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一种基于数据科学的方法来估计美国因驾驶而停止相关自杀的频率:来自国家暴力死亡报告系统的证据。

A Data Science Approach to Estimating the Frequency of Driving Cessation Associated Suicide in the US: Evidence From the National Violent Death Reporting System.

机构信息

Rutgers-Robert Wood Johnson Medical School, Piscataway, NJ, United States.

Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States.

出版信息

Front Public Health. 2021 Aug 16;9:689967. doi: 10.3389/fpubh.2021.689967. eCollection 2021.

DOI:10.3389/fpubh.2021.689967
PMID:34485220
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8415628/
Abstract

Driving cessation is a common transition experienced by aging adults that confers both a symbolic and literal loss of independence due to the central role of automobiles for mobility in the US. Prior research has shown that driving cessation has negative implications for mental health, social participation, and access to healthcare. Given these sequelae of driving cessation and prior work showing that late-life transitions related to independence (e.g., transitioning into residential care) are associated with suicide, we sought to estimate the frequency of driving cessation associated suicide. Data include suicide ( = 59,080) and undetermined ( = 6,862) deaths aged ≥55 from the National Violent Death Reporting System (NVDRS, 2003-2017). Each case in the NVDRS has both quantitative data (e.g., demographic characteristics) and qualitative text narratives, derived from coroner/medical examiner reports, which describe the most salient circumstances and features of each death. To identify cases associated with driving cessation, we employed a supervised random forest algorithm to develop a Natural Language Processing (NLP) classifier. Identified driving cessation associated cases were then categorized and characterized using descriptive statistics and qualitative content analysis. From 2003 to 2017, there were an estimated 305 cases of suicide/undetermined deaths associated with driving cessation in the NVDRS, representing 0.04% of all cases. Cases associated with driving cessation were older, more likely to be male, more likely to have a physical health problem, more likely to have experienced a recent crisis, and more likely to have lived in a rural county than other decedents. Qualitative analysis identified functional impairment, alcohol-related driving limitations, loss of employment, and recent car accidents as common themes among cases associated with driving cessation. This analysis illustrates the utility of NLP in identifying novel correlates of suicide in later life. Although driving cessation associated suicide is a rare outcome, further research is warranted on understanding the conditions under which driving cessation is associated with suicidal behavior, and how to support the well-being of aging adults during these types of major life transitions.

摘要

停止驾驶是老年人常见的过渡阶段,由于汽车在美国机动性中的核心作用,这既带来了象征性的,也带来了字面意义上的独立性丧失。先前的研究表明,停止驾驶对心理健康、社会参与和获得医疗保健都有负面影响。考虑到停止驾驶的这些后果,以及先前的研究表明与独立性相关的晚年过渡(例如,过渡到居住护理)与自杀有关,我们试图估计与停止驾驶相关的自杀频率。数据包括国家暴力死亡报告系统(NVDRS,2003-2017 年)中年龄≥55 岁的自杀(=59080 人)和未确定原因(=6862 人)的死亡。NVDRS 中的每个案例都既有定量数据(例如人口统计学特征),也有源自验尸官/法医报告的定性文本叙述,这些叙述描述了每个死亡的最突出情况和特征。为了识别与停止驾驶相关的案例,我们使用了监督随机森林算法来开发自然语言处理(NLP)分类器。然后,使用描述性统计和定性内容分析对识别出的与停止驾驶相关的案例进行分类和特征描述。从 2003 年到 2017 年,NVDRS 中估计有 305 例与停止驾驶相关的自杀/未确定死因案例,占所有案例的 0.04%。与停止驾驶相关的案例年龄更大,更可能是男性,更可能有身体健康问题,更可能经历过近期危机,更可能居住在农村县,而不是其他死者。定性分析确定了功能障碍、与酒精相关的驾驶限制、失业和最近的车祸是与停止驾驶相关的案例中的常见主题。这项分析说明了 NLP 在识别晚年自杀新相关因素方面的作用。尽管与停止驾驶相关的自杀是一种罕见的结果,但仍有必要进一步研究了解在何种情况下停止驾驶与自杀行为相关,以及如何在这些重大生活过渡时期支持老年人的福祉。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f1e/8415628/705074538a38/fpubh-09-689967-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f1e/8415628/705074538a38/fpubh-09-689967-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f1e/8415628/705074538a38/fpubh-09-689967-g0001.jpg

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