Maintenance Note

On Friday, August 31, 2018 at 12:00 pm Eastern Time, JMIR will be completing a server migration to improve site stability and user experience. We expect to be back online Friday, August 31, 2018 at 5:00 pm Eastern Time. Should any problems arise our technical team will be using the weekend to resolve them, and users will be able to access our site by Sunday, September 2, 2018 at 1:00pm Eastern Time.

Who will be affected?


Journal Description

The Journal of Medical Internet Research (JMIR), now in its 20th year, is the pioneer open access eHealth journal and is the flagship journal of JMIR Publications. It is the leading digital health journal globally in terms of quality/visibility (Impact Factor 2017: 4.671, ranked #1 out of 22 journals) and in terms of size (number of papers published). The journal focuses on emerging technologies, medical devices, apps, engineering, and informatics applications for patient education, prevention, population health and clinical care. As leading high-impact journal in its' disciplines (health informatics and health services research), it is selective, but it is now complemented by almost 30 specialty JMIR sister journals, which have a broader scope. Peer-review reports are portable across JMIR journals and papers can be transferred, so authors save time by not having to resubmit a paper to different journals. 

As open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).

We are also a leader in participatory and open science approaches, and offer the option to publish new submissions immediately as preprints, which receive DOIs for immediate citation (eg, in grant proposals), and for open peer-review purposes. We also invite patients to participate (eg, as peer-reviewers) and have patient representatives on editorial boards.

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


Recent Articles:

  • A patient and the physician discussing Internet health information. Source: Pxhere; Copyright:; URL:; License: Public Domain (CC0).

    Relationship Between Internet Health Information and Patient Compliance Based on Trust: Empirical Study


    Background: The internet has become a major mean for acquiring health information; however, Web-based health information is of mixed quality and may markedly affect patients’ health-related behavior and decisions. According to the social information processing theory, patients’ trust in their physicians may potentially change due to patients’ health-information-seeking behavior. Therefore, it is important to identify the relationship between internet health information and patient compliance from the perspective of trust. Objective: The objective of our study was to investigate the effects of the quality and source of internet health information on patient compliance using an empirical study based on the social information processing theory and social exchange theory. Methods: A Web-based survey involving 336 valid participants was conducted in China. The study included independent variables (internet health information quality and source of information), 2 mediators (cognition-based trust [CBT] and affect-based trust [ABT]), 1 dependent variable (patient compliance), and 3 control variables (gender, age, and job). All variables were measured using multiple-item scales from previously validated instruments, and confirmative factor analysis as well as structural equation modeling was used to test hypotheses. Results: The questionnaire response rate was 77.16% (375/486), validity rate was 89.6% (336/375), and reliability and validity were acceptable. We found that the quality and source of internet health information affect patient compliance through the mediation of CBT and ABT. In addition, internet health information quality has a stronger influence on patient compliance than the source of information. However, CBT does not have any direct effect on patient compliance, but it directly affects ABT and then indirectly impacts patient compliance. Therefore, the effect of ABT seems stronger than that of CBT. We found an unexpected, nonsignificant relationship between the source of internet health information and ABT. Conclusions: From patients’ perspective, internet health information quality plays a stronger role than its source in impacting their trust in physicians and the consequent compliance with physicians. Therefore, patient compliance can be improved by strengthening the management of internet health information quality. The study findings also suggest that physicians should focus on obtaining health information from health websites, thereby expanding their understanding of patients’ Web-based health-information-seeking preferences, and enriching their knowledge structure to show their specialization and reliability in the communication with patients. In addition, the mutual demonstration of care and respect in the communication between physicians and patients is important in promoting patients’ ABT in their physicians.

