Journal of Educational Evaluation for Health Professions

Most-download articles are from the articles published in 2021 during the last three month.

Reviews

Sample size determination and power analysis using the G*Power software: Hyun Kang; J Educ Eval Health Prof. 2021;18:17. Published online July 30, 2021; DOI: https://doi.org/10.3352/jeehp.2021.18.17

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Appropriate sample size calculation and power analysis have become major issues in research and publication processes. However, the complexity and difficulty of calculating sample size and power require broad statistical knowledge, there is a shortage of personnel with programming skills, and commercial programs are often too expensive to use in practice. The review article aimed to explain the basic concepts of sample size calculation and power analysis; the process of sample estimation; and how to calculate sample size using G*Power software (latest ver. 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany) with 5 statistical examples. The null and alternative hypothesis, effect size, power, alpha, type I error, and type II error should be described when calculating the sample size or power. G*Power is recommended for sample size and power calculations for various statistical methods (F, t, χ2, Z, and exact tests), because it is easy to use and free. The process of sample estimation consists of establishing research goals and hypotheses, choosing appropriate statistical tests, choosing one of 5 possible power analysis methods, inputting the required variables for analysis, and selecting the “calculate” button. The G*Power software supports sample size and power calculation for various statistical methods (F, t, χ2, z, and exact tests). This software is helpful for researchers to estimate the sample size and to conduct power analysis.

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Educational applications of metaverse: possibilities and limitations: Bokyung Kye, Nara Han, Eunji Kim, Yeonjeong Park, Soyoung Jo; J Educ Eval Health Prof. 2021;18:32. Published online December 13, 2021; DOI: https://doi.org/10.3352/jeehp.2021.18.32

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Abstract PDF Supplementary Material

This review aims to define the 4 types of the metaverse and to explain the potential and limitations of its educational applications. The metaverse roadmap categorizes the metaverse into 4 types: augmented reality, lifelogging, mirror world, and virtual reality. An example of the application of augmented reality in medical education would be an augmented reality T-shirt that allows students to examine the inside of the human body as an anatomy lab. Furthermore, a research team in a hospital in Seoul developed a spinal surgery platform that applied augmented reality technology. The potential of the metaverse as a new educational environment is suggested to be as follows: a space for new social communication; a higher degree of freedom to create and share; and the provision of new experiences and high immersion through virtualization. Some of its limitations may be weaker social connections and the possibility of privacy impingement; the commission of various crimes due to the virtual space and anonymity of the metaverse; and maladaptation to the real world for students whose identity has not been established. The metaverse is predicted to change our daily life and economy beyond the realm of games and entertainment. The metaverse has infinite potential as a new social communication space. The following future tasks are suggested for the educational use of the metaverse: first, teachers should carefully analyze how students understand the metaverse; second, teachers should design classes for students to solve problems or perform projects cooperatively and creatively; third, educational metaverse platforms should be developed that prevent misuse of student data.

