Norman Hilary, Marzano Lisa, Fields Bob, Brown Sophie, MacDonald Hart Steven, Kruger Ian
Department of Psychology, Goldsmiths, University of London, UK.
Faculty of Science and Technology, Middlesex University, UK.
J Affect Disord. 2024 Jun 1;354:397-407. doi: 10.1016/j.jad.2024.03.020. Epub 2024 Mar 8.
Around 4 % of all suicide deaths in Great Britain occur on the railways. This exploratory study was designed to increase understanding of the individuals that take their lives in this way, and the circumstances of their death.
Data were obtained from fatality investigation files compiled by the British Transport Police (BTP) relating to suspected suicides on the mainline railway in England from April 2019 to March 2021. Cluster analysis was carried out to identify grouped associations of characteristics and circumstances relating to rail suicide.
A total of 436 files were analysed, representing 93 % of all suspected railway suicides during this period. Cluster analysis identified four groups of almost equal size, distinguished principally by age, living arrangements, employment status and location of death. The study is novel in the way it integrates individual characteristics and circumstances of death. The identified clusters may provide a multidimensional way of conceptualising suicide risk that could inform more targeted interventions at rail locations.
A high proportion of missing data means that the findings need to be interpreted with caution. It also restricted the multivariate analysis to those categories of information for which sufficient information was available.
The characteristics and circumstances of suicide deaths on the railways are complex and multifaceted. The typology identified in this study may help to target preventative strategies prior to the incident as well as at different location types.
在英国，约4%的自杀死亡事件发生在铁路上。这项探索性研究旨在增进对以这种方式自杀的个体及其死亡情况的了解。
数据来自英国交通警察（BTP）编制的死亡调查档案，涉及2019年4月至2021年3月期间英格兰铁路主干线的疑似自杀事件。进行聚类分析以确定与铁路自杀相关的特征和情况的分组关联。
共分析了436份档案，占该期间所有疑似铁路自杀事件的93%。聚类分析确定了四组规模几乎相等的人群，主要区别在于年龄、生活安排、就业状况和死亡地点。该研究在整合个体特征和死亡情况的方式上具有创新性。所确定的聚类可能提供一种多维的方式来概念化自杀风险，可为铁路沿线更有针对性的干预措施提供参考。
高比例的缺失数据意味着研究结果需要谨慎解读。这也将多变量分析限制在有足够信息的信息类别上。
铁路自杀死亡的特征和情况复杂且多面。本研究确定的类型学可能有助于在事件发生前以及不同地点类型实施预防策略。