  • Browsing ratings of a physician. Source: The Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Developing Embedded Taxonomy and Mining Patients’ Interests From Web-Based Physician Reviews: Mixed-Methods Approach


    Background: Web-based physician reviews are invaluable gold mines that merit further investigation. Although many studies have explored the text information of physician reviews, very few have focused on developing a systematic topic taxonomy embedded in physician reviews. The first step toward mining physician reviews is to determine how the natural structure or dimensions is embedded in reviews. Therefore, it is relevant to develop the topic taxonomy rigorously and systematically. Objective: This study aims to develop a hierarchical topic taxonomy to uncover the latent structure of physician reviews and illustrate its application for mining patients’ interests based on the proposed taxonomy and algorithm. Methods: Data comprised 122,716 physician reviews, including reviews of 8501 doctors from a leading physician review website in China (, collected between 2007 and 2015. Mixed methods, including a literature review, data-driven-based topic discovery, and human annotation were used to develop the physician review topic taxonomy. Results: The identified taxonomy included 3 domains or high-level categories and 9 subtopics or low-level categories. The physician-related domain included the categories of medical ethics, medical competence, communication skills, medical advice, and prescriptions. The patient-related domain included the categories of the patient profile, symptoms, diagnosis, and pathogenesis. The system-related domain included the categories of financing and operation process. The F-measure of the proposed classification algorithm reached 0.816 on average. Symptoms (Cohen d=1.58, Δu=0.216, t=229.75, and P<.001) are more often mentioned by patients with acute diseases, whereas communication skills (Cohen d=−0.29, Δu=−0.038, t=−42.01, and P<.001), financing (Cohen d=−0.68, Δu=−0.098, t=−99.26, and P<.001), and diagnosis and pathogenesis (Cohen d=−0.55, Δu=−0.078, t=−80.09, and P<.001) are more often mentioned by patients with chronic diseases. Patients with mild diseases were more interested in medical ethics (Cohen d=0.25, Δu 0.039, t=8.33, and P<.001), operation process (Cohen d=0.57, Δu 0.060, t=18.75, and P<.001), patient profile (Cohen d=1.19, Δu 0.132, t=39.33, and P<.001), and symptoms (Cohen d=1.91, Δu=0.274, t=62.82, and P<.001). Meanwhile, patients with serious diseases were more interested in medical competence (Cohen d=−0.99, Δu=−0.165, t=−32.58, and P<.001), medical advice and prescription (Cohen d=−0.65, Δu=−0.082, t=−21.45, and P<.001), financing (Cohen d=−0.26, Δu=−0.018, t=−8.45, and P<.001), and diagnosis and pathogenesis (Cohen d=−1.55, Δu=−0.229, t=−50.93, and P<.001). Conclusions: This mixed-methods approach, integrating literature reviews, data-driven topic discovery, and human annotation, is an effective and rigorous way to develop a physician review topic taxonomy. The proposed algorithm based on Labeled-Latent Dirichlet Allocation can achieve impressive classification results for mining patients’ interests. Furthermore, the mining results reveal marked differences in patients’ interests across different disease types, socioeconomic development levels, and hospital levels.

  • Set-up of the intervention in the waiting room. Source: Image created by the Authors; Copyright: Titus Josef Brinker; URL:; License: Creative Commons Attribution (CC-BY).

    A Face-Aging App for Smoking Cessation in a Waiting Room Setting: Pilot Study in an HIV Outpatient Clinic


    Background: There is strong evidence for the effectiveness of addressing tobacco use in health care settings. However, few smokers receive cessation advice when visiting a hospital. Implementing smoking cessation technology in outpatient waiting rooms could be an effective strategy for change, with the potential to expose almost all patients visiting a health care provider without preluding physician action needed. Objective: The objective of this study was to develop an intervention for smoking cessation that would make use of the time patients spend in a waiting room by passively exposing them to a face-aging, public morphing, tablet-based app, to pilot the intervention in a waiting room of an HIV outpatient clinic, and to measure the perceptions of this intervention among smoking and nonsmoking HIV patients. Methods: We developed a kiosk version of our 3-dimensional face-aging app Smokerface, which shows the user how their face would look with or without cigarette smoking 1 to 15 years in the future. We placed a tablet with the app running on a table in the middle of the waiting room of our HIV outpatient clinic, connected to a large monitor attached to the opposite wall. A researcher noted all the patients who were using the waiting room. If a patient did not initiate app use within 30 seconds of waiting time, the researcher encouraged him or her to do so. Those using the app were asked to complete a questionnaire. Results: During a 19-day period, 464 patients visited the waiting room, of whom 187 (40.3%) tried the app and 179 (38.6%) completed the questionnaire. Of those who completed the questionnaire, 139 of 176 (79.0%) were men and 84 of 179 (46.9%) were smokers. Of the smokers, 55 of 81 (68%) said the intervention motivated them to quit (men: 45, 68%; women: 10, 67%); 41 (51%) said that it motivated them to discuss quitting with their doctor (men: 32, 49%; women: 9, 60%); and 72 (91%) perceived the intervention as fun (men: 57, 90%; women: 15, 94%). Of the nonsmokers, 92 (98%) said that it motivated them never to take up smoking (men: 72, 99%; women: 20, 95%). Among all patients, 102 (22.0%) watched another patient try the app without trying it themselves; thus, a total of 289 (62.3%) of the 464 patients were exposed to the intervention (average waiting time 21 minutes). Conclusions: A face-aging app implemented in a waiting room provides a novel opportunity to motivate patients visiting a health care provider to quit smoking, to address quitting at their subsequent appointment and thereby encourage physician-delivered smoking cessation, or not to take up smoking.

