BACKGROUND: Process-based teaching is a new education model. SPARK case database is a free medical imaging case database. This manuscript aimed to explore the application of the process-based teaching based on SPARK case database in the practice teaching of radiology in the musculoskeletal system.
METHODS: 117 third year medical students were included. They were divided into Group A, B, C and D according to the curriculum arrangement. Group A and B attended the experimental class at the same time, A was the experimental group, B was the control group. Group C and D attended experimental classes at the same time, C was the experimental group, D was the control group. The experimental group used SPARK case database, while the control group used traditional teaching model for learning. The four groups of students were respectively tested after the theoretical class, before the experimental class, after the experimental class, and one week after the experimental class to compare the results. Finally, all students used SPARK case database to study, and were tested one month after the experimental class to compare their differences.
RESULTS: The scores after the theoretical class of Group A and B were (100.0 ± 25.4), (101.0 ± 23.8)(t=-0.160, P > 0.05), Group C and D were (94.7 ± 23.7), (92.1 ± 18.6)(t = 0.467, P > 0.05). The scores of Group A and B before and after the experimental class and one week after the experimental class were respectively (84.1 ± 17.4), (72.1 ± 21.3)(t = 2.363, P < 0.05), (107.6 ± 14.3), (102.1 ± 18.0)(t = 1.292, P > 0.05), (89.7 ± 24.3), (66.6 ± 23.2)(t = 3.706, P < 0.05). The scores of Group C and D were (94.0 ± 17.3), (72.8 ± 25.5)(t = 3.755, P < 0.05), (107.3 ± 20.3), (93.1 ± 20.9)(t = 2.652, P < 0.05), (100.3 ± 19.7), (77.2 ± 24.0)(t = 4.039, P < 0.05). The scores of Group A and B for one month after the experimental class were (86.6 ± 28.8), (84.5 ± 24.0)(t = 0.297, P > 0.05), and Group C and D were (95.7 ± 20.3), (91.7 ± 23.0)(t = 0.699, P > 0.05).
CONCLUSIONS: The process-based teaching based on SPARK case database could improve the radiology practice ability of the musculoskeletal system of students.

BACKGROUND: Blended learning comprised with flipped classroom (FC) and \"internet plus\" is a new learning strategy that reverses the position of teacher and students in class, and provides abundant learning resources before and after class. This study aimed to assess the impact of blended learning on learning outcomes in evidence-based medicine course, and compare with traditional learning method.
METHODS: The participants of the two groups were from two difference cohorts in Air force medical university in China. The two groups toke the same pre-test before class and then were given the teaching of same chapters of evidence-based medicine with two different learning strategy. In the blended learning group, the participants were required to create a debriefing slide about their learning outcomes and the answers of questions given in advance after study the learning material sent by teacher a week before class, and the teacher gave a detailed summary based on the common problems, and distributed multimedia resources for review. After the experiment was carried out, learning outcomes including mastering knowledge, learning satisfaction, and self-evaluation were compared.
RESULTS: 37 and 39 participants were enrolled to blended learning and traditional learning groups, respectively, and no statistically significant difference were found in baseline information and pre-test grades. Statistically significant differences were found in learning outcomes including post-test score (t = 2.90, p = 0.005), changes of scores between pre-test and post-test (t = 2.49, p = 0.022), learning satisfaction (t = 12.41, p = 0.001), and self-evaluation of the two groups (t = 7.82, p = 0.001). Especially, the changes of scores between pre-test and post-test of blended learning and traditional learning groups were 4.05 (4.26), and 2.00 (2.85), respectively.
CONCLUSIONS: This study showed that compared with traditional learning strategy, blended learning can effectively enhanced participants\' acquisition of knowledge, learning satisfaction, and self-evaluation in evidence-based medicine. Using blended learning method including \"internet plus\" and flipped classroom is recommended in the teaching of evidence-based medicine course.

