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Journal Description

JMIR Medical Education (JME) is an open access, Pubmed-indexed, peer-reviewed journal with focus on technology, innovation and openess in medical education. Another focus is on how to train health professionals to use digital tools. We publish original research, reviews, viewpoint and policy papers on innovation and technology in medical education. As an open access journal we have special interest in open and free tools and digitial learning objects for medical education, and urge authors to make their tools and learning objects freely available (we may also publish them as Multimedia Appendix). We also invite submissions of non-conventional articles (eg, open medical education material and software resources that are not yet evaluated but free for others to use/implement). 

In our "Students' Corner", we invite students and trainees from various health professions to submit short essays and viewpoints on all aspects of medical education, but in particular suggestions on how to improve medical education, and suggestions for new technologies, applications and approaches (no article processing fees) are the main focuses.

Articles published in JME will be submitted to PubMed and Pubmed Central.

 

Recent Articles:

  • Source: The Authors / Placeit; Copyright: The Authors; URL: http://mededu.jmir.org/2020/3/e14428/; License: Licensed by JMIR.

    Comparison of Assessment by a Virtual Patient and by Clinician-Educators of Medical Students' History-Taking Skills: Exploratory Descriptive Study

    Abstract:

    Background: A virtual patient (VP) can be a useful tool to foster the development of medical history–taking skills without the inherent constraints of the bedside setting. Although VPs hold the promise of contributing to the development of students’ skills, documenting and assessing skills acquired through a VP is a challenge. Objective: We propose a framework for the automated assessment of medical history taking within a VP software and then test this framework by comparing VP scores with the judgment of 10 clinician-educators (CEs). Methods: We built upon 4 domains of medical history taking to be assessed (breadth, depth, logical sequence, and interviewing technique), adapting these to be implemented into a specific VP environment. A total of 10 CEs watched the screen recordings of 3 students to assess their performance first globally and then for each of the 4 domains. Results: The scores provided by the VPs were slightly higher but comparable with those given by the CEs for global performance and for depth, logical sequence, and interviewing technique. For breadth, the VP scores were higher for 2 of the 3 students compared with the CE scores. Conclusions: Findings suggest that the VP assessment gives results akin to those that would be generated by CEs. Developing a model for what constitutes good history-taking performance in specific contexts may provide insights into how CEs generally think about assessment.

  • Medical educator and students. Source: iStock by Getty Images; Copyright: skynesher; URL: https://www.istockphoto.com/ca/photo/mid-adult-doctor-teaching-on-a-seminar-in-a-board-room-gm1006430612-271624542; License: Licensed by the authors.

    Introducing Artificial Intelligence Training in Medical Education

    Abstract:

    Health care is evolving and with it the need to reform medical education. As the practice of medicine enters the age of artificial intelligence (AI), the use of data to improve clinical decision making will grow, pushing the need for skillful medicine-machine interaction. As the rate of medical knowledge grows, technologies such as AI are needed to enable health care professionals to effectively use this knowledge to practice medicine. Medical professionals need to be adequately trained in this new technology, its advantages to improve cost, quality, and access to health care, and its shortfalls such as transparency and liability. AI needs to be seamlessly integrated across different aspects of the curriculum. In this paper, we have addressed the state of medical education at present and have recommended a framework on how to evolve the medical education curriculum to include AI.

  • Laptops and mutual study image. Source: Foter; Copyright: Foter; URL: https://foter.com/photo3/notebook-person-man-laptops/; License: Public Domain (CC0).

    Opportunities and Obstacles for Providing Medical Education Through Social Media

    Abstract:

    Social media has infiltrated almost every sector of life, and medical education is no exception. As this technology becomes mainstream within society, an increasing number of health care students and professionals are using it for learning. Several important considerations for the risks of this technology are discussed here.

  • Source: energepic.com; Copyright: Pexels; URL: https://www.pexels.com/photo/design-desk-display-eyewear-313690/; License: Licensed by the authors.

