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The leading peer-reviewed journal for digital medicine, and health & healthcare in the Internet age
The Journal of Medical Internet Research (JMIR), now in its' 20th year, is the pioneering 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 2016: 5.175, 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 (e.g. in grant proposals), and for open peer-review purposes. We also invite patients to participate, e.g. 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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Background: The past decades depression prevention and early intervention has become a top priority within the Netherlands, however, there is still considerable room for improvement. To this extent, w...
Background: The past decades depression prevention and early intervention has become a top priority within the Netherlands, however, there is still considerable room for improvement. To this extent, web-based complaint-directed mini-interventions (CDMIs) were developed. These brief and low-threshold interventions focus on psychological stress, sleep problems, and worry, because these complaints are highly prevalent, are demonstrably associated with depression and have a substantial economic impact. Objective: Aim of the current economic evaluation is to examine the added value of web-based unguided self-help CDMIs as compared to a wait-listed control group with unrestricted access to usual care both from a societal and healthcare perspective. Methods: This health economic evaluation was embedded in a randomized controlled trial. The study entailed two-arms in which three web-based CMDIs were compared to a no-intervention waiting-list control group (control group received intervention at three months follow-up). Measurements were conducted at baseline, and at three- and six-months follow-up. Primary outcome of the study was response rate on depressive symptomatology as measured by the Inventory of Depressive Symptomatology Self-Report (IDS-SR). Change in quality of life was estimated by calculating effect sizes (Cohens’ d) for individual pre- and post-treatment IDS-SR scores. Incremental cost-effectiveness ratios (ICERs) were calculated using bootstraps (5000 times) of seemingly unrelated regression equations and cost-effectiveness acceptability curves were constructed for the costs per QALY gained. Results: In total, 329 participants were included in the study of which 165 randomized to the CDMI group. At three months follow-up the responder rate was 13.9% in the CDMI group and 7.3% in the control group. Participants in the CDMI group gained 0.15 QALY at three months follow-up compared to baseline, whereas participants in the control group gained 0.03 QALY at three months follow-up. Average total costs per patient during 3 months follow-up were €2,094 for the CDMI group and €2,230 for the control group (excluding baseline costs). Bootstrapped SURE models resulted in a dominant ICER (i.e. less costs and a higher responder rate) for the CDMI group compared to the control group at three months follow-up. The same result was found for the costs per QALY gained. Various sensitivity analyses attested to the robustness of the findings of the main analysis. Conclusions: This study demonstrated that brief and low-threshold web-based unguided self-help CDMIs have the potential to be a cost-effective addition to usual care for adults with mild-to-moderate depressive symptoms. The CDMIs were shown to improve health status while at the same time reduced healthcare costs of participants and hence dominates the care as usual control condition. As intervention costs are relatively low, and Internet is nowadays readily available in the Western world, we believe the CDMIs can be easily implemented on a large scale. Clinical Trial: Netherlands Trial Register (NTR): NTR4612; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4612 (Archived by WebCite at http://www.webcitation.org/6n4PVYddM)
Background: Tinnitus is the perception of a sound without any outside source. It affects 6 million people in the UK. Sound therapy is a core component of many tinnitus management programmes. Potential...
Background: Tinnitus is the perception of a sound without any outside source. It affects 6 million people in the UK. Sound therapy is a core component of many tinnitus management programmes. Potential mechanisms of benefit include making tinnitus less noticeable, habituation, distracting attention from tinnitus, relaxation, and promoting neuroplastic changes within the brain. In recent years there has been a substantial increase in the use of mobile technology. This provided an additional medium via which people with tinnitus can access different tinnitus management options including sound therapy. Objective: The purpose of this study was to: 1) generate the list of apps that people use for management of their tinnitus; 2) explore reasons for apps use and non-use; 3) perform quality assessment of the most cited apps; 4) perform content analysis to explore and describe options and management techniques available in the most cited apps. Methods: An online survey consisting of 33 open and closed questions captured: i) demographic information about respondents, information about tinnitus, hearing loss; ii) mobile apps specific questions asked about the motivation to use an app to manage tinnitus, the apps which respondents used for managing tinnitus, important factors when choosing an app, devices used to access apps, reasons for not using apps. The quality of the most cited apps listed by respondents was assessed using the Mobile Apps Rating Scale (MARS) Content and features of the most cited apps were analysed. Results: Data from 643 respondents were analysed. The majority of respondents (75%) had never used an app for management of tinnitus mainly due to lack of awareness (79%). The list of the 55 apps that people use for the management of their tinnitus was generated. These included apps which were developed specifically for the management of tinnitus, however the majority of cited apps were developed for other problems (e.g. sleep, depression/anxiety, relaxation). Quality assessment of the 18 most popular apps, using MARS resulted in a range of mean scores from 1.6 to 4.2 (out of 5). In line with the current model of tinnitus management, sound was the main focus of the majority of the apps. Other components included relaxation exercises, elements of cognitive behaviour therapy, information and education and hypnosis. Conclusions: People use apps for the management of their tinnitus, however this was done mostly as a self-help option without conjunction with management provided by hearing healthcare professionals. Further research should consider the place for apps in the tinnitus management (standalone self-management intervention vs part of the management by a hearing professional). As the content of the apps varies in respect to sound options, information and management strategies it seems that the choice of the best management app should be guided by individual patient needs and preferences.
