Proactive Suicide Prevention Online (PSPO): Machine Identification and Crisis Management for Chinese Social Media Users With Suicidal Thoughts and Behaviors

社会化媒体 微博 自杀预防 鉴定(生物学) 心理学 危机管理 考试(生物学) 毒物控制 自杀未遂 应用心理学 精神科 医学 医疗急救 计算机科学 万维网 生物 古生物学 法学 植物 政治学
作者
Xingyun Liu,Xiaoqian Liu,Jiumo Sun,Nancy Xiaonan Yu,Bingli Sun,Qing Li,Tingshao Zhu
出处
期刊:Journal of Medical Internet Research 卷期号:21 (5): e11705-e11705 被引量:70
标识
DOI:10.2196/11705
摘要

Suicide is a great public health challenge. Two hundred million people attempt suicide in China annually. Existing suicide prevention programs require the help-seeking initiative of suicidal individuals, but many of them have a low motivation to seek the required help. We propose that a proactive and targeted suicide prevention strategy can prompt more people with suicidal thoughts and behaviors to seek help.The goal of the research was to test the feasibility and acceptability of Proactive Suicide Prevention Online (PSPO), a new approach based on social media that combines proactive identification of suicide-prone individuals with specialized crisis management.We first located a microblog group online. Their comments on a suicide note were analyzed by experts to provide a training set for the machine learning models for suicide identification. The best-performing model was used to automatically identify posts that suggested suicidal thoughts and behaviors. Next, a microblog direct message containing crisis management information, including measures that covered suicide-related issues, depression, help-seeking behavior and an acceptability test, was sent to users who had been identified by the model to be at risk of suicide. For those who replied to the message, trained counselors provided tailored crisis management. The Simplified Chinese Linguistic Inquiry and Word Count was also used to analyze the users' psycholinguistic texts in 1-month time slots prior to and postconsultation.A total of 27,007 comments made in April 2017 were analyzed. Among these, 2786 (10.32%) were classified as indicative of suicidal thoughts and behaviors. The performance of the detection model was good, with high precision (.86), recall (.78), F-measure (.86), and accuracy (.88). Between July 3, 2017, and July 3, 2018, we sent out a total of 24,727 direct messages to 12,486 social media users, and 5542 (44.39%) responded. Over one-third of the users who were contacted completed the questionnaires included in the direct message. Of the valid responses, 89.73% (1259/1403) reported suicidal ideation, but more than half (725/1403, 51.67%) reported that they had not sought help. The 9-Item Patient Health Questionnaire (PHQ-9) mean score was 17.40 (SD 5.98). More than two-thirds of the participants (968/1403, 69.00%) thought the PSPO approach was acceptable. Moreover, 2321 users replied to the direct message. In a comparison of the frequency of word usage in their microblog posts 1-month before and after the consultation, we found that the frequency of death-oriented words significantly declined while the frequency of future-oriented words significantly increased.The PSPO model is suitable for identifying populations that are at risk of suicide. When followed up with proactive crisis management, it may be a useful supplement to existing prevention programs because it has the potential to increase the accessibility of antisuicide information to people with suicidal thoughts and behaviors but a low motivation to seek help.
最长约 10秒,即可获得该文献文件

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
zero桥完成签到,获得积分10
1秒前
充电宝应助Ste采纳,获得10
2秒前
2秒前
4秒前
5秒前
WH发布了新的文献求助10
6秒前
背后瑾瑜发布了新的文献求助10
7秒前
9秒前
852应助不发一区不改名采纳,获得10
9秒前
10秒前
10秒前
唯有发布了新的文献求助10
10秒前
CY完成签到,获得积分10
13秒前
背后瑾瑜完成签到,获得积分10
14秒前
彭于晏应助松本润不足采纳,获得10
15秒前
香蕉觅云应助哦啦啦采纳,获得10
15秒前
CY发布了新的文献求助10
15秒前
明亮靖柔发布了新的文献求助10
16秒前
McQueen发布了新的文献求助10
18秒前
cc发布了新的文献求助10
18秒前
李N完成签到,获得积分10
20秒前
20秒前
Ade阿德发布了新的文献求助10
20秒前
20秒前
quhayley应助ok采纳,获得10
21秒前
wtg发布了新的文献求助10
26秒前
刘娇娇完成签到,获得积分10
26秒前
斯文败类应助青安采纳,获得10
26秒前
JKIKU发布了新的文献求助10
26秒前
28秒前
CipherSage应助快乐的晓刚采纳,获得10
28秒前
28秒前
dww发布了新的文献求助10
33秒前
33秒前
忙碌的数学人完成签到,获得积分10
34秒前
Ade阿德完成签到,获得积分10
34秒前
caicai完成签到,获得积分10
34秒前
35秒前
36秒前
36秒前
高分求助中
Evolution 10000
Sustainability in Tides Chemistry 2800
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
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
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 3149289
求助须知:如何正确求助?哪些是违规求助? 2800391
关于积分的说明 7839862
捐赠科研通 2457980
什么是DOI,文献DOI怎么找? 1308158
科研通“疑难数据库(出版商)”最低求助积分说明 628456
版权声明 601706