Internet-Based Assessment of Oncology Health Care Professional Learning Style and Optimization of Materials for Web-Based Learning: Controlled Trial With Concealed Allocation

Identifying Learning Preferences and Strategies in Health Data Science Courses: Systematic Review

BACKGROUND

Learning and teaching interdisciplinary health data science (HDS) is highly challenging, and despite the growing interest in HDS education, little is known about the learning experiences and preferences of HDS students.

OBJECTIVE

We conducted a systematic review to identify learning preferences and strategies in the HDS discipline.

METHODS

We searched 10 bibliographic databases (PubMed, ACM Digital Library, Web of Science, Cochrane Library, Wiley Online Library, ScienceDirect, SpringerLink, EBSCOhost, ERIC, and IEEE Xplore) from the date of inception until June 2023. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and included primary studies written in English that investigated the learning preferences or strategies of students in HDS-related disciplines, such as bioinformatics, at any academic level. Risk of bias was independently assessed by 2 screeners using the Mixed Methods Appraisal Tool, and we used narrative data synthesis to present the study results.

RESULTS

After abstract screening and full-text reviewing of the 849 papers retrieved from the databases, 8 (0.9%) studies, published between 2009 and 2021, were selected for narrative synthesis. The majority of these papers (7/8, 88%) investigated learning preferences, while only 1 (12%) paper studied learning strategies in HDS courses. The systematic review revealed that most HDS learners prefer visual presentations as their primary learning input. In terms of learning process and organization, they mostly tend to follow logical, linear, and sequential steps. Moreover, they focus more on abstract information, rather than detailed and concrete information. Regarding collaboration, HDS students sometimes prefer teamwork, and sometimes they prefer to work alone.

CONCLUSIONS

The studies' quality, assessed using the Mixed Methods Appraisal Tool, ranged between 73% and 100%, indicating excellent quality overall. However, the number of studies in this area is small, and the results of all studies are based on self-reported data. Therefore, more research needs to be conducted to provide insight into HDS education. We provide some suggestions, such as using learning analytics and educational data mining methods, for conducting future research to address gaps in the literature. We also discuss implications for HDS educators, and we make recommendations for HDS course design; for example, we recommend including visual materials, such as diagrams and videos, and offering step-by-step instructions for students.

Providing insights into health data science education through artificial intelligence

BACKGROUND

Health Data Science (HDS) is a novel interdisciplinary field that integrates biological, clinical, and computational sciences with the aim of analysing clinical and biological data through the utilisation of computational methods. Training healthcare specialists who are knowledgeable in both health and data sciences is highly required, important, and challenging. Therefore, it is essential to analyse students' learning experiences through artificial intelligence techniques in order to provide both teachers and learners with insights about effective learning strategies and to improve existing HDS course designs.

METHODS

We applied artificial intelligence methods to uncover learning tactics and strategies employed by students in an HDS massive open online course with over 3,000 students enrolled. We also used statistical tests to explore students' engagement with different resources (such as reading materials and lecture videos) and their level of engagement with various HDS topics.

RESULTS

We found that students in HDS employed four learning tactics, such as actively connecting new information to their prior knowledge, taking assessments and practising programming to evaluate their understanding, collaborating with their classmates, and repeating information to memorise. Based on the employed tactics, we also found three types of learning strategies, including low engagement (Surface learners), moderate engagement (Strategic learners), and high engagement (Deep learners), which are in line with well-known educational theories. The results indicate that successful students allocate more time to practical topics, such as projects and discussions, make connections among concepts, and employ peer learning.

CONCLUSIONS

We applied artificial intelligence techniques to provide new insights into HDS education. Based on the findings, we provide pedagogical suggestions not only for course designers but also for teachers and learners that have the potential to improve the learning experience of HDS students.

Asynchronous e-learning with technology-enabled and enhanced training for continuing education of nurses: a scoping review

BACKGROUND

Asynchronous e-learning has become the mainstream choice since the transformation of learning formats by the coronavirus disease-19 pandemic. This scoping review aimed to examine the technologies used in asynchronous e-learning for the continuing education of clinical nurses and their modes of delivery and effectiveness.

METHODS

This scoping review covered the period between 2011 and 2023. Six databases were searched for relevant studies following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) protocol.

RESULTS

Sixty articles met the inclusion criteria. There was a noticeable trend toward using diverse technology-enabled and enhanced training (TEET) options after 2017. The enabling technological approaches, such as interactive online modules (25 articles) and video modules (25 articles), are described in the articles. The most commonly used enhancing technologies were scenario-based learning (nine articles), resource access (eight articles), computer simulation or virtual reality (three articles), and gamification (three articles). Among the outcomes, knowledge acquisition was the most commonly examined outcome (41 articles).

CONCLUSIONS

Notably, many interactive TEET modules were used in asynchronous e-learning. There were few studies on gamification, computer simulation or virtual reality, and scenario-based learning (techniques to enhance intrinsic motivation further). However, the adoption of asynchronous e-learning with advanced TEET options is anticipated to increase in the future. Therefore, objective outcome measures are required to determine the effects of such learning methods on knowledge acquisition and behavioral changes.

