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

Area of Science:

• Digital Health
• Maternal Health Technology
• Human-Computer Interaction

Background:

• Mobile chatbots offer a promising avenue for prenatal education, especially during public health crises.
• Limited understanding exists regarding pregnant women's real-world experiences with these digital tools in clinical settings.

Purpose of the Study:

• To explore pregnant women's perceptions and experiences with a specific maternal chatbot intervention.

Main Methods:

• Qualitative descriptive study involving 11 first-trimester pregnant women.
• Participants used a maternal chatbot during clinic wait times, followed by semi-structured interviews.
• Thematic analysis was employed for data analysis using MAXQDA software.

Main Results:

• Three themes emerged: initial perceptions, usability, and acceptability.
• Participants viewed the chatbot as convenient for learning about early pregnancy and useful during wait times.
• Limitations included inadequate search, lack of personalization, and absence of empathetic interaction; some preferred Google, others valued credible information.

Conclusions:

• Maternal chatbots are perceived as useful supplementary tools for prenatal education.
• User expectations for emotional engagement and system functionality significantly influence perceived effectiveness.
• Future designs should enhance searchability, broaden topics, and include optional human support to improve digital maternal care experiences.