BACKGROUND: This study aims to determine the satisfaction and future training needs of general practice residents participating in a novel model of ambulatory teaching aligned with the specifications for standardized residency training in outpatient management issued by the Chinese Medical Doctor Association (CMDA).
METHODS: A cross-sectional survey of the satisfaction and training needs was conducted among general practice residents at West China Hospital, Sichuan University. Patient characteristics and preceptors\' feedback on the residents\' performance were also analyzed.
RESULTS: The study involved 109 residents (30.28% men) and 161 patients (34.78% men; age: 52.63 ± 15.87 years). Residents reported an overall satisfaction score of 4.28 ± 0.62 with the ambulatory teaching program. Notably, residents scored lower in the Subjective-Objective-Assessment-Plan (SOAP) evaluation when encountering patients with the greater the number of medical problems (P < 0.001). Residents encountering patients with a shorter duration of illness (< 3 months) achieved higher scores than those with longer illness durations (≥ 3 months, P = 0.044). Residency general practitioners (GPs) were most challenged by applying appropriate and effective patient referrals (43/109; 39.45%). GPs expressed a strong desire to learn how to make decisions when facing challenging patient situations (4.51 ± 0.63).
CONCLUSIONS: This study suggests selecting patients with multiple comorbidities for ambulatory teaching and enhancing training on practical problem-solving abilities for GPs. The findings provide insights for the development of future ambulatory teaching programs.

BACKGROUND: The aim of this study was to evaluate the effectiveness of team-, case-, lecture-, and evidence-based learning (TCLEBL) methods in cultivating students\' clinical and research abilities, as compared to traditional lecture-based learning (LBL) approaches.
METHODS: Forty-one medical postgraduates were divided into two groups, a TCLEBL group and an LBL group. Teaching effectiveness was evaluated through student- and teacher-feedback questionnaires, scores from theoretical examinations and written literature reviews, and student learning burdens.
RESULTS: Compared to the LBL approach, both teachers and students were more satisfied with the TCLEBL model (p < 0.001 for both teachers and students). The TCLEBL group performed significantly higher on the theory test compared to the LBL group (p = 0.009). There were significant differences between the LBL and TCLEBL groups, respectively, in terms of literature review and citations (12.683 ± 2.207 vs. 16.302 ± 1.095, p < 0.001), argument and perspective (12.55 ± 1.572 vs. 16.333 ± 1.354, p < 0.001), comprehensiveness of content (13.3 ± 2.268 vs. 16.683 ± 1.344, p < 0.001), and scientific rigor and accuracy (10.317 ± 1.167 vs. 12.746 ± 0.706, p < 0.001). There was no significant difference in the total extracurricular time expended between the two groups (323.75 ± 30.987 min vs. 322.619 ± 24.679 min, respectively for LBL vs. TCLEBL groups, p = 0.898).
CONCLUSIONS: TCLEBL is an effective teaching method that cultivates students\' clinical and research abilities.

OBJECTIVE: Currently, there are still some shortcomings in EBM education in China.The study aimed to investigate the effectiveness of the novel evidence-based medicine (EBM) learning model of \"autonomy-collaboration.\"
METHODS: A total of 91 undergraduate students majoring in clinical medicine at Zhongshan Clinical College of Dalian University from the 2019 batch were selected as the participants in this study. They were instructed to follow the EBM learning model of \"autonomy-collaboration.\" Upon completion of the course, questionnaires, records of participants\' sentiments and insights, and evidence-based clinical practice reports were used as indicators to evaluate the effectiveness of the training.
RESULTS: This learning modality effectively enhanced independent learning ability of the students, stimulated their interest in learning, and strengthened the communication between students and teachers, thereby improving the quality of teaching.
CONCLUSIONS: The novel EBM learning model of \"autonomy-collaboration,\" exhibited robust effectiveness in instruction and facilitated the seamless integration of theoretical knowledge with clinical practice. Consequently, its widespread adoption is strongly recommended.

