# A mobile digital device proficiency performance test for cognitive clinical research

**Authors:** Alan Cronemberger Andrade, Diógenes de Souza Bido, Ana Carolina Bottura de Barros, Walter Richard Boot, Paulo Henrique Ferreira Bertolucci  
**arXiv:** [2310.01774](https://arxiv.org/abs/2310.01774)  
**Date:** 2023-10-03  
**Summary page:** https://www.summarizepaper.com/en/paper/2310.01774v1/

## Key points

- Mobile device proficiency is a crucial skill in healthcare and cognitive research
- Integration of digital devices can revolutionize cognitive assessment processes
- Studies often overlook measures of mobile device proficiency, especially in older adults
- The DigiTAU project aims to establish refined methodological parameters for investigating digital biomarkers
- The Mobile Device Abilities Test (MDAT) is an open-source framework to assess digital competencies
- A recent study showed strong internal consistency and content validity of the MDAT
- Limitations exist that require further exploration for refining the MDAT framework

## Summary

In the rapidly evolving landscape of healthcare and cognitive research, mobile device proficiency has emerged as a crucial skill for individuals of all ages. The ability to effectively interact with digital devices not only enhances everyday living but also holds significant potential in the realms of cognitive neurology and aging research. While traditional pen-and-paper evaluations have long been utilized in public health strategies for population-scale cognitive assessments, the integration of digital devices could revolutionize the field by amplifying the accuracy and efficiency of cognitive assessment processes. Despite the clear advantages offered by digital technology, studies often overlook measures of mobile device proficiency, particularly in research involving older adults who may be at higher risk for cognitive impairment and dementia. To address this gap, the DigiTAU collaborative project has embarked on an interdisciplinary effort to establish refined methodological parameters for investigating digital biomarkers. Central to this initiative is the development of the Mobile Device Abilities Test (MDAT), an open-source and performance-based framework designed to assess individuals' digital competencies. In a recent study involving a diverse sample of 101 low and middle-income subjects aged 20 to 79 years old, researchers employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the reliability and validity of the MDAT. The results demonstrated that the test exhibited strong internal consistency and content validity related to digital competences, while also minimizing interference with factors such as global functional disability, health self-perception, and motor dexterity. While these findings represent a significant step forward in standardizing cognitive assessments using digital devices, there are limitations that warrant further exploration. By acknowledging these constraints and identifying opportunities for improvement, researchers can continue to refine the MDAT framework and establish best practices for leveraging mobile technology in cognitive clinical research. Ultimately, this work holds promise for enhancing our understanding of cognitive function across diverse populations and advancing personalized approaches to brain health evaluation.