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Most-download articles are from the articles published in 2022 during the last three month.

Review
Application of artificial intelligence chatbots, including ChatGPT, in education, scholarly work, programming, and content generation and its prospects: a narrative review
Tae Won Kim
J Educ Eval Health Prof. 2023;20:38.   Published online December 27, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.38
  • 705 View
  • 157 Download
AbstractAbstract PDFSupplementary Material
This study aims to explore ChatGPT’s (GPT-3.5 version) functionalities, including reinforcement learning, diverse applications, and limitations. ChatGPT is an artificial intelligence (AI) chatbot powered by OpenAI’s Generative Pre-trained Transformer (GPT) model. The chatbot’s applications span education, programming, content generation, and more, demonstrating its versatility. ChatGPT can improve education by creating assignments and offering personalized feedback, as shown by its notable performance in medical exams and the United States Medical Licensing Exam. However, concerns include plagiarism, reliability, and educational disparities. It aids in various research tasks, from design to writing, and has shown proficiency in summarizing and suggesting titles. Its use in scientific writing and language translation is promising, but professional oversight is needed for accuracy and originality. It assists in programming tasks like writing code, debugging, and guiding installation and updates. It offers diverse applications, from cheering up individuals to generating creative content like essays, news articles, and business plans. Unlike search engines, ChatGPT provides interactive, generative responses and understands context, making it more akin to human conversation, in contrast to conventional search engines’ keyword-based, non-interactive nature. ChatGPT has limitations, such as potential bias, dependence on outdated data, and revenue generation challenges. Nonetheless, ChatGPT is considered to be a transformative AI tool poised to redefine the future of generative technology. In conclusion, advancements in AI, such as ChatGPT, are altering how knowledge is acquired and applied, marking a shift from search engines to creativity engines. This transformation highlights the increasing importance of AI literacy and the ability to effectively utilize AI in various domains of life.
Research articles
Importance, performance frequency, and predicted future importance of dietitians’ jobs by practicing dietitians in Korea: a survey study
Cheongmin Sohn, Sooyoun Kwon, Won Gyoung Kim, Kyung-Eun Lee, Sun-Young Lee, Seungmin Lee
J Educ Eval Health Prof. 2024;21:1.   Published online January 2, 2024
DOI: https://doi.org/10.3352/jeehp.2024.21.1
  • 325 View
  • 108 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to explore the perceptions held by practicing dietitians of the importance of their tasks performed in current work environments, the frequency at which those tasks are performed, and predictions about the importance of those tasks in future work environments.
Methods
This was a cross-sectional survey study. An online survey was administered to 350 practicing dietitians. They were asked to assess the importance, performance frequency, and predicted changes in the importance of 27 tasks using a 5-point scale. Descriptive statistics were calculated, and the means of the variables were compared across categorized work environments using analysis of variance.
Results
The importance scores of all surveyed tasks were higher than 3.0, except for the marketing management task. Self-development, nutrition education/counseling, menu planning, food safety management, and documentation/data management were all rated higher than 4.0. The highest performance frequency score was related to documentation/data management. The importance scores of all duties, except for professional development, differed significantly by workplace. As for predictions about the future importance of the tasks surveyed, dietitians responded that the importance of all 27 tasks would either remain at current levels or increase in the future.
Conclusion
Twenty-seven tasks were confirmed to represent dietitians’ job functions in various workplaces. These tasks can be used to improve the test specifications of the Korean Dietitian Licensing Examination and the curriculum of dietetic education programs.
Information amount, accuracy, and relevance of generative artificial intelligence platforms’ answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study
Hyunju Lee, Soobin Park
J Educ Eval Health Prof. 2023;20:39.   Published online December 28, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.39
  • 657 View
  • 117 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study assessed the performance of 6 generative artificial intelligence (AI) platforms on the learning objectives of medical arthropodology in a parasitology class in Korea. We examined the AI platforms’ performance by querying in Korean and English to determine their information amount, accuracy, and relevance in prompts in both languages.
Methods
From December 15 to 17, 2023, 6 generative AI platforms—Bard, Bing, Claude, Clova X, GPT-4, and Wrtn—were tested on 7 medical arthropodology learning objectives in English and Korean. Clova X and Wrtn are platforms from Korean companies. Responses were evaluated using specific criteria for the English and Korean queries.
Results
Bard had abundant information but was fourth in accuracy and relevance. GPT-4, with high information content, ranked first in accuracy and relevance. Clova X was 4th in amount but 2nd in accuracy and relevance. Bing provided less information, with moderate accuracy and relevance. Wrtn’s answers were short, with average accuracy and relevance. Claude AI had reasonable information, but lower accuracy and relevance. The responses in English were superior in all aspects. Clova X was notably optimized for Korean, leading in relevance.
