How Can an App Help People with Disabilities Use Their Smartphone Better?

Smartphones are now part of everyday life, but for people with disabilities they don’t always unlock all their possibilities. To fill this gap, MoDAT – the Mobile Device Assessment Tool – was created, an app designed to evaluate users’ functional abilities and suggest the most accessible settings. The project followed a user‑centered approach: first, advisory committees of experts were consulted, then focus groups with people with disabilities and assistive‑technology professionals. Based on this feedback, the team built a pilot version that offers simulated tasks, such as sending messages or navigating apps. During testing, participants completed the tasks while the app recorded times, errors and difficulties. The data are then sent to a secure portal where professionals can analyze them and recommend accessibility settings or additional devices. Early results show that users find MoDAT intuitive and helpful, and assistive‑technology providers value the comprehensive view of individual needs. The next step will be to verify the tool’s psychometric validity and study the long‑term impact of personalized recommendations. In short, MoDAT aims to turn the smartphone from a simple gadget into a true ally for everyone.

MoDAT was developed following the iterative User‑Centered Design (UCD) framework, which involves cycles of design‑evaluation‑revision. Initially, an advisory committee of researchers, clinicians, and disability association representatives defined the app’s functional goals, pinpointing everyday smartphone activities (e.g., texting, map navigation, notification management). Focus groups then gathered qualitative insights on perceived barriers, interface preferences, and usage contexts. These insights guided low‑fidelity prototype creation, tested in usability sessions with real users. Collected data (completion time, error count, navigation paths) were analyzed using descriptive statistics and logistic regression models to identify the most predictive difficulty variables. The outcome is a personalized recommendation matrix, integrated into a cloud portal with end‑to‑end encryption to ensure privacy. For psychometric validation, the next study will apply confirmatory factor analysis (CFA) and test‑retest reliability on a larger sample, establishing MoDAT’s construct validity and temporal stability. Clinical impact will be assessed using functional outcome measures such as the System Usability Scale and the Quebec User Evaluation of Satisfaction with Assistive Technology. This rigorous approach aims to make MoDAT a standardized tool for mobile accessibility assessment, influencing assistive‑technology prescription and system‑setting personalization.