Correlates of Medical and Allied Health Students' Engagement with Generative AI in Nigeria

The extent of artificial intelligence (AI) engagement and factors influencing its use among medical and allied health students in low-resource settings are not well documented. We assessed the knowledge and correlates of ChatGPT use among medical, dental, and allied health students in Nigeria.

We used a cross-sectional mixed-methods study design and self-administered structured questionnaires, followed by in-depth interviews with a sub-sample (n = 20) of students. We employed logistic regression models to generate adjusted odds ratios, and thematic analysis to identify key factors.

Of the 420 respondents, 77.4% (n = 325) demonstrated moderate to good knowledge of ChatGPT. Most respondents (61.9%, n = 260) reported prior ChatGPT use in medical education, motivated mainly by ease of use (75.0%) and efficiency (72.1%). Major concerns included risk of dependency (65.0%), inaccuracy (49.7%), doubts about reliability (49.3%), and ethical issues (41.7%). ChatGPT use was more likely among male students (adjusted odds ratio (aOR) = 1.62, 95% confidence interval (95%CI) 1.13-3.72), older cohorts (≥ 25 years) (aOR = 1.74, 95%CI 1.16-4.50), final-year students (aOR = 2.46, 95%CI 1.12-5.67), those with good knowledge (aOR = 3.27, 95%CI 1.59-7.36), and those with positive attitudes (aOR = 4.29, 95%CI 1.92-8.56). Qualitative themes reinforced concerns about errors, ethics, and infrastructure limitations.

We found moderate knowledge and engagement with ChatGPT among medical and allied health students in Nigeria. Engagement was influenced by gender, age, year of study, knowledge, and attitude. Targeted education and guidelines for responsible AI use will be important in shaping the future of medical and health professional education in similar settings.