Current landscape of the use of artificial intelligence-based conversational agents (chatbots) in prenatal care: A scoping review.

Introduction: Uninterrupted prenatal care is fundamental for mitigating maternal-fetal morbidity and mortality. However, limited consultation times and structural barriers within primary care restrict the provision of comprehensive health education. Consequently, pregnant women frequently turn to digital sources to resolve doubts, risking exposure to medical misinformation. In recent years, the advancement of artificial intelligence (AI) and automated conversational agents (chatbots) has offered a scalable solution to provide immediate, empathetic, and evidence-based support. Objective: To explore and describe the scope of current literature regarding the design, clinical application, and acceptability of artificial intelligence-driven conversational agents (chatbots) used for health education and the promotion of adherence during prenatal care. Methodology: A scoping review of scientific articles, clinical trials, and observational studies published in the last 10 years in databases such as PubMed, Scopus, and Web of Science. The search strategy utilizes MeSH terms and text words associated with the themes of prenatal care, artificial intelligence, natural language processing, chatbots, and health education. Expected results: This study expects to consolidate an evidence map detailing the design, architecture, and implementation of artificial intelligence-based conversational agents (chatbots) during prenatal care. Additionally, it projects evaluating their clinical and educational benefits regarding maternal adherence, outlining the ethical, technical, and acceptability barriers for their future application in primary care. Descriptors (DeCS/MeSH): Prenatal Care; Artificial Intelligence; Natural Language Processing; Health Education; Patient Compliance. Keywords:Prenatal care, chatbots, artificial intelligence, health education, adherence.