  • Source: Ciran /; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Effectiveness of Serious Gaming During the Multidisciplinary Rehabilitation of Patients With Complex Chronic Pain or Fatigue: Natural Quasi-Experiment


    Background: Current evidence for the effectiveness of specialist multidisciplinary programs for burdensome chronic pain and functional somatic syndromes drives the effort to improve approaches, strategies, and delivery modes. It remains unknown to what extent and in what respect serious gaming during the regular outpatient rehabilitation can contribute to health outcomes. Objective: The objectives of our study were to determine the effect of additional serious gaming on (1) physical and emotional functioning in general; (2) particular outcome domains; and (3) patient global impressions of change, general health, and functioning and to determine (4) the dependency of serious gaming effects on adherence. Methods: We conducted a naturalistic quasi-experiment using embedded qualitative methods. The intervention group patients received an additional guided (mindfulness-based) serious gaming intervention during weeks 9-12 of a 16-week rehabilitation program at 2 sites of a Dutch rehabilitation clinic. Simultaneously, 119 control group patients followed the same program without serious gaming at 2 similar sites of the same clinic. Data consisted of 10 semistructured patient interviews and routinely collected patient self-reported outcomes. First, multivariate linear mixed modeling was used to simultaneously estimate a group effect on the outcome change between weeks 8 and 16 in 4 primary outcomes: current pain intensity, fatigue, pain catastrophizing, and psychological distress. Second, similar univariate linear mixed models were used to estimate effects on particular (unstandardized) outcomes. Third, secondary outcomes (ie, global impression of change, general health, functioning, and treatment satisfaction) were compared between the groups using independent t tests. Finally, subgroups were established according to the levels of adherence using log data. Influences of observed confounding factors were considered throughout analyses. Results: Of 329 eligible patients, 156 intervention group and 119 control group patients (N=275) with mostly chronic back pain and concomitant psychosocial problems participated in this study. Of all, 119 patients played ≥75% of the game. First, the standardized means across the 4 primary outcomes showed a significantly more favorable degree of change during the second part of the treatment for the intervention group than for the control group (beta=−0.119, SE=0.046, P=.009). Second, the intervention group showed a greater outcome change in depressive mood (b=−2.748, SE=1.072, P=.011) but not in “insufficiency” or concentration problems. Third, no significant group effects on secondary outcomes were found. Fourth, adherence was generally high and invariant. Conclusions: The findings of this study suggest a very small favorable average effect on relevant health outcomes of additional serious gaming during multidisciplinary rehabilitation. The indication that serious gaming could be a relatively time-efficient component warrants further research into if, when, how, and for which patients serious gaming could be cost-effective in treatment and why. Trial Registration: Netherlands Trial Registry NTR6020; (Archived by WebCite at

  • Source: Vaping360 (; Copyright: Vaping360; URL:; License: Creative Commons Attribution + NoDerivatives (CC-BY-ND).