Conclusion
In a study of 6 generative AI platforms applied to medical arthropodology, GPT-4 excelled overall, while Clova X, a Korea-based AI product, achieved 100% relevance in Korean queries, the highest among its peers. Utilizing these AI platforms in classrooms improved the authors’ self-efficacy and interest in the subject, offering a positive experience of interacting with generative AI platforms to question and receive information.
Editorial
Educational/Faculty development material
Common models and approaches for the clinical educator to plan effective feedback encounters  
Cesar Orsini, Veena Rodrigues, Jorge Tricio, Margarita Rosel
J Educ Eval Health Prof. 2022;19:35.   Published online December 19, 2022
DOI: https://doi.org/10.3352/jeehp.2022.19.35
  • 3,337 View
  • 546 Download
  • 1 Web of Science
  • 2 Crossref
AbstractAbstract PDFSupplementary Material
Giving constructive feedback is crucial for learners to bridge the gap between their current performance and the desired standards of competence. Giving effective feedback is a skill that can be learned, practiced, and improved. Therefore, our aim was to explore models in clinical settings and assess their transferability to different clinical feedback encounters. We identified the 6 most common and accepted feedback models, including the Feedback Sandwich, the Pendleton Rules, the One-Minute Preceptor, the SET-GO model, the R2C2 (Rapport/Reaction/Content/Coach), and the ALOBA (Agenda Led Outcome-based Analysis) model. We present a handy resource describing their structure, strengths and weaknesses, requirements for educators and learners, and suitable feedback encounters for use for each model. These feedback models represent practical frameworks for educators to adopt but also to adapt to their preferred style, combining and modifying them if necessary to suit their needs and context.

Citations

Citations to this article as recorded by  
  • Navigating power dynamics between pharmacy preceptors and learners
    Shane Tolleson, Mabel Truong, Natalie Rosario
    Exploratory Research in Clinical and Social Pharmacy.2024; 13: 100408.     CrossRef
  • Feedback conversations: First things first?
    Katharine A. Robb, Marcy E. Rosenbaum, Lauren Peters, Susan Lenoch, Donna Lancianese, Jane L. Miller
    Patient Education and Counseling.2023; 115: 107849.     CrossRef
Research article
Use of learner-driven, formative, ad-hoc, prospective assessment of competence in physical therapist clinical education in the United States: a prospective cohort study  
Carey Holleran, Jeffrey Konrad, Barbara Norton, Tamara Burlis, Steven Ambler
J Educ Eval Health Prof. 2023;20:36.   Published online December 8, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.36
  • 382 View
  • 89 Download
AbstractAbstract PDFSupplementary Material
Purpose
The purpose of this project was to implement a process for learner-driven, formative, prospective, ad-hoc, entrustment assessment in Doctor of Physical Therapy clinical education. Our goals were to develop an innovative entrustment assessment tool, and then explore whether the tool detected (1) differences between learners at different stages of development and (2) differences within learners across the course of a clinical education experience. We also investigated whether there was a relationship between the number of assessments and change in performance.
Methods
A prospective, observational, cohort of clinical instructors (CIs) was recruited to perform learner-driven, formative, ad-hoc, prospective, entrustment assessments. Two entrustable professional activities (EPAs) were used: (1) gather a history and perform an examination and (2) implement and modify the plan of care, as needed. CIs provided a rating on the entrustment scale and provided narrative support for their rating.
Results
Forty-nine learners participated across 4 clinical experiences (CEs), resulting in 453 EPA learner-driven assessments. For both EPAs, statistically significant changes were detected both between learners at different stages of development and within learners across the course of a CE. Improvement within each CE was significantly related to the number of feedback opportunities.
Conclusion
The results of this pilot study provide preliminary support for the use of learner-driven, formative, ad-hoc assessments of competence based on EPAs with a novel entrustment scale. The number of formative assessments requested correlated with change on the EPA scale, suggesting that formative feedback may augment performance improvement.
Brief report
Are ChatGPT’s knowledge and interpretation ability comparable to those of medical students in Korea for taking a parasitology examination?: a descriptive study  
Sun Huh
J Educ Eval Health Prof. 2023;20:1.   Published online January 11, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.1
  • 10,096 View
  • 990 Download
  • 95 Web of Science
  • 55 Crossref
AbstractAbstract PDFSupplementary Material
This study aimed to compare the knowledge and interpretation ability of ChatGPT, a language model of artificial general intelligence, with those of medical students in Korea by administering a parasitology examination to both ChatGPT and medical students. The examination consisted of 79 items and was administered to ChatGPT on January 1, 2023. The examination results were analyzed in terms of ChatGPT’s overall performance score, its correct answer rate by the items’ knowledge level, and the acceptability of its explanations of the items. ChatGPT’s performance was lower than that of the medical students, and ChatGPT’s correct answer rate was not related to the items’ knowledge level. However, there was a relationship between acceptable explanations and correct answers. In conclusion, ChatGPT’s knowledge and interpretation ability for this parasitology examination were not yet comparable to those of medical students in Korea.

