Medicine Education Research Articles

Environmental sustainability in intensive care medicine

Intensive care medicine is an area with aparticularly high consumption of resources. This review presents important new findings relating to the environmental sustainability of intensive care medicine. For example, the drugs used in intensive care medicine can end up in the environment and cause relevant ecotoxicity. The consumption of material items is very high in intensive care medicine and the increasing replacement of reusable items by disposable items is amajor problem. Simple measures can reduce the ecological footprint of materials and introduce the recycling of waste in intensive care units. The high energy consumption of air conditioning, lighting and medical technology varies between facilities but in most cases is substantial and can be significantly reduced through appropriate measures. Ideally, the consumption should be measured and analyzed in detail. In the future, support from artificial intelligence is conceivable in this aspect. Sustainability must be given amuch higher priority in the training, continued and advanced education in intensive care medicine than it has been to date and in intensive care research sustainability aspects should be given equal consideration alongside economic aspects when it comes to assessing otherwise equivalent treatments. It is particularly important to avoid the misuse and overuse of intensive care. It brings no benefit to patients and hinders needs-based treatment that is oriented towards the patient's well-being. In addition, misuse and overuse increases costs and drives up the consumption of resources and thus the ecological footprint. Sustainability in the intensive care unit can only be achieved as ateam. Various approaches are presented on how anetworked Green Team can promote sustainability in the intensive care unit.

Neuraxial biomechanics, fluid dynamics, and myodural regulation: rethinking management of hypermobility and CNS disorders

Individuals with joint hypermobility and the Ehlers-Danlos Syndromes (EDS) are disproportionately affected by neuraxial dysfunction and Central Nervous System (CNS) disorders: such as Spontaneous Intracranial Hypotension (SIH) due to spinal cerebrospinal fluid (CSF) leaks, Upper Cervical Instability (UCI; including craniocervical or atlantoaxial instability (CCI/AAI)), Occult Tethered Cord Syndrome (TCS), Chiari Malformation (CM) and Idiopathic Intracranial Hypertension (IIH). The neuraxis comprises the parts of the nervous system (brain, nerves, spinal cord) along the craniospinal axis of the body. Neuraxial tissue includes all tissue structures that comprise, support, sheath, and connect along the neuraxis and peripheral nerves. Altered mechanical loading or vascular supply of neural structures can adversely impact neural health and conductivity, with local and remote effects on inflammation, venous congestion, and muscle control. With EDS characterized by altered structure of the connective tissues found throughout the body including the neural system, altered mechanical properties of the central nervous system (CNS) and its surrounding tissue structures are important considerations in the development and diagnostics of these CNS disorders, as well as response to therapeutic interventions. Experts have identified a need for neuraxial curriculum in medical education and hypermobility-adapted treatment approaches in pain management, neurosurgery, anesthesiology, hematology, gastrointestinal surgery, dermatology, cardiology, dentistry, gastroenterology, allergy/immunology, physical therapy, primary care, radiology and emergency medicine. This paper reviews the interactions between neuraxial biomechanics and pathology related to CNS disorders seen commonly with EDS. First, we provide a concise synthesis of the literature on neuraxial kinematics and fluid dynamics. We then discuss the interplay of these biomechanics and their involvement in clinically-relevant diagnoses and overlapping symptom presentations, modeling physiological reasoning to highlight knowledge gaps, support clinical decision-making, improve multidisciplinary management of hypermobility-associated complexity, and add weight to the call for medical education reform.

Pulmonary Embolism as a Cause of Death in Medico-legal Death in North of Jordan in the Period of 2017-2021

