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Journal of Medical Internet Research
The leading peer-reviewed journal for digital medicine, and health & healthcare in the Internet age
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Journal Description
The Journal of Medical Internet Research (JMIR), now in its 20th 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 2017: 4.671, ranked #1 out of 22 journals) and in terms of size (number of papers published). The journal focuses on emerging technologies, medical devices, apps, engineering, and informatics applications for patient education, prevention, population health and clinical care. As 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. 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 journals.
As open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as 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.
Be a widely cited leader in the digitial health revolution and submit your paper today!
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Latest Submissions Open for Peer-Review:
View All Open Peer Review Articles-
A web-based appearance intervention to promote sleep: Randomized controlled trial
Date Submitted: Oct 14, 2018
Open Peer Review Period: Oct 14, 2018 - Dec 9, 2018
Background: Receiving insufficient sleep has wide-ranging consequences for health and well-being. Although educational programs have been developed to promote sleep, these have had limited success in...
Background: Receiving insufficient sleep has wide-ranging consequences for health and well-being. Although educational programs have been developed to promote sleep, these have had limited success in extending sleep duration. To address this gap, we developed a web-based program emphasizing how physical appearances change with varying amounts of sleep. Objective: The aims of this study were to evaluate: (1) whether participants can detect changes in appearances as a function of sleep, and (2) whether this intervention can alter habitual sleep patterns. Methods: We conducted a 5-week, parallel-group, randomized controlled trial amongst 70 habitual short sleepers (healthy adults who reported having <7 hours of sleep routinely). Upon study enrolment, participants were randomly assigned (1:1) to receive either standard information or an appearance-based intervention. Both groups received educational materials about sleep, but those in the appearance group also viewed a website containing digitally-edited photographs that showed how they would look with varying amounts of sleep. As outcome variables, sleep duration was monitored objectively via actigraphy (at baseline, and at post-intervention weeks 1 and 4), and participants completed a measure of sleep hygiene (at baseline, and at post-intervention weeks 2, 4, and 5). For each outcome, we ran intention-to-treat analyses using linear mixed-effects models. Results: In total, 35 participants were assigned to each group. Validating the intervention, participants in the appearance group: (i) were able to identify what they looked like at baseline, and (ii) judged that they would look more attractive with a longer sleep duration (P < .001). In turn, this translated to changes in sleep hygiene: whereas participants in the appearance group showed improvements following the intervention (P = .003), those in the information group did not (P = .66). Finally, there was no significant effect of group nor interaction of group and time on actigraphy-measured sleep duration (smallest P = .26). Conclusions: Our findings suggest that an appearance-based intervention – while not sufficient as a standalone – could have an adjunctive role in sleep promotion. Clinical Trial: ClinicalTrials.gov NCT02491138
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The Rise of the Empowered Physician in the Digital Health Era
Date Submitted: Oct 13, 2018
Open Peer Review Period: Oct 14, 2018 - Dec 9, 2018
Background: Being 21st century healthcare workers is extremely demanding. The growing number of chronic diseases, lack of medical workforce, increasing amount of administrative tasks and cost of medic...
Background: Being 21st century healthcare workers is extremely demanding. The growing number of chronic diseases, lack of medical workforce, increasing amount of administrative tasks and cost of medical treatment and the rising of life expectancy mean immense challenge on medical professionals. This transformation is triggered by the appearance of digital health. Digital health doesn’t only mean technological transformation but it fundamentally reshapes physician-patient relationship and treatment circumstances. We argue that patient empowerment, the spread of digital health, the bio-psycho-social-digital approach and the disappearance of the ivory tower of medicine lead to a new role for physicians. Main text: Digital health offers the opportunity to make the job of being a medical professional rewarding and creative. The general idol of a physician could shift from self-confident to curious; from rule-follower to creative; and from the lone hero to a team worker. E-physicians are “electronic” they use digital technologies in their practice with ease. They are “enabled" by regulations and guidelines and "empowered" by technologies that support their job and e-patients. They are "experts" of using technologies in their practice or know the best and most reliable and trustworthy sources and technologies. And also “engaged” to understand the feelings and point of view of the patients, giving relevant feedback and involving them throughout the whole healing process. Conclusion: There are major factors that facilitate this transition from demigods to guides who enjoy their job. Examples include meaningful incentives proposed by providers; a well-designed medical curriculum, post-graduate education teaching relevant skills; the wider availability of technologies; useful recommendations from peers; a rising number of evidence-based papers and guidelines; technologies that help save time and effort; and generally, a good experience with e-patients.
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Efficacy of an online self-management enhancing programme for patients with rheumatoid arthritis: an explorative RCT
Date Submitted: Oct 12, 2018
Open Peer Review Period: Oct 14, 2018 - Dec 9, 2018
Background: Online self-management enhancing programmes has the potential to support patients with Rheumatoid Arthritis in their self-management, for example improve their health status and self-effic...
