Representation of Rural Older Adults in AI for Health Research: Systematic Literature Review

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.