Aliya S Khan, Caroline J Cushman, Cameran Mecham, Stephanie Stroever, Trey Morris
{"title":"Preparing Emergency Medicine Residents to Lead Level 1 Multidisciplinary Trauma Teams: A Scoping Review.","authors":"Aliya S Khan, Caroline J Cushman, Cameran Mecham, Stephanie Stroever, Trey Morris","doi":"10.1002/aet2.70185","DOIUrl":"10.1002/aet2.70185","url":null,"abstract":"<p><strong>Background: </strong>In the United States, the initial management of trauma patients is coordinated by multidisciplinary teams, typically led by surgeons. As a result, Emergency Medicine (EM) residents often have limited experience in the trauma team lead role. However, in rural or critical access hospitals, EM physicians frequently serve as team leaders without surgical backup.</p><p><strong>Objective: </strong>To map and summarize educational strategies used to train EM residents to lead Level 1 trauma resuscitations and describe how outcomes such as confidence, performance, and preparedness are assessed.</p><p><strong>Methods: </strong>Following Joanna Briggs Institute scoping review methodology, a systematic search of PubMed and Embase was conducted. Inclusion criteria focused on training EM residents in trauma leadership using keywords related to education, competence, and leadership. Covidence was used for blinded screening and data extraction, and 23 studies were included following double-blind review.</p><p><strong>Results: </strong>Simulation-based training dominated the literature, including high-fidelity mannequins, cadaver labs, animal models, and standardized patients. Combined approaches integrating didactics, video-assisted debriefs, and mental rehearsal improved trauma leadership, procedural, and nontechnical skills. Most studies evaluated outcomes using self-reported confidence and perceived competence, while fewer used validated performance assessment tools in simulated settings, and only one study evaluated resident leadership in real-world trauma activations. Studies also assessed psychosocial constructs such as confidence and stress.</p><p><strong>Conclusion: </strong>Existing literature describes simulation as the most frequently used modality for trauma leadership training among EM residents, often paired with structured debriefing, didactics, mental rehearsal, and progressive complexity. Most studies assess learner-reported outcomes and simulated performance, while real-world clinical leadership assessment remains limited. Future efforts should prioritize curriculum development, standardized evaluation tools (Kirkpatrick or milestone-based outcomes), and longitudinal models that combine simulation with real-world practice to ensure consistent, high-quality trauma leadership preparation.</p>","PeriodicalId":37032,"journal":{"name":"AEM Education and Training","volume":"10 ","pages":"e70185"},"PeriodicalIF":1.6,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13176107/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147965014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Aldalou, William S Brooks, Emily Rush, Bernard Landry-Wegener, Corey Bills, David A Cook, John Swope, Adam B Wilson
{"title":"Using Generative AI to Appraise the Quality of Medical Education Research Studies: Agreement Between AI-Generated and Human MERSQI Scores.","authors":"Mohammad Aldalou, William S Brooks, Emily Rush, Bernard Landry-Wegener, Corey Bills, David A Cook, John Swope, Adam B Wilson","doi":"10.1002/aet2.70189","DOIUrl":"10.1002/aet2.70189","url":null,"abstract":"<p><strong>Objectives: </strong>The increasing volume of medical education research necessitates efficient, reliable, and scalable methods for conducting quality appraisals. The Medical Education Research Study Quality Instrument (MERSQI) is a widely used tool, although its manual scoring process remains resource-intensive. This study evaluated how well large language models (LLMs) appraise medical education research using the MERSQI tool in comparison with human judges.</p><p><strong>Methods: </strong>Three LLMs (GPT-5, Claude Sonnet 4, and Gemini 2.5 Pro) assigned MERSQI domain scores to 1423 medical education research articles. The authors compared AI-generated scores with human-generated scores using intraclass correlation coefficients (ICCs) across the six MERSQI domains. They evaluated the agreement between AI- and human-generated MERSQI composite scores using Bland-Altman plots.</p><p><strong>Results: </strong>Domain-level ICC values ranged from fair (0.24) to near perfect (0.81), with the lowest agreement observed in the 'sampling,' 'validity evidence,' and 'data analysis' domains. No single LLM consistently outperformed the others across all domains. Composite score agreement with human ratings was substantial and similar across LLMs (ICC range: 0.65-0.69). GPT-5 produced slightly lower composite scores than humans, while Claude Sonnet 4 and Gemini 2.5 Pro produced higher scores, with Gemini showing the largest deviation. The Bland-Altman plots for Gemini 2.5 Pro suggested proportional bias, indicating its agreement with human scores varied across the range of study quality.</p><p><strong>Conclusions: </strong>These LLMs demonstrated substantial agreement with human raters for MERSQI composite scores, but domain-level agreement varied. Systematic differences in scoring patterns highlight the need for human oversight and additional calibrations before integrating LLMs into systematic review appraisal workflows.</p>","PeriodicalId":37032,"journal":{"name":"AEM Education and Training","volume":"10 ","pages":"e70189"},"PeriodicalIF":1.6,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13176095/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147965093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Neelou Weeker, Ivan Zvonar, Esther H Chen, Samuel O Clarke
