Pilot study of a newly developed eLearning tool to teach CT and PET/CT in radiology and nuclear medicine

2020 ◽  
Vol 59 (02) ◽  
pp. 79-84
Author(s):  
Alexander Heinzel ◽  
Jörg Marienhagen ◽  
Sareh Said Yekta-Michael ◽  
Felix M. Mottaghy ◽  
Jennifer Krzemien ◽  
...  
Keyword(s):  
Nuclear Medicine ◽  
Medical Students ◽  
User Experience ◽  
Free Text ◽  
Undergraduate Medical Students ◽  
Web Based ◽  
Pet Ct ◽  
System Usability Scale ◽  
Positive Evaluation

Abstract Aim To test the usability and user experience of a newly self-developed eLearning tool to teach PET/CT and CT to undergraduate medical students. Methods The eLearning tool permits to display PET and CT DICOM images web-based. It contains a healthy subject with anatomical annotations and a clinical case study. The usability and user experience of the eLearning tool was evaluated in undergraduate medical students of the medical faculty of the RWTH Aachen. We applied a survey based on different already existing and validated questionnaires such as System Usability Scale (SUS) and User Experience Questionnaire (UEQ-S) as well as specific questions regarding the eLearning tool. Results 38 volunteers (9 males) participated in our study. Applying the SUS resulted in a mean of 82.24, and a median of 83.75. This positive evaluation is supported by the results of the UEQ-S that were 2.2 with regard to the pragmatic quality, 2.3 with regard to hedonic quality and 2.3 for overall quality indicating a very positive evaluation. In the free-text answers, students emphasised easy and intuitive use of the eLearning tool that was additionally described as interesting and exciting. The students also positively mentioned the case study and the possibility of practice-based learning. Negative aspects were mainly problems with synchronisation of the PET and CT images. Conclusion The positive evaluation is encouraging and form a foundation for further development of the eLearning module. It may be the basis for the implementation of a sustainable blended learning concept in the nuclear medicine curriculum.

Quantifying empathy levels among UK undergraduate medical students: an online survey

2020 ◽  
Vol 70 (suppl 1) ◽  
pp. bjgp20X711293
Author(s):  
Sarah Garnett ◽  
Hajira Dambha-Miller ◽  
Beth Stuart
Keyword(s):  
Medical Students ◽  
Health Outcomes ◽  
Medical School ◽  
Curriculum Design ◽  
Online Survey ◽  
Mental Wellbeing ◽  
Reactivity Index ◽  
Free Text ◽  
Undergraduate Medical Students ◽  
Cross Sectional

BackgroundEmpathy is a key health care concept and refers to care that incorporates understanding of patient perspective’s, shared decision making, and consideration of the broader context in which illness is experience. Evidence suggests experiences of doctor empathy correlate with improved health outcomes and patient satisfaction. It has also been linked to job satisfaction, and mental wellbeing for doctors. To date, there is a paucity of evidence on empathy levels among medical students. This is critical to understand given that it is a key point at which perceptions and practices of empathy in the longer term might be formed.AimTo quantify the level of empathy among UK undergraduate medical studentsMethodAn anonymised cross-sectional online survey was distributed to medical students across three universities. The previously validated Davis’s Interpersonal Reactivity Index was used to quantify empathy. The survey also collected information on age, sex, ethnicity, year of medical school training and included a free-text box for ‘any other comments’.ResultsData analysis is currently underway with high response rates. Mean empathy scores by age, sex, year of study and ethnic group are presented. A correlation analysis will examine associations between age and year of study, and mean empathy sores.ConclusionThese data will help to provide a better understanding of empathy levels to inform the provision of future empathy training and medical school curriculum design. Given previous evidence linking experiences of empathy to better health outcomes, the findings may also be significant to future patient care

scholarly journals P083 A rheumatology carousel: three-year results from an open-access teaching workshop designed for core rheumatology assessments for undergraduate medical students

Rheumatology ◽  
2021 ◽  
Vol 60 (Supplement_1) ◽  
Author(s):  
Pritesh Mistry ◽  
James Bateman ◽  
Helen Foss ◽  
Muhamad Jasim
Keyword(s):  
Medical Students ◽  
Open Access ◽  
Clinical Teaching ◽  
Lesson Plan ◽  
Clinical History ◽  
Teaching Staff ◽  
Free Text ◽  
Undergraduate Medical Students ◽  
Core Conditions

