生命线澳大利亚在线聊天服务寻求帮助者的心理状态的变化:词汇分析方法
Kelly Mazzer1, Sonia Curll1, Hakar Barzinjy1
1Faculty of Health, University of Canberra, 11 Kirinari Street, Bruce, Canberra, 2611, Australia, 610262015266.
JMIR formative research
|June 20, 2025
概括
对危机热线聊天的词汇分析显示,痛苦和自杀倾向的显著减少,证明了其用于监测心理状态变化的可行性. 这种方法可以加强危机支持服务和结果测量.
科学领域:
- 计算语言学计算语言学
- 心理健康信息学心理健康信息学
- 情感计算是一种情感计算.
背景情况:
- 全球心理健康挑战的增加需要了解危机救援电话的有效性.
- 有限的洞察力如何危机热线帮助个人在谈话中受益.
- 情感计算具有潜力,但缺乏足够的帮助电话数据.
研究的目的:
- 探索使用词汇分析来追踪在线危机聊天交互期间寻求帮助者的心理状态的动态变化的可行性.
- 评估经过验证和特定于背景的词汇类别在表现心理状态转变中的有用性.
主要方法:
- 来自澳大利亚生命线的6618个身份不明的在线聊天记录的词汇分析.
- 利用了同情类别 (积极情绪,消极情绪,痛苦,乐观) 并开发了痛苦和自杀倾向类别.
- 采用相关性分析,跨对话阶段的ANOVA和趋势分析的回归建模.
主要成果:
- 从对话的开始到结束,观察到痛苦 (d=0.79) 和自杀倾向 (d=0.49) 的显著减少.
- 负面框架的同情类别 (痛苦,负面情绪) 也显著下降.
- 趋势分析显示,在对话窗口上,痛苦,负面情绪和自杀倾向的持续下降.
结论:
- 词汇分析是一种可行的方法,用于在线危机支持中表示和监测心理状态的变化.
- 结果表明,整合情感计算有潜力,以改善危机急救服务和结果测量.
- 未来的研究应该验证这些发现,并探索危机干预的实时应用.
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