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Updated: May 6, 2026

07:40
Multi-Modal Home Sleep Monitoring in Older Adults
Published on: January 26, 2019
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开创了一个多阶段的框架,以协调跨队伍的自我报告睡眠数据
Meredith L Wallace1, Susan Redline2,3, Nina Oryshkewych4
1Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
Sleep
|May 16, 2024
概括
这项研究提供了一个框架,用于协调跨研究的自我报告的睡眠数据,创建一个聚合样本,以便更好地分析. 开发的方法成功地协调了大多数睡眠项目,改善了用于研究的数据聚合.
科学领域:
- 睡眠科学 睡眠科学
- 数据科学是数据科学.
- 流行病学 流行病学
背景情况:
- 协调和汇总跨研究的数据对于聚合分析至关重要,增强外部验证,可复制性和可通用性.
- 睡眠的多维性质给数据协调和聚合带来了重大挑战.
研究的目的:
- 描述和实施协调自我报告睡眠数据的过程.
- 为睡眠研究创建一个协调,聚合的多队列样本.
主要方法:
- 建立了一个多阶段的框架:项目编译,领域分组,项目协调和可协调性评估.
- 该过程应用于五个美国队列和一个单独的鹿特丹样本.
- 收集了190个独特的睡眠项目,并将其分组为15个领域,导致了14个协调的项目.
主要成果:
- 开发了14个协调的睡眠项目,测量了满意度,警觉度,时间,效率,持续时间,失眠和睡眠呼吸暂停.
- 在14个项目中,有13个项目表现出中度至高水平的协调性,连续数量项目显示出更高的比率.
- 描述性统计揭示了样本中一致的特征 (例如,起床时间,持续时间) 和异质的特征 (例如,上床时间,上床时间).
结论:
- 开发的过程为研究人员和队列管理员在睡眠数据协调方面提供了指导.
- 为了加强未来的协调和聚合努力,需要进一步的方法开发和更广泛的倡议,促进共同的数据元素.
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