利用EMA调查中的语言嵌入来预测中风幸存者对社会隔离的看法
medRxiv : the preprint server for health sciences
|August 12, 2025
概括
这项研究引入了一种使用语言嵌入来预测中风幸存者的感知社会隔离 (PSI) 的新方法. 该方法准确地识别PSI,改善情绪健康监测和个性化护理.
科学领域:
- 神经科学是一个神经科学.
- 心理学 心理学 心理学
- 计算机科学 计算机科学
背景情况:
- 感知到的社会隔离 (PSI) 对中风幸存者的情感福祉产生了负面影响.
- 生态瞬间评估 (EMA) 用于识别PSI前体.
- 目前使用手工制作的特征的预测方法缺乏语义深度.
研究的目的:
- 开发一种用于预测中风幸存者的PSI的新方法.
- 为了利用语言嵌入来处理结构化EMA数据.
- 改善对心理社会结果的实时监测.
主要方法:
- 从218名中风幸存者中收集了11,802个EMA调查.
- 从EMA调查中提取语言嵌入,使用预先训练的模型.
- 训练了一个自动编码器用于潜伏表示和PSI预测.
主要成果:
- 实现了准确的PSI预测,加权F1得分为0.84和AUPRC为0.92.
- 在预测准确度方面表现优于传统的手工制品.
- 仅使用三个选定的问题证明了优化的有效性和可用性.
结论:
- 拟议的语言嵌入方法为中风幸存者实时PSI监测提供了一种有效的方法.
- 这种方法增强了早期干预和个性化护理策略.
- 这项研究强调了NLP在理解和管理中风后的社会心理健康方面的潜力.
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