Background: Pulmonary embolism (PE) is a potentially fatal illness where blood clots block the arteries in the lungs. These clots typically come from the deep veins in the lower limbs. It is a significant contributor to illness and death on a global scale. Objective: This study aims to analyze the forensic deaths resulting from PE in the northern region of Jordan, namely those received at the Forensic Medicine Teaching Centre in Irbid, Jordan, between the years 2017 and 2021. Methods: A retrospective study was conducted to collect data from files of cases diagnosed with PE as a prime cause of death. The study sample included 80 cases of PE. A working Excel spreadsheet was created to collect data for all cases. Data analysis was made using the SPSS software version 21. Descriptive statistics were used to describe and represent data in tables. Result: During a span of 5 years, a total of 80 instances of death caused by PE were examined. Our study revealed that 55% of the cases were females, and the bulk of fatalities (67.6%) took place during the cold months of winter and fall. Regarding the age group, it was discovered that 46.3% of individuals fell within the age range of 25 to 45 years. 45% of the cases were not obese, and 81.3% of the cases had no history of prior surgery. Out of the total number of cases, 66.3% had not been immobilized. Additionally, 88.6% of the female cases were not pregnant, and 82.5% of cases did not have any prior trauma. Most individuals had large thromboembolism 56.3% and 70% of patients exhibited emboli in both pulmonary arteries. Out of all the patients, 76.3% exhibited lung congestion, whereas only 15% reported discharge. Conclusion: Multiple reasons cause PE deaths in northern Jordan. Female death rates rise somewhat, mostly among 25-45-year-olds. Recent surgery, trauma, and immobility dramatically affect PE death rates. Obese people had a lower PE mortality rate than non-obese people. Winter and fall have a somewhat greater PE rate than summer and spring.

Bioethics in the Teaching of Human Medicine

Bioethics in the Teaching of Human Medicine

Efficacy of Flipped Classroom and Didactic Lecture Approaches in Undergraduate Respiratory Medicine Education

ABSTRACT Background: This study used a mixed-methods design, analyzing quantitative pre- and post-assessment scores alongside qualitative student feedback. Undergraduate students in Respiratory Medicine were randomly assigned to either the Flipped Classroom or Didactic Lecture groups. Method: The study compares the effectiveness and perceived impact of the Flipped Classroom versus Didactic Lecture approaches in Undergraduate Respiratory Medicine Education. Results: The Flipped Classroom group showed significantly higher post-assessment scores and positive feedback, highlighting increased engagement, collaborative learning, and self-directed study. Conclusion: The study supports the effectiveness of the Flipped Classroom over traditional lectures, emphasizing active student involvement and personalized learning in Respiratory Medicine education.

Asian adult sleep medicine fellowship training curriculum: one curriculum, many contexts.

To develop a comprehensive Asian adult sleep medicine fellowship training curriculum to address the significant disparities in sleep medicine training across Asia, guided by the principle of "One Curriculum, Many Contexts," providing a standardized yet adaptable framework for sleep medicine education across the diverse healthcare landscapes of Asian countries. The curriculum development process involved a gap analysis, comprehensive literature review, and expert consensus through a modified RAND appropriateness method (RAM)/Delphi survey. The curriculum offers two flexible tracks: a one-year program (Track A) and a two-year program (Track B), accommodating varied educational pathways and healthcare system structures across Asia. Key features of the curriculum include detailed learning outcomes, competency-based educational content, and recommendations for teaching and learning activities. The assessment strategy incorporates summative and formative methods, with standard setting and program evaluation guidelines. The curriculum also provides recommendations for program accreditation, fellow-faculty ratios, and funding considerations. The Asian adult sleep medicine fellowship training curriculum provides a standardized yet adaptable framework for sleep medicine education across diverse Asian healthcare landscapes. By emphasizing flexibility and customization while maintaining high training standards, the curriculum aims to bridge the gap in sleep medicine training across Asia, ultimately improving the quality of sleep healthcare and patient outcomes throughout the region.

GENERAL MODEL OF ACHIEVING QUALITY AND EFFICIENCY IN TEACHING THE SCIENCE OF RADIATION MEDICINE AND TECHNOLOGIES IN HIGHER EDUCATION INSTITUTIONS

In this article, ways to achieve quality and efficiency in the teaching of radiation medicine and technologies in higher educational institutions, a model of the educational process that takes into account the high level of technologization of professional orientation in the training of medical physics specialists, its implementation or 's, as well as the most important components of increasing students' intellectual potential are highlighted.

