Work

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

Year: 2026

Type: preprint

Abstract: 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.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.23997667

Authors: Chukwunweike, Ifeanyi, Silas, Ibrahim, Amirat, Idris, Zainab Isa, Onyia Chimeremiheoma, Linus, Kolapo, Ridwan

Institution: Nile University of Nigeria

Language: English

Topic: Digital Mental Health Interventions

Subfield: Applied Psychology

Field: Psychology

Domain: Social Sciences

SDGs: Good health and well-being, Reduced inequalities

Open Access status: green

OpenAlex ID: W7225399871

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