DOSE:一个基于iOS手表的开源工具,用于体验采样
medRxiv : the preprint server for health sciences
|November 24, 2025
概括
研究人员创建了DOSE,这是Apple Watch体验采样方法 (ESM) 的开源框架. 这种实用工具使ESM研究能够轻松部署,在实地研究中显示出高响应率和快速交互.
科学领域:
- 数字健康数字健康
- 人与计算机的交互
- 心理学研究方法 心理学研究方法
背景情况:
- 智能手表提供适合经验采样方法 (ESM) 的低负荷微互动.
- 尽管果手表很受欢迎,但它缺乏用于ESM部署的可访问框架,这阻碍了研究.
- 现有的方法往往需要技术专业知识,限制了更广泛的采用.
研究的目的:
- 开发和评估DOSE,这是一个开源框架,用于使用Apple Watch进行ESM研究.
- 为研究人员提供无代码解决方案,用于调查配置,应用程序构建和数据部署.
- 在现实环境中评估DOSE框架的可行性和有效性.
主要方法:
- 开发了DOSE框架,这是Apple Watch ESM的开源工具包.
- 这是一项为期28天的实地研究,涉及18名参与者 (平均年龄=55.3岁).
- 评估快速交付可靠性,响应率和交互时间.
主要成果:
- DOSE证明了可靠的及时交付,并实现了超过80%的整体响应率.
- 对于ESM提示的中位相互作用时间始终在10秒以下.
- 在整个研究期间,参与者表现出更好的反应效率.
结论:
- DOSE框架是基于Apple Watch的ESM的实用和可扩展的解决方案.
- 它降低了研究人员的技术障碍,促进了基于智能手表的研究的更广泛采用.
- DOSE为推进使用智能手表的移动健康和心理研究提供了坚实的基础.
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