Journal of Educational Evaluation for Health Professions最新文献

{"title":"A practical guide to automated test assembly for educational evaluation in health professions: a demonstration using the R package ROI.","authors":"Hwanggyu Lim, Kyung Sik Kim, Jeongwook Choi","doi":"10.3352/jeehp.2026.23.31","DOIUrl":"https://doi.org/10.3352/jeehp.2026.23.31","url":null,"abstract":"<p><p>Automated test assembly (ATA) using mixed-integer programming (MIP) is standard practice in international testing organizations, but detailed and accessible practical guidelines remain scarce for health professions assessment. This study introduces the mathematical foundations of MIP-based ATA and provides a step-by-step tutorial demonstrating its implementation with the open-source R package ROI and the HiGHS solver. We constructed a modified 928-item pool with empirical item parameters from the Clinical Medical Science Comprehensive Examination, establishing 31 content categories and 18 enemy-item groups. Using the ROI package and the HiGHS solver, we modeled and solved 3 assembly scenarios: a single 80-item form under a relative target, 2 parallel 80-item forms under a relative target, and 2 parallel 80-item forms under an absolute target combined with additional mean item difficulty constraints. All 3 optimization scenarios satisfied the test-length, content-blueprint, and enemy-item constraints. The relative-target forms attained observed-to-target information ratios within rounding error of the targets, producing closely equivalent parallel forms. The absolute-target forms closely approximated the specified information curve, with a maximum deviation of 0.27 information units, and their mean difficulties fell within the targeted range of 0.2 to 0.4. All formulated MIP models converged to optimal solutions within a few minutes. The practical combination of the ROI package and the HiGHS solver offers an efficient, reproducible, and cost-effective method for test assembly. This approach may enable Korean health professions examination programs to construct psychometrically equivalent and content-balanced test forms, facilitating the transition toward item-bank-based testing systems.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"31"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149185261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large language model-generated versus teacher-written objective structured clinical examination stations for medical students: a blinded comparative pilot study.","authors":"Piotr Szychowiak, Jonathan Wong-So, Hélène Messet, Mélanie Faure, Isaure Breteau, Simon Jamard, François Barbier, Maxime Desgrouas","doi":"10.3352/jeehp.2026.23.9","DOIUrl":"10.3352/jeehp.2026.23.9","url":null,"abstract":"<p><p>Developing objective structured clinical examination (OSCE) stations is time-consuming for medical teachers. We aimed to evaluate the ability of a large language model (LLM) to generate ready-to-use OSCE stations. Five OSCE stations generated by the LLM GPT-4o were evaluated by 7 expert assessors using a 5-point Likert scale and compared with 5 teacher-written stations targeting similar learning objectives. A station was considered to be of good quality if most assessors responded \"agree\" or \"strongly agree\" to the statement \"The station is good enough to be used by students.\" All teacher-written stations were rated as being of good quality, compared with only one GPT-4o-generated station. The LLM produced adequate clinical scenarios when reference knowledge was provided and tasks were clearly ordered, but it failed to generate reliable assessment grids. Careful review by teachers remained essential. GPT-4o failed to consistently produce fully ready-to-use OSCE stations.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"9"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148018160","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":"From accommodation to inclusion: understanding barriers and facilitators in clinical dental education for Chilean students with hearing disabilities: a qualitative study.","authors":"Josefa P Retamal-Martínez","doi":"10.3352/jeehp.2026.23.20","DOIUrl":"10.3352/jeehp.2026.23.20","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to describe inclusive mechanisms supporting dental students with hearing disabilities, focusing on facilitators of and barriers to participation in clinical education.</p><p><strong>Methods: </strong>A qualitative case study was conducted at a Chilean university. Data were collected through semi-structured interviews with 2 students with hearing disabilities, 3 clinical instructors, and 1 Chilean Sign Language interpreter who works at the university and supports dental students with hearing disabilities, as well as through direct observation. Data were analyzed using inductive thematic analysis. Participant validation was used to enhance credibility.</p><p><strong>Results: </strong>Facilitators were identified across pedagogical, technological, communicative, and relational domains. Pedagogical adaptations included early access to materials, visual resources, and flexible assessments. Technological tools such as real-time transcription supported communication and access to information. Alternative communication strategies included lip reading, written support, visual cues, and Chilean Sign Language. The presence of an interpreter was a key enabling factor. Relational support from faculty, peers, and family members also contributed substantially. Faculty flexibility and willingness to adapt were particularly important. Barriers were identified at structural, institutional, communicative, and attitudinal levels. Clinical environments presented physical and acoustic challenges, including noise, limited space, and complex interactions. Institutional responses were often reactive and involved limited planning. Communication barriers affected interactions with patients and peers, as well as academic literacy. Faculty reported limited training in inclusive education. Attitudinal barriers included misconceptions about disability and limited experience with disability.