Exploring the Design of a LLM-Based AI Assistant for Mindfulness Practice With Older Adults

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Authors: Lucy McCarren, Ulrika Eriksson, Laura Ortiz Mengual, Sanna Kuoppamäki
Cited by: 1
References: 76

Abstract

Large Language Models (LLMs) are increasingly integrated into mental health and well-being technologies, yet little is known about how they are perceived by older adults or how they should be designed to meet later-life needs. Mindfulness technologies, often promoted as tools for healthy ageing, provide a useful context for exploring these questions. We conducted participatory workshops with sixteen older adults using LugnAI, a prototype LLM-based system for guided mindfulness practice. Participants reflected on their experiences with AI-guided mindfulness and contributed design preferences for future systems. Analysis revealed tensions between adaptivity and autonomy, supportive versus intrusive engagement strategies, and AI-enabled emotional support versus the preservation of human connection and self-regulation practices. Based on these findings, we provide concrete design considerations for LLM-based mindfulness technologies that are sensitive to the socioaffective realities of ageing. While situated in mindfulness, the insights extend to broader applications of LLMs in supporting older adults’ well-being.

Fields of Study & Subjects

Digital Mental Health Interventions Innovative Human-Technology Interaction Mental Health via Writing

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–16
Publication date
13 April 2026