Raising concerns (speaking up or whistleblowing) is essential to detect and prevent unsafe practice and to uphold professional standards. While medical and dental students are frontline observers during clinical rotations, they face barriers to escalation. However, to guide policy and training, it is essential to gather local data on students' confidence and the readiness of institutions to support them in raising concerns. This study aimed to assess Syrian medical and dental students' institutional awareness and exposure to safety concerns, confidence in speaking up, perceived barriers to raising concerns, and institutional readiness to support reporting during clinical training. A cross-sectional survey was administered to a total of 812 medical and dental students in clinical training from all 13 universities offering undergraduate medical education in Syria between 15 October and 22 December 2025. A scenario-based Arabic questionnaire, translated and back-translated, was delivered via online and paper modes to maximize inclusion, with a pilot study of 40 students demonstrating excellent internal consistency (Cronbach's α = 0.95). Data were analyzed using descriptive statistics, t-tests, one-way ANOVA with Tukey's post-hoc tests, and multivariate linear regression to identify predictors of confidence (SPSS v27). Sample size calculations indicated a minimum requirement of 385 participants, and statistical significance was set at p < 0.05. Among participants, 40.9% reported encountering unsafe or unprofessional behavior, while 17.6% reported the presence of an institutional whistleblowing policy and 4.8% had received formal training, despite 82.3% expressing interest in such training. Overall confidence in raising concerns was moderate, with the highest confidence reported for patient safety issues and reporting to clinical supervisors. Confidence declined significantly with each advancing academic year (p < .001) and was independently associated with formal training in multivariable analysis (p = .001). The most frequently reported barriers were reluctance to "cause trouble" (42.6%), uncertainty about whom to contact (41.9%) and perceived lack of institutional support (39.0%); top enablers were assurances of reporter safety (74.1%) and ensuring changes will be implemented following reporting (59.9%). A substantial proportion of students reported exposure to unsafe or unprofessional behavior, while reporting policies, training, and institutional support were limited. These findings suggest gaps in reporting preparedness and perceived safety that may influence students' willingness to raise concerns. Further research is needed to evaluate strategies to improve reporting confidence and institutional support. In this context, educational institutions should incorporate practical, scenario-based training into their curricula. Future research should also assess the long-term effects of these measures on students, and extend the evaluation to include residents and practitioners.
The deep integration of artificial intelligence (AI) and medical imaging represents a major trend in the transformation of healthcare, driving advancements in technologies such as image reconstruction. At the same time, medical schools worldwide are integrating AI into medical imaging education. This paper reviews recent advances in artificial intelligent medical imaging education and offers recommendations regarding curriculum design and faculty development for training professionals in artificial intelligent medical imaging. This study analyzed the application of AI in medical imaging education and corresponding talent development models through a literature review of core databases such as PubMed and Web of Science, supplemented by case studies, to draw conclusions and propose targeted recommendations. AI has been widely applied in medical imaging education to enhance educational quality and other aspects. However, globally, AI-related radiology education exhibits inconsistencies in curriculum design and insufficient integration of technology. Although preliminary evidence suggests that AI can effectively improve teaching outcomes, the lack of standardized teaching guidelines has led to gaps in the knowledge system. The integration of AI and medical imaging offers significant advantages in medical imaging education. However, while the education sector has already adopted various strategies-such as human-machine collaborative education-it still faces challenges, including a shortage of interdisciplinary faculty and a disconnect between the curriculum and clinical practice. Improvements must be made through strategies such as faculty development, pedagogical transformation, fostering AI literacy, and standardizing teaching frameworks. Future research should explore the adaptability of AI across different training stages to promote the sustainable integration of these two fields and the development of relevant professionals.
End-of-life (EOL) care is a frequent and complex aspect of internal medicine, yet data on physicians' training, clinical practices, and perceived challenges are limited. This study aimed to explore current practices, knowledge gaps, and unmet needs in EOL care among Italian internal medicine physicians and residents. A cross-sectional survey was conducted under the auspices of the Piedmont-Liguria-Aosta Valley Section of the Italian Society of Internal Medicine (SIMI). The survey included 25 closed-ended questions addressing five domains: epidemiological, pharmacological, practical, psychological, and educational aspects of EOL care. Physicians actively involved in clinical care from multiple internal medicine wards participated voluntarily. Responses were collected anonymously via paper and online formats. Descriptive statistics were used to summarize data. Differences between groups (specialists vs. residents, oncology/hematology vs. non-oncology wards, low vs. medium vs. high clinical intensity wards) were assessed using the Mann-Whitney U and Kruskal-Wallis tests. Associations between ordinal variables were evaluated using Spearman's rank correlation coefficient. P-values were adjusted using the Benjamini-Hochberg procedure. Of approximately 7,400 invited physicians, 619 completed the survey (response rate ≈ 8.4%; median age 38 years; 60.5% female; 70.8% board-certified internists). More than 88% reported facing terminal patients at least weekly, yet only 2.5% were aware of Advance Directives for > 25% of inpatients. Use of sedatives and analgesics during terminal sedation varied, while discontinuation of active therapies, total parenteral nutrition (TPN), and transfusions was widely accepted. Internal protocols and dedicated multidisciplinary discussions were infrequently used. Most respondents reported difficulties communicating with patients and families at EOL. Formal training in EOL care was perceived as largely inadequate during undergraduate, residency, and postgraduate education. Compared with residents, board-certified internists more frequently reported postgraduate/Master training, whereas residents more frequently reported undergraduate and residency training in EOL. Exploratory correlation analyses generated hypotheses linking communication difficulties with patients to those with family members and training experiences across educational stages. The study highlights substantial gaps in training, communication, and organizational support, independent of clinical setting. Structured education and integration of psychological support are urgently needed. These findings can inform curriculum development, hospital policies, and future research to improve physician preparedness and patient-centered EOL care.
