Medical students’ knowledge, attitudes, and practices toward generative artificial intelligence in Egypt 2024: a Cross-Sectional study

Generative AI (GenAI) use is increasing across society in many different industries. Despite widespread adoption in workplaces, there is little consensus on the scope of its benefits and challenges at the level of most industries. Universities are being called upon to equip graduates with important knowledge and skills using GenAI for their professional contexts. Higher education, however, faces issues in effectively and sustainability embedding a use of GenAI in the student experience, which requires adjustments to learning and teaching activities, assessment, and learning outcomes and in access to useful GenAI platforms relevant to the various disciplines. As pedagogical models, ethical debates, and technologies continue to develop in this space, university teachers’ experiences of teaching with GenAI have yet to be explored in detail. Adopting a phenomenographic perspective, this study examines university teachers’ conceptions, perceptions, and approaches to using GenAI in teaching. Leveraging semi-structured interviews with 30 teaching academics, variations of teaching using GenAI were identified. Quantitative analysis was also conducted to capture the associations between these variations. By exploring the qualitative differences between these variations, a nuanced and important contribution to the GenAI discussion from the understanding of university teachers is uncovered. The results show that some ways of understanding and teaching with GenAI are more likely to help students develop effective knowledge and skills for the workplace than others. The findings also offer education leaders evidence to help design effective support for teachers using GenAI to innovate in the student experience. Through investigating the university teacher experience of GenAI, this research adds to the growing debate on the GenAI enabled benefits and challenges that are set to shape the higher education sector.

Generative AI (GenAI) is a disruptive technology likely to generate a major impact on faculty and learners in medical education. This work aims to measure the perception of GenAI among medical educators and to gain insights into its major advantages and concerns in medical education. A survey invitation was distributed to medical education faculty of colleges of allopathic and osteopathic medicine within a single university during the fall of 2023. The survey comprised 12 items, among those assessing the role of GenAI for students and educators, the need to modify teaching approaches, GenAI's perceived advantages, applications of GenAI in the educational context, and the concerns, challenges, and trustworthiness associated with GenAI. Responses were obtained from 48 faculty. They showed a positive attitude toward GenAI and disagreed on GenAI having a very negative effect on either the students' or faculty's educational experience. Eighty-five percent of our medical schools' faculty responded to had heard about GenAI, while 42% had not used it at all. Generating text (33%), automating repetitive tasks (19%), and creating multimedia content (17%) were some of the common utilizations of GenAI by school faculty. The majority agreed that GenAI is likely to change its role as an educator. A perceived advantage of GenAI in conducting more effective background research was reported by 54% of faculty. The greatest perceived strengths of GenAI were the ability to conduct more efficient research, task automation, and increased content accessibility. The faculty's major concerns were cheating in home assignments in assessment (97%), tendency for blunder and false information (95%), lack of context (86%), and removal of human interaction in important feedback processes (83%). The majority of the faculty agrees on the lack of guidelines for safe use of GenAI from both a governmental and an institutional policy. The main perceived challenges were cheating, the tendency of GenAI to make errors, and privacy concerns.The faculty recognized the potential impact of GenAI in medical education. Careful deliberation of the pros and cons of GenAI is needed for its effective integration into medical education. There is general agreement that plagiarism and lack of regulations are two major areas of concern. Consensus-based guidelines at the institutional and/or national level need to start to be implemented to govern the appropriate use of GenAI while maintaining ethics and transparency. Faculty responses reflect an optimistic and favorable outlook on GenAI's impact on student learning.