</p><p><strong>Conclusion: </strong>Inclusive mechanisms are present but insufficiently systematized. Strengthening institutional planning and structural adaptations is essential to ensuring equitable clinical education.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"20"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13500177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148346827","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":"Evaluation of a peer-assisted, simulation-based clinical skills training program in Spain: a prospective single-group before-and-after study.","authors":"Maria López-Brotons, Sergio Javaloy-Ballestero, José-Manuel Ramos-Rincón","doi":"10.3352/jeehp.2026.23.15","DOIUrl":"10.3352/jeehp.2026.23.15","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to evaluate the implementation and evolution of a peer-assisted, simulation-based clinical skills program at Miguel Hernández University, Spain, focusing on medical student participation, perceptions, and perceived educational value.</p><p><strong>Methods: </strong>A prospective quasi-experimental pre-post study without a control group was conducted. Sessions were organized in small groups and led by senior student tutors under faculty supervision. Six workshops were offered during the first academic year and 8 during the second, with the addition of lumbar puncture and introductory clinical ultrasound. Knowledge acquisition was assessed using pre- and post-workshop questionnaires, and satisfaction was evaluated with Likert-scale surveys.</p><p><strong>Results: </strong>A total of 154 students participated, including 77 in 2023-2024 and 77 in 2024-2025, generating 440 workshop attendances. After incomplete questionnaires were excluded, 425 paired pre- and post-workshop evaluations were analyzed. Students reported improved learning, with self-reported knowledge scores increasing significantly from 6.1±2.6 to 8.7±1.6 (Δ=2.5; 95% confidence interval [CI], 2.29-2.71; Cohen's d=1.14; P<0.001). Male students showed greater knowledge gain than female students (Δ=2.8 vs. 2.3; 95% CI, 2.17-3.43 vs. 1.91-2.69; Cohen's d=1.17 vs. 1.15; P=0.034), and second-year students improved more than third-year students (Δ=2.9 vs. 2.1; 95% CI, 2.36-3.44 vs. 1.67-2.53; Cohen's d=1.21 vs. 1.11; P=0.001). Satisfaction was high, with mean scores above 4/5.</p><p><strong>Conclusion: </strong>Clinical simulation combined with peer tutoring was feasible and well accepted in an undergraduate medical curriculum in Spain, achieving sustained participation over 2 academic years and consistently high satisfaction ratings. The program was associated with significant immediate improvements in workshop-specific knowledge test scores.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"15"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13506240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148220204","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":"Police search and seizure during ongoing care in a pediatric emergency center in Korea: implications for medical training and the emergency care workforce.","authors":"Sun Huh","doi":"10.3352/jeehp.2026.23.32","DOIUrl":"https://doi.org/10.3352/jeehp.2026.23.32","url":null,"abstract":"","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"32"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149197171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of artificial intelligence in the 2025 medical parasitology course at Hallym University.","authors":"Eun Hee Ha","doi":"10.3352/jeehp.2026.23.4","DOIUrl":"10.3352/jeehp.2026.23.4","url":null,"abstract":"","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"4"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12976625/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146158799","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":"Personality type profiles of medical students and their differences by gender, age, and academic level in Korea: a cross-sectional study.","authors":"Yera Hur, Sanghee Yeo","doi":"10.3352/jeehp.2026.23.7","DOIUrl":"10.3352/jeehp.2026.23.7","url":null,"abstract":"<p><strong>Purpose: </strong>Understanding the psychological characteristics of contemporary medical students is essential for effective educational design and learner support. This study aimed to identify medical students' personality types using a geometric personality assessment tool (GEOPIA), determine whether differences exist by gender, age, or academic level, and explore the practical utility of such profiling for supporting educational practices in medical school settings.</p><p><strong>Methods: </strong>The 40-item Korean Geometric Psychological Assessment (GEOPIA) was administered to 1,173 students across 5 Korean medical schools. GEOPIA classifies individuals into 4 primary types-Round (sociable, relationship-oriented), Triangle (task-oriented, challenging), Box (prudent, stability-seeking), and Curve (creative, sensitive). Frequency analyses and χ2 tests were conducted. Of the 1,016 respondents (response rate, 86.61%), 981 were included in the final analysis.</p><p><strong>Results: </strong>The most common primary type was Round (40.3%), followed by Box (31.7%), Triangle (15.2%), and Curve (12.8%). Across the 12 combined profiles, Round-Box (21.9%) was the most prevalent, followed by Box-Round (19.0%) and Round-Triangle (9.7%). No significant differences were observed by gender (χ2=6.360, P=0.095, Cramer's V=0.082), age (χ2=8.314, P=0.091, Cramer's V=0.065), or academic level (χ2=18.044, P=0.260, Cramer's V=0.078).