    Students' Experiences of Seeking Web-Based Animal Health Information at the Ontario Veterinary College: Exploratory Qualitative Study

    Abstract:

    Background: Although searching for health information on the internet has offered clear benefits of rapid access to information for seekers such as patients, medical practitioners, and students, detrimental effects on seekers’ experiences have also been documented. Health information overload is one such side effect, where an information seeker receives excessive volumes of potentially useful health-related messages that cannot be processed in a timely manner. This phenomenon has been documented among medical professionals, with consequences that include impacts on patient care. Presently, the use of the internet for health-related information, and particularly animal health information, in veterinary students has received far less research attention. Objective: The purpose of this study was to explore veterinary students’ internet search experiences to understand how students perceived the nature of Web-based information and how these perceptions influence their information management. Methods: For this qualitative exploratory study, 5 separate focus groups and a single interview were conducted between June and October 2016 with a sample of 21 veterinary students in Ontario, Canada. Results: Thematic analysis of focus group transcripts demonstrated one overarching theme, The Overwhelming Nature of the Internet, depicted by two subthemes: Volume and Type of Web-based Health Information and Processing, Managing, and Evaluating Information. Conclusions: Integrating electronic health information literacy training into human health sciences students’ training has shown to have positive effects on information management skills. Given a recent Association of American Veterinary Medical Colleges report that considers health literacy as a professional competency, results of this study point to a direction for future research and for institutions to contemplate integrating information literacy skills in veterinary curricula. Specifically, we propose that the information literacy skills should include knowledge about access, retrieval, evaluation, and timely application of Web-based information.

  • Researcher examines the geographic distribution of practice locations of graduates from the University of Minnesota Medical School (montage). Source: The Authors / Placeit; Copyright: JMIR Publications; URL: https://mededu.jmir.org/2019/2/e14651; License: Creative Commons Attribution (CC-BY).

    Building a Medical Education Outcomes Center: Development Study

    Abstract:

    Background: Medical education and clinical data exist in multiple unconnected databases, resulting in 3 problems: (1) it is difficult to connect learner outcomes with patient outcomes, (2) learners cannot be easily tracked over time through the education-training-practice continuum, and (3) no standard methodology ensures quality and privacy of the data. Objective: The purpose of this study was to develop a Medical Education Outcomes Center (MEOC) to integrate education data and to build a framework to standardize the intake and processing of requests for using these data. Methods: An inventory of over 100 data sources owned or utilized by the medical school was conducted, and nearly 2 dozen of these data sources have been vetted and integrated into the MEOC. In addition, the American Medical Association (AMA) Physician Masterfile data of the University of Minnesota Medical School (UMMS) graduates were linked to the data from the National Provider Identifier (NPI) registry to develop a mechanism to connect alumni practice data to education data. Results: Over 160 data requests have been fulfilled, culminating in a range of outcomes analyses, including support of accreditation efforts. The MEOC received data on 13,092 UMMS graduates in the AMA Physician Masterfile and could link 10,443 with NPI numbers and began to explore their practice demographics. The technical and operational work to expand the MEOC continues. Next steps are to link the educational data to the clinical practice data through NPI numbers to assess the effectiveness of our medical education programs by the clinical outcomes of our graduates. Conclusions: The MEOC provides a replicable framework to allow other schools to more effectively operate their programs and drive innovation.

  • Source: Freepik; Copyright: Freepik; URL: https://www.freepik.com/free-photo/doctor-working-with-laptop_1093189.htm#page=1&query=ultrasound&position=14; License: Licensed by JMIR.

