic Surgery, University of Toronto, Toronto, ON, Canada.

出版信息

JMIR Public Health Surveill. 2020 Feb 10;6(1):e14995. doi: 10.2196/14995.

Abstract

BACKGROUND

Distracted driving is a global epidemic, injuring and killing thousands of people every year. To better understand why people still engage in this dangerous behavior, we need to assess how the public gets informed about this issue. Knowing that many people use the internet as their primary source of initial research on topics of interest, we conducted an assessment of popular distracted driving videos found on YouTube.

OBJECTIVE

This study aimed to gauge the popularity of distracted driving videos and to assess the messages portrayed by classifying the content, context, and quality of the information available on YouTube.

METHODS

We conducted a search on YouTube using 5 different phrases related to distracted driving. Videos with more than 3000 views that mentioned or portrayed any aspect of distracted driving were identified, collected, and analyzed. We measured popularity by the number of videos uploaded annually and the number of views and reactions. Two independent researchers reviewed all the videos for categorical variables. Content variables included distractions; consequences; orthopedic injuries; and whether the videos were real accounts, reenactments, fictitious, funny, serious, and graphic. Context variables assessed the setting of the events in the video, and quality of information was measured by the presence of peer-reviewed studies and inclusion and referencing of statistics. Discrepancies in data collection were resolved by consensus via the coding authors. A comparative subanalysis of the 10 most viewed videos and the overall results was also done.

RESULTS

The study included a total of 788 videos for review, uploaded to YouTube from 2006 to 2018. An average of 61 videos with greater than 3000 views were uploaded each year (SD 34.6, range 3-113). All videos accumulated 223 million views, 104 million (46.50%) of them being among the 10 most viewed videos. The top 3 distractions depicted included texting, talking on the phone, and eating and/or drinking. Motor vehicle crashes (MVCs) and death were depicted in 742 (94.2%) videos, whereas 166 (21.1%) of the videos depicted injuries. Orthopedic injuries were described in 90 (11.4%) videos. Furthermore, 220 (27.9%) of the videos contained statistics, but only 27 (3.7%) videos referenced a peer-reviewed study.

CONCLUSIONS

This study demonstrates that there is a high interest in viewing distracted driving videos, and the popularity of these videos appears to be relatively stable over time on a forum that fluxes based on the current opinions of its users. The videos mostly focused on phone-related distractions, overlooking many other equally or more common forms of distracted driving. Death, which in reality is a far less common distracted driving consequence than injuries, was portrayed 1.7 times as much. Surprisingly, orthopedic injuries, which lead to a massive source of long-term disability and often result from MVCs, are vastly underrepresented.

摘要

背景

分心驾驶是一个全球性的问题,每年导致数千人伤亡。为了更好地理解为什么人们仍然会从事这种危险行为,我们需要评估公众是如何了解这个问题的。鉴于许多人将互联网作为其对感兴趣话题进行初步研究的主要来源,我们对YouTube上流行的分心驾驶视频进行了评估。

目的

本研究旨在评估分心驾驶视频的受欢迎程度,并通过对YouTube上可用信息的内容、背景和质量进行分类来评估所传达的信息。

方法

我们在YouTube上使用了5个与分心驾驶相关的不同短语进行搜索。识别、收集并分析了浏览量超过3000且提及或描绘了分心驾驶任何方面的视频。我们通过每年上传的视频数量以及浏览量和反馈数量来衡量受欢迎程度。两名独立研究人员对所有视频的分类变量进行了审查。内容变量包括分心行为;后果;骨科损伤;以及视频是否为真实记录、重演、虚构、有趣、严肃和生动的。背景变量评估了视频中事件的发生场景,信息质量通过同行评审研究的存在以及统计数据的纳入和引用情况来衡量。数据收集方面的差异通过编码作者之间的共识得到解决。还对浏览量最高的10个视频和总体结果进行了比较性子分析。

结果

该研究共纳入了788个视频进行审查,这些视频于2006年至2018年上传至YouTube。每年平均上传61个浏览量超过3000的视频(标准差34.6,范围3 - 113)。所有视频累计浏览量达2.23亿次,其中1.04亿次(46.50%)来自浏览量最高的10个视频。所描绘的前三大分心行为包括发短信、打电话以及饮食。742个(94.2%)视频描绘了机动车碰撞(MVC)和死亡,而166个(21.1%)视频描绘了受伤情况。90个(11.4%)视频描述了骨科损伤。此外,220个(27.9%)视频包含统计数据,但只有27个(3.7%)视频引用了同行评审研究。

结论

本研究表明,人们对观看分心驾驶视频兴趣浓厚,而且在一个基于用户当前观点不断变化的平台上,这些视频的受欢迎程度似乎相对稳定。这些视频大多聚焦于与手机相关的分心行为,忽略了许多其他同样或更常见的分心驾驶形式。在现实中,死亡作为分心驾驶后果远不如受伤常见,但在视频中的呈现却多了1.7倍。令人惊讶的是,导致大量长期残疾且常由MVC引发的骨科损伤在视频中的呈现严重不足。

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