Journal of Educational Evaluation for Health Professions

Reviews

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

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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 ChatGPT has limitations, such as potential bias, dependence on outdated data, and revenue generation challenges.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.

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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.

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Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review: Xiaojun Xu, Yixiao Chen, Jing Miao; J Educ Eval Health Prof. 2024;21:6. Published online March 15, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.6

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Abstract PDF Supplementary Material

Background
ChatGPT is a large language model (LLM) based on artificial intelligence (AI) capable of responding in multiple languages and generating nuanced and highly complex responses. While ChatGPT holds promising applications in medical education, its limitations and potential risks cannot be ignored.
Methods
A scoping review was conducted for English articles discussing ChatGPT in the context of medical education published after 2022. A literature search was performed using PubMed/MEDLINE, Embase, and Web of Science databases, and information was extracted from the relevant studies that were ultimately included.
Results
ChatGPT exhibits various potential applications in medical education, such as providing personalized learning plans and materials, creating clinical practice simulation scenarios, and assisting in writing articles. However, challenges associated with academic integrity, data accuracy, and potential harm to learning were also highlighted in the literature. The paper emphasizes certain recommendations for using ChatGPT, including the establishment of guidelines. Based on the review, 3 key research areas were proposed: cultivating the ability of medical students to use ChatGPT correctly, integrating ChatGPT into teaching activities and processes, and proposing standards for the use of AI by medical students.
Conclusion
ChatGPT has the potential to transform medical education, but careful consideration is required for its full integration. To harness the full potential of ChatGPT in medical education, attention should not only be given to the capabilities of AI but also to its impact on students and teachers.

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Immersive simulation in nursing and midwifery education: a systematic review: Lahoucine Ben Yahya, Aziz Naciri, Mohamed Radid, Ghizlane Chemsi; J Educ Eval Health Prof. 2024;21:19. Published online August 8, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.19

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Abstract PDF Supplementary Material

Purpose
Immersive simulation is an innovative training approach in health education that enhances student learning. This study examined its impact on engagement, motivation, and academic performance in nursing and midwifery students.
Methods
A comprehensive systematic search was meticulously conducted in 4 reputable databases—Scopus, PubMed, Web of Science, and Science Direct—following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The research protocol was pre-registered in the PROSPERO registry, ensuring transparency and rigor. The quality of the included studies was assessed using the Medical Education Research Study Quality Instrument.
Results
Out of 90 identified studies, 11 were included in the present review, involving 1,090 participants. Four out of 5 studies observed high post-test engagement scores in the intervention groups. Additionally, 5 out of 6 studies that evaluated motivation found higher post-test motivational scores in the intervention groups than in control groups using traditional approaches. Furthermore, among the 8 out of 11 studies that evaluated academic performance during immersive simulation training, 5 reported significant differences (P<0.001) in favor of the students in the intervention groups.
Conclusion
Immersive simulation, as demonstrated by this study, has a significant potential to enhance student engagement, motivation, and academic performance, surpassing traditional teaching methods. This potential underscores the urgent need for future research in various contexts to better integrate this innovative educational approach into nursing and midwifery education curricula, inspiring hope for improved teaching methods.

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Educational/Faculty development material

The 6 degrees of curriculum integration in medical education in the United States: Julie Youm, Jennifer Christner, Kevin Hittle, Paul Ko, Cinda Stone, Angela D. Blood, Samara Ginzburg; J Educ Eval Health Prof. 2024;21:15. Published online June 13, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.15

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Abstract PDF Supplementary Material: Despite explicit expectations and accreditation requirements for integrated curriculum, there needs to be more clarity around an accepted common definition, best practices for implementation, and criteria for successful curriculum integration. To address the lack of consensus surrounding integration, we reviewed the literature and herein propose a definition for curriculum integration for the medical education audience. We further believe that medical education is ready to move beyond “horizontal” (1-dimensional) and “vertical” (2-dimensional) integration and propose a model of “6 degrees of curriculum integration” to expand the 2-dimensional concept for future designs of medical education programs and best prepare learners to meet the needs of patients. These 6 degrees include: interdisciplinary, timing and sequencing, instruction and assessment, incorporation of basic and clinical sciences, knowledge and skills-based competency progression, and graduated responsibilities in patient care. We encourage medical educators to look beyond 2-dimensional integration to this holistic and interconnected representation of curriculum integration.

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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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.

