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JMIR's Thomson Reuter Impact Factor of 5.175 for 2016

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 pioneering open access eHealth journal, and is the flagship journal of JMIR Publications. It is the leading digital health journal, 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 joined by almost 30 specialty JMIR sister journals, which have a broader scope (peer-review reports are portable across JMIR journals). 

As open access journal we are read by clinicians 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).

Be a widely cited leader in the digitial health revolution and submit your paper today!

 

Recent Articles:

  • Source: Unsplash; Copyright: Ali Inay; URL: https://unsplash.com/photos/y3aP9oo9Pjc; License: Public Domain (CC0).

    Users, Uses, and Effects of Social Media in Dietetic Practice: Scoping Review of the Quantitative and Qualitative Evidence

    Abstract:

    Background: Social media platforms are increasingly used by registered dietitians (RDs) to improve knowledge translation and exchange in nutrition. However, a thorough understanding of social media in dietetic practice is lacking. Objective: The objective of this study was to map and summarize the evidence about the users, uses, and effects of social media in dietetic practice to identify gaps in the literature and inform future research by using a scoping review methodology. Methods: Stages for conducting the scoping review included the following: (1) identifying the research question; (2) identifying relevant studies through a comprehensive multidatabase and gray literature search strategy; (3) selecting eligible studies; (4) charting the data; and (5) collating, summarizing, and reporting results for dissemination. Finally, knowledge users (RDs working for dietetic professional associations and public health organizations) were involved in each review stage to generate practical findings. Results: Of the 47 included studies, 34 were intervention studies, 4 were descriptive studies, 2 were content analysis studies, and 7 were expert opinion papers in dietetic practice. Discussion forums were the most frequent social media platform evaluated (n=19), followed by blogs (n=13) and social networking sites (n=10). Most studies targeted overweight and obese or healthy users, with adult populations being most studied. Social media platforms were used to deliver content as part of larger multiple component interventions for weight management. Among intervention studies using a control group with no exposition to social media, we identified positive, neutral, and mixed effects of social media for outcomes related to users’ health behaviors and status (eg, dietary intakes and body weight), participation rates, and professional knowledge. Factors associated with the characteristics of the specific social media, such as ease of use, a design for quick access to desired information, and concurrent reminders of use, were perceived as the main facilitators to the use of social media in dietetic practice, followed to a lesser extent by interactions with an RD and social support from fellow users. Barriers to social media use were mostly related to complicated access to the site and time issues. Conclusions: Research on social media in dietetic practice is at its infancy, but it is growing fast. So far, this field of research has targeted few social media platforms, most of which were assessed in multiple-component interventions for weight management among overweight or obese adults. Trials isolating the effects and mechanisms of action of specific social media platforms are needed to draw conclusions regarding the effectiveness of those tools to support dietetic practice. Future studies should address barriers and facilitators related to the use of social media written by RDs and should explore how to make these tools useful for RDs to reach health consumers to improve health through diet.

  • Source: Flickr; Copyright: United States Government; URL: https://www.flickr.com/photos/usnavy/5964973510; License: Public Domain (CC0).

    Ecuadorian Cancer Patients’ Preference for Information and Communication Technologies: Cross-Sectional Study

    Abstract:

    Background: The instantaneous spread of information, low costs, and broad availability of information and communication technologies (ICTs) make them an attractive platform for managing care, patient communication, and medical interventions in cancer treatment. There is little information available in Latin America about the level of usage of ICTs for and by cancer patients. Our study attempts to fill this gap. Objective: The aim of this study was to assess the level of ICT use and patterns of preferences among cancer patients. Methods: We conducted an anonymous cross-sectional survey study in 500 Ecuadorian cancer patients. This questionnaire consisted of 22 items about demographic and clinical data, together with the preferences of people who use ICTs. Chi-square, crude, and adjusted logistic regressions were performed. Results: Of the total, 43.2% (216/500) of participants reported that they had access to the Internet, and 25.4% (127/500) reported that they neither owned a cell phone nor did they have access to the Internet. The Internet constituted the highest usage rate as a source of information about malignant diseases (74.3%, 162/218) regardless of age (P<.001). With regard to the preferences on how patients would like to use ICTs to receive information about diseases, WhatsApp (66.5%, 145/218) and short message service (SMS) text messaging (61.0%, 133/218) were widely reported as interesting communication channels. Similarly, WhatsApp (72.0%, 157/218) followed by SMS (63.8%, 139/218) were reported as the preferred ICTs through which patients would like to ask physicians about diseases. Adjusted regression analysis showed that patients aged between 40 and 64 years were more likely to be interested in receiving information through SMS (odds ratio, OR 5.09, 95% CI 1.92-13.32), as well as for asking questions to physicians through this same media (OR 9.78, CI 3.45-27.67) than the oldest group. Conclusions: WhatsApp, SMS, and email are effective and widely used ICTs that can promote communication between cancer patients and physicians. According to age range, new ICTs such as Facebook are still emerging. Future studies should investigate how to develop and promote ICT-based resources more effectively to engage the outcomes of cancer patients. The widespread use of ICTs narrows the gap between cancer patients with restricted socioeconomic conditions and those with wealth and easily available technological means, thereby opening up new possibilities in low-income countries.

