Journal of Medical Internet Research
The leading peer-reviewed journal for digital medicine and health and health care in the internet age
Editor-in-Chief: Gunther Eysenbach, MD, MPH, FACMI, Founding Editor and Publisher; Adjunct Professor, School of Health Information Science, University of Victoria (Canada) Rita Kukafka, DrPH, MA, FACMI, Professor, Biomedical Informatics and Sociomedical Sciences; Director, Laboratory for Precision Prevention, Columbia University, NY
Impact Factor 5.03
Gunther Eysenbach, MD, MPH, FACMI, Founding Editor and Publisher; Adjunct Professor, School of Health Information Science, University of Victoria (Canada)
Rita Kukafka, DrPH, MA, FACMI, Professor, Biomedical Informatics and Sociomedical Sciences; Director, Laboratory for Precision Prevention, Columbia University, NY
The Journal of Medical Internet Research (JMIR) (founded in 1999, now in its' 22nd year!), is the pioneer open access eHealth journal and is the flagship journal of JMIR Publications. It is the leading digital health journal globally in terms of quality/visibility (Impact Factor 2019: 5.03), ranking Q1 in the medical informatics category, and is also the largest journal in the field. The journal focuses on emerging technologies, medical devices, apps, engineering, telehealth and informatics applications for patient education, prevention, population health and clinical care. As a leading high-impact journal in its disciplines (health informatics and health services research), it is selective, but it is now complemented by almost 30 specialty JMIR sister journals, which have a broader scope, and which together receive over 6.000 submissions a year. Peer-review reports are portable across JMIR journals and papers can be transferred, so authors save time by not having to resubmit a paper to different journal but can simply transfer it between journals.
As an open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as with all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).
We are also a leader in participatory and open science approaches, and offer the option to publish new submissions immediately as preprints, which receive DOIs for immediate citation (eg, in grant proposals), and for open peer-review purposes. We also invite patients to participate (eg, as peer-reviewers) and have patient representatives on editorial boards.
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By applying advanced health information technology to the health care field, health informatization helps optimize health resource allocation, improve health care services, and realize universal health coverage. COVID-19 has tested the status quo of China’s health informatization, revealing challenges to the health care system. This viewpoint evaluates the development, status quo, and practice of China’s health informatization, especially during COVID-19, and makes recommendations to address the health informatization challenges. We collected, assessed, and evaluated data on the development of China’s health informatization from five perspectives—health information infrastructure, information technology (IT) applications, financial and intellectual investment, health resource allocation, and standard system—and discussed the status quo of the internet plus health care service pattern during COVID-19. The main data sources included China’s policy documents and national plans on health informatization, commercial and public welfare sources and websites, public reports, institutional reports, and academic papers. In particular, we extracted data from the 2019 National Health Informatization Survey released by the National Health Commission in China. We found that China developed its health information infrastructure and IT applications, made significant financial and intellectual informatization investments, and improved health resource allocations. Tested during COVID-19, China’s current health informatization system, especially the internet plus health care system, has played a crucial role in monitoring and controlling the pandemic and allocating medical resources. However, an uneven distribution of health resources and insufficient financial and intellectual investment continue to challenge China’s health informatization. China’s rapid development of health informatization played a crucial role during COVID-19, providing a reference point for global pandemic prevention and control. To further promote health informatization, China’s health informatization needs to strengthen top-level design, increase investment and training, upgrade the health infrastructure and IT applications, and improve internet plus health care services.
The COVID-19 pandemic has highlighted the importance of rapid dissemination of scientific and medical discoveries. Current platforms available for the distribution of scientific and clinical research data and information include preprint repositories and traditional peer-reviewed journals. In recent times, social media has emerged as a helpful platform to share scientific and medical discoveries.
Lying on the floor for a long period of time has been described as a critical determinant of prognosis following a fall. In addition to fall-related injuries due to the trauma itself, prolonged immobilization on the floor results in a wide range of comorbidities and may double the risk of death in elderly. Thus, reducing the length of Time On the Ground (TOG) in fallers seems crucial in vulnerable individuals with cognitive disorders who cannot get up independently.
In China, significant emphasis and investment in health care reform since 2009 has brought with it increasing scrutiny of its public hospitals. Calls for greater accountability in the quality of hospital care have led to increasing attention toward performance measurement and the development of hospital ratings. Despite such interest, there has yet to be a comprehensive analysis of what performance information is publicly available to understand the performance of hospitals in China.
Body image and eating disorders represent a significant public health concern; however, many affected individuals never access appropriate treatment. Conversational agents or chatbots reflect a unique opportunity to target those affected online by providing psychoeducation and coping skills, thus filling the gap in service provision.
Compared with White Americans, Black Americans have higher colon cancer mortality rates but lower up-to-date screening rates. Chadwick Boseman was a prominent Black American actor who died of colon cancer on August 28, 2020. As announcements of celebrity diagnoses often result in increased awareness, Boseman’s death may have resulted in greater interest in colon cancer on the internet, particularly among Black Americans.
Chronic diseases often present severe consequences for those affected. The management and treatment of chronic diseases largely depend on patients’ lifestyle choices and how they cope with the disease in their everyday lives. Accordingly, the ability of patients to self-manage diseases is a highly relevant topic. In relation to self-management, studies refer to patient empowerment as strengthening patients’ voices and enabling them to assert control over their health and treatment. Mobile health (mHealth) provides cost-efficient means to support self-management and foster empowerment.
Missing data are common in mobile health (mHealth) research. There has been little systematic investigation of how missingness is handled statistically in mHealth randomized controlled trials (RCTs). Although some missing data patterns (ie, missing at random [MAR]) may be adequately addressed using modern missing data methods such as multiple imputation and maximum likelihood techniques, these methods do not address bias when data are missing not at random (MNAR). It is typically not possible to determine whether the missing data are MAR. However, higher attrition in active (ie, intervention) versus passive (ie, waitlist or no treatment) conditions in mHealth RCTs raise a strong likelihood of MNAR, such as if active participants who benefit less from the intervention are more likely to drop out.
Phenotypes characterize the clinical manifestations of diseases and provide important information for diagnosis. Therefore, the construction of phenotype knowledge graphs for diseases is valuable to the development of artificial intelligence in medicine. However, phenotype knowledge graphs in current knowledge bases such as WikiData and DBpedia are coarse-grained knowledge graphs because they only consider the core concepts of phenotypes while neglecting the details (attributes) associated with these phenotypes.
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