Designing Universally Accessible Telehealth Interfaces: An Empirical Study on Inclusive UX/UI for Neurodivergent and Cognitively Impaired Geriatric Patients

• Adaan Ahsun

  Covenant University

  Author

The rapid proliferation of telehealth services has created unprecedented opportunities for healthcare access, yet older adults with neurodivergent conditions and cognitive impairments remain systematically excluded due to inaccessible interface design. Despite established accessibility standards, empirical evidence on effective interface adaptations for this population is limited, and existing guidelines often fail to address the intersectional needs of geriatric users with diverse cognitive profiles. This study employed a mixed-methods design-based research approach to develop and evaluate an inclusive telehealth interface tailored for neurodivergent and cognitively impaired geriatric patients (N=127, mean age=72.3 years). A participatory design methodology was utilized, involving iterative usability testing with three participant cohorts: older adults with mild cognitive impairment (n=42), those with autism spectrum conditions (n=38), and neurotypical older adults (n=47). The proposed interface incorporated simplified navigation pathways, multimodal interaction options, personalized cognitive load adjustments, and visual accessibility features aligned with the WHO-ITU Global standard for accessible telehealth services. Quantitative evaluation demonstrated significant improvements across all cohorts, with task completion rates increasing from 47.2% (SD=14.3) on standard interfaces to 89.4% (SD=6.1) on the adapted interface (p<0.001). System Usability Scale scores improved from 43.7 to 86.2 for cognitively impaired participants. The findings demonstrate that systematic application of universal design principles, combined with personalization capabilities, can effectively bridge the accessibility gap in telehealth for vulnerable geriatric populations. This research contributes both a validated design framework and empirical evidence supporting the adoption of inclusive interface standards in digital health.

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