BMC Medical Education最新文献

{"title":"The effects of e-learning vs. gamification-based training on ICU nurses' knowledge and attitudes toward organ donation candidates: a study based on the psychological security and empowerment model.","authors":"Meysam Pour Hossein, Mojgan Ansari, Nazanin Fekri, Hamideh Yazdimoghaddam","doi":"10.1186/s12909-025-07299-0","DOIUrl":"10.1186/s12909-025-07299-0","url":null,"abstract":"<p><strong>Background: </strong>Effective training of nurses who manage candidates for organ donation is a critical issue that can enhance nurses' knowledge and attitudes, ultimately improving the quality and efficiency of donated organs. This study aims to compare the effects of e-learning and gamification-based training on ICU nurses' knowledge and attitudes toward organ donation candidates based on the Improving Psychological Security and Empowerment (IPSE) model.</p><p><strong>Methods: </strong>This clinical trial used a pre- and post-intervention design with three groups and was conducted on 45 ICU nurses. Participants were randomly assigned to one of three groups: e-learning, gamification-based training, and a control group (15 participants per group). The e-learning group attended two two-hour webinars based on the IPSE model. After reviewing educational materials prepared based on the IPSE model, the gamification group completed six scenarios via email. The control group received no intervention. A questionnaire assessing the nurses' knowledge and attitudes toward the care of organ donation candidates was administered before and after the intervention. To evaluate the retention of learning, the same questionnaire was completed again one month after the intervention. Data analysis was performed using mixed- ANOVA in SPSS (version 26) and R (version 4.1.2). The assumptions of mixed-ANOVA were checked. In both knowledge and attitude modeling, the normality assumption was confirmed by gg-plot. The homogeneity of variances assumption was tested and confirmed by Levene test. The sphericity assumption for the time effect as well as the interaction effect of time and group was tested and rejected, and we used Greenhouse-Geisser correction P-value.</p><p><strong>Results: </strong>The results revealed that, after the intervention, participants' mean knowledge scores increased significantly in both the e-learning and gamification groups. The score of the e-learning group (Group 1) rose from 9.33 to 14.86, while in the gamification group (Group 2), it increased from 8.87 to 18.00. Both groups demonstrated statistically significant improvements in knowledge scores (P < 0.001). In the control group, the mean knowledge score increased from 9.93 to 12.80, which was also statistically significant (P < 0.001). Regarding attitudes, the e-learning group (Group 1) showed an increase in mean score from 45.73 to 56.86, while the gamification group (Group 2) improved from 47.33 to 61.46. Both groups exhibited statistically significant improvements in attitude scores post-intervention (P < 0.001). The control group's mean attitude score also increased from 48.26 to 51.13, showing a statistically significant change (P < 0.001).</p><p><strong>Conclusion: </strong>The results demonstrated that gamification-based training had a greater impact on nurses' knowledge and attitudes than e-learning. Given the positive effects of both educational approaches, educational and","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"760"},"PeriodicalIF":2.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12100980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144133365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disability training for healthcare workers in Uganda: qualitative findings from the pilot test.","authors":"Tracey Smythe, Andrew Sentoogo Ssemata, Abdmagidu Menya, Femke Bannink Mbazzi, Hannah Kuper","doi":"10.1186/s12909-025-07330-4","DOIUrl":"10.1186/s12909-025-07330-4","url":null,"abstract":"<p><strong>Background: </strong>People with disabilities experience barriers to healthcare, resulting in poorer health outcomes. There is limited disability training for healthcare workers globally. A disability training was co-developed with people with disabilities and healthcare workers and pilot-tested in Uganda.</p><p><strong>Objective: </strong>To use qualitative methods to understand co-learning experiences, identify strengths and areas for improvement, and to explore a disability training's effect on practices in Uganda.</p><p><strong>Methods: </strong>We conducted a two-day Train-the-Trainer programme in September 2023 with ten trainers (5 people with disabilities, 5 healthcare workers). The trainers then delivered two one-day disability training programmes to 27 healthcare workers. Data on the perceptions and experience of the trainings were collected through focus group discussions with trainers and in-depth interviews with trainers and participants. We used an inductive approach for analysis and Kirkpatrick's Four-Level Training Evaluation Model to assess reactions, learning, behaviour changes, and results.