AI usage among medical students in Palestine: a cross-sectional study and demonstration of AI-assisted research workflows | BMC Medical Education

This study offers an in-depth look at how medical students in Palestine integrate artificial intelligence (AI) tools into their academic and clinical training. A unique aspect of the project was the active role of AI in the research process itself: from drafting the questionnaire to performing data analyses and assisting in manuscript preparation. Such involvement not only streamlined the workflow but also illustrated AI’s capacity to minimize human labor in certain stages of research. Consistent with emerging global trends, these findings underscore the versatile potential of AI in both scholarly work and medical training, especially as healthcare systems worldwide move toward digital transformation [7]. Yet, the results also raise important questions regarding equity, ethics, and the broader educational framework necessary to ensure effective AI adoption.

The sample of 550 students provided a comprehensive representation of Palestinian medical trainees at various stages of preclinical, clinical, and internship. Although the majority reported substantial usage of AI tools, more frequent use was noted among certain subgroups. These patterns suggest that AI’s value depends considerably on the learners’ evolving academic requirements: as students advance through their training, they tend to encounter more tasks where AI-driven support proves beneficial. Indeed, senior students and interns commonly described AI-based applications that expedite literature reviews, manuscript drafting, and exam preparation, aligning with evidence from multiple regions in the Middle East where near-graduation students often seek additional resources for research collaboration and practice-oriented learning [8].

AI in research execution

Perhaps most striking was the manner in which AI systems bolstered this very study. Leveraging AI to generate the questionnaire minimized subjective bias in survey-question wording and expedited item design, thereby offering a glimpse of how future research might be optimized [9]. After data collection, automated algorithms handled tasks such as descriptive statistics, thematic categorization of qualitative responses, and preliminary drafts of sections in this manuscript. These efficiencies echo prior studies that used AI-assisted literature mining or machine learning–based text generation to reduce the timeline for academic deliverables [10]. Despite these advantages, caution remains warranted. Algorithms, while time-saving, can inadvertently introduce errors or biases if not carefully supervised. For instance, AI language models may produce misleading references or incomplete content if their training data is not adequately validated [11]. The present study addressed this by subjecting AI outputs to rigorous manual review, an approach that may serve as a template for responsible AI adoption in future scholarly endeavors.

AI usage patterns and impact

In examining the prevalence and variety of AI tools, respondents predominantly used ChatGPT for academic tasks, while automated coding platforms (e.g., Copilot) and clinical simulators were also frequently mentioned. This aligns with global observations that large language models have quickly become favored among students due to their user-friendly interfaces and high adaptability [12]. Surveyed students generally believed AI contributed positively to both academic performance and research productivity, a finding bolstered by statistical analyses indicating a correlation between frequent AI usage and improvements in relevant skill domains. These quantitative data reinforce the idea that strategic adoption of AI can support deeper learning, more comprehensive research inquiries, and faster mastery of certain theoretical concepts. Furthermore, respondents reported that AI tools freed them from routine or repetitive work such as formatting bibliographies leading to greater focus on critical thinking and practical competencies.

Nonetheless, the perceived influence of AI on clinical competence was somewhat mixed. Although students recognized potential benefits, such as clinical decision support tools or virtual simulators, they also acknowledged AI’s limited capacity in teaching the hands-on elements of physical examinations and other procedural skills. This ambivalence aligns with prior research showing that while AI can excel at providing structured factual knowledge or diagnostic suggestions, it has yet to replicate the nuanced, interpersonal aspects of clinical practice [2]. In more resource-limited settings where direct patient interaction can be constrained AI might serve as a supplemental resource but must be carefully integrated to avoid fostering overreliance or neglecting the development of students’ clinical intuition [13].

Challenges and limitations of AI adoption

Despite the generally positive sentiment, nearly half of the respondents encountered at least one significant difficulty with AI deployment. Qualitative responses underscored three core themes: trust and accuracy issues, accessibility barriers, and ethical considerations. Concerns over reliability align with a broader global discourse cautioning that AI-generated content may contain inaccuracies or unverified assumptions [14]. Students, while appreciative of AI’s efficiency, felt uneasy about blindly accepting its suggestions. This underscores the importance of critical evaluation and the necessity for rigorous methods to confirm AI-derived insights. In contexts like Palestine and neighboring regions with variable internet infrastructure, students also cited technological constraints that hamper the seamless use of more sophisticated AI utilities. Such barriers illustrate that AI’s benefits can be unevenly distributed within the same cohort, dependent on local factors like network connectivity and hardware availability [15].