BackgroundArtificial intelligence (AI) is increasingly being integrated into medical education. As AI technologies continue to evolve, they are expected to enable more sophisticated student tutoring, performance evaluation, and reforms of curricula. However, medical education entities have been ill-prepared to embrace this technological revolution, and there is anxiety concerning its potential harm to the community.ObjectiveTo explore research trends in the field and identify future directions for AI-enabled medical education, we conducted a systematic bibliometric analysis focusing on temporal trajectories in the field.MethodsDocuments were collected from the Web of Science and Scopus databases covering the period from 2000 to 2024. A multistep search strategy combining information retrieval, a definitive journal list, and cocitation analysis was used to identify relevant publications. Journal and author impact were assessed using both publication and citation metrics. Research trends and hot spots were examined through citation burst detection, frequency analysis, and co-occurrence networks, with a color gradient used to indicate the average occurrence year of keywords. The citation lineage structure of the field was evaluated using a k-means clustering-based analysis of cocitation networks to trace influential references.ResultsOur analysis revealed a significant increase in publications since 2021, with foundational works emerging as early as 2019. Influential journals in this domain included JMIR Medical Education, Anatomical Sciences Education, and Medical Education. The evolving research trajectory exhibited a shift from conventional computer-assisted learning tools toward generative AI platforms. Earlier applications of AI in medical education were predominantly concentrated at the undergraduate level, indicating substantial potential for expansion into graduate and continuing medical education. Furthermore, limited cocitation connections were observed between recent generative AI research and conventional medical AI studies, and investigations into medical students’ attitudes toward generative AI remain scarce.ConclusionsThere are critical needs for (1) interdisciplinary studies that intentionally integrate generative AI with foundational medical AI work and (2) involving medical educators and students in AI development. Future research should focus on building theoretical frameworks and collaborative projects that connect these currently separate domains to foster a more cohesive knowledge base.

The incorporation of generative artificial intelligence in governance, political knowledge, electoral, and democratic processes is essential as the world transitions to a digital paradigm. Numerous nations have adopted Generative AI (GenAI), a disruptive technology that compels electoral bodies to advocate for the integration of such tools into governance, electoral, and democratic processes. Nevertheless, these technologies do not ensure effortless integration or efficient usage owing to intricate socio-cultural and human dynamics. Certain African jurisdictions are ill-prepared for the adoption of these technologies due to factors including underdevelopment, insufficient electrical supply, lack of technology literacy, reluctance to change, and the goals of governing parties. This study examines generative artificial intelligence as a disruptive technology for enhancing governance, political knowledge, electoral processes, and democracy. A mixed-method approach was employed, incorporating surveys and in-person interviews. The analysis of data, debates, and interpretation of findings were grounded in postdigital theory and theme analysis employing an abductive reasoning technique, in alignment with the tenets of critical realism. The study demonstrated that GENAI can influence political knowledge, election processes, and enhance efficiency in government and democracy. Moreover, GENAI, including ChatGPT, can either exacerbate or mitigate societal tendencies that contribute to human division, facilitate the dissemination of misinformation, perpetuate echo chambers, and undermine social and political trust, as well as polarise disparate groups or sets of viewpoints or beliefs. AI offers substantial opportunities but also poses many obstacles, including technical constraints, ethical dilemmas, and social ramifications. The swift progression of AI may disrupt labour markets by automating tasks conventionally executed by people, resulting in job displacement. Implementing AI necessitates significant upskilling and proficiency with digital tools; therefore, governments and organisations must adequately train their personnel to reconcile the disparity between AI's capabilities and users' comprehension. Additionally, there is a requisite for governmental oversight, regulation, and monitoring of AI adoption and utilisation across all facets of its implementation.

Background: Blood saves millions of life. It cannot be manufactured artificially. Young people are the hope and future of a safe blood supply in the world. So this study was conducted to know the knowledge, awareness and practices among medical students regarding blood donation. Aim & Objective: To study the level of knowledge, attitude and practices about blood donation among undergraduate medical students. To educate the students about blood donation. Settings and Design: The present study was carried out among MBBS students of UPUMS, Saifai. A cross-sectional study was conducted on 452 medical college students. Methods and Material: A pretested, semi-structured questionnaire was used for collecting the necessary information after getting informed consent. Statistical analysis used: Descriptive statistics was used to assess the level of knowledge, attitude and practice. Chi square test was applied to examine the association between knowledge level and other independent variables. Results: A questionnaire based survey among 452 medical students (59.5% males & 40.4% females) regarding blood donation revealed that majority knew about age and weight criteria (57.3% & 67.9% respectively). Of all 93% were willing to donate, while 36% had donated previously; out of which 52.7% had donated more than once. There is significant association between blood donation practice with academic year and gender. Conclusions: The study concludes that many of the students did not have adequate knowledge on blood donation but they have positive attitude towards blood donation. There is a need for education and motivation regarding blood donation through regular CMEs, seminars and campaigns

