在慢性腰痛患者的演讲中发现情绪和网络动态
Felipe J J Reis1, Igor da Silva Bonfim2, Leticia Amaral Corrêa3
1Physical Therapy Department, Instituto Federal do Rio de Janeiro (IFRJ), Rio de Janeiro, RJ, Brazil; Pain in Motion Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education & Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium.
患有慢性腰部疼痛的患者在讨论诊断时经常表达负面情绪. 情感分析显示,疼痛程度,残疾和情绪表达之间没有显著的联系,尽管教育与话语复杂性相关.
科学领域:
- 计算语言学计算语言学
- 自然语言处理自然语言处理.
- 心理语言学 心理语言学
背景情况:
- 计算语言学为患者的感知和语言提供了洞察力.
- 了解患者的言论对于管理慢性疾病,如腰部疼痛至关重要.
研究的目的:
- 通过情绪分析 (SA) 和网络分析,分析慢性腰部疼痛患者的言论.
- 与SA和网络分析指标相关联患者的个人资料,疼痛强度和残疾.
- 根据语言和SA使用机器学习识别患者集群.
主要方法:
- 从慢性非特异性腰部疼痛患者的定性数据的二次分析.
- 使用Valence Aware词典和sEntiment Reasoner (VADER) 的情感分析.
- 使用语音图和K-means集群进行网络分析,用于无监督学习.
主要成果:
- 大多数参与者 (72%) 在他们的话语中表现出负面情绪.
- 在疼痛强度,残疾和SA或网络分析之间没有发现显著的相关性.
- 高等教育水平与单词数 (WC) 和最大强度连接组件 (LSC) 有正相关.
结论:
- 患有慢性腰部疼痛的患者在描述诊断时倾向于表达负面情绪.
- 疼痛强度和残疾水平与情绪或网络分析结果没有相关性.
- 教育水平与患者话语中更复杂的语言使用有关.
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