Shared decision-making (SDM) is a key element of patient-centered care; however, opportunities for structured and scalable SDM training remain limited in both medical education and clinical practice. Advances in AI have enabled chatbot-based simulations that may support repeated practice and provide automated feedback on SDM-related communication behaviors. This study aimed to (1) evaluate the agreement between AI-generated and human ratings of SDM performance, (2) compare SDM-related performance and attitudes between medical students and physicians, and (3) explore changes in communicative self-efficacy (CSE) following chatbot-based SDM practice. We conducted a feasibility study using a pre-post mixed methods design. Medical students and physicians practiced SDM in a 20-minute chat-based interaction with an AI-simulated patient, followed by automated feedback on SDM performance. Prior to the interaction, participants' attitudes toward SDM (IcanSDM) and their CSE (Self-Efficacy in Patient-Centeredness Questionnaire [SEPCQ-24-GER]) were assessed; CSE was reevaluated after the intervention. SDM performance was measured using the validated Observing Patient Involvement in Decision Making (OPTION-12) scale, with the AI evaluating participants' performance from the patient's perspective. These AI-generated ratings were then compared with human ratings to evaluate agreement and rating quality. To further investigate discrepancies between AI and human ratings, a qualitative analysis of selected cases was conducted. Additional measures included demographics, perceived authenticity, and benefits of the interaction. Quantitative analyses included group comparisons, pre-post analyses, and psychometric evaluation of the OPTION-12 scale in an AI-mediated setting. The study was preregistered on the Open Science Framework. A total of 58 participants were included in the analysis, 22 (37.9%) of whom were students, 34 (58.2%) were physicians, and 2 did not declare. Both groups reported similarly positive attitudes toward SDM, but medical students (n=22; mean 28.67, SD 4.32) achieved higher OPTION-12 performance scores than physicians (n=34; mean 22.79, SD 8.14). CSE showed a slight decrease following the intervention. Agreement between AI-generated and human OPTION-12 total scores was high (intraclass correlation coefficient=0.86, df=2,1; P<.001), although AI ratings were systematically higher. The OPTION-12 scale in the AI setting demonstrated good internal consistency (Cronbach α=0.88; mean interitem correlation r=0.43). Participants perceived the AI-simulated interaction as authentic and potentially useful for SDM training. This feasibility study provides preliminary and exploratory insights into the use of AI-simulated patients for SDM training in medical education. The findings contribute to the contextual validation of the OPTION-12 scale in AI-mediated consultations and provide valuable insights into participants' attitudes toward SDM. However, while findings suggest potential for supporting communication skills development and structured feedback, conclusions are limited by the study design and sample size. Further research with larger samples and controlled designs is needed to establish effectiveness and generalizability.
Road injuries are a leading cause of mortality and morbidity worldwide. Years of international efforts have aimed to strengthen policy engagement, including the 2020 UN General Assembly's proclamation of the Second Decade of Action for Road Safety (2021-30), targeting a 50% reduction in road traffic deaths and serious injuries by 2030. The aim of this study is to provide estimates to monitor progress and identify intervention gaps. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2023, we estimated incidence, mortality, and morbidity of road injuries for 204 countries and territories from 1990 to 2023. Four road injury types and 47 nature-of-injury categories were examined. Morbidity and mortality data from clinical records, vital registration, and police reports were harmonised using meta-analytic techniques to ensure consistency and correct for systematic bias. Incidence was modelled with the meta-regression tool Disease Modelling-Meta-Regression version 2.1 and cause-specific mortality with the Cause of Death Ensemble model, both incorporating location-specific covariates to support interpolation. Years of life lived with disability (YLDs) were estimated from the prevalence and severity of the nature of road injury, and years of life lost (YLLs) from the number of cause-specific deaths multiplied by the standard life expectancy at the age of death. Disability-adjusted life-years (DALYs) were the sum of YLLs and YLDs. All metrics were calculated with 95% uncertainty intervals (UIs). In 2023, there were 50·9 million (95% UI 46·1-56·1) road injury incident cases, 1·34 million (1·04-1·58) deaths, and 75·3 million (59·8-89·2) DALYs globally. Road injuries were the leading global cause of death among males aged 10-39 years. Between 1990 and 2023, age-standardised incidence decreased by 38·3% (95% UI 36·9-39·7) and mortality decreased by 32·3% (6·1-49·0), but progress varied widely by World Bank income group. Mortality in low-income countries (43·8 [95% UI 31·7-56·0] deaths per 100 000 population) was approximately six times higher than in high-income countries (7·5 [7·1-7·9] deaths per 100 000), despite the high-income countries showing the highest age-standardised incidence rates (858·1 [95% UI 781·9-947·1] cases per 100 000). In the past decade, many countries achieved notable reductions in road injuries, but others, including Ghana and the USA, saw increases. More severe injuries tended to occur in low-income and middle-income countries. Although global incidence, mortality, and DALY rates from road injuries have declined, progress remains uneven, with pronounced disparities across income groups reflecting systemic inadequacies in infrastructure, vehicle standards, enforcement, and post-crash care. Strengthening emergency response, improving road design, enforcing safety measures, and adapting policies to the evolving demographics remain essential. Gates Foundation.