A study on the Attitudes and Experiences of Korean Medicine College Students toward Integrated Education in the Acupuncture&Moxibustion Medicine and Korean Rehabilitation Medicine

Objectives: This study aimed to compare the satisfaction, comprehension levels of students taking integrated or non-integrated musculoskeletal education in Korean medicine colleges.Methods: We conducted a survey targeting third year students at University A taking musculoskeletal medicine (integrated education) and third year students at University A and third, fourth year students at University B taking acupuncture and moxibustion medicine and Korean rehabilitation medicine (separate education). The questionnaire, consisting of 25 items, was developed through consultation with faculty members in major of acupuncture or education. Questions include items related to general perceptions of the subjects, operation, and evaluation of the courses, and learning experiences. The collected data were analyzed through frequency analysis, t-test and Chi-square tests.Results: A total of 114 out of 217 people responded, of which 112 responses were valid. When comparing the comprehension of subjects, significant differences were mostly not observed. In other words, subject comprehension was found to have no correlation with the implementation of integrated education. In terms of the need for integrated education, the third year students at university B (non-integrated education / 5.0±0.7) showed significantly higher scores than the third year students at university A (integrated education / 4.2±1.4) (t=-2.594, p=0.012). Regarding the components for implementing integrated education, it was found that unification of learning tools such as textbooks and teaching methods is necessary.Conclusions: We conducted a survey to analyze students’ perceptions of musculoskeletal integration education. This study could be utilized not only in musculoskeletal medicine but also in future integrated education studies in Korean medicine.

Development of an LLM-based CPX Practicing Chatbot for Korean Medicine Education: Implementation of Automated Scoring and Feedback Generation Framework

Objectives: This study aimed to develop an AI-based CPX (Clinical Performance Examination) practicing chatbot for Korean medicine education, implementing automated quantitative scoring and qualitative feedback systems to enhance individualized learning experiences.Methods: Building upon a previously developed CPX practicing chatbot, we integrated a quantitative scoring system and a qualitative text feedback system using Large Language Models (LLMs). Scoring prompts and feedback prompts were designed based on standardized CPX scenarios. We compared the performance of OpenAI's GPT-4 and Anthropic's Claude-3.5-Sonnet models in terms of scoring accuracy, feedback quality, consistency, latency, and fluency. Three sample chat histories representing varying levels of student performance were created for evaluation.Results: Claude-3.5-Sonnet demonstrated perfect accuracy in quantitative scoring across all samples and faster execution times (average 43.2 seconds) compared to GPT-4. In qualitative feedback generation, GPT-4 provided more specific and actionable feedback, while Claude-3.5-Sonnet produced more natural and supportive language. By combining the strengths of both models, we implemented an optimized system that first uses GPT-4 for detailed feedback generation and then refines the language with Claude-3.5-Sonnet, resulting in accurate scoring and high-quality feedback.Conclusions: The study successfully developed an LLM-based CPX practicing chatbot that offers automated scoring and individualized feedback for Korean medicine education. The optimized system enhances the learning experience by providing accurate assessments and specific, supportive feedback, addressing limitations in current CPX education practices and resource constraints.

Artificial intelligence and pain medicine education: Benefits and pitfalls for the medical trainee.

Artificial intelligence (AI) represents an exciting and evolving technology that is increasingly being utilized across pain medicine. Large language models (LLMs) are one type of AI that has become particularly popular. Currently, there is a paucity of literature analyzing the impact that AI may have on trainee education. As such, we sought to assess the benefits and pitfalls that AI may have on pain medicine trainee education. Given the rapidly increasing popularity of LLMs, we particularly assessed how these LLMs may promote and hinder trainee education through a pilot quality improvement project. A comprehensive search of the existing literature regarding AI within medicine was performed to identify its potential benefits and pitfalls within pain medicine. The pilot project was approved by UPMC Quality Improvement Review Committee (#4547). Three of the most commonly utilized LLMs at the initiation of this pilot study - ChatGPT Plus, Google Bard, and Bing AI - were asked a series of multiple choice questions to evaluate their ability to assist in learner education within pain medicine. Potential benefits of AI within pain medicine trainee education include ease of use, imaging interpretation, procedural/surgical skills training, learner assessment, personalized learning experiences, ability to summarize vast amounts of knowledge, and preparation for the future of pain medicine. Potential pitfalls include discrepancies between AI devices and associated cost-differences, correlating radiographic findings to clinical significance, interpersonal/communication skills, educational disparities, bias/plagiarism/cheating concerns, lack of incorporation of private domain literature, and absence of training specifically for pain medicine education. Regarding the quality improvement project, ChatGPT Plus answered the highest percentage of all questions correctly (16/17). Lowest correctness scores by LLMs were in answering first-order questions, with Google Bard and Bing AI answering 4/9 and 3/9 first-order questions correctly, respectively. Qualitative evaluation of these LLM-provided explanations in answering second- and third-order questions revealed some reasoning inconsistencies (e.g., providing flawed information in selecting the correct answer). AI represents a continually evolving and promising modality to assist trainees pursuing a career in pain medicine. Still, limitations currently exist that may hinder their independent use in this setting. Future research exploring how AI may overcome these challenges is thus required. Until then, AI should be utilized as supplementary tool within pain medicine trainee education and with caution.

