Representation of Rural Older Adults in AI for Health Research: Systematic Literature Review
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) research for older adults lacks focus on rural populations, potentially worsening health disparities. Future studies must prioritize rural representation and community-specific AI solutions for equitable access.
Area Of Science
- Health Informatics
- Artificial Intelligence
- Gerontology
Background
- Rural older adults face unique healthcare challenges like isolation and limited provider access.
- Artificial intelligence (AI) offers potential solutions for improving healthcare delivery to this demographic.
- Concerns exist regarding equitable access and representation of marginalized populations in AI healthcare innovations.
Purpose Of The Study
- Identify AI for health research literature concerning rural older adults.
- Critically evaluate existing research to find gaps.
- Inform inclusive AI research and design practices for this population.
Main Methods
- Systematic literature review following PRISMA 2020 Protocol.
- Searched 7 databases (PubMed, CINAHL, PsycINFO, Web of Science, IEEE, ACM, Scopus) for papers from 2013-2023.
- Thematic analysis of 23 selected empirical studies focusing on older adults, rural populations, and AI.
Main Results
- Limited representation of rural older adults in AI for health literature.
- Research predominantly focuses on quantitative data and clinical efficacy over broader impact.
- Existing AI health research risks deepening disparities due to the lack of rural focus.
Conclusions
- Significant gap in AI for health research specifically for rural older adults.
- Lack of representation raises concerns about generalizability and potential exacerbation of health disparities.
- Future research needs targeted recruitment, community-based AI development, and equitable solutions for rural populations.
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