Citations

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    Aesthetic Surgery Journal.2024; 44(3): 329.     CrossRef
  • Unveiling the ChatGPT phenomenon: Evaluating the consistency and accuracy of endodontic question answers
    Ana Suárez, Víctor Díaz‐Flores García, Juan Algar, Margarita Gómez Sánchez, María Llorente de Pedro, Yolanda Freire
    International Endodontic Journal.2024; 57(1): 108.     CrossRef
  • Bob or Bot: Exploring ChatGPT's Answers to University Computer Science Assessment
    Mike Richards, Kevin Waugh, Mark Slaymaker, Marian Petre, John Woodthorpe, Daniel Gooch
    ACM Transactions on Computing Education.2024; 24(1): 1.     CrossRef
  • Examining the use of ChatGPT in public universities in Hong Kong: a case study of restricted access areas
    Michelle W. T. Cheng, Iris H. Y. YIM
    Discover Education.2024;[Epub]     CrossRef
  • Performance of ChatGPT on Ophthalmology-Related Questions Across Various Examination Levels: Observational Study
    Firas Haddad, Joanna S Saade
    JMIR Medical Education.2024; 10: e50842.     CrossRef
  • A comparative vignette study: Evaluating the potential role of a generative AI model in enhancing clinical decision‐making in nursing
    Mor Saban, Ilana Dubovi
    Journal of Advanced Nursing.2024;[Epub]     CrossRef
  • Comparison of the Performance of GPT-3.5 and GPT-4 With That of Medical Students on the Written German Medical Licensing Examination: Observational Study
    Annika Meyer, Janik Riese, Thomas Streichert
    JMIR Medical Education.2024; 10: e50965.     CrossRef
  • From hype to insight: Exploring ChatGPT's early footprint in education via altmetrics and bibliometrics
    Lung‐Hsiang Wong, Hyejin Park, Chee‐Kit Looi
    Journal of Computer Assisted Learning.2024;[Epub]     CrossRef
  • Applicability of ChatGPT in Assisting to Solve Higher Order Problems in Pathology
    Ranwir K Sinha, Asitava Deb Roy, Nikhil Kumar, Himel Mondal
    Cureus.2023;[Epub]     CrossRef
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    Sun Huh
    Journal of Educational Evaluation for Health Professions.2023; 20: 5.     CrossRef
  • Emergence of the metaverse and ChatGPT in journal publishing after the COVID-19 pandemic
    Sun Huh
    Science Editing.2023; 10(1): 1.     CrossRef
  • Assessing the Capability of ChatGPT in Answering First- and Second-Order Knowledge Questions on Microbiology as per Competency-Based Medical Education Curriculum
    Dipmala Das, Nikhil Kumar, Langamba Angom Longjam, Ranwir Sinha, Asitava Deb Roy, Himel Mondal, Pratima Gupta
    Cureus.2023;[Epub]     CrossRef
  • Evaluating ChatGPT's Ability to Solve Higher-Order Questions on the Competency-Based Medical Education Curriculum in Medical Biochemistry
    Arindam Ghosh, Aritri Bir
    Cureus.2023;[Epub]     CrossRef
  • Overview of Early ChatGPT’s Presence in Medical Literature: Insights From a Hybrid Literature Review by ChatGPT and Human Experts
    Omar Temsah, Samina A Khan, Yazan Chaiah, Abdulrahman Senjab, Khalid Alhasan, Amr Jamal, Fadi Aljamaan, Khalid H Malki, Rabih Halwani, Jaffar A Al-Tawfiq, Mohamad-Hani Temsah, Ayman Al-Eyadhy
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  • ChatGPT for Future Medical and Dental Research
    Bader Fatani
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  • Can we trust AI chatbots’ answers about disease diagnosis and patient care?