Educational Case Study of the Total Plate Count of Jamu Gendong in Cirebon City

Indonesian herbal heritage that still survives and continues to be preserved. Jamu that is very well known by the people of Indonesia is jamu gendong. Based on the Regulation of the Head of the Food and Drug Administration of the Republic of Indonesia number 12 of 2014 concerning traditional medicines that are prohibited from circulating, namely traditional medicines that do not meet the quality safety and usefulness requirements, one of which meets the TPC test requirements. The Total Plate Count (TPC) test is used to calculate the number of bacteria that grow and develop in a sample, as well as a reference for determining the quality and safety of simplisia. One of the regulations of the Food and Drug Supervisory Agency (BPOM) no 32 of 2019 concerning the safety and quality requirements of traditional medicines that in the process of making liquid preparations of internal medicine must meet the requirements of a total plate number value of r < 105 colonies / mL. The purpose of this study was to determine the TPC value before and after How to Make Good Fresh Herbal Medicine (CPJB) education and to determine the effect of CPJB education on jamu gendong rice kencur sellers in Kejaksan District and Kesambi District. Samples in this study were taken from 5 herbal medicine sellers. The results of this study showed the TPC value before CPJB education, sample 1 12 x 10-5, sample 2 1.4 x 10-4, sample 3 2.6 x 10-4, sample 4 3.6 x 10-4, sample 5 2.2 x 10-4. This study used leaflet media to conduct CPJB education. TPC value after CPJB education, in sample 1 amounted to 2.7 x 10-4. The conclusion of this study is that there is an effect of CPJB education on kencur rice herbal sellers, as evidenced by changes in TPC values before education and after education.

Impact of online expert interview-based research training on medical trainees’ knowledge and confidence: a mixed-methods design

BackgroundResearch training is important for medical trainees, because it improves their critical thinking, problem-solving, and the application of scientific principles to clinical practice. The COVID-19 Pandemic, which limited trainees’ access to hospitals, had also disrupted traditional research training. The International Emergency Medicine Education Project introduced the online Fundamentals of Research in Medicine course to support trainees. The course was designed as an expert interview. This format intended to foster a relaxed learning environment and promote experience sharing rather than transferring only factual information about research. This study assesses the course’s effect on participants’ perceived knowledge and confidence in research concepts.MethodsA prospective observational mixed-methods research was conducted through the International Emergency Medicine Education Project’s online platform. Pre- and post-course surveys measured participants’ perceived knowledge and confidence levels across 16 research-related topics. Quantitative survey data were analysed using the Wilcoxon Signed-Rank test, and qualitative feedback was evaluated to explore participants’ experiences.ResultsA total of 272 participants enrolled in the course. 168 participants started, and 52 (19.2%) completed the pre- and post-surveys and the course completion exam. Medical students and interns, as well as participants from Africa and Asia, comprised the majority. Most participants were from India. 78.8% of the participants were from low-income or lower-middle-income countries. Participants’ perceived knowledge and confidence significantly improved after completing the course, p < 0.001, with large effect sizes (-0.902 and − 0.819, respectively). Qualitative feedback highlighted the course’s clarity, simplicity, and effectiveness of the informal interview format. Some participants suggested adding more visual aids and detailed explanations for complex topics.ConclusionsThe online course, designed as an interview format, effectively enhanced participants’ perceived research knowledge and confidence. Future studies should incorporate objective measures of research skill acquisition from online courses and evaluate the long-term impact on participants’ academic and professional development.