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Research article

The effect of simulation-based training on problem-solving skills, critical thinking skills, and self-efficacy among nursing students in Vietnam: a before-and-after study: Tran Thi Hoang Oanh, Luu Thi Thuy, Ngo Thi Thu Huyen; J Educ Eval Health Prof. 2024;21:24. Published online September 23, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.24

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Abstract PDF Supplementary Material

Purpose
This study investigated the effect of simulation-based training on nursing students’ problem-solving skills, critical thinking skills, and self-efficacy.
Methods
A single-group pretest and posttest study was conducted among 173 second-year nursing students at a public university in Vietnam from May 2021 to July 2022. Each student participated in the adult nursing preclinical practice course, which utilized a moderate-fidelity simulation teaching approach. Instruments including the Personal Problem-Solving Inventory Scale, Critical Thinking Skills Questionnaire, and General Self-Efficacy Questionnaire were employed to measure participants’ problem-solving skills, critical thinking skills, and self-efficacy. Data were analyzed using descriptive statistics and the paired-sample t-test with the significance level set at P<0.05.
Results
The mean score of the Personal Problem-Solving Inventory posttest (127.24±12.11) was lower than the pretest score (131.42±16.95), suggesting an improvement in the problem-solving skills of the participants (t172=2.55, P=0.011). There was no statistically significant difference in critical thinking skills between the pretest and posttest (P=0.854). Self-efficacy among nursing students showed a substantial increase from the pretest (27.91±5.26) to the posttest (28.71±3.81), with t172=-2.26 and P=0.025.
Conclusion
The results suggest that simulation-based training can improve problem-solving skills and increase self-efficacy among nursing students. Therefore, the integration of simulation-based training in nursing education is recommended.

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The Effect of Work-Based Learning on Employability Skills: The Role of Self-Efficacy and Vocational Identity
Suyitno Suyitno, Muhammad Nurtanto, Dwi Jatmoko, Yuli Widiyono, Riawan Yudi Purwoko, Fuad Abdillah, Setuju Setuju, Yudan Hermawan
European Journal of Educational Research.2025; 14(1): 309. CrossRef
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Mohamad Zaki Mohamad Saad, Shafinah Kamarudin, Zuraini Zukiffly, Siti Soleha Zuaimi
Progress in Computers and Learning .2025; 2(1): 29. CrossRef

Educational/Faculty development material

The role of large language models in the peer-review process: opportunities and challenges for medical journal reviewers and editors: Jisoo Lee, Jieun Lee, Jeong-Ju Yoo; J Educ Eval Health Prof. 2025;22:4. Published online January 16, 2025; DOI: https://doi.org/10.3352/jeehp.2025.22.4

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Abstract PDF Supplementary Material: The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generative artificial intelligence, especially large language models (LLMs) such as ChatGPT, may assist researchers with efficient, high-quality reviews. This review explores the integration of LLMs into peer review, highlighting their strengths in linguistic tasks and challenges in assessing scientific validity, particularly in clinical medicine. Key points for integration include initial screening, reviewer matching, feedback support, and language review. However, implementing LLMs for these purposes will necessitate addressing biases, privacy concerns, and data confidentiality. We recommend using LLMs as complementary tools under clear guidelines to support, not replace, human expertise in maintaining rigorous peer review standards.

Research article

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

7,085 View
474 Download
4 Web of Science
6 Crossref

Abstract PDF Supplementary 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.

Citations

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Wellness and Stress Management Practices Among Healthcare Professionals and Health Professional Students
Asli C. Yalim, Katherine Daly, Monica Bailey, Denise Kay, Xiang Zhu, Mohammed Patel, Laurie C. Neely, Desiree A. Díaz, Denyi M. Canario Asencio, Karla Rosario, Melissa Cowan, Magdalena Pasarica
American Journal of Health Promotion.2025; 39(2): 204. CrossRef
Final results of the National Oncology Mentorship Program 2023 and its impact on burnout and professional fulfilment
Udit Nindra, Gowri Shivasabesan, Rhiannon Mellor, Weng Ng, Wei Chua, Deme Karikios, Bethan Richards, Jia Liu
Internal Medicine Journal.2025; 55(2): 233. CrossRef
Incidence of Shared Clinical Instruction in Physical Therapy Clinical Education in the United States
Nicki Silberman, Lori Hochman, Jaya Rachwani
Journal of Physical Therapy Education.2025;[Epub] CrossRef
Assessing and Managing Prevalence of Burnout in Inpatient Occupational and Physical Therapists in an Acute Care Setting
Kelly Murphy, Maria Tucker, Laura Cataldo, Sarah Sergeant, Bill Kuklinski, Jordan Billings, Katrina Jancsy
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Review

Attraction and achievement as 2 attributes of gamification in healthcare: an evolutionary concept analysis: Hyun Kyoung Kim; J Educ Eval Health Prof. 2024;21:10. Published online April 11, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.10

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355 Download
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Abstract PDF Supplementary Material