Abstract Background/Aims  Medical students need to gain patient contact to develop their skills in history taking and examinations. In year three, undergraduate students typically rotate across various hospitals and specialties and are expected to have dedicated rheumatology exposure for history and examination competencies. Rheumatology as an out-patient specialty can limit opportunities for medical students to have broad exposure to rheumatological conditions. Methods  In January 2018, we designed an annual rheumatology half-day teaching workshop (‘Rheumatology Carousel’) using a combination of lecture-based teaching and small group based guided clinical history and examination stations, aimed at third-year medical students from the University of Birmingham. This covered key presentations in rheumatology: axial spondyloarthropathy, rheumatoid arthritis, systemic sclerosis (connective tissue disease), osteoarthritis, and vasculitis. Each station required a Clinical Teaching Fellow or Rheumatology ST trainee, overseen by one consultant facilitator. We designed patient proforma’s incorporating consent, demographics, key clinical history, therapy, and examination findings. We produced a written patient guide, and consultants invited appropriate patients to volunteer for the day. We designed a one-hour lecture-based tutorial. A lesson plan and schedule were created outlining faculty requirements; including time, roles, and faculty numbers. We invited five to six patients to each session, with a plan of four to five focussed examinations. We designed the carousel to accommodate up to 40 students, split into two groups running over a day. Focussed examinations involved students in groups of four, with each student being a lead examiner in at least one station, each station lasting 20 minutes. Best practice examination techniques for each condition were assessed and emphasised. Following a debrief, we collected feedback from students, faculty, and patients (online and written feedback), using Likert scores for teaching content, and quality of the session delivery. Results  The carousel ran in February 2018, 19, and 20. The sessions were positively evaluated by students, faculty, and patients. In total, 93 students attended, 89/93 completed feedback. Satisfaction scores (mean; SD; range) were high (1-strongly disagree, 5-strongly agree) for content (4.8; 0.49, range 3-5) and quality of delivery (4.7; 0.54; 3-5). All patients who participated volunteered to return for future teaching sessions, with several patients attending all three years. Free text feedback indicated students valued structured exposure to core conditions and called for more sessions of this nature. Conclusion  This sustainable reproducible intervention ensures students have structured exposure to important rheumatological conditions. The methodology allows reproducible sessions that are positively evaluated despite rotating clinical teaching staff. We have made all our teaching materials, logistical plan, and scheduling tools available as open access resources under a Creative Commons license for free re-use and adaptation by any healthcare professional, via a web link. We plan to record an electronic version to distribute post the COVID-19 pandemic. Disclosure  P. Mistry: None. J. Bateman: None. H. Foss: None. M. Jasim: None.

Measuring the Conceptual Variables for E-Services Acceptance

2013 ◽  
pp. 302-309
Author(s):  
Kamaljeet Sandhu
Keyword(s):  
User Experience ◽  
Service System ◽  
Descriptive Data ◽  
Web Based ◽  
Electronic Service ◽  
Insight Into ◽  
The Web ◽  
Service Framework

This case study examines the Web Electronic Service framework for a University in Australia. The department is in the process of developing and implementing a Web-based e-service system. The user experience to use e-services requires insight into the attributes that shape the experience variable. The descriptive data about the attributes that form the experience variable is provided in this study.

scholarly journals A Practical Approach to Clinical Ethics Education for Undergraduate Medical Students: A Case Study From Guatemala

2019 ◽  
Vol 6 ◽  
pp. 238212051986920 ◽  
Author(s):  
María Lorena Aguilera ◽  
Sergio Martínez Siekavizza ◽  
Francis Barchi
Keyword(s):  
Medical Education ◽  
Medical Students ◽  
Ethics Education ◽  
Evidence Base ◽  
Learning Goals ◽  
Student Interest ◽  
Undergraduate Medical Students ◽  
Formal Curriculum ◽  
Critical Reasoning