Exploring Filipino Medical Students’ Attitudes and Perceptions of Artificial Intelligence in Medical Education: A Mixed-Methods Study

Background Artificial intelligence (AI) is emerging as one of the most revolutionary technologies shaping the educational system utilized by this generation of learners globally. AI enables opportunities for innovative learning experiences, while helping teachers devise teaching strategies through automation and intelligent tutoring systems. The integration of AI into medical education has potential for advancing health management frameworks and elevating the quality of patient care. However, developing countries, including the Philippines, face issues on equitable AI use. Furthermore, medical educators struggle in learning AI which imposes a challenge in teaching its use. To address this, the current study aims to investigate the current perceptions of medical students on the role of AI in medical education and practice of medicine. Methods The study utilized a mixed-methods approach to quantitatively and qualitatively assess the current attitudes and perceptions of medicine students of AI. Quantitative assessment was done via survey and qualitative analysis via focus group discussion. Participants were composed of 20 medical students from the College of Medicine, University of the Philippines Manila. Results Analysis of the attitudes and perceptions of Filipino medical students on AI showed that participants had a baseline understanding and awareness, but lack opportunities in studying medicine and clinical practice. Majority of participants recognize the advantages in medical education but have reservations on its overall application in a clinical setting. Conclusions The results of this investigation can direct future studies that aim to guide educators on the emerging role of AI in medical practice and the healthcare system, on its effect on physicians-in-training under contemporary medical educational practices. Findings from our study revealed key focal points which need to be sufficiently addressed in order to better equip medical students with knowledge, tools, and skills needed to utilize and integrate AI into their education and eventual practice as healthcare professionals.

Exploring Medical Trainees’ Perspectives on Narrative Medicine Education and Narrative Humility

Exploring Medical Trainees’ Perspectives on Narrative Medicine Education and Narrative Humility

When math legitimizes knowledge: a step by step approach to Bayes’ rule in diagnostic reasoning

INTRODUCTION: Many mistakes in clinical practice arise from confusing the probability of a positive test in those with the disease and the probability of having the disease in those who test positive. This misunderstanding leads to overestimating disease probability, diagnosing diseases in healthy individuals, ordering invasive diagnostic tests, and prescribing unnecessary treatments, resulting in unjustified adverse effect, psychological stress, and increased cost. Probabilistic reasoning is an essential skill to mitigate this confusion, and Bayes theorem is an important tool to accomplish this goal. OBJECTIVE: To present a step-by-step demonstration of Bayes' formula for positive and negative predictive values, fostering understanding and enabling its adoption in evidence-based medicine education and clinical practice as a supporting tool in the decision-making process. METHODS: In this article, we explain the difference between deductive and inductive thinking and how diagnostic reasoning is predominantly inductive, where evidence (the test result) is used to predict the cause (the presence of disease), a path that involves reverse probability, for which our reasoning is hazier. Through a clinical example involving the diagnosis of systemic lupus erythematosus, we use the Bayesian framework as a tool to help understand the difference between sensitivity/specificity (forward probability; deductive) and positive/negative predictive values (reverse probability: inductive). CONCLUSIONS: Excellent doctors are masters at applying Bayesian reasoning without using any formulas: they understand that the most important component of the diagnostic process is the reasoning that originates it and the resulting clinical decision depends on interpreting results considering their interaction with the context, not in isolation. Bad clinical reasoning results in bad clinical decisions, despite how accurate the diagnostic test: garbage in, garbage out. We hope our step-by-step approach to Bayes' rule can help demystify this powerful statistical tool and strengthen the idea that the value of a diagnostic test is directly proportional to the quality of clinical reasoning that led to its request.

Assessment of forensic medicine education impact on medical students' knowledge and specialisation attitudes: a multicenter analysis from Italian universities.