This study conducted a conceptual analysis of gamification in healthcare utilizing Rogers’ evolutionary concept analysis methodology to identify its attributes and provide a method for its applications in the healthcare field. Gamification has recently been used as a health intervention and education method, but the concept is used inconsistently and confusingly. A literature review was conducted to derive definitions, surrogate terms, antecedents, influencing factors, attributes (characteristics with dimensions and features), related concepts, consequences, implications, and hypotheses from various academic fields. A total of 56 journal articles in English and Korean, published between August 2 and August 7, 2023, were extracted from databases such as PubMed Central, the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery Digital Library, the Research Information Sharing Service, and the Korean Studies Information Service System, using the keywords “gamification” and “healthcare.” These articles were then analyzed. Gamification in healthcare is defined as the application of game elements in health-related contexts to improve health outcomes. The attributes of this concept were categorized into 2 main areas: attraction and achievement. These categories encompass various strategies for synchronization, enjoyable engagement, visual rewards, and goal-reinforcing frames. Through a multidisciplinary analysis of the concept’s attributes and influencing factors, this paper provides practical strategies for implementing gamification in health interventions. When developing a gamification strategy, healthcare providers can reference this analysis to ensure the game elements are used both appropriately and effectively.

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The effect of DECO-MOM mobile application for a prenatal environmental health program on environmental health behaviors: a pilot test
Hae Kyung Jo, Hyun Kyoung Kim
BMC Pregnancy and Childbirth.2025;[Epub] CrossRef
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Technical report

Item difficulty index, discrimination index, and reliability of the 26 health professions licensing examinations in 2022, Korea: a psychometric study: Yoon Hee Kim, Bo Hyun Kim, Joonki Kim, Bokyoung Jung, Sangyoung Bae; J Educ Eval Health Prof. 2023;20:31. Published online November 22, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.31

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Abstract PDF Supplementary Material: Purpose
This study presents item analysis results of the 26 health personnel licensing examinations managed by the Korea Health Personnel Licensing Examination Institute (KHPLEI) in 2022.
Methods
The item difficulty index, item discrimination index, and reliability were calculated. The item discrimination index was calculated using a discrimination index based on the upper and lower 27% rule and the item-total correlation.
Results
Out of 468,352 total examinees, 418,887 (89.4%) passed. The pass rates ranged from 27.3% for health educators level 1 to 97.1% for oriental medical doctors. Most examinations had a high average difficulty index, albeit to varying degrees, ranging from 61.3% for prosthetists and orthotists to 83.9% for care workers. The average discrimination index based on the upper and lower 27% rule ranged from 0.17 for oriental medical doctors to 0.38 for radiological technologists. The average item-total correlation ranged from 0.20 for oriental medical doctors to 0.38 for radiological technologists. The Cronbach α, as a measure of reliability, ranged from 0.872 for health educators-level 3 to 0.978 for medical technologists. The correlation coefficient between the average difficulty index and average discrimination index was -0.2452 (P=0.1557), that between the average difficulty index and the average item-total correlation was 0.3502 (P=0.0392), and that between the average discrimination index and the average item-total correlation was 0.7944 (P<0.0001).
Conclusion
This technical report presents the item analysis results and reliability of the recent examinations by the KHPLEI, demonstrating an acceptable range of difficulty index and discrimination index values, as well as good reliability.

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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1,139 Download
202 Web of Science
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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.

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Emergence of the metaverse and ChatGPT in journal publishing after the COVID-19 pandemic
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Assessing the Capability of ChatGPT in Answering First- and Second-Order Knowledge Questions on Microbiology as per Competency-Based Medical Education Curriculum
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ChatGPT in Dentistry: A Comprehensive Review
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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
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Sam Sedaghat
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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
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Cosima C. Hoch, Barbara Wollenberg, Jan-Christoffer Lüers, Samuel Knoedler, Leonard Knoedler, Konstantin Frank, Sebastian Cotofana, Michael Alfertshofer
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Research article

Validation of the 21st Century Skills Assessment Scale for public health students in Thailand: a methodological study: Suphawadee Panthumas, Kaung Zaw, Wirin Kittipichai; J Educ Eval Health Prof. 2024;21:37. Published online December 10, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.37

