Exploring Pregnant Women’s Experiences With Mobile Chatbot-Based Antenatal Education: A Qualitative Descriptive Study

Abstract

Background:

Mobile chatbot technology is a promising tool for delivering prenatal education, particularly during public health crises such as the COVID-19 pandemic. However, little is known about pregnant women’s firsthand experiences with such digital tools in clinical settings.

Objective:

The purpose of this study was to explore women’s perceptions of a specific chatbot intervention.

Methods:

A qualitative descriptive study was conducted with 11 first-trimester pregnant women recruited from a university-affiliated hospital in Taipei, Taiwan. Participants used a maternal chatbot for approximately 30 minutes while waiting for their scheduled outpatient consultation, followed by semi-structured, face-to-face interviews. Data were analyzed using thematic analysis supported by MAXQDA software.

Results:

Three main themes emerged: initial perceptions, usability, and acceptability of the maternal chatbot. Participants found the chatbot convenient and helpful for learning about early pregnancy, and expected it to be especially useful during wait times. They also identified certain limitations, such as inadequate keyword search, a lack of personalized content, and the absence of empathetic human interaction. Some preferred the immediacy and familiarity of Google searches, while others valued the credibility of the vetted health information provided by the chatbot.

Conclusion:

The maternal chatbot was generally perceived as a useful supplementary tool for prenatal education. However, users’ expectations of emotional engagement and system functionality were found to influence its perceived effectiveness. Designs in the future should incorporate improved searchability, broader health topics, and optional human support to enhance users’ experiences of digital maternal care.