Enhancing Maternal Education in the Perinatal Period Through Chatbot Technology

It is essential that pregnant women in the United States receive comprehensive medical  care throughout the perinatal period, which consist of three trimesters:

1)       Prenatal (antepartum)- pregnancy,

2)       Intrapartum-labor and birth, and

3)       Postpartum- the first 42 days after the birth.

According to 2023 data from the National Center for Health Statistics [NCHS], Hoyert (2023) reported that non-Hispanic Black women in the United States experienced significantly higher rates of maternal mortality rates (50.3%) compared to White women (14.5%), Hispanic women (12.4%), and Asian women (10.7%). Declercq and Zephyrin (2025), in a report from the Common Wealth Funds, found that most maternal deaths occur in the first year after birth and are often a result of severe bleeding -related conditions, infections, and hypertension. Notably, most maternal of these deaths occurred in the postpartum period.

Infant mortality deaths in the United States also remains high. In 2022, more than 20,500 infant deaths were reported due to birth defects, preterm birth, sudden infant syndrome (SIDS), unintentional injuries (such as motor vehicle crashes), and maternal pregnancy complications (Center for Disease Control and Prevention [CDC], 2024). Increasing perinatal education is critical to reducing both maternal and infant morbidity and mortality. Mothers must understand warning signs and know when to seek care for themselves and their infants (Rivera Rivera, 2024). Integrating chatbot technology into perinatal education may strengthen women’s health outcomes and serve as a valuable extension of the perinatal healthcare team.

Artificial Intelligence and Maternal Health

Maternal health is a vital component of public health, and artificial intelligence (AI) has emerged as a powerful tool to help women remain connected to essential health information throughout the antepartum, intrapartum, and postpartum periods. Recently, chatbots-- an increasingly sophisticated form of digital technology-- was developed  to educate pregnant women and new mothers about the perinatal and newborn care (Mapari et al., 2024; Rivera Rivera et al., 2024.)

 But first, what are chatbots? According to IBM, “A chatbot is a computer program that simulates human conversation with an end user.” In practical terms, users type or verbally ask a question and receives a conversational response that mimics human interaction (https://www.ibm.com/think/topics/chatbots).

Chatbots vary in complexity. Some chatbots offer simple menu options, while others offer AI and natural language processing (NLP) to manage complex, nuanced conversations. Overall, the two main types of chatbots are menu-based and AI-based. The specific types of chatbots will be discussed in the next section.

Types of Chatbots

·       Menu Based (Button-Based Chatbots)

These chatbots provide basic functionality through scripted menus designed to meet client’s needs. They are good for answering repetitive questions but struggle with nuanced or complex inquiries. They operate using simple decision trees.

·       Rule-Based Chatbots

Using “if-then” logic, rule-based chatbots answer to predefined questions and are commonly used to answer frequently asked questions (FAQs). However, they cannot respond effectively to queries outside their programmed rules.

·       AI-Powered Chatbots

AI-powered chatbots understand user input regardless of phrasing. These chatbots can quickly find relevant information which allows for smoother and conversational language. Machine learning algorithms allow them to continuously expand their knowledge base of questions and provide increasingly accurate responses. Deep learning enhances their ability to generate more detailed and contextually relevant answers. Conversational chatbots can remember prior conversations with customers and incorporate this context for future conversations. For example, the chatbot can pull information from previous orders, such as food orders or personal addresses, to streamline the ordering process.

·       Voice Chatbots

Users interact with voice chatbot by speaking rather than typing. AI-driven voice chatbots utilize speech-to text and text-speech technologies to deliver conversational responses. However, more rudimentary versions may provide limited functionality.

·       Generative AI Chatbots

Generative AI chatbots offer advanced capabilities, including summarizing, translating, predicting, and creating content in response to a user’s queries. They adapt to a user’s language style and may incorporate empathetic language into responses.

·       Hybrid Chatbots

Hybrid systems combine rule-based logic with AI and machine learning capabilities, offering the best of both worlds—structured reliability and conversational flexibility (https://www.ibm.com/think/topics/chatbot-types).

Chatbot Uses in Perinatal and Infant Education

Chatbots are increasingly used in perinatal settings to prepare women for pregnancy, childbirth postpartum recovery, and infant care.  Further, their continued integration into healthcare represents a paradigm shift in how perinatal health is delivered (Amil et al., 2025). Women can access 24/7 support for symptom assessment and health education, particularly when health care providers (HCPs) are not readily available (Clark & Bailey, 2024). In addition, chatbots can provide personalized, real-time information across all  perinatal periods too (Nguyen et al., 2024).

 Examples of current chatbots and their uses in the perinatal setting are discussed below:

·       Rosie, A Health Education Question-and-Answer Chatbot for New Mothers-Rosie is a mobile app designed to answer questions about pregnancy, parenting, breastfeeding, and child development. Researchers have used Rosie to refine and improve language models for maternal education (Mane et al., 2023), Nguyen et al., 2024; Rivera Rivera, et al., 2026).

·       Parentbot-A Digital Healthcare Assistant

Parentbot is designed to improve women’s well-being across the perinatal period. Studies have shown improvement in maternal self-efficacy and state anxiety at 1 and 3 months after birth of their infant. When the chatbot cannot  answer a question, users are transferred to a “Ask an Expert” platform where HCPs provide direct support (Chua et al., 2024).

·       Moment for Parents Chatbot to Address Maternal Depression

This chatbot application supports the mental health needs of pregnant and postpartum women. One-month postpartum feedback highlighted its value in supporting perinatal mental health concerns, suggesting it is a practical tool for supporting maternal emotional well-being (McAllister et al., 2025).

Ethical Considerations of Using AI in Maternal Health

The integration of AL into maternal health requires careful ethical consideration:

·       Data Privacy and Security: Medical records, genetic information, and personal data must be safeguarded. Compliance with HIPPA is essential.

·      

Bias in AL Algorithms-Al systems must be trained on diverse and representative datasets to reduce racial and socioeconomic bias.

·       Informed Consent and Autonomy-Mothers should clearly understand how AI tools are used in their care.

·       Access to AI Technology-Policymakers must ensure equitable access to AI in underserved communities.

·       Human Oversight-Balance AI recommendations should complement--not replace— clinical expertise (Mapari et al., 2024).

Conclusion

Chatbots demonstrate significant promise in delivering accessible, timely, and personalized perinatal education to mothers. This technology maybe particularly impactful for Black mothers who experience disproportionately higher maternal mortality rates in the United States. As digital literacy increases among newer generations, the demand for sophisticated, AL-driven health education tools will likely continue to grow. Current generations feel comfortable receiving information from digital chatbots and will want to use more sophisticated applications in the future (Chua et al., 2023). When implemented ethically and equitable, chatbot technology can serve as a powerful adjunct to the perinatal healthcare team and contribute to improved maternal and infant health outcomes.

Assessed and Endorsed by the MedReport Medical Review Board