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Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.
JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, Scopus, and Science Citation Index Expanded (SCIE), and in June 2018 received an Impact Factor of 4.541, which ranks the journal #2 (behind JMIR) out of 25 journals in the medical informatics category indexed by the Science Citation Index Expanded (SCIE) by Thomson Reuters/Clarivate.
The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics.
JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
JMIR mHealth and uHealth features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.
JMIR mHealth and uHealth adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics.
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Introduction: Mobile augmented reality (MAR) applications offer support for emergency responders in rural areas. We describe the lessons learned from the development process of AR MAPPER, a MAR app th...
Introduction: Mobile augmented reality (MAR) applications offer support for emergency responders in rural areas. We describe the lessons learned from the development process of AR MAPPER, a MAR app that provides emergency responders onsite information about the agricultural operation they enter. Methods: Cross-platform frameworks were used to create AR MAPPER to accommodate budget constraints and overcome issues with markerless MAR technologies. While the single codebase and web technologies streamlined development, cross-device hardware limitations impacted location accuracy, lengthened the development cycle, and required regular updates to third-party libraries. Lessons learned: Developers should consider single platform native development to benefit from platform-specific MAR implementations and to avoid development and testing costs associated with cross-platform implementation. Emergency response organizations may be more likely to utilize a single platform across their devices, reducing the benefit of cross-platform development. Furthermore, providing map-based, non-AR cross-platform applications for landowners, farmers, and ranchers would help improve and maintain data quality.
Background: Technology use is ubiquitous in the digital age, especially in the X, Millennial/Y and Z generations. To ensure quality care, clinicians need skills, knowledge and attitudes that can be me...
Background: Technology use is ubiquitous in the digital age, especially in the X, Millennial/Y and Z generations. To ensure quality care, clinicians need skills, knowledge and attitudes that can be measured. This paper proposes mobile health, smartphone/device and app competencies based on a literature review, expert consensus and recommendations of the Institute of Medicine’s Health Professions Educational Summit. Objective: Outline competencies for mH, SP/D and apps using the Accreditation Council of Graduate Medical Education (ACGME) framework. Methods: Literature is integrated on patient-, learner-, competency- and outcome-based themes from the fields of technology, healthcare, pedagogy and business. Mobile health, smartphone/device and app competencies may be situated within the graduate medical education domains of patient care, medical knowledge, practice based learning and improvement, systems based practice, professionalism, and interpersonal skills and communication. Teaching methods are suggested to align competency outcomes, learning context and evaluation. Results: Health care via mobile health (mH), smartphone/device (SP/D) and apps have enough similarities to in-person and telepsychiatric care that competencies can be placed in milestone domains. Additional competencies are needed since mH includes clinical decision support, device/technology assessment/selection and information flow management across an e-platform. Since care with mH may have asynchronous components – like social media – competencies for trainees and clinicians may help them shift traditional learning, teaching, supervisory and evaluation practices to achieve targeted outcomes. Clinicians have to best assess, triage and treat patients using technology in a much broader context, while maintaining the therapeutic relationship. Curricula with interactive case-, problem- and system-based teaching are suggested for faculty, along with clinical exposure to new technologies and adaptation of systems-based practice. Health systems need to manage change and create a positive e-culture. Conclusions: Research is needed on implementing and evaluating mH competencies, organization change with technology and how a paradigm shift like mobile health re-contextualizes digital healthcare Clinical Trial: Not applicable.
Background: Interventions delivered by mobile phones or other digital devices have the potential to improve outcomes and prevention for people with cardiovascular disease (CVD) by supporting behaviour...