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Milli Eğitim Dergisi.2023;[Epub] CrossRef
A Study on the Future Prospect of the Metaverse through Human Cognition
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The Journal of Korean Institute of Information Technology.2023; 21(7): 149. CrossRef
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Journal of Educational Evaluation for Health Professions.2022; 19: 2. CrossRef
The Metaverse—An Alternative Education Space
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AI, Computer Science and Robotics Technology.2022; 2022: 1. CrossRef
The Metaverse in Cardiovascular Medicine: Applications, Challenges, and the Role of Non-Fungible Tokens
Ioannis Skalidis, Olivier Muller, Stephane Fournier
Canadian Journal of Cardiology.2022; 38(9): 1467. CrossRef
UTAUT in Metaverse: An “Ifland” Case
Un-Kon Lee, Hyekyung Kim
Journal of Theoretical and Applied Electronic Commerce Research.2022; 17(2): 613. CrossRef
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Faruk YILMAZ, Anı Hande METE, Buse FİDAN TÜRKÖN, Özgür İNCE
Eurasian Journal of Health Technology Assessment.2022; 6(1): 12. CrossRef
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Shruti Jha
SBV Journal of Basic, Clinical and Applied Health Science.2022; 5(1): 19. CrossRef
CardioVerse: The cardiovascular medicine in the era of Metaverse
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Trends in Cardiovascular Medicine.2022;[Epub] CrossRef
Definition, roles, and potential research issues of the metaverse in education: An artificial intelligence perspective
Gwo-Jen Hwang, Shu-Yun Chien
Computers and Education: Artificial Intelligence.2022; 3: 100082. CrossRef
EĞİTİM BAĞLAMINDA METAVERSE
Ahmet GÖÇEN
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METAVERSE VE SAĞLIK HİZMETLERİ ÜZERİNE BİR DEĞERLENDİRME
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Smart Learning Environments.2022;[Epub] CrossRef
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Antonio Sánchez-Puente, P. Ignacio Dorado-Díaz, Pedro L Sánchez
Trends in Cardiovascular Medicine.2022;[Epub] CrossRef
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Zaheer Allam, Ayyoob Sharifi, Simon Elias Bibri, David Sydney Jones, John Krogstie
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BioMedical Engineering OnLine.2022;[Epub] CrossRef
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JMIR Serious Games.2022; 10(3): e35202. CrossRef
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I-Chen Tsai, Hyun Woo Goo, Haifa Abdul Latiff, Seon Young Goo, Sang Joon Park
Cardiovascular Imaging Asia.2022; 6(3): 82. CrossRef
Future era of techno-economic analysis: Insights from review
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Frontiers in Sustainability.2022;[Epub] CrossRef
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Frontiers in Medicine.2022;[Epub] CrossRef
Into the Metaverse – Perspectives on a New Reality
Tariq Rahaman
Medical Reference Services Quarterly.2022; 41(3): 330. CrossRef
Factors Affecting Learners’ Adoption of an Educational Metaverse Platform: An Empirical Study Based on an Extended UTAUT Model
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Frontiers in Sports and Active Living.2022;[Epub] CrossRef
Metaverse Dünyasının Eğitim Modeli Olarak Kullanımı ve Muhasebe Eğitimine Yansımaları
Işık ALTUNAL
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The metaverse in education: Definition, framework, features, potential applications, challenges, and future research topics
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Frontiers in Psychology.2022;[Epub] CrossRef
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Interactive Learning Environments.2022; : 1. CrossRef
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The Korean Journal of Internal Medicine.2022; 37(6): 1223. CrossRef
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Rocco Salvatore Calabrò, Antonio Cerasa, Irene Ciancarelli, Loris Pignolo, Paolo Tonin, Marco Iosa, Giovanni Morone
Biomedicines.2022; 10(10): 2602. CrossRef
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Frontiers in Public Health.2022;[Epub] CrossRef
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Erciyes Akademi.2022; 36(4): 1792. CrossRef
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Sustainability.2022; 14(22): 14747. CrossRef
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Sustainability.2022; 14(23): 15718. CrossRef
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Touch IoT enabled by wireless self-sensing and haptic-reproducing electronic skin
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Journal of Metaverse.2022; 2(2): 62. CrossRef
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Şebnem YAŞAR
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Research articles

Experience of introducing an electronic health records station in an objective structured clinical examination to evaluate medical students’ communication skills in Canada: a descriptive study: Kuan-chin Jean Chen, Ilona Bartman, Debra Pugh, David Topps, Isabelle Desjardins, Melissa Forgie, Douglas Archibald; J Educ Eval Health Prof. 2023;20:22. Published online July 4, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.22

