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临床表现 临床表现

Paul W H Brewster1, Diane M Jacobs2, Nicole D Anderson3,4

  • 1University of Victoria, Victoria, BC, Canada.

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概括
此摘要是机器生成的。

大脑健康支持计划的数字认知评估显示了与传统方法相似的基线结果,但随着时间的推移揭示了微妙的改进和生活方式的关联. 这些发现支持用于痴呆症风险降低研究的数字工具.

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科学领域:

  • 神经科学是一个神经科学.
  • 老年学是一门学科.
  • 数字健康数字健康

背景情况:

  • CAN-THUMBS-UP大脑健康支持计划 (BHP) 是一项为期一年的基于网络的研究,专注于降低痴呆风险.
  • 它结合了两个数字认知评估:Cogniciti的大脑健康评估 (BHA) 和基于智能手机的MyCogHealth.
  • 这些与传统的神经心理学电池 (NTB) 进行了比较,以获得探索性结果.

研究的目的:

  • 将新的数字认知评估方法 (BHA,MyCogHealth) 与传统的神经心理学电池 (NTB) 进行比较.
  • 通过使用不同的评估频率来调查基线关联和认知的纵向变化.
  • 在痴呆症风险降低框架内探索认知与生活方式的关联.

主要方法:

  • 重复测量混合模型 (MMRM) 分析了来自NTB,BHA和MyCogHealth的全球复合物,根据年龄,性别,教育和认知状态进行调整.
  • 结构方程建模 (双增长模型) 研究了认知 (BHA,MyCogHealth) 和生活方式之间的合变化.
  • 生活方式复合和时间被建模为时间变化的共变量.

主要成果:

  • 在所有测量方法中,基线认知与年龄,教育和认知状态显著相关.
  • 虽然BHA保持稳定,但MyCogHealth随着时间的推移显著改善,受年龄和教育的影响.
  • 生活方式组合与MyCogHealth拦截和改进有关,但没有观察到它们的变化率的合变化.

结论:

  • 数字认知评估显示了与NTB可比的基线关联.
  • 数字工具的测量频率增加揭示了微妙的认知改善和传统方法错过的认知与生活方式的联系.
  • 数字评估是基于生活方式的痴呆症风险降低研究中的认知终点的可行,灵活的替代方案.