Medical students showed favorable knowledge and positive attitudes, but their AI practices remained limited, indicating that integrating AI into medical curricula, including fundamentals, applications, and ethical aspects, is essential to prepare future physicians for AI-driven health care.
Abstract
Abstract Background In recent years, artificial intelligence (AI) has ushered in a promising era in medicine, particularly in medical education. However, studies assessing the knowledge, attitudes, and practices related to AI among medical students in Vietnam remain limited. Objective This study aimed to evaluate AI knowledge, attitudes, and practices among Vietnamese medical students in learning and research, and to identify factors associated with their AI practices. Methods A cross-sectional study was conducted among medical students at Thai Binh University of Medicine and Pharmacy from November to December 2025. Data were collected using an online structured questionnaire covering demographic characteristics and AI knowledge, attitudes, and practices. The main outcome of interest was AI practices in learning and research. Descriptive statistics and multivariable linear regression were used to examine associated factors. Regression coefficients (β), 95% CIs, and P values are reported. Results A total of 1002 medical students (mean age 21.00, IQR 19.00-23.00 years; n=596, 59.5% female) were included. The median percentage of maximum possible (POMP) score of AI knowledge was 66.67 (IQR 33.33‐83.33), with a high level of familiarity with common tools (n=798, 79.6%). AI attitudes were generally positive (median POMP score 70.00, IQR 53.33‐76.67). AI-related practices were lower (median POMP score 50.00, IQR 46.88-71.88), with AI being used primarily for information retrieval and literature research support. In the multivariable analysis, knowledge POMP score (β=0.12, 95% CI 0.08-0.16) and attitudes POMP score (β=0.42, 95% CI 0.34-0.51) were significantly associated with AI practices POMP score (P<.001). Age, gender, major, grade point average classification, and having participated in an AI seminar or training were not associated with AI practices. Conclusions Medical students showed favorable knowledge and positive attitudes, but their AI practices remained limited. Integrating AI into medical curricula, including fundamentals, applications, and ethical aspects, is essential to prepare future physicians for AI-driven health care.
Background: Artificial intelligence (AI), often termed the "fourth industrial revolution," is transforming healthcare by improving decision-making, diagnosis, and patient management. Despite its potential, understanding and integration of AI into medical education and practice remain limited, especially in resource-constrained regions. This study explores medical students' knowledge, attitudes, and practices concerning AI in a rural medical college in Haryana, India. Material and Methods: A cross-sectional online survey was conducted among 189 medical students at BhagatPhool Singh Government Medical College for Women, Haryana. Data were collected using a 13-item questionnaire on demographic details, knowledge, attitudes, and practices related to AI. Convenience sampling was employed, and data analysis was performed using SPSS v26.0. Frequency tables were used to summarize the findings. Results: Among respondents, 91.5% were aware of AI, yet only 53.4% knew about its medical applications. Most participants (81.5%) reported not being taught about AI during medical school, but 79.9% expressed an interest in learning more. While 76.7% agreed AI aids in early diagnosis, only 20.6% believed it could replace doctors. Regarding AI's potential burden, 18.5% agreed, while 45.5% remained neutral. For future practices, 51.9% showed willingness to work with AI, 66.7% believed it could aid in information gathering, and 78.8% thought AI would revolutionize medical teaching and research. Conclusion: The majority of medical students demonstrated a positive attitude toward AI and recognized its potential in healthcare, despite limited knowledge of its applications. Specific training and curriculum integration of AI in medical education are essential to prepare future doctors for the evolving digital landscape. Keywords: Artificial intelligence, medical education, medical students, rural healthcare, AI applications.
The findings highlight the need for a supportive educational environment with guidance to enable nursing students to use artificial intelligence appropriately and responsibly when needed, particularly among vocational college students and those from socioeconomically disadvantaged backgrounds.
Hui-Ying Fan, Qing Zhou, Lili Deng et al.· BMC Nursing· 0 citations
Background: Artificial intelligence (AI) is increasingly being used in medical education, offering opportunities for personalized learning, rapid access to information, and support for academic activities. However, concerns regarding accuracy, overdependence, and reduced critical thinking remain.
Objectives: To assess the perceptions, attitudes, perceived benefits and concerns regarding the use of AI tools among undergraduate medical students.
Methods: A cross-sectional study was conducted among 767 undergraduate medical students at a tertiary care teaching institution in Bharuch, Gujarat, India, from January to March 2026. Students from all MBBS years who provided informed consent were included. Data were collected using a pre-tested, semi-structured questionnaire administered through Google Forms. Descriptive statistics were used to summarize the findings as frequencies and percentages.
