JMIR Publications

ABSTRACT

Background:

Albeit the increasing focus in perinatal care, preventive digital interventions are still scarce. Furthermore, the literature suggests that the design and development of the latter are mainly conducted through a top-down approach that limitedly accounts for direct end-user perspectives.

Objective:

Building from a previous co-design study, the aim of the present study was to qualitatively evaluate pregnant women’s experiences with a chatbot (Juno) prototype designed to deploy a preventive behavioral activation intervention. Using a multiple-case study design, the research aims to uncover similarities and differences in participants’ perceptions of the chatbot, while also exploring women’s desires for improvement and technological advancements in chatbot-based interventions in perinatal mental health.

Methods:

N=5 pregnant women interacted weekly with the chatbot, operationalized in Telegram, following a 6-week intervention. Self-report questionnaires were administered at baseline and at post-intervention. After 10-14 days from concluding interactions with Juno, women participated in a semi-structured interview focused on (a) their personal experience with Juno, (b) user experience (UX) and user engagement (UE), and (c) their opinions for future technological advancements. Interviews’ transcripts, comprising 15 questions, were qualitatively evaluated, and compared. Text-mining analysis of transcripts was lastly performed.

Results:

Similarities and differences have emerged regarding women’ experiences with Juno, appreciating its aesthetic but highlighting technical issues and desiring clearer guidance. They found the content useful and pertinent to pregnancy but differed on when they deemed it most helpful. Women expressed interest in receiving increasingly personalized responses and for future integration with existing healthcare systems for better support. Accordingly, they generally viewed Juno as an effective momentary support but emphasized the need for human interaction in mental health care, particularly if increasingly personalized. Further concerns included overreliance on chatbots when seeking for psychological support and the importance of clearly educating users on the chatbot’s limitations.

Conclusions:

Overall, results highlighted both the positive aspects and the shortcoming of the chatbot-based intervention, providing insight for its refinement and future developments. However, women stressed the need to balance technological support with human interactions, particularly when moving beyond a preventive mental health context, to favor a greater and more reliable monitoring.