Lukas Weidener, Michael Fischer
The use of Artificial Intelligence (AI) in medicine, potentially leading to substantial advancements, such as improved diagnostics, has been of increased scientific and societal interest in recent years. However, the use of AI raises new ethical challenges, such as an increased risk of bias and potential discrimination of patients, as well as misdiagnoses potentially leading to over- or underdiagnosis with substantial consequences for patients. Recognizing these challenges, current research underscores the importance of integrating AI ethics into medical education...
January 29, 2024: JMIR Medical Education
Argyro Kavadella, Marco Antonio Dias da Silva, Eleftherios Kaklamanos, Vassilis Stamatopoulos, Kostis Giannakopoulos
BACKGROUND: The recently introduced Artificial Intelligence tool ChatGPT seems to offer a range of benefits in academic education, while also raising concerns. The relevant literature revolves around issues of plagiarism and academic dishonesty, as well as pedagogy and educational affordances, yet no real-life implementation of ChatGPT in the educational process has been reported to our knowledge so far. OBJECTIVE: The aim of this mixed-methods study was to evaluate ChatGPT's implementation in the educational process, both quantitatively and qualitatively...
December 11, 2023: JMIR Medical Education
Sarah Marie Jacobs, Neva Nicole Lundy, Saul Barry Issenberg, Latha Chandran
The proliferation of generative artificial intelligence (AI) and its extensive potential for integration into many aspects of healthcare signal a transformational shift within the healthcare environment. In this context, medical education must evolve to ensure that medical trainees are adequately prepared to navigate the rapidly changing healthcare landscape. Medical education has moved towards a competency-based education paradigm, leading the Association of American Medical Colleges (AAMC) to define a set of Entrustable Professional Activities (EPAs) as its practical operational framework in undergraduate medical education...
December 5, 2023: JMIR Medical Education
Kiyoshi Shikino, Yuji Nishizaki, Sho Fukui, Daiki Yokokawa, Yu Yamamoto, Hiroyuki Kobayashi, Taro Shimizu, Yasuharu Tokuda
BACKGROUND: Medical students in Japan undergo a 2-year postgraduate residency program to acquire clinical knowledge and general medical skills. The General Medicine In-Training Examination (GM-ITE) assesses postgraduate residents' clinical knowledge. A clinical simulation video (CSV) may assess learners' interpersonal abilities. OBJECTIVE: This study aimed to evaluate the relationship between GM-ITE scores and resident physicians' diagnostic skills by having them watch a CSV and to explore resident physicians' perceptions of the CSV's realism, educational value, and impact on their motivation to learn...
February 29, 2024: JMIR Medical Education
Amanda Willms, Sam Liu
BACKGROUND: Achieving physical activity (PA) guidelines' recommendation of 150 minutes of moderate-to-vigorous PA per week has been shown to reduce the risk of many chronic conditions. Despite the overwhelming evidence in this field, PA levels remain low globally. By creating engaging mobile health (mHealth) interventions through strategies such as just-in-time adaptive interventions (JITAIs) that are tailored to an individual's dynamic state, there is potential to increase PA levels...
February 29, 2024: JMIR Medical Education
Aidan Gilson, Conrad W Safranek, Thomas Huang, Vimig Socrates, Ling Chi, Richard Andrew Taylor, David Chartash
[This corrects the article DOI: 10.2196/45312.].
February 27, 2024: JMIR Medical Education
Chih-Wei Chen, Paul Walter, James Cheng-Chung Wei
The communication gap between patients and health care professionals has led to increased disputes and resource waste in the medical domain. The development of artificial intelligence and other technologies brings new possibilities to solve this problem. This viewpoint paper proposes a new relationship between patients and health care professionals-"shared decision-making"-allowing both sides to obtain a deeper understanding of the disease and reach a consensus during diagnosis and treatment. Then, this paper discusses the important impact of ChatGPT-like solutions in treating rheumatoid arthritis using methotrexate from clinical and patient perspectives...