</p><p><strong>Results: </strong>The trainers valued the emphasis on practical application and the collaborative approach used during the sessions. Trainers with disabilities expressed increased confidence and ability to advocate for inclusive healthcare practices. Healthcare workers reported that the training was engaging and relevant to their roles. Three months post-training, healthcare workers reported improved attitudes and skills toward providing care for people with disabilities. Challenges in applying new practices included limitations in facility accommodations and accessibility. Further support and training were requested.</p><p><strong>Conclusion: </strong>The co-designed disability training programme can enhance healthcare workers' skills and interactions with patients with disabilities. Policy support is important for the implementation of disability training at scale.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"763"},"PeriodicalIF":2.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12103015/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144133330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current state and future education implication of enhanced recovery after surgery (ERAS) among Chinese anesthesiologists: national repeated cross-sectional surveys from 2019 to 2023.","authors":"Yuelun Zhang, Zijia Liu, Lulu Ma, Xu Li, Qianmei Zhu, Guonian Wang, Jing Cang, Yugang Diao, Tiezheng Zhang, Le Shen, Yuguang Huang","doi":"10.1186/s12909-025-07351-z","DOIUrl":"10.1186/s12909-025-07351-z","url":null,"abstract":"<p><strong>Background: </strong>Enhanced recovery after surgery (ERAS) protocols have been widely adopted to improve surgical outcomes. In this study, we aimed to assess the current state of awareness and specific knowledge of ERAS among Chinese anesthesiologists, examine difficulties in implementation, and identify future priorities for ERAS education and training.</p><p><strong>Methods: </strong>A self-designed, repeated national survey regarding awareness and practice of the ERAS concept, specific knowledge, learning modalities, and difficulties in ERAS implementation was conducted in 2019, 2021, and 2023. Factors related to mastery of knowledge were analyzed via subgroup analysis and multivariable linear regression.</p><p><strong>Results: </strong>A total of 6385 participants were included; 96.2% were anesthesiologists. Approximately half of the participants reported implementing ERAS in more than 40% of patients. Compared with those in the 2019 survey, the overall proportion of participants who had heard about the concept of ERAS remained relatively stable across the three surveys (P = 0.078). However, significant improvements were observed in participants reported good understanding (defined as responding \"very familiar\" or \"quite familiar\") of ERAS and implementing rate of ERAS in clinical practice (P < 0.001). The mean score on the 15-question quiz was 8.5 ± 2.5. Significant differences in scores were observed across various geographic regions, levels of hospitals, education, professional titles, and age. Most anesthesiologists expressed a strong desire for additional education on ERAS in several ways. Feedback from the open-ended question in the survey indicated that multidisciplinary collaboration was a major challenge in implementing ERAS.</p><p><strong>Conclusions: </strong>This nationwide study indicates a notable enhancement in the comprehension and implementation of ERAS among Chinese anesthesiologists, although there is still room for improvement. Future efforts should focus on improving education and training to enhance ERAS knowledge and practice levels among health care providers.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"765"},"PeriodicalIF":2.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12103054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144133329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preferred communication techniques by student-providers and patients during caries management in a teaching practice: a quality improvement study.","authors":"Franklin Zhang, Juanna J Xie, Supattriya Chutinan, Christine A Riedy","doi":"10.1186/s12909-025-07354-w","DOIUrl":"10.1186/s12909-025-07354-w","url":null,"abstract":"<p><strong>Background: </strong>Clear and concise communication between providers and patients is the cornerstone of building trust and delivering effective medical and oral healthcare. The aim of this quality improvement study was to examine patient-provider communication during caries management sessions in an academic dental teaching practice.