While industry practices evolve rapidly, marketing education in Australia and New Zealand faces challenges in keeping pace, particularly regarding the adoption of current marketing technologies (Harrigan et al., 2022). Generative AI, exemplified by systems like ChatGPT and DALL·E, has demonstrated benefits for learning (Baidoo-Anu & Ansah, 2023). However, despite its potential, there remains a dearth of practical guidance on effectively incorporating these technologies into marketing courses. This gap persists even as general frameworks for responsible and ethical AI use, such as the Australian Framework for Generative AI in Schools (2023), emerge. As the demand for graduates with generative AI skills grows in the job market, educators must explore innovative pedagogical approaches to bridge this gap. This academic poster presents an innovative application of generative artificial intelligence (GenAI) in the context of teaching digital marketing at the postgraduate level. Its purpose is to bridge the gap between academic theory and industry practice by encouraging educators to integrate AI tools into their curriculum through experiential learning pedagogy (Kolb, 2014), characterized by a learning process whereby knowledge is created through hands-on experiences. The poster exemplifies how various types of GenAI technologies — specifically text-based, image-based, and video-based — can enhance teaching content, tutorial exercises, and assessments within the digital marketing course. The poster showcases examples of how these GenAI tools are integrated in the course content, to guide students in generating innovative ideas for using AI in marketing to gain a competitive edge: Text-based GenAI: Tools like ChatGPT and Gemini can automatically generate search keywords for search engine marketing. By integrating text-based GenAI tools with established marketing technology (MarTech) tools such as Google Ads and Google Ads Keyword Planner, students engage in practical exercises that combine AI-generated initial ideas (e.g., search keywords) with further analysis (e.g., search volume, click-through rates, and bidding costs) using established MarTech tools. This hands-on approach enhances their learning experience and prepares them for real-world applications. Image-based GenAI: Platforms such as DALL·E, Midjourney, and Stable Diffusion enable the creation of custom images for display advertising, enhancing visual communication in marketing materials. Through experiential learning activities, students can explore ideas, seek unusual combinations, and inspire creativity faster with image-based GenAI tools, resulting in a greater variety of display ad materials. Video-based GenAI: Applications like Sora and Synthesia facilitate the production of short video clips suitable for social media marketing (e.g., YouTube Shorts, TikTok). By engaging in dynamic content creation exercises, students learn to streamline content creation, reduce manual work, and save both time and budget, thereby gaining practical skills in social media marketing. By incorporating these GenAI technologies through experiential learning pedagogy, educators can enrich the learning experience, foster critical thinking, and prepare students for the evolving landscape of digital marketing. Future research can study the use of GenAI in marketing education using theoretical frameworks such as the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2016).

INTRODUCTION: Prevention of disease is the necessity of today's life. Immunization is the most important component of preventive medicine. Knowledge and attitude of health professionals have significant role in increasing the acceptance of immunization. This study is aimed to determine the association between knowledge and attitude towards immunization and its practice among medical students and emphasis on the need of immunization education intervention among medical students.
 MATERIAL AND METHODS: Institutional based cross-sectional study among 397 medical students studying Bachelor in Medicine and Bachelor in Surgery (MBBS) was conducted in Universal College of Medical Sciences, Bhairahawa, Nepal. Purposively 1st to 4th year medical students were selected.
 RESULTS: Among 397 students, 59% had good knowledge regarding immunization, 63% had positive attitude and 47% had applied the knowledge and attitude in practice. Level of knowledge, attitude as well as practice regarding immunization was found statistically significant among medical students with their year of study. The analysis found that level of knowledge was more with 4th year students 89.47±7.92 and least with 1st year students 62.82±13.01. Third year and 4th year students had good attitude with mean score of 85.66±9.13 and 85.49 ± 9.51 respectively. Similarly, practice level was found more among 3rd and 4th year student, while least among 1st year students 39.89±21.16. There is statistically weekly positive correlation between knowledge, attitude and practice in overall among the medical students.
 CONCLUSION: The acceptance of immunization can be increased by increasing the level of knowledge and attitude regarding immunization thus providing a foundation to include a comprehensive immunization education to medical students.

