AI readiness at Buea Regional Hospital
A 387-respondent study of what health workers actually know and feel about AI in clinical decisions, and what is really blocking it.
Principal investigator
- 387 respondents
- 92.4% response rate
- Six professional cadres
- First baseline for the hospital
Problem
Everyone talks about whether African health workers will accept AI. Almost nobody had measured it at a specific hospital, cadre by cadre.
Why it matters
Without a profession-by-profession baseline, any AI rollout at a hospital like this is guesswork, and when it fails, the failure gets blamed on staff resistance that was never actually measured.
My role
Principal investigator, for my BSc nursing research at Gracious Higher Institute of Excellence, supervised by Mr Boris Eko. The full title is “Knowledge, Attitude and Factors Influencing the Implementation of Artificial Intelligence in Clinical Decision-Making Among Health Professionals at Buea Regional Hospital.”
Stack
KoboToolbox for data collection. SPSS for statistical analysis.
Challenges
Existing instruments ask about AI in computer science vocabulary, which measures whether a respondent recognises jargon rather than whether they understand what the technology does. I built a custom KAP questionnaire testing concrete, awareness-level statements instead, for a low digital literacy context.
Screenshots
Not applicable. This is a research study, not a software product. See the full dissertation for the complete methodology.
Architecture
419 questionnaires went out across six professional cadres at Buea Regional Hospital. 387 came back complete and consented, a 92.4% response rate, above the 377 minimum the sample size calculation required. Analysis ran in SPSS with significance at p < 0.05.
Outcome
The staff at Buea Regional Hospital are not resistant to AI. They are under-trained and under-equipped, and they know it. That changes the local problem from persuasion to provision.
Knowledge was moderate, averaging 61.3%. Attitudes were cautiously optimistic at 30.7% positive, 66.9% moderate, 2.3% negative. When staff rated what would actually influence their use of AI, the top four were reliable electricity, cost, reliable internet, and access to computers. Fear of losing their job ranked dead last out of eighteen factors.
Lessons learned
Attitude turned out not to be a fixed trait. Positive attitude climbed from 1.8% among those with poor knowledge to 57.1% among those with good knowledge. Exposure raises knowledge, knowledge raises attitude. It can be moved.
Read the full dissertation on the research page.