Journal of CME最新文献

{"title":"Cumulative Cognition: Strengthening Learning with Progressive Content Delivery.","authors":"Carley Yawn, Logan Van Ravenswaay, Krista Marcello, Sarah Nisly","doi":"10.1080/28338073.2025.2532247","DOIUrl":"10.1080/28338073.2025.2532247","url":null,"abstract":"<p><p>Cognitive research consistently demonstrates that spaced repetition enhances memory consolidation and retrieval by reinforcing learned material over time. This study applies the Precede-Proceed Model of Learning framework to examine how predisposing, enabling, and reinforcing educational strategies support sustained knowledge retention among healthcare professionals. The analysis focused on three accredited continuing professional development (CPD) programs conducted between 2022 and 2024. Participants engaged in educational activities that included baseline pre-test and post-activity post-test assessments, with exposure categorized based on prior interaction with related content. Learners were stratified into groups by timing and frequency of exposure to the material. The primary outcome measured was improvement in test performance across sequential learning engagements. Results indicated that learners who accessed educational content prior to the activity demonstrated a significantly higher mean pre-test score of 31% (<i>n</i> = 443) compared to 27% (<i>n</i> = 1,416) among those who viewed it afterward (<i>p</i> = 0.041). Furthermore, repeat learners, regardless of content timing, achieved greater knowledge gains, improving by 34% (<i>p</i> < 0.001), in contrast to a 26% improvement among first-time learners (<i>p</i> < 0.001). These findings highlight the additive value of progressive and repeated exposure in CPD programs. By analysing longitudinal engagement patterns, this study reinforces the importance of strategically structured educational design to foster enduring clinical competence.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2532247"},"PeriodicalIF":0.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278455/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144683670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Validation of an Instrument for Measuring Equality, Diversity and Inclusivity (EDI) in Medical Education Teaching Resources: The GRADES10.","authors":"Zachary Hollenberg, Claire Parkin","doi":"10.1080/28338073.2025.2525692","DOIUrl":"10.1080/28338073.2025.2525692","url":null,"abstract":"<p><p>Higher education institutions around the world have a responsibility to diversify their course content. This is an important consideration to ensure that students are prepared to serve a diverse population once they graduate, however, a lack of diversity representation in medical school curricula in particular, is reported in the literature. A paucity of reliable resources to support creating more inclusive content is also reported. This study developed and validated a diversity measurement instrument, designed to look at representation in the areas of gender, religion, age, disability, ethnicity/race, sexuality, and socio-economic status. Early prototypes were sent to experts for validity testing and using their feedback, improvements and iterations were made to the instrument until the final instrument was agreed: the GRADES10©. The instrument was then applied to a variety of medical education resources to test for rater-reliability. An accompanying user guide was developed to support users with the application of the GRADES10© in practice. Face validity was conducted by 10 experts on several iterations of the instrument from the early prototype (GRADESs7), until the final agreed GRADES10©. Rater-reliability was calculated by intraclass correlation coefficient (ICC) and Cronbach's Alpha measure of internal consistency. The GRADES10© instrument was shown to have an ICC of 0.83% (SD 0.725-0.907) <i>p</i>= < .0001, and Cronbach's Alpha of 0.97. Overall, this study has shown that the validated GRADES10© instrument is able to measure diversity in medical teaching resources reliably. The GRADES10© has the potential to contribute to creating a more inclusive learning environment by allowing its users to apply a diversity metric to their educational materials, to identify gaps and areas for improvement. If applied by medical schools and organisations offering continuing medical education courses in future, the GRADES10© may impact the grassroots of medical education diversification, which may have a beneficial effect on medical student and doctors' attitudes, experiences and ultimately on patient care.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2525692"},"PeriodicalIF":0.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12247083/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144627935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Simulation with ChatGpt: A Revolution in Medical Education?","authors":"Aziel Alejandro Peralta Ramirez, Sergio Trujillo López, Gonzalo Armando Navarro Armendariz, Sayil Alejandra De la Torre Othón, Marcial Ramin Sierra Cervantes, Juan Antonio Medina Aguirre","doi":"10.1080/28338073.2025.2525615","DOIUrl":"10.1080/28338073.2025.2525615","url":null,"abstract":"<p><p>Clinical simulation is key in medical education, but its traditional implementation is costly and complex. This study explored the use of ChatGPT (generative AI) to create interactive clinical scenarios and evaluated students' perceptions of this innovative tool. An exploratory, cross-sectional study was conducted with 32 fourth- and fifth-year medical students. A case of acute coronary syndrome was designed, where ChatGPT (GPT-4) acted as a virtual patient, dynamically responding to students' questions and decisions. After the simulation, participants completed a survey with 20 Likert-scale items and open-ended questions. The results showed high satisfaction: more than 90% considered the case clear and realistic, 94% positively evaluated the virtual patient's responses, and 88% perceived the difficulty as appropriate. Additionally, 97% found automated feedback useful. Qualitative comments highlighted the immersion and safety of the experience, allowing students to practice without fear of making mistakes. Some suggestions included adding greater clinical depth and adjusting the case difficulty. ChatGPT is a promising tool for clinical simulation, offering realistic and challenging scenarios that students perceive as beneficial for developing clinical reasoning and decision-making skills in a safe environment. Automated feedback was highly valued. However, this study is exploratory, and further research with larger samples is needed to validate its educational impact and address challenges such as content supervision and the ethical integration of AI in medical education.