    Sun Huh
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  • Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions
    Alaa Abd-alrazaq, Rawan AlSaad, Dari Alhuwail, Arfan Ahmed, Padraig Mark Healy, Syed Latifi, Sarah Aziz, Rafat Damseh, Sadam Alabed Alrazak, Javaid Sheikh
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    Sam Sedaghat
    Clinical Medicine.2023; 23(3): 278.     CrossRef
  • A Review of Research on Teaching and Learning Transformation under the Influence of ChatGPT Technology
    璇 师
    Advances in Education.2023; 13(05): 2617.     CrossRef
  • Performance of GPT-3.5 and GPT-4 on the Japanese Medical Licensing Examination: Comparison Study
    Soshi Takagi, Takashi Watari, Ayano Erabi, Kota Sakaguchi
    JMIR Medical Education.2023; 9: e48002.     CrossRef
  • ChatGPT’s quiz skills in different otolaryngology subspecialties: an analysis of 2576 single-choice and multiple-choice board certification preparation questions
    Cosima C. Hoch, Barbara Wollenberg, Jan-Christoffer Lüers, Samuel Knoedler, Leonard Knoedler, Konstantin Frank, Sebastian Cotofana, Michael Alfertshofer
    European Archives of Oto-Rhino-Laryngology.2023; 280(9): 4271.     CrossRef
  • Analysing the Applicability of ChatGPT, Bard, and Bing to Generate Reasoning-Based Multiple-Choice Questions in Medical Physiology
    Mayank Agarwal, Priyanka Sharma, Ayan Goswami
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  • The Intersection of ChatGPT, Clinical Medicine, and Medical Education
    Rebecca Shin-Yee Wong, Long Chiau Ming, Raja Affendi Raja Ali
    JMIR Medical Education.2023; 9: e47274.     CrossRef
  • The Role of Artificial Intelligence in Higher Education: ChatGPT Assessment for Anatomy Course
    Tarık TALAN, Yusuf KALINKARA
    Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi.2023; 7(1): 33.     CrossRef
  • Comparing ChatGPT’s ability to rate the degree of stereotypes and the consistency of stereotype attribution with those of medical students in New Zealand in developing a similarity rating test: a methodological study
    Chao-Cheng Lin, Zaine Akuhata-Huntington, Che-Wei Hsu
    Journal of Educational Evaluation for Health Professions.2023; 20: 17.     CrossRef
  • Examining Real-World Medication Consultations and Drug-Herb Interactions: ChatGPT Performance Evaluation
    Hsing-Yu Hsu, Kai-Cheng Hsu, Shih-Yen Hou, Ching-Lung Wu, Yow-Wen Hsieh, Yih-Dih Cheng
    JMIR Medical Education.2023; 9: e48433.     CrossRef
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    Arijita Banerjee, Aquil Ahmad, Payal Bhalla, Kavita Goyal
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    Xinyi Wang, Zhenye Gong, Guoxin Wang, Jingdan Jia, Ying Xu, Jialu Zhao, Qingye Fan, Shaun Wu, Weiguo Hu, Xiaoyang Li
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    ICST Transactions on Scalable Information Systems.2023;[Epub]     CrossRef
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    Carl Preiksaitis, Christian Rose
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  • Redesigning Tertiary Educational Evaluation with AI: A Task-Based Analysis of LIS Students’ Assessment on Written Tests and Utilizing ChatGPT at NSTU
    Shamima Yesmin
    Science & Technology Libraries.2023; : 1.     CrossRef
  • ChatGPT and the AI revolution: a comprehensive investigation of its multidimensional impact and potential
    Mohd Afjal
    Library Hi Tech.2023;[Epub]     CrossRef
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    Hasan B Ilgaz, Zehra Çelik
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  • Is ChatGPT’s Knowledge and Interpretative Ability Comparable to First Professional MBBS (Bachelor of Medicine, Bachelor of Surgery) Students of India in Taking a Medical Biochemistry Examination?
    Abhra Ghosh, Nandita Maini Jindal, Vikram K Gupta, Ekta Bansal, Navjot Kaur Bajwa, Abhishek Sett
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    Sun Huh
    Child Health Nursing Research.2023; 29(4): 249.     CrossRef
  • Potential Use of ChatGPT for Patient Information in Periodontology: A Descriptive Pilot Study
    Osman Babayiğit, Zeynep Tastan Eroglu, Dilek Ozkan Sen, Fatma Ucan Yarkac
    Cureus.2023;[Epub]     CrossRef
  • Efficacy and limitations of ChatGPT as a biostatistical problem-solving tool in medical education in Serbia: a descriptive study
    Aleksandra Ignjatović, Lazar Stevanović
    Journal of Educational Evaluation for Health Professions.2023; 20: 28.     CrossRef
  • Assessing the Performance of ChatGPT in Medical Biochemistry Using Clinical Case Vignettes: Observational Study
    Krishna Mohan Surapaneni
    JMIR Medical Education.2023; 9: e47191.     CrossRef
  • A systematic review of ChatGPT use in K‐12 education
    Peng Zhang, Gemma Tur
    European Journal of Education.2023;[Epub]     CrossRef
  • Performance of ChatGPT, Bard, Claude, and Bing on the Peruvian National Licensing Medical Examination: a cross-sectional study
    Betzy Clariza Torres-Zegarra, Wagner Rios-Garcia, Alvaro Micael Ñaña-Cordova, Karen Fatima Arteaga-Cisneros, Xiomara Cristina Benavente Chalco, Marina Atena Bustamante Ordoñez, Carlos Jesus Gutierrez Rios, Carlos Alberto Ramos Godoy, Kristell Luisa Teresa
    Journal of Educational Evaluation for Health Professions.2023; 20: 30.     CrossRef
  • ChatGPT’s performance in German OB/GYN exams – paving the way for AI-enhanced medical education and clinical practice