  • Picture of a person sitting with a laptop and a light lunch. Source: iStockphoto; Copyright: royalty free - image bought from website; URL: https://www.istockphoto.com/gb/photo/light-meal-at-work-gm465139161-33193556; License: Fair use/fair dealings.

    Digital Health Interventions for Adults With Type 2 Diabetes: Qualitative Study of Patient Perspectives on Diabetes Self-Management Education and Support

    Abstract:

    Background: The prevalence of type 2 diabetes is increasing globally, and health services in many countries are struggling with the morbidity, mortality, and costs associated with the complications of this long-term condition. Diabetes self-management education (DSME) and behavioral support can reduce the risks of developing diabetes-related complications and improve glycemic control. However, their uptake is low. Digital health interventions (DHI) can provide sustained support and may overcome challenges associated with attending diabetes self-management sessions. They have the potential for delivery at multiple locations at convenient times, anonymity, and presentation of content in attractive and tailored formats. This study investigates the needs and wants of patients with type 2 diabetes to inform the development of digital self-management education and support. Objective: The objective of this study was to explore patient perspectives on unmet needs for self-management and support and the role of DHI in adults living with type 2 diabetes. Methods: This study used a qualitative approach based on data generated from 4 focus groups with 20 patients. Results: The data generated by the focus groups illustrated the significant burden that the diagnosis of diabetes places on many patients and the negative impacts on their emotional well-being, work, social life, and physical health. Although patients’ experiences of the health care services varied, there was agreement that even the best services were unable to meet all users’ needs to support the emotional regulation, psychological adjustment, and behavioral changes needed for successful self-management. Conclusions: By focusing on medical management and information provision, existing health care services and education programs may not be adequately meeting all the needs of patients with type 2 diabetes. DHIs have the potential to improve access to DSME and behavioral support and extend the range of content offered by health services to fit with a wider range of patient needs. Features that could help DHIs address some of the unmet needs described by participants in this study included placing an emphasis on emotional and role management, being available at all times, having up-to-date evidence-based guidance for patients, and providing access to peer-generated and professional advice.

  • Source: Pixabay; Copyright: 350543; URL: https://pixabay.com/en/laptop-woman-coffee-breakfast-943558/; License: Public Domain (CC0).

    Attitudes Toward e-Mental Health Services in a Community Sample of Adults: Online Survey

    Abstract:

    Background: Despite evidence that e-mental health services are effective, consumer preferences still appear to be in favor of face-to-face services. However, the theory of planned behavior (TPB) suggests that cognitive intentions are more proximal to behavior and thus may have a more direct influence on service use. Investigating individual characteristics that influence both preferences and intentions to use e-mental health services is important for better understanding factors that might impede or facilitate the use of these services. Objective: This study explores predictors of preferences and intentions to access e-mental health services relative to face-to-face services. Five domains were investigated (demographics, technology factors, personality, psychopathology, and beliefs), identified from previous studies and informed by the Internet interventions model. We expected that more participants would report intentions to use e-mental health services relative to reported preferences for this type of support and that these 5 domains would be significantly associated with both intentions and preferences toward online services. Methods: A mixed sample of 308 community members and university students was recruited through social media and the host institution in Australia. Ages ranged between 17 and 68 years, and 82.5% (254/308) were female. Respondents completed an online survey. Chi-square analysis and t tests were used to explore group differences, and logistic regression models were employed to explore factors predicting preferences and intentions. Results: Most respondents (85.7%, 264/308) preferred face-to-face services over e-mental health services. Relative to preferences, a larger proportion of respondents (39.6%, 122/308) endorsed intentions to use e-mental health services if experiencing mental health difficulties in the future. In terms of the 5 predictor domains, 95% CIs of odds ratios (OR) derived from bootstrapped standard errors suggested that prior experience with online services significantly predicted intentions to use self-help (95% CI 2.08-16.24) and therapist-assisted (95% CI 1.71-11.90) online services in future. Being older predicted increased intentions to use therapist-assisted online services in future (95% CI 1.01-1.06), as did more confidence using computers and the Internet (95% CI 1.06-2.69). Technology confidence was also found to predict greater preference for online services versus face-to-face options (95% CI 1.24-4.82), whereas higher doctor-related locus of control, or LOC (95% CI 0.76-0.95), and extraversion (95% CI 0.88-1.00) were predictive of lower likelihood of preferring online services relative to face-to-face services. Conclusions: Despite generally low reported preferences toward e-mental health services, intentions to access these services are higher, raising the question of how to best encourage translation of intentions into behavior (ie, actual use of programs). Strategies designed to ease people into new Internet-based mental health programs (to enhance confidence and familiarity) may be important for increasing the likelihood that they will return to such programs later.

  • Home page in desktop and mobile versions with an user (montage). Source: The Authors / Placeit.net; Copyright: The Authors; URL: http://www.jmir.org/2018/2/e57/; License: Licensed by the authors.