Background: The Recovery Record smartphone app is a self-monitoring tool for individuals recovering from an eating disorder. Unlike traditional pen-and-paper meal diaries, which are often used in trad...
Background: The Recovery Record smartphone app is a self-monitoring tool for individuals recovering from an eating disorder. Unlike traditional pen-and-paper meal diaries, which are often used in traditional eating disorder treatment, the app holds novel features, such as meal reminders, affirmations, and patient-clinician in-app linkage allowing for clinicians to continuously monitor patients' app data. Objective: To explore patients' experiences with using Recovery Record as part of eating disorder treatment. Methods: A total of 41 patients from a Danish eating disorder treatment facility were included. All 41 patients were part of participant observations, and 26 were interviewed. Data were generated and analyzed concurrently, applying the inductive methodology of Interpretive Description. Results: The patients' experiences with Recovery Record depended on its app features, the impact of these app features on patients, and patients' specific app usage. This patient-app interaction affected and was affected by changeable contexts making patients' experiences dynamic. Furthermore, the patient-app interaction affected patients' placement of specific Recovery Record app features along a continuum from supportive to obstructive of individual everyday life activities, including the eating disorder treatment. Conclusions: To achieve optimal usage of Recovery Record, we recommend a patient-clinician collaboration including the individual patient's preferences regarding app usage as well as the clinician's professional judgment on the appropriate course of treatment. Thus, ongoing discussions between patients and clinicians are needed in relation to which Recovery Record app features are supportive, when taking patients' individual treatment needs, everyday life activities, and preferences into account. Consequently, the supportive app features may be applied further, while primarily obstructive app features may be avoided.
Background: The Strengthening and Stretching for Rheumatoid Arthritis of the Hand (SARAH) programme is a tailored, progressive 12-week exercise programme for people with hand problems due to rheumatoi...
Background: The Strengthening and Stretching for Rheumatoid Arthritis of the Hand (SARAH) programme is a tailored, progressive 12-week exercise programme for people with hand problems due to rheumatoid arthritis. The programme was shown to be clinically and cost-effective in a large clinical trial and is recommended by the UK National Institute for Health and Care Excellence (NICE) guidelines for rheumatoid arthritis in adults. Objective: We have developed an online version of the SARAH programme (mySARAH) to make the SARAH programme widely accessible to people with rheumatoid arthritis. The purposes of this study were to develop mySARAH and to evaluate and address its usability issues. Methods: We developed mySARAH using a three-step process and gaining feedback from patient contributors. After initial development, mySARAH was tested in two iterative usability cycles in nine participants using a simplified think-aloud protocol and self-reported questionnaires. We also evaluated if participants executed the SARAH exercises correctly after watching the exercise videos included on the website. Results: A preliminary version of mySARAH consisting of six sessions over a 12-week period and delivered via text, exercise videos, images, exercise plan form, exercise diaries, and links to additional information on rheumatoid arthritis was developed. Five participants (1 male; 4 females; median age 64 years) and four participants (four females; median age 64.5 years) took part in the first and second usability testing cycles respectively. Usability issues identified from Cycle 1 such as having a navigation tutorial video and individualised feedback on pain levels were addressed prior to Cycle 2. The need for more instructions to complete the mySARAH patient forms was identified in Cycle 2 and was rectified. Self-reports from both cycles indicated that participants found the programme useful and easy to use and were confident in performing the SARAH exercises themselves. Eight of the nine participants correctly demonstrated all the exercises. Conclusions: mySARAH is the first online hand exercise intervention for people with rheumatoid arthritis. We actively involved target users in the development and usability evaluation and ensured mySARAH met their needs and preferences.