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  • Medical students’ patterns of using ChatGPT as a feedback tool and perceptions of ChatGPT in a Leadership and Communication course in Korea: a cross-sectional study
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    Journal of Educational Evaluation for Health Professions.2023; 20: 29.     CrossRef
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    Biochemistry and Molecular Biology Education.2023;[Epub]     CrossRef
  • FROM TEXT TO DIAGNOSE: CHATGPT’S EFFICACY IN MEDICAL DECISION-MAKING
    Yaroslav Mykhalko, Pavlo Kish, Yelyzaveta Rubtsova, Oleksandr Kutsyn, Valentyna Koval
    Wiadomości Lekarskie.2023; 76(11): 2345.     CrossRef
  • Using ChatGPT for Clinical Practice and Medical Education: Cross-Sectional Survey of Medical Students’ and Physicians’ Perceptions
    Pasin Tangadulrat, Supinya Sono, Boonsin Tangtrakulwanich
    JMIR Medical Education.2023; 9: e50658.     CrossRef
  • Below average ChatGPT performance in medical microbiology exam compared to university students
    Malik Sallam, Khaled Al-Salahat
    Frontiers in Education.2023;[Epub]     CrossRef
  • ChatGPT: "To be or not to be" ... in academic research. The human mind's analytical rigor and capacity to discriminate between AI bots' truths and hallucinations
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    Nur Izah Ab Razak, Muhammad Fawwaz Muhammad Yusoff, Rahmita Wirza O.K. Rahmat
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  • Application of artificial intelligence chatbots, including ChatGPT, in education, scholarly work, programming, and content generation and its prospects: a narrative review
    Tae Won Kim
    Journal of Educational Evaluation for Health Professions.2023; 20: 38.     CrossRef
  • Trends in research on ChatGPT and adoption-related issues discussed in articles: a narrative review
    Sang-Jun Kim
    Science Editing.2023; 11(1): 3.     CrossRef
  • Information amount, accuracy, and relevance of generative artificial intelligence platforms’ answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study
    Hyunju Lee, Soobin Park
    Journal of Educational Evaluation for Health Professions.2023; 20: 39.     CrossRef
Review
How to review and assess a systematic review and meta-analysis article: a methodological study (secondary publication)  
Seung-Kwon Myung
J Educ Eval Health Prof. 2023;20:24.   Published online August 27, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.24
  • 1,669 View
  • 206 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract PDFSupplementary Material
Systematic reviews and meta-analyses have become central in many research fields, particularly medicine. They offer the highest level of evidence in evidence-based medicine and support the development and revision of clinical practice guidelines, which offer recommendations for clinicians caring for patients with specific diseases and conditions. This review summarizes the concepts of systematic reviews and meta-analyses and provides guidance on reviewing and assessing such papers. A systematic review refers to a review of a research question that uses explicit and systematic methods to identify, select, and critically appraise relevant research. In contrast, a meta-analysis is a quantitative statistical analysis that combines individual results on the same research question to estimate the common or mean effect. Conducting a meta-analysis involves defining a research topic, selecting a study design, searching literature in electronic databases, selecting relevant studies, and conducting the analysis. One can assess the findings of a meta-analysis by interpreting a forest plot and a funnel plot and by examining heterogeneity. When reviewing systematic reviews and meta-analyses, several essential points must be considered, including the originality and significance of the work, the comprehensiveness of the database search, the selection of studies based on inclusion and exclusion criteria, subgroup analyses by various factors, and the interpretation of the results based on the levels of evidence. This review will provide readers with helpful guidance to help them read, understand, and evaluate these articles.

Citations

Citations to this article as recorded by  
  • The Role of BIM in Managing Risks in Sustainability of Bridge Projects: A Systematic Review with Meta-Analysis
    Dema Munef Ahmad, László Gáspár, Zsolt Bencze, Rana Ahmad Maya
    Sustainability.2024; 16(3): 1242.     CrossRef
Research articles
Negative effects on medical students’ scores for clinical performance during the COVID-19 pandemic in Taiwan: a comparative study  
Eunice Jia-Shiow Yuan, Shiau-Shian Huang, Chia-An Hsu, Jiing-Feng Lirng, Tzu-Hao Li, Chia-Chang Huang, Ying-Ying Yang, Chung-Pin Li, Chen-Huan Chen
J Educ Eval Health Prof. 2023;20:37.   Published online December 26, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.37
  • 478 View
  • 64 Download
AbstractAbstract PDFSupplementary Material
Purpose
Coronavirus disease 2019 (COVID-19) has heavily impacted medical clinical education in Taiwan. Medical curricula have been altered to minimize exposure and limit transmission. This study investigated the effect of COVID-19 on Taiwanese medical students’ clinical performance using online standardized evaluation systems and explored the factors influencing medical education during the pandemic.