    Web-Based Alcohol, Smoking, and Substance Involvement Screening Test Results for the General Spanish Population: Cross-Sectional Study

    Abstract:

    Background: Information technology in health sciences could be a screening tool of great potential and has been shown to be effective in identifying single-drug users at risk. Although there are many published tests for single-drug screening, there is a gap for concomitant drug use screening in general population. The ASSIST (Alcohol, Smoking and Substance Involvement Screening Test) website was launched on February 2015 in Madrid, Spain, as a tool to identify those at risk. Objective: The aim of this study was to describe the use of a tool and to analyze profiles of drug users, their consumption patterns, and associated factors. Methods: Government- and press-released launching of a Spanish-validated ASSIST test from the World Health Organization (WHO) was used for voluntary Web-based screening of people with drug-related problems. The tests completed in the first 6 months were analyzed . Results: A total of 1657 visitors of the 15,867 visits (1657/15,867, 10.44%) completed the whole Web-based screening over a 6-month period. The users had an average age of 37.4 years, and 78.87% (1307/1657) screened positive for at least one of the 9 drugs tested. The drugs with higher prevalence were tobacco (840/1657, 50.69%), alcohol (437/1657, 26.37%), cannabis (361/1657, 21.79%), and sedatives or hypnotics (192/1657, 11.59%). Polyconsumption or concomitant drug use was stated by 31.80% (527/1657) of the users. Male respondents had a higher risk of having alcohol problems (odds ratio, OR 1.55, 95% CI 1.18-2.04; P=.002) and double the risk for cannabis problems (OR 2.07, 95% CI 1.46-2.92; P<.001). Growing age increased by 3 times the risk of developing alcohol problems for people aged between 45 and 65 years (OR 3.01, 95% CI 1.89-4.79; P<.001). Conclusions: A Web-based screening test could be useful to detect people at risk. The drug-related problem rates detected by the study are consistent with the current literature. This tool could be useful for users, who use information technology on a daily basis, not seeking medical attention.

  • Seeking health information online. Source: iStock by Getty Images; Copyright: AJ Watt; URL: https://www.istockphoto.com/ca/photo/its-so-easy-once-you-get-the-hang-of-it-gm467221074-60893676; License: Licensed by the authors.

    Implementation of Digital Awareness Strategies to Engage Patients and Providers in a Lung Cancer Screening Program: Retrospective Study

    Abstract:

    Background: Lung cancer is the leading cause of cancer-related deaths in the United States. Despite mandated insurance coverage for eligible patients, lung cancer screening rates remain low. Digital platforms, including social media, provide a potentially valuable tool to enhance health promotion and patient engagement related to lung cancer screening (LCS). Objective: The aim was to assess the effectiveness of LCS digital awareness campaigns on utilization of low-dose computed tomography (LDCT) and visits to institutional online educational content. Methods: A pay-per-click campaign utilizing Google and Facebook targeted adults aged 55 years and older and caregivers aged 18 years and older (eg, spouses, adult children) with LCS content during a 20-week intervention period from May to September 2016. A concurrent pay-per-click campaign using LinkedIn and Twitter targeted health care providers with LCS content. Geographic target radius was within 60 miles of an academic medical center. Social media data included aggregate demographics and click-through rates (CTRs). Primary outcome measures were visits to institutional Web pages and scheduled LDCT exams. Study period was 20 weeks before, during, and after the digital awareness campaigns. Results: Weekly visits to the institutional LCS Web pages were significantly higher during the digital awareness campaigns compared to the 20-week period prior to implementation (mean 823.9, SD 905.8 vs mean 51, SD 22.3, P=.001). The patient digital awareness campaign surpassed industry standard CTRs on Google (5.85%, 1108/18,955 vs 1.8%) and Facebook (2.59%, 47,750/1,846,070 vs 0.8%). The provider digital awareness campaign surpassed industry standard CTR on LinkedIn (1.1%, 630/57,079 vs 0.3%) but not Twitter (0.19%, 1139/587,133 vs 0.25%). Mean scheduled LDCT exam volumes per week before, during, and after the digital awareness campaigns were 17.4 (SD 7.5), 20.4 (SD 5.4), and 26.2 (SD 6.4), respectively, with the difference between the mean number of scheduled exams after the digital awareness campaigns and the number of exams scheduled before and after the digital awareness campaigns being statistically significant (P<.001). Conclusions: Implementation of the LCS digital awareness campaigns was associated with increased visits to institutional educational Web pages and scheduled LDCT exams. Digital platforms are an important tool to enhance health promotion activities and engagement with patients and providers.

  • Village doctor in rural China. Source: Chinese Medial News; Copyright: Michael Woodhead; URL: http://www.chinesemedicalnews.com/2014/07/; License: Fair use/fair dealings.

    Web-Based Just-in-Time Information and Feedback on Antibiotic Use for Village Doctors in Rural Anhui, China: Randomized Controlled Trial

    Abstract:

