JuNEX – The co-design of a Chatbot-Delivered Psychological Preventive Intervention to support Pregnant Women’s Well-being

The realm of Digital Healthcare represents a transformative force in traditional healthcare, empowering patients and shifting dynamics of care. This evolution has significant implications for mental healthcare, particularly amidst a global mental health crisis where accessibility and the cost-effectiveness of treatments are critical. In this regard, digital tools offer a promising solution, allowing for a spectrum of care from primary to specialized services. Within this context, maternal mental health during the perinatal period emerges as a focal point, highlighting substantial challenges faced by women transitioning to motherhood. Peripartum depression, often exacerbated by limited access to specialized services, underscores the need for timely interventions. In this regard, digital interventions hold promise in overcoming these barriers by enhancing accessibility to psychological support. In line with this, in the present dissertation, digital Behavioral Activation (BA) interventions have been explored to address depressive symptoms among perinatal women. A scoping review mapped existing literature on digital BA interventions during the perinatal period, revealing preliminary evidence of effectiveness in reducing depression symptoms. However, challenges such as low adherence and inadequate usability evaluation were identified, indicating the need for further refinement. Building on this foundation, and with a particular focus on prevention, an explorative co-design study was performed to evaluate the feasibility of delivering a digital replica of the Brief Behavioral Treatment for Depression-Revised (BATD-R) to pregnant women. The study compared guided and unguided internet-based interventions implemented in Moodle, revealing insights into the usability and user engagement challenges of such an e-learning format applied to this context. Despite high dropout rates and usability concerns, participants expressed satisfaction with the intervention’s content and relevance to their pregnancy experiences. After revising and refining the intervention and the digital tool, a qualitative evaluation focused on Juno, a chatbot prototype delivering the BA intervention via Telegram, was conducted employing a multiple-case study design. Pregnant women’s perceptions highlighted both the benefits and limitations of chatbot-delivered interventions, underscoring preferences for greater personalization and human contact. Ethical considerations, including the risk of overreliance on digital tools, were also addressed, emphasizing the importance of balanced integration into comprehensive healthcare frameworks. Looking forward, findings suggest that integration efforts should be made to blend digital and in-person care, optimizing maternal mental health support through innovative, user-centered digital tools. By integrating advanced technologies with human-centered approaches, future developments should aim to enhance accessibility, effectiveness, and user satisfaction in addressing perinatal mental health challenges while serving to fill in the gaps in existing healthcare services.