预测社会焦虑障碍认知行为治疗的结果:贝叶斯网络分析
Emily Rogerson1, Mel Simmonds-Buckley2, Stephen Kellett3
1University of Sheffield, UK.
Journal of anxiety disorders
|February 1, 2026
概括
在治疗前识别关键的社会焦虑障碍 (SAD) 症状,例如害怕尬,可以预测认知行为疗法 (CBT) 的反应. 针对这些特定的SAD症状可能会提高CBT的有效性.
科学领域:
- 精神病学是一个精神病学.
- 临床心理学 临床心理学
- 数据科学数据科学数据科学
背景情况:
- 在社会焦虑障碍 (SAD) 中预测治疗反应对于优化认知行为疗法 (CBT) 至关重要.
- 识别特定的治疗前症状预测因素可以提高SAD患者的治疗结果.
研究的目的:
- 在接受CBT治疗SAD的患者中,识别与治疗后结果相关的治疗前社会焦虑症状.
- 根据症状概况,开发治疗反应的预测模型.
主要方法:
- 一项追溯的队列研究,对1315名SAD患者进行CBT治疗.
- 使用训练样本 (n=658) 开发了贝叶斯网络模型,并在测试样本 (n=657) 上进行了验证.
- 变量选择使用了10倍的交叉验证,并使用接收器操作特征曲线 (AUC) 下的面积来评估预测准确性.
主要成果:
- 预测模型显示出适度的样本外准确性 (AUC = 0.58),与训练表现相比收缩6.76% (AUC = 0.67).
- 四个关键的相互关联的SAD症状成为重要的预测因素:避免公开演讲,害怕尬,避免批评和害怕被观察.
- 这些确定的症状使用社会恐惧症清单 (SPIN) 进行了测量.
结论:
- 在基线确定的特定社会焦虑症状与CBT的治疗反应有关.
- 在CBT评估和干预期间针对这些关键症状可以提高社会焦虑障碍的治疗效率和有效性.
- 这些发现支持基于症状概况的SADCBT更个性化的方法.
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