在每日计算机化评估后COVID患者的认知功能的挑战
Ann-Kathrin Knak1,2, Mandy Roheger3, Antje Wulff1
1Big Data in Medicine, Department of Health Services Research, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
Studies in health technology and informatics
|August 23, 2024
概括
调查后COVID疲劳和认知功能的日常变化是具有挑战性的. 这项研究为COVID后患者的计算机认知评估提供了解决方案,使得有价值的症状轨迹研究成为可能.
科学领域:
- 神经科学是一个神经科学.
- 心理学 心理学 心理学
- 康复医学 康复医学 康复医学
背景情况:
- 后COVID条件经常涉及持续的疲劳和认知障碍,影响日常功能.
- 准确评估这些波动性症状对于了解长期康复轨迹至关重要.
- 由于COVID后症状的性质,目前的评估方法面临挑战.
研究的目的:
- 为了确定在每天对后COVID患者进行计算机化认知评估的挑战.
- 为克服这些评估挑战提出实际解决方案.
- 确定产生有关COVID后认知症状轨迹的有价值数据的可行性.
主要方法:
- 定性研究涉及与后COVID患者和临床从业人员的讨论.
- 在日常计算机化认知测试中识别和分类特定挑战.
- 开发针对参与者福祉和研究设计灵活性量身定制的建议解决方案.
主要成果:
- 在COVID后的人口中,每日计算机化认知评估的六个关键挑战被确定.
- 解决方案强调灵活的研究设计和持续的参与者福祉监测.
- 证明了对症状轨迹进行可靠数据收集的可行性.
结论:
- 通过灵活的,以参与者为中心的方法解决已识别的挑战,使日常认知评估成为可能.
- 这种方法可以为后COVID认知症状的不断变化的性质提供关键的见解.
- 使用这些适应的评估策略进行进一步的研究是有必要的.
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