    Introduction of Ultrasound Simulation in Medical Education: Exploratory Study

    Abstract:

    Background: Ultrasound is ubiquitous across all disciplines of medicine; it is one of the most commonly used noninvasive, painless diagnostic tools. However, not many are educated and trained well enough in its use. Ultrasound requires not only theoretical knowledge but also extensive practical experience. The simulated setting offers the safest environment for health care professionals to learn and practice using ultrasound. Objective: This study aimed to (1) assess health care professionals’ need for and enthusiasm toward practicing using ultrasound via simulation and (2) gauge their perception and acceptance of simulation as an integral element of ultrasound education in medical curricula. Methods: A day-long intervention was organized at the American University of Beirut Medical Center (AUBMC) to provide a free-of-charge interactive ultrasound simulation workshop—using CAE Vimedix high-fidelity simulator—for health care providers, including physicians, nurses, ultrasound technicians, residents, and medical students. Following the intervention, attendees completed an evaluation, which included 4 demographic questions and 16 close-ended questions based on a Likert scale agree-neutral-disagree. The results presented are based on this evaluation form. Results: A total of 41 participants attended the workshop (46% [19/41] physicians, 30% [12/41] residents, 19% [8/41] sonographers, and 5% [2/41] medical students), mostly from AUBMC (88%, 36/41), with an average experience of 2.27 (SD 3.45) years and 30 (SD 46) scans per attendee. Moreover, 15 out of 41 (36%) participants were from obstetrics and gynecology, 11 (27%) from internal medicine, 4 (10%) from pediatrics, 4 (10%) from emergency medicine, 2 (5%) from surgery and family medicine, and 5 (12%) were technicians. The majority of participants agreed that ultrasound provided a realistic setting (98%, 40/41) and that it allowed for training and identification of pathologies (88%, 36/41). Furthermore, 100% (41/41) of the participants agreed that it should be part of the curriculum either in medical school or residency, and most of the participants approved it for training (98%, 40/41) and teaching (98%, 40/41). Conclusions: All attendees were satisfied with the intervention. There was a positive perception toward the use of simulation for training and teaching medical students and residents in using ultrasound, and there was a definite need and enthusiasm for its integration into curricula. Simulation offers an avenue not only for teaching but also for practicing the ultrasound technology by both medical students and health care providers.

  • Source: Siddharth Bhogra / Unsplash; Copyright: Siddharth Bhogra; URL: https://unsplash.com/photos/k3kdc5MQYyk; License: Licensed by JMIR.

    Understanding the Use and Perceived Impact of a Medical Podcast: Qualitative Study

    Abstract:

    Background: Although podcasts are increasingly being produced for medical education, their use and perceived impact in informal educational settings are understudied. Objective: This study aimed to explore how and why physicians and medical learners listen to The Rounds Table (TRT), a medical podcast, as well as to determine the podcast’s perceived impact on learning and practice. Methods: Web-based podcast analytics were used to collect TRT usage statistics. A total of 17 medical TRT listeners were then identified and interviewed through purposive and convenience sampling, using a semistructured guide and a thematic analysis, until theoretical sufficiency was achieved. Results: The following four themes related to podcast listenership were identified: (1) participants thought that TRT increased efficiency, allowing them to multitask, predominantly using mobile listening platforms; (2) participants listened to the podcast for both education and entertainment, or “edutainment”; (3) participants thought that the podcast helped them keep up to date with medical literature; and (4) participants considered TRT to have an indirect effect on learning and clinical practice by increasing overall knowledge. Conclusions: Our results highlight how a medical podcast, designed for continuing professional development, is often used informally to promote learning. These findings enhance our understanding of how and why listeners engage with a medical podcast, which may be used to inform the development and evaluation of other podcasts.

  • AMBOSS website (montage). Source: Authors; Copyright: JMIR Publications; URL: https://mededu.jmir.org/2019/2/e13529; License: Creative Commons Attribution (CC-BY).