{"title":"Structural Competency: A Lifeline in a Time of Crisis.","authors":"Neelou Weeker, Ivan Zvonar, Esther H Chen, Samuel O Clarke","doi":"10.1002/aet2.70186","DOIUrl":"10.1002/aet2.70186","url":null,"abstract":"<p><p>Emergency departments occupy a unique position in the healthcare system: they are often where the consequences of upstream policy manifest most acutely. Structural competency-a framework for understanding how economic, political, and historical forces shape health-offers emergency medicine educators a practical means of preparing trainees to recognize and respond to those forces. This framework is grounded in five core domains: <i>recognizing structures that shape clinical interactions</i>, <i>developing an extra-clinical language of structure</i>, <i>rearticulating \"cultural\" presentations in structural terms</i>, <i>observing and imagining structural interventions</i>, and <i>developing structural humility</i>. In this current political climate, structural competency can serve as a catalyst for training reform, particularly in areas where recent legislative changes have directly impacted patient care: reproductive health, immigration enforcement, and gender-affirming care. Drawing on published curricula, institutional experience, and a growing body of evidence documenting the structural barriers facing emergency department patients, we outline how the five domains of structural competency translate into specific educational interventions such as didactic teaching, simulation, community engagement, and systems-level initiatives. By focusing on practical strategies that extend beyond the bedside, this commentary highlights the importance of equipping trainees to navigate policy-driven challenges and deliver equitable care. Structural competency is therefore not an abstract framework but a practical tool for equipping residents to provide equitable care in a rapidly changing sociopolitical environment.</p>","PeriodicalId":37032,"journal":{"name":"AEM Education and Training","volume":"10 ","pages":"e70186"},"PeriodicalIF":1.6,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13176084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147965045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mastering Pediatric Airway Skills: A Procedural Simulation Using Rapid Cycle Deliberate Practice for Emergency Medicine Residents.","authors":"Kei U Wong, Isabel T Gross","doi":"10.1002/aet2.70180","DOIUrl":"10.1002/aet2.70180","url":null,"abstract":"<p><strong>Background: </strong>Pediatric emergency medicine (PEM) training within emergency medicine (EM) residency programs varies widely in preceptor expertise, critical care exposure, and procedural opportunities. Despite the importance of pediatric airway management, real-world exposure to critically ill children remains limited and inconsistent across training sites. Current ACGME guidelines provide minimal direction on pediatric-specific content or mandatory procedures, leaving gaps in emergent airway training.</p><p><strong>Objective of the innovation: </strong>To address perceived deficiencies in pediatric airway skills among EM residents, we implemented a longitudinal, simulation-based pediatric airway curriculum. The primary goal was to improve pediatric airway knowledge, confidence, procedural competency in airway equipment setup, bag-valve-mask (BVM) ventilation, troubleshooting, intubation techniques using a flipped classroom model, and rapid cycle deliberate practice (RCDP).</p><p><strong>Development process and implementation: </strong>Guided by Kern's curriculum design framework and selected components of Sawyer's six-step procedural learning model, the curriculum incorporated asynchronous learning and eight interactive simulation sessions over a 12-month period. 40 residents in four postgraduate years participated in two individualized RCDP sessions annually, supported by faculty trained in pediatric airway management. A novel checklist was used for objective performance assessment.</p><p><strong>Outcomes: </strong>Thirty-one residents completed baseline and post-intervention procedural assessments. Significant improvements were observed in equipment setup and intubation steps (<i>p</i> < 0.05), with first-pass intubation time reduced from 9 min and 12 s to 7 min and 9 s (<i>p</i> < 0.05). Self-reported confidence in pediatric airway management increased across all PGY levels (<i>p</i> < 0.05), and knowledge scores improved (7.8 vs. 9.7, <i>p</i> < 0.05). Resident feedback strongly endorsed the curriculum's value in building skills and confidence.</p><p><strong>Conclusion: </strong>A structured, simulation-based pediatric airway curriculum using RCDP effectively enhances EM residents' procedural performance and confidence. This model offers a scalable approach for addressing critical skill gaps in PEM training. Future directions include integrating advanced airway techniques and longitudinal retention assessments.</p>","PeriodicalId":37032,"journal":{"name":"AEM Education and Training","volume":"10 ","pages":"e70180"},"PeriodicalIF":1.6,"publicationDate":"2026-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13159709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147934220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}