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Abstract PDF Supplementary Material: Purpose
There is limited literature related to the assessment of electronic medical record (EMR)-related competencies. To address this gap, this study explored the feasibility of an EMR objective structured clinical examination (OSCE) station to evaluate medical students’ communication skills by psychometric analyses and standardized patients’ (SPs) perspectives on EMR use in an OSCE.
Methods
An OSCE station that incorporated the use of an EMR was developed and pilot-tested in March 2020. Students’ communication skills were assessed by SPs and physician examiners. Students’ scores were compared between the EMR station and 9 other stations. A psychometric analysis, including item total correlation, was done. SPs participated in a post-OSCE focus group to discuss their perception of EMRs’ effect on communication.
Results
Ninety-nine 3rd-year medical students participated in a 10-station OSCE that included the use of the EMR station. The EMR station had an acceptable item total correlation (0.217). Students who leveraged graphical displays in counseling received higher OSCE station scores from the SPs (P=0.041). The thematic analysis of SPs’ perceptions of students’ EMR use from the focus group revealed the following domains of themes: technology, communication, case design, ownership of health information, and timing of EMR usage.
Conclusion
This study demonstrated the feasibility of incorporating EMR in assessing learner communication skills in an OSCE. The EMR station had acceptable psychometric characteristics. Some medical students were able to efficiently use the EMRs as an aid in patient counseling. Teaching students how to be patient-centered even in the presence of technology may promote engagement.

Implementation strategy for introducing a clinical skills examination to the Korean Oriental Medicine Licensing Examination: a mixed-method modified Delphi study: Chan-Young Kwon, Sanghoon Lee, Min Hwangbo, Chungsik Cho, Sangwoo Shin, Dong-Hyeon Kim, Aram Jeong, Hye-Yoon Lee; J Educ Eval Health Prof. 2023;20:23. Published online July 17, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.23

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Abstract PDF Supplementary Material: Purpose
This study investigated the validity of introducing a clinical skills examination (CSE) to the Korean Oriental Medicine Licensing Examination through a mixed-method modified Delphi study.
Methods
A 3-round Delphi study was conducted between September and November 2022. The expert panel comprised 21 oriental medicine education experts who were officially recommended by relevant institutions and organizations. The questionnaires included potential content for the CSE and a detailed implementation strategy. Subcommittees were formed to discuss concerns around the introduction of the CSE, which were collected as open-ended questions. In this study, a 66.7% or greater agreement rate was defined as achieving a consensus.
Results
The expert panel’s evaluation of the proposed clinical presentations and basic clinical skills suggested their priorities. Of the 10 items investigated for building a detailed implementation strategy for the introduction of the CSE to the Korean Oriental Medicine Licensing Examination, a consensus was achieved on 9. However, the agreement rate on the timing of the introduction of the CSE was low. Concerns around 4 clinical topics were discussed in the subcommittees, and potential solutions were proposed.
Conclusion
This study offers preliminary data and raises some concerns that can be used as a reference while discussing the introduction of the CSE to the Korean Oriental Medicine Licensing Examination.

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

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10 Citations

Abstract PDF Supplementary 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.

Citations

Citations to this article as recorded by

Universal skepticism of ChatGPT: a review of early literature on chat generative pre-trained transformer
Casey Watters, Michal K. Lemanski
Frontiers in Big Data.2023;[Epub] CrossRef
The importance of human supervision in the use of ChatGPT as a support tool in scientific writing
William Castillo-González
Metaverse Basic and Applied Research.2023;[Epub] CrossRef
ChatGPT for Future Medical and Dental Research
Bader Fatani
Cureus.2023;[Epub] CrossRef
Chatbots in Medical Research
Punit Sharma
Clinical Nuclear Medicine.2023; 48(9): 838. CrossRef
Potential applications of ChatGPT in dermatology
Nicolas Kluger
Journal of the European Academy of Dermatology and Venereology.2023;[Epub] CrossRef
The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research
Tariq Alqahtani, Hisham A. Badreldin, Mohammed Alrashed, Abdulrahman I. Alshaya, Sahar S. Alghamdi, Khalid bin Saleh, Shuroug A. Alowais, Omar A. Alshaya, Ishrat Rahman, Majed S. Al Yami, Abdulkareem M. Albekairy
Research in Social and Administrative Pharmacy.2023; 19(8): 1236. CrossRef
ChatGPT Performance on the American Urological Association Self-assessment Study Program and the Potential Influence of Artificial Intelligence in Urologic Training
Nicholas A. Deebel, Ryan Terlecki
Urology.2023; 177: 29. CrossRef
Intelligence or artificial intelligence? More hard problems for authors of Biological Psychology, the neurosciences, and everyone else
Thomas Ritz
Biological Psychology.2023; 181: 108590. CrossRef
The ethics of disclosing the use of artificial intelligence tools in writing scholarly manuscripts
Mohammad Hosseini, David B Resnik, Kristi Holmes
Research Ethics.2023;[Epub] CrossRef
How trustworthy is ChatGPT? The case of bibliometric analyses
Faiza Farhat, Shahab Saquib Sohail, Dag Øivind Madsen
Cogent Engineering.2023;[Epub] CrossRef