    Association of Online Learning Behavior and Learning Outcomes for Medical Students: Large-Scale Usage Data Analysis

    Abstract:

    Background: Digital learning environments have become very common in the training of medical professionals, and students often use such platforms for exam preparation. Multiple choice questions (MCQs) are a common format in medical exams and are used by students to prepare for said exams. Methods: We analyzed data from users of an online platform that provides learning materials for medical students in preparation for their final exams. We analyzed whether the number of learning cards viewed and the number of MCQs taken were positively related to learning outcomes. We also examined whether viewing learning cards or answering MCQs was more effective. Finally, we tested whether taking individual notes predicted learning outcomes, and whether taking notes had an effect after controlling for the effects of learning cards and MCQs. Our analyses from the online platform Amboss are based on user activity data, which supplied the number of learning cards studied and test questions answered. We also included the number of notes from each of those 23,633 users who had studied at least 200 learning cards and had answered at least 1000 test exam questions in the 180 days before their state exam. The activity data for this analysis was collected retrospectively, using Amboss archival usage data from April 2014 to April 2017. Learning outcomes were measured using the final state exam scores that were calculated by using the answers voluntarily entered by the participants. Results: We found correlations between the number of cards studied (r=.22; P<.001) and the number of test questions that had been answered (r=.23; P<.001) with the percentage of correct answers in the learners’ medical exams. The number of test questions answered still yielded a significant effect, even after controlling for the number of learning cards studied using a hierarchical regression analysis (β=.14; P<.001; ΔR2=.017; P<.001). We found a negative interaction between the number of learning cards and MCQs, indicating that users with high scores for learning cards and MCQs had the highest exam scores. Those 8040 participants who had taken at least one note had a higher percentage of correct answers (80.94%; SD=7.44) than those who had not taken any notes (78.73%; SD=7.80; t23631=20.95; P<.001). In a stepwise regression, the number of notes the participants had taken predicted the percentage of correct answers over and above the effect of the number of learning cards studied and of the number of test questions entered in step one (β=.06; P<.001; ΔR2=.004; P<.001). Conclusions: These results show that online learning platforms are particularly helpful whenever learners engage in active elaboration in learning material, such as by answering MCQs or taking notes.

  • Interprofessional mobile learning. Source: rawpixel / Pexels; Copyright: rawpixel; URL: https://www.pexels.com/photo/woman-holding-white-smartphone-with-black-case-1331970/; License: Licensed by JMIR.

    Media Use Among Students From Different Health Curricula: Survey Study

    Abstract:

    Background: Mobile devices such as smartphones, tablets, and laptop computers enable users to search for information and communicate with others at any place and any time. Such devices are increasingly being used at universities for teaching and learning. The use of mobile devices by students depends, among others, on the individual media literacy level and the curricular framework. Objective: The objective of this study was to explore whether there were differences in media use in students from various curricula at the Faculty of Health, Witten/Herdecke University. Methods: During the 2015-16 winter term, a survey was conducted at the Faculty of Health, Witten/Herdecke University, in which a total of 705 students (out of 1091 students; response rate: 705/1091, 64.61%) from 4 schools participated voluntarily: medicine (346/598), dentistry (171/204), psychology (142/243), and nursing science (46/46). The questionnaire developed for the study included 132 questions on 4 topics: (1) electronic and mobile devices (19 questions), (2) communication and organization of learning (45 questions), (3) apps/programs/websites/media (34 questions), and (4) media literacy (34 questions). The questionnaire was distributed and anonymously completed during in-class courses. Results: Students from all 4 schools had at least two electronic devices, with smartphones (97.4%, 687/705) and laptops (94.8%, 669/705) being the most common ones. Students agreed that electronic devices enabled them to effectively structure the learning process (mean 3.16, SD 0.62) and shared the opinion that university teaching should include imparting media literacy (mean 2.84, SD 0.84). Electronic device ownership was the highest among medical students (mean 2.68, SD 0.86) and medical students were the only ones to use a tutorial (36.1%, 125/346). Dental students most widely used text messages (mean 3.41, SD 0.49) and social media (mean 2.57, SD 1.10) to organize learning. Psychology students considered mobile devices to be most ineffective (mean 2.81, SD 0.83). Nursing science students used emails (mean 3.47, SD 0.73) and desktop computers (39%, 18/46) most widely. Conclusions: The results show that almost all students use electronic learning (e-learning) tools. At the same time, different profiles for different degree programs become apparent, which are to be attributed to not only the varying curricula and courses but also to the life circumstances of different age groups. Universities should, therefore, pay attention to the diverse user patterns and media literacy levels of students when planning courses to enable successful use of e-learning methods.