BACKGROUND: This study aimed to assess the impact of the pandemic of the coronavirus disease 2019 (COVID-19) on neonatology residency training in a tertiary children\'s hospital in Chongqing, located in southwest China. Specifically, the study encompassed the effects on residents\' education, lived experiences, well-being, and the quality of neonatal care delivered. As higher educational institutions adapt to the post-COVID-19 era after the pandemic disruption, it is imperative that educational designers/academics learn from their experiences and challenges in curriculum design and delivery, ensuring quality and relevance in education.
METHODS: This study employed a mixed-methods approach to investigate the influence of the COVID-19 pandemic on neonatology residency training at a tertiary children\'s hospital in Chongqing. The first phase surveyed residents\' perceptions and experiences of their clinical education and well-being during the crisis. The second phase compared the quality of neonatal care between the pre-pandemic and pandemic periods.
RESULTS: The survey of 123 neonatology residents examines the effects of COVID-19 on their learning, training, and mental health. The survey showed that most residents adapted well to the situation. Still, some faced challenges in their clinical education and experiences, such as reduced clinical exposure and opportunities to see rare diseases and conditions. A retrospective analysis of clinical data revealed that 7,151 neonates were admitted to the neonatology department during the study period. There was a 27.6% decrease in neonatal admissions during COVID-19, with more premature births and transfers. Residents conducted fewer clinical procedures but managed more complex cases. During COVID, hospital stays and costs were higher, but antibiotic use was lower. Although the case-mix index (CMI) score increased during the pandemic (1.25 vs. 1.18, p < 0.05), there was no significant difference in the rates of readmission within 7 days or poor prognosis.
CONCLUSIONS: Despite reduced clinical exposure, the quality of neonatal care was maintained through innovative training methods that enhanced comprehensive residency programs. The study suggested that neonatology residency education remained effective and resilient during the crisis. Exceptional health professional education is vital to train qualified physicians and enhance healthcare systems for future challenges.

BACKGROUND: Learning to perform strabismus surgery is an essential aspect of ophthalmologists\' surgical training. Automated classification strategy for surgical steps can improve the effectiveness of training curricula and the efficient evaluation of residents\' performance. To this end, we aimed to develop and validate a deep learning (DL) model for automated detecting strabismus surgery steps in the videos.
METHODS: In this study, we gathered 479 strabismus surgery videos from Shanghai Children\'s Hospital, affiliated to Shanghai Jiao Tong University School of Medicine, spanning July 2017 to October 2021. The videos were manually cut into 3345 clips of the eight strabismus surgical steps based on the International Council of Ophthalmology\'s Ophthalmology Surgical Competency Assessment Rubrics (ICO-OSCAR: strabismus). The videos dataset was randomly split by eye-level into a training (60%), validation (20%) and testing dataset (20%). We evaluated two hybrid DL algorithms: a Recurrent Neural Network (RNN) based and a Transformer-based model. The evaluation metrics included: accuracy, area under the receiver operating characteristic curve, precision, recall and F1-score.
RESULTS: DL models identified the steps in video clips of strabismus surgery achieved macro-average AUC of 1.00 (95% CI 1.00-1.00) with Transformer-based model and 0.98 (95% CI 0.97-1.00) with RNN-based model, respectively. The Transformer-based model yielded a higher accuracy compared with RNN-based models (0.96 vs. 0.83, p < 0.001). In detecting different steps of strabismus surgery, the predictive ability of the Transformer-based model was better than that of the RNN. Precision ranged between 0.90 and 1 for the Transformer-based model and 0.75 to 0.94 for the RNN-based model. The f1-score ranged between 0.93 and 1 for the Transformer-based model and 0.78 to 0.92 for the RNN-based model.
CONCLUSIONS: The DL models can automate identify video steps of strabismus surgery with high accuracy and Transformer-based algorithms show excellent performance when modeling spatiotemporal features of video frames.