</p><p><strong>Methods: </strong>Questionnaires were administered to student-providers (3rd and 4th years) and patients (age 18+) in the Harvard Dental Center Teaching Practice from July through December 2022. The student-provider questionnaire assessed challenges, adherence, and communication approaches used during caries management. The patient questionnaire focused on patients' communication preferences, understanding of caries, oral health literacy, and attitudes towards caries management. Descriptive analyses were calculated for both student-provider and patient data, and open-ended student-provider responses were analyzed using a content analysis and organized into themes.</p><p><strong>Results: </strong>Questionnaires were completed by 34 student-providers (50% response rate) and a convenience sample of 110 patients. Among student-providers who reported conducting a caries management session, all reported using simple language and 65.6% focused on discussing limited concepts at a time. Patients preferred simple language (54.8%), motivational interviewing (47.1%), and visual aids, such as models and x-rays (40.4%), to better understand concepts. A subset of student-providers (39.3%) reported challenges in effectively communicating and motivating patients to improve oral hygiene habits. Approximately half of the patients (55.2%) felt confident completing dental forms independently. Regarding their understanding of caries, 54.7% of patients responded that tooth decay will always necessitate fillings and 43.6% of patients responded that they will know when they have tooth decay.</p><p><strong>Conclusions: </strong>These findings highlight the importance of interpersonal communication skill training in dental education to facilitate productive provider-patient communication, particularly in the context of caries risk assessment and management.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"764"},"PeriodicalIF":2.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12102887/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144133363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing ChatGPT-4's performance on the US prosthodontic exam: impact of fine-tuning and contextual prompting vs. base knowledge, a cross-sectional study.","authors":"Mahmood Dashti, Farshad Khosraviani, Tara Azimi, Delband Hefzi, Shohreh Ghasemi, Amir Fahimipour, Niusha Zare, Zohaib Khurshid, Syed Rashid Habib","doi":"10.1186/s12909-025-07371-9","DOIUrl":"10.1186/s12909-025-07371-9","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI), such as ChatGPT-4 from OpenAI, has the potential to transform medical education and assessment. However, its effectiveness in specialized fields like prosthodontics, especially when comparing base to fine-tuned models, remains underexplored. This study evaluates the performance of ChatGPT-4 on the US National Prosthodontic Resident Mock Exam in its base form and after fine-tuning. The aim is to determine whether fine-tuning improves the AI's accuracy in answering specialized questions.</p><p><strong>Methods: </strong>An official sample questions from the 2021 US National Prosthodontic Resident Mock Exam was used, obtained from the American College of Prosthodontists. A total of 150 questions were initially considered, and resources were available for 106 questions. Both the base and fine-tuned models of ChatGPT-4 were tested under simulated exam conditions. Performance was assessed by comparing correct and incorrect responses. The Chi-square test was used to analyze accuracy, with significance set at p < 0.05. The Kappa coefficient was calculated to measure agreement between the models' responses.</p><p><strong>Results: </strong>The base model of ChatGPT-4 correctly answered 62.7% of the 150 questions. For the 106 questions with resources, the fine-tuned model answered 73.6% correctly. The Chi-square test showed a significant improvement in performance after fine-tuning (p < 0.001). The Kappa coefficient was 0.39, indicating moderate agreement between the models (p < 0.001). Performance varied by topic, with lower accuracy in areas such as Implant Prosthodontics, Removable Prosthodontics, and Occlusion, though the fine-tuned model consistently outperformed the base model.</p><p><strong>Conclusions: </strong>Fine-tuning ChatGPT-4 with specific resources significantly enhances its accuracy in answering specialized prosthodontic exam questions. While the base model provides a solid baseline, fine-tuning is essential for improving AI performance in specialized fields. However, certain topics may require more targeted training to achieve higher accuracy.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"761"},"PeriodicalIF":2.