Obesity is a leading public health concern in the United States, yet medical education continues to inadequately prepare future providers to manage it as a complex, chronic disease. Compounding this issue is the pervasive presence of weight bias in healthcare, which contributes to poorer patient outcomes, diminished quality of care, and reduced patient engagement. Despite growing awareness, obesity and weight bias education remain inconsistently integrated into medical curricula, often lacking structured, longitudinal, and competency-based approaches. While frameworks such as those developed by the Obesity Medicine Education Collaborative have advanced obesity-related competencies, weight bias remains underrepresented, with few formalized competencies guiding its instruction or assessment. Current efforts to reduce weight bias among medical school students are fragmented and often short-term. Interventions such as didactic modules, simulation-based experiences, and reflective exercises have shown promise in improving attitudes, yet most lack explicit mapping to weight bias competencies and fail to assess observable clinical behaviors. Weight bias education is rarely positioned as a core clinical skill, and standardized methods for competency assessment are virtually absent. In this article, we first review the current state of obesity and weight bias education in medical education and, second, reflect on experiences in developing the Weight of Words educational model, rooted in competency-based assessment and using our original instrument, the Weight Sensitivity Instrument (WSI©). We propose a theory-based approach informed by best practices, called the Weight of Words model, for weight bias education. The four-part educational model includes: (1) content delivery; (2) experiential learning; (3) reflection; and (4) competency assessment. The model represents a novel contribution to medical education by operationalizing weight bias competencies within a scalable, pedagogically rigorous framework and thus has far-reaching implications for medical practice. Without adequate training, future providers may unknowingly perpetuate stigma, erode patient trust, and compromise care quality. Addressing weight bias is essential for improving individual patient-provider interactions and for advancing health equity across the healthcare system.
Interprofessional collaboration is essential in today's healthcare environment. As such, preparing the next generation to confidently and sustainably enter the workforce is increasingly urgent. Experiential interprofessional education (IPE) interventions are particularly effective in bridging the gap between classroom learning and practical application. Community-based education further enriches these outcomes by immersing students in real-world environments that emphasize patient-centered care and responsiveness to community needs. However, IPE remains challenging to design and deliver in the clinical learning environment. The purpose of this report is to describe the design, implementation, and five-year outcomes of the Interprofessional Internship as a proof of concept for high-quality, community-based IPE, delivered from September 2020 to May 2025 through the University of Minnesota in Minneapolis, Minnesota. The model incorporates health profession intern teams carefully matched with community partner projects in areas such as quality improvement, community engagement, and organizational change, as well as professional development experiences designed to further advance interns' interprofessional competency. The Interprofessional Internship has completed 36 projects with 19 community organizations and involved 69 students from 24 academic programs. In line with internship goals, interns reported increased confidence in interprofessional competencies, corroborated by peer assessments, and outcomes demonstrate community partner engagement and their ability to advance their work through high-impact projects addressing health needs across the state. This innovative Interprofessional Internship offers a tangible, replicable model of training that integrates IPE into community-based experiential education while yielding meaningful community outcomes. Future pursuits beyond for-credit offerings include, but are not limited to, multi-partner community-based project design, longitudinal connections to geographically- or organizationally aligned learner teams with on-site experiential rotations, and integration of patients and communities in project work.