    Background: Excessive use of antibiotics is very common worldwide, especially in rural China; various measures that have been used in curbing the problem have shown only marginal effects. Objective: The objective of this study was to test an innovative intervention that provided just-in-time information and feedback (JITIF) to village doctors on care of common infectious diseases. Methods: The information component of JITIF consisted of a set of theory or evidence-based ingredients, including operation guideline, public commitment, and takeaway information, whereas the feedback component tells each participating doctor about his or her performance scores and percentages of antibiotic prescriptions. These ingredients were incorporated together in a synergetic way via a Web-based aid. Evaluation of JITIF adopted a randomized controlled trial design involving 24 village clinics randomized into equal control and intervention arms. Measures used included changes between baseline and endpoint (1 year after baseline) in terms of: percentages of patients with symptomatic respiratory or gastrointestinal tract infections (RTIs or GTIs) being prescribed antibiotics, delivery of essential service procedures, and patients’ beliefs and knowledge about antibiotics and infection prevention. Two researchers worked as a group in collecting the data at each site clinic. One performed nonparticipative observation of the service process, while the other performed structured exit interviews about patients’ beliefs and knowledge. Data analysis comprised mainly of: (1) descriptive estimations of beliefs or knowledge, practice of indicative procedures, and use of antibiotics at baseline and endpoint for intervention and control groups and (2) chi-square tests for the differences between these groups. Results: A total of 1048 patients completed the evaluation, including 532 at baseline (intervention=269, control=263) and 516 at endpoint (intervention=262, control=254). Patients diagnosed with RTIs and GTIs accounted for 76.5% (407/532) and 23.5% (125/352), respectively, at baseline and 80.8% (417/532) and 19.2% (99/532) at endpoint. JITIF resulted in substantial improvement in delivery of essential service procedures (2.6%-24.8% at baseline on both arms and at endpoint on the control arm vs 88.5%-95.0% at endpoint on the intervention arm, P<.001), beliefs favoring rational antibiotics use (11.5%-39.8% at baseline on both arms and at endpoint on the control arm vs 19.8%-62.6% at endpoint on the intervention arm, P<.001) and knowledge about side effects of antibiotics (35.7% on the control arm vs 73.7% on the intervention arm, P<.001), measures for managing or preventing RTIs (39.1% vs 66.7%, P=.02), and measures for managing or preventing GTIs (46.8% vs 69.2%, P<.001). It also reduced antibiotics prescription (from 88.8%-62.3%, P<.001), and this decrease was consistent for RTIs (87.1% vs 64.3%, P<.001) and GTIs (94.7% vs 52.4%, P<.001). Conclusions: JITIF is effective in controlling antibiotics prescription at least in the short term and may provide a low-cost and sustainable solution to the widespread excessive use of antibiotics in rural China.

  • Source: Pixabay; Copyright: rebcenter-moscow; URL: https://pixabay.com/en/emotions-sorrow-emotional-view-2764936/; License: Public Domain (CC0).

    Effectiveness of a Web-Based Self-Help Program for Suicidal Thinking in an Australian Community Sample: Randomized Controlled Trial

    Abstract:

    Background: Treatment for suicidality can be delivered online, but evidence for its effectiveness is needed. Objective: The goal of our study was to examine the effectiveness of an online self-help intervention for suicidal thinking compared to an attention-matched control program. Methods: A 2-arm randomized controlled trial was conducted with assessment at postintervention, 6, and, 12 months. Through media and community advertizing, 418 suicidal adults were recruited to an online portal and were delivered the intervention program (Living with Deadly Thoughts) or a control program (Living Well). The primary outcome was severity of suicidal thinking, assessed using the Columbia Suicide Severity Rating Scale. Results: Intention-to-treat analyses showed significant reductions in the severity of suicidal thinking at postintervention, 6, and 12 months. However, no overall group differences were found. Conclusions: Living with Deadly Thoughts was of no greater effectiveness than the control group. Further investigation into the conditions under which this program may be beneficial is now needed. Limitations of this trial include it being underpowered given the effect size ultimately observed, a high attrition rate, and the inability of determining suicide deaths or of verifying self-reported suicide attempts. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12613000410752; https://www.anzctr.org.au/ Trial/Registration/TrialReview.aspx?id=364016 (Archived by WebCite at http://www.webcitation.org/6vK5FvQXy); Universal Trial Number U1111-1141-6595

  • Source: The Authors / Placeit.net; Copyright: JMIR Publications; URL: http://www.jmir.org/2018/2/e54/; License: Creative Commons Attribution (CC-BY).

    Patient-Reported Measures for Person-Centered Coordinated Care: A Comparative Domain Map and Web-Based Compendium for Supporting Policy Development and...

    Abstract:

    Background: Patient-reported measure (PRM) questionnaires were originally used in research to measure outcomes of intervention studies. They have now evolved into a diverse family of tools measuring a range of constructs including quality of life and experiences of care. Current health and social care policy increasingly advocates their use for embedding the patient voice into service redesign through new models of care such as person-centered coordinated care (P3C). If chosen carefully and used efficiently, these tools can help improve care delivery through a variety of novel ways, including system-level feedback for health care management and commissioning. Support and guidance on how to use these tools would be critical to achieve these goals. Objective: The objective of this study was to develop evidence-based guidance and support for the use of P3C-PRMs in health and social care policy through identification of PRMs that can be used to enhance the development of P3C, mapping P3C-PRMs against an existing model of domains of P3C, and integration and organization of the information in a user-friendly Web-based database. Methods: A pragmatic approach was used for the systematic identification of candidate P3C-PRMs, which aimed at balancing comprehensiveness and feasibility. This utilized a number of resources, including existing compendiums, peer-reviewed and gray literature (using a flexible search strategy), and stakeholder engagement (which included guidance for relevant clinical areas). A subset of those candidate measures (meeting prespecified eligibility criteria) was then mapped against a theoretical model of P3C, facilitating classification of the construct being measured and the subsequent generation of shortlists for generic P3C measures, specific aspects of P3C (eg, communication or decision making), and condition-specific measures (eg, diabetes, cancer) in priority areas, as highlighted by stakeholders. Results: In total, 328 P3C-PRMs were identified, which were used to populate a freely available Web-based database. Of these, 63 P3C-PRMs met the eligibility criteria for shortlisting and were classified according to their measurement constructs and mapped against the theoretical P3C model. We identified tools with the best coverage of P3C, thereby providing evidence of their content validity as outcome measures for new models of care. Transitions and medications were 2 areas currently poorly covered by existing measures. All the information is currently available at a user-friendly web-based portal (p3c.org.uk), which includes all relevant information on each measure, such as the constructs targeted and links to relevant literature, in addition to shortlists according to relevant constructs. Conclusions: A detailed compendium of P3C-PRMs has been developed using a pragmatic systematic approach supported by stakeholder engagement. Our user-friendly suite of tools is designed to act as a portal to the world of PRMs for P3C, and have utility for a broad audience, including (but not limited to) health care commissioners, managers, and researchers.

