A Chatbot (Juno) Prototype to Deploy a Behavioral Activation Intervention to Pregnant Women: Qualitative Evaluation...

Area of Science:

• Digital health interventions in perinatal care.
• Behavioral activation for maternal mental health.
• Human-computer interaction in healthcare.

Background:

• Preventive digital interventions in perinatal care remain scarce.
• Existing digital health tools often use a top-down design approach, neglecting end-user perspectives.

Purpose of the Study:

• To qualitatively evaluate pregnant women's experiences with a chatbot prototype (Juno) for preventive behavioral activation.
• To gather insights for improving chatbot-based interventions in perinatal mental health.

Main Methods:

• Multiple-case study design involving five pregnant women interacting with a Telegram-based chatbot (Juno) for 6 weeks.
• Data collection through baseline and post-intervention questionnaires, and semistructured interviews.
• Qualitative evaluation and text-mining analysis of interview transcripts.

Main Results:

• Participants appreciated the chatbot's aesthetics but reported technical issues and desired clearer guidance.
• Content was perceived as useful, though opinions varied on optimal timing; interest in personalized responses and healthcare integration was high.
• Juno was seen as effective momentary support, but participants stressed the need for human interaction and clear communication of chatbot limitations.

Conclusions:

• The chatbot-based intervention shows promise but requires refinement, particularly regarding technical aspects and user guidance.
• A balance between technological support and human interaction is crucial for effective perinatal mental health care.
• Future developments should consider personalization and integration with existing healthcare systems, while managing user expectations.