The learning preferences of aspiring orthopaedic surgeons in the UK

BACKGROUND/AIMS

The workload of orthopaedic trainees is rapidly increasing at the expense of training. Trainees are expected to assimilate large quantities of information efficiently. This prospective cohort study explores the learning styles, resource preferences and educational needs of aspiring orthopaedic trainees.

METHOD

A 21-item questionnaire was distributed to delegates of an orthopaedic teaching series. Data were obtained pertaining to demographics, visual, aural, read/write and kinaesthetic learning styles, study materials used and teaching exposure.

RESULTS

Participants had a strong preference for visual (48.0%) and kinaesthetic (43.0%) learning modalities. Most participants prepared for written exams using online question banks (85.9%), clinical exams using question banks (37.5%) and discussion with colleagues (27.3%), and surgical procedures intraoperatively (43.8%). Only 12.4% of participants felt the teaching they received was consistently adapted to their visual, aural, read/write or kinaesthetic learning preference.

CONCLUSIONS

The surgical landscape is rapidly changing. It is vital that trainers take into consideration how budding orthopaedic surgeons learn and make the relevant accommodations, to ensure optimal learning.

My Cancer Genome: Coevolution of Precision Oncology and a Molecular Oncology Knowledgebase

PURPOSE

The My Cancer Genome (MCG) knowledgebase and resulting website were launched in 2011 with the purpose of guiding clinicians in the application of genomic testing results for treatment of patients with cancer. Both knowledgebase and website were originally developed using a wiki-style approach that relied on manual evidence curation and synthesis of that evidence into cancer-related biomarker, disease, and pathway pages on the website that summarized the literature for a clinical audience. This approach required significant time investment for each page, which limited website scalability as the field advanced. To address this challenge, we designed and used an assertion-based data model that allows the knowledgebase and website to expand with the field of precision oncology.

METHODS

Assertions, or computationally accessible cause and effect statements, are both manually curated from primary sources and imported from external databases and stored in a knowledge management system. To generate pages for the MCG website, reusable templates transform assertions into reconfigurable text and visualizations that form the building blocks for automatically updating disease, biomarker, drug, and clinical trial pages.

RESULTS

Combining text and graph templates with assertions in our knowledgebase allows generation of web pages that automatically update with our knowledgebase. Automated page generation empowers rapid scaling of the website as assertions with new biomarkers and drugs are added to the knowledgebase. This process has generated more than 9,100 clinical trial pages, 18,100 gene and alteration pages, 900 disease pages, and 2,700 drug pages to date.

CONCLUSION

Leveraging both computational and manual curation processes in combination with reusable templates empowers automation and scalability for both the MCG knowledgebase and MCG website.

The Learning Styles Neuromyth Is Still Thriving in Medical Education

Learning Styles theory promises improved academic performance based on the identification of a personal, sensory preference for informational processing. This promise is not supported by evidence, and is in contrast to our current understanding of the neuroscience of learning. Despite this lack of evidence, prior research shows that that belief in the Learning Styles “neuromyth” remains high amongst educators of all levels, around the world. This perspective article is a follow up on prior research aimed at understanding why belief in the neuromyth of Learning Styles remains so high. We evaluated current research papers from the field of health professions education, to characterize the perspective that an educator would be given, should they search for evidence on Learning Styles. As in earlier research on Higher Education, we found that the use of Learning Style frameworks persist in education research for the health professions; 91% of 112 recent research papers published on Learning Styles are based upon the premise that Learning Styles are a useful approach to education. This is in sharp contrast to the fundamental principle of evidence-based practice within these professions. Thus any educator who sought out the research evidence on Learning Styles would be given a consistent but inaccurate endorsement of the value of a teaching technique that is not evidence based, possibly then propagating the belief in Learning Styles. Here we offer perspectives from both research and student about this apparent mismatch between educational practice and clinical practice, along with recommendations and considerations for the future.

An online curriculum in movement disorders for neurology housestaff

Introduction

In many neurology residency programs, outpatient neurology subspecialties are underrepresented. Trainee exposure to these subspecialties, including movement disorders, is limited by paucity and variability of clinical experiences. We designed a structured educational tool to address this variability and allow for standardization of elements of movement disorders teaching.

Methods

We designed and implemented a web-based curriculum in movement disorders for neurology housestaff, in order to improve participant knowledge. The curriculum includes an introduction with a structured framework for the description of abnormal movements and 10 interactive modules focusing on common movement disorders. The curriculum was piloted with nine neurology housestaff at Yale-New Haven Hospital. Evaluation of the curriculum was performed using pre- and post-tests, a survey, and semi-structured interviews.