  • iRobi robot being used by a patient. Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2018/2/e45/; License: Creative Commons Attribution (CC-BY).

    Using Robots at Home to Support Patients With Chronic Obstructive Pulmonary Disease: Pilot Randomized Controlled Trial

    Abstract:

    Background: Socially assistive robots are being developed for patients to help manage chronic health conditions such as chronic obstructive pulmonary disease (COPD). Adherence to medication and availability of rehabilitation are suboptimal in this patient group, which increases the risk of hospitalization. Objective: This pilot study aimed to investigate the effectiveness of a robot delivering telehealth care to increase adherence to medication and home rehabilitation, improve quality of life, and reduce hospital readmission compared with a standard care control group. Methods: At discharge from hospital for a COPD admission, 60 patients were randomized to receive a robot at home for 4 months or to a control group. Number of hospitalization days for respiratory admissions over the 4-month study period was the primary outcome. Medication adherence, frequency of rehabilitation exercise, and quality of life were also assessed. Implementation interviews as well as benefit-cost analysis were conducted. Results: Intention-to-treat and per protocol analyses showed no significant differences in the number of respiratory-related hospitalizations between groups. The intervention group was more adherent to their long-acting inhalers (mean number of prescribed puffs taken per day=48.5%) than the control group (mean 29.5%, P=.03, d=0.68) assessed via electronic recording. Self-reported adherence was also higher in the intervention group after controlling for covariates (P=.04). The intervention group increased their rehabilitation exercise frequency compared with the control group (mean difference −4.53, 95% CI −7.16 to −1.92). There were no significant differences in quality of life. Of the 25 patients who had the robot, 19 had favorable attitudes. Conclusions: This pilot study suggests that a homecare robot can improve adherence to medication and increase exercise. Further research is needed with a larger sample size to further investigate effects on hospitalizations after improvements are made to the robots. The robots could be especially useful for patients struggling with adherence. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12615000259549; http://www.anzctr.org.au (Archived by WebCite at  http://www.webcitation.org/6whIjptLS)

  • Source: Flickr; Copyright: UK Department for International Development; URL: https://www.flickr.com/photos/14214150@N02/5331065350; License: Creative Commons Attribution (CC-BY).

    Role of Social Media in Diabetes Management in the Middle East Region: Systematic Review

    Authors List:

    Abstract:

    Background: Diabetes is a major health care burden in the Middle East region. Social networking tools can contribute to the management of diabetes with improved educational and care outcomes using these popular tools in the region. Objective: The objective of this review was to evaluate the impact of social networking interventions on the improvement of diabetes management and health outcomes in patients with diabetes in the Middle East. Methods: Peer-reviewed articles from PubMed (1990-2017) and Google Scholar (1990-2017) were identified using various combinations of predefined terms and search criteria. The main inclusion criterion consisted of the use of social networking apps on mobile phones as the primary intervention. Outcomes were grouped according to study design, type of diabetes, category of technological intervention, location, and sample size. Results: This review included 5 articles evaluating the use of social media tools in the management of diabetes in the Middle East. In most studies, the acceptance rate for the use of social networking to optimize the management of diabetes was relatively high. Diabetes-specific management tools such as the Saudi Arabia Networking for Aiding Diabetes and Diabetes Intelligent Management System for Iraq systems helped collect patient information and lower hemoglobin A1c (HbA1c) levels, respectively. Conclusions: The reviewed studies demonstrated the potential of social networking tools being adopted in regions in the Middle East to improve the management of diabetes. Future studies consisting of larger sample sizes spanning multiple regions would provide further insight into the use of social media for improving patient outcomes.

  • Mobile e-learning with an interactive multimedia module for emergent otorhinolaryngology-head and neck surgery disorders. Source: Image created by the authors.; Copyright: The Authors; URL: http://www.jmir.org/2018/2/e56/; License: Creative Commons Attribution (CC-BY).

    Cognitive Style and Mobile E-Learning in Emergent Otorhinolaryngology-Head and Neck Surgery Disorders for Millennial Undergraduate Medical Students:...