Objective: This case study describes a faculty initiative to create a curriculum in applied medical ethics for undergraduate medical students at the Universidad Francisco Marroquin (UFM) in Guatemala City, Guatemala. Methods: The new ethics curriculum (PRACTICE) incorporates ethics short-courses into the university’s system of nontraditional, credit-bearing electives offered to students as part of their 6-year undergraduate medical education and complements existing didactic courses in normative ethics. Structured case-based activities allow for flexibility in design and scheduling, do not compete with core requirements of the existing curriculum, and enable students to develop critical reasoning approaches to ethical situations they will encounter in medical practice. Two preliminary workshops provided teaching opportunities for the faculty, stimulated student interest in future ethics courses, and provided an evidence base to guide the development of a formal curriculum. Results: The elective currently includes six 2-hour modules, each of which is a stand-alone unit with learning goals and objectives, brief didactic lecture, assigned readings, discussion case, and assessment. To date, more than 110 students have participated in the workshops and courses. Student feedback and evaluations are being used to refine pedagogical approaches and drive future course content. Conclusions: The PRACTICE course format offers a transformative model for ethics education in Guatemala that can be used in medical education throughout the country and region.

scholarly journals Machine Learning Creates a Simple Endoscopic Classification System that Improves Dysplasia Detection in Barrett’s Oesophagus amongst Non-expert Endoscopists

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Vinay Sehgal ◽  
Avi Rosenfeld ◽  
David G. Graham ◽  
Gideon Lipman ◽  
Raf Bisschops ◽  
...  
Keyword(s):  
Machine Learning ◽  
Medical Students ◽  
Sensitivity And Specificity ◽  
Expert Opinion ◽  
Barrett’S Oesophagus ◽  
Oesophageal Adenocarcinoma ◽  
Undergraduate Medical Students ◽  
Web Based ◽  
Barrett's Oesophagus ◽  
Before And After

Introduction. Barrett’s oesophagus (BE) is a precursor to oesophageal adenocarcinoma (OAC). Endoscopic surveillance is performed to detect dysplasia arising in BE as it is likely to be amenable to curative treatment. At present, there are no guidelines on who should perform surveillance endoscopy in BE. Machine learning (ML) is a branch of artificial intelligence (AI) that generates simple rules, known as decision trees (DTs). We hypothesised that a DT generated from recognised expert endoscopists could be used to improve dysplasia detection in non-expert endoscopists. To our knowledge, ML has never been applied in this manner. Methods. Video recordings were collected from patients with non-dysplastic (ND-BE) and dysplastic Barrett’s oesophagus (D-BE) undergoing high-definition endoscopy with i-Scan enhancement (PENTAX®). A strict protocol was used to record areas of interest after which a corresponding biopsy was taken to confirm the histological diagnosis. In a blinded manner, videos were shown to 3 experts who were asked to interpret them based on their mucosal and microvasculature patterns and presence of nodularity and ulceration as well as overall suspected diagnosis. Data generated were entered into the WEKA package to construct a DT for dysplasia prediction. Non-expert endoscopists (gastroenterology specialist registrars in training with variable experience and undergraduate medical students with no experience) were asked to score these same videos both before and after web-based training using the DT constructed from the expert opinion. Accuracy, sensitivity, and specificity values were calculated before and after training where p<0.05 was statistically significant. Results. Videos from 40 patients were collected including 12 both before and after acetic acid (ACA) application. Experts’ average accuracy for dysplasia prediction was 88%. When experts’ answers were entered into a DT, the resultant decision model had a 92% accuracy with a mean sensitivity and specificity of 97% and 88%, respectively. Addition of ACA did not improve dysplasia detection. Untrained medical students tended to have a high sensitivity but poor specificity as they “overcalled” normal areas. Gastroenterology trainees did the opposite with overall low sensitivity but high specificity. Detection improved significantly and accuracy rose in both groups after formal web-based training although it did it reach the accuracy generated by experts. For trainees, sensitivity rose significantly from 71% to 83% with minimal loss of specificity. Specificity rose sharply in students from 31% to 49% with no loss of sensitivity. Conclusion. ML is able to define rules learnt from expert opinion. These generate a simple algorithm to accurately predict dysplasia. Once taught to non-experts, the algorithm significantly improves their rate of dysplasia detection. This opens the door to standardised training and assessment of competence for those who perform endoscopy in BE. It may shorten the learning curve and might also be used to compare competence of trainees with recognised experts as part of their accreditation process.

scholarly journals Self-Reflected Well-Being via a Smartphone App in Clinical Medical Students: Feasibility Study (Preprint)