As medical education shifts toward competency-based curricula, faculty must navigate evolving expectations for teaching, mentoring, assessment, and scholarship. Despite their central role in training future health professionals, medical educators often face ambiguity regarding career advancement through teaching. Promotion criteria in academic institutions are frequently research-focused, leaving faculty unclear about how to document and demonstrate teaching excellence and educational innovation. This gap can hinder motivation, professional identity, and faculty retention. This study aims to explore the faculty development activities at Avalon University School of Medicine, a Caribbean medical school. This is a descriptive case study examining outcomes, including scholarly output, faculty ranking promotions, and fellowships, following the implementation of faculty development activities. Over 10 years, 20 medical educators involved in preclinical teaching were included in this study. They participated in various faculty development activities, including teaching, designing assessments, delivering effective feedback, developing curricula, and applying medical education research methodologies. Faculty members reflected on and practiced these practices in their teaching methods, assessment practices, and research in medical education. A total of eight faculty members received the Academy of Medical Educators (AoME) Fellowship. Four faculty members completed the IAMSE fellowship. One received the AMEE fellowship, and another received an associate fellowship. One received the AdvanceHE fellowship, and another received a principal fellowship. During these 10 years, 42 publications by faculty members in peer-reviewed journals in educational research were published, 26 abstracts were accepted at International medical education conferences, and 8 faculty members were promoted in faculty rankings. The findings from this case study indicate that the faculty development initiatives implemented at AUSOM were associated with enhanced faculty engagement in educational scholarship, professional recognition through educator fellowships, and academic career advancement. This experience suggests how a structured, longitudinal faculty development program can support faculty capacity building.
After nearly four decades of Chinese one-child policy, only-children have reached a point where they need to face the challenge of parental end-of-life care. However, current studies are limited to the whole process of parental aging and lacks attention to the difficulties and challenges that arise in end-of-life care. This study aims to explore experiences and supportive needs of adult only-children confronting their parental end-of-life care. This study was conducted in four medical institutions in Beijing, China. Sixteen participants were recruited through purposive and snowball sampling. Data were collected through semi-structured interviews. Interviews recordings were transcribed verbatim and analyzed following conventional content analysis approach. Three themes and nine subthemes were identified. Theme 1: Lonely boats: the characteristics of only-children confronting parental end-of-life care which includes: (a) there is no one to share burden, (b) there is no one to discuss, (c) there is no one to accompany. Theme 2: "Swaying in the storm": experiences of adult only-children confronting parental end-of-life care, including: (a) intensive physical caregiving burden, (b) solitary decision-making, (c) emotional turbulence and psychological pressure. Theme 3: Supportive needs in confronting parental end-of-life care, including (a) need for additional caregiving assistance, (b) need for medical decision and information support, and (c) need for empathy and emotional support. For adult only-children, parental end-of-life care is shaped by a structurally singular filial position in which there is no sibling to share caregiving responsibilities, no sibling to discuss difficult decisions with, and no sibling to accompany them emotionally through parental decline. This position may intensify their physical caregiving burden, solitary decision-making role, emotional turbulence and psychological strain. Targeted support should include flexible and trustworthy respite or caregiving services to relieve care burden. It should also include accessible medical information, decision-making support, advance care planning, and end-of-life education to reduce decisional isolation. Compassionate communication from healthcare professionals, together with peer and bereavement support, is needed to address emotional distress and grief. Coordinated healthcare, community, and social support systems are required to meet the distinctive needs of this growing caregiver population in China. Not registered.
Chikungunya (CHIK) is an emerging mosquito-borne disease with increasing importation risk in China. In non-endemic settings, delayed detection may facilitate local transmission, making healthcare workers' knowledge and attitudes critical for rapid response. To assess CHIK-related knowledge and attitudes among medical personnel in Chengdu, Sichuan Province, and identify factors associated with positive prevention attitudes. A cross-sectional, self-administered online survey was executed from July 30 to August 6, 2025, targeting medical workers across 20 healthcare institutions in Chengdu using the Wenjuanxing platform. The questionnaire gathered demographic information, CHIK-related training exposure (yes/no), and assessments of knowledge and attitudes. Knowledge was assessed using 15 items (range 0-15; 1 point awarded for each right response). Attitudes were evaluated using Likert-type items; a cumulative attitude score of ≥20 signified a favorable attitude. Group disparities were analyzed with Chi-square tests alongside suitable parametric and nonparametric assessments. Hierarchical logistic regression (Block 1: demographics/occupational characteristics; Block 2: training; Block 3: knowledge score) was employed to ascertain factors correlated with positive attitudes. 1,092 questionnaires were included, yielding an effective response rate of 90.10%; 83.70% indicated they had received training relevant. The average knowledge score was 11.66 ± 2.15. Despite high performance in primary prevention and clinical management, significant deficiencies were noted in early detection and surveillance-related operational knowledge: merely 42.58% accurately interpreted the RT-PCR Ct criterion, 54.85% recognized suspected cases, 56.14% comprehended diagnostic criteria, and 59.80% were aware of the 24 h online reporting requirement. Knowledge scores were elevated among individuals with advanced education, physicians, tertiary hospital personnel, and those who had training (p < 0.05). Attitude scores varied according to age, job type, hospital type, practice category, years of experience, and professional title (p < 0.05). In hierarchical logistic regression, training (OR = 3.971, p < 0.001) and elevated knowledge scores (OR per point = 1.130, p < 0.001) were independently linked to a favorable prevention-and-control attitude. Chengdu medical personnel demonstrated general CHIK knowledge and positive attitudes, yet significant operational gaps persist in early detection and reporting protocols. Training and knowledge are key determinants of favorable attitudes, highlighting the need for standardized, process-oriented training emphasizing diagnostic and reporting procedures.
