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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:

  • 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)

  • Source: iStock by Getty Images; Copyright: Wavebreakmedia; URL: https://www.istockphoto.com/dk/photo/senior-couple-using-laptop-gm650006194-119418467?clarity=false; License: Licensed by the authors.

    A Multidimensional Tool Based on the eHealth Literacy Framework: Development and Initial Validity Testing of the eHealth Literacy Questionnaire (eHLQ)

    Abstract:

    Background: For people to be able to access, understand, and benefit from the increasing digitalization of health services, it is critical that services are provided in a way that meets the user’s needs, resources, and competence. Objective: The objective of the study was to develop a questionnaire that captures the 7-dimensional eHealth Literacy Framework (eHLF). Methods: Draft items were created in parallel in English and Danish. The items were generated from 450 statements collected during the conceptual development of eHLF. In all, 57 items (7 to 9 items per scale) were generated and adjusted after cognitive testing. Items were tested in 475 people recruited from settings in which the scale was intended to be used (community and health care settings) and including people with a range of chronic conditions. Measurement properties were assessed using approaches from item response theory (IRT) and classical test theory (CTT) such as confirmatory factor analysis (CFA) and reliability using composite scale reliability (CSR); potential bias due to age and sex was evaluated using differential item functioning (DIF). Results: CFA confirmed the presence of the 7 a priori dimensions of eHLF. Following item analysis, a 35-item 7-scale questionnaire was constructed, covering (1) using technology to process health information (5 items, CSR=.84), (2) understanding of health concepts and language (5 items, CSR=.75), (3) ability to actively engage with digital services (5 items, CSR=.86), (4) feel safe and in control (5 items, CSR=.87), (5) motivated to engage with digital services (5 items, CSR=.84), (6) access to digital services that work (6 items, CSR=.77), and (7) digital services that suit individual needs (4 items, CSR=.85). A 7-factor CFA model, using small-variance priors for cross-loadings and residual correlations, had a satisfactory fit (posterior productive P value: .27, 95% CI for the difference between the observed and replicated chi-square values: −63.7 to 133.8). The CFA showed that all items loaded strongly on their respective factors. The IRT analysis showed that no items were found to have disordered thresholds. For most scales, discriminant validity was acceptable; however, 2 pairs of dimensions were highly correlated; dimensions 1 and 5 (r=.95), and dimensions 6 and 7 (r=.96). All dimensions were retained because of strong content differentiation and potential causal relationships between these dimensions. There is no evidence of DIF. Conclusions: The eHealth Literacy Questionnaire (eHLQ) is a multidimensional tool based on a well-defined a priori eHLF framework with robust properties. It has satisfactory evidence of construct validity and reliable measurement across a broad range of concepts (using both CTT and IRT traditions) in various groups. It is designed to be used to understand and evaluate people’s interaction with digital health services.

  • Source: Pexels; Copyright: Startup Stock Photos; URL: https://www.pexels.com/photo/working-woman-technology-computer-7374/; License: Public Domain (CC0).

    Health Information Obtained From the Internet and Changes in Medical Decision Making: Questionnaire Development and Cross-Sectional Survey

    Abstract:

    Background: The increasing utilization of the internet has provided a better opportunity for people to search online for health information, which was not easily available to them in the past. Studies reported that searching on the internet for health information may potentially influence an individual’s decision making to change her health-seeking behaviors. Objective: The objectives of this study were to (1) develop and validate 2 questionnaires to estimate the strategies of problem-solving in medicine and utilization of online health information, (2) determine the association between searching online for health information and utilization of online health information, and (3) determine the association between online medical help-seeking and utilization of online health information. Methods: The Problem Solving in Medicine and Online Health Information Utilization questionnaires were developed and implemented in this study. We conducted confirmatory factor analysis to examine the structure of the factor loadings and intercorrelations for all the items and dimensions. We employed Pearson correlation coefficients for examining the correlations between each dimension of the Problem Solving in Medicine questionnaire and each dimension of the Online Health Information Utilization questionnaire. Furthermore, we conducted structure equation modeling for examining the possible linkage between each of the 6 dimensions of the Problem Solving in Medicine questionnaire and each of the 3 dimensions of the Online Health Information Utilization questionnaire. Results: A total of 457 patients participated in this study. Pearson correlation coefficients ranged from .12 to .41, all with statistical significance, implying that each dimension of the Problem Solving in Medicine questionnaire was significantly associated with each dimension of the Online Health Information Utilization questionnaire. Patients with the strategy of online health information search for solving medical problems positively predicted changes in medical decision making (P=.01), consulting with others (P<.001), and promoting self-efficacy on deliberating the online health information (P<.001) based on the online health information they obtained. Conclusions: Present health care professionals have a responsibility to acknowledge that patients’ medical decision making may be changed based on additional online health information. Health care professionals should assist patients’ medical decision making by initiating as much dialogue with patients as possible, providing credible and convincing health information to patients, and guiding patients where to look for accurate, comprehensive, and understandable online health information. By doing so, patients will avoid becoming overwhelmed with extraneous and often conflicting health information. Educational interventions to promote health information seekers’ ability to identify, locate, obtain, read, understand, evaluate, and effectively use online health information are highly encouraged.

