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：移动设备能力对日常生活日益重要，包括提供医疗服务。人机交互在认知神经学和衰老研究中具有潜在价值。尽管传统纸笔评估作为人口规模认知评估的公共卫生策略中的有效工具，数字设备可能增强认知评估。然而，即使是针对个人的研究也常未能纳入移动设备能力测量，而基于数字移动技术的研究经常忽视这些评估。此外，作为脑健康评估基础部分及识别认知障碍和痴呆高风险个体的广泛接受策略，认知筛查在针对老年人的数字设备研究中存在标准化需求。为解决这一不足，DigiTAU协作跨学科项目正在创建用于数字生物标志物研究的精细方法论参数。通过审慎考虑认知设计要素，本文描述了基于开放源代码的性能测试——移动设备能力测试（MDAT），这是一个简单、低成本、可重复的开源测试框架。该成果基于一项横断面研究，样本包括101名来自中低收入背景、年龄20至79岁的受试者。采用偏最小二乘结构方程模型（PLS-SEM）评估构建效度。我们成功建立了一种具有内部一致性的可靠方法，该方法在与数字能力相关的内容效度方面表现良好，且对自评整体功能残疾、健康自我感知及运动灵活性干扰较小。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路径。