Academic Medicine最新文献

{"title":"One-time introductory language experiences as gateways to longitudinal medical Spanish education.","authors":"Juli McCarroll","doi":"10.1093/acamed/wvag296","DOIUrl":"https://doi.org/10.1093/acamed/wvag296","url":null,"abstract":"","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149118132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Specialty‑level patterns of professionalism concerns in academic health systems: a multi‑system analysis with heat map visualizations.","authors":"Heather A Davidson, William Martinez, Thomas W Doub, Cynthia A Baldwin, Henry Domenico, William O Cooper, Gerald B Hickson","doi":"10.1093/acamed/wvag293","DOIUrl":"https://doi.org/10.1093/acamed/wvag293","url":null,"abstract":"<p><strong>Purpose: </strong>Unprofessional behavior in healthcare settings can undermine teamwork, communication, and patient outcomes. Although prior studies have shown that professionalism concerns are disproportionately concentrated among a subset of individual clinicians, less is known about specialty-level patterns. The purpose of this study was to examine whether professionalism concerns, measured using the Patient Advocacy Reporting System (PARS) risk categories, cluster at the specialty-group level within and across academic health systems (AHSs).</p><p><strong>Method: </strong>This retrospective, cross-sectional study used PARS risk categories, derived from deidentified unsolicited patient complaint data collected between March 1, 2014, and November 30, 2019. The study population consisted of 23,789 physicians representing 52 specialty groups and practicing across 19 Academic Health Systems (AHS) from multiple geographic areas regions of the United States. Physicians were categorized into high, intermediate, or low PARS risk categories. Inferential analyses used Pearson's chi-square tests to compare proportions of physicians within each risk category across specialties within the same AHS and within specialties across AHSs. Heat maps were created to visually summarize risk-category distributions.</p><p><strong>Results: </strong>Across the 19 AHSs, an average of 1.5% (n = 341) of physicians were classified as high PARS risk and 8.6% (n = 2149) as intermediate PARS risk, with substantial site-level variation. Statistically significant differences in PARS risk-category distributions across specialties were observed within 16 of 19 AHS (P<.001). Among the 23 specialties represented at all 19 AHSs, 69.6% (16/23) demonstrated significant (P<.05) between-system differences in risk-category distributions.</p><p><strong>Conclusions: </strong>The findings suggests that professionalism concerns may cluster at the specialty- group level both within and across AHSs. Routine specialty-level review, guided by statistical comparisons and complemented by heat map visualizations, may help leaders identify specialty groups and organizational contexts that warrant further evaluation to support professionalism and teamwork.</p>","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining academic physicians across health systems: a perspective from China.","authors":"Fei Zhang, Zhong Wang","doi":"10.1093/acamed/wvag298","DOIUrl":"https://doi.org/10.1093/acamed/wvag298","url":null,"abstract":"","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond applicant priorities: unintended consequences of pass/fail USMLE Step 1 on institutional equity.","authors":"Riya Mehta","doi":"10.1093/acamed/wvag299","DOIUrl":"https://doi.org/10.1093/acamed/wvag299","url":null,"abstract":"","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond learning analytics: toward learning ecosystems in artificial intelligence-enabled health professions education.","authors":"Rebekah Cole","doi":"10.1093/acamed/wvag295","DOIUrl":"https://doi.org/10.1093/acamed/wvag295","url":null,"abstract":"","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149065694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal Changes in Feedback Quality After Nationwide Implementation of a Mobile Application for Entrustable Professional Activity Data Management in Thailand.","authors":"Khuansiri Narajeenron, Stephen J Kerr, Intanon Imsuwan, Cherdsak Iramaneerat, Ara Tekian, Yoon Soo Park","doi":"10.1093/acamed/wvag290","DOIUrl":"https://doi.org/10.1093/acamed/wvag290","url":null,"abstract":"<p><strong>Purpose: </strong>This national study examined longitudinal changes in perceived feedback quality during phased rollout of a mobile entrustable professional activity (EPA)-based feedback application across Thai College of Emergency Physicians-accredited emergency medicine residency programs and explored institutional, contextual, and application-use variables associated with perceived feedback quality.