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12102979/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144133278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Educational utility of observational workplace-based assessment modalities in Australian vocational general practice training: a cross-sectional study.","authors":"Alison Fielding, Benjamin Mundy, Amanda Tapley, Sarah Gani, Rula Ali, Michael Bentley, Rachael Boland, Lina Zbaidi, Elizabeth Holliday, Jean Ball, Mieke van Driel, Linda Klein, Parker Magin","doi":"10.1186/s12909-025-07328-y","DOIUrl":"10.1186/s12909-025-07328-y","url":null,"abstract":"<p><strong>Background: </strong>Direct observation, workplace-based assessments (WBAs) are a fundamental component of competency-based postgraduate medical education. In Australian general practice vocational training, external clinical teaching visits (ECTVs) are key observation-based WBAs. Traditionally, ECTVs are conducted face-to-face, but the COVID-19 pandemic saw the development and implementation of remote ECTV modalities. It remains unknown if perceived educational utility of remote ECTVs differs from traditional face-to-face ECTVs. This study explored the educational utility of ECTVs, including face-to-face and remote formats.</p><p><strong>Methods: </strong>General practice trainees ('registrars') and external clinical teaching visitors ('ECT visitors', who are independent experienced GP observers) each completed a cross-sectional questionnaire following individual ECTVs undertaken in 2020. Outcomes included overall educational utility of the ECTV as perceived by registrars, registrar ratings of likelihood to change their clinical practice as a result of the ECTV, registrar ratings of likelihood to change their approach to learning/training as a result of the ECTV, and overall educational utility of the ECTV as perceived by the ECT visitor. Educational utility ratings (5-point scales) were analysed descriptively. Univariable and multivariable logistic regression were employed to examine factors associated with dichotomised educational utility ratings.</p><p><strong>Results: </strong>Response rates were 41% (n = 801) for registrars and 39% (n = 742) for ECT visitors. Most registrars (64.1%) rated ECTV overall educational utility as 'very useful'; 58.5% and 47.9% of registrars rated their likelihood to change practice and approach to learning/training, respectively, as 'very likely'. No statistically significant differences in perceived educational utility ratings were identified between face-to-face and remote video/phone ECTVs (multivariable p-value range: .07-.96). Receiving feedback that was focused/specific/easy to translate into action was consistently associated with registrars' rating overall educational utility as 'very useful' (odds ratio (OR): 12.8, 95% confidence interval (CI): 8.26 to19.9), rating likelihood to change practice as 'very likely' (OR: 2.5, 95%CI: 1.59 to 3.94), and rating likelihood to change learning/training approach as 'very likely' (OR: 3.19, 95%CI: 1.97 to 5.17).</p><p><strong>Conclusions: </strong>ECTVs are perceived by registrars and ECT visitors to be educationally useful across different delivery modalities and formats. The quality and features of the feedback provided appear most important in ECTVs as an assessment for learning.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"762"},"PeriodicalIF":2.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12102905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144133361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the landscape of student representation in medical curriculum development across U.S. MD schools: A comparative analysis.","authors":"Ish Sethi, C Jessica Dine","doi":"10.1186/s12909-025-07114-w","DOIUrl":"10.1186/s12909-025-07114-w","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to investigate the various models of student representation in curriculum development across medical schools in the United States, based on the participatory governance theory. Recognizing the critical role of student feedback in enhancing medical education, the work sought to assess the diversity of student representation models, identify key elements that contribute to effective student involvement, and evaluate the potential impact on curriculum outcomes.</p><p><strong>Methods: </strong>An initial list of 166 allopathic MD schools was curated from the AAMC Medical Schools Admission Requirements website. Schools were selected based on the presence of information about student representation in curriculum design. This selection was refined through a Google search using specific search terms related to student representation, followed by an evaluation based on the amount and relevance of available information on each school's website. The methodology involved a detailed examination of the websites for selected schools, focusing on the structure and organization of student involvement in curriculum development.