Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers

2025-06-18

AI Summary

Alzheimer’s disease family caregivers endure chronic psychological burden, yet existing AI support tools lack deep understanding of their authentic needs and trust mechanisms. Method: Leveraging GPT-4o–powered Carey chatbot as a technical probe, we conducted in-depth interviews with 16 caregivers and applied reflexive thematic analysis. Contribution/Results: We introduce the first “Caregiver Needs–AI Capabilities” mapping framework, identifying six core needs—information access, emotional support, crisis response, care coordination, cognitive assistance, and self-care promotion—and uncovering three structural tensions: safety, personalization, and privacy protection. Based on these findings, we propose caregiver-centered, trustworthy AI design principles and derive 12 actionable design guidelines. This work establishes a theoretical foundation and practical roadmap for AI systems supporting the mental health of caregivers of individuals with neurodegenerative diseases.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: AI for Accessibility
• Cognitive Modeling & Cognitive Systems: Affective Computing

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Algorithmic accountability and transparency on the web

Abstract

Family caregivers of individuals with Alzheimer's Disease and Related Dementia (AD/ADRD) face significant emotional and logistical challenges that place them at heightened risk for stress, anxiety, and depression. Although recent advances in generative AI -- particularly large language models (LLMs) -- offer new opportunities to support mental health, little is known about how caregivers perceive and engage with such technologies. To address this gap, we developed Carey, a GPT-4o-based chatbot designed to provide informational and emotional support to AD/ADRD caregivers. Using Carey as a technology probe, we conducted semi-structured interviews with 16 family caregivers following scenario-driven interactions grounded in common caregiving stressors. Through inductive coding and reflexive thematic analysis, we surface a systemic understanding of caregiver needs and expectations across six themes -- on-demand information access, emotional support, safe space for disclosure, crisis management, personalization, and data privacy. For each of these themes, we also identified the nuanced tensions in the caregivers' desires and concerns. We present a mapping of caregiver needs, AI chatbot's strengths, gaps, and design recommendations. Our findings offer theoretical and practical insights to inform the design of proactive, trustworthy, and caregiver-centered AI systems that better support the evolving mental health needs of AD/ADRD caregivers.

Problem

• Addressing emotional and logistical challenges of AD/ADRD caregivers
• Exploring caregiver perceptions of AI chatbot mental health support
• Designing proactive, trustworthy AI systems for caregiver needs

Innovation

• GPT-4o-based chatbot for caregiver support
• Scenario-driven semi-structured caregiver interviews
• Inductive coding and thematic needs analysis