  • Participants at work in the 2nd Symposium on Computing in Mental Health at the ACM Computer-Human Interaction conference. Source: Image created by the Authors; Copyright: Rafael Calvo; URL: https://pbs.twimg.com/media/C_LTap3XkAEwbUW.jpg:large; License: Public Domain (CC0).

    Toward Impactful Collaborations on Computing and Mental Health

    Abstract:

    We describe an initiative to bring mental health researchers, computer scientists, human-computer interaction researchers, and other communities together to address the challenges of the global mental ill health epidemic. Two face-to-face events and one special issue of the Journal of Medical Internet Research were organized. The works presented in these events and publication reflect key state-of-the-art research in this interdisciplinary collaboration. We summarize the special issue articles and contextualize them to present a picture of the most recent research. In addition, we describe a series of collaborative activities held during the second symposium and where the community identified 5 challenges and their possible solutions.

  • Source: Flickr; Copyright: Scott Brown; URL: http://www.flickr.com/photos/37831155@N06/5590877394; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    Effect of Recruitment Methods on Response Rate in a Web-Based Study for Primary Care Physicians: Factorial Randomized Controlled Trial

    Abstract:

    Background: Low participation rates are one of the most serious disadvantages of Web-based studies. It is necessary to develop effective strategies to improve participation rates to obtain sufficient data. Objective: The objective of this trial was to investigate the effect of emphasizing the incentive in the subject line of the invitation email and the day of the week of sending the invitation email on the participation rate in a Web-based trial. Methods: We conducted a 2×2 factorial design randomized controlled trial. We contacted 2000 primary care physicians from members of the Japan Primary Care Association in January 2017 and randomly allocated them to 1 of 4 combinations of 2 subject lines (presence or absence of an emphasis on a lottery for an Amazon gift card worth 3000 yen or approximately US $30) and 2 delivery days (sending the invitation email on Tuesday or Friday). The primary outcome was the response rate defined as the number of participants answering the first page of the questionnaire divided by the number of invitation emails delivered. All outcomes were collected between January 17, 2017, and February 8, 2017. Results: We analyzed data from 1943 out of 2000 participants after excluding those whose email addresses were invalid. The overall response rate was 6.3% (123/1943). There was no significant difference in the response rates between the 2 groups regarding incentive in the subject line: the risk ratio was 1.12 (95% CI 0.80 to 1.58) and the risk difference was 0.7% (95% CI –1.5% to 2.9%). Similarly, there was no significant difference in the response rates between the 2 groups regarding sending the email on Tuesday or Friday: the risk ratio was 0.98 (95% CI 0.70 to 1.38) and the risk difference was –0.1% (95% CI –2.3% to 2.1%). Conclusions: Neither emphasizing the incentive in the subject line of the invitation email nor varying the day of the week the invitation email was sent led to a meaningful increase in response rates in a Web-based trial with primary care physicians. Trial Registration: University Hospital Medical Information Network Clinical Trials Registry UMIN000025317; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000029121 (Archived by WebCite at http://www.webcitation. org/6wOo1jl9t)

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  • 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.

  • Features of an Online Health Prevention and Peer Support Intervention for Young People who have a Parent with a Mental illness: A Delphi Study Among Potential Future Users

    Date Submitted: Feb 16, 2018

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

    Background: Young people who have a parent with a mental illness face elevated risks to their wellbeing. However, they may not have access to appropriate interventions. Online interventions may reach...

    Background: Young people who have a parent with a mental illness face elevated risks to their wellbeing. However, they may not have access to appropriate interventions. Online interventions may reach and meet the needs of this at-risk group, yet their preferences regarding the features of this medium are unknown. Objective: This study sought to determine the utility of an online intervention to meet the needs of young people who have a parent with a mental illness, and their perspectives regarding the types of features of such a website. Methods: A systematic, two-round Delphi study was employed to solicit the views of 282 young people aged 16 to 21 years (Round 1 n = 14, Round 2 n = 268), from urban and regional settings in Australia. ‘Regional’ was used to refer to non-urban participants in the study. After first ascertaining whether an online intervention was warranted, an extensive list of online intervention features was identified, including how the site might be facilitated, topics, duration and frequency, and the nature of professional contact. The extent to which young people agreed on the importance of these factors was assessed. Differences and similarities across gender and location were investigated. A mixed method analytic framework was employed using thematic analysis as well as two-way between-groups analysis of covariance controlling for age (ANCOVA) and chi-square test of independence analysis. Results: Both rounds highlighted a strong preference for an online intervention. Consensus was reached for 1) a professionally monitored site; 2) young people and professionals having equal input into the weekly facilitated sessions (e.g., sharing lead role in discussions or deciding on relevant session content); 3) unlimited time access; 4) one-hour, open discussion, weekly sessions over 6 weeks; 5) preferred features for an online intervention; 6) psychoeducation about mental illness; and, 7) considerations for the management of safety violations. There were significant main effects of location type and several of the preferred features for an online intervention for young people who have a parent with a mental illness; however, effect sizes were small to moderate, limiting practical application. Conclusions: Young people aged 16 to 21 years indicated a need for a professionally monitored, psychoeducational, online intervention, with input from professional facilitators and other similar young people, in addition to recommendations to external resources. The findings can be used to inform the development of future online interventions for this highly vulnerable group.

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