Methods
Medical students were scored from 0 to 100 based on their clinical performance from 1/1/2018 to 6/31/2021. The students were placed into pre-COVID-19 (before 2/1/2020) and midst-COVID-19 (on and after 2/1/2020) groups. Each group was further categorized into COVID-19-affected specialties (pulmonary, infectious, and emergency medicine) and other specialties. Generalized estimating equations (GEEs) were used to compare and examine the effects of relevant variables on student performance.
Results
In total, 16,944 clinical scores were obtained for COVID-19-affected specialties and other specialties. For the COVID-19-affected specialties, the midst-COVID-19 score (88.513.52) was significantly lower than the pre-COVID-19 score (90.143.55) (P<0.0001). For the other specialties, the midst-COVID-19 score (88.323.68) was also significantly lower than the pre-COVID-19 score (90.063.58) (P<0.0001). There were 1,322 students (837 males and 485 females). Male students had significantly lower scores than female students (89.333.68 vs. 89.993.66, P=0.0017). GEE analysis revealed that the COVID-19 pandemic (unstandardized beta coefficient=-1.99, standard error [SE]=0.13, P<0.0001), COVID-19-affected specialties (B=0.26, SE=0.11, P=0.0184), female students (B=1.10, SE=0.20, P<0.0001), and female attending physicians (B=-0.19, SE=0.08, P=0.0145) were independently associated with students’ scores.
Conclusion
COVID-19 negatively impacted medical students' clinical performance, regardless of their specialty. Female students outperformed male students, irrespective of the pandemic.
Performance of ChatGPT, Bard, Claude, and Bing on the Peruvian National Licensing Medical Examination: a cross-sectional study
Betzy Clariza Torres-Zegarra, Wagner Rios-Garcia, Alvaro Micael Ñaña-Cordova, Karen Fatima Arteaga-Cisneros, Xiomara Cristina Benavente Chalco, Marina Atena Bustamante Ordoñez, Carlos Jesus Gutierrez Rios, Carlos Alberto Ramos Godoy, Kristell Luisa Teresa Panta Quezada, Jesus Daniel Gutierrez-Arratia, Javier Alejandro Flores-Cohaila
J Educ Eval Health Prof. 2023;20:30.   Published online November 20, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.30
  • 794 View
  • 137 Download
  • 1 Crossref
AbstractAbstract PDFSupplementary Material
Purpose
We aimed to describe the performance and evaluate the educational value of justifications provided by artificial intelligence chatbots, including GPT-3.5, GPT-4, Bard, Claude, and Bing, on the Peruvian National Medical Licensing Examination (P-NLME).
Methods
This was a cross-sectional analytical study. On July 25, 2023, each multiple-choice question (MCQ) from the P-NLME was entered into each chatbot (GPT-3, GPT-4, Bing, Bard, and Claude) 3 times. Then, 4 medical educators categorized the MCQs in terms of medical area, item type, and whether the MCQ required Peru-specific knowledge. They assessed the educational value of the justifications from the 2 top performers (GPT-4 and Bing).
Results
GPT-4 scored 86.7% and Bing scored 82.2%, followed by Bard and Claude, and the historical performance of Peruvian examinees was 55%. Among the factors associated with correct answers, only MCQs that required Peru-specific knowledge had lower odds (odds ratio, 0.23; 95% confidence interval, 0.09–0.61), whereas the remaining factors showed no associations. In assessing the educational value of justifications provided by GPT-4 and Bing, neither showed any significant differences in certainty, usefulness, or potential use in the classroom.
Conclusion
Among chatbots, GPT-4 and Bing were the top performers, with Bing performing better at Peru-specific MCQs. Moreover, the educational value of justifications provided by the GPT-4 and Bing could be deemed appropriate. However, it is essential to start addressing the educational value of these chatbots, rather than merely their performance on examinations.