</p><p><strong>Results: </strong>Of the initial 166 medical schools, 49 (29.7%) had publicly available information on student involvement in curriculum development. These schools were categorized into three main models of student representation: direct representation, feedback-driven, and hybrid models. The analysis revealed significant diversity in how student representation is implemented, with each model exhibiting unique strengths and limitations. Direct representation models were found to facilitate substantive student roles in decision-making, feedback-driven models excelled in rapidly integrating student feedback into curricular adjustments, and hybrid models combined aspects of both to provide a comprehensive approach to student involvement.</p><p><strong>Conclusions: </strong>There is no one-size-fits-all model for student representation in medical education. However, the hybrid model shows promise for its balanced approach to integrating student perspectives into curriculum development. Continuous evaluation and refinement of student representation models are essential for ensuring that medical education remains responsive to the needs of students and the evolving landscape of the medical field. This work underscores the importance of student feedback in medical education and advocates for further studies to quantify the impact of different models of student representation on educational outcomes and professional success.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"747"},"PeriodicalIF":2.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12096781/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144128696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing pathophysiology instruction in dental school: examination paper analysis and strategic reflections.","authors":"Zheng Wang, Xing-Long Zheng, Xi He, Jin-Jun Liu","doi":"10.1186/s12909-025-07360-y","DOIUrl":"10.1186/s12909-025-07360-y","url":null,"abstract":"<p><strong>Background: </strong>Pathophysiology, a bridge between basic and clinical medicine, is particularly crucial for dental students. This article analyzes the final pathophysiology examination paper for the 2021 grade dental medicine students at Xi'an Jiaotong University to understand the students' knowledge mastery, assess teaching effectiveness, and ultimately improve teaching quality.</p><p><strong>Methods: </strong>The theoretical examination results of 93 dental medicine students from the 2021 grade were analyzed and graded using the Optical Mark Recognition digital grading system to ensure accuracy and efficiency in processing multiple-choice responses. Statistical analyses were conducted using SPSS 26.0 to determine the score distribution, difficulty index, discrimination index, and reliability.</p><p><strong>Results: </strong>The examination scores of the 93 dental medicine students showed a skewed distribution, with an average score of 74.32, a median of 76, and a standard deviation of 17.31. The pass rate was 83.87%. The detailed score distribution was as follows: 23.66% of students scored between 90 and 100, 18.28% scored between 80 and 89, 22.58% scored between 70 and 79, 19.35% scored between 60 and 69, and 16.13% scored below 60. The Kolmogorov-Smirnov (K-S) test confirmed a significant deviation from normality (K-S value = 0.1477, P < 0.0001), with a skewness coefficient of -0.75 and a kurtosis coefficient of 0.45. The overall difficulty index of the exam was 0.73, the discrimination index was 0.42, and the reliability was high at 0.86.</p><p><strong>Conclusions: </strong>Our data suggest that the examination demonstrated high reliability and acceptable discrimination but was relatively easy. Future examinations should increase the difficulty level and discrimination appropriately. In teaching, we should continue to enhance teaching quality by focusing on key knowledge points, optimizing the assessment system, exploring innovative teaching modes, and further improving overall teaching quality.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"754"},"PeriodicalIF":2.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12100804/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144128993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing ChatGPT adoption in Jordanian medical education: a UTAUT model approach.","authors":"Noura Alqaisi, Sakhr Alshwayyat, Saif Aburumman, Nour Qassim, Noor Almasri, Fatima Algroosh, Mesk Alkhatib, Hamdah Hanifa, Saif Aldeen AlRyalat","doi":"10.1186/s12909-025-07336-y","DOIUrl":"10.1186/s12909-025-07336-y","url":null,"abstract":"<p><strong>Background: </strong>ChatGPT has shown significant promise in transforming medical education by streamlining research and improving teaching methods. However, its adoption in Middle Eastern medical education has remained underexplored. This study investigated the factors influencing the adoption of ChatGPT in Jordanian medical education using a modified Unified Theory of Acceptance and Use of Technology (UTAUT) framework.