Artificial Intelligence for Health Message Generation: Theory, Method, and an Empirical Study Using Prompt Engineering
This work addresses the need for efficient health communication tools, particularly for public health campaigns, though it is incremental as it applies existing AI methods to a specific domain.
The study tackled the problem of generating health awareness messages by developing an AI system using prompt engineering, specifically for folic acid during pregnancy, and found that AI-generated messages were comparable to human-generated ones in computational metrics and ranked higher in quality and clarity in human evaluations.
This study introduces and examines the potential of an AI system to generate health awareness messages. The topic of folic acid, a vitamin that is critical during pregnancy, served as a test case. Using prompt engineering, we generated messages that could be used to raise awareness and compared them to retweeted human-generated messages via computational and human evaluation methods. The system was easy to use and prolific, and computational analyses revealed that the AI-generated messages were on par with human-generated ones in terms of sentiment, reading ease, and semantic content. Also, the human evaluation study showed that AI-generated messages ranked higher in message quality and clarity. We discuss the theoretical, practical, and ethical implications of these results.