    Understanding Users’ Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques


    Background: E-liquid is one of the main components in electronic nicotine delivery systems (ENDS). ENDS review comments could serve as an early warning on use patterns and even function to serve as an indicator of problems or adverse events pertaining to the use of specific e-liquids—much like types of responses tracked by the Food and Drug Administration (FDA) regarding medications. Objective: This study aimed to understand users’ “vaping” experience using sentiment opinion summarization techniques, which can help characterize how consumers think about specific e-liquids and their characteristics (eg, flavor, throat hit, and vapor production). Methods: We collected e-liquid reviews on JuiceDB from June 27, 2013 to December 31, 2017 using its public application programming interface. The dataset contains 27,070 reviews for 8058 e-liquid products. Each review is accompanied by an overall rating and a set of 4 aspect ratings of an e-liquid, each on a scale of 1-5: flavor accuracy, throat hit, value, and cloud production. An iterative dichotomiser 3 (ID3)-based influential aspect analysis model was adopted to learn the key elements that impact e-liquid use. Then, fine-grained sentiment analysis was employed to mine opinions on various aspects of vaping experience related to e-liquids. Results: We found that flavor accuracy and value were the two most important aspects that affected users’ sentiments toward e-liquids. Of reviews in JuiceDB, 67.83% (18,362/27,070) were positive, while 12.67% (3430/27,070) were negative. This indicates that users generally hold positive attitudes toward e-liquids. Among the 9 flavors, fruity and sweet were the two most popular. Great and sweet tastes, reasonable value, and strong throat hit made users satisfied with fruity and sweet flavors, whereas “strange” tastes made users dislike those flavors. Meanwhile, users complained about some e-liquids’ steep or expensive prices, bad quality, and harsh throat hit. There were 2342 fruity e-liquids and 2049 sweet e-liquids. There were 55.81% (1307/2342) and 59.83% (1226/2049) positive sentiments and 13.62% (319/2342) and 12.88% (264/2049) negative sentiments toward fruity e-liquids and sweet e-liquids, respectively. Great flavors and good vapors contributed to positive reviews of fruity and sweet products. However, bad tastes such as “sour” or “bitter” resulted in negative reviews. These findings can help businesses and policy makers to further improve product quality and formulate effective policy. Conclusions: This study provides an effective mechanism for analyzing users’ ENDS vaping experience based on sentiment opinion summarization techniques. Sentiment opinions on aspect and products can be found using our method, which is of great importance to monitor e-liquid products and improve work efficiency.

  • Source: Pexels; Copyright:; URL:; License: Licensed by the authors.

    Information and Communication Technologies Interest, Access, and Use: Cross-Sectional Survey of a Community Sample of Urban, Predominantly Black Women


    Background: Information and communication technologies (ICT) offer the potential for delivering health care interventions to low socioeconomic populations who often face barriers in accessing health care. However, most studies on ICT for health education and interventions have been conducted in clinical settings. Objective: The aim of this study was to examine access to and use of mobile phones and computers, as well as interest in, using ICT for receipt of behavioral health information among a community sample of urban, predominately black, women with low socioeconomic status. Methods: Participants (N=220) were recruited from hair salons and social service centers and completed audio-computer assisted self-interviews. Results: The majority of the participants (212/220, 96.3%) reported use of a cell phone at least weekly, of which 89.1% (189/212) used smartphones and 62.3% (137/220) reported computer use at least weekly. Of the women included in the study, 51.9% (107/206) reported using a cell phone and 39.4% (74/188) reported using a computer to access health and/or safety information at least weekly. Approximately half of the women expressed an interest in receiving information about stress management (51%-56%) or alcohol and health (45%-46%) via ICT. Smartphone ownership was associated with younger age (odds ratio [OR] 0.92, 95% CI 0.87-0.97) and employment (OR 5.12, 95% CI 1.05-24.95). Accessing health and safety information weekly by phone was associated with younger age (OR 0.96, 95% CI 0.94-0.99) and inversely associated with higher income (OR 0.42, 95% CI 0.20-0.92). Conclusions: Our findings suggest that ICT use, particularly smartphone use, is pervasive among predominantly black women with low socioeconomic status in urban, nonclinical settings. These results show that ICT is a promising modality for delivering health information to this population. Further exploration of the acceptability, feasibility, and effectiveness of using ICT to disseminate behavioral health education and intervention is warranted.