Background: Interventions delivered by mobile phones or other digital devices have the potential to improve outcomes and prevention for people with cardiovascular disease (CVD) by supporting behaviour change towards healthier lifestyle and successful treatment adherence. To allow replication and adaptation of these interventions across settings it is important to fully understand how they have been developed. However, the differing development processes have not been systematically compared. Objective: To systematically describe and compare the development process for text messaging interventions targeting the prevention and management of cardiovascular disease collaborating in the Text2Prevent CVD study group. Methods: We gathered data from the nine trials identified in the Text2PreventCVD meta-analysis describing the intervention development process. Data extraction was guided by frameworks for the development of complex interventions that included the following development stages: intervention planning, design, development, and pretesting. Following systematic data extraction from available publications, we invited authors to contribute by reviewing extracted data and providing additional details not reported in publications. Results: A comprehensive description of the intervention development process was available for five trials. A variety of methodologies were reported for the development of each intervention. Intervention planning involved gathering information from stakeholder consultations, literature reviews, examination of relevant theory, and preliminary qualitative research. Intervention design involved the theories of behaviour change (in some cases to select or develop intervention techniques, or to tailor intervention techniques to recipients), and the use of multiple behaviour change techniques. Intervention development involved i) generating messages content based on clinical guidelines and expert opinions, ii) conducting literature reviews and primary qualitative research to inform decisions about other intervention characteristics (message frequency, timing, directionality, or level of tailoring), and iii) gathering end of user feedback (through structured questionnaires, semi-structured interviews, or focus groups) to examine message readability, intervention acceptability and perceived utility. Intervention pre-testing involved pilot studies with a purposive or convenience sample of 10 to 30 participants receiving messages for a period of one to four weeks. Conclusions: The development process of the text messaging interventions for the prevention and management of CVD identified in this review was complex and comprehensive, requiring numerous studies to obtain evidence to inform decisions about the scope, content, and structure of the interventions. Additional research is needed to examine the potential association between development methods and intervention success, as well as trying to identify "active ingredients" in the development methods. Further work is also needed to establish whether effective messaging systems can be adapted from work already done, or whether this level of development is needed for application in other conditions and settings.
Background: An incentive spirometer (IS) plays a key role in the prevention of post-operative complications, and the appropriate use of an IS is especially well-known for the prevention of respiratory...
Background: An incentive spirometer (IS) plays a key role in the prevention of post-operative complications, and the appropriate use of an IS is especially well-known for the prevention of respiratory complications. However, IS utilization depends on the patient’s engagement, and information and communication technology (ICT) can help in this area. Objective: This study’s aim was to determine the effect of mobile ICT on the usage of an IS [Go-breath] app by post-operative patients after general anesthesia. Methods: Our study recruited a total of 42 patients from April to May 2018 who used the Go-breath app at a single tertiary hospital in South Korea. The patients were randomly classified into either a test or control group. The main function of the Go-breath app was to allow for self-reporting and frequency monitoring of IS use, deep breathing, and active coughing in real-time. The Go-breath app was identical for both the test and control groups, except for the presence of the alarm function. The test group heard an alarm every 60 minutes from 9 am to 9 pm for two days. For the test group only, a dashboard was established in the nurse’s station through which a nurse could rapidly assess the performance of multiple patients. Results: The incentive spirometer index (ISI) in the test group was 20.2 points higher than that in the control group (113.5 points in the test group and 93.2 points in the control group, p=.22). The system usability scale generally showed the same score in the two groups. We observed that the performance rates of IS count, active coughing, and deep breathing were also higher in the test group, but with no statistically significant difference between the groups. For the usefulness “yes or no” question, over 90.0% of patients answered “yes” and wanted more functional options and information. Conclusions: The use of the Go-breath app resulted in considerable differences between the test group and control group, but with no statistically significant differences. Clinical Trial: US National Institutes of Health Clinical Trials Registry : NCT03569332 institutional review board of the study site number : 2018-02-135
Background: When individuals are active self-managers of their own health patient outcomes are improved and the burden to the healthcare system is reduced. There is a need for technology that facilita...
