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数字技术在评估认知障碍老年人跌倒风险中的性能:系统评价。

Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review.

机构信息

Programme in Health Services and Systems Research (HSSR), Duke-NUS Medical School, Singapore, Singapore.

Centre for Ageing Research and Education (CARE), Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore.

出版信息

Geroscience. 2024 Jun;46(3):2951-2975. doi: 10.1007/s11357-024-01098-z. Epub 2024 Mar 4.

Abstract

Older adults with cognitive impairment (CI) are twice as likely to fall compared to the general older adult population. Traditional fall risk assessments may not be suitable for older adults with CI due to their reliance on attention and recall. Hence, there is an interest in using objective technology-based fall risk assessment tools to assess falls within this population. This systematic review aims to evaluate the features and performance of technology-based fall risk assessment tools for older adults with CI. A systematic search was conducted across several databases such as PubMed and IEEE Xplore, resulting in the inclusion of 22 studies. Most studies focused on participants with dementia. The technologies included sensors, mobile applications, motion capture, and virtual reality. Fall risk assessments were conducted in the community, laboratory, and institutional settings; with studies incorporating continuous monitoring of older adults in everyday environments. Studies used a combination of technology-based inputs of gait parameters, socio-demographic indicators, and clinical assessments. However, many missed the opportunity to include cognitive performance inputs as predictors to fall risk. The findings of this review support the use of technology-based fall risk assessment tools for older adults with CI. Further advancements incorporating cognitive measures and additional longitudinal studies are needed to improve the effectiveness and clinical applications of these assessment tools. Additional work is also required to compare the performance of existing methods for fall risk assessment, technology-based fall risk assessments, and the combination of these approaches.

摘要

认知障碍(CI)的老年人跌倒的可能性是普通老年人群体的两倍。传统的跌倒风险评估可能不适合认知障碍的老年人,因为它们依赖于注意力和记忆力。因此,人们有兴趣使用基于客观技术的跌倒风险评估工具来评估该人群的跌倒情况。本系统评价旨在评估针对认知障碍老年人的基于技术的跌倒风险评估工具的特点和性能。我们在 PubMed 和 IEEE Xplore 等多个数据库中进行了系统搜索,共纳入了 22 项研究。大多数研究都集中在痴呆症患者上。所使用的技术包括传感器、移动应用程序、运动捕捉和虚拟现实。跌倒风险评估在社区、实验室和机构环境中进行;研究采用了在日常生活环境中对老年人进行连续监测的方法。研究使用了基于技术的步态参数、社会人口学指标和临床评估的组合。然而,许多研究都错过了将认知表现作为跌倒风险预测因素纳入的机会。本综述的结果支持使用基于技术的跌倒风险评估工具来评估认知障碍的老年人。需要进一步的改进,包括纳入认知措施和更多的纵向研究,以提高这些评估工具的有效性和临床应用。还需要开展更多的工作来比较现有的跌倒风险评估方法、基于技术的跌倒风险评估以及这些方法的组合的性能。

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