    Abstract:

    Background: Electronic learning (e-learning) through mobile technology represents a novel way to teach emergent otorhinolaryngology-head and neck surgery (ORL-HNS) disorders to undergraduate medical students. Whether a cognitive style of education combined with learning modules can impact learning outcomes and satisfaction in millennial medical students is unknown. Objective: The aim of this study was to assess the impact of cognitive styles and learning modules using mobile e-learning on knowledge gain, competence gain, and satisfaction for emergent ORL-HNS disorders. Methods: This randomized controlled trial included 60 undergraduate medical students who were novices in ORL-HNS at an academic teaching hospital. The cognitive style of the participants was assessed using the group embedded figures test. The students were randomly assigned (1:1) to a novel interactive multimedia (IM) group and conventional Microsoft PowerPoint show (PPS) group matched by age, sex, and cognitive style. The content for the gamified IM module was derived from and corresponded to the textbook-based learning material of the PPS module (video lectures). The participants were unblinded and used fully automated courseware containing the IM or PPS module on a 7-inch tablet for 100 min. Knowledge and competence were assessed using multiple-choice questions and multimedia situation tests, respectively. Each participant also rated their global satisfaction. Results: All of the participants (median age 23 years, range 22-26 years; 36 males and 24 females) received the intended intervention after randomization. Overall, the participants had significant gains in knowledge (median 50%, interquartile range [IQR]=17%-80%, P<.001) and competence (median 13%, IQR=0%-33%, P=.006). There were no significant differences in knowledge gain (40%, IQR=13%-76% vs 60%, IQR=20%-100%, P=.42) and competence gain (0%, IQR= −21% to 38% vs 25%, IQR=0%-33%, P=.16) between the IM and PPS groups. However, the IM group had a higher satisfaction score (8, IQR=6-9 vs 6, IQR=4-7, P=.01) compared with the PPS group. Using Friedman’s two-way nonparametric analysis of variance, cognitive styles (field-independent, field-intermediate, or field-dependent classification) and learning modules (IM or PPS) had significant effects on both knowledge gain (both adjusted P<.001) and satisfaction (both adjusted P<.001). Conclusions: Mobile e-learning is an effective modality to improve knowledge of emergent ORL-HNS in millennial undergraduate medical students. Our findings suggest the necessity of developing various modules for undergraduate medical students with different cognitive styles. Trial Registration: Clinicaltrials.gov NCT02971735; https://clinicaltrials.gov/ct2/show/NCT02971735 (Archived by WebCite at http://www.webcitation.org/6waoOpCEV)

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    Open Peer Review Period: Feb 19, 2018 - Apr 16, 2018

    Background: The clinical heterogeneity of patients with diabetes increases the challenge of maintaining glycemic control and therapy adherence. It is fundamental that patients are actively involved in...

    Background: The clinical heterogeneity of patients with diabetes increases the challenge of maintaining glycemic control and therapy adherence. It is fundamental that patients are actively involved in the management of the disease in their living environments. This requires taking medicines, following a proper diet, trying to do some exercise, and being educated about and trained on the condition and its main risks. Objective: To build on top of User Centered Design techniques a supporting self-management system for diabetes in community settings. The aim is to show how User Centered Design techniques can be relevant to define and personalize eHealth solutions for the management of diabetes by assessing the use and compliance of the self-management system in a small-scale multicenter randomized study Methods: User Centered Design principles was used to involve diabetic patients and treating rpofessionals into the design, development and evaluation of a self-management system. An adaptation of the G-OD methodology was used throughout the whole process, through three main iterative cycles: scenario definition, user archetype definition and system development. Usage and compliance metrics were defined for assessing the level of engagement of patients towards their prescribed treatment and the adherence to the proposed self-management system during a four week duration study. The Wilcoxon test was chosen as a particularly conservative method, sacrificing test-power for accurateness under possibly non-parametric conditions for comparing the observed measurements for each of the weeks in the study. Results: A comprehensive system incorporating modules for the management of blood glucose levels, medication, food intake habits, physical activity, diabetic education and messaging was adapted to each of the two type of principal users (personas): Type 1 Diabetes user and Type 2 Diabetes User. 20 patients and 24 treating professionals enrolled the study and used the implemented system for a period of four weeks. The assessment of usage and compliance metrics was similar and did not achieve a significant difference among the two type of users, except to the medication module, which show a significant different use and compliance (P=.01) Conclusions: A self-management system for diabetes based on User Centered Design empowered patients to make their own decisions and help to expand the concept of Personal Health Records as an addition to the Electronic Health Records. After an initial period of time, T1DM are more prone to use less the parts of the designed app, however the use and the communications sent from the app still remain similar among T1DM and T2DM patients

  • Health topics on Facebook groups: content analysis of posts in Multiple Sclerosis communities

    Date Submitted: Feb 16, 2018

    Open Peer Review Period: Feb 17, 2018 - Apr 14, 2018

    Background: Social Network Sites (SNSs) are increasingly being used to exchange health information from patients and practitioners/pharmaceutical companies/research centers. Research contributions hav...