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

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21 Citations

Abstract PDF Supplementary 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

Citations to this article as recorded by

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
Issues in the 3rd year of the COVID-19 pandemic, including computer-based testing, study design, ChatGPT, journal metrics, and appreciation to reviewers
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
Cureus.2023;[Epub] CrossRef
ChatGPT for Future Medical and Dental Research
Bader Fatani
Cureus.2023;[Epub] CrossRef
ChatGPT in Dentistry: A Comprehensive Review
Hind M Alhaidry, Bader Fatani, Jenan O Alrayes, Aljowhara M Almana, Nawaf K Alfhaed
Cureus.2023;[Epub] CrossRef
Can we trust AI chatbots’ answers about disease diagnosis and patient care?
Sun Huh
Journal of the Korean Medical Association.2023; 66(4): 218. CrossRef
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
JMIR Medical Education.2023; 9: e48291. CrossRef
Early applications of ChatGPT in medical practice, education and research
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
Cureus.2023;[Epub] CrossRef
The Intersection of ChatGPT, Clinical Medicine, and Medical Education: Viewpoint (Preprint)
Rebecca Shin-Yee Wong, Long Chiau Ming, Raja Affendi Raja Ali
JMIR Medical Education.2023;[Epub] 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
Assessing the Efficacy of ChatGPT in Solving Questions Based on the Core Concepts in Physiology
Arijita Banerjee, Aquil Ahmad, Payal Bhalla, Kavita Goyal
Cureus.2023;[Epub] CrossRef
ChatGPT Performs on the Chinese National Medical Licensing Examination
Xinyi Wang, Zhenye Gong, Guoxin Wang, Jingdan Jia, Ying Xu, Jialu Zhao, Qingye Fan, Shaun Wu, Weiguo Hu, Xiaoyang Li
Journal of Medical Systems.2023;[Epub] CrossRef

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

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1 Citations

Abstract PDF Supplementary 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

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

Development of a character qualities test for medical students in Korea using polytomous item response theory and factor analysis: a preliminary scale development study: Yera Hur, Dong Gi Seo; J Educ Eval Health Prof. 2023;20:20. Published online June 26, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.20

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Abstract PDF Supplementary Material: Purpose
This study aimed to develop a test scale to measure the character qualities of medical students as a follow-up study on the 8 core character qualities revealed in a previous report.
Methods
In total, 160 preliminary items were developed to measure 8 core character qualities. Twenty questions were assigned to each quality, and a questionnaire survey was conducted among 856 students in 5 medical schools in Korea. Using the partial credit model, polytomous item response theory analysis was carried out to analyze the goodness-of-fit, followed by exploratory factor analysis. Finally, confirmatory factor and reliability analyses were conducted with the final selected items.
Results
The preliminary items for the 8 core character qualities were administered to the participants. Data from 767 students were included in the final analysis. Of the 160 preliminary items, 25 were removed by classical test theory analysis and 17 more by polytomous item response theory assessment. A total of 118 items and sub-factors were selected for exploratory factor analysis. Finally, 79 items were selected, and the validity and reliability were confirmed through confirmatory factor analysis and intra-item relevance analysis.
Conclusion
The character qualities test scale developed through this study can be used to measure the character qualities corresponding to the educational goals and visions of individual medical schools in Korea. Furthermore, this measurement tool can serve as primary data for developing character qualities tools tailored to each medical school’s vision and educational goals.

Editorial

Journal of Educational Evaluation for Health Professions received the Journal Impact Factor, 4.4 for the first time on June 28, 2023: Sun Huh; J Educ Eval Health Prof. 2023;20:21. Published online June 29, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.21

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PDF

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

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Abstract PDF Supplementary 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.