February 27, 2024: JMIR Medical Education
Marko Marelić, Ksenija Klasnić, Tea Vukušić Rukavina
BACKGROUND: Previous studies have predominantly measured e-professionalism through perceptions or attitudes, yet there exists no validated measure specifically targeting the actual behaviors of health care professionals (HCPs) in this realm. This study addresses this gap by constructing a normative framework, drawing from 3 primary sources to define e-professional behavior across 6 domains. Four domains pertain to the dangers of social networking sites (SNSs), encompassing confidentiality, privacy, patient interaction, and equitable resource allocation...
February 27, 2024: JMIR Medical Education
Ajay Kumar, Pierce Burr, Tim Michael Young
Our research letter investigates the potential, as well as the current limitations, of widely available text-to-image tools in generating images for medical education. We focused on illustrations of important physical signs in the face (for which confidentiality issues in conventional patient photograph use may be a particular concern) that medics should know about, and we used facial images of hypothyroidism and Horner syndrome as examples.
February 22, 2024: JMIR Medical Education
Faiza Farhat, Beenish Moalla Chaudhry, Mohammad Nadeem, Shahab Saquib Sohail, Dag Øivind Madsen
BACKGROUND: Large language models (LLMs) have revolutionized natural language processing with their ability to generate human-like text through extensive training on large data sets. These models, including Generative Pre-trained Transformers (GPT)-3.5 (OpenAI), GPT-4 (OpenAI), and Bard (Google LLC), find applications beyond natural language processing, attracting interest from academia and industry. Students are actively leveraging LLMs to enhance learning experiences and prepare for high-stakes exams, such as the National Eligibility cum Entrance Test (NEET) in India...
February 21, 2024: JMIR Medical Education
Amish Acharya, Ruth Claire Black, Alisdair Smithies, Ara Darzi
BACKGROUND: The key to the digital leveling-up strategy of the National Health Service is the development of a digitally proficient leadership. The National Health Service Digital Academy (NHSDA) Digital Health Leadership program was designed to support emerging digital leaders to acquire the necessary skills to facilitate transformation. This study examined the influence of the program on professional identity formation as a means of creating a more proficient digital health leadership...
February 21, 2024: JMIR Medical Education
Susanne G Johnson, Birgitte Espehaug, Lillebeth Larun, Donna Ciliska, Nina Rydland Olsen
BACKGROUND: Evidence-based practice (EBP) is an important aspect of the health care education curriculum. EBP involves following the 5 EBP steps: ask, assess, appraise, apply, and audit. These 5 steps reflect the suggested core competencies covered in teaching and learning programs to support future health care professionals applying EBP. When implementing EBP teaching, assessing outcomes by documenting the student's performance and skills is relevant. This can be done using mobile devices...
February 21, 2024: JMIR Medical Education
Areeba Abid, Avinash Murugan, Imon Banerjee, Saptarshi Purkayastha, Hari Trivedi, Judy Gichoya
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are poised to have a substantial impact in the health care space. While a plethora of web-based resources exist to teach programming skills and ML model development, there are few introductory curricula specifically tailored to medical students without a background in data science or programming. Programs that do exist are often restricted to a specific specialty. OBJECTIVE: We hypothesized that a 1-month elective for fourth-year medical students, composed of high-quality existing web-based resources and a project-based structure, would empower students to learn about the impact of AI and ML in their chosen specialty and begin contributing to innovation in their field of interest...
February 20, 2024: JMIR Medical Education
Justina Yat Wa Liu, Pui Ying Mak, Kitty Chan, Daphne Sze Ki Cheung, Kin Cheung, Kenneth N K Fong, Patrick Pui Kin Kor, Timothy Kam Hung Lai, Tulio Maximo
BACKGROUND: Immersive virtual reality (IVR)-assisted experiential learning has the potential to foster empathy among undergraduate health care students toward older adults with cognitive impairment by facilitating a sense of embodiment. However, the extent of its effectiveness, including enhancing students' learning experiences and achieving intended learning outcomes, remains underexplored. OBJECTIVE: This study aims to evaluate the impacts of IVR-assisted experiential learning on the empathy of undergraduate health care students toward older people with cognitive impairment as the primary outcome (objective 1) and on their learning experience (objective 2) and their attainment of learning outcomes as the secondary outcomes (objective 3)...
