Ecological Momentary Assessment Data for GenAI for mental health project

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. Firstly, this involves using ecological momentary assessments to explore mental health challenges of people with LTCs in Nigeria and their perspectives of Gen AI use. In this study, out of 28 people with diabetes who started and signed up, 21 participants, categorised as E1 – E21 completed the study. We start with prompts that explore daily routines within the context of wellbeing, progress to prompts exploring socio cultural parameters of wellbeing, before exploring how this intersects with participants’ use of technology and reflecting on how these activities may have contributed to their awareness of wellbeing and any future preferences. In other words, the EMA prompts were structured into four domains (daily wellbeing and illness experiences; social and cultural influences; digital engagement; and reflection/future preferences).All data has been completely anonymized and personal identifiable information has been removed.