ArticleMedical science educator2025
Correlates of Medical and Allied Health Students' Engagement with Generative AI in Nigeria.
Article in Medical science educator, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- A scoping review of the use of generative artificial intelligence tools in health profession education.BMC medical education · 2026Article
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Authors and funding
13 authors.
Funding
Abstract
Introduction: 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. Methods: We used a cross-sectional mixed-methods study design and self-administered structured questionnaires, followed by in-depth interviews with a sub-sample ( Results: Of the 420 respondents, 77.4% ( Conclusion: 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.
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Registered trials
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