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2525615"},"PeriodicalIF":0.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12207779/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144531432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking the Impact of Single Continuing Educational Activities: Navigating Complexity Through Insights from Real-World Evaluation and Contemporary Literature.","authors":"Robert Schaefer, Joerg Stein, Louise Niven, Mia Hill, Onno Kaagman, Anja J Gerrits, Pan Chen, Yvonne Oliver, Eugene Pozniak, Cara L Mcfarlane, Denise Thom, Arne Stachmann, Giovanni Torsello, Reinhard Griebenow","doi":"10.1080/28338073.2025.2498292","DOIUrl":"https://doi.org/10.1080/28338073.2025.2498292","url":null,"abstract":"<p><p>Real-world evaluation data strongly suggest that substantial multi-level heterogeneity of continuing education (CE) audiences, though considered highly desirable, poses severe challenges to the assessment of what a single CE activity might have contributed to either improve or maintain achievements or prevent change for the worse. This relates in particular to change in higher levels of outcomes, such as performance, patient health, and/or community health. This sets narrow limits to the design of an objective, reliable and reasonably valid assessment of change in evaluating the effectiveness of a single CE activity. Although CE may be more effective in leading to consistent behaviour in homogeneous groups with regard to background and motivation, trying to reduce the various levels of heterogeneity would be an unrealistic, and also unwanted, approach. Thus, we still have to trust physicians (and other healthcare professionals) to exercise their professionalism in pursuit of individual opinion forming trajectories in the best interests of their patients. However, providers may also choose some more targeted approaches to influence the mindset even in heterogeneous learner groups: - integrating not only knowledge and competence but also current performance gaps into pre-/post-tests - increasing opportunities for discussion will allow optimal matching of the individual needs of participants with the CE content. When reported, unprecedented numbers of participants' questions (>50 per webinar) have been processed during and/or after an e-learning activity, and even higher numbers of interactions might be expected in demand use of e-learning material. Thus, e-learning in combination with long-term faculty engagement has promising potential for sustainable competence.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2498292"},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12077434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Report on the 17th Annual European CME Forum: Tomorrow's World Today.","authors":"Cara L Macfarlane, Eugene Pozniak","doi":"10.1080/28338073.2025.2480460","DOIUrl":"10.1080/28338073.2025.2480460","url":null,"abstract":"<p><p>The 17th Annual European CME Forum (17ECF) took place 6-8 November 2024 in Madrid, Spain. The meeting was subdivided into three main parts to address the theme \"Tomorrow's world today\": 1) GenAI and digital innovations; 2) Thriving today - anticipating tomorrow; 3) Tomorrow's world today. As is customary, the Forum unofficially began with the pre-meeting sessions before being formally opened. This year's pre-meeting sessions included a new \"Core competencies in CME/CPD\" track to address fundamental topics for the continuing medical education (CME) / continuing professional development (CPD) professional, as well as sessions led by key stakeholder groups in Europe. Throughout the two-day meeting, participants engaged in a series of interactive plenary sessions, workshops, breakouts and oral poster presentations led by European and international providers, accreditors, medical societies, grantors and learners. The <i>Journal of CME</i> also attended to discuss the 2024 Special Collection of articles, which covered the theme \"AI innovations in lifelong learning: Revolutionising CME and CPD\". About 100 stakeholders participated in the annual meeting, with one-third attending for the first time. In keeping with the mission of European CME Forum, 17ECF aimed to facilitate education, interaction and engagement among all stakeholder groups with an interest in European and global CME and CPD, promoting multi-channel discussion in an independent and neutral environment. This meeting report summarises the meeting content and key takeaways from 17ECF.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2480460"},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11951316/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Face and Content Validity of Farra Eye Model as a Surgical Simulator for Capsulorhexis Training.","authors":"Hanifah Rahmani Nursanti, Julie Dewi Barliana, Syska Widyawati, Faraby Martha, Levina Chandra Khoe","doi":"10.1080/28338073.2025.2467566","DOIUrl":"10.1080/28338073.2025.2467566","url":null,"abstract":"<p><p>Several simulation models are available for cataract surgery training, but they have limitations in terms of quality and availability. The Farra Eye Model, a new cataract surgery simulator, was developed using 3D-printing technology to provide residents with more options. This study aims to determine its face and content validity as a surgical simulator for training capsulorhexis, a crucial step in cataract surgery. Ophthalmology residents and consultants at the Faculty of Medicine, Universitas Indonesia, were asked to complete three capsulorhexis tasks in the eye model. Then, subjects were surveyed using a validated questionnaire to assess the face and content validity of the model. Responses were recorded using a 5-point Likert scale ranging from (1) disagree to (5) strongly agree. Twenty-two subjects completed the tasks. The overall face validity score was favourable (3.67 ± 0.67). However, the resident group considered capsule elasticity poor (2.73 ± 1.1), while the consultant group still felt it realistic (3.64 ± 0.9). The content validity had a favourable score in the overall assessment (4.15 ± 0.58) and for each assessment component. Despite the challenge of replicating human lens capsule elasticity, the Farra Eye Model demonstrates initial evidence supporting its use for capsulorhexis training. It can be helpful for training programs with limited access to commercially available simulation models.