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  • Information amount, accuracy, and relevance of generative artificial intelligence platforms’ answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study
    Hyunju Lee, Soobin Park
    Journal of Educational Evaluation for Health Professions.2023; 20: 39.     CrossRef
Effect of a transcultural nursing course on improving the cultural competency of nursing graduate students in Korea: a before-and-after study
Kyung Eui Bae, Geum Hee Jeong
J Educ Eval Health Prof. 2023;20:35.   Published online December 4, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.35
  • 452 View
  • 100 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to evaluate the impact of a transcultural nursing course on enhancing the cultural competency of graduate nursing students in Korea. We hypothesized that participants’ cultural competency would significantly improve in areas such as communication, biocultural ecology and family, dietary habits, death rituals, spirituality, equity, and empowerment and intermediation after completing the course. Furthermore, we assessed the participants’ overall satisfaction with the course.
Methods
A before-and-after study was conducted with graduate nursing students at Hallym University, Chuncheon, Korea, from March to June 2023. A transcultural nursing course was developed based on Giger & Haddad’s transcultural nursing model and Purnell’s theoretical model of cultural competence. Data was collected using a cultural competence scale for registered nurses developed by Kim and his colleagues. A total of 18 students participated, and the paired t-test was employed to compare pre-and post-intervention scores.
Results
The study revealed significant improvements in all 7 categories of cultural nursing competence (P<0.01). Specifically, the mean differences in scores (pre–post) ranged from 0.74 to 1.09 across the categories. Additionally, participants expressed high satisfaction with the course, with an average score of 4.72 out of a maximum of 5.0.
Conclusion
The transcultural nursing course effectively enhanced the cultural competency of graduate nursing students. Such courses are imperative to ensure quality care for the increasing multicultural population in Korea.
Review
Can an artificial intelligence chatbot be the author of a scholarly article?  
Ju Yoen Lee
J Educ Eval Health Prof. 2023;20:6.   Published online February 27, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.6
  • 6,367 View
  • 601 Download
  • 26 Web of Science
  • 33 Crossref
AbstractAbstract PDFSupplementary Material
At the end of 2022, the appearance of ChatGPT, an artificial intelligence (AI) chatbot with amazing writing ability, caused a great sensation in academia. The chatbot turned out to be very capable, but also capable of deception, and the news broke that several researchers had listed the chatbot (including its earlier version) as co-authors of their academic papers. In response, Nature and Science expressed their position that this chatbot cannot be listed as an author in the papers they publish. Since an AI chatbot is not a human being, in the current legal system, the text automatically generated by an AI chatbot cannot be a copyrighted work; thus, an AI chatbot cannot be an author of a copyrighted work. Current AI chatbots such as ChatGPT are much more advanced than search engines in that they produce original text, but they still remain at the level of a search engine in that they cannot take responsibility for their writing. For this reason, they also cannot be authors from the perspective of research ethics.

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    Journal of Craniofacial Surgery.2024; 35(1): 274.     CrossRef
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    Justyna Zybaczynska, Matthew Norris, Sunjay Modi, Jennifer Brennan, Pooja Jhaveri, Timothy J. Craig, Taha Al-Shaikhly
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    Goetsch Thibaut, Armaghan Dabbagh, Philippe Liverneaux
    International Orthopaedics.2024; 48(1): 151.     CrossRef
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Research articles
Mentorship and self-efficacy are associated with lower burnout in physical therapists in the United States: a cross-sectional survey study  
Matthew Pugliese, Jean-Michel Brismée, Brad Allen, Sean Riley, Justin Tammany, Paul Mintken
J Educ Eval Health Prof. 2023;20:27.   Published online September 27, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.27
  • 2,069 View
  • 234 Download
AbstractAbstract PDFSupplementary Material
Purpose
This study investigated the prevalence of burnout in physical therapists in the United States and the relationships between burnout and education, mentorship, and self-efficacy.
Methods
This was a cross-sectional survey study. An electronic survey was distributed to practicing physical therapists across the United States over a 6-week period from December 2020 to January 2021. The survey was completed by 2,813 physical therapists from all states. The majority were female (68.72%), White or Caucasian (80.13%), and employed full-time (77.14%). Respondents completed questions on demographics, education, mentorship, self-efficacy, and burnout. The Burnout Clinical Subtypes Questionnaire 12 (BCSQ-12) and self-reports were used to quantify burnout, and the General Self-Efficacy Scale (GSES) was used to measure self-efficacy. Descriptive and inferential analyses were performed.
Results
Respondents from home health (median BCSQ-12=42.00) and skilled nursing facility settings (median BCSQ-12=42.00) displayed the highest burnout scores. Burnout was significantly lower among those who provided formal mentorship (median BCSQ-12=39.00, P=0.0001) compared to no mentorship (median BCSQ-12=41.00). Respondents who received formal mentorship (median BCSQ-12=38.00, P=0.0028) displayed significantly lower burnout than those who received no mentorship (median BCSQ-12=41.00). A moderate negative correlation (rho=-0.49) was observed between the GSES and burnout scores. A strong positive correlation was found between self-reported burnout status and burnout scores (rrb=0.61).
