Clustering Suicide Attempters

社会心理的 自杀未遂 星团(航天器) 心理学 临床心理学 自杀行为 自杀预防 毒物控制 医学 精神科 医疗急救 计算机科学 程序设计语言
作者
Jorge López‐Castromán,Erika Nogué,Sébastien Guillaume,Marie Christine Picot,Philippe Courtet
出处
期刊:The Journal of Clinical Psychiatry [Physicians Postgraduate Press, Inc.]
卷期号:77 (06): e711-e718 被引量:35
标识
DOI:10.4088/jcp.15m09882
摘要

Article Abstract Background: Attempts to predict suicidal behavior within high-risk populations have so far shown insufficient accuracy. Although several psychosocial and clinical features have been consistently associated with suicide attempts, investigations of latent structure in well-characterized populations of suicide attempters are lacking. Methods: We analyzed a sample of 1,009 hospitalized suicide attempters that were recruited between 1999 and 2012. Eleven clinically relevant items related to the characteristics of suicidal behavior were submitted to a Hierarchical Ascendant Classification. Phenotypic profiles were compared between the resulting clusters. A decisional tree was constructed to facilitate the differentiation of individuals classified within the first 2 clusters. Results: Most individuals were included in a cluster characterized by less lethal means and planning ("impulse-ambivalent"). A second cluster featured more carefully planned attempts ("well-planned"), more alcohol or drug use before the attempt, and more precautions to avoid interruptions. Finally, a small, third cluster included individuals reporting more attempts ("frequent"), more often serious or violent attempts, and an earlier age at first attempt. Differences across clusters by demographic and clinical characteristics were also found, particularly with the third cluster whose participants had experienced high levels of childhood abuse. Conclusions: Cluster analysis consistently supported 3 distinct clusters of individuals with specific features in their suicidal behaviors and phenotypic profiles that could help clinicians to better focus prevention strategies.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
数学情缘发布了新的文献求助10
刚刚
zismooo完成签到,获得积分10
1秒前
1秒前
LkKidmo完成签到,获得积分10
1秒前
星河zp发布了新的文献求助10
1秒前
cgg发布了新的文献求助10
2秒前
程贝贝发布了新的文献求助10
2秒前
3秒前
3秒前
wanghq完成签到,获得积分10
3秒前
4秒前
白小黑完成签到,获得积分0
5秒前
Xu发布了新的文献求助10
5秒前
虚拟的饼干完成签到,获得积分10
5秒前
5秒前
数学情缘完成签到,获得积分10
6秒前
7秒前
7秒前
syy关闭了syy文献求助
8秒前
yanhuazi发布了新的文献求助10
8秒前
111发布了新的文献求助10
8秒前
李健应助星河zp采纳,获得10
9秒前
阿九发布了新的文献求助10
11秒前
cyn0762完成签到 ,获得积分10
12秒前
13秒前
13秒前
白天完成签到,获得积分10
13秒前
悲凉的老虎完成签到,获得积分10
14秒前
CipherSage应助niche9964采纳,获得10
14秒前
林林发布了新的文献求助10
15秒前
复杂雁桃关注了科研通微信公众号
15秒前
16秒前
17秒前
zz发布了新的文献求助10
18秒前
18秒前
陪你闯荡发布了新的文献求助10
19秒前
ff关注了科研通微信公众号
20秒前
红柚发布了新的文献求助30
21秒前
杨然完成签到 ,获得积分10
22秒前
莫弈花茶发布了新的文献求助10
22秒前
高分求助中
Evolution 10000
Sustainability in Tides Chemistry 2800
юрские динозавры восточного забайкалья 800
Diagnostic immunohistochemistry : theranostic and genomic applications 6th Edition 500
Chen Hansheng: China’s Last Romantic Revolutionary 500
China's Relations With Japan 1945-83: The Role of Liao Chengzhi 400
Classics in Total Synthesis IV 400
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3150244
求助须知:如何正确求助?哪些是违规求助? 2801374
关于积分的说明 7844178
捐赠科研通 2458888
什么是DOI,文献DOI怎么找? 1308710
科研通“疑难数据库(出版商)”最低求助积分说明 628562
版权声明 601721