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短信能否实时识别自杀风险?一项关于自杀风险时间敏感标志物的受试者内初步检验。

Can Text Messages Identify Suicide Risk in Real Time? A Within-Subjects Pilot Examination of Temporally Sensitive Markers of Suicide Risk.

作者信息

Glenn Jeffrey J, Nobles Alicia L, Barnes Laura E, Teachman Bethany A

机构信息

University of Virginia.

Durham Veterans Affairs Health Care System.

出版信息

Clin Psychol Sci. 2020 Jul;8(4):704-722. doi: 10.1177/2167702620906146. Epub 2020 May 28.

DOI:10.1177/2167702620906146
PMID:35692890
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9186807/
Abstract

Objective tools to assess suicide risk are needed to determine someone is at imminent risk. This pilot laboratory investigation utilized a within-subjects design to identify patterns in text messaging (SMS) unique to high-risk periods preceding suicide attempts. Individuals reporting a history of suicide attempt (=33) retrospectively identified past attempts and periods of lower risk (e.g., suicide ideation). Language analysis software scored 189,478 text messages to capture three psychological constructs: self-focus, sentiment, and social engagement. Mixed-effects models tested whether these constructs differed in general (means) and over time (slopes) two weeks before a suicide attempt, relative to lower-risk periods. Regarding mean differences, no language features uniquely differentiated suicide attempts from other episodes. However, when examining patterns , anger increased and positive emotion decreased to a greater extent as one approached a suicide attempt. Results suggest private electronic communication has the potential to provide real-time digital markers of suicide risk.

摘要

需要客观工具来评估自杀风险,以确定某人是否处于紧迫风险之中。这项初步实验室调查采用了受试者内设计,以识别自杀企图前高风险时期特有的短信(SMS)模式。报告有自杀企图史(n = 33)的个体回顾性地确定过去的自杀企图和低风险时期(例如自杀意念)。语言分析软件对189,478条短信进行评分,以捕捉三种心理结构:自我关注、情绪和社交参与度。混合效应模型测试了这些结构在自杀企图前两周相对于低风险时期在总体(均值)和随时间(斜率)上是否存在差异。关于均值差异,没有语言特征能将自杀企图与其他时期独特地区分开来。然而,在检查模式时,随着接近自杀企图,愤怒情绪增加,积极情绪下降的幅度更大。结果表明,私人电子通信有可能提供自杀风险的实时数字标记。

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Proc SIGCHI Conf Hum Factor Comput Syst. 2016 May;2016:2098-2110. doi: 10.1145/2858036.2858207.
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Gaining insights from social media language: Methodologies and challenges.从社交媒体语言中获得洞见:方法与挑战。
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Psychol Med. 2025 May 9;55:e144. doi: 10.1017/S0033291725001199.
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