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自主管理语音语言治疗中的量化剂量:在现实世界移动健康数据集中探索累积干预强度的组件
Claire Cordella1, Swathi Kiran1
1Department of Speech, Language & Hearing Sciences, Boston University, MA.
American journal of speech-language pathology
|April 4, 2024
概括
这项研究表明,可以从移动健康数据计算累积干预强度 (CII) 参数,用于在家进行语音语言治疗 (SLT). 会议频率为患者的实践模式提供了独特的见解.
科学领域:
- 语音语言病理学 语言病理学
- 数字健康数字健康
- 康复科学是康复的科学.
背景情况:
- 累积干预强度 (CII) 是一个在受控环境中量化语音语言治疗 (SLT) 剂量的框架.
- 它对使用现实数据的在家自主管理SLT的适用性尚不清楚.
研究的目的:
- 调查应用CII参数来描述自主管理的SLT实践模式的可行性.
- 检查CII参数之间的相互关系.
- 根据使用移动健康数据的实践模式识别患者子组.
主要方法:
- 使用Constant Therapy应用程序对2,223名中风后幸存者的匿名数据进行分析.
- 在三个月内计算四个CII参数 (剂量,会话频率,会话持续时间,总干预时间).
- 相关性分析和k-平均分类以确定实践模式子组.
主要成果:
- CII组件可以从自主管理SLT的商业应用程序使用数据中计算出来.
- 虽然相关,但会话频率提供了不同的剂量信息.
- 聚类揭示了实践模式,根据实践的数量和频率进行区分.
结论:
- 计算CII提供了对家庭SLT实践习惯的全面了解.
- 这项研究是迈向自主管理SLT中可靠剂量报告的基本步骤.
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