Results: Among 767 participants, AI use was reported daily by 207 (27.0%) students, on a few days per week by 282 (36.8%), and occasionally or rarely by 278 (36.2%). ChatGPT was the most commonly used AI tool reported by 698 (91.0%) students, followed by Google Gemini 398 (51.9%). The most common academic purpose of AI use was clarifying difficult concepts, reported by 561 (73.1%) students, followed by obtaining quick summaries or notes 460 (60.0%). AI was considered very helpful for understanding concepts by 445 (58.0%) students, while 515 (67.1%) reported faster learning. Nearly half 367 (47.8%) supported integrating AI into medical teaching. However, inaccurate information 334 (43.4%), reduced critical thinking 327 (42.6%), and overdependence 252 (32.8%) were major concerns.
Conclusions: AI tools are widely used and positively perceived by medical students. Structured and responsible integration of AI into medical education may maximize its benefits while minimizing potential risks.
Keywords: Artificial Intelligence, ChatGPT, Medical Education, Medical Students
Vaishali Patel, Vallari Jadav, Kuntal Patel· International journal of sci...· 0 citations
Artificial intelligence (AI) is rapidly transforming healthcare, medical education, and scientific research. As AI integration into medical education becomes inevitable, faculty development programs are needed to equip medical educators with the necessary knowledge, skills, and attitudes. This study aimed to analyze the AI training needs of faculty members and teaching assistants at the Alexandria Faculty of Medicine (AFM) as a crucial step in planning an AI faculty development program. A web-based cross-sectional survey was conducted to assess respondents’ current knowledge, attitudes and practices regarding the use of AI in their professional practice, along with their learning preferences. A total of 336 faculty members and teaching assistants completed the survey. Quantitative data were analyzed using descriptive statistics, while qualitative responses were summarized via content analysis. While 52.1% of respondents expressed a high interest in integrating AI into their professional practice and 55.6% considered learning about AI highly important, about 56.0% were unaware of AI uses in medicine, and 67.0% had never used AI applications in their work. Key barriers included limited access to AI tools (72.9%), insufficient knowledge (64%), and a lack of training opportunities (60.7%). Most respondents (84.2%) preferred workshop-based training. This study highlights the need for a faculty development program to develop AI competencies of faculty members to fully leverage AI tools and mitigate their limitations at AFM. The findings provide initial guidance for the planning of context‑appropriate AI faculty development initiatives for medical educators.
N. Elnemr, S. R. Aref, Aly Abdelmohsen et al.· Discover Education· 0 citations
Healthcare students had unsatisfactory awareness of AI, and their overall attitude was negative, highlighting an urgent need for an integrated AI curriculum tailored to their actual needs.
Waghachavare Vivek B., Dhobale Randhir V., Gore Alka D. et al.· International journal of com...· 0 citations
Background: Artificial intelligence (AI) is increasingly being applied in medicine for diagnosis, treatment, and decision-making. While enthusiasm for AI training among healthcare workers has been reported globally, little is known about awareness and attitudes in Afghanistan, where limited access to advanced diagnostic tools makes AI particularly valuable. Objective: This study aimed to assess the knowledge, attitude, and practices of AI among healthcare workers in Kabul City. Methods: A cross-sectional survey was conducted from January to February 2025 among 256 healthcare staff, including physicians, nurses, technicians, and administrative personnel. Data were collected using a structured questionnaire distributed online and in paper format. Responses were recorded on a three-point Likert scale. Statistical analysis was performed using SPSS version 26, employing descriptive statistics, chi-square tests, regression, and correlation analyses. Reliability was assessed using Cronbach’s alpha. Results: Of the participants, 71.1% were male (28.9% were female), and 43.8% were aged 21–29 years. Knowledge of AI was limited: only 1.6% demonstrated good knowledge, 44.7% poor knowledge, and 53.9% had insufficient knowledge. Attitudes were more favorable, with 47.3% expressing positive views, 37.5% somewhat agreeing, and 15.2% expressing negative views. Regression analysis revealed that age was significantly associated with knowledge scores, and knowledge strongly predicted positive attitudes. Reliability analysis confirmed acceptable internal consistency across domains (α ≥ 0.72). Conclusion: Knowledge of AI among medical staff in Kabul is limited, but attitudes are generally favorable. Structured training programs, conferences, and AI-enabled systems are needed to strengthen Afghanistan’s healthcare sector.
Ahmad Mustafa Rahimi, Abdul Bashir Bashari, M. Mohammadi et al.· Annals of Medicine and Surge...· 0 citations
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