OBJECTIVES: To examine artificial intelligence (AI) chat’s ability to assess and improve the readability level of patient-facing materials, inclusive of patient-reported outcome (PRO) measures.

METHODS: AI chat was used to evaluate the readability level (i.e. Flesch-Kincaid and Coleman-Liau formulas) of text from an established PRO measure, the SF-12, text from a patient interview guide, and an informed consent form (ICF). Depending on the established readability level, the chat was then queried to revise the text to be appropriate for a 6^th or 3^rd grade reading level. The appropriateness of recommended revisions were then evaluated.

RESULTS: The SF-12 instructions, item, and associated response options were determined to have a Flesch-Kincaid readability level of around the 10^th grade and were revised to a 6^th grade reading level by AI chat client. Similarly, interview guide text was revised from a 6^th grade to a 3^rd grade reading level, and the ICF was revised from a 7^th grade to a 3^rd grade reading level. AI-recommended revisions focused on simplifying the language, breaking down complex sentences, and removing complex terminology and/or replacing words with more appropriate vocabulary for each reading level. Revisions were determined to retain the intended meaning of the text. Some words (e.g., strenuous) were identified as candidates for further simplification.

CONCLUSIONS: AI chat can provide fast and effective insight into identifying challenging language in patient-facing materials and can inform revisions to improve readability. Revisions made by AI chat still need to be evaluated by researchers for appropriateness. AI chat cannot replace the value of engaging with patients directly, especially given the need to consider the unique perspectives of patients in various disease populations, including pediatric patients or patients with cognitive impairment. Including AI chat review of patient-facing materials and modifying materials accordingly is recommended prior to engaging with patients.