Using artificial intelligence to expedite and enhance plain language summary abstract writing of scientific content

Abstract

Objective: To assess the capacity of a bespoke artificial intelligence (AI) process to help medical writers efficiently generate quality plain language summary abstracts (PLSAs). Materials and Methods: Three independent studies were conducted. In Studies 1 and 3, original scientific abstracts (OSAs; n ¼ 48, n ¼ 2) and corresponding PLSAs written by medical writers versus bespoke AI were assessed using standard readability metrics. Study 2 compared time and effort of medical writers (n ¼ 10) drafting PLSAs starting with an OSA (n ¼ 6) versus the output of 1 bespoke AI (n ¼ 6) and 1 non-bespoke AI (n ¼ 6) process. These PLSAs (n ¼ 72) were assessed by subject matter experts (SMEs; n ¼ 3) for accuracy and physicians (n ¼ 7) for patient suitability. Lastly, in Study 3, medical writers (n ¼ 22) and patients/patient advocates (n ¼ 5) compared quality of medical writer and bespoke AI-generated PLSAs. Results: In Study 1, bespoke AI PLSAs were easier to read than medical writer PLSAs across all readability metrics (P 40% in time for PLSA creation and required less effort than unassisted writing. SME-assessed quality was higher for AI-assisted PLSAs, and physicians preferred bespoke AI-generated outputs for patient use. In Study 3, bespoke AI PLSAs were more readable and rated of higher quality than medical writer PLSAs. Discussion: The bespoke AI process may enhance access to health information by helping medical writers produce PLSAs of scientific content that are fit for purpose. Conclusion: The bespoke AI process can more efficiently create better quality, more readable first draft PLSAs versus medical writer-generated PLSAs.