English

Artificial Intelligence for Health Message Generation: Theory, Method, and an Empirical Study Using Prompt Engineering

Computation and Language 2024-02-23 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2212.07507,
  title  = {Artificial Intelligence for Health Message Generation: Theory, Method, and an Empirical Study Using Prompt Engineering},
  author = {Sue Lim and Ralf Schmälzle},
  journal= {arXiv preprint arXiv:2212.07507},
  year   = {2024}
}

Comments

26 pages including references, 3 figures

R2 v1 2026-06-28T07:35:28.859Z