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Abstract PDF Supplementary Material: Purpose
This study aimed to develop and validate the 21st Century Skills Assessment Scale (21CSAS) for Thai public health (PH) undergraduate students using the Partnership for 21st Century Skills framework.
Methods
A cross-sectional survey was conducted among 727 first- to fourth-year PH undergraduate students from 4 autonomous universities in Thailand. Data were collected using self-administered questionnaires between January and March 2023. Exploratory factor analysis (EFA) was used to explore the underlying dimensions of 21CSAS, while confirmatory factor analysis (CFA) was conducted to test the hypothesized factor structure using Mplus software (Muthén & Muthén). Reliability and item discrimination were assessed using Cronbach’s α and the corrected item-total correlation, respectively.
Results
EFA performed on a dataset of 300 students revealed a 20-item scale with a 6-factor structure: (1) creativity and innovation; (2) critical thinking and problem-solving; (3) information, media, and technology; (4) communication and collaboration; (5) initiative and self-direction; and (6) social and cross-cultural skills. The rotated eigenvalues ranged from 2.12 to 1.73. CFA performed on another dataset of 427 students confirmed a good model fit (χ2/degrees of freedom=2.67, comparative fit index=0.93, Tucker-Lewis index=0.91, root mean square error of approximation=0.06, standardized root mean square residual=0.06), explaining 34%–71% of variance in the items. Item loadings ranged from 0.58 to 0.84. The 21CSAS had a Cronbach’s α of 0.92.
Conclusion
The 21CSAS proved be a valid and reliable tool for assessing 21st century skills among Thai PH undergraduate students. These findings provide insights for educational system to inform policy, practice, and research regarding 21st-century skills among undergraduate students.

Software report

Special article on the 20th anniversary of the journal

The irtQ R package: a user-friendly tool for item response theory-based test data analysis and calibration: Hwanggyu Lim, Kyungseok Kang; J Educ Eval Health Prof. 2024;21:23. Published online September 12, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.23

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Abstract PDF Supplementary Material: Computerized adaptive testing (CAT) has become a widely adopted test design for high-stakes licensing and certification exams, particularly in the health professions in the United States, due to its ability to tailor test difficulty in real time, reducing testing time while providing precise ability estimates. A key component of CAT is item response theory (IRT), which facilitates the dynamic selection of items based on examinees' ability levels during a test. Accurate estimation of item and ability parameters is essential for successful CAT implementation, necessitating convenient and reliable software to ensure precise parameter estimation. This paper introduces the irtQ R package (http://CRAN.R-project.org/), which simplifies IRT-based analysis and item calibration under unidimensional IRT models. While it does not directly simulate CAT, it provides essential tools to support CAT development, including parameter estimation using marginal maximum likelihood estimation via the expectation-maximization algorithm, pretest item calibration through fixed item parameter calibration and fixed ability parameter calibration methods, and examinee ability estimation. The package also enables users to compute item and test characteristic curves and information functions necessary for evaluating the psychometric properties of a test. This paper illustrates the key features of the irtQ package through examples using simulated datasets, demonstrating its utility in IRT applications such as test data analysis and ability scoring. By providing a user-friendly environment for IRT analysis, irtQ significantly enhances the capacity for efficient adaptive testing research and operations. Finally, the paper highlights additional core functionalities of irtQ, emphasizing its broader applicability to the development and operation of IRT-based assessments.

Research article

Empathy and tolerance of ambiguity in medical students and doctors participating in art-based observational training at the Rijksmuseum in Amsterdam, the Netherlands: a before-and-after study: Stella Anna Bult, Thomas van Gulik; J Educ Eval Health Prof. 2025;22:3. Published online January 14, 2025; DOI: https://doi.org/10.3352/jeehp.2025.22.3

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Abstract PDF Supplementary Material: Purpose
This research presents an experimental study using validated questionnaires to quantitatively assess the outcomes of art-based observational training in medical students, residents, and specialists. The study tested the hypothesis that art-based observational training would lead to measurable effects on judgement skills (tolerance of ambiguity) and empathy in medical students and doctors.
Methods
An experimental cohort study with pre- and post-intervention assessments was conducted using validated questionnaires and qualitative evaluation forms to examine the outcomes of art-based observational training in medical students and doctors. Between December 2023 and June 2024, 15 art courses were conducted in the Rijksmuseum in Amsterdam. Participants were assessed on empathy using the Jefferson Scale of Empathy (JSE) and tolerance of ambiguity using the Tolerance of Ambiguity in Medical Students and Doctors (TAMSAD) scale.
Results
In total, 91 participants were included; 29 participants completed the JSE and 62 completed the TAMSAD scales. The results showed statistically significant post-test increases for mean JSE and TAMSAD scores (3.71 points for the JSE, ranging from 20 to 140, and 1.86 points for the TAMSAD, ranging from 0 to 100). The qualitative findings were predominantly positive.
Conclusion
The results suggest that incorporating art-based observational training in medical education improves empathy and tolerance of ambiguity. This study highlights the importance of art-based observational training in medical education in the professional development of medical students and doctors.

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