What Will Patients Find When They Search Online for AI and Mammography? An Examination of Readability and Understandability Metrics in Online Patient Education Materials.

BACKGROUND

Artificial intelligence (AI) is rapidly being integrated into breast cancer screening, improving cancer detection and workflow efficiency. As patients become increasingly exposed to information about AI in mammography through news outlets, hospitals, and commercial entities, they are likely to seek information online. However, the readability and understandability of Online patient education materials (OPEM) for AI in mammography have not been examined.

METHODS

We collected the top 20 nonsponsored results for each of 5 AI-related internet search terms in mammography. After removing duplicates, each webpage (n = 56) was categorized by the source type and evaluated for readability using 6 readability algorithms, as well as for understandability using the Patient Education Materials Assessment Tool for Printable Materials.

RESULTS

The average grade-level readability across all webpages was 14.2, exceeding both the American Medical Association (sixth grade) and Centers for Disease Control and Prevention (eighth grade) recommendations. Reading ease scores placed most content in the "difficult" range, which is most suitable for college-level readers. Understandability averaged 72.4%, with variation by source type: commercial, government, and patient advocacy pages scored highest, while academic and medical media sources scored lowest.

CONCLUSION

Online information about AI in mammography is generally written at a level too advanced for most patients and meets only the minimum standards of understandability. Because patients are likely to encounter both OPEM and non-OPEM sources when searching online, clinicians should be prepared to guide them toward accessible, reliable resources. Developing standardized, patient-focused education materials by professional medical societies could ensure access to comprehensible information.