负面和积极的身体相关的情绪来自语音录音在厌食症和 Bulimia Nervosa 的镜子任务:使用 RoBERTa 的自然语言处理方法
Linda Marie Sadowski1, Christopher Lalk2, Vanessa Hofschröer1
1Institute of Psychology, Department of Clinical Psychology and Psychotherapy, Osnabrück University, Osnabrück, Germany.
The International journal of eating disorders
|November 26, 2025
概括
患有饮食障碍的女性在镜子里看到自己时会经历更多的负面情绪,比如厌恶和不那么积极的情绪. 厌恶特别预测了饮食障碍症状的严重程度,这表明干预措施应该培养积极的情绪.
科学领域:
- 心理学 心理学 心理学
- 临床心理学 临床心理学
- 医疗保健中的人工智能
背景情况:
- 身体不满与各种情绪有关,但饮食障碍 (ED) 人群的自我报告限制需要客观措施.
- 自然语言处理 (NLP) 为分析语音内容提供了一个有希望的途径,以了解EDS患者的情绪.
研究的目的:
- 利用人工智能 (AI) 和NLP来识别ED的女性在镜子曝光时表达的特定身体相关情绪.
- 为了比较厌食症 (AN), Bulimia Nervosa (BN) 和健康对照的女性之间的情绪表达.
主要方法:
- 132名女性 (24名AN,36名BN,72名健康) 接受了为期3分钟的镜子曝光任务,表达情绪.
- 音频录音被转录并使用GermanEmotions AI模型进行分析,以检测28种不同的情绪.
- 统计分析 (ANOVA) 确定了群体差异,回归分析探索了ED症状严重程度的情绪预测.
主要成果:
- 与健康对照组相比,患有AN和BN的女性报告了显著更多的负面情绪 (例如,厌恶,悲伤,恐惧) 和显著更少的积极情绪 (例如,快乐,自豪,佩).
- 在所有组中,更高水平的厌恶表达是增加饮食障碍症状严重程度的重要预测因素.
- 消极和减少积极情绪的特定模式将ED组与对照组区分开来.
结论:
- 与身体相关的独特情绪概况是AN和BN的女性的特征.
- 对于ED患者的身体不满的干预措施可能更有效,如果它们专注于培养积极的情绪,同时减少消极的情绪.
- 人工智能驱动的情绪分析为患有饮食障碍的人的情绪体验提供了宝贵的见解.
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