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.

翻译：移动设备熟练度对日常生活日益重要，包括医疗服务的提供。人机交互为认知神经学和衰老研究提供了潜在的研究途径。尽管传统的纸笔评估作为公共卫生策略中人群规模认知评估的宝贵工具，但数字设备可以增强认知评估。然而，即使是以人为中心的研究也常常未能纳入移动设备熟练度的测量，而使用数字移动技术的研究也经常忽视这些评估。此外，认知筛查作为脑健康评估的基本组成部分，以及识别易受认知障碍和痴呆影响的高风险个体的广泛接受策略，针对老年人使用数字设备的研究需要标准化。为了解决这一不足，DigiTAU协作和跨学科项目正在为数字生物标志物的研究创建精细的方法学参数。通过仔细考虑认知设计元素，本文描述了基于表现的开源移动设备能力测试（MDAT），这是一个简单、低成本且可重复的开源测试框架。这一成果是通过对101名年龄在20至79岁之间的中低收入受试者进行横断面研究样本实现的。采用偏最小二乘结构方程模型（PLS-SEM）来评估构念的测量。该方法实现了具有内部一致性的可靠方法，与数字能力相关的内容效度良好，并且对自我感知的整体功能障碍、健康自我感知和运动灵巧性的干扰不大。本文讨论了该方法的局限性，并强调了改进和建立更好标准的途径。