  • Source:; Copyright: Intel Free Press; URL:; License: Creative Commons Attribution (CC-BY).

    Social Media Use in Interventions for Diabetes: Rapid Evidence-Based Review


    Background: Health authorities recommend educating diabetic patients and their families and initiating measures aimed at improving self-management, promoting a positive behavior change, and reducing the risk of complications. Social media could provide valid channel to intervene in and deliver diabetes education. However, it is not well known whether the use of these channels in such interventions can help improve the patients’ outcomes. Objective: The objective of our study was to review and describe the current existing evidence on the use of social media in interventions targeting people affected with diabetes. Methods: A search was conducted across 4 databases (PubMed, Scopus, EMBASE, and Cochrane Library).The quality of the evidence of the included primary studies was graded according to the Grading of Recommendations Assessment, Development and Evaluation criteria, and the risk of bias of systematic reviews was assessed by drawing on AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines. The outcomes reported by these studies were extracted and analyzed. Results: We included 20 moderate- and high-quality studies in the review: 17 primary studies and 3 systematic reviews. Of the 16 publications evaluating the effect on glycated hemoglobin (HbA1c) of the interventions using social media, 13 reported significant reductions in HbA1c values. The 5 studies that measured satisfaction with the interventions using social media found positive effects. We found mixed evidence regarding the effect of interventions using social media on health-related quality of life (2 publications found positive effects and 3 found no differences) and on diabetes knowledge or empowerment (2 studies reported improvements and 2 reported no significant changes). Conclusions: There is very little good-quality evidence on the use of social media in interventions aimed at helping people with diabetes. However, the use of these channels is mostly linked to benefits on patients’ outcomes. Public health institutions, clinicians, and other stakeholders who aim at improving the knowledge of diabetic patients could consider the use of social media in their interventions.

  • Source:; Copyright:; URL:; License: Licensed by JMIR.

    Differences in the Effect of Internet-Based Cognitive Behavioral Therapy for Improving Nonclinical Depressive Symptoms Among Workers by Time Preference:...


    Background: Previous randomized controlled trials (RCTs) have shown a significant intervention effect of internet-based computerized cognitive behavioral therapy (iCBT) on improving nonclinical depressive symptoms among healthy workers and community residents in a primary prevention setting. Time preference is one’s relative valuation for having a reward (eg, money) at present than at a later date. Time preference may affect the effectiveness of cognitive behavioral therapy. Objective: This RCT aimed to test the difference of intervention effect of an iCBT program on improving nonclinical depressive symptoms between two subgroups classified post-hoc on the basis of time preference among workers in Japan. Methods: All workers in one corporate group (approximate n=20,000) were recruited. Participants who fulfilled the inclusion criteria were randomly allocated to either intervention or control groups. Participants in the intervention group completed 6 weekly lessons and homework assignments within the iCBT program. The Beck Depression Inventory-II (BDI-II) and Kessler’s Psychological Distress Scale (K6) measures were obtained at baseline and 3-, 6-, and 12-month follow-ups. Two subgroups were defined by the median of time preference score at baseline. Results: Only few (835/20,000, 4.2%) workers completed the baseline survey. Of the 835 participants, 706 who fulfilled the inclusion criteria were randomly allocated to the intervention or control group. Participants who selected irrational time preference options were excluded (21 and 18 participants in the intervention and control groups, respectively). A three-way interaction (group [intervention/control] × time [baseline/follow-up] × time preference [higher/lower]) effect of iCBT was significant for BDI-II (t1147.42=2.33, P=.02) and K6 (t1254.04=2.51, P=.01) at the 3-month follow-up, with a greater effect of the iCBT in the group with higher time preference. No significant three-way interaction was found at the 6- and 12-month follow-ups. Conclusions: The effects of the iCBT were greater for the group with higher time preference at the shorter follow-up, but it was leveled off later. Workers with higher time preference may change their cognition or behavior more quickly, but these changes may not persist. Trial Registration: UMIN Clinical Trials Registry UMIN000014146; recptno=R000016466 (Archived by WebCite at

  • Restroom placard. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Internet of Things Buttons for Real-Time Notifications in Hospital Operations: Proposal for Hospital Implementation