    Background: Social Network Sites (SNSs) are increasingly being used to exchange health information from patients and practitioners/pharmaceutical companies/research centers. Research contributions have explored the contents discussed online, categorized the topics, and explored their engagement levels. Objective: This research aims at investigating the potential role of Social Networks Site (SNSs) in Healthcare. Specifically it provides a clustering of health information available on SNSs and creates an initial research design that would allow the use of this information to enhance healthcare delivery. In addition, this research aims at testing whether SNSs valid tools for sharing drug related information by patients. Methods: The research is based on a specific chronic disease: Multiple Sclerosis. We searched the SNS Facebook and looked at all existing groups on this condition. The analysis was restricted to public groups for privacy concerns. We created a database by downloading posts from two main groups on which we performed a content analysis and a statistical analysis; this allowed us to discriminate between categories, their engagement level, and type of posts shared. The mean of engagement for each topic was analyzed using one-way ANOVA and followed up by pairwise comparisons using TukeyHSD. Results: On a sample of 7029 posts, initial results show that there are 8 categories of topics that have resonance (percentage of times the topic appears in our sample) with those who post on Facebook: Patient Support (3.09%), Information/Awareness (70.02%), Event Advertising and Petitions (5.19%), Products and Drugs Advertising (0.68%), Fundraising (5.04%), Clinical Trials or Research Studies (0.84%), Drug Discussion (2.05%), and Other (14.14%). Initial analysis shows that “comments” and “likes” (as measures of engagement level) are more frequently used than other measures of engagement. The results show high engagement level (in terms of views, likes, comments, etc.) for Patient support, Information/Awareness. In addition, although Drug Discussion had low resonance it had unexpected highly engagement level which we found worthy of further exploration. Conclusions: SNSs have become important tools for patients and healthcare practitioners to share or seek information. We identify the type of information shared and how the public reacts to it. Our research confirms that the categories of topics discussed in social media related to specific diseases are appropriate as they are similar to the categories observed by other researchers. Additionally, we found other categories such as drug discussion which was unexpected. This and other results of our study enhance our understanding of how contents are disseminated and perceived within a specific disease based community. We conclude that this information has useful implications in the design of prevention campaigns, educational programs, and chronic disease management.

  • Unobstrusive mobile monitoring of well-being of ambulatory patients in palliative care: what can remote data tell us?

    Date Submitted: Feb 16, 2018

    Open Peer Review Period: Feb 16, 2018 - Apr 13, 2018

    Background: For advanced cancer patients in palliative care, a crucial phase is the transition from palliative care in the hospital to the home setting, where 24-7 care is not guaranteed any more. To...

    Background: For advanced cancer patients in palliative care, a crucial phase is the transition from palliative care in the hospital to the home setting, where 24-7 care is not guaranteed any more. To fill this gap after transition, we are evaluating the feasibility of a physical and social activity tracking system consisting of a FDA approved bracelet (Biovotion Everion MD®) collecting vital data, e.g., heart rate, oxygen saturation etc., and an Android smart-phone (Samsung Galaxy S5) collecting patients’ self-reports of pain and distress as well as acceleration, GPS and phone call statistics data. When study participants are asked, how they are doing in general, a common answer is “There are good days and there are bad days.” Apparently, they order their days into different groups. We argue that these “good” and “bad” days have impact on a patient’s behavior and is therefore visible in the collected activity data. Objective: As a part of the study’s goals, we aim to show the explanatory power of the collected data: the collected data reflect the health status of a patient. Methods: Data is collected over a study period of 12 weeks as part of a feasibility study with an explorative and descriptive study design. Study participants are enrolled from the wards of the Clinic of Radiation-Oncology at the University Hospital Zurich, including the specialized palliative care ward. The data collection chain consists of the patients’ devices, Wi-Fi and internet for secured data upload and a receiving web server. The raw data is preprocessed involving resampling and basic feature extraction. Complex features are extracted using unsupervised machine learning methods, e.g., clustering. Heat maps are used to provide overview visualizations of sensor modalities. Integrated views are generated for multi-modal reconstruction and visualization of patients’ daily routines. Results: Data collection started in March 2017 and already 13 study participants have finished their study participation or had to abort their participation due to health reasons. We collected more than 10000 hours of valid bracelet data and about 410000 GPS positions from the smart-phone. The cohort shows a high variability in live circumstances, e.g., some are still working, and others hardly leave their homes. We give examples of two patients with different courses of disease in order to demonstrate our approach. Conclusions: Our remote monitoring system delivers a large amount of data that allows us to reconstruct the daily routines of the patients showing differences between good and bad days. Clinical Trial: The local Ethics Committee (Kantonale Ethikkommission Zürich) has approved the study protocol; approval number PB_2016-00895.

  • Predicting Concussions Using Data Analytic Approaches

    Date Submitted: Feb 15, 2018

    Open Peer Review Period: Feb 16, 2018 - Apr 13, 2018

    Background: Background: Sports related concussion forms a major component of all brain injuries occurring in the United States and has a huge detrimental impact on the quality of life and various heal...

    Background: Background: Sports related concussion forms a major component of all brain injuries occurring in the United States and has a huge detrimental impact on the quality of life and various health outcome. Predicting concussion is an important way to achieve prevention. Understanding concussion likelihood in the context of different data such as demographic, life style and mental health information related injury will support the development of better diagnostics and preventative techniques. Objective: The objective of this study is to predict the concussion occurrence, number of the concussion, and number of the years since the last concussion using the analytical models. Methods: We develop analytic models that are built using disparate data about lifestyle, demographics and medical history. These models that are based on various machine learning algorithms such as K_Nearest Neighbor, Support Vector Machines, Regression, Ensemble models, Artificial Neural Networks, Decision Tree, General Linear Model and Multivariate Adaptive Regression Splines. In this paper the synthetic minority over-sampling (SMOTE) is employed to overcome the data-imbalance problems. Results: The results show that the predictors associated with the cognitive-mental health plays an important role as a predictor of concussions. Findings suggest that Random forest, Artificial Neural Networks and Decision Tree demonstrate superior performance (sensitivity-80, specificity-88, accuracy- 86) over the other analytics approaches. The number of the concussions are best predicted by K_Nearest Neighbor (sensitivity-83, specificity-75, accuracy-80) while Multivariate Adaptive Regression Splines (mean absoluter error - 2.45) and General Linear Model (mean absoluter error - 2.67) outperform the other machine learning methods for predicting the number of the years past from last concussion Conclusions: Using the data derived from a series of easily executable screening test supported with IoT devices and self-reports, comprehensive analytics models to predict concussion occurrence, reoccurrence and duration since last concussion based on their demographic, lifestyle and mental health information can be developed. Such computational models could lead to customized training approaches and improved efforts for concussion prevention and management.