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2467566"},"PeriodicalIF":0.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11837912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143461001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction.","authors":"","doi":"10.1080/28338073.2025.2454117","DOIUrl":"https://doi.org/10.1080/28338073.2025.2454117","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1080/28338073.2024.2437294.].</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2454117"},"PeriodicalIF":0.0,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753005/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143025938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revolutionizing Diabetic Retinopathy Screening: Integrating AI-Based Retinal Imaging in Primary Care.","authors":"Dale Kummerle, Dean Beals, Lesley Simon, Faith Rogers, Stan Pogroszewski","doi":"10.1080/28338073.2024.2437294","DOIUrl":"10.1080/28338073.2024.2437294","url":null,"abstract":"<p><p>Diabetic retinopathy (DR) is a public health issue affecting millions in the United States and Europe. However, despite strong recommendations for screening at regular intervals by many professional societies, including the American Diabetes Association and the American Academy of Ophthalmology, screening rates remain suboptimal, with only 50-70% of patients with diabetes adhering to recommended annual eye exams. Barriers to screening include lack of awareness, socioeconomic factors, health care system fragmentation, and workforce shortages, among others. Artificial intelligence (AI)-based retinal screening tools offer promising solutions to improve DR detection in primary care settings. We describe a quality improvement and continuing medical education programme, starting in 2020, which has so far deployed 198 AI-equipped cameras in 5 health systems, covering approximately 151,000 patients with diabetes. To date, over 20,000 screenings were completed, with more than mild DR detected in more than 3,450 people, leading to specialist referrals for follow-up care. Notably, negative screenings potentially represent deferred specialist care. While AI adoption in healthcare presents challenges, its potential benefits in improving patient care and optimising resources are significant. Integrating AI-based DR screening with a comprehensive education and process improvement initiative in primary care practices warrants serious consideration, promising to enhance patient outcomes.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2437294"},"PeriodicalIF":0.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703125/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing an Annual Review of the Literature.","authors":"Weinstein R Amy, Szauter Karen, Duca Nicholas, Jacob Jackcy, Ismail Nadia, Pincavage Amber, Walsh Katherine, Alexandraki Irene","doi":"10.1080/28338073.2024.2444726","DOIUrl":"https://doi.org/10.1080/28338073.2024.2444726","url":null,"abstract":"<p><p>Many national meetings and speaker series feature an \"Annual Review of the Literature\" (ARL) session in which an individual or team presents a sampling of articles, selected and prepared because they represent important current topics or new ideas in the discipline of interest. Despite this, there is little in the medical literature describing how to thoughtfully and systematically develop these sessions. We identify best practices that we have developed and used in the United States Clerkship Directors of Internal Medicine (CDIM) over many years. These include identification of a theme, team assembly, timeline development, search strategy and rubric development and employment, and presentation planning strategies. Employing the steps described can help facilitate this otherwise arduous process.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2444726"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence and ChatGPT in Medical Education: A Cross-Sectional Questionnaire on students' Competence.","authors":"L Maaß, C Grab-Kroll, J Koerner, W Öchsner, M Schön, Dac Messerer, T M Böckers, Anja Böckers","doi":"10.1080/28338073.2024.2437293","DOIUrl":"https://doi.org/10.1080/28338073.2024.2437293","url":null,"abstract":"<p><p>Artificial intelligence is rapidly transforming the field of health science and medical education, but less is known about the students´ competencies related to knowledge, skills and attitudes towards the application of AI tools like ChatGPT. Therefore, a unicentric questionnaire-based cross-sectional study was applied to students in the medical field (<i>n</i> = 207). The data revealed that while most students were familiar with ChatGPT (66.7%), other AI tools were significantly less known or utilised for study purposes. Students approached AI tools rather informally, often preferring to use them as a simple search engine. More than half of the students admitted that they were not sufficiently informed about the underlying technology of AI. They applied ChatGPT in a self-directed manner but expressed considerable uncertainty regarding effective prompt engineering and ChatGPT's legal implications. Overall, the majority of respondents showed interest in and positivity towards the introduction of AI. However, they did not feel adequately prepared to handle AI confidently, leading many to express interest in further training. This training should be directly related to students' professional roles, e.g. as a physician. The three most favoured AI-topics for voluntary learning formats were AI in their studies (62.5%), AI in general (58.0%), and the use of AI in scientific writing (57.0%). Notable subgroup differences related to the students\" gender or self-assessed study performance were observed and should be considered in future research.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"14 1","pages":"2437293"},"PeriodicalIF":0.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703531/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142959841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}