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自然语言情绪作为抑郁和焦虑症状的指标:一个纵向混合方法研究1
Izabela Kaźmierczak1, Adrianna Jakubowska1, Agnieszka Pietraszkiewicz2
1Institute of Psychology, Maria Grzegorzewska University, Warsaw, Poland.
Cognition & emotion
|May 13, 2024
概括
总的来说,消极词语的使用强烈预测了抑郁和焦虑的增加,而积极的词语稍微减少了症状. 随着时间的推移,词语使用的变化影响较小.
科学领域:
- 心理学 心理学 心理学
- 计算语言学 计算语言学
- 数字精神病学数字精神病学
背景情况:
- 情绪的语言表达与心理健康有关.
- 自然语言处理 (NLP) 为心理健康评估提供了潜在的工具.
研究的目的:
- 调查自然语言中积极和消极词语使用与抑郁和焦虑症状的严重程度之间的关联.
- 检查随着时间的推移,单词价值的变化如何影响抑郁和非抑郁个体的症状严重程度.
主要方法:
- 一项纵向混合方法研究,40名参与者在一年内提供了1440个叙述.
- 用三个测量点来跟踪症状严重程度和语言使用.
- 分析的重点是单词价值的人与人之间的影响和人与人之间的影响.
主要成果:
- 总体上,更高的负值词的使用与抑郁症和焦虑症症状严重程度的增加密切相关.
- 总体上,较高的正值词的使用与症状严重程度的降低略有相关.
- 随着时间的推移,词语使用的变化 (人与人之间) 并没有显著影响症状严重程度.
结论:
- 积极和消极的词语使用的总体频率,特别是消极的,是精神病理症状严重程度的重要指标.
- 对语言价值的NLP分析显示,对诊断和监测抑郁症和焦虑症有很大的希望.
- 这项研究强调了整体语言情绪对症状严重程度的动态变化的重要性.
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