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Cognitive Development During Adulthood01:30

Cognitive Development During Adulthood

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Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
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Updated: Jan 9, 2026

A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills
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在社区居住的老年人中进行基于人工智能的计算机化数字警测试:开发和验证研究

Gong-Hong Lin1, Dorothy Bai2, Yi-Jing Huang3,4

  • 1International Ph.D. Program in Gerontology and Long-Term Care, College of Nursing, Taipei Medical University, Taipei, Taiwan.

JMIR medical informatics
|December 2, 2025
PubMed
概括

这项研究为老年人引入了人工智能计算机化数字警觉测试 (AI-CDVT),增强持续注意力评估. AI-CDVT显示出良好的有效性和可靠性,提供比传统方法更全面的评估.

关键词:
年龄友好型的年龄友好型.人工智能的人工智能是人工智能.评估评估的评估评估的评估.关注注意力注意力注意力注意力认知 认知 认知

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科学领域:

  • 老年学是一门学科.
  • 认知神经科学 认知神经科学
  • 人工智能的人工智能

背景情况:

  • 标准的计算机化数字警测试 (CDVT) 通过反应时间和准确度来测量持续的注意力.
  • 然而,它忽略了关键的注意力指标,如眼,打哈欠和头/眼动.
  • 这种限制可能会导致对持续注意力的不完全评估.

研究的目的:

  • 开发一种基于人工智能 (AI) 的计算机化数字警测试 (AI-CDVT),专为老年人量身定制.
  • 通过结合额外的行为特征来提高持续注意力的评估.
  • 为了验证AI-CDVT在老年人群中的表现.

主要方法:

  • 使用OpenFace AI软件分析了接受CDVT的参与者的视频录像,以提取面部和头部运动数据.
  • 一个基于人工智能的评分模型是使用极端梯度增强回归器开发的.
  • 对AI-CDVT的有效性进行了对既有认知测试 (MoCA,SCW,CTT) 的评估,并使用类内相关系数 (ICC) 确定了其测试-重新测试可靠性.

主要成果:

  • 人工智能-CDVT与已建立的认知指标显示了中等到良好的相关性:皮尔森r值范围从-0.42到0.61.
  • 人工智能-CDVT的测试-重新测试可靠性被发现是良好的,其类内相关系数 (ICC) 为0.78.
  • 该研究包括153名参与者,为分析提供了强大的样本.

结论:

  • 成功开发了一种AI-CDVT,整合了人工智能驱动的视频记录行为的分析,以获得全面的注意力得分.
  • AI-CDVT显示出有希望的有效性和测试重复测试可靠性,用于评估老年人的持续注意力.
  • 与传统方法相比,这种人工智能增强的工具提供了更完整,更准确的持续注意力测量方法.