Supervisory support during clinical placements is central to nursing students' professional development. Professional self-efficacy, students' confidence in performing clinical tasks, is increasingly recognised as a key outcome associated with transition to practice and workforce retention. In Saudi Arabia, Vision 2030 healthcare reforms have intensified demand for qualified nurses, making the quality of clinical supervision a strategic priority. This study examined the relationships among supervisory support, professional self-efficacy, and nursing student satisfaction at King Saud University-affiliated hospitals. This descriptive cross-sectional study was conducted among 145 nursing students (second-, third-, and fourth-year bachelor's degree students) at three King Saud University-affiliated teaching hospitals in Riyadh, Saudi Arabia. Participants were selected using stratified random sampling based on year of study. Data were collected using four validated instruments: a sociodemographic questionnaire, the Supervisory Support Scale (9 items; Cronbach's α = 0.90), the Nursing Student Satisfaction Scale (6 items; α = 0.88), and an adapted Professional Self-Efficacy Scale (12 items; α = 0.90). Descriptive statistics summarised the three key study variables (supervisory support, professional self-efficacy, and student satisfaction) alongside sociodemographic characteristics. Pearson correlation coefficients assessed the strength and direction of linear associations among continuous study variables. Formal mediation analysis was conducted using the PROCESS macro (Model 4) with 5,000 bias-corrected bootstrap resampling iterations. Of 175 students approached and meeting eligibility criteria, 145 returned valid questionnaires (response rate = 82.9%). The sample was predominantly female (60.7%) and in the age range of 20-22 years (66.9%). Students reported high levels of supervisory support (mean = 4.10 ± 0.53 out of 5), satisfaction with clinical placements (mean = 4.11 ± 0.52), and professional self-efficacy (mean = 4.06 ± 0.56). Supervisory support was strongly correlated with satisfaction (r = 0.68, p < 0.001) and professional self-efficacy (r = 0.57, p < 0.001); professional self-efficacy was positively correlated with satisfaction (r = 0.49, p < 0.001Statistical mediation analysis revealed that professional self-efficacy partially mediated the supervisory support-satisfaction relationship: the indirect association (ab = 0.13, 95% CI [0.07, 0.19]) was statistically significant and accounted for approximately 19% of the total association. In regression analysis, supervisory support remained significantly associated with satisfaction (β = 0.43, p < 0.001) even after accounting for professional self-efficacy, consistent with partial statistical mediation. Supervisory support was significantly and positively associated with nursing students' satisfaction and professional self-efficacy. These findings, grounded in social cognitive theory, suggest that high-quality supervision may enhance clinical learning outcomes both directly and through strengthening students' professional confidence. Standardising supervisory practices, investing in supervisor training, and creating structured feedback mechanisms are priorities for improving nursing education in Saudi Arabia and advancing national nursing workforce goals under Vision 2030.
Pediatric neurology training must evolve to meet increasing clinical complexity and rapid advances in neuroscience while maintaining high standards of family-centered care. In Saudi Arabia, structured residency programs have expanded under national accreditation frameworks; however, systematic evaluations of curriculum adequacy from the faculty perspective remain limited. This study aimed to comprehensively evaluate the pediatric neurology training curriculum within the Saudi Commission for Health Specialties (SCFHS)-accredited training system (including programs in Saudi Arabia and the United Arab Emirates [UAE]) from the faculty perspective, identifying strengths, gaps, and differences between program directors (PDs) and non-director faculty. We conducted a multi-institutional cross-sectional study between September and December 2025 targeting pediatric neurology faculty, including PDs, deputy directors, core faculty, and clinical staff involved in resident education. A validated 47-item questionnaire assessed satisfaction across six core curriculum components (educational resources, graduate autonomy and safety, clinical knowledge, clinical-academic balance, research opportunities, and professionalism), identified priority training gaps, and collected qualitative recommendations. Quantitative data were analyzed using descriptive statistics, non-parametric comparisons, correlation analysis, and exploratory multivariable linear regression. Open-ended responses underwent inductive thematic analysis. Forty-three consultants participated, including nine PDs. Overall satisfaction was moderate, with the highest ratings for resident professionalism (mean 3.8/5) and the lowest for clinical-academic balance (2.8/5) and research opportunities (2.9/5). Genetics and hereditary diseases (74%), neuroimmunology (70%), and neurodevelopmental disorders (63%) were the most frequently cited domains requiring greater emphasis. PDs reported significantly lower overall satisfaction than non-directors (β = -0.37, p = 0.02), particularly regarding academic time and research infrastructure. Satisfaction with educational resources strongly correlated with perceived research opportunities (ρ = 0.58, p < 0.001). Qualitative themes highlighted excessive service demands, insufficient protected academic time, limited research mentorship, and the need for structured training in rapidly evolving subspecialties. Pediatric neurology training in the region demonstrates strong clinical and professional foundations but is constrained by systemic challenges in academic balance, research support, and subspecialty preparedness. These perception-based findings suggest that PDs' heightened concerns may inform future curriculum development. Potential areas for consideration include protected academic time, enhanced research infrastructure, and nationally coordinated curricula in high-priority domains. However, these are exploratory implications requiring further evaluation before implementation.
