Balancing Efficiency and Engagement: AI-Assisted Content for Research Communications in the RECOVER Initiative

Abstract Introduction The growing availability of AI tools is transforming health and science communication by streamlining content creation and promotion. This study investigates the impact of AI-assisted research summaries on user engagement with the NIH-funded RECOVER program's website and evaluates the efficiency and readability of the content. Methods We analyzed Google Analytics 4 data from two distinct periods: one with entirely human-generated content and a second with AI-assisted content. We measured changes in page views, active users, and average engagement time, and assessed the review time and readability of the AI-enhanced summaries. Results There was no significant change in page views or active users between the two periods. However, average engagement time increased by 4.37 seconds (P = .0461), suggesting AI-assisted content may be more compelling. Human review of AI-drafts averaged 19.88 changes, and readability improved, with the mean Flesch-Kincaid grade level decreasing from 12.28 to 11.56. Conclusion This study demonstrates that AI can be a valuable tool for accelerating the creation of accessible and engaging content. Our findings highlight a crucial balance: while AI can save effort and reduce cost in public engagement efforts, human oversight remains essential to ensure the accuracy, clarity, and accessibility of vital health communications.