Data Management Plan for "Generative AI for Mental Health Support for Africans with Long-term Health Conditions"

The mental health landscape in sub-Saharan Africa is critically underserved, especially for people with long-term conditions (LTCs). Countries like Zimbabwe, Kenya, and Nigeria each have fewer than ten public mental health institutions. Even South Africa, a more developed nation, has only 24, which is insufficient for its population. This shortage is worsened by socio-cultural factors wheremental health issues are often misunderstood or stigmatized, leading to poor attitudes toward mental health. These attitudes often remain unchanged even when Africans migrate to countries like the U.K., increasing the burden on emergency services andcontributing to broader public health challenges such as family instability and reliance on social services.

To understand the mental health needs of Africans and position generative AI as a transformative tool, I select Nigeria as a case study due to its mental health gaps, limited digital infrastructure, and cultural diversity. Also, I will evaluate designed AI-supportedinterventions among the Nigerian diaspora in the U.K. to explore how context influences adoption and outcomes. This aims to support both people with LTCs and mental health professionals (MHP) by strengthening technology-enabled care.

The project will engage at least 100 participants across three work packages. Using ecological momentary assessments, interviews, and distributed design workshops, the project will explore mental health challenges of people with LTCs in Nigeria. These findings will inform the development of a chatbot and a custom-GPT tool for delivering personalised support. The tools will be tested on accessible platforms like WhatsApp with Nigerians in the U.K. to evaluate cultural fit, usability, and effectiveness.