This research looks at the potential effects of generative artificial intelligence AI on the country's media landscape. Given their pervasiveness, it aims to reveal how AI-powered technologies in media content creation, distribution, and personalisation contribute to the overall process of national progress. Using well-designed questionnaires, the study quantitatively collects data from media professionals, techies, and communication scholars in large cities throughout China. Using statistical tools such as structural equation modelling and regression analysis, one investigated the interplay between the rate of modernisation, the effects of national development, and AI-driven media innovation. Media indices of generative AI demonstrate a clear positive correlation with the effect of modernism and national development programs. As China strives to digitally change its communication infrastructure and increase its cultural influence, technological prowess, and media production, generative AI is playing an increasingly crucial role. This study shows that AI in media may lead to more dynamic stories, practical audience participation, and worldwide outreach, all thanks to modernist techniques. There is no part of this that does not contribute to the advancement of national development goals. The results provide policymakers, media outlets, and AI developers with valuable information for formulating strategies to integrate AI with sustainable development objectives. Via an experimental interaction between generative AI and national development perceived via a modernist lens, this study provides a framework for future research on new media technologies and national change. The discussion of the societal potential presented by AI may now begin.

The emergence of large language models (LLMs) has ushered in a new era of generative AI, exhibiting broad human-level capabilities and achieving meaningful progress toward Artificial General Intelligence (AGI). To realize AGI that truly benefits each individual, one next key direction for generative AI is to develop personal intelligence -understanding individuals and enhancing personal thinking, planning, and life experiences through personalization. Although evolving generative AI toward personal intelligence is emerging, it has attracted considerable interest from both research institutions and industry, even becoming a strategic direction for many companies. This workshop aims to provide a platform for discussing innovative ideas that facilitate personal intelligence with generative AI, 1) envisioning the future of personal intelligence powered by generative AI, 2) item establishing benchmarks for personal intelligence tasks, 3) advancing user modeling/personalization techniques for generative models/agents, 4) enhancing real-world applications, and 4) ensuring privacy and trustworthiness. This workshop aims to deepen understanding, accelerate progress, and support the transformative development of personal intelligence. The website for the workshop is: https://generative-rec.github.io/workshop-www25.

Background: A patient information leaflet (PIL) is a valuable tool that can convey basic information about the disease conditions and the recommended medication enabling both the patients and the health care professional to get rapid, easy, and precise access to the treatment process. Objective: To evaluate the level of knowledge and practices for appropriate and useful use of PIL among final-year medical and non-medical undergraduate university students in Baghdad, Iraq. Method: A descriptive, cross-sectional study was conducted among final-year undergraduate university students with different academic disciplines, including medical (pharmacy, dentistry) and non-medical disciplines (law, media) in Baghdad, Iraq, using a structured questionnaire to evaluate the level of knowledge and practices towards the proper use of PIL. Result: A total of 384 students enrolled in this study and the majority were medical students (59.1%). The proportion of non-medical students who read the PILs was lower than that of medical students (82.2% vs. 91.6%, p<0.0001). According to participants’ responses, 84.6% (p=0.03) of the medical students stated that reading PIL was useful for accurate medication use, while 60.5% of the non-medical students reported that the language of PIL was difficult to understand. Instructions for proper medication intake were significantly higher among the medical students (78%, p<0.0001). Conclusion: An acceptable level of knowledge along with several different practices toward the proper use of PIL while taking medicines was reported among medical and non-medical undergraduate university students.