February 15, 2024: JMIR Medical Education
Tassallah Abdullahi, Ritambhara Singh, Carsten Eickhoff
BACKGROUND: Patients with rare and complex diseases often experience delayed diagnoses and misdiagnoses because comprehensive knowledge about these diseases is limited to only a few medical experts. In this context, large language models (LLMs) have emerged as powerful knowledge aggregation tools with applications in clinical decision support and education domains. OBJECTIVE: This study aims to explore the potential of 3 popular LLMs, namely Bard (Google LLC), ChatGPT-3...
February 13, 2024: JMIR Medical Education
Guido Giunti, Colin P Doherty
BACKGROUND: The use of mobile devices for delivering health-related services (mobile health [mHealth]) has rapidly increased, leading to a demand for summarizing the state of the art and practice through systematic reviews. However, the systematic review process is a resource-intensive and time-consuming process. Generative artificial intelligence (AI) has emerged as a potential solution to automate tedious tasks. OBJECTIVE: This study aimed to explore the feasibility of using generative AI tools to automate time-consuming and resource-intensive tasks in a systematic review process and assess the scope and limitations of using such tools...
February 12, 2024: JMIR Medical Education
Peng Yu, Changchang Fang, Xiaolin Liu, Wanying Fu, Jitao Ling, Zhiwei Yan, Yuan Jiang, Zhengyu Cao, Maoxiong Wu, Zhiteng Chen, Wengen Zhu, Yuling Zhang, Ayiguli Abudukeremu, Yue Wang, Xiao Liu, Jingfeng Wang
BACKGROUND: ChatGPT, an artificial intelligence (AI) based on large-scale language models, has sparked interest in the field of health care. Nonetheless, the capabilities of AI in text comprehension and generation are constrained by the quality and volume of available training data for a specific language, and the performance of AI across different languages requires further investigation. While AI harbors substantial potential in medicine, it is imperative to tackle challenges such as the formulation of clinical care standards; facilitating cultural transitions in medical education and practice; and managing ethical issues including data privacy, consent, and bias...
February 9, 2024: JMIR Medical Education
Annika Meyer, Janik Riese, Thomas Streichert
BACKGROUND: The potential of artificial intelligence (AI)-based large language models, such as ChatGPT, has gained significant attention in the medical field. This enthusiasm is driven not only by recent breakthroughs and improved accessibility, but also by the prospect of democratizing medical knowledge and promoting equitable health care. However, the performance of ChatGPT is substantially influenced by the input language, and given the growing public trust in this AI tool compared to that in traditional sources of information, investigating its medical accuracy across different languages is of particular importance...
February 8, 2024: JMIR Medical Education
Megan Gray, Austin Baird, Taylor Sawyer, Jasmine James, Thea DeBroux, Michelle Bartlett, Jeanne Krick, Rachel Umoren
BACKGROUND: Using virtual patients, facilitated by natural language processing, provides a valuable educational experience for learners. Generating a large, varied sample of realistic and appropriate responses for virtual patients is challenging. Artificial intelligence (AI) programs can be a viable source for these responses, but their utility for this purpose has not been explored. OBJECTIVE: In this study, we explored the effectiveness of generative AI (ChatGPT) in developing realistic virtual standardized patient dialogues to teach prenatal counseling skills...
February 1, 2024: JMIR Medical Education
Wei How Darryl Ang, Zhi Qi Grace Lim, Siew Tiang Lau, Jie Dong, Ying Lau
BACKGROUND: The COVID-19 pandemic has resulted in a greater workload in the health care system. Therefore, health care professionals (HCPs) continue to experience high levels of stress, resulting in mental health disorders. From a preventive perspective, building resilience has been associated with reduced stress and mental health disorders and promotes HCPs' intent to stay. Despite the benefits of resilience training, few studies provided an in-depth understanding of the contextual factors, implementation, and mechanisms of impact that influences the sustainability of resilience programs...
January 31, 2024: JMIR Medical Education
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