The third theme of ethical and educational implications echoes calls for robust guidance on academic honesty and appropriate utilization of AI. Automated tools pose new forms of ethical quandaries, particularly regarding originality, plagiarism, and professional integrity [16]. Students who rely excessively on AI-generated answers for assignments risk impeding their own intellectual growth. This potential decline in critical reasoning is a worrying sign that must be tackled through explicit university policies defining boundaries, clarifying citation requirements, and providing instructions on verifying AI outputs. Multiple institutions across the Middle East are experimenting with codes of conduct tailored to AI usage, informed by both international guidelines and cultural priorities [17]. Such protocols ensure that future physicians harness AI to augment but never supplant the human dimension of healthcare.

AI in Palestine and the middle East

Within Palestine, expanding AI-based educational opportunities is particularly salient, as national initiatives seek to revamp digital infrastructure and improve overall healthcare delivery. Researchers have noted a growing appetite for AI integration in medical schools across the Middle East, partly spurred by cross-border collaborations and an eagerness to keep pace with more technologically advanced regions [8, 18]. Participants in this study who had collaborated with peers or faculty abroad described experiences that broadened their exposure to AI tools not easily accessible within Palestine. While this highlights avenues for global partnerships, it also underscores local disparities in resource allocation. Institutions aiming to incorporate advanced platforms into their curricula must balance cost considerations, faculty training needs, and alignment with accreditation standards [19]. In Jordan, for example, certain universities have introduced elective courses emphasizing machine learning basics or invited guest lecturers from data science departments. Early evaluations of these efforts suggest that structured AI curricula can cultivate more confident and ethically aware graduates who can harness new technologies responsibly [8].

Similar ambitions resonate across medical schools in Saudi Arabia, Egypt, and the United Arab Emirates, which have begun exploring AI-driven simulations and telemedicine frameworks [12, 20]. These expansions show that the Palestinian context is not isolated; it stands alongside a regional shift toward digital transformation. Yet, the journey is far from complete. Many programs remain in pilot phases, lacking the robust infrastructure, trained instructors, and standardization necessary for large-scale impact. Encouragingly, the demand from students evident in their readiness to adopt AI solutions provides strong motivation for academic leaders to secure funding, equip labs, and design specialized courses.

AI in research writing and data analysis

That AI can assist in automating literature reviews, generating structured reports, and performing statistical analyses is of particular interest to students in research-heavy contexts. In this study, students who leveraged AI for drafting manuscripts found it helped them identify relevant studies faster while refining their own writing. These observations mirror findings from multiple global surveys, where medical students credited AI-based writing assistance with enhanced clarity, better organization of ideas, and improved literature search capabilities [10, 12]. However, educators caution that delegating extensive tasks like result interpretation or full manuscript composition could undermine a student’s development of essential research skills [16]. Thoughtful policies that require students to maintain full accountability over their final products might serve as an effective middle ground, allowing them to benefit from AI’s efficiency without bypassing the intellectual rigor of independent inquiry.

Moreover, the reliability of AI in data analysis hinges on the model and the data used to train it. If the model lacks exposure to medical contexts relevant to Palestinian populations, it may produce skewed results or incomplete insight. This becomes especially critical in clinical research, where population-specific factors (genetic, environmental, or cultural) influence disease patterns and outcomes [13, 14]. Consequently, local collaborations that refine AI tools for Palestinian demographics could lead to more accurate analytics, strengthen the validity of findings, and increase the acceptability of AI-based methods among students and faculty.

Limitations and future directions

Several considerations limit the generalizability of these results. Although participants represented multiple universities in Palestine, further expansion to other regions or private institutions could yield different outcomes, especially if resource availability varies. The study’s reliance on self-reported measures of AI proficiency and impact introduces the possibility of social desirability bias, where students may overestimate positive experiences. Moreover, while the role of AI in executing the research highlights its practicality, it also raises questions about the potential for automation bias or errors if human oversight is insufficient [11]. Future inquiries might consider longitudinal designs to track how students’ perceptions and competencies evolve as AI tools become increasingly embedded in educational frameworks.

Notwithstanding these caveats, the data imply that AI’s integration is largely welcomed by Palestinian medical students, provided it is accompanied by relevant training and clear ethical guidelines. The next steps will likely involve formalizing AI instruction within the curriculum, encouraging interdisciplinary collaborations with computer science departments, and establishing institutional policies for responsible AI usage [17]. As these changes unfold, schools can conduct follow-up studies to evaluate whether the introduction of AI-specific courses measurably boosts student competence and confidence. The prospect of further refining AI algorithms to reflect localized epidemiological data could improve clinical simulations and research reliability, ultimately strengthening the quality of medical education in Palestine.