BACKGROUND: The rapid growth of artificial intelligence (AI) technologies has been driven by the latest advances in computing power. Although, there exists a dearth of research on the application of AI in medical education.
METHODS: this study is based on the TAM-ISSM-UTAUT model and introduces STARA awareness and chilling effect as moderating variables. A total of 657 valid questionnaires were collected from students of a medical university in Dalian, China, and data were statistically described using SPSS version 26, Amos 3.0 software was used to validate the research model, as well as moderated effects analysis using Process (3.3.1) software, and Origin (2021) software.
RESULTS: The findings reveal that both information quality and perceived usefulness are pivotal factors that positively influence the willingness to use AI products. It also uncovers the moderating influence of the chilling effect and STARA awareness.
CONCLUSIONS: This suggests that enhancing information quality can be a key strategy to encourage the widespread use of AI products. Furthermore, this investigation offers valuable insights into the intersection of medical education and AI use from the standpoint of medical students. This research may prove to be pertinent in shaping the promotion of Medical Education Intelligence in the future.

BACKGROUND: Despite the numerous advantages of mastering biostatistics, medical students generally perceive biostatistics as a difficult and challenging subject and even experience anxiety during the courses. Evidence for the correlation between students\' academic achievements and their attitudes, indicating that attitudes at the beginning of the biostatistics course may affect cognitive competence at the end of the course and subsequently influence student academic performance. However, there are current disagreements regarding the measurement and evaluation of attitudes related to statistics. Thus, there is a need for standard instruments to assess them. This study was conducted to develop a Chinese version of the Survey of Attitudes Toward Statistics (SATS-36) in order to acquire a valid instrument to measure medical students\' attitudes toward biostatistics under Chinese medical educational background.
METHODS: The Chinese version SATS-36 was developed through translation and back-translation of the original scale, with subsequent revisions based on expert advice to ensure the most appropriate item content. The local adaption was performed with a cohort of 1709 Chinese-speaking medical undergraduate and graduate students enrolled in biostatistics courses. And then, the reliability, validity and discrimination of the questionnaires were evaluated through correlation coefficient calculation, factor analysis, parallel analysis and other methods.
RESULTS: The Chinese version SATS-36 consisted of 36 items and loaded a five-factor structure by factor analysis, which offered an alternative similar but not equal to that original six-factor structure. The cumulative variance contribution rate was 62.20%, the Cronbach\'s α coefficient was 0.908, the Guttman split-half reliability coefficient was 0.905 and the test-retest reliability coefficient was 0.752. Discriminant analysis revealed small to large significant differences in the five attitude subscales.
CONCLUSIONS: The Chinese version SATS-36 with good validity and reliability in this study can be used to evaluate the learning framework of Chinese medical students.

UNASSIGNED: Mobile health (mHealth) is an emerging mobile communication and networking technology for health care systems. The integration of mHealth in medical education is growing extremely rapidly, bringing new changes to the field. However, no study has analyzed the publication and research trends occurring in both mHealth and medical education.
UNASSIGNED: The aim of this study was to summarize the current application and development trends of mHealth in medical education by searching and analyzing published articles related to both mHealth and medical education.
UNASSIGNED: The literature related to mHealth and medical education published from 2003 to 2023 was searched in the Web of Science core database, and 790 articles were screened according to the search strategy. The HistCite Pro 2.0 tool was used to analyze bibliometric indicators. VOSviewer, Pajek64, and SCImago Graphica software were used to visualize research trends and identify hot spots in the field.
UNASSIGNED: In the past two decades, the number of published papers on mHealth in medical education has gradually increased, from only 3 papers in 2003 to 130 in 2022; this increase became particularly evident in 2007. The global citation score was determined to be 10,600, with an average of 13.42 citations per article. The local citation score was 96. The United States is the country with the most widespread application of mHealth in medical education, and most of the institutions conducting in-depth research in this field are also located in the United States, closely followed by China and the United Kingdom. Based on current trends, global coauthorship and research exchange will likely continue to expand. Among the research journals publishing in this joint field, journals published by JMIR Publications have an absolute advantage. A total of 105 keywords were identified, which were divided into five categories pointing to different research directions.
UNASSIGNED: Under the influence of COVID-19, along with the popularization of smartphones and modern communication technology, the field of combining mHealth and medical education has become a more popular research direction. The concept and application of digital health will be promoted in future developments of medical education.