This study aimed to assess students' knowledge, awareness, and attitudes regarding forensic-medicine concepts taught during a Medicine and Surgery degree program at eight Italian universities. Additionally, the study aimed to evaluate the impact of the course on students' knowledge and attitudes toward choosing medical residency. A cross-sectional study was conducted through an anonymous web-based survey of medical students at eight italian universities. Descriptive, univariate, and logistic regression analyses were performed for the selected questions. The survey was completed by 1022 students. Forensic medicine appears to be important for providing training in the fundamental concepts of forensic medicine, especially professional liability, defensive medicine, and forensic pathology. The descriptive and univariate analyses demonstrate that the course can assist students in choosing their specialisation school. The multivariate analysis highlighted the impact of the forensic medicine course on orienting students' choice of medical residency, increasing it by nine times after attending the course. In the logistic regression analysis of the influence of medical liability on the choice of medical residency, students recognised a doubled effect after attending the course. Finally, the perceived usefulness of the course was significantly higher after attendance. Forensic medicine courses have the task of defining the duties and responsibilities of forensic physicians, providing indispensable tools for future medical practitioners regardless of their future specialisation, and limiting the increasing use of defensive medicine. In conclusion, it is imperative for governments to implement measures directed at diminishing the risk of burnout arising from the ongoing pressure associated with the fear of medicolegal litigation, encompassing both criminal and civil contexts.

Role of visual information in multimodal large language model performance: an evaluation using the Japanese nuclear medicine board examination.

This study aimed to assess the performance of state-of-the-art multimodal large language models (LLMs), specifically GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro, on Japanese Nuclear Medicine Board Examination (JNMBE) questions and to evaluate the influence of visual information on the decision-making process. This study utilized 92 questions with images from the JNMBE (2019-2023). The LLMs' responses were assessed under two conditions: providing both text and images and providing only text. Each model answered all questions thrice, and the most frequent answer choice was considered the final answer. The accuracy and agreement rates among the model answers were evaluated using statistical tests. GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro exhibited no significant differences in terms of accuracy between the text-and-image and text-only conditions. GPT-4o and Claude 3 Opus demonstrated accuracies of 54.3% (95% CI: 44.2%-64.1%) each when provided with both text and images; however, they selected the same options as in the text-only condition for 71.7% of the questions. Gemini 1.5 Pro performed significantly worse than GPT-4o under text and image conditions. The agreement rates among the model answers ranged from weak to moderate. The influence of images on decision-making in nuclear medicine is limited to the latest multimodal LLMs, and their diagnostic ability in this highly specialized field remains insufficient. Improving the utilization of image information and enhancing the answer reproducibility are crucial for the effective application of LLMs in nuclear medicine education and practice. Further advancements in these areas are necessary to harness the potential of LLMs as assistants in nuclear medicine diagnosis.

Precision education in medicine: A necessary transformation to better prepare physicians to meet the needs of their patients.

Precision education in medicine: A necessary transformation to better prepare physicians to meet the needs of their patients.

Undergraduate general medicine education in Japan: A nationwide cross‐sectional survey of medical trainees' perspectives

AbstractBackgroundThe 2022 revised version of the Model Core Curriculum (MCC) for Medical Education in Japan includes “generalism” as a new expertise quality and ability, based on the results of surveys of experts in health professions education. However, the perspectives of medical trainees under the pre‐2022 MCC revision were under‐examined. Here, we investigated what these trainees felt they had learned about general medicine (GM)‐related topics.MethodsWe performed a nationwide cross‐sectional study using an anonymous online questionnaire, which was developed with reference to the 2022 revised MCC. The questionnaire consisted of 14 items. For all items, we asked, “Did you learn enough during medical school?” Respondents were asked to respond on a 5‐point Likert scale (from 1 = strongly disagree to 5 = strongly agree).ResultsThree hundred and eighty‐six participants (response rate 55.4%) were included in the analysis. For the item “Behavioral science,” the number of participants who chose “3 = neither agree nor disagree” was highest, at 171 (44.3%) and with an average of 3.28, indicating that this item was perceived as insufficiently studied. Approximately half of the participants chose “4 = agree” for all items other than “Behavioral science.”ConclusionsThe study suggested that behavioral science may be underlearned among medical trainees of the pre‐2022 MCC generation. Medical educators in Japan should formulate curricula in accordance with the 2022 revision MCC and improve curricula regarding behavioral science. Future research should survey the generation of trainees who receive 2022 revision MCC‐compliant medical education; comparison of results with those of this study would be valuable in examining the effects of the revised guideline and inform international medical educators.

Coproducing a Faculty Feedback Program for School of Medicine Educators

Coproducing a Faculty Feedback Program for School of Medicine Educators