在患者,普通人群,亲属和心理健康专业人员中识别跨诊断现象,使用主题建模技术
Alexis Vancappel1, Hugo Kazzi1, Hayfa Zgaya-Biau2
1Univ. Lille, ULR 4072 - PSITEC - Psychologie: Interactions Temps Émotions Cognition, Lille, France.
Frontiers in psychology
|January 22, 2026
概括
这项研究使用了主题建模来分析患者叙事,识别精神健康障碍的共同主题. 这些发现支持了跨诊断的方法,突出了共同的心理因素和心理痛苦的经验.
科学领域:
- 心理学 心理学 心理学
- 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:
- 对精神障碍的分类方法有局限性.
- 跨诊断的观点侧重于各种心理痛苦背后的共同因素.
- 这种视角检查远程因素 (环境,生物学,社会) 和心理过程.
研究的目的:
- 识别跨诊断的远端因素,心理过程和症状.
- 使用主题建模分析患者叙述,一种自然语言处理 (NLP) 技术.
- 从无结构文本中提取潜在的主题,以识别心理模式.
主要方法:
- 招募了四组参与者:患者 (N=445),普通人口 (N=570),亲属 (N=354) 和心理健康专业人员 (N=131).
- 收集关于痛苦的原因,所需的变化和治疗经验的开放式叙述.
- 应用主题建模来分析叙事和识别主题.
主要成果:
- 确定了258个主题,分为12个总体主题.
- 最突出的主题包括情绪和心理困难,家庭和社会关系以及治疗过程.
- 主题在诊断类别中显示了可比的流行率,支持跨诊断方法.
结论:
- 主题建模有效地从各种叙述中识别跨诊断因素,过程和症状.
- 这种方法验证了心理健康的跨诊断观点.
- 它提供了一种新的方法来理解跨疾病的心理痛苦.
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