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Mobile device proficiency is increasingly important for everyday living,including to deliver healthcare services. Human-device interactions represent apotential in cognitive neurology and aging research. Although traditionalpen-and-paper evaluations serve as valuable tools within public healthstrategies for population-scale cognitive assessments, digital devices couldamplify cognitive assessment. However, even person-centered studies often failto incorporate measures of mobile device proficiency and research with digitalmobile technology frequently neglects these evaluations. Besides that,cognitive screening, a fundamental part of brain health evaluation and a widelyaccepted strategy to identify high-risk individuals vulnerable to cognitiveimpairment and dementia, has research using digital devices for older adults inneed for standardization. To address this shortfall, the DigiTAU collaborativeand interdisciplinary project is creating refined methodological parameters forthe investigation of digital biomarkers. With careful consideration ofcognitive design elements, here we describe the open-source andperformance-based Mobile Device Abilities Test (MDAT), a simple, low-cost, andreproductible open-sourced test framework. This result was achieved with across-sectional study population sample of 101 low and middle-income subjectsaged 20 to 79 years old. Partial least squares structural equation modeling(PLS-SEM) was used to assess the measurement of the construct. It was possibleto achieve a reliable method with internal consistency, good content validityrelated to digital competences, and that does not have much interference withauto-perceived global functional disability, health self-perception, and motordexterity. Limitations for this method are discussed and paths to improve andestablish better standards are highlighted.

A mobile digital device proficiency performance test for cognitive clinical research