验证计算机生成的语言风格匹配和适应在患者-临床医生沟通中的语言风格匹配和适应的措施
Salar Khaleghzadegan1, Michael Rosen2, Anne Links3
1Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, Baltimore, MD, USA; The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA.
Patient education and counseling
|December 9, 2023
概括
临床医生在访问期间调整他们的沟通风格以与患者相匹配,可能会改善患者的感知. 语言风格匹配 (LSM) 的计算机分析显示了实时反的前景.
科学领域:
- 医学沟通 医学沟通
- 计算语言学 计算语言学
背景情况:
- 患者与临床医生的沟通显著影响医疗保健结果.
- 语言风格匹配 (Linguistic Style Matching,简称LSM) 是一种沟通策略,在这种策略中,个人会调整自己的语音模式,使其与对话伙伴保持一致.
- 通信模式的自动化分析为客观评估提供了潜力.
研究的目的:
- 评估计算机分析的语言风格匹配 (LSM) 在评估患者-临床医生沟通中的有效性.
- 确定使用文本分析软件量化的LSM是否与患者对沟通相似性的感知相关.
主要方法:
- 利用330个转录的艾滋病毒患者遇到的情况进行分析.
- 雇佣的语言调查和词汇计数 (LIWC) 软件来量化单词的使用情况.
- 开发并测试了三个LSM指标:整体访问,逐步转换和滚动窗口方法.
主要成果:
- 在静态的LSM测量 (全访,轮回,滚动窗口) 和患者评级的语音相似性之间没有发现显著的关联.
- 在增加LSM轨迹 (从访问开始到结束) 和更高的患者评级语音相似性 (β = 0.35) 之间观察到显著的积极关联.
结论:
- 临床医生沟通风格的动态适应,在整个访问期间与患者相匹配,与患者对相似性的感知有所改善有关.
- 基于计算机的语言分析有潜力成为一种有效的工具,可以实时反沟通模式.
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