"Words are not enough": Examining Emotional Support by Conversational AI for Caregivers
Melika Vafafar, Sian Joel-Edgar, Casper Harteveld, Hossein Dabbagh, Andrew K. Martin, Chee Siang Ang
Abstract
Caregivers often experience emotional difficulties and social isolation due to their demanding caregiving duties. Conversational AI has the potential to provide emotional support, yet it lacks effective emotional-regulation support. In this study, we conducted focus groups and semi-structured interviews with mental health professionals and caregivers (n = 17) to explore the potential benefits, challenges, and concerns of users on the applications of conversational AI for caregivers’ emotional support. Our findings suggest that, while current text-based conversational AI is deemed valuable for emotional support, there is a desire to have a more empathic AI, an AI that actively listens, takes cultural, religious, and linguistic context into consideration; and makes humans feel heard. We examined the dimensions of empathic AI in mental health, from authenticity and trust to over-reliance, misuse, and even exacerbating mental health problems, and how this can potentially be addressed to improve caregivers’ well-being.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 73ba9c27-f35d-4e6c-ba48-d5e3628aead9Builds on11
- PromptMagician: Interactive Prompt Engineering for Text-to-Image CreationYingchaojie Feng, Xingbo Wang, Kamkwai Wong, Sijia Wang et al.IEEE VIS 2023 · 127 citations
- The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI RelationshipsRenwen Zhang, Han Li, Han Meng, Jinyuan Zhan et al.CHI 2025 · 122 citations
- Using Thematic Analysis in Healthcare HCI at CHI: A Scoping ReviewRobert Bowman, Camille Nadal, Kellie Morrissey, Anja Thieme et al.CHI 2023 · 106 citations
- MindTalker: Navigating the Complexities of AI-Enhanced Social Engagement for People with Early-Stage DementiaAnna Xygkou, Chee Siang Ang, Panote Siriaraya, Jonasz Piotr Kopecki et al.CHI 2024 · 55 citations
- Alexa as an Active Listener: How Backchanneling Can Elicit Self-Disclosure and Promote User ExperienceEugene Cho, Nasim Motalebi, S. Shyam Sundar, Saeed AbdullahCSCW 2022 · 36 citations
Related papers
- The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health SupportInhwa Song, Sachin R. Pendse, Neha Kumar, Munmun De ChoudhuryCSCW 2025 · 41 citations
- Sharing the Care: Investigating How Conversational AI Might Facilitate Coordination Among Home Care Workers and Family CaregiversIan René Solano-Kamaiko, Ariel C. Avgar, Madeline R. Sterling, Aditya Vashistha et al.CHI 2026 · 1 citation
- One Question, Four Voices: How Advice for Alzheimer's Caregiving Differs Between Caregivers, Clinicians, and Large Language ModelsCongning Ni, Jinkyung Katie Park, Yang Li, Sarvech Qadir et al.CSCW 2026
- Understanding the Benefits and Challenges of Deploying Conversational AI Leveraging Large Language Models for Public Health InterventionEunkyung Jo, Daniel A. Epstein, Hyunhoon Jung, Young-Ho KimCHI 2023 · 167 citations
- Chaplains' Reflections on the Design and Usage of AI for Conversational CareJoel Wester, Samuel Rhys Cox, Henning Pohl, Niels van BerkelCHI 2026 · 3 citations
