跨语言跨文体检测青少年心理扭曲，为早期干预提供新方法
Signs of Struggle: Spotting Cognitive Distortions across Language and Register
- 基于荷兰青少年论坛文本，研究认知扭曲的跨语言跨文体检测
- 语言风格变化显著影响模型表现，但领域自适应方法效果最佳
- 适合心理健康监测、多语言NLP研究者参考
青少年心理健康问题日益突出，推动了对数字文本中心理困扰早期迹象的自动化检测研究。其中关键方向是识别认知扭曲——不合理的思维模式，这些模式会加剧心理困扰。早期发现有助于实现及时、低成本的干预。以往研究集中于英文临床数据，本文首次深入分析了认知扭曲检测在跨语言和跨文体场景下的泛化能力，基于荷兰青少年撰写的论坛帖子进行评估。结果表明，语言与写作风格的变化会显著影响模型性能，而领域自适应方法展现出最大潜力。
原文摘要 · Abstract (English)
Rising mental health issues among youth have increased interest in automated approaches for detecting early signs of psychological distress in digital text. One key focus is the identification of cognitive distortions, irrational thought patterns that have a role in aggravating mental distress. Early detection of these distortions may enable timely, low-cost interventions. While prior work has focused on English clinical data, we present the first in-depth study of cross-lingual and cross-register generalization of cognitive distortion detection, analyzing forum posts written by Dutch adolescents. Our findings show that while changes in language and writing style can significantly affect model performance, domain adaptation methods show the most promise.
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