Background: Online self-management enhancing programmes has the potential to support patients with Rheumatoid Arthritis in their self-management, for example improve their health status and self-efficacy or decrease overuse of medication. We developed an online self-management enhancing program in collaboration with RA patients and professionals as co-designers, based on the Intervention Mapping Framework. While self-management programs are complex interventions, it is informative to perform an explorative Randomized Controlled Trial before embarking on a larger trial. Objective: This study aimed to evaluate the efficacy of an online self-management enhancing programme for patients with rheumatoid arthritis and to identify outcome measures most likely to capture potential benefits. Methods: A multicentre exploratory randomised controlled trial was performed with an intervention and a control group. Both groups received care as usual. In addition, the intervention group received 12 months of access to an online self-management programme. Assessment occurred at baseline, 6 and 12 months. Outcome measures included self-management behaviour (PAM-13, SMAS-S), self-efficacy (RASE, PEPPI-5), general health status (RAND-36), focus on fatigue (MPCI-F), perceived pain and fatigue (NRS scales). A linear mixed model for repeated measures, using the intention-to-treat principle, was applied to study differences between the patients in the intervention (n=78) and control (n=79) groups. A sensitivity analysis was performed in the intervention group to study the influence of patients with high (N=30) and low (N=40) use of the intervention. Results: The intervention group scored statistically significantly better on the subscale RAND-36 vitality. The group with high use scored statistically significantly better on the subscale RAND-36 perception, although the effect sizes were small. No other statistically significant or clinically relevant effects were found. Conclusions: Based on these results, it is not possible to conclude on the positive effects of the intervention or to select outcome measures to be regarded as the primary/main or secondary outcomes for a future trial. A process evaluation should be performed to provide more insight into the low compliance with and effectiveness of the intervention. Clinical Trial: The trial is registered in the Dutch Trial Register (ID: NTR4871). URL: http://www.trialregister.nl/trialreg/admin/rctsearch.asp?Term=4871
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Preliminary Flu Outbreak Prediction Using Efficient Twitter Posts Classification and Linear Regression with Historical CDC Reports
Date Submitted: Oct 7, 2018
Open Peer Review Period: Oct 14, 2018 - Dec 9, 2018
Background: Social Networking Sites (SNS) such as Twitter are widely used by diverse demographic populations. The amount of data within SNS has created an efficient resource for real-time analysis. Th...
Background: Social Networking Sites (SNS) such as Twitter are widely used by diverse demographic populations. The amount of data within SNS has created an efficient resource for real-time analysis. Thus, SNS data can be used effectively to track disease outbreaks and provide necessary warnings. Current SNS-based flu detection and prediction frameworks apply conventional machine learning approaches that require lengthy training and testing which is not the optimal solution for new outbreaks with new signs and symptoms. Objective: The objective of this study is to propose an efficient and accurate framework that uses SNS data to track disease outbreaks and provide early warnings, even for newest outbreaks accurately. Methods: We present a framework of outbreak prediction that includes three main modules: text classification, mapping, and linear regression for weekly flu rate predictions. The text classification module utilizes the features of sentiment analysis and predefined keyword occurrences. Various classifiers, including FastText and six conventional machine learning algorithms, are evaluated to identify the most efficient and accurate one for the proposed framework. The text classifiers have been trained and tested using a pre-labeled dataset of flu-related and unrelated Twitter postings. The selected text classifier is then used to classify over 8,400,000 tweet documents. The flu-related documents are then mapped on a weekly basis using a mapping module. Lastly, the mapped results are passed together with historical Center for Disease Control and Prevention (CDC) data to a linear regression module for weekly flu rate predictions. Results: The evaluation of flu tweet classification shows that FastText, together, with the extracted features, has achieved accurate results with an F-measure value of 89.9% in addition to its efficiency. Therefore, FastText has been chosen to be the classification module to work together with the other modules in the proposed framework, including the linear regression module, for flu trend predictions. The prediction results are compared with the available recent data from CDC as the ground truth, and show a strong correlation of 96.29%. Conclusions: The results demonstrate the efficiency and the accuracy of the proposed framework that can be used even for new outbreaks with new signs and symptoms. The classification results demonstrate that the FastText based framework improves the accuracy and the efficiency of flu disease surveillance systems that use unstructured data such as SNS data.
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Telehealth Interventions for Improving Self-Management in Patients with Hemophilia: A Systematic Review of Clinical Studies
Date Submitted: Oct 8, 2018
Open Peer Review Period: Oct 14, 2018 - Dec 9, 2018
Background: The introduction of home therapy for hemophilia has empowered patients and their families to manage the disease more independently. However, the self-management of hemophilia is demanding...
