Abstract

Mental health issues affect university students, particularly from developing countries, who are mostly faced with social, economic, and environmental challenges, which significantly impact students’ academic performance and well-being. Furthermore, the literature shows that seeking professional mental health support is usually associated with excessive costs and stigmatization. Moreover, existing generic Chatbots do not address the specific contextual needs of students. This paper therefore presents a Chatbot tailored for students from a developing country context.  Qualitative data were collected from ten final-year undergraduate students with a mental breakdown who are currently enrolled at a single university case in Zimbabwe. A thematic analysis of collected data provided key constructs for designing a Chatbot that employs natural language understanding techniques to afford university students a convenient platform for acquiring mental health support. Kanban methodology was employed to develop the machine learning Chatbot using the Rasa open-source framework which is a development framework that provides open-source tools and libraries for building conversational chatbots, leveraging a collection of different pre-trained and customizable machine-learning models for varying tasks within the chatbot such as intent classification, entity recognition, and natural language understanding. The findings from this research reveal that university students appreciate this innovative approach that promotes a private and user-friendly environment for their mental health care. The findings also suggest that students who experience mental breakdown only prefer to use Chatbots as an alternative intervention rather than a replacement for mental health professionals due to the unpredictable performance of chatbots, which sometimes results in inconsistent and varying solutions for mental health care. These findings add value to the knowledge body and impact university students who can now freely access mental health support without stigmatization. The parents or guardians of affected students can now be relieved from incurring high costs for some avoidable professional mental health services for their children. Lecturers can lecture and impart knowledge to mentally relieved, present, and attentive students. The findings also add to the university management’s understanding of the student's mental health needs and, can be able to strategize policies aimed at minimizing students’ mental breakdown and recurrences.