The integration of artificial intelligence into healthcare is rapidly transforming clinical practice. Nurses' acceptance of artificial intelligence is influenced by their digital literacy and ethical awareness, yet empirical evidence examining these interrelationships is limited. We aimed to examine the direct and indirect effects of digital literacy on nurses' acceptance of artificial intelligence, with ethical awareness of artificial intelligence serving as a mediating factor. A cross-sectional, correlational design was conducted among 350 nurses working in medical-surgical and critical care units at El-Kasr Al-Aini hospital in Egypt from March 2025 to December 2025. Participants completed validated instruments assessing digital literacy, artificial intelligence ethical awareness, and artificial intelligence acceptance. Data were analyzed using descriptive statistics, Pearson correlations, and structural equation modeling (SEM) with bootstrapping to assess mediation effects. Participants demonstrated moderate levels of digital literacy, artificial intelligence ethical awareness, and artificial intelligence acceptance. SEM analysis revealed that digital literacy had a significant direct effect on artificial intelligence acceptance (β = 0.29, p < 0.001) and a strong effect on artificial intelligence ethical awareness (β = 0.46, p < 0.001). Artificial intelligence ethical awareness significantly mediated the relationship between digital literacy and artificial intelligence acceptance (indirect effect β = 0.13, p < 0.001), indicating partial mediation. The model exhibited good fit indices: chi-square/df (χ²/df) = 1.98, Comparative Fit Index= 0.95, Tucker-Lewis Index= 0.93, Root Mean Square Error of Approximation= 0.057, and Standardized Root Mean Square Residual= 0.045. Digital literacy enhanced participants' acceptance of artificial intelligence both directly and indirectly through ethical awareness. Ethical preparedness may, therefore, be a critical factor alongside technical competence in promoting artificial intelligence adoption among Egyptian nurses. Integrating digital literacy training with ethical education in Egyptian nursing curricula and continuing professional development programs may be able to facilitate safe and effective artificial intelligence adoption, supporting high-quality patient care in technologically advanced healthcare environments.
English proficiency is essential for medical students in non-English-medium settings, yet evidence on the effectiveness of fully web-based English for Medical Purposes (EMP) instruction remains limited. This study evaluated structured web-based EMP courses integrated into the preclinical curriculum of a Thai medical school. A pretest and posttest study was conducted with 535 second- and third-year medical students who completed newly developed online EMP courses aligned with concurrent preclinical subjects. English proficiency was assessed using the validated Khon Kaen University Medical English Test (KKUMET), covering listening, reading, writing, and speaking. Paired-sample t-tests demonstrated significant improvements across all language domains and total scores (from 64.62 (SD 11.42) to 79.33 (SD 7.23), P < .001), with large effect sizes (η2 = 0.77). Speaking and writing showed the greatest gains (+ 27.72 and + 25.54, respectively, all P < .001), reflecting improvements in active language production skills. The proportion of students at advanced or expert proficiency levels increased substantially (from 31.4% to 90.1%), and subgroup analysis indicated particularly strong improvements among those who were initially at beginner or intermediate levels (n = 356), mean scores increased by 18.91 points (P < .001, η2 = 0.85). These findings suggest that structured web-based EMP courses can effectively enhance medical English proficiency in large cohorts of preclinical learners. The online format provides flexibility for students managing heavy workloads and may reduce inequities in language readiness within medical curricula. Web-based EMP instruction represents a scalable approach for institutions seeking to strengthen communication competencies, academic readiness, and professional development in non-English-speaking contexts.
