背景中的急性自杀念头:通过临床抑郁样本的日记条目突出显示基于情绪的标记
Damien Lekkas1,2, Amanda C Collins3,4, Michael V Heinz3,5
1Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, 46 Centerra Parkway, Suite 300, Lebanon, 03766, NH, USA. Damien.Lekkas.GR@dartmouth.edu.
BMC psychiatry
|July 2, 2025
概括
使用自然语言处理 (NLP) 分析自杀念头 (SI) 的短期变化,可以发现不同的写作模式. 这些模式为自杀思想和行为 (STB) 的动态表达提供了新的见解.
科学领域:
- 心理健康研究 心理健康研究
- 计算语言学 计算语言学
- 精神病学是一个精神病学.
背景情况:
- 自杀思想和行为 (STB) 的可预测性仍然是一个挑战,尽管有概念上的进步.
- 自杀念头 (SI) 的动态,每小时的波动在研究中经常被忽视.
- 自然语言处理 (NLP) 为分析书面数据提供了有前途的机会,以更好地理解急性SI.
研究的目的:
- 通过生态瞬间评估 (EMA) 和NLP来调查SI的急性变化.
- 识别与不同SI轨迹相关的语言特征.
- 开发一个框架来分析和量化急性SI.
主要方法:
- 利用了来自268名患有严重抑郁症 (MDD) 的参与者的EMA数据.
- 收集每天三次的SI严重性得分 (MPHQ-9) 和自由形式的日记文本.
- 定义了11种急性SI阶段轨迹类型,并使用SEANCE工具对语言特征分析了5938个轨迹.
主要成果:
- 确定了SI轨迹组之间的131个统计学上显著的对差异,涉及31个NLP特征.
- 证实了个人代名词的使用,被动性和负价值与高SI相关.
- 发现了与短期SI变化相关的多言多语,敌意,愤怒和愉快的新鲜细微差别.
结论:
- 开发了一个可访问的框架,使用EMA和NLP来描述急性SI轨迹.
- 使用MPHQ第9项的已知的局限性,这可能会高估SI.
- 强调了短时间框架对于揭示微妙的SI表达信号的重要性.
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