Journal of Educational Evaluation for Health Professions

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

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 ChatGPT has limitations, such as potential bias, dependence on outdated data, and revenue generation challenges.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

Citations

Citations to this article as recorded by

Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review
Xiaojun Xu, Yixiao Chen, Jing Miao
Journal of Educational Evaluation for Health Professions.2024; 21: 6. CrossRef
Artificial Intelligence: Fundamentals and Breakthrough Applications in Epilepsy
Wesley Kerr, Sandra Acosta, Patrick Kwan, Gregory Worrell, Mohamad A. Mikati
Epilepsy Currents.2024;[Epub] CrossRef
A Developed Graphical User Interface-Based on Different Generative Pre-trained Transformers Models
Ekrem Küçük, İpek Balıkçı Çiçek, Zeynep Küçükakçalı, Cihan Yetiş, Cemil Çolak
ODÜ Tıp Dergisi.2024; 11(1): 18. CrossRef
Art or Artifact: Evaluating the Accuracy, Appeal, and Educational Value of AI-Generated Imagery in DALL·E 3 for Illustrating Congenital Heart Diseases
Mohamad-Hani Temsah, Abdullah N. Alhuzaimi, Mohammed Almansour, Fadi Aljamaan, Khalid Alhasan, Munirah A. Batarfi, Ibraheem Altamimi, Amani Alharbi, Adel Abdulaziz Alsuhaibani, Leena Alwakeel, Abdulrahman Abdulkhaliq Alzahrani, Khaled B. Alsulaim, Amr Jam
Journal of Medical Systems.2024;[Epub] CrossRef
Authentic assessment in medical education: exploring AI integration and student-as-partners collaboration
Syeda Sadia Fatima, Nabeel Ashfaque Sheikh, Athar Osama
Postgraduate Medical Journal.2024;[Epub] CrossRef
Comparative performance analysis of large language models: ChatGPT-3.5, ChatGPT-4 and Google Gemini in glucocorticoid-induced osteoporosis
Linjian Tong, Chaoyang Zhang, Rui Liu, Jia Yang, Zhiming Sun
Journal of Orthopaedic Surgery and Research.2024;[Epub] CrossRef
Can AI-Generated Clinical Vignettes in Japanese Be Used Medically and Linguistically?
Yasutaka Yanagita, Daiki Yokokawa, Shun Uchida, Yu Li, Takanori Uehara, Masatomi Ikusaka
Journal of General Internal Medicine.2024;[Epub] CrossRef
ChatGPT vs. sleep disorder specialist responses to common sleep queries: Ratings by experts and laypeople
Jiyoung Kim, Seo-Young Lee, Jee Hyun Kim, Dong-Hyeon Shin, Eun Hye Oh, Jin A Kim, Jae Wook Cho
Sleep Health.2024;[Epub] CrossRef
Technology integration into Chinese as a foreign language learning in higher education: An integrated bibliometric analysis and systematic review (2000–2024)
Binze Xu
Language Teaching Research.2024;[Epub] CrossRef

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.

Citations

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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
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The association between long noncoding RNA ABHD11-AS1 and malignancy prognosis: a meta-analysis
Guangyao Lin, Tao Ye, Jing Wang
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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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912 Download
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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

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 in Medical Education—Its Importance and How to Do It
Tarik Babar, Omer A. Awan
Academic Radiology.2024;[Epub] CrossRef
Comparison of the effects of apprenticeship training by sandwich feedback and traditional methods on final-semester operating room technology students’ perioperative competence and performance: a randomized, controlled trial
Azam Hosseinpour, Morteza Nasiri, Fatemeh Keshmiri, Tayebeh Arabzadeh, Hossein Sharafi
BMC Medical Education.2024;[Epub] 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

Review

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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464 Download
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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.

Citations

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Chatbots in neurology and neuroscience: Interactions with students, patients and neurologists
Stefano Sandrone
Brain Disorders.2024; 15: 100145. CrossRef
ChatGPT in education: unveiling frontiers and future directions through systematic literature review and bibliometric analysis
Buddhini Amarathunga
Asian Education and Development Studies.2024;[Epub] CrossRef
Evaluating the performance of ChatGPT-3.5 and ChatGPT-4 on the Taiwan plastic surgery board examination
Ching-Hua Hsieh, Hsiao-Yun Hsieh, Hui-Ping Lin
Heliyon.2024; 10(14): e34851. CrossRef
Preparing for Artificial General Intelligence (AGI) in Health Professions Education: AMEE Guide No. 172
Ken Masters, Anne Herrmann-Werner, Teresa Festl-Wietek, David Taylor
Medical Teacher.2024; 46(10): 1258. CrossRef
A Comparative Analysis of ChatGPT and Medical Faculty Graduates in Medical Specialization Exams: Uncovering the Potential of Artificial Intelligence in Medical Education
Gülcan Gencer, Kerem Gencer
Cureus.2024;[Epub] CrossRef
Research ethics and issues regarding the use of ChatGPT-like artificial intelligence platforms by authors and reviewers: a narrative review
Sang-Jun Kim
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Innovation Off the Bat: Bridging the ChatGPT Gap in Digital Competence among English as a Foreign Language Teachers
Gulsara Urazbayeva, Raisa Kussainova, Aikumis Aibergen, Assel Kaliyeva, Gulnur Kantayeva
Education Sciences.2024; 14(9): 946. CrossRef
Exploring the perceptions of Chinese pre-service teachers on the integration of generative AI in English language teaching: Benefits, challenges, and educational implications
Ji Young Chung, Seung-Hoon Jeong
Online Journal of Communication and Media Technologies.2024; 14(4): e202457. CrossRef