</p><p><strong>Methods: </strong>A cross-sectional survey was conducted with medical students and faculty members at the University of Jordan. A validated 33-item questionnaire distributed online and on campus targeted individuals familiar with the ChatGPT. Structural equation modeling (SEM) assessed the relationships between key constructs, including Performance Expectancy (PE), Effort Expectancy (EE), Perceived Risk (PR), Facilitating Conditions (FC), and attitude (ATT).</p><p><strong>Results: </strong>Among 127 participants (53% male, mean age 23.2 ± 7.6), ATT was significantly influenced by PE and EE, explaining 37% of its variance. Behavioral Intention (BI) was predicted by ATT and had a significant positive effect on actual usage. FC did not significantly influence EE or BI, suggesting a limited reliance on external support. Contrary to expectations, PR did not negatively affect ATT, indicating that utility outweighed concerns about misinformation or privacy. Overall, the model explained 53% of the variance in BI and 36.5% of the variance in actual usage.</p><p><strong>Conclusion: </strong>The adoption of ChatGPT in Jordanian medical education is driven by perceived utility and ease of use, with attitudes playing a pivotal role. Addressing misinformation risks and improving trust through tailored strategies can foster broader integration of AI tools, such as ChatGPT, in medical training.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"750"},"PeriodicalIF":2.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12100967/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenging cases of hyponatremia incorrectly interpreted by ChatGPT.","authors":"Kenrick Berend, Ashley Duits, Reinold O B Gans","doi":"10.1186/s12909-025-07235-2","DOIUrl":"10.1186/s12909-025-07235-2","url":null,"abstract":"<p><strong>Background: </strong>In clinical medicine, the assessment of hyponatremia is frequently required but also known as a source of major diagnostic errors, substantial mismanagement, and iatrogenic morbidity. Because artificial intelligence techniques are efficient in analyzing complex problems, their use may possibly overcome current assessment limitations. There is no literature concerning Chat Generative Pre-trained Transformer (ChatGPT-3.5) use for evaluating difficult hyponatremia cases. Because of the interesting pathophysiology, hyponatremia cases are often used in medical education for students to evaluate patients with students increasingly using artificial intelligence as a diagnostic tool. To evaluate this possibility, four challenging hyponatremia cases published previously, were presented to the free ChatGPT-3.5 for diagnosis and treatment suggestions.</p><p><strong>Methods: </strong>We used four challenging hyponatremia cases, that were evaluated by 46 physicians in Canada, the Netherlands, South-Africa, Taiwan, and USA, and published previously. These four cases were presented two times in the free ChatGPT, version 3.5 in December 2023 as well as in September 2024 with the request to recommend diagnosis and therapy. Responses by ChatGPT were compared with those of the clinicians.</p><p><strong>Results: </strong>Case 1 and 3 have a single cause of hyponatremia. Case 2 and 4 have two contributing hyponatremia features. Neither ChatGPT, in 2023, nor the previously published assessment by 46 clinicians, whose assessment was described in the original publication, recognized the most crucial cause of hyponatremia with major therapeutic consequences in all four cases. In 2024 ChatGPT properly diagnosed and suggested adequate management in one case. Concurrent Addison's disease was correctly recognized in case 1 by ChatGPT in 2023 and 2024, whereas 81% of the clinicians missed this diagnosis. No proper therapeutic recommendations were given by ChatGPT in 2023 in any of the four cases, but in one case adequate advice was given by ChatGPT in 2024. The 46 clinicians recommended inadequate therapy in 65%, 57%, 2%, and 76%, respectively in case 1 to 4.</p><p><strong>Conclusion: </strong>Our study currently does not support the use of the free version ChatGPT 3.5 in difficult hyponatremia cases, but a small improvement was observed after ten months with the same ChatGPT 3.5 version. Patients, health professionals, medical educators and students should be aware of the shortcomings of diagnosis and therapy suggestions by ChatGPT.</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"751"},"PeriodicalIF":2.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12100905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}