Results

The mean pre-test score was 0.7 (±0.19), and the mean post-test score was 0.95 (±0.05) (t = 3.27). Surveys demonstrated mean Likert values >4/5 for all questions in all categories (knowledge acquisition, quantity, enthusiasm and technical). Semi-structured interviews revealed the following themes: 1) the modules increased participant comfort with the topic, 2) the format was engaging, and 3) the curriculum accommodated different learning styles. All participants remarked that the structured framework was a particular strength.

Conclusion

We have created, implemented, and evaluated a foundational curriculum in movement disorders for neurology trainees, using readily-available technology. Housestaff responded positively to the curriculum, both in terms of content and format. This curriculum can be implemented in a variety of educational settings, as a central component of a standardized approach to movement disorders teaching.

Efficacy of adaptive e-learning for health professionals and students: a systematic review and meta-analysis

OBJECTIVE

Although adaptive e-learning environments (AEEs) can provide personalised instruction to health professional and students, their efficacy remains unclear. Therefore, this review aimed to identify, appraise and synthesise the evidence regarding the efficacy of AEEs in improving knowledge, skills and clinical behaviour in health professionals and students.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

CINAHL, EMBASE, ERIC, PsycINFO, PubMed and Web of Science from the first year of records to February 2019.

ELIGIBILITY CRITERIA

Controlled studies that evaluated the effect of an AEE on knowledge, skills or clinical behaviour in health professionals or students.

SCREENING, DATA EXTRACTION AND SYNTHESIS

Two authors screened studies, extracted data, assessed risk of bias and coded quality of evidence independently. AEEs were reviewed with regard to their topic, theoretical framework and adaptivity process. Studies were included in the meta-analysis if they had a non-adaptive e-learning environment control group and had no missing data. Effect sizes (ES) were pooled using a random effects model.

RESULTS

From a pool of 10 569 articles, we included 21 eligible studies enrolling 3684 health professionals and students. Clinical topics were mostly related to diagnostic testing, theoretical frameworks were varied and the adaptivity process was characterised by five subdomains: method, goals, timing, factors and types. The pooled ES was 0.70 for knowledge (95% CI -0.08 to 1.49; p.08) and 1.19 for skills (95% CI 0.59 to 1.79; p<0.00001). Risk of bias was generally high. Heterogeneity was large in all analyses.

CONCLUSIONS

AEEs appear particularly effective in improving skills in health professionals and students. The adaptivity process within AEEs may be more beneficial for learning skills rather than factual knowledge, which generates less cognitive load. Future research should report more clearly on the design and adaptivity process of AEEs, and target higher-level outcomes, such as clinical behaviour.

PROSPERO REGISTRATION NUMBER

CRD42017065585.

Outpatient Cancer Care Delivery in the Context of E-Oncology: A French Perspective on "Cancer outside the Hospital Walls"

In oncology, the treatment of patients outside of hospitals has become imperative due to an increasing number of patients who are older and live longer, along with issues such as medical desertification, oncologist hyperspecialization, and difficulties in financing mounting health expenditures. Treatments have become less "invasive", with greater precision and efficiency. Patients can therefore receive most of their care outside of hospitals. The development of e-health can address these new imperatives. In this letter, we describe the different e-health tools and their potential clinical impacts in oncology, as already reported at every level of care, including education, prevention, diagnosis, treatment, and monitoring. A few randomized studies have yet demonstrated the clinical benefit. We also comment on issues and limits of "cancer outside the hospital walls" from the point of view of patients, health care professionals, health facilities, and public authorities. Care providers in hospitals and communities will have to adapt to these changes within well-coordinated networks in order to better meet patient expectations regarding increasing education and personalizing management. Ultimately, controlled studies should aim to definitively demonstrate areas of interest, benefits, and incentives, for not only patients, but also caregivers (formal and informal) and health care providers, health care facilities, and the nation.

The reach of Spanish-language YouTube videos on physical examinations made by undergraduate medical students

This study was conducted to evaluate the performance and reach of YouTube videos on physical examinations made by Spanish university students. We analyzed performance metrics for 4 videos on physical examinations in Spanish that were created by medical students at Miguel Hernández University (Elche, Spain) and are available on YouTube, on the following topics: the head and neck (7:30), the cardiovascular system (7:38), the respiratory system (13:54), and the abdomen (11:10). We used the Analytics application offered by the YouTube platform to analyze the reach of the videos from the upload date (February 17, 2015) to July 28, 2017 (2 years, 5 months, and 11 days). The total number of views, length of watch-time, and the mean view duration for the 4 videos were, respectively: 164,403 views (mean, 41,101 views; range, 12,389 to 94,573 views), 425,888 minutes (mean, 106,472 minutes; range, 37,889 to 172,840 minutes), and 2:56 minutes (range, 1:49 to 4:03 minutes). Mexico was the most frequent playback location, followed by Spain, Colombia, and Venezuela. Uruguay, Ecuador, Mexico, and Puerto Rico had the most views per 100,000 population. Spanish-language tutorials are an alternative tool for teaching physical examination skills to students whose first language is not English. The videos were especially popular in Uruguay, Ecuador, and Mexico.