2017 ◽  
Author(s):  
Elizabeth K Berryman ◽  
Daniel J Leonard ◽  
Andrew R Gray ◽  
Ralph Pinnock ◽  
Barry Taylor
Keyword(s):  
Medical Students ◽  
Data Collection ◽  
Well Being ◽  
Primary Objective ◽  
The Self ◽  
Smartphone App ◽  
Free Text ◽  
Undergraduate Medical Students ◽  
Negative Experiences ◽  
Before And After

BACKGROUND Well-being in medical students has become an area of concern, with a number of studies reporting high rates of clinical depression, anxiety, burnout, and suicidal ideation in this population. OBJECTIVE The aim of this study was to increase awareness of well-being in medical students by using a smartphone app. The primary objective of this study was to determine the validity and feasibility of the Particip8 app for student self-reflected well-being data collection. METHODS Undergraduate medical students of the Dunedin School of Medicine were recruited into the study. They were asked to self-reflect daily on their well-being and to note what experiences they had encountered during that day. Qualitative data were also collected both before and after the study in the form of focus groups and “free-text” email surveys. All participants consented for the data collected to be anonymously reported to the medical faculty. RESULTS A total of 29 participants (69%, 20/29 female; 31%, 9/29 male; aged 21-30 years) were enrolled, with overall median compliance of 71% at the study day level. The self-reflected well-being scores were associated with both positive and negative experiences described by the participants, with most negative experiences associated with around 20% lower well-being scores for that day; the largest effect being “receiving feedback that was not constructive or helpful,” and the most positive experiences associated with around 20% higher scores for that day. CONCLUSIONS The study of daily data collection via the Particip8 app was found to be feasible, and the self-reflected well-being scores showed validity against participant’s reflections of experiences during that day.

scholarly journals Medical Data Mining Course Development in Postgraduate Medical Education: Web-Based Survey and Case Study (Preprint)

2020 ◽  
Author(s):  
Lin Yang ◽  
Si Zheng ◽  
Xiaowei Xu ◽  
Yueping Sun ◽  
Xuwen Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Medical Education ◽  
Medical Students ◽  
Postgraduate Medical Education ◽  
Medical Data ◽  
Medical Data Mining ◽  
Web Based ◽  
Wide Range ◽  
R Programming

BACKGROUND Medical postgraduates’ demand for data capabilities is growing, as biomedical research becomes more data driven, integrative, and computational. In the context of the application of big data in health and medicine, the integration of data mining skills into postgraduate medical education becomes important. OBJECTIVE This study aimed to demonstrate the design and implementation of a medical data mining course for medical postgraduates with diverse backgrounds in a medical school. METHODS We developed a medical data mining course called “Practical Techniques of Medical Data Mining” for postgraduate medical education and taught the course online at Peking Union Medical College (PUMC). To identify the background knowledge, programming skills, and expectations of targeted learners, we conducted a web-based questionnaire survey. After determining the instructional methods to be used in the course, three technical platforms—Rain Classroom, Tencent Meeting, and WeChat—were chosen for online teaching. A medical data mining platform called Medical Data Mining - R Programming Hub (MedHub) was developed for self-learning, which could support the development and comprehensive testing of data mining algorithms. Finally, we carried out a postcourse survey and a case study to demonstrate that our online course could accommodate a diverse group of medical students with a wide range of academic backgrounds and programming experience. RESULTS In total, 200 postgraduates from 30 disciplines participated in the precourse survey. Based on the analysis of students’ characteristics and expectations, we designed an optimized course structured into nine logical teaching units (one 4-hour unit per week for 9 weeks). The course covered basic knowledge of R programming, machine learning models, clinical data mining, and omics data mining, among other topics, as well as diversified health care analysis scenarios. Finally, this 9-week course was successfully implemented in an online format from May to July in the spring semester of 2020 at PUMC. A total of 6 faculty members and 317 students participated in the course. Postcourse survey data showed that our course was considered to be very practical (83/83, 100% indicated “very positive” or “positive”), and MedHub received the best feedback, both in function (80/83, 96% chose “satisfied”) and teaching effect (80/83, 96% chose “satisfied”). The case study showed that our course was able to fill the gap between student expectations and learning outcomes. CONCLUSIONS We developed content for a data mining course, with online instructional methods to accommodate the diversified characteristics of students. Our optimized course could improve the data mining skills of medical students with a wide range of academic backgrounds and programming experience.

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