The recognition of complementary and alternative medicine (CAM) is increasingly growing worldwide. Positive attitudes toward using CAM may reflect an evidence-based understanding and awareness of its common uses and potential abuses, facilitating its sound integration into the society for positive results. This study aimed to identify the level of knowledge, practices, and barriers associated with the use of CAM among medical and nonmedical students. A cross-sectional study was conducted between April 2023 and July 2023 involving a sample group of medical and nonmedical students from King Khalid University, Abha, Saudi Arabia. A total of 341 students completed the survey. Approximately 53.4% of the participants were medical and 46.6% were nonmedical students. Herbal medicine was the most used among medical students (21%) followed by aromatherapy (12%) and chiropractic (11%), while the most used CAM among nonmedical students was spiritual healing/Quran (19%). The prevalence of good knowledge is higher in medical students compared to nonmedical students in some CAM modalities. In addition, the results show that there are no significant differences in attitudes toward CAM among medical and nonmedical students. Respondents from both groups were keen on gaining more knowledge about all the CAM modalities. It is important to utilize the data from this study for enhancing curricula in university programs and promoting education and practice related to CAM.

The introduction of generative artificial intelligence (GenAI) has been met with a mix of reactions by higher education institutions, ranging from consternation and resistance to whole-hearted acceptance. Previous work has looked at the discourse and policies adopted by universities across the U.S. as well as educators, along with the inclusion of GenAI-related content and topics in higher education. Building on previous research, this study reports findings from a survey of engineering educators on their use of and perspectives toward generative AI. Specifically, we surveyed 98 educators from engineering, computer science, and education who participated in a workshop on GenAI in Engineering Education to learn about their perspectives on using these tools for teaching and research. We asked them about their use of and comfort with GenAI, their overall perspectives on GenAI, the challenges and potential harms of using it for teaching, learning, and research, and examined whether their approach to using and integrating GenAI in their classroom influenced their experiences with GenAI and perceptions of it. Consistent with other research in GenAI education, we found that while the majority of participants were somewhat familiar with GenAI, reported use varied considerably. We found that educators harbored mostly hopeful and positive views about the potential of GenAI. We also found that those who engaged more with their students on the topic of GenAI, both as communi-cators (those who spoke directly with their students) and as incorporators (those who included it in their syllabus), tend to be more positive about its contribution to learning, while also being more attuned to its potential abuses. These findings suggest that integrating and engaging with generative AI is essential to foster productive interactions between instructors and students around this technology. Our work ultimately contributes to the evolving discourse on GenAI use, integration, and avoidance within educational settings. Through exploratory quantitative research, we have identified specific areas for further investigation.

