一种用于认知临床研究的移动数字设备熟练度性能测试
A mobile digital device proficiency performance test for cognitive clinical research
AI总结：
针对数字认知筛查缺乏标准化、移动设备熟练度评估被忽视的问题，DigiTAU项目开发了开源的MDAT移动设备能力测试框架，经101名受试者验证具备良好信效度，为数字生物标志物研究提供方法学支撑。
摘要：
移动设备熟练度对日常生活（包括提供医疗保健服务）愈发重要。人机交互在认知神经病学与衰老研究中具备潜在价值。尽管传统纸笔评估是公共卫生策略中用于人群规模认知评估的宝贵工具，但数字设备可强化认知评估的效能。然而，即便以人为中心的研究也常常未纳入移动设备熟练度的测量指标，且数字移动技术相关研究往往忽视这类评估。除此之外，认知筛查作为脑健康评估的基础环节，也是识别易患认知障碍与痴呆的高风险人群的广泛认可策略，目前针对老年人使用数字设备开展的认知筛查研究亟需标准化。为弥补这一不足，DigiTAU（数字tau蛋白相关生物标志物研究）跨学科协作项目正在为数字生物标志物研究构建精细化的方法学参数。在审慎考量认知设计要素的基础上，本文介绍了开源的、基于性能表现的移动设备能力测试（Mobile Device Abilities Test, MDAT）——这是一套简易、低成本且可复现的开源测试框架。该研究基于一项横断面研究样本开展，样本包含101名年龄在20至79岁的中低收入受试者。研究采用偏最小二乘结构方程模型（Partial least squares structural equation modeling, PLS-SEM）评估该构念的测量效果。结果显示，该方法具备可靠性，拥有良好的内部一致性，与数字能力相关的内容效度良好，且受自我感知的整体功能障碍、健康自我感知及运动灵巧度的干扰较小。本文还讨论了该方法的局限性，并指明了改进与建立更完善标准的方向。
英文摘要：
Mobile device proficiency is increasingly important for everyday living, including to deliver healthcare services. Human-device interactions represent a potential in cognitive neurology and aging research. Although traditional pen-and-paper evaluations serve as valuable tools within public health strategies for population-scale cognitive assessments, digital devices could amplify cognitive assessment. However, even person-centered studies often fail to incorporate measures of mobile device proficiency and research with digital mobile technology frequently neglects these evaluations. Besides that, cognitive screening, a fundamental part of brain health evaluation and a widely accepted strategy to identify high-risk individuals vulnerable to cognitive impairment and dementia, has research using digital devices for older adults in need for standardization. To address this shortfall, the DigiTAU collaborative and interdisciplinary project is creating refined methodological parameters for the investigation of digital biomarkers. With careful consideration of cognitive design elements, here we describe the open-source and performance-based Mobile Device Abilities Test (MDAT), a simple, low-cost, and reproductible open-sourced test framework. This result was achieved with a cross-sectional study population sample of 101 low and middle-income subjects aged 20 to 79 years old. Partial least squares structural equation modeling (PLS-SEM) was used to assess the measurement of the construct. It was possible to achieve a reliable method with internal consistency, good content validity related to digital competences, and that does not have much interference with auto-perceived global functional disability, health self-perception, and motor dexterity. Limitations for this method are discussed and paths to improve and establish better standards are highlighted.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
