The utility of artificial intelligence in plain language writing: A scoping review.

Abstract

The prevalence of medical and technical jargon makes the dissemination of healthcare information to patients challenging. Plain language (PL) writing, a style of written communication that strives to employ clear and concise language, is a critical tool for overcoming these hurdles, but is hindered by resource constraints. The emergence of generative Artificial Intelligence (AI) has led to research aimed at assessing its PL writing capacity. The aim of this scoping review was to explore what is known about the use of generative AI platforms for writing in PL. A scoping review was conducted via searches across nine databases in Summer 2024. Studies were included if they evaluated a generative AI platform for the use of writing patient education materials (PEMs) in PL and measured best practices (e.g. readability). In total, 47 articles were included. Most studies were conducted in the United States (n = 29, 61.7 %). Prompt engineering strategies included specifying a reading grade level, audience, health condition, and resource type. AI-generated PEMs improved readability in 28.3 % of the 46 studies that measured Reading Grade level and in 46.2 % of the 26 studies that measured Reading Ease. This review highlights the potential of generative AI for writing PEMs and assisting in the promotion of health literacy in patient care. AI models varied in their ability to generate or edit PEMs into plain language. Further research is needed to determine whether this can be done to industry standards and outside English-language contexts.