Research article

Effect of an interprofessional simulation program on patient safety competencies of healthcare professionals in Switzerland: a before and after study: Sylvain Boloré, Thomas Fassier, Nicolas Guirimand; J Educ Eval Health Prof. 2023;20:25. Published online August 28, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.25

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Abstract PDF Supplementary Material: Purpose
This study aimed to identify the effects of a 12-week interprofessional simulation program, operated between February 2020 and January 2021, on the patient safety competencies of healthcare professionals in Switzerland.
Methods
The simulation training was based on 2 scenarios of hospitalized patients with septic shock and respiratory failure, and trainees were expected to demonstrate patient safety competencies. A single-group before and after study was conducted after the intervention—simulation program, using a measurement tool (the Health Professional Education in Patient Safety Survey) to measure the perceived competencies of physicians, nurses, and nursing assistants. Out of 57 participants, 37 answered the questionnaire surveys 4 times: 48 hours before the training, followed by post-surveys at 24 hours, 6 weeks, and 12 weeks after the training. The linear mixed effect model was applied for the analysis.
Results
Four components out of 6 perceived patient safety competencies improved at 6 weeks but returned to a similar level before training at 12 weeks. Competencies of “communicating effectively,” “managing safety risks,” “understanding human and environmental factors that influence patient safety,” and “recognize and respond to remove immediate risks of harm” are statistically significant both overall and in the comparison between before the training and 6 weeks after the training.
Conclusion
Interprofessional simulation programs contributed to developing some areas of patient safety competencies of healthcare professionals, but only for a limited time. Interprofessional simulation programs should be repeated and combined with other forms of support, including case discussions and debriefings, to ensure lasting effects.

Brief report

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; J Educ Eval Health Prof. 2023;20:17. Published online June 12, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.17

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Abstract PDF Supplementary Material: Learning about one’s implicit bias is crucial for improving one’s cultural competency and thereby reducing health inequity. To evaluate bias among medical students following a previously developed cultural training program targeting New Zealand Māori, we developed a text-based, self-evaluation tool called the Similarity Rating Test (SRT). The development process of the SRT was resource-intensive, limiting its generalizability and applicability. Here, we explored the potential of ChatGPT, an automated chatbot, to assist in the development process of the SRT by comparing ChatGPT’s and students’ evaluations of the SRT. Despite results showing non-significant equivalence and difference between ChatGPT’s and students’ ratings, ChatGPT’s ratings were more consistent than students’ ratings. The consistency rate was higher for non-stereotypical than for stereotypical statements, regardless of rater type. Further studies are warranted to validate ChatGPT’s potential for assisting in SRT development for implementation in medical education and evaluation of ethnic stereotypes and related topics.

Educational/Faculty development material

Environmental management education using immersive virtual reality in asthmatic children in Korea: a randomized controlled study (secondary publication): Seung Hyun Kim, Sang Hyun Park, Insoon Kang, Yuyoung Song, Jaehoon Lim, Wonsuck Yoon, Young Yoo; J Educ Eval Health Prof. 2022;19:15. Published online July 11, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.15

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232 Download
2 Citations

Abstract PDF Supplementary Material

Awareness of environmental control is considered a significant influence on the performance of asthma self-management behaviors, which are involved in maintaining effective asthma control. This study aimed to investigate whether immersive virtual reality (VR) education is effective in environmental control education for asthmatic children in Korea. Thirty asthmatic children aged 9 to 13 years with aeroallergen sensitization were enrolled. Environmental control education for asthmatic participants was performed using immersive VR (VR group) or conventional leaflets provided by asthma specialists (control group). Five questionnaires, on awareness of environmental control, memory, assessment of intent to act, a satisfaction test, and an Asthma Control Test (ACT), were used to estimate the effects of education. The scores for awareness of environmental control, memory, and intent to act significantly increased after education in both groups, and the scores remained high until 4 weeks after education. Both groups’ ACT scores were consistently high before and 4 weeks after education. Satisfaction scores were very high in the VR group. The increased scores in awareness of environmental control and intent to act indicate that the environmental control education using VR is worthy of attention as an effective educational tool for asthma management. Further developed techniques, including active environmental interventions by participants in VR, could be applied to effective asthma management.