Electroencephalography (EEG) is a noninvasive tool used by healthcare professionals to measure brain electrical activity. EEG analysis can indicate various anomalies linked to different brain pathologies, including seizures. Traditionally, the analysis is confined to two-dimensional displays and relies exclusively on the visual modality, limiting a comprehensive overview. EEG analysis through visualisation is challenging and time-consuming, and artificial intelligence (AI) is increasingly used to aid the process of seizure detection. However, the educational value of AI-assisted seizure detection models depends on the explainability of the underlying models. Explainable AI can help learners understand the features and patterns associated with seizure detection and also support informed use of AI-based decision support systems. M2EEG-VR leverages the focus and immersive capabilities of virtual reality (VR) with the aim of developing a multi-modal platform for EEG seizure detection analysis with a human-in-the-loop. The ability to understand EEG and seizure patterns is key to addressing and effectively treating many neurological conditions. Neonatal seizure detection is particularly challenging where seizure patterns are subtle and context dependent. This study advances toward multi-modal analysis by encoding EEG signals into auditory representations using AI that aids in the acoustic detection of the presence of neonatal seizures in EEG. The platform also introduces a 3D brain model with a spatial mapping of seizure regions. In a user study (N = 20, 4 prior EEG experience, 16 no prior EEG experience), participants achieved higher seizure detection accuracy in the combined visual and auditory condition (mean = 7.6 ± 1.2) than in visual-only or audio-only modes. These preliminary findings suggest that a multi-modal environment may improve the accuracy of detection. However, further controlled studies are needed to ascertain the performance benefits. Usability was rated excellent (SUS = 83 ± 11), and task load remained moderate (NASA-TLX = 36.6). The findings suggest that VR multi-modal interaction can reduce cognitive load and enhance the explainability of complex EEG data in a focused virtual environment. The analysis of the diagnostic accuracy showed that participants without prior EEG knowledge performed similarly across all modalities to those with prior EEG knowledge. This implies that the accessibility barrier is reduced for novice users using the tool for the EEG review/detection task. This, together with high usability and moderate task load scores, indicates that the tool may be suitable for medical training applications. A multi-modal EEG in VR may prove useful in education and also be used as a test bench to further explore AI with human-in-the-loop paradigms for seizure detection.
End-of-life care raises complex ethical and legal questions shaped by national frameworks, cultural contexts, and personal beliefs. This comparative study explores how fifth-year medical students in Verona (Italy) and in Halle (Germany) understand and evaluate key end-of-life practices, including advance directives, withholding or withdrawing life-sustaining treatment, palliative care, medically assisted suicide, and life termination through drugs. The study also examines whether religiosity influences ethical orientations. A structured questionnaire consisting of 16 closed-ended items and one open question was administered to fifth-year medical students at the University of Verona and the University of Halle during the 2024-2025 academic year. Items assessed knowledge of legal frameworks, ethical attitudes, personal experiences with dying patients, and perceived educational preparedness. Descriptive statistics, cross-tabulations, and chi-square tests were used to compare cohorts, with statistical significance set at p < 0.05. A total of 259 valid responses were analyzed. Students in both countries showed strong consensus regarding the legitimacy and clinical usefulness of advance directives and the central role of palliative care. Acceptance of withholding or withdrawing treatment was high in both cohorts, though slightly higher in Germany. Marked differences emerged regarding life termination through drugs, with Italian students expressing more permissive and polarized positions and German students showing more moderate and cautious responses. Attitudes toward medically assisted suicide were broadly permissive in both groups, with religiosity emerging as a consistent predictor of more restrictive positions, particularly in Italy. While future physicians in both countries share core commitments to patient autonomy and palliative care, significant differences persist in their evaluation of practices intended to hasten death. These findings suggest that ethical orientations at the end of life are shaped not only by shared professional principles but also by national cultural environments and personal belief systems. Comparative research among medical students offers valuable insight into how medico-legal contexts and education influence emerging professional ethics.
Education on intersex health remains limited across healthcare professional training pathways, resulting in persistent gaps in workforce competencies. Existing educational initiatives are often fragmented, small in scale, and rarely evaluated beyond immediate post-training outcomes. Robust evidence on the sustainability of educational effects over time is still scarce. To evaluate the immediate and six-month educational impact of a large-scale e-learning training program on intersex health among healthcare professionals. We conducted a longitudinal cohort study of a national asynchronous e-learning program delivered between February and August 2023. The program targeted physicians, psychologists, midwives, and healthcare assistants and was designed using a problem-based learning approach. Educational outcomes were assessed at baseline (T0), immediately after course completion (T1), and at six-month follow-up (T2), using self-reported measures of attitudes and perceived skills, a knowledge assessment test, and a training satisfaction questionnaire. Statistical analyses included paired t-tests, ANCOVA, and McNemar tests. Among 6,332 participants completing both T0 and T1 assessments, 1,036 also completed the six-month follow-up. Participants were predominantly female (73.9%), with psychologists (47.8%) and physicians (39.1%) representing the largest professional groups. Significant improvements were observed at T1 in attitudes (+0.54), perceived skills (+1.45), and knowledge (+11.7 percentage points; all p < 0.001). Improvements were largely sustained at T2, with only modest declines across domains. Baseline differences by gender, geographic area, and professional group were substantially reduced following training. Overall satisfaction with the program was high (mean score 4.48/5) across participant subgroups. This study provides longitudinal evidence that a large-scale e-learning training program was associated with significant and sustained improvements in healthcare workforce competencies in a traditionally under-addressed area of care. Structured, cross-disciplinary training delivered through accessible digital formats may offer a scalable strategy to strengthen workforce preparedness and reduce educational gaps in intersex healthcare.
