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Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers
Jiayue Melissa Shi, Dong Whi Yoo, Keran Wang, Violeta J. Rodriguez, Ravi Karkar, Koustuv Saha. ACM Transactions on Computing for Healthcare, 2026-03-24
Topic: Risk, prevention and care in population studies
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, safe space for disclosure, emotional support, 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 chatbots’ 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.
Key findings
- 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.
- 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.
Why it matters
Researchers built a GPT-4o-based chatbot called Carey and interviewed 16 family caregivers after scenario-driven interactions to learn what they need and expect from such tools. The findings are design insights for future AI systems, not evidence that a chatbot improves caregiver mental health.
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Study details
- Evidence strengthLow
How this study scored 41/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (ACM Transactions on Computing for Healthcare) |
| Journal's citation record | 0 / 4 | ACM Transactions on Computing for Healthcare: journal h-index 30 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 9 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 4.5 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | 6 / 6 | Cited 59.1× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 9 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Koustuv Saha: h-index 32 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | University of Illinois Urbana-Champaign: institution h-index 1,439 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 3 institution(s) in 1 country |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Total | 41 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Shi, J. M., Yoo, D. W., Wang, K., Rodriguez, V. J., Karkar, R., & Saha, K. (2026). Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers. ACM Transactions on Computing for Healthcare. https://doi.org/10.1145/3803549
Vancouver
Shi JM, Yoo DW, Wang K, Rodriguez VJ, Karkar R, Saha K. Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers. ACM Transactions on Computing for Healthcare. 2026. doi:10.1145/3803549.
BibTeX
@article{shi2026-a7ab09d0,
author = {Shi, Jiayue Melissa and Yoo, Dong Whi and Wang, Keran and Rodriguez, Violeta J. and Karkar, Ravi and Saha, Koustuv},
title = {{Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers}},
journal = {ACM Transactions on Computing for Healthcare},
year = {2026},
doi = {10.1145/3803549},
url = {https://doi.org/10.1145/3803549}
}
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