Background: When individuals are active self-managers of their own health patient outcomes are improved and the burden to the healthcare system is reduced. There is a need for technology that facilitates self-management of rheumatoid arthritis (RA) that can reduce the number of patient visits, promptly identify treatment needs, and reduce the costs associated with poor RA management. A smartphone application named LiveWith™ Arthritis has been developed that allows patients with RA to use their smartphone to regularly collect self-management data and to take objective measurements of the impact of RA on their finger joints using optical imaging technology. Objective: The objectives of this pilot study were to 1) gather preliminary data as to whether a smartphone application with hand optical imaging capabilities improves self-management behaviors (self-efficacy in managing symptoms and patient activation), 2) determine if app use shows promise in improving health outcomes (pain, HAQ-II), and 3) determine barriers to use of the smartphone application in adults with RA. Methods: This pilot study used a mixed-method design. The quantitative portion was a traditional two-group experimental design, and the qualitative portion was a follow up telephone interview for intervention participants who did not complete the study. Measures of self management included the PROMIS self efficacy in managing symptoms (P-SEMS) and Patient Activation Measure (PAM). Health outcomes included pain by Visual Analog Scale and disability by Health Assessment Questionnaire II (HAQ-II). Results: The final sample consisted of 21 intervention participants and 15 controls. There was a statistically significant improvement in self-efficacy in managing symptoms (P-SEMS) and promising trends for improvement in PAM, HAQ-II and pain scores for participants who used the app. Of the intervention participants who did not complete the study, n=12 completed the qualitative interview on barriers to use. Qualitative content analysis revealed three themes for barriers to using the app including 1)frustration with technology, 2) RA made the app difficult to use, and 3) I already have a self-management system that works for me. Conclusions: The LiveWith™ Arthritis app shows promise for improving self-management behaviors and health outcomes in adults with RA. Future study with a larger sample size is required to confirm findings. Initial app experience is important for adoption and continual use of the app. Individuals with significant disability to the hand would benefit from voice activated app features. Participants who already have a system of managing their RA may not feel compelled to switch methods, even when a novel optical imagining feature is available.
Background: By 2019, there will be an estimated 4.68-billion mobile phone users globally. Along with this comes an unprecedented proliferation in mobile Apps, a plug and play product positioned to imp...
Background: By 2019, there will be an estimated 4.68-billion mobile phone users globally. Along with this comes an unprecedented proliferation in mobile Apps, a plug and play product positioned to improve lives in innumerable ways. Within this landscape, medical Apps will see a 41% compounded annual growth rate (CAGR) between 2015-2020, but paradoxically, prevailing evidence indicates declining downloads of such Apps and decreasing “stickiness” with the intended end users. Objective: As usability is a prerequisite for success of health and wellness mobile Apps, this paper aims to provide insights and suggestions for improving the mHealth App usability experience, by exploring the degree of alignment between mHealth Insiders and consumers. Methods: A need gap was identified in past mHealth research approaches, where few mixed-methods studies have been performed. A customized mixed-research data synchronization was used to align (i) categorical data from qualitative mHealth insider interviews and (ii) numerical data from a quantitative consumer survey, in order to identify common usability themes and areas of divergence. Results: Of the five usability attributes described in Nielsen’s model, Satisfaction ranked as the top attribute for both mHealth Insiders and consumers. Satisfaction refers to user-likability, comfort and pleasure. Also, five out of nine mHealth Insiders’ top concerns are similar to consumers. On the other hand, consumers did not grade themes such as intuitiveness – deemed vital by mHealth Insiders – as important. Other concerns by the consumers include in-App charging and advertisements. Conclusions: Strengthening the connectivity between suppliers and users (through the designed research tool) will contribute to increased uptake of mHealth Apps. This study supports and has also contributed to the existing pool of mixed-research studies. In addition, this work has generated several ideas (e.g. sustainable business model Apps) and initiated new avenues of inquiry (e.g. dominant category players to lead future development) for future validation. Clinical Trial: No Clinical Trial