PDF(Pubmed)
Abstract：
BACKGROUND: Suicide has emerged as a critical public health concern during the COVID-19 pandemic. With social distancing measures in place, social media has become a significant platform for individuals expressing suicidal thoughts and behaviors. However, existing studies on suicide using social media data often overlook the diversity among users and the temporal dynamics of suicide risk.
OBJECTIVE: By examining the variations in post volume trajectories among users on the r/SuicideWatch subreddit during the COVID-19 pandemic, this study aims to investigate the heterogeneous patterns of change in suicide risk to help identify social media users at high risk of suicide. We also characterized their linguistic features before and during the pandemic.
METHODS: We collected and analyzed post data every 6 months from March 2019 to August 2022 for users on the r/SuicideWatch subreddit (N=6163). A growth-based trajectory model was then used to investigate the trajectories of post volume to identify patterns of change in suicide risk during the pandemic. Trends in linguistic features within posts were also charted and compared, and linguistic markers were identified across the trajectory groups using regression analysis.
RESULTS: We identified 2 distinct trajectories of post volume among r/SuicideWatch subreddit users. A small proportion of users (744/6163, 12.07%) was labeled as having a high risk of suicide, showing a sharp and lasting increase in post volume during the pandemic. By contrast, most users (5419/6163, 87.93%) were categorized as being at low risk of suicide, with a consistently low and mild increase in post volume during the pandemic. In terms of the frequency of most linguistic features, both groups showed increases at the initial stage of the pandemic. Subsequently, the rising trend continued in the high-risk group before declining, while the low-risk group showed an immediate decrease. One year after the pandemic outbreak, the 2 groups exhibited differences in their use of words related to the categories of personal pronouns; affective, social, cognitive, and biological processes; drives; relativity; time orientations; and personal concerns. In particular, the high-risk group was discriminant in using words related to anger (odds ratio [OR] 3.23, P<.001), sadness (OR 3.23, P<.001), health (OR 2.56, P=.005), achievement (OR 1.67, P=.049), motion (OR 4.17, P<.001), future focus (OR 2.86, P<.001), and death (OR 4.35, P<.001) during this stage.
CONCLUSIONS: Based on the 2 identified trajectories of post volume during the pandemic, this study divided users on the r/SuicideWatch subreddit into suicide high- and low-risk groups. Our findings indicated heterogeneous patterns of change in suicide risk in response to the pandemic. The high-risk group also demonstrated distinct linguistic features. We recommend conducting real-time surveillance of suicide risk using social media data during future public health crises to provide timely support to individuals at potentially high risk of suicide.
OBJECTIVE: By examining the variations in post volume trajectories among users on the r/SuicideWatch subreddit during the COVID-19 pandemic, this study aims to investigate the heterogeneous patterns of change in suicide risk to help identify social media users at high risk of suicide. We also characterized their linguistic features before and during the pandemic.
METHODS: We collected and analyzed post data every 6 months from March 2019 to August 2022 for users on the r/SuicideWatch subreddit (N=6163). A growth-based trajectory model was then used to investigate the trajectories of post volume to identify patterns of change in suicide risk during the pandemic. Trends in linguistic features within posts were also charted and compared, and linguistic markers were identified across the trajectory groups using regression analysis.
RESULTS: We identified 2 distinct trajectories of post volume among r/SuicideWatch subreddit users. A small proportion of users (744/6163, 12.07%) was labeled as having a high risk of suicide, showing a sharp and lasting increase in post volume during the pandemic. By contrast, most users (5419/6163, 87.93%) were categorized as being at low risk of suicide, with a consistently low and mild increase in post volume during the pandemic. In terms of the frequency of most linguistic features, both groups showed increases at the initial stage of the pandemic. Subsequently, the rising trend continued in the high-risk group before declining, while the low-risk group showed an immediate decrease. One year after the pandemic outbreak, the 2 groups exhibited differences in their use of words related to the categories of personal pronouns; affective, social, cognitive, and biological processes; drives; relativity; time orientations; and personal concerns. In particular, the high-risk group was discriminant in using words related to anger (odds ratio [OR] 3.23, P<.001), sadness (OR 3.23, P<.001), health (OR 2.56, P=.005), achievement (OR 1.67, P=.049), motion (OR 4.17, P<.001), future focus (OR 2.86, P<.001), and death (OR 4.35, P<.001) during this stage.
CONCLUSIONS: Based on the 2 identified trajectories of post volume during the pandemic, this study divided users on the r/SuicideWatch subreddit into suicide high- and low-risk groups. Our findings indicated heterogeneous patterns of change in suicide risk in response to the pandemic. The high-risk group also demonstrated distinct linguistic features. We recommend conducting real-time surveillance of suicide risk using social media data during future public health crises to provide timely support to individuals at potentially high risk of suicide.