Research article

Performance of GPT-3.5 and GPT-4 on standardized urology knowledge assessment items in the United States: a descriptive study: Max Samuel Yudovich, Elizaveta Makarova, Christian Michael Hague, Jay Dilip Raman; J Educ Eval Health Prof. 2024;21:17. Published online July 8, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.17

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Abstract PDF Supplementary Material

Purpose
This study aimed to evaluate the performance of Chat Generative Pre-Trained Transformer (ChatGPT) with respect to standardized urology multiple-choice items in the United States.
Methods
In total, 700 multiple-choice urology board exam-style items were submitted to GPT-3.5 and GPT-4, and responses were recorded. Items were categorized based on topic and question complexity (recall, interpretation, and problem-solving). The accuracy of GPT-3.5 and GPT-4 was compared across item types in February 2024.
Results
GPT-4 answered 44.4% of items correctly compared to 30.9% for GPT-3.5 (P<0.00001). GPT-4 (vs. GPT-3.5) had higher accuracy with urologic oncology (43.8% vs. 33.9%, P=0.03), sexual medicine (44.3% vs. 27.8%, P=0.046), and pediatric urology (47.1% vs. 27.1%, P=0.012) items. Endourology (38.0% vs. 25.7%, P=0.15), reconstruction and trauma (29.0% vs. 21.0%, P=0.41), and neurourology (49.0% vs. 33.3%, P=0.11) items did not show significant differences in performance across versions. GPT-4 also outperformed GPT-3.5 with respect to recall (45.9% vs. 27.4%, P<0.00001), interpretation (45.6% vs. 31.5%, P=0.0005), and problem-solving (41.8% vs. 34.5%, P=0.56) type items. This difference was not significant for the higher-complexity items.
Conclusions
ChatGPT performs relatively poorly on standardized multiple-choice urology board exam-style items, with GPT-4 outperforming GPT-3.5. The accuracy was below the proposed minimum passing standards for the American Board of Urology’s Continuing Urologic Certification knowledge reinforcement activity (60%). As artificial intelligence progresses in complexity, ChatGPT may become more capable and accurate with respect to board examination items. For now, its responses should be scrutinized.

Citations

Citations to this article as recorded by

From GPT-3.5 to GPT-4.o: A Leap in AI’s Medical Exam Performance
Markus Kipp
Information.2024; 15(9): 543. CrossRef

Reviews

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.

Citations

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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.

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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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

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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.

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

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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

Citations to this article as recorded by

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.2024;[Epub] CrossRef
Interprofessional education to support alcohol use screening and future team-based management of stress-related disorders in vulnerable populations
Taylor Fitzpatrick-Schmidt, Scott Edwards
Frontiers in Education.2024;[Epub] CrossRef

Doctoral physical therapy students’ increased confidence following exploration of active video gaming systems in a problem-based learning curriculum in the United States: a pre- and post-intervention study: Michelle Elizabeth Wormley, Wendy Romney, Diana Veneri, Andrea Oberlander; J Educ Eval Health Prof. 2022;19:7. Published online April 26, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.7

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Abstract PDF Supplementary Material

Purpose
Active video gaming (AVG) is used in physical therapy (PT) to treat individuals with a variety of diagnoses across the lifespan. The literature supports improvements in balance, cardiovascular endurance, and motor control; however, evidence is lacking regarding the implementation of AVG in PT education. This study investigated doctoral physical therapy (DPT) students’ confidence following active exploration of AVG systems as a PT intervention in the United States.
Methods
This pretest-posttest study included 60 DPT students in 2017 (cohort 1) and 55 students in 2018 (cohort 2) enrolled in a problem-based learning curriculum. AVG systems were embedded into patient cases and 2 interactive laboratory classes across 2 consecutive semesters (April–December 2017 and April–December 2018). Participants completed a 31-question survey before the intervention and 8 months later. Students’ confidence was rated for general use, game selection, plan of care, set-up, documentation, setting, and demographics. Descriptive statistics and the Wilcoxon signed-rank test were used to compare differences in confidence pre- and post-intervention.
Results
Both cohorts showed increased confidence at the post-test, with median (interquartile range) scores as follows: cohort 1: pre-test, 57.1 (44.3–63.5); post-test, 79.1 (73.1–85.4); and cohort 2: pre-test, 61.4 (48.0–70.7); post-test, 89.3 (80.0–93.2). Cohort 2 was significantly more confident at baseline than cohort 1 (P<0.05). In cohort 1, students’ data were paired and confidence levels significantly increased in all domains: use, Z=-6.2 (P<0.01); selection, Z=-5.9 (P<0.01); plan of care, Z=-6.0 (P<0.01); set-up, Z=-5.5 (P<0.01); documentation, Z=-6.0 (P<0.01); setting, Z=-6.3 (P<0.01); and total score, Z=-6.4 (P<0.01).
Conclusion
Structured, active experiences with AVG resulted in a significant increase in students’ confidence. As technology advances in healthcare delivery, it is essential to expose students to these technologies in the classroom.

