在饮食障碍治疗环境中检查会话患者记录上的情绪算法:初步研究
Sophie M Huisman1, Jannis T Kraiss1, Jan Alexander de Vos2,3
1Department of Psychology, Health and Technology, Centre for eHealth and Wellbeing Research, University of Twente, Enschede, Netherlands.
Frontiers in psychiatry
|March 28, 2024
概括
自动化情绪分析显示,在评估患者治疗笔记时,与人类评价者之间存在适度的共识,但需要进一步开发以在饮食障碍治疗中临床使用.
科学领域:
- 临床心理学 临床心理学
- 自然语言处理自然语言处理.
- 计算语言学 计算语言学
背景情况:
- 患者会话记录包含有关治疗进展的宝贵数据.
- 情感分析可以从文本中提取情感色调.
- 自动化情绪分析可能会随着时间的推移提供对患者情绪的见解.
研究的目的:
- 在饮食障碍 (ED) 治疗中调查患者会话记录上的自动情绪分析的有效性.
- 为了比较自动化情绪分析与人类评分器的性能.
主要方法:
- 分析了8名患有ED的参与者的460个患者会话记录.
- 自动化情绪分析和两个人类评价者评估了整体情绪.
- 评估者间的协议是使用类内相关性 (ICC) 和科恩的卡帕.
主要成果:
- 发现了中度的自动化-人类协议 (ICC = 0.55) 和公平的自动化-人类协议 (kappa = 0.29).
- 观察到大量的人与人之间的一致性 (kappa = 0.68).
- 自动化分析缺乏特定于饮食障碍的术语.
结论:
- 目前,自动化情绪分析在ED会话记录方面表现低于人类评级者.
- 需要进一步发展,包括纳入ED特定词汇.
- 为未来的评估,建议将患者的心情作为基准.
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