摘要：
背景：在COVID-19大流行期间，自杀已成为一个关键的公共卫生问题。有了社交距离措施，社交媒体已成为个人表达自杀想法和行为的重要平台。然而,现有的使用社交媒体数据的自杀研究通常忽略了用户之间的多样性和自杀风险的时间动态。
目标：通过检查在COVID-19大流行期间r/SuicideWatchsubreddit上用户的发布量轨迹变化，这项研究旨在调查自杀风险变化的异质性模式，以帮助识别具有高自杀风险的社交媒体用户。我们还在大流行之前和期间描述了他们的语言特征。
方法：我们从2019年3月至2022年8月每6个月为r/SuicideWatchsubreddit上的用户收集和分析帖子数据（N=6163）。然后使用基于增长的轨迹模型来研究后容量的轨迹，以识别大流行期间自杀风险的变化模式。还绘制并比较了帖子中语言特征的趋势，使用回归分析在轨迹组中识别语言标记。
结果：我们在r/SuicideWatchsubreddit用户中确定了两个不同的发布量轨迹。一小部分用户（744/6163，12.07％）被标记为具有高自杀风险，在大流行期间，员额数量急剧而持久地增加。相比之下,大多数使用者(5419/6163，87.93%)被归类为低自杀风险，大流行期间员额数量持续低且温和增加。就大多数语言特征的频率而言，两组在大流行的初始阶段都显示出增加。随后，在高风险人群中，上升趋势继续下降，而低危组显示立即下降。大流行爆发一年后，两组在使用与人称代词类别相关的单词方面表现出差异；情感，社会,认知，和生物过程；驱动器；相对性；时间取向；和个人关注。特别是,高风险组在使用与愤怒相关的词语时是有区别的(比值比[OR]3.23,P<.001),悲伤（OR3.23，P<.001），健康（OR2.56，P=0.005），成就（OR1.67，P=.049），运动（OR4.17，P<.001），未来焦点(OR2.86，P<.001)，和死亡（OR4.35，P<.001）在这个阶段。
结论：根据大流行期间确定的2个后容量轨迹，这项研究将r/SuicideWatchsubreddit上的用户分为自杀高风险和低风险人群。我们的发现表明，应对大流行的自杀风险变化的异质性模式。高危人群也表现出明显的语言特征。我们建议在未来的公共卫生危机期间使用社交媒体数据对自杀风险进行实时监测，以便为潜在自杀风险高的个人提供及时的支持。
目标：通过检查在COVID-19大流行期间r/SuicideWatchsubreddit上用户的发布量轨迹变化，这项研究旨在调查自杀风险变化的异质性模式，以帮助识别具有高自杀风险的社交媒体用户。我们还在大流行之前和期间描述了他们的语言特征。
方法：我们从2019年3月至2022年8月每6个月为r/SuicideWatchsubreddit上的用户收集和分析帖子数据（N=6163）。然后使用基于增长的轨迹模型来研究后容量的轨迹，以识别大流行期间自杀风险的变化模式。还绘制并比较了帖子中语言特征的趋势，使用回归分析在轨迹组中识别语言标记。
结果：我们在r/SuicideWatchsubreddit用户中确定了两个不同的发布量轨迹。一小部分用户（744/6163，12.07％）被标记为具有高自杀风险，在大流行期间，员额数量急剧而持久地增加。相比之下,大多数使用者(5419/6163，87.93%)被归类为低自杀风险，大流行期间员额数量持续低且温和增加。就大多数语言特征的频率而言，两组在大流行的初始阶段都显示出增加。随后，在高风险人群中，上升趋势继续下降，而低危组显示立即下降。大流行爆发一年后，两组在使用与人称代词类别相关的单词方面表现出差异；情感，社会,认知，和生物过程；驱动器；相对性；时间取向；和个人关注。特别是,高风险组在使用与愤怒相关的词语时是有区别的(比值比[OR]3.23,P<.001),悲伤（OR3.23，P<.001），健康（OR2.56，P=0.005），成就（OR1.67，P=.049），运动（OR4.17，P<.001），未来焦点(OR2.86，P<.001)，和死亡（OR4.35，P<.001）在这个阶段。
结论：根据大流行期间确定的2个后容量轨迹，这项研究将r/SuicideWatchsubreddit上的用户分为自杀高风险和低风险人群。我们的发现表明，应对大流行的自杀风险变化的异质性模式。高危人群也表现出明显的语言特征。我们建议在未来的公共卫生危机期间使用社交媒体数据对自杀风险进行实时监测，以便为潜在自杀风险高的个人提供及时的支持。
