ArticleBMC medical education2026
Knowledge, perception, and attitude of healthcare students towards artificial intelligence: a multi-center cross sectional study.
Article in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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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Who cites it
3 citing papers in PubMed.
- Translation, cultural adaptation, and validation of the perceived Artificial Intelligence Literacy Questionnaire-6 (PAILQ-6) in Arabic-speaking pharmacists: A cross-sectional methodological study.Exploratory research in clinical and social pharmacy · 2026Article
- Artificial intelligence readiness and its association with artificial intelligence literacy among Chinese medical students: a latent profile analysis.Frontiers in public health · 2026Article
- Clinical nursing interns' perceptions of artificial intelligence-assisted tools in human-AI collaboration: a qualitative persona-based study.Frontiers in public health · 2026Article
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Authors and funding
3 authors.
Funding
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Abstract
backgroundArtificial intelligence (AI) is reshaping healthcare across various specialties. Thus, understanding how undergraduate students in healthcare specialties perceive and understand AI is important for evaluating their preparedness and digital competence as they enter clinical practice. This study aims to evaluate Jordanian undergraduate healthcare students’ knowledge, perceptions, and attitudes toward artificial intelligence in healthcare and examine their associations with demographic and educational characteristics.
methodsA cross-sectional, multi-center study was conducted between July and October 2025, using an online close-ended questionnaire distributed to undergraduate students from five colleges representing dentistry, nursing, medicine, and nutritional sciences across Jordan. The study assessed basic AI knowledge and prior exposure, measurement of perceptions of AI, and evaluation of attitudes toward AI in healthcare. Descriptive statistics were calculated and Analysis of Variance (ANOVA) assessed variation by demographic factors. Data analyses were completed through SPSS version 25.
resultsA total of 474 students participated. Overall, students expressed interest in AI and moderate confidence in its use, but the majority still lacks the organized conceptual knowledge, training, and practical awareness of AI in healthcare. The mean perception score was 46.25 ± 11.96, reflecting moderate confidence in AI’s ability to perform selected clinical and administrative tasks. Attitudes toward the impact of AI on healthcare professions were mixed (34.95 ± 26.55), while attitudes toward the future role and benefits of AI were generally positive (74.76 ± 25.46). Age, gender, university, and discipline were significantly associated with one or more of the investigated aspects (knowledge, attitudes, or perceptions).
conclusionHealthcare students in Jordan expressed clear interest in AI and were generally positive about AI’s future role, however, the majority lacked conceptual knowledge, structured training and was uncertain about its limitations and risks. This highlights the need to integrate AI competencies into undergraduate education, and establish clear ethical and regulatory guidance.
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