BackgroundAt the beginning of their clinical clerkships (CCs), medical students face multiple challenges related to acquiring clinical and communication skills, building professional relationships, and managing psychological stress. While mentoring and structured feedback are known to provide critical support, existing systems may not offer sufficient and timely guidance owing to the faculty’s limited availability. Generative artificial intelligence, particularly large language models, offers new opportunities to support medical education by providing context-sensitive responses.ObjectiveThis study aimed to develop a generative artificial intelligence CC mentor (AI-CCM) based on ChatGPT and evaluate its effectiveness in supporting medical students’ clinical learning, addressing their concerns, and supplementing human mentoring. The secondary objective was to compare AI-CCM’s educational value with responses from senior student mentors.MethodsWe conducted 2 studies. In study 1, we created 5 scenarios based on challenges that students commonly encountered during CCs. For each scenario, 5 senior student mentors and AI-CCM generated written advice. Five medical education experts evaluated these responses using a rubric to assess accuracy, practical utility, educational appropriateness (5-point Likert scale), and safety (binary scale). In study 2, a total of 17 fourth-year medical students used AI-CCM for 1 week during their CCs and completed a questionnaire evaluating its usefulness, clarity, emotional support, and impact on communication and learning (5-point Likert scale) informed by the technology acceptance model.ResultsAll results indicated that AI-CCM achieved higher mean scores than senior student mentors. AI-CCM responses were rated higher in educational appropriateness (4.2, SD 0.7 vs 3.8, SD 1.0; P=.001). No significant differences with senior student mentors were observed in accuracy (4.4, SD 0.7 vs 4.2, SD 0.9; P=.11) or practical utility (4.1, SD 0.7 vs 4.0, SD 0.9; P=.35). No safety concerns were identified in AI-CCM responses, whereas 2 concerns were noted in student mentors’ responses. Scenario-specific analysis revealed that AI-CCM performed substantially better in emotional and psychological stress scenarios. In the student trial, AI-CCM was rated as moderately useful (mean usefulness score 3.9, SD 1.1), with positive evaluations for clarity (4.0, SD 0.9) and emotional support (3.8, SD 1.1). However, aspects related to feedback guidance (2.9, SD 0.9) and anxiety reduction (3.2, SD 1.0) received more neutral ratings. Students primarily consulted AI-CCM regarding learning workload and communication difficulties; few students used it to address emotional stress–related issues.ConclusionsAI-CCM has the potential to serve as a supplementary educational partner during CCs, offering comparable support to that of senior student mentors in structured scenarios. Despite challenges of response latency and limited depth in clinical content, AI-CCM was received well by and accessible to students who used ChatGPT’s free version. With further refinements, including specialty-specific content and improved responsiveness, AI-CCM may serve as a scalable, context-sensitive support system in clinical medical education.

Background: The adequate knowledge about scabies and its preventive measures are important for diagnosis and managing scabies. Objectives: Evaluating the knowledge, attitude and practice of scabies among medical students in Kingdom of Saudi Arabia (KSA). Methods: A cross sectional study that was conducted at KSA, for 4 months from May to August 2018. The study included 445 medical Saudi students from both genders. A self-administrated questionnaire was distributed among all the participants. Conclusion: This study showed a satisfactory level of knowledge, attitude and practice among medical students in KSA regarding scabies, clinical characteristics and its preventive measures. Keywords: Knowledge, Attitude, Practice, scabies, medical students, Kingdom of Saudi Arabia (KSA). Ohoud Mohammed ALshehri1,Rawabi Abdullah Alharbi2, Bayan Mohammed ALsoraya3 1-Taif University, 2-Umm al qura University, 3-Qassim University (Unizah college of medicine) Results: The study included 445 medical students from different parts of KSA in which the level of knowledge among them regarding scabies and its preventive measures was adequate among most of the participants regarding the causative agents, features of scabies, its associated spreading factors and diagnosis. The attitude and practice of most of the subjects were positive.

Ethics deal with standards of conduct and moral judgment. Every day nurses require to make ethical decisions during patient care. They should have good knowledge and adequate practice of ethics to make ethical decisions. The aim of this study was to identify the knowledge and practice of patient care ethics among nurses. A descriptive cross sectional research design was used to conduct the study. Simple random sampling method was adopted to select 108 nurses among 133 nurses working in a regional hospital, Pokhara. Self-administered structured questionnaire schedule was used for data collection and analyzed using IBM SPSS Version 20. Descriptive and inferential statistics such as frequency, percentage, mean, standard deviation, Chi-square test was used to analyze the data. The findings revealed that 65.1 percent of nurses had satisfactory level knowledge and 76.4 percent had adequate practice level of patient care ethics. There was significant association between nurses knowledge level and professional qualification (p<.001). The level of practice does not have significant association with socio-demographic and job related variables. Similarly, no significant association between knowledge and practice level of patient care ethics was found. It concludes that the nurses with satisfactory level of knowledge and adequate level of practice are more than the nurses with unsatisfactory knowledge level and inadequate practice level of patient care ethics. Their practice of ethical principle is better than their knowledge in all principles except in the principle of justice. Nurses’ knowledge and practice of patient care ethics should be upgraded through educational and awareness programme. Janapriya Journal of Interdisciplinary Studies, Vol. 6 (December 2017), page: 17-28