ArticleBMC medical education2025
AI usage among medical students in Palestine: a cross-sectional study and demonstration of AI-assisted research workflows.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- AI Tool Use Among Osteopathic Medical Students: Pilot Digital Diary Study.JMIR formative research · 2026Observational
- Current Status of Generative Artificial Intelligence Utilization in Medical Education: A Cross-Sectional Survey of Medical Students and Faculty.JMA journal · 2026Article
- Knowledge, Attitudes, and Practices Related to AI in Learning and Research Among Medical Students in Vietnam: Cross-Sectional Study.JMIR formative research · 2026Article
- The role of AI-mediated learning contexts in the personality-self-directed learning relationship among Chinese medical undergraduates: a cross-sectional study.BMC medical education · 2026Article
- The Presence and Nature of AI-Use Disclosure Statements in Medical Education Journals: A Bibliometric Study.Perspectives on medical education · 2026Article
- What Are the Opportunities and Challenges of Using AI in Medical Education in Vietnam?JMIR medical education · 2025Article
- Attitudes and perceptions of dental students towards artificial intelligence.BMC medical education · 2025Article
- Exploring the use and perceived impact of artificial intelligence in medical internship: a cross-sectional study of Palestinian doctors.Frontiers in artificial intelligence · 2025Article
- Artificial Intelligence in Healthcare: Awareness, Perceptions, and Future Perspectives of Palestinian Medical Students and Physicians.Journal of medical education and curricular developmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial Intelligence (AI) is transforming medical education globally, offering solutions to challenges such as resource limitations and limited clinical exposure. However, its integration in resource-constrained settings like Palestine remains underexplored. This study evaluates the prevalence, impact, and challenges of AI use among Palestinian medical students, focusing on academic performance, clinical competence, and research productivity.
methodsA cross-sectional study was conducted among 590 medical students from Palestinian universities. Data were collected using a validated electronic questionnaire, covering demographics, AI usage patterns, and perceived impacts across academic, clinical, and research domains. Initial analysis was conducted using AI tools, specifically ChatGPT, to facilitate insights and structure the results effectively. Statistical analyses were performed using IBM SPSS v27 to validate findings. Statistical significance was set at p < 0.05. The draft underwent detailed reviews by the research team to confirm accuracy and validity.
resultsAI adoption was high, with 87% of students frequently using tools like ChatGPT (76%) and virtual simulators (26%). Students reported significant improvements in academic performance (mean score: 4.2, SD = 0.7) and research productivity (mean score: 4.5, SD = 0.6), particularly in literature reviews and data analysis. Clinical competence received moderate ratings (mean score: 3.6, SD = 0.8), reflecting AI's limited role in practical skill development. Time management was highly rated (mean score: 4.6, SD = 0.5), highlighting AI's ability to automate repetitive tasks. Challenges included ethical concerns, data accuracy, and limited AI literacy, with 91% lacking formal AI training.
conclusionAI demonstrates significant potential to enhance medical education in resource-constrained settings by improving academic outcomes and research efficiency. ChatGPT played a critical role in this study, not only as a tool used by participants but also in the research process itself, including data analysis and manuscript drafting. These findings were cross-verified using SPSS to ensure robustness. Despite its promise, limitations in practical clinical applications and technical understanding highlight the need for targeted AI literacy programs and ethical guidelines. This study underscores the importance of integrating AI into medical curricula to address existing gaps and maximize its benefits in similar global contexts.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.