</p><p><strong>Method: </strong>This national, multisite prospective observational study (December 2019 to September 2020) included 135 faculty and 357 residents from accredited Thai emergency medicine residency programs. The application was implemented in three phases: notifications, feedback guide/self-reflection prompts, and dashboard. Participants completed FEED-ER across five domains (timeliness, specificity, communication, action plan, feedback culture) using 5-point Likert-type items. Scores were converted to Percent of Maximum Possible (POMP; 0-100; higher scores indicate higher perceived feedback quality). Linear mixed-effects models estimated changes in domain and total FEED-ER POMP scores over time; total-score models assessed associations with institutional, contextual, and application-use variables.</p><p><strong>Results: </strong>Faculty-reported overall perceived feedback quality did not change significantly at 3 months but increased at 6 months (4.03 POMP; 95% CI, 1.99 to 6.07) and 9 months (3.57; 95% CI, 1.02 to 6.11). Resident-reported overall scores did not change significantly. In resident models, dashboard review (always 2.54; 95% CI, 0.18 to 4.89; sometimes 2.21; 95% CI, 0.32 to 4.09) and resident rules (1.78; 95% CI, 0.09 to 3.48) were associated with higher scores; absence of formal feedback strategies was associated with lower scores (-2.00; 95% CI, -3.87 to -0.13).</p><p><strong>Conclusions: </strong>During implementation of a mobile EPA-based feedback application, faculty reported modest improvements in perceived feedback quality, whereas resident perceptions remained stable. Digital tools may support feedback processes when aligned with institutional context. Future studies should link feedback to encounters and evaluate mechanisms and downstream educational outcomes using designs that strengthen causal inference.</p>","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149018627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current state and future opportunities in applying visual analytics in medical education: a scoping review.","authors":"Scott Vennemeyer, Andy Gao, Gargi Rajput, Daniel J Schumacher, Brad Sobolewski, Melissa D Klein, Umberto Tachinardi, Mark H Eckman, Eric J Warm, Danny T Y Wu","doi":"10.1093/acamed/wvag291","DOIUrl":"https://doi.org/10.1093/acamed/wvag291","url":null,"abstract":"<p><strong>Purpose: </strong>Visual analytics is a nascent and underexplored area in the medical education literature that can assist in synthesizing large volumes of data and information to provide actionable insight. This scoping review aims to identify: 1) the characteristics of the studies that have applied visual analytics in medical education, 2) how visual analytics are being used to support medical education efforts.</p><p><strong>Method: </strong>This study followed the Joanna Briggs Institute (JBI) scoping review guidelines to search four databases in mid-April 2026: PubMed, IEEE Xplore, Scopus, ACM Digital, along with Google Scholar. Key search terms included \"medical education\" and \"visual analytics\"; papers that did not implement visual analytics systems in the medical education context were excluded. Variables of the eligible papers were extracted and further analyzed in terms of study characteristics (publication year, study location, primary focus & level of trainees assessed) and application of visual analytics (type of visualization, framework guidance, hardware/software, evaluation technique).</p><p><strong>Results: </strong>Of the 39 eligible papers from 584 screened, 20 (51.3%) were published in the United States. Using visual analytics for learner competency assessment and quality improvement of training programs were the primary focuses. For trainees, nearly all papers focused on assessing residents and medical students. More than 28 (71.8%) studies utilized an interactive tool/dashboard and/or applied an evaluation technique. Only 14 (35.9%) involved a framework-guided design of the visualization.</p><p><strong>Conclusions: </strong>This review highlights that while visual analytics is maturing in medical education, systemic application requires adopting framework-guided visualization design, expertise-matched tools, and goal-oriented evaluation. Future research should prioritize interoperable frameworks for knowledge sharing, controlled field studies assessing impacts on learner competencies, and patient outcomes, and \"cross-continuum\" dashboards spanning pre-medical through faculty levels. These strategies allow educators and learners to make sense of complex educational data through visual analytics dashboards, ultimately enhancing assessment and patient care quality.</p>","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149026732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Not meeting expectations: A qualitative study of feedback from program directors about residents who did not meet performance expectations.","authors":"John W Ragsdale, Amy Pineda, Lynn Shaull, Douglas Grbic, Lisa Doyle Howley","doi":"10.1093/acamed/wvag292","DOIUrl":"https://doi.org/10.1093/acamed/wvag292","url":null,"abstract":"<p><strong>Purpose: </strong>The AAMC's Resident Readiness Survey (RRS) is administered to program directors (PDs) nationally about their postgraduate year-1 (PGY-1) residents and provides feedback to medical schools about their effectiveness in preparing graduates for residency. The authors sought to characterize the factors contributing to a PD's assessment that a resident had not met expectations.