</p><p><strong>Conclusion: </strong>GEOPIA may provide a practical tool for identifying learner characteristics and supporting educational decision-making in medical school settings. In instructional design, personality-type data can inform group formation, activity planning, and assignment structure. In student support, the tool offers instructors and advisors a quick way to understand learners' characteristics, which may help guide individualized counseling and promote effective learning experiences.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"7"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13213262/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147785227","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":"Presidential address 2026: celebrating academic excellence and expanding computer-based testing across health professions.","authors":"Hyunjoo Pai","doi":"10.3352/jeehp.2026.23.1","DOIUrl":"10.3352/jeehp.2026.23.1","url":null,"abstract":"","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"1"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12976626/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145999404","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":"Strategies for remediating clinical reasoning skill deficits in underperforming residents: a scoping review.","authors":"Jovian Philip Swatan, Fithriyah Cholifatul Ummah, Cecilia Felicia Chandra, Nooreen Adnan","doi":"10.3352/jeehp.2026.23.3","DOIUrl":"10.3352/jeehp.2026.23.3","url":null,"abstract":"<p><p>Clinical reasoning is a core competency in medical practice; however, deficits in this domain among residents are often difficult to identify and remediate because of its cognitive complexity and the absence of standardized assessment approaches. This scoping review aimed to map and analyze existing evidence on strategies to remediate clinical reasoning skill deficits in underperforming medical residents. Using the Arksey and O'Malley framework as refined by Levac and his colleagues, and reported in accordance with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we systematically searched PubMed, Scopus, MEDLINE, Web of Science, SpringerLink, ProQuest, and EBSCOhost for studies published between 2000 and 2024. Definitions of clinical reasoning, underperformance, and remediation were adopted from prior literature. Twenty studies met the inclusion criteria, comprising original research and literature reviews in multiple medical specialties. Methods for identifying clinical reasoning deficits included written, oral, and performance-based assessments, as well as routine workplace-based evaluations. Remediation strategies ranged from structured institutional programs to individualized, case-specific interventions, with coaching, deliberate practice, guided reflection, and structured thinking frameworks frequently employed. Two studies reported positive outcomes following completion of remediation for clinical reasoning deficits. Key enablers included psychological safety, learner engagement, and accessible faculty support, whereas barriers included learner resistance, inadequate baseline knowledge, faculty skill limitations, and institutional resource constraints. Effective remediation requires early identification, comprehensive diagnostic assessment, and tailored, coaching-based interventions supported by institutional commitment. Nonetheless, substantial variability in definitions, remediation protocols, and evaluation methods highlights the need for greater standardization and further research across diverse contexts to inform evidence-based frameworks for clinical reasoning remediation.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"3"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13039651/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146158767","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":"Comparison of reference management software with new artificial intelligence-based tools.","authors":"Jae Gyeong Jin, Seung Gyu Lee, Jea Hyeun Park, Jang Won Han, Jae Young Kim, Jungirl Seok, Jeong-Ju Yoo","doi":"10.3352/jeehp.2026.23.2","DOIUrl":"10.3352/jeehp.2026.23.2","url":null,"abstract":"<p><p>Reference management software (RMS) represents a cornerstone of modern academic writing and publishing. For decades, programs such as EndNote, Zotero, and Mendeley have played central roles in facilitating citation organization, bibliography formatting, and collaborative scholarship. Although each platform has introduced unique innovations, persistent limitations remain, particularly with respect to usability, accessibility, and accuracy. In parallel, the rise of generative artificial intelligence has introduced an unprecedented challenge: the inadvertent inclusion of fabricated or incorrect references mistakenly incorporated into manuscripts. This phenomenon has exposed a critical limitation of traditional RMS platforms, namely their inability to verify reference authenticity. Against this backdrop, new solutions have emerged. One such example is CiteWell (https://citewell.org/), an artificial intelligence (AI)-era RMS that introduces several notable innovations, including PubMed-integrated verification, an intuitive interface for new users, customizable journal-specific styles, and multilingual accessibility. This review provides a comprehensive historical overview of RMS, evaluates the strengths and weaknesses of major platforms, and positions emerging AI-based tools as a new paradigm that combines traditional reference management with essential safeguards for contemporary academic challenges.</p>","PeriodicalId":46098,"journal":{"name":"Journal of Educational Evaluation for Health Professions","volume":"23 ","pages":"2"},"PeriodicalIF":5.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12976740/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145999443","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}