  • Using technology in medical education. Source: iStock by Getty Images; Copyright: Natali_Mis; URL: https://www.istockphoto.com/ca/photo/doctor-shows-a-virtual-hologram-from-your-tablet-gm920013790-252880205; License: Licensed by the authors.

    Microlearning in Health Professions Education: Scoping Review

    Abstract:

    Background: Microlearning, the acquisition of knowledge or skills in the form of small units, is endorsed by health professions educators as a means of facilitating student learning, training, and continuing education, but it is difficult to define in terms of its features and outcomes. Objective: This review aimed to conduct a systematic search of the literature on microlearning in health professions education to identify key concepts, characterize microlearning as an educational strategy, and evaluate pedagogical outcomes experienced by health professions students. Methods: A scoping review was performed using the bibliographic databases PubMed (MEDLINE), CINAHL, Education Resources Information Center, EMBASE, PsycINFO, Education Full Text (HW Wilson), and ProQuest Dissertations and Theses Global. A combination of keywords and subject headings related to microlearning, electronic learning, or just-in-time learning combined with health professions education was used. No date limits were placed on the search, but inclusion was limited to materials published in English. Pedagogical outcomes were evaluated according to the 4-level Kirkpatrick model. Results: A total of 3096 references were retrieved, of which 17 articles were selected after applying the inclusion and exclusion criteria. Articles that met the criteria were published between 2011 and 2018, and their authors were from a range of countries, including the United States, China, India, Australia, Canada, Iran, Netherlands, Taiwan, and the United Kingdom. The 17 studies reviewed included various health-related disciplines, such as medicine, nursing, pharmacy, dentistry, and allied health. Although microlearning appeared in a variety of subject areas, different technologies, such as podcast, short messaging service, microblogging, and social networking service, were also used. On the basis of Buchem and Hamelmann’s 10 microlearning concepts, each study satisfied at least 40% of the characteristics, whereas all studies featured concepts of maximum time spent less than 15 min as well as content aggregation. According to our assessment of each article using the Kirkpatrick model, 94% (16/17) assessed student reactions to the microlearning (level 1), 82% (14/17) evaluated knowledge or skill acquisition (level 2), 29% (5/17) measured the effect of the microlearning on student behavior (level 3), and no studies were found at the highest level. Conclusions: Microlearning as an educational strategy has demonstrated a positive effect on the knowledge and confidence of health professions students in performing procedures, retaining knowledge, studying, and engaging in collaborative learning. However, downsides to microlearning include pedagogical discomfort, technology inequalities, and privacy concerns. Future research should look at higher-level outcomes, including benefits to patients or practice changes. The findings of this scoping review will inform education researchers, faculty, and academic administrators on the application of microlearning, pinpoint gaps in the literature, and help identify opportunities for instructional designers and subject matter experts to improve course content in didactic and clinical settings.

  • Students attending an electronic case seminar with free choice of teaching format. Source: Image created by the Authors; Copyright: The Authors; URL: http://mededu.jmir.org/2019/2/e13386/; License: Licensed by JMIR.

