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列车自杀行为及其与位置的关系。

Behavioral and location-related antecedents of train suicides.

机构信息

Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Johann Christian Senckenberg Distinguished Professorship, Department for Psychiatry, Psychosomatics and Psychotherapy, Goethe University Frankfurt am Main, Frankfurt am Main, Germany.

出版信息

Suicide Life Threat Behav. 2023 Apr;53(2):303-311. doi: 10.1111/sltb.12941. Epub 2023 Jan 30.

DOI:10.1111/sltb.12941
PMID:36714989
Abstract

BACKGROUND

In the European Union, over 2000 suicides on railway premises were reported in 2020. Identifying individuals' behavioral and location patterns just before they die or attempt to die by train suicide (ITS) is critical for effective prevention of suicides by train. We conducted a naturalistic study using a newly developed instrument for the assessment of fatalities in rail traffic that used information from on-site video cameras.

METHODS

A total of 56 case files and surveillance recordings of ITS prior to their suicide or suicide attempt were compared to 46 surveillance recordings of matched regular train passengers (RTP) before they boarded their trains. Groups were compared on individuals' behavior as well as location and contextual parameters.

RESULTS

ITS performed unusual movement patterns more frequently, carried luggage less often, stayed on the platform longer, and let more trains pass relative to RTP.

CONCLUSIONS

If this study is replicated with a larger sample, artificial intelligence could be used to detect suspicious/unusual (movement) patterns in order to prevent train suicide. Social awareness campaigns that foster the identification of people in distress at train stations in combination with lower thresholds for the use of emergency devices on platforms may help to detect potential train suicides and reduce their incidence.

摘要

背景

2020 年,欧盟报告称,有 2000 多起在铁路场所发生的自杀事件。识别个人在自杀或企图自杀前的行为和位置模式,对于有效预防火车自杀至关重要。我们使用一种新开发的评估铁路交通中死亡的工具进行了一项自然主义研究,该工具使用了现场摄像机的信息。

方法

将 56 例自杀或企图自杀前的 ITS 案例档案和监视录像与 46 例乘坐火车前的匹配普通列车乘客(RTP)的监视录像进行了比较。比较了两组人员的行为以及位置和环境参数。

结果

ITS 更频繁地表现出异常的运动模式,携带行李的频率较低,在站台上停留的时间较长,让更多的火车通过。

结论

如果这项研究在更大的样本中得到复制,人工智能可以用于检测可疑/异常(运动)模式,以防止火车自杀。在火车站培养识别处于困境中的人的社会意识运动,并结合降低平台上紧急设备使用的门槛,可能有助于发现潜在的火车自杀者并降低其发生率。

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