Background: The introduction of home therapy for hemophilia has empowered patients and their families to manage the disease more independently. However, the self-management of hemophilia is demanding and complex. The uses of innovative interventions delivered by telehealth routes, such as social media, web-based and mobile applications, may help to monitor bleeding events and promote the appropriate use of clotting factors among patients with hemophilia. Objective: This review aims to systematically summarize the literature evaluating the effectiveness of telehealth interventions for improving health outcomes in patients with hemophilia, and provides direction for future research. Methods: A search was conducted on Ovid MEDLINE, EMBASE and PubMed for studies that (1) focused on patients with hemophilia A or B; (2) tested the use of remote telehealth interventions via Internet, wireless, satellite, telephone and mobile phone media; (3) and reported on at least one of the following outcomes: quality of life; monitoring of bleeding episodes, joint damage or other measures of functional status; medication adherence; patient knowledge or any other outcomes related to empowering patients to be active decision makers in the emotional, social or medical management of their illness. Reviews, commentaries or case reports comprising 10 or fewer cases, were excluded. Results: Sixteen articles fulfilled the inclusion criteria. The majority of the interventions (n=13) were designed with the primary objective of empowering patients and caregivers to manage their condition and treatment more independently. The components of the interventions were rather homogenous and typically involved electronic (1) logging and reminders for prophylactic infusions; (2) reporting of spontaneous and traumatic bleeding events; (3) monitoring of infusion product usage and home inventory and (4) real-time communication with healthcare professionals and hemophilia clinics. Telemedicine-supported education and information interventions seemed to be particularly effective among adolescent and young adult patients. Although the patients reported improvements in their health-related quality of life and perception of illness, telemonitoring devices did not appear to have a significant effect on quantifiable health outcomes, such as joint health. Longitudinal studies seemed to suggest that the response and compliance rates decreased over time. Conclusions: Preliminary evidence from this review suggests that telehealth-delivered interventions could feasibly improve patients’ adherence to medication use and promote independence in disease management. Given the complexity and resources involved in developing a mature and established system, support from a dedicated network of hemophilia specialists and data managers will be required to maintain the technology, improve compliance and validate the electronic data locally.
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Internet-Based Mindfulness Interventions: A Systematic Literature Review
Date Submitted: Oct 12, 2018
Open Peer Review Period: Oct 14, 2018 - Dec 9, 2018
Background: Internet-based mindfulness interventions are a promising approach to address challenges in the dissemination and implementation of mindfulness interventions across various clinical and non...
Background: Internet-based mindfulness interventions are a promising approach to address challenges in the dissemination and implementation of mindfulness interventions across various clinical and non-clinical conditions. However, evidence regarding the effectiveness of Internet-based mindfulness interventions is inconsistent. In addition, it is unclear which instructional design components of Internet-based mindfulness interventions are associated with intervention effectiveness. Objective: The present manuscript a) examines the effectiveness of Internet-based mindfulness interventions across the various health conditions upon which they are applied; and b) identifies instructional design components associated with intervention effectiveness. Methods: A systematic literature review was conducted in alignment with PICOS criteria, across the databases of PsycINFO, PsycARTICLES, PubMed, and Web of Science. Empirical trials of Internet-based mindfulness interventions based on formal mindfulness practice as the main intervention component were considered. The quality of the studies was assessed in accordance with the risk-bias standards defined by the Cochrane Back Review Group. The studies were further evaluated in terms of intervention effectiveness, and adherence and acceptance. Relevant instructional design components of the interventions were identified based on the 4-Component/Instructional Design Model (4C/ID). Results: Eighteen studies qualified for the systematic literature review. Fifteen studies were of high quality, three of moderate quality. Ten studies reported treatment effectiveness on symptoms of depression and anxiety, with large effect sizes for clinical populations (d ≥ 0.8), and effects persisting over weeks or even months. Seven studies assessed perceived stress, with mixed results for treatment effectiveness. Three studies focused on life satisfaction, two of which found improvements for individuals with pre-clinical symptoms of anxiety, depression, or chronic pain, with varying effect sizes. Eight studies focused on mindfulness as an outcome measure and reported increases of small to moderate effect sizes for six of these studies (0.2 ≤ d ≤ 0.8). Eight studies focused on physical health, two of which found decreases in heart rate, two found improvements in exercise capacity and blood pressure, two found improvements in vitality, and two improvements in coping mechanisms for pain patients, with varying effect sizes. With regard to instructional design, the most effective Internet-based mindfulness interventions employed a combination of formal learning tasks (i.e. formal mindfulness exercises), supportive information (i.e. psycho-educative components and reflection exercises), and part-task practice (i.e. informal mindfulness exercises), and were implemented for approximately six to eight weeks. The least effective interventions were shorter interventions containing only formal mindfulness exercises, but no supportive information or part-task practice. Conclusions: The most effective Internet-based mindfulness interventions are aimed at psychological symptoms, are implemented for six to eight weeks, contain formal meditation exercises in combination with informal exercises, and provide supportive information - typically represented by psycho-education and reflection exercises.
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