    The Impact of Medical Students’ Individual Teaching Format Choice on the Learning Outcome Related to Clinical Reasoning

    Abstract:

    Background: Repeated formative assessments using key feature questions have been shown to enhance clinical reasoning. Key feature questions augmented by videos presenting clinical vignettes may be more effective than text-based questions, especially in a setting where medical students are free to choose the format they would like to work with. This study investigated learning outcomes related to clinical reasoning in students using video- or text-based key feature questions according to their individual preferences. Objective: The aim of this study was to test the hypothesis that repeated exposure to video-based key feature questions enhances clinical reasoning to a greater extent than repeated exposure to text-based key feature questions if students are allowed to choose between those different formats on their own. Methods: In this monocentric, prospective, nonrandomized trial, fourth-year medical students attended 12 computer-based case seminars during which they worked on case histories containing key feature questions. Cases were available in a text- and a video-based format. Students chose their preferred presentation format at the beginning of each case seminar. Student performance in key feature questions was assessed in formative entry, exit, and retention exams and was analyzed with regard to preceding exposure to video- or text-based case histories. Results: Of 102 eligible students, 75 provided written consent and complete data at all study exams (response rate=73.5%). A majority of students (n=52) predominantly chose the text-based format. Compared with these, students preferring the video-based format achieved a nonsignificantly higher score in the exit exam (mean 76.2% [SD 12.6] vs 70.0% [SD 19.0]; P=.15) and a significantly higher score in the retention exam (mean 75.3% [SD 16.6] vs 63.4% [SD 20.3]; P=.02). The effect was independent of the video- or text-based presentation format, which was set as default in the respective exams. Conclusions: Despite students’ overall preference for text-based case histories, the learning outcome with regard to clinical reasoning was higher in students with higher exposure to video-based items. Time-on-task is one conceivable explanation for these effects as working with video-based items was more time-consuming. The baseline performance levels of students do not account for the results as the preceding summative exam results were comparable across the 2 groups. Given that a substantial number of students chose a presentation format that was less effective, students might need to be briefed about the beneficial effects of using video-based case histories to be able to make informed choices about their study methods.

  • The 9 steps model. Source: The Authors / CanStockPhoto; Copyright: The Authors; URL: https://mededu.jmir.org/2019/2/e13004; License: Creative Commons Attribution (CC-BY).

    A 9-Step Theory- and Evidence-Based Postgraduate Medical Digital Education Development Model: Empirical Development and Validation

    Abstract:

    Background: Digital education tools (e-learning, technology-enhanced learning) can be defined as any educational intervention that is electronically mediated. Decveloping and applying such tools and interventions for postgraduate medical professionals who work and learn after graduation can be called postgraduate medical digital education (PGMDE), which is increasingly being used and evaluated. However, evaluation has focused mainly on reaching the learning goals and little on the design. Design models for digital education (instructional design models) help educators create a digital education curriculum, but none have been aimed at PGMDE. Studies show the need for efficient, motivating, useful, and satisfactory digital education. Objective: Our objective was (1) to create an empirical instructional design model for PGMDE founded in evidence and theory, with postgraduate medical professionals who work and learn after graduation as the target audience, and (2) to compare our model with existing models used to evaluate and create PGMDE. Methods: Previously we performed an integrative literature review, focus group discussions, and a Delphi procedure to determine which building blocks for such a model would be relevant according to experts and users. This resulted in 37 relevant items. We then used those 37 items and arranged them into chronological steps. After we created the initial 9-step plan, we compared these steps with other models reported in the literature. Results: The final 9 steps were (1) describe who, why, what, (2) select educational strategies, (3) translate to the real world, (4) choose the technology, (5) complete the team, (6) plan the budget, (7) plan the timing and timeline, (8) implement the project, and (9) evaluate continuously. On comparing this 9-step model with other models, we found that no other was as complete, nor were any of the other models aimed at PGMDE. Conclusions: Our 9-step model is the first, to our knowledge, to be based on evidence and theory building blocks aimed at PGMDE. We have described a complete set of evidence-based steps, expanding a 3-domain model (motivate, learn, and apply) to an instructional design model that can help every educator in creating efficient, motivating, useful, and satisfactory PGMDE. Although certain steps are more robust and have a deeper theoretical background in current research (such as education), others (such as budget) have been barely touched upon and should be investigated more thoroughly in order that proper guidelines may also be provided for them.

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