Background: The use of mHealth has gained popularity globally including for use in variety of health interventions, particularly through SMS. However, there are challenges to the use of mHealth, parti...
Background: The use of mHealth has gained popularity globally including for use in variety of health interventions, particularly through SMS. However, there are challenges to the use of mHealth, particularly amongst older users who have a large heterogeneity in usability and accessibility barriers when using technology. In order to better understand and conceptualise the diversity of users and give insight into their particular needs, we turned to persona creation. Personas are user archetypes created through data generated from mixed-methods inquiry with actual target users. Personas are an appropriate yet largely underutilised component of current mHealth research. Methods: Leveraging on data from a mixed methods study conducted in Singapore with an ethnically diverse population including Chinese, Malay and Indian participants, we used a proforma to analyse data from the qualitative component (n=20 in-depth interviews) and quantitative component (n=100 interviewer guided surveys). We then identified key characteristics including technology use and preferences as well as adherence factors to synthesize five personas reflective of persons over the age of 40 years old with atherosclerotic cardiovascular disease (ASCVD) or ASCVD risk factors such as hypertension, in Singapore. Results: We present five personas typologized as 1) The Quiet Analog, 2) The Busy Grandparent, 3) The Socializer, 4) The Newly Diagnosed and 5) The Hard-to-Reach. We report on four key characteristics - health care access, medication adherence, mobile phone technology usage (ownership, access and utilization) and interest in mHealth. Finally, we provide insights into how these personas may be used in the design and implementation of an mHealth intervention. Our work demonstrates how mixed methods data can create biopsychosocial personas which can be used to explore and address the diversity in behaviours, preferences and needs in user groups. Conclusion: With wider adoption of mHealth, it is important that we consider user-centered design techniques, and design thinking in order to create meaningful, patient centered interventions for adherence to medications. Future research in this area should include greater exploration of how these five personas can be used to better understand how and when is best to deliver mHealth interventions in Singapore and beyond.
Background: Electronic health (eHealth) is engrained in the healthcare experience to engage patients across the lifespan. eHealth accessibility and optimization is influenced by lifespan development,...
Background: Electronic health (eHealth) is engrained in the healthcare experience to engage patients across the lifespan. eHealth accessibility and optimization is influenced by lifespan development, as older adults experience greater challenges in accessing and using eHealth compared to their younger counterparts. The eHealth Literacy Scale (eHEALS) is the most popular measure to assess patients’ confidence in locating, understanding, evaluating, and acting upon online health information. Currently, however, it is unknown if eHEALS measurement properties support empirical comparisons across the lifespan. Objective: The purpose of this study was to examine the structure of eHEALS scores and the degree of measurement invariance by age among a sample of United States (US) adults. Methods: A Qualtrics panel (N = 830) completed the online survey. The sample was categorized into younger (18-48) and middle-to-older (49-84) age groups. Multi-group exploratory structural equation modeling was conducted to identify and confirm the number of underlying eHEALS factors. A structural equation modeling approach was also conducted to explore the degree of configural (number of factors and items on each factor), pattern (factor loading equivalence), and unique (item measurement error equivalence) measurement invariance between age groups. In the best-fitted 3-factor model, independent t-tests were conducted to examine age group differences in average responses. Results: Young (18-48 years old; N = 411) and old (49-84 years old; N = 419) adults completed the survey. A 3-factor model had the best fit (RMSEA = .06; CFI = .99; TLI = .98), as compared to the 1-factor, 2-factor, and 4-factor models. These 3-factors included eHealth Information Awareness (2 items), Information Seeking (2 Items), and Information and Evaluation (4 items). Pattern invariance was supported with acceptable model fit (RMSEA = .06; ΔX2 = p > .05; ΔCFI = 0). Compared with younger adults, older adults had less confidence in eHealth resource awareness (p < .001), information seeking skills (p < .01), and ability to evaluate and act upon online health information (p < .001). Conclusions: Evidence for measurement invariance across the lifespan is supported by this study. The eHEALS can be used to uniquely assess, monitor, and evaluate self-efficacy of Internet users’ eHealth information awareness, information seeking skills, and evaluation/action abilities. This finding will allow health researchers and practitioners identify the eHealth deficits experienced by their respondents, so that timely and relevant trainings can be recommended. Future research is needed to extend the number of eHEALS items to capture the social nature of eHealth and to meet gold standard expectations for factor representation (i.e., 3 items).