Weight mitigation and tolerability of adjunctive topiramate in acute pediatric psychiatry: a retrospective real-world analysis.

Artificial Intelligence (AI) is broadly defined as the simulation of human intelligence by systems capable of perception, reasoning, learning, planning, and prediction (). Generative AI (GenAI) and Large Language Models (LLMs) are presently reshaping higher education in a way that is considered transformative as the internet's inception (, ). In health professions education (HPE), GenAI is used for several educational processes such as resource development and delivery, personalizing learning, assessments, providing feedback and formulating evaluation and to a lesser extend for curriculum design (). Gen AI is perceived to be user friendly and is seen to be transformative by both faculty and students. Studies report that a large majority of university students (80%–86%) use AI tools for learning, such as creating resources, to seek feedback for communication skills and exercises in humanities, support their self-directed learning for exam preparation, as well as for research and publications for writing assistance, and data analysis (–). Educational chatbots using GenAI like ChatGPT are used by medical and dental students as virtual patients creating clinical scenarios allowing practice of history taking, diagnostic reasoning and treatment planning (). These experiences were perceived to be more satisfying, less stressful and improved their motivation and engagement (). A study comparing learning outcomes amongst dental students found better results among those who used ChatGPT for test preparation (). Studies have shown that patients use GenAI, mostly ChatGPT and Google Gemini, to obtain health information, seek explanation of symptoms experienced and their self-management. The most common reasons cited are easy accessibility, speed of response and a perception of empathy in the results received (). However, the extent of its use is determined by the educational level, field of expertise and awareness of AI tools and its use (). However, some unsettling limitations and challenges faced with the use of GenAI are the generation of fake information, overdependence and academic dishonesty. The term “hallucination” is used to describe the phenomenon of misinformation with a clear explanation and fabrication of citations and references. This results in the propagation of the deceptive or biased information, especially if the student does not verify the authenticity of the generated content (, ). Additionally, the information generated in response to prompts in some areas may be biased or based on old information or errors in training, resulting in misinformation; the latest research may add a layer of clarification or even contradict an existing concept (, , ). Overreliance on GenAI without actually investing efforts to learn or complete assigned tasks reduces the effectiveness of the learning exercise (). Academic integrity, an important criterion for professionalism, may be breached when students use AI to cheat in exams or plagiarize academic work (, ). Some researchers also argue that the use of GenAI removes the human perspective from the learning experience due to its capabilities being limited to a textual format and its inability to identify or interpret nonverbal cues, which in some students may have a detrimental effect (, ). A study on measurable impacts of AI based strategies on educational outcomes in HPE, showed that the strength of evidence is poor, and there is a lack of guidelines and criteria to evaluate the impact (). Further, it suggests that AI integration should be attempted in blended learning environments to add the benefit of human interaction. With increasing use of GenAI in education, another growing concern regarding its negative effect on the learning process is the limited use of critical reasoning and problem-solving skills, because of AI dependency and lack of human interaction, crucial for communication and patient interactions and a student's transition to a professional (–). AI is progressively becoming integrated into current dental workflows, particularly in diagnosis, treatment design, and predictive models of disease (). These evolving technologies are transforming clinical practice, alongside a shift in the core competencies demanded by future dental practitioners ().