Student Promotions Committees (SPCs) are tasked with making life-altering decisions regarding student advancement, remediation, and dismissal. Most research focuses on the legal requirements of due process, yet the nuanced role of the student's case presentation has received minimal scholarly attention. This study investigates the criteria SPC committees utilize when evaluating student presentations and how these factors influence committee decisions. This qualitative study employed elements of constructivist grounded theory to frame data collection and analysis. We conducted 15 semi-structured interviews with current and former SPC members at a U.S. military medical school. Using constant comparative methods, 'insight' was identified as a salient in faculty decisions. To interpret these findings, we utilized a conceptual framework from rehabilitation science, which describes the mechanisms by which courts evaluate an individual's potential for reform. Insight emerged as a critical component of the SPC's deliberation process, serving as both an essential prerequisite for professional growth and a significant indicator of future risk when found lacking. Students demonstrated insight by assuming full ownership of their academic or professional issues, utilizing institutional resources, and actively collaborating with the committee. Conversely, a lack of insight was signaled by doing nothing, externalizing blame, or repeating problematic actions despite prior interventions. The prominence of insight suggests that medical education has unintentionally adopted a burden of proof like the legal system, requiring students to demonstrate rehabilitation to maintain their professional standing. By articulating these implicit expectations, this study provides transparency, potentially fostering a more equitable and effective remediation process.
Continuous professional development is essential for maintaining teaching excellence in health professions education. However, the extent to which faculty development is valued in high-stakes personnel decisions remains unclear. This study conducted a comprehensive systematic review of the seven core health professions to determine how participation in faculty development is codified and incentivized within advancement, promotion, and tenure (APT) policies. A definitive study population (N = 3,101) was established using official accreditation directories for dentistry, medicine (MD/DO), nursing, pharmacy, physical therapy, and physician assistant programs in the United States. We employed a comprehensive, automated data harvesting pipeline to retrieve public policy documents via the Google Custom Search API. Following PRISMA guidelines, an automated content refinery filtered the dataset to 10,850 valid policy documents. Thematic analysis quantified the prevalence of faculty development terminology and requirements. Text analysis of the final corpus identified 29,812 unique policy excerpts related to faculty development. The most dominant themes were Process/Requirement (41.5%) and General Terminology (41.4%), while Assessment requirements appeared in 13% of excerpts, and explicit Formal Structure requirements (e.g., Teaching Academies) appeared in only 4.1% of excerpts. A significant prevalence gap emerged between disciplines: Physician Assistant programs were the most likely to reference professional development (65.3%), whereas Physical Therapy programs were the least likely (11.0%). Pharmacy (28.6%) and Medicine (MD: 49.4%; DO: 32.3%) fell in the middle range. While universities frequently reference professional development as a general value, they rarely codify it as a requirement for tenure. A systemic Input/Output Paradox exists: institutions rigorously assess teaching effectiveness (outputs) but treat the developmental activities necessary to achieve it (inputs) as voluntary resources rather than professional standards. To better align institutional values with faculty incentives, Health Professions Institutional leaders may examine their policies to ensure alignment between faculty development and promotion criteria.
Artificial intelligence (AI), particularly machine learning and large language models (LLMs), has seen rapid advancements and widespread adoption over the past decade, transforming many fields, including healthcare. ChatGPT is one of the prominent chatbot interfaces that is powered by generative pre-trained transformers. ChatGPT can generate natural, human-like conversations on diverse topics, and its performance depends on the underlying model version. Due to its accessibility and versatility, this chatbot interface has generated significant interest in its use for patient education, especially among those seeking information about orthopaedic procedures, such as hip replacement surgery. Despite growing enthusiasm, the extent and nature of evidence regarding AI-based chatbots' role in educating hip replacement patients remain unclear. To systematically map and summarise the existing literature on AI-based chatbot interventions for patient education in hip replacement surgery. Specifically, to identify relevant studies, describe their characteristics and outcomes, highlight gaps in the current evidence, and provide recommendations to inform future research and clinical practice in digital health education for orthopaedic care. Following PRISMA-ScR guidelines, a systematic search of peer-reviewed articles published in English and available in databases such as EBSCO, PubMed, and Scopus was conducted. Studies were screened and selected based on predefined inclusion and exclusion criteria. Key data on chatbot features, educational content, and outcomes were extracted and thematically synthesised. Methodological quality was appraised using the Mixed Methods Appraisal Tool (MMAT) to ensure transparency and rigour. Ten studies, 4 quantitative non-randomised and 6 quantitative descriptive, evaluated a specific LLM, i.e. ChatGPT. Chatbots generally provided accurate, clear, and patient-friendly information, facilitating engagement and readability. Limitations included unreliable references, a limited personalisation, and a need for clinician oversight. Overall, AI-based chatbots show promise as supplementary educational tools but should not currently replace expert guidance. AI-based chatbots show promise as supplementary tools for educating hip replacement patients, but require careful integration with clinical guidance. This review maps current evidence, guiding future research to optimise their use in orthopaedic patient education. These findings are particularly relevant for orthopaedic nurses, who play a central role in delivering patient education and supporting informed recovery.