    Background: Hospital staff frequently performs the same process hundreds to thousands of times a day. Customizable Internet of Things buttons are small, wirelessly-enabled devices that trigger specific actions with the press of an integrated button and have the potential to automate some of these repetitive tasks. In addition, IoT buttons generate logs of triggered events that can be used for future process improvements. Although Internet of Things buttons have seen some success as consumer products, little has been reported on their application in hospital systems. Objective: We discuss potential hospital applications categorized by the intended user group (patient or hospital staff). In addition, we examine key technological considerations, including network connectivity, security, and button management systems. Methods: In order to meaningfully deploy Internet of Things buttons in a hospital system, we propose an implementation framework grounded in the Plan-Do-Study-Act method. Results: We plan to deploy Internet of Things buttons within our hospital system to deliver real-time notifications in public-facing tasks such as restroom cleanliness and critical supply restocking. We expect results from this pilot in the next year. Conclusions: Overall, Internet of Things buttons have significant promise; future rigorous evaluations are needed to determine the impact of Internet of Things buttons in real-world health care settings.

  • Source:; Copyright: StockSnap; URL:; License: Public Domain (CC0).

    Using Mobile Apps to Assess and Treat Depression in Hispanic and Latino Populations: Fully Remote Randomized Clinical Trial


    Background: Most people with mental health disorders fail to receive timely access to adequate care. US Hispanic/Latino individuals are particularly underrepresented in mental health care and are historically a very difficult population to recruit into clinical trials; however, they have increasing access to mobile technology, with over 75% owning a smartphone. This technology has the potential to overcome known barriers to accessing and utilizing traditional assessment and treatment approaches. Objective: This study aimed to compare recruitment and engagement in a fully remote trial of individuals with depression who either self-identify as Hispanic/Latino or not. A secondary aim was to assess treatment outcomes in these individuals using three different self-guided mobile apps: iPST (based on evidence-based therapeutic principles from problem-solving therapy, PST), Project Evolution (EVO; a cognitive training app based on cognitive neuroscience principles), and health tips (a health information app that served as an information control). Methods: We recruited Spanish and English speaking participants through social media platforms, internet-based advertisements, and traditional fliers in select locations in each state across the United States. Assessment and self-guided treatment was conducted on each participant's smartphone or tablet. We enrolled 389 Hispanic/Latino and 637 non-Hispanic/Latino adults with mild to moderate depression as determined by Patient Health Questionnaire-9 (PHQ-9) score≥5 or related functional impairment. Participants were first asked about their preferences among the three apps and then randomized to their top two choices. Outcomes were depressive symptom severity (measured using PHQ-9) and functional impairment (assessed with Sheehan Disability Scale), collected over 3 months. Engagement in the study was assessed based on the number of times participants completed active surveys. Results: We screened 4502 participants and enrolled 1040 participants from throughout the United States over 6 months, yielding a sample of 348 active users. Long-term engagement surfaced as a key issue among Hispanic/Latino participants, who dropped from the study 2 weeks earlier than their non-Hispanic/Latino counterparts (P<.02). No significant differences were observed for treatment outcomes between those identifying as Hispanic/Latino or not. Although depressive symptoms improved (beta=–2.66, P=.006) over the treatment course, outcomes did not vary by treatment app. Conclusions: Fully remote mobile-based studies can attract a diverse participant pool including people from traditionally underserved communities in mental health care and research (here, Hispanic/Latino individuals). However, keeping participants engaged in this type of “low-touch” research study remains challenging. Hispanic/Latino populations may be less willing to use mobile apps for assessing and managing depression. Future research endeavors should use a user-centered design to determine the role of mobile apps in the assessment and treatment of depression for this population, app features they would be interested in using, and strategies for long-term engagement. Trial Registration: NCT01808976; (Archived by WebCite at

  • Wechat interface of a tertiary referral hospital. Source: Image created by the authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Social Media Landscape of the Tertiary Referral Hospitals in China: Observational Descriptive Study


