パレスチナの医学生を対象とした人工知能の利用とその認識された影響に関する横断研究

Artificial intelligence (AI) is increasingly used in medical education to support academic learning, clinical competence, and efficiency. However, the extent and impact of AI usage among medical interns, particularly in Palestine, remain underexplored.

This study aimed to assess the prevalence of AI usage among internship doctors in Palestine and evaluate its perceived impact on their academic performance, clinical competence, time management, and research skills.

A cross-sectional survey was conducted with 307 internship doctors in Palestine. The survey collected data on the frequency and types of AI tools used, including ChatGPT, and interns' perceptions of AI's impact on their training. Demographic information, such as age, gender, and university affiliation, was also gathered to explore potential associations with AI usage patterns.

The study found that 76.9% of interns used AI regularly, with ChatGPT being the most popular tool (76.2%). Despite frequent use, only 3.3% reported formal AI training. The majority of interns perceived AI as beneficial in improving academic performance (61%), clinical competence (67%), and time management (74%). Notably, time management showed the highest perceived improvement. However, 75.9% expressed concerns about becoming overly reliant on AI, fearing it could diminish critical thinking and clinical judgment. Age and university affiliation were associated with differences in AI usage patterns and perceived benefits, with older interns and those from international universities reporting greater perceived improvements.

This cross-sectional study highlights the widespread use of AI among internship doctors in Palestine and generally positive perceptions of its educational value, particularly for academic performance and clinical competence. However, it also reveals a substantial gap in formal AI training, suggesting a need for structured, ethically grounded AI education in medical curricula. Because the study is exploratory and cross-sectional, these findings should be interpreted as perceived associations rather than evidence that AI use or training causes improved outcomes; future longitudinal and interventional studies are needed to clarify long term effects.