Data · dataset · 2026
Title: Bridge or Substitute? Generative AI, Self-Diagnosis and Health Equity among Nigerian University Students
Listed in Teesside University Research Data Repository
This dataset contains anonymised responses from an online qualitative survey examining how Nigerian university students use generative artificial intelligence (GenAI) tools such as ChatGPT and Meta AI for self-diagnosis and health management.
Description
The survey was completed by 196 respondents, of whom 191 gave consent and are retained in the analytical sample; 146 reported having used GenAI for health purposes. Data collection covered demographic and screening information, usage narratives, access and equity barriers, trust and verification practices, and future expectations regarding AI in healthcare, gathered through closed and open ended questions.
Directly identifying information, including names and contact details, has been removed; contact details volunteered for optional follow up interviews were separated from responses prior to anonymisation. The dataset includes the cleaned survey responses, first pass content analysis codes, and the survey instrument, and supports the findings reported in "Bridge or Substitute? Generative AI, Self-Diagnosis and Health Equity among Nigerian University Students.
Links
Where it is published
- DOI doi.org/10.17632/htkthrgmkg.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Digital health · Earth & Environmental Science · Medicine & Health
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/htkthrgmkg.1 | 12 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:420302 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Digital Health'] |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |