OrthoBoard: an orthopaedic app for medical education

Introduction: Use of mobile apps as a pedagogical tool in the medical education has gained popularity as mobile apps have great potentials in perpetuating clinical knowledge and skills. To leverage mobile technology in medical education, we designed a hybrid mobile app based on our undergraduate orthopaedic curriculum. Materials and Methods: The frontend was created using hybrid mobile framework to target both iOS and Android platforms. The backend is powered by Firebase (Google Inc.) to manage authentication and social messaging. The content consisted of basic orthopaedic skills, trauma and resuscitation skills, Islamic input in orthopaedic and information cheatsheets. Results: OrthoBoard is being used by IIUM medical undergraduates as an ancillary source of learning, particularly useful as quick references and visual guides for enhancing orthopaedic knowledge and performing clinical procedures. The social messaging capability built into the app serves as a platform for discussion and exchange of information. This is the first medical app, to our knowledge, that integrates orthopaedic clinical knowledge and practice as well as Islamic input in orthopaedics into teaching and learning with the integration of social messaging as a platform for enhancement of knowledge and practice. Conclusion: Use of mobile apps as pedagogical tool in the medical education will undoubtedly increase in the future. As students and teachers embrace mobile technology in and outside the classroom, better user-centric and subject-specific apps will be required to fulfil the needs. For medical educators, developing mobile apps will possibly be one of the future armamentarium in the delivery of knowledge and skills

How Education Level and Willingness to Learn Affect Older Adults in their use of Mobile Technology in Southwest Idaho

As a person’s age increases, their use of technology decreases (Casado- Muñoz, 2015), which can hinder their access to resources, such as medical care, online products and services, and basic communication. For 90% of American adults, the use of mobile technology is a part of daily life (Pew Research Center, 2014). Previous research shows that if seniors have higher education levels and willingness to learn, they are more likely to use technology (Bailey & Sheehan, 2009). This project will examine how education levels affect a senior’s use of technology, and how their willingness to learn affects their adoption of mobile technology. I will conduct interviews and surveys with 100 individuals, aged 65 years or older; 50 individuals enrolled currently in educational courses and 50 individuals who are not. This research gives a deeper understanding of the factors that influence technology use in seniors, and how to encourage such usage

A Study of the Effects of Mobile Technology Solutions on Effective Deployment of Mobile Learning in Medical Education Based on the Technology Acceptance Model

Background & Objective: Mobile learning, as a new stage of development in e-learning, provides opportunities for information transfer, and strengthening and improving lifelong learning in students of medical sciences. The present study was conducted to evaluate the effect of mobile technology solutions on effective deployment of mobile learning in medical education based on the Technology Acceptance Model (TAM). Methods: This was an objective-based applied research and, based on the method of data collection, a descriptive survey. The statistical population consisted of all faculty members of the Hamadan University of Medical Sciences in 2014. The sample size (n = 188) was determined using Cochran formula. Data were collected using the Mobile Technology Development Strategies Questionnaires and Davis’ TAM. Data analysis was performed using the correlation coefficient, t-test, confirmatory factor analysis, structural equation modeling, and path analysis and LISREL and SPSS software. Results: Instructional strategies, administrative-structural, managerial, and motivational–recreational, respectively, had the most significant effect (at the level of 0.01) on the teachers’ perception of the usefulness of mobile learning and the simplicity of its use. Based on TAM, these two components had positive effects on attitude toward using and deciding to use mobile technology. Thereby, they have significant positive effects on the application of mobile technology in teaching and learning by teachers (at the level of 0.01). Conclusion: Based on these results, TAM was approved according to the guidelines provided on mobile learning development in the study population, and thus, has deployment potential in the target population. Key Words: Mobile technology, Mobile learning, Technology Acceptance Model (TAM), Structural equation, Path analysi

Mobile Learning in Medical Education: Review

In the past several years, mobile learning made rapid inroads into the provision of medical education. There are significant advantages associated with mobile learning. These include high access, low cost, more  situated and contextual learning, convenience for the learner, continuous communication and interaction  between learner and tutor and between learner and other learners, and the ability to self-assess themselves  while learning. Like any other form of medical pedagogy, mobile learning has its downsides. Disadvantages of mobile learning include: inadequate technology, a risk of distraction from learning by using a device that can be used for multiple purposes, and the potential for breakdown in barriers between personal usage of the mobile  device and professional or educational use. Despite these caveats, there is no question but that mobile  learning offers much potential. In the future, it is likely that the strategy of mobile first, whereby providers of e-learning think of the user experience on a mobile first, will result in learners who increasingly expect that all e-learning provision will work seamlessly on a mobile device.KEYWORS: Medical education, mobile learning, technolog

Investigating the Use of M-Health for Learning and Clinical Training by Medical Students in Ghana

There is a challenge with healthcare access in most developing countries. With the high rate of mobile technology penetration in these countries, there is a strong belief that mobile technology can help address this and other health system and education challenges. This study investigated how clinical year medical students in Ghana used m-health and with what outcomes. This was a mixed-methods study to assess what technologies students used, what the impact of use was, what enablers and barriers they encountered, what factors explained m-health adoption and what the attitudes of students, staff and faculty members were towards m-health use. The study was conducted in four out of five medical schools in Ghana with clinical year students, namely, Kwame Nkrumah University of Science and Technology School of Medical Sciences (KNUST-SMS), University of Cape Coast School of Medical Sciences (UCC-SMS), University of Development Studies School of Medicine and Health Sciences (UDS-SMHS) and University of Ghana School of Medicine and Dentistry (UG-SMD). Online and paper questionnaires were distributed to 828 students and 291 questionnaires were returned. Questionnaires from dental students at UG-SMD (n = 5) were excluded from the analysis.Two focus group discussions were held involving seven students while three students, seven faculty members and five staff were interviewed. Qualitative data were analyzed using thematic analysis. Only one student did not own a mobile device. About 78% of students reported using m-health at some point during their medical education. The most popular devices used by students were laptop computers (90.8%), smartphones (66.2%), cellular phones (46.6%) and tablets (44.1%). Over 84% of the students owned Android devices, while 21% owned iPhones and iPads. Majority of students owned three devices or less. Students used mobile technologies in ways that suited their learning needs and contexts. M-health helped students to participate better in lessons and improve their knowledge, skills and efficiency in various contexts. The main drawbacks of m-health use were distraction and time wasting, difficulty in determining credibility of some online information and the risk of using these technologies inappropriately around patients and during assessments. The main facilitating conditions for m-health use were availability, quality and reliability of technological services, technical support, security, price value, technology competence and training, portability, task and goal fit, social influence and organizational factors. Habit and Hedonic Motivation were the only significant factors that explained intention to use m-health and actual m-health use respectively in the UTAUT2 model, in the presence of age, gender and experience. Students, staff and faculty members were open to using m-health in teaching and learning, although they recommended regulation of use through policies and guidelines to ensure effective teaching and learning and ethical m-health use. Considering the benefits offered by m-health, the study encourages medical schools in Ghana to explore mobile learning with the possibility of incorporating it into their curricula. This should be accompanied by development of policies and guidelines to spell out how mobile technologies should be used in order to mitigate most of the drawbacks identified. This study contributed empirical evidence from the Ghanaian context regarding m-health adoption and use in medical education. This evidence will contribute to theory regarding benefits, drawbacks, facilitating conditions and factors that influence m-health adoption among medical students in a developing country context. Understanding how medical students use mobile technology in learning will be useful in planning how m-health can be incorporated into their curricula. It will also help in informing development and deployment of m-health in healthcare in contexts similar to Ghana

A Survey of Mobile Technology Usage and Desires by Caregivers of Children with Cancer

Background The use of mobile health (mHealth) has grown exponentially, even by caregivers of vulnerable populations. The study objective was to understand mobile technology usage, barriers, and desires by caregivers of children with cancer. Procedure Paper surveys were mailed to caregivers of children diagnosed with cancer at Riley Hospital for Children between June 2015 and June 2017. The survey contained 13 questions, both fixed and open‐ended, and was sent in both English and Spanish up to three times. Results Respondents (n = 121) were primarily parents (93.2%), median age was 40.7 years (range 23–63), and most were white, non‐Hispanic (74.4%). The majority made under $100,000 annual household income (72.9%) and had an education of at least some college or greater (74.5%). Nearly all owned a smart phone (99.2%) and most (61.2%) owned a tablet. Among operating systems, the majority used iOS (62.8%), while 49.6% used Android. About a third (37.1%) reported no barriers to mobile technology use, but 22.4% experienced “data limitations.” Overall, 86.2% wanted at least one medical management website/app: medical knowledge (61.2%), symptom tracking/management (49.1%), and medication reminders (44.8%). Further, 62.1% wanted access to child's medical record and 58.6% wanted communication with medical providers. Lower education was significantly associated with experiencing phone/plan barriers (P = 0.008). Conclusion The majority of caregivers of children with cancer use mobile technology with minimal barriers; future research should focus on designing an mHealth tool to address the medical management needs by caregivers of children with cancer

Use of mobile learning technology among final year medical students in Kenya

Introduction: Mobile phone penetration has increased exponentially over the last decade as has its application in nearly all spheres of life including health and medical education. This study aimed at assessing the use of mobile learning technology and its challenges among final year undergraduate students in the College of Health sciences, University of Nairobi. Methods: This was a cross-sectional descriptive study conducted among final year undergraduate students at the University of Nairobi, College of Health Sciences. Self-administered, anonymous questionnaires were issued to all final year students in their lecture rooms after obtaining informed consent. Data on demographics, mobile device ownership and mobile learning technology use and its challenges was collected. Data entry and analysis was done using SPSS®. Chi-square and t-test were used for bivariate analysis. Results: We had 292 respondents; 62% were medical students, 16% were nursing students, 13% were pharmacy students and 9% were dental surgery students. The majority were female (59%) and the average age was 24 years. Eighty eight percent (88%) of the respondents owned a smart device and nearly all of them used it for learning. 64% of the respondents used medical mobile applications. The main challenges were lack of a smart device, lack of technical know-how in accessing or using apps, sub-optimal internet access, cost of acquiring apps and limited device memory. Conclusion: Mobile learning is increasingly popular among medical students and should be leveraged in promoting access and quality of medical education.Pan African Medical Journal 2015; 2

Do Mobile Addicts have Poor Sleep Quality?

Background: The dawn of technology in form of smartphones has brought about an epidemic but in addition to the beneficial use of mobile phone its causing the sleep loss and disturbance in the circadian rhythms of the body.  Objective: The objective of this study is to determine the association between the mobile phone addiction with sleep quality among medical students as this association can have long-term consequences on the life of the students.  Materials and methods: It was a descriptive study conducted on students of  Wah Medical College. The questionnaires comprising of three parts: the demographic profile, the Pittsburgh sleep quality index for sleep quality and Mobile Phone Use Scale for mobile phone addiction were distributed among all the students after informed consent. The data was analyzed using SPSS version 21. Chi-square test was applied to find the association between Mobile Phone addiction and Sleep quality at α-value of 0.05.  Results: The sleep quality index score showed that 130(38.6%) students had a good quality of sleep and 162(48.1%) were addicted to mobile phone use. A significant association was found between mobile phone addiction and sleep quality among medical students with a p-value of 0.001. Conclusion: Mobile phone addiction is an important health problem in our medical college and because of this addiction there is poor sleep quality among the students. Health education sessions on a frequent basis should be conducted for all to disseminate the adverse effects of addictive mobile use

Mobile learning devices in the workplace: 'as much a part of the junior doctors' kit as a stethoscope'?

Background Smartphones are ubiquitous and commonly used as a learning and information resource. They have potential to revolutionize medical education and medical practice. The iDoc project provides a medical textbook smartphone app to newly-qualified doctors working in Wales. The project was designed to assist doctors in their transition from medical school to workplace, a period associated with high levels of cognitive demand and stress. Methods Newly qualified doctors submitted case reports (n = 293) which detail specific instances of how the textbook app was used. Case reports were submitted via a structured online form (using Bristol Online Surveys - BOS) which gave participants headings to elicit a description of: the setting/context; the problem/issue addressed; what happened; any obstacles involved; and their reflections on the event. Case reports were categorised by the purpose of use, and by elements of the quality improvement framework (IoM 2001). They were then analysed thematically to identify challenges of use. Results Analysis of the case reports revealed how smartphones are a viable tool to address clinical questions and support mobile learning. They contribute to novice doctors’ provision of safe, effective, timely, efficient and patient-centred care. The case reports also revealed considerable challenges for doctors using mobile technology within the workplace. Participants reported concern that using a mobile phone in front of patients and staff might appear unprofessional. Conclusion Mobile phones blur boundaries between the public and private, and the personal and professional. In contrast to using a mobile as a communication device, using a smartphone as an information resource in the workplace requires different rituals. Uncertain etiquette of mobile use may reduce the capacity of smartphone technology to improve the learning experience of newly qualified doctors

Introducing a mobile learning model in medical education during COVID-19; a critical review

Introduction: Mobile learning is one of the innovative teaching techniques that help medical students gain knowledge and skills. One of the factors that expanded the use of this strategy was the COVID-19 pandemic. However, the educational pedagogy of such technology has been neglected. This article aimed to critically review available mobile learning models in medical education to suggest a comprehensive model in the field of mobile learning.Methods: We conducted this critical review based on the five steps of the Carnwell and Daly method. For a comprehensive systematic search from 2000 to April 2021, the following keywords were used: Personal Digital Assistant, m learning, Mobile learning, Ubiquitous learning, U learning, medical students, and medical education. 3176 studies in PubMed, Scopus, ERIC, Magiran, and Web of Science were identified. In total, 8 articles entered the study.Results: Eight models of mobile learning in medical education were identified. The key features of each model were extracted and integrated into the new model for the successful design and implementation of mobile learning. This model includes three main elements of mobile learning: 1-stakeholders, 2-interaction, and 3-technology, which are influenced by external factors including Mobiquette, legitimacy, and awareness.Conclusion: The results of this study are an important contribution to the knowledge collection in mobile learning inmedical education. We introduced a comprehensive model of mobile learning including specific characteristics of strategies in the context of medical education