在精神病发作之前,期间和之后的基于语音的自然语言概况:集群分析
Tyler C Dalal1, Liangbing Liang2, Angelica M Silva2
1Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Acta psychiatrica Scandinavica
|April 10, 2024
概括
自然语言处理 (NLP) 在早期和成熟的精神分裂症中揭示了不同的语音模式. 这些语言概况有助于区分精神病的阶段,并识别正式的思维障碍.
科学领域:
- 计算语言学计算语言学
- 精神病学神经科学 精神病学神经科学
- 临床心理学 临床心理学
背景情况:
- 语音标记提供了与社会功能相关的神经认知过程的可量化的见解.
- 在历史上,语言和沟通的"怪异性"被认为是精神分裂症的核心特征.
- 自然语言处理 (NLP) 可以检测语音样本中的微妙语言偏差.
研究的目的:
- 确定NLP衍生语言概况是否可以在不同临床阶段区分精神分裂症.
- 调查NLP在识别精神病中的"正式思维障碍"中的实用性.
主要方法:
- 分析了来自147名参与者的语音样本 (39名健康对照,72名第一发精神病,18名临床高风险,18名精神分裂症).
- 从3分钟的结构化演讲任务中量化了12个语言变量 (词汇,语法,语义).
- 使用基于健康变异的集群分析来识别基于语言的子组.
主要成果:
- 一个三集群解决方案出现了:一个典型的语言概况 (TLP) 与大多数健康的对照和患者,一个早期阶段概况 (EPP) 与高语义相似性和更少的感知词,和一个稳定的阶段概况 (SPP) 与更多的感知,但更少的认知/情感词.
- 欧洲人民党集群主要包括早期精神病患者,其特点是凝聚力和分析结构较低.
- 该SPP集群包括了更成熟的精神分裂症患者,表现出更简单的语法和减少对先前信息的引用.
结论:
- 在早期和已确定的精神分裂症阶段之间存在明显的语言偏差模式.
- 对词汇,语义和语法特征的NLP分析可以区分这些阶段.
- 这些发现支持NLP在评估精神病范围内的"形式思维障碍"时的使用.
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