Conclusion
Burnout is prevalent in the physical therapy profession, as almost half of respondents (49.34%) reported burnout. Providing or receiving mentorship and higher self-efficacy were associated with lower burnout. Organizations should consider measuring burnout levels, investing in mentorship programs, and implementing strategies to improve self-efficacy.
Medical students’ patterns of using ChatGPT as a feedback tool and perceptions of ChatGPT in a Leadership and Communication course in Korea: a cross-sectional study  
Janghee Park
J Educ Eval Health Prof. 2023;20:29.   Published online November 10, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.29
  • 927 View
  • 105 Download
  • 1 Web of Science
  • 2 Crossref
AbstractAbstract PDFSupplementary Material
Purpose
This study aimed to analyze patterns of using ChatGPT before and after group activities and to explore medical students’ perceptions of ChatGPT as a feedback tool in the classroom.
Methods
The study included 99 2nd-year pre-medical students who participated in a “Leadership and Communication” course from March to June 2023. Students engaged in both individual and group activities related to negotiation strategies. ChatGPT was used to provide feedback on their solutions. A survey was administered to assess students’ perceptions of ChatGPT’s feedback, its use in the classroom, and the strengths and challenges of ChatGPT from May 17 to 19, 2023.
Results
The students responded by indicating that ChatGPT’s feedback was helpful, and revised and resubmitted their group answers in various ways after receiving feedback. The majority of respondents expressed agreement with the use of ChatGPT during class. The most common response concerning the appropriate context of using ChatGPT’s feedback was “after the first round of discussion, for revisions.” There was a significant difference in satisfaction with ChatGPT’s feedback, including correctness, usefulness, and ethics, depending on whether or not ChatGPT was used during class, but there was no significant difference according to gender or whether students had previous experience with ChatGPT. The strongest advantages were “providing answers to questions” and “summarizing information,” and the worst disadvantage was “producing information without supporting evidence.”
Conclusion
The students were aware of the advantages and disadvantages of ChatGPT, and they had a positive attitude toward using ChatGPT in the classroom.

Citations

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  • ChatGPT and Clinical Training: Perception, Concerns, and Practice of Pharm-D Students
    Mohammed Zawiah, Fahmi Al-Ashwal, Lobna Gharaibeh, Rana Abu Farha, Karem Alzoubi, Khawla Abu Hammour, Qutaiba A Qasim, Fahd Abrah
    Journal of Multidisciplinary Healthcare.2023; Volume 16: 4099.     CrossRef
  • Information amount, accuracy, and relevance of generative artificial intelligence platforms’ answers regarding learning objectives of medical arthropodology evaluated in English and Korean queries in December 2023: a descriptive study
    Hyunju Lee, Soobin Park
    Journal of Educational Evaluation for Health Professions.2023; 20: 39.     CrossRef
Assessment of the viability of integrating virtual reality programs in practical tests for the Korean Radiological Technologists Licensing Examination: a survey study  
Hye Min Park, Eun Seong Kim, Deok Mun Kwon, Pyong Kon Cho, Seoung Hwan Kim, Ki Baek Lee, Seong Hu Kim, Moon Il Bong, Won Seok Yang, Jin Eui Kim, Gi Bong Kang, Yong Su Yoon, Jung Su Kim
J Educ Eval Health Prof. 2023;20:33.   Published online November 28, 2023
DOI: https://doi.org/10.3352/jeehp.2023.20.33
  • 647 View
  • 80 Download
AbstractAbstract PDFSupplementary Material
Purpose
The objective of this study was to assess the feasibility of incorporating virtual reality/augmented reality (VR/AR) programs into practical tests administered as part of the Korean Radiological Technologists Licensing Examination (KRTLE). This evaluation is grounded in a comprehensive survey that targeted enrolled students in departments of radiology across the nation.
Methods
In total, 682 students from radiology departments across the nation were participants in the survey. An online survey platform was used, and the questionnaire was structured into 5 distinct sections and 27 questions. A frequency analysis for each section of the survey was conducted using IBM SPSS ver. 27.0.
Results
Direct or indirect exposure to VR/AR content was reported by 67.7% of all respondents. Furthermore, 55.4% of the respondents expressed that VR/AR could be integrated into their classes, which signified a widespread acknowledgment of VR among the students. With regards to the integration of a VR/AR or mixed reality program into the practical tests for purposes of the KRTLE, a substantial amount of the respondents (57.3%) exhibited a positive inclination and recommended its introduction.
Conclusion
The application of VR/AR programs within practical tests of the KRTLE will be used as an alternative for evaluating clinical examination procedures and validating job skills.

JEEHP : Journal of Educational Evaluation for Health Professions