Citations

Citations to this article as recorded by

The use of artificial intelligence in crafting a novel method for teaching normal human gait
Scott W. Lowe
European Journal of Physiotherapy.2024; : 1. CrossRef

Editorial

Journal of Educational Evaluation for Health Professions received the top-ranking Journal Impact Factor―9.3—in the category of Education, Scientific Disciplines in the 2023 Journal Citation Ranking by Clarivate: Sun Huh; J Educ Eval Health Prof. 2024;21:16. Published online June 24, 2024; DOI: https://doi.org/10.3352/jeehp.2024.21.16

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PDF

Research article

No difference in factual or conceptual recall comprehension for tablet, laptop, and handwritten note-taking by medical students in the United States: a survey-based observational study: Warren Wiechmann, Robert Edwards, Cheyenne Low, Alisa Wray, Megan Boysen-Osborn, Shannon Toohey; J Educ Eval Health Prof. 2022;19:8. Published online April 26, 2022; DOI: https://doi.org/10.3352/jeehp.2022.19.8

11,798 View
490 Download
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Abstract PDF Supplementary Material

Purpose
Technological advances are changing how students approach learning. The traditional note-taking methods of longhand writing have been supplemented and replaced by tablets, smartphones, and laptop note-taking. It has been theorized that writing notes by hand requires more complex cognitive processes and may lead to better retention. However, few studies have investigated the use of tablet-based note-taking, which allows the incorporation of typing, drawing, highlights, and media. We therefore sought to confirm the hypothesis that tablet-based note-taking would lead to equivalent or better recall as compared to written note-taking.
Methods
We allocated 68 students into longhand, laptop, or tablet note-taking groups, and they watched and took notes on a presentation on which they were assessed for factual and conceptual recall. A second short distractor video was shown, followed by a 30-minute assessment at the University of California, Irvine campus, over a single day period in August 2018. Notes were analyzed for content, supplemental drawings, and other media sources.
Results
No significant difference was found in the factual or conceptual recall scores for tablet, laptop, and handwritten note-taking (P=0.61). The median word count was 131.5 for tablets, 121.0 for handwriting, and 297.0 for laptops (P=0.01). The tablet group had the highest presence of drawing, highlighting, and other media/tools.
Conclusion
In light of conflicting research regarding the best note-taking method, our study showed that longhand note-taking is not superior to tablet or laptop note-taking. This suggests students should be encouraged to pick the note-taking method that appeals most to them. In the future, traditional note-taking may be replaced or supplemented with digital technologies that provide similar efficacy with more convenience.

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Typed Versus Handwritten Lecture Notes and College Student Achievement: A Meta-Analysis
Abraham E. Flanigan, Jordan Wheeler, Tiphaine Colliot, Junrong Lu, Kenneth A. Kiewra
Educational Psychology Review.2024;[Epub] CrossRef

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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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.

Research article

Effect of motion-graphic video-based training on the performance of operating room nurse students in cataract surgery in Iran: a randomized controlled study: Behnaz Fatahi, Samira Fatahi, Sohrab Nosrati, Masood Bagheri; J Educ Eval Health Prof. 2023;20:34. Published online November 28, 2023; DOI: https://doi.org/10.3352/jeehp.2023.20.34

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Abstract PDF Supplementary Material: Purpose
The present study was conducted to determine the effect of motion-graphic video-based training on the performance of operating room nurse students in cataract surgery using phacoemulsification at Kermanshah University of Medical Sciences in Iran.
Methods
This was a randomized controlled study conducted among 36 students training to become operating room nurses. The control group only received routine training, and the intervention group received motion-graphic video-based training on the scrub nurse’s performance in cataract surgery in addition to the educator’s training. The performance of the students in both groups as scrub nurses was measured through a researcher-made checklist in a pre-test and a post-test.
Results
The mean scores for performance in the pre-test and post-test were 17.83 and 26.44 in the control group and 18.33 and 50.94 in the intervention group, respectively, and a significant difference was identified between the mean scores of the pre- and post-test in both groups (P=0.001). The intervention also led to a significant increase in the mean performance score in the intervention group compared to the control group (P=0.001).
Conclusion
Considering the significant difference in the performance score of the intervention group compared to the control group, motion-graphic video-based training had a positive effect on the performance of operating room nurse students, and such training can be used to improve clinical training.

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