  • Instant Automated Inference of Perceived Mental Stress through Smartphone PPG and Thermal Imaging

    Date Submitted: Feb 15, 2018

    Open Peer Review Period: Feb 16, 2018 - Apr 13, 2018

    Background: A smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. Photoplethysmography (PPG) and low-cost thermography can be used to create cheap, conven...

    Background: A smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. Photoplethysmography (PPG) and low-cost thermography can be used to create cheap, convenient and mobile systems. However, to achieve robustness, a person has to remain still for several minutes while a measurement is being taken. This is very cumbersome, and limits the usage in applications such producing instant measurements of stress. Objective: We propose to use smartphone-based mobile PPG and thermal imaging to provide a fast binary measure of stress responses to an event using dynamical physiological changes which occur within 20 seconds of the event finishing. Methods: We propose a system that uses a smartphone and its physiological sensors to reliably and continuously measure over a short window of time a person’s blood volume pulse, the time interval between heartbeats (R-R interval) and the 1D thermal signature of the nose tip. 17 healthy participants, involved in a series of stress-inducing mental activities, measured their physiological response to stress in the 20 second-window immediately following each activity. A 10-cm Visual Analogue Scale was used by them to self-report their level of mental stress. As a main labeling strategy, normalized K-means clustering is used to better treat inter-personal differences in ratings. By taking an array of the R-R intervals and thermal directionality as a low-level feature input, we mainly use an artificial neural network to enable the automatic feature learning and the machine learning inference process. To compare the automated inference performance, we also extracted widely used high level features from HRV (e.g., LF/HF ratio) and the thermal signature and input them to a k-nearest neighbor to infer perceived stress levels. Results: First, we tested the physiological measurement reliability. The measured cardiac signals were considered highly reliable (signal goodness probability used, Mean=0.9584, SD=0.0151). The proposed 1D thermal signal processing algorithm effectively minimized the effect of respiratory cycles on detecting the apparent temperature of the nose tip (respiratory signal goodness probability Mean=0.8998 to Mean=0). Second, we tested the 20 seconds instant perceived stress inference performance. The best results were obtained by using automatic feature learning and classification using artificial neural networks rather than using pre-crafted features. The combination of both modalities produced higher accuracy on the binary classification task using 17-fold leave-one-subject-out (LOSO) cross-validation (accuracy: HRV+Thermal: 76.96%; HRV: 60.29%; Thermal: 61.37%). The results are comparable with the state of the art automatic stress recognition methods requiring long term measurements (a minimum of 2 minutes for up to around 80% accuracy from LOSO). Lastly, we explored the impact of different data labeling strategies used in the field on the sensitivity of our inference methods and the need for normalization within individual. Conclusions: Results demonstrate the capability of smartphone biomedical imaging in instant mental stress recognition. Given that this approach does not require long measurements requiring attention and reduced mobility, it is more feasible for mobile mental healthcare solution in the wild.

  • SoTRAACE for active security in Ambient Assisted Living

    Date Submitted: Feb 16, 2018

    Open Peer Review Period: Feb 16, 2018 - Apr 13, 2018

    Background: Ambient Assisted Living (AAL) solutions have been conquering an important place among strategies to promote ageing in place and address the societal challenges of population ageing. AAL is...

    Background: Ambient Assisted Living (AAL) solutions have been conquering an important place among strategies to promote ageing in place and address the societal challenges of population ageing. AAL is deeply rooted on the computing paradigm of Ambient Intelligence which strongly impacts the technological phenomenon of Internet of Things (IoT), currently covering a plethora of ageing related application areas. The pervasiveness of IoT raise, however, security challenges and require more flexible and better adapted availability and privacy measures. Still, IoT devices and services are frequently described in the literature without any reference to privacy and security issues they may integrate and the few works in the Ambient Assisted Living (AAL) field focus mostly on authentication or physical access control. Objective: This paper describes the SoTRAACE - Socio-Technical Risk-Adaptable Access Control - model, designed to better adapt users’ access control needs to each AAL security context. The model is applied to use cases based on AAL for mental health personas and scenarios. Methods: SoTRAACE architecture takes into account contextual, technological and user’s interaction profiling functionalities to act in each AAL situation/request and perform a quantitative and qualitative risk assessment analysis. The risk analysis supports decision-making on the most secure, private and usable way to access and display information. Results: SoTRAACE unique advantages for improved availability and privacy are discussed in contrast with existing access control models. The model is showcased and discussed within two AAL for mental health use case scenarios. SoTRAACE new and reused components are varied and versatile enough to adapt to different situations and user’s goals, whether these are patient or caregiver oriented. Conclusions: SoTRAACE is an innovative and complete proposal for secure and adaptable access control in AAL or similar environments.

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