ArticleACM transactions on computing for healthcare2026
"I don't see anything specifically about Black/African Americans." Testing an Alzheimer-specific generative AI tool tailored for African American/Black communities.
Article in ACM transactions on computing for healthcare, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Exploring Design Recommendations for Promoting Brain Health, ADRD Health Literacy, and Participation in clinical ADRD trials in Older African American/Black Adults.Proceedings of the ACM on human-computer interaction · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
Abstract
Low levels of health literacy concerning Alzheimer's Disease and related dementias (ADRD) impact African American/Black communities access to appropriate ADRD care. Additionally, a legacy of mistrust in medical research due to systemic racism, has resulted in insufficient participation in ADRD clinical trials among African American/Black adults. This study explores the potential of generative AI to improve ADRD literacy and encourage participation in clinical trials among African American/Black older adults. We designed a mobile health intervention featuring AI-driven conversational agents - a chatbot and a voice assistant - specifically developed for this population. We tested the quality of the intervention using heuristics methodology adapted to the target population along with inputs from African American/ Black medical professionals and UX designers. Key findings highlight the unique needs of the African American/Black communities for culturally relevant content that is accessible to users with varying language levels and tailored to users' geographical location. Concerning the interaction, high levels of personalization and control over the interaction can promote the use of the tool, by minimizing complexity and maximizing accessibility. These findings show the novel contribution offered by our study in the domain of designing health technology with generative AI, particularly LLMS, for African American/Black communities.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.