</p><p><strong>Method: </strong>Using 2023-2024 RRS data, the authors performed a qualitative analysis of free text responses from PDs regarding residents who were evaluated as \"did not meet overall performance expectations.\" The authors independently coded those comments using conventional content analysis to describe the categories of comments present. Using a recursive approach, they iteratively discussed and refined their codes until achieving consensus.</p><p><strong>Results: </strong>On the RRS, 431 PGY-1 residents were evaluated by PDs as not meeting expectations (2.9% of 14,641 completed surveys). Of these 431 residents, 309 residents (71.7%) had comments available for analysis. Categories for PDs' comments corresponded to challenges in five competencies with identified subcategories for each. In addition, professionalism and practice-based learning and improvement were identified as mitigators of challenges in other domains. PDs also provided comments about potential reasons a resident was not meeting performance expectations, including limited clinical exposure in medical school, inadequate identification by the medical school of performance issues, or a lack of communication to residency programs about those issues.</p><p><strong>Conclusions: </strong>PDs' comments described challenges of PGY-1 residents in five particular competencies, highlighting alignment between national competency frameworks for undergraduate medical education and how PDs view resident performance. The findings also highlight opportunities to improve the transition ecosystem, including enhanced student assessment in undergraduate medical education and improved communication to residency programs about medical school graduates' strengths and areas for continued growth and development.</p>","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149026762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Academic Medicine: Where have we been? Where are we going?","authors":"Kenneth M Ludmerer","doi":"10.1093/acamed/wvag286","DOIUrl":"https://doi.org/10.1093/acamed/wvag286","url":null,"abstract":"<p><p>The occasion of Academic Medicine's centennial anniversary (2026) provides the opportunity to look back to its history and forward to its future. The journal was founded in the aftermath of the revolution in American medical education of the late 19th and early 20th centuries. The events of that era are reviewed to correct the common misperception that little had happened in American medical education before the Flexner report of 1910. The work of Academic Medicine over 100 years is described, with an emphasis on how its focus expanded from the internal mechanics of medical education to include the complex, powerful external forces that affect medical education, research, and practice. In this effort, Academic Medicine has served as the profession's conscience, helping identify core values that must be defended to allow success in any future scenario.</p>","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149002837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging algorithm and narrative: natural language processing, narratology, and radical empathy as core competencies in medical education.","authors":"Omar Dabash, Michael J Daly","doi":"10.1093/acamed/wvag289","DOIUrl":"https://doi.org/10.1093/acamed/wvag289","url":null,"abstract":"<p><p>As artificial intelligence (AI) increasingly shapes clinical practice, medical education faces a critical moment: integrating computational literacy with narrative understanding and radical empathy. This commentary argues that future physicians must master not only how machines extract meaning from clinical text but also how to preserve narrative complexity, honor patient agency, and maintain relational care in technologically mediated environments. The authors propose a framework for integrating natural language processing (NLP), narratology, and radical empathy into medical curricula. Drawing on evidence from narrative medicine interventions, emerging applications of clinical NLP, and literature on clinician well-being, the commentary demonstrates that narrative literacy-coupled with computational awareness-enhances diagnostic reasoning, reduces bias, and cultivates the empathy essential for patient-centered care. The authors examine barriers to curricular integration, propose pedagogical strategies, and outline implications for medical education reform.</p>","PeriodicalId":50929,"journal":{"name":"Academic Medicine","volume":" ","pages":""},"PeriodicalIF":4.5,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148978351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}