Development of a Web-Based Mental Health Support System with Integrated Chatbot and Therapist Referral for Nigeria

Nigeria’s mental health crisis is exacerbated by a severe shortage of professionals, with only 250 psychiatrists serving over 200 million people. This study develops a web-based mental health support system combining a rule-based chatbot and therapist referral mechanism to improve accessibility. The system, built with React.js (frontend), Node.js/Express.js (backend), and MongoDB (database), offers immediate mental health guidance, mood tracking, and appointment booking with licensed consultants. A dataset of predefined responses for common mental health queries (e.g., anxiety, depression) was used to train the chatbot, while referral protocols escalate complex cases to human professionals. Testing demonstrated 85% user satisfaction in handling basic queries and 90% accuracy in identifying cases requiring therapist intervention. The system addresses critical gaps in Nigeria’s mental health landscape by providing stigma-free, scalable support, particularly in underserved regions. This research contributes a model for hybrid (AI + human) mental health solutions in low-resource settings.