Citations

Citations to this article as recorded by

A Systematic Review of Randomized Controlled Trials on Virtual Reality Application in Pediatric Patients
Ashish Varma, Waqar M Naqvi, Salima Mulla, Samana Syed, Sumit Thakur, Sakshi P Arora, Anuj R Varma, Smruti Besekar
Cureus.2022;[Epub] CrossRef
Medical students’ self-assessed efficacy and satisfaction with training on endotracheal intubation and central venous catheterization with smart glasses in Taiwan: a non-equivalent control-group pre- and post-test study
Yu-Fan Lin, Chien-Ying Wang, Yen-Hsun Huang, Sheng-Min Lin, Ying-Ying Yang
Journal of Educational Evaluation for Health Professions.2022; 19: 25. CrossRef

Research articles

Enhancement of the technical and non-technical skills of nurse anesthesia students using the Anesthetic List Management Assessment Tool in Iran: a quasi-experimental study: Ali Khalafi, Maedeh Kordnejad, Vahid Saidkhani; J Educ Eval Health Prof. 2023;20:19. Published online June 16, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.19

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Abstract PDF Supplementary Material: Purpose
This study investigated the effect of evaluations based on the Anesthetic List Management Assessment Tool (ALMAT) form on improving the technical and non-technical skills of final-year nurse anesthesia students at Ahvaz Jundishapur University of Medical Sciences (AJUMS).
Methods
This was a semi-experimental study with a pre-test and post-test design. It included 45 final-year nurse anesthesia students of AJUMS and lasted for 3 months. The technical and non-technical skills of the intervention group were assessed at 4 university hospitals using formative-feedback evaluation based on the ALMAT form, from induction of anesthesia until reaching mastery and independence. Finally, the students’ degree of improvement in technical and non-technical skills was compared between the intervention and control groups. Statistical tests (the independent t-test, paired t-test, and Mann-Whitney test) were used to analyze the data.
Results
The rate of improvement in post-test scores of technical skills was significantly higher in the intervention group than in the control group (P˂0.0001). Similarly, the students in the intervention group received significantly higher post-test scores for non-technical skills than the students in the control group (P˂0.0001).
Conclusion
The findings of this study showed that the use of ALMAT as a formative-feedback evaluation method to evaluate technical and non-technical skills had a significant effect on improving these skills and was effective in helping students learn and reach mastery and independence.

Suggestion for item allocation to 8 nursing activity categories of the Korean Nursing Licensing Examination: a survey-based descriptive study: Kyunghee Kim, So Young Kang, Younhee Kang, Youngran Kweon, Hyunjung Kim, Youngshin Song, Juyeon Cho, Mi-Young Choi, Hyun Su Lee; J Educ Eval Health Prof. 2023;20:18. Published online June 12, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.18

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Abstract PDF Supplementary Material: Purpose
This study aims to suggest the number of test items in each of 8 nursing activity categories of the Korean Nursing Licensing Examination, which comprises 134 activity statements including 275 items. The examination will be able to evaluate the minimum ability that nursing graduates must have to perform their duties. Methods: Two opinion surveys involving the members of 7 academic societies were conducted from March 19 to May 14, 2021. The survey results were reviewed by members of 4 expert associations from May 21 to June 4, 2021. The results for revised numbers of items in each category were compared with those reported by Tak and his colleagues and the National Council License Examination for Registered Nurses of the United States. Results: Based on 2 opinion surveys and previous studies, the suggestions for item allocation to 8 nursing activity categories of the Korean Nursing Licensing Examination in this study are as follows: 50 items for management of care and improvement of professionalism, 33 items for safety and infection control, 40 items for management of potential risk, 28 items for basic care, 47 items for physiological integrity and maintenance, 33 items for pharmacological and parenteral therapies, 24 items for psychosocial integrity and maintenance, and 20 items for health promotion and maintenance. Twenty other items related to health and medical laws were not included due to their mandatory status. Conclusion: These suggestions for the number of test items for each activity category will be helpful in developing new items for the Korean Nursing Licensing Examination.

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