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Artificial Intelligence Techniques and Health Literacy: A Systematic Review
Abigail Naa Amankwaa Abeo1, Sophie Armstrong1, Michael Scriney2
1School of Health and Human Performance, Dublin City University, Ireland.
Mayo Clinic Proceedings. Digital Health
|November 10, 2025
Summary
Artificial intelligence (AI) is increasingly used in health literacy, but measuring its effectiveness remains a challenge. Future research needs to focus on rigorous health literacy measurement and AI implementation for better outcomes.
Area of Science:
- Health Informatics
- Artificial Intelligence
- Health Literacy Research
Background:
- Artificial intelligence (AI) offers potential solutions for improving health literacy.
- Understanding AI's current role and limitations in health literacy is crucial for future development.
Purpose of the Study:
- To systematically review the utilization of artificial intelligence (AI) in health literacy.
- To identify limitations and future developments in AI applications for health literacy.
Main Methods:
- Systematic review following PRISMA guidelines.
- Searched 6 databases (Jan 2014 - Apr 2024).
- Extracted data on population, health literacy definitions/measurement, AI techniques, and metrics; assessed risk of bias.
Main Results:
- 18 studies (1.4%) met inclusion criteria, focusing on text-based materials (online articles, EHRs).
- AI applications included complexity evaluation, text simplification, translation, and question-answering.
- Limited health literacy measurement (individual/organizational), with only 1 study using a measurement tool; 5 studies involved participant engagement.
Conclusions:
- AI shows dynamic application in health literacy, but measurement of its effectiveness is limited.
- Future research must rigorously measure health literacy outcomes and enhance AI model performance, evaluation, and implementation.
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