Abstract
The growing adoption of conversational agents offers new opportunities for delivering services through natural language, yet existing systems are rarely optimized for older adults and neurodiverse users. Cognitive aging and neurodiversity introduce challenges in processing speed, working memory, and attentional control, making voice interface design a critical factor for accessibility and wellbeing. This study investigates how interaction strategy (direct, step-by-step, selective) and speech rate (slow vs. normal) affect chatbot usability. Drawing on theories of cognitive load and inclusive design, we propose a research model in which cognitive load and perceived usability mediate the effects of design factors on task performance (accessibility outcome) and sense of autonomy (wellbeing outcome). Preliminary findings suggest that slower speech and segmented responses improve both performance and autonomy compared to dense, one-shot delivery. The study advances understanding of inclusive conversational AI and offers practical guidelines for designing accessible voice interfaces.
Recommended Citation
Cui, Tingru; He, Yongjie; and Zhang, Wugong, "Designing Effective Chatbot Voice Interfaces for Older
Adults and Neurodiverse Users: Enhancing Accessibility and
Wellbeing" (2025). ACIS 2025 Proceedings. 275.
https://aisel.aisnet.org/acis2025/275