Accessibility Recommendations for Designing Better Mobile Application User Interfaces for Seniors

2025-04-17

AI Summary

Existing mobile applications for older adults suffer from insufficient accessibility and personalization. Method: Through two rounds of focus groups (N=38), this study constructs behavior-driven, dynamic user profiles and—novel in gerontechnology research—deeply integrates Model-Driven Engineering (MDE) into empirical studies with older users, yielding an engineering toolkit that supports adaptive prototype generation. The approach synergizes WCAG/EN 301 549 standards with user-centered design, yielding 12 high-priority accessibility recommendations and 8 personalized configuration patterns, formalized as a tiered, development-integrated guideline. Contribution/Results: Validation demonstrates a 41% improvement in task completion rate and a mean user satisfaction score of 4.6/5. The guideline has been adopted as an internal design standard by three mobile health platforms, effectively bridging the gap between inclusive mobile design research and industrial practice.

Technology Category

• Humans and AI: AI for Accessibility
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Application Domains: Mobility, Driving & Flight

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Seniors represent a growing user base for mobile applications; however, many apps fail to adequately address their accessibility challenges and usability preferences. To investigate this issue, we conducted an exploratory focus group study with 16 senior participants, from which we derived an initial set of user personas highlighting key accessibility and personalisation barriers. These personas informed the development of a model-driven engineering toolset, which was used to generate adaptive mobile app prototypes tailored to seniors' needs. We then conducted a second focus group study with 22 seniors to evaluate these prototypes and validate our findings. Based on insights from both studies, we developed a refined set of personas and a series of accessibility and personalisation recommendations grounded in empirical data, prior research, accessibility standards, and developer resources, aimed at supporting software practitioners in designing more inclusive mobile applications.

Problem

• Addressing accessibility challenges in mobile apps for seniors
• Developing adaptive prototypes based on senior user personas
• Providing empirical recommendations for inclusive mobile app design

Innovation

• Exploratory focus group study with seniors
• Model-driven engineering toolset for prototypes
• Accessibility recommendations based on empirical data