    Background: Social media has penetrated all walks of life. Chinese health care institutions are increasingly utilizing social media to connect with their patients for better health service delivery. Current research has focused heavily on the use of social media in developed countries, with few studies exploring its usage in the context of developing countries, such as China. Tertiary hospitals in China are usually located in city centers, and they serve as medical hubs for multiple regions, with comprehensive and specialized medical care being provided. These hospitals are assumed to be the pioneers in creating official social media accounts to connect with their patients due to the fact that they appear to have more resources to support this innovative approach to communication and health care education. Objective: The objective of our study was to examine China’s best tertiary hospitals, as recognized by The National Health Commission of the People’s Republic of China (NHCPRC), and to map out the landscape of current social media usage by hospitals when engaging with patients. Methods: We examined the best 705 tertiary hospitals in China by collecting and analyzing data regarding their usage of popular Chinese social media apps Sina Weibo and WeChat. The specific data included (1) hospital characteristics (ie, time since established, number of beds, hospital type, and regions or localities) and (2) status of social media usage regarding two of the most popular local social media platforms in China (ie, time of initiation, number of followers, and number of tweets or posts). We further used a logistic regression model to test the association between hospital characteristics and social media adoption. Results: Of all, 76.2% (537/705) tertiary referral hospitals have created official accounts on either Sina Weibo or WeChat, with the latter being more popular among the two. In addition, our study suggests that larger and newer hospitals with greater resources are more likely to adopt social media, while hospital type and affiliation with universities are not significant predictors of social media adoption among hospitals. Conclusions: Our study demonstrated that hospitals are more inclined to use WeChat. The move by hospitals from Sina Weibo to WeChat indicates that patients are not satisfied by mere communication and that they now place more value on health service delivery. Meanwhile, utilizing social media requires comprehensive thinking from the hospital side. Once adopted, hospitals are encouraged to implement specific rules regarding social media usage. In the future, a long journey still lies ahead for hospitals in terms of operating their official social media accounts.

  • Source: iStock by Getty Images; Copyright: AlexRaths; URL:; License: Creative Commons Attribution (CC-BY).

    Cloud Computing for Infectious Disease Surveillance and Control: Development and Evaluation of a Hospital Automated Laboratory Reporting System


    Background: Outbreaks of several serious infectious diseases have occurred in recent years. In response, to mitigate public health risks, countries worldwide have dedicated efforts to establish an information system for effective disease monitoring, risk assessment, and early warning management for international disease outbreaks. A cloud computing framework can effectively provide the required hardware resources and information access and exchange to conveniently connect information related to infectious diseases and develop a cross-system surveillance and control system for infectious diseases. Objective: The objective of our study was to develop a Hospital Automated Laboratory Reporting (HALR) system based on such a framework and evaluate its effectiveness. Methods: We collected data for 6 months and analyzed the cases reported within this period by the HALR and the Web-based Notifiable Disease Reporting (WebNDR) systems. Furthermore, system evaluation indicators were gathered, including those evaluating sensitivity and specificity. Results: The HALR system reported 15 pathogens and 5174 cases, and the WebNDR system reported 34 cases. In a comparison of the two systems, sensitivity was 100% and specificity varied according to the reported pathogens. In particular, the specificity for Streptococcus pneumoniae, Mycobacterium tuberculosis complex, and hepatitis C virus were 99.8%, 96.6%, and 97.4%, respectively. However, the specificity for influenza virus and hepatitis B virus were only 79.9% and 47.1%, respectively. After the reported data were integrated with patients’ diagnostic results in their electronic medical records (EMRs), the specificity for influenza virus and hepatitis B virus increased to 89.2% and 99.1%, respectively. Conclusions: The HALR system can provide early reporting of specified pathogens according to test results, allowing for early detection of outbreaks and providing trends in infectious disease data. The results of this study show that the sensitivity and specificity of early disease detection can be increased by integrating the reported data in the HALR system with the cases’ clinical information (eg, diagnostic results) in EMRs, thereby enhancing the control and prevention of infectious diseases.

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  • Profiles of health information seeking and the current digital divide within a California population-based sample

    Date Submitted: Aug 14, 2018

    Open Peer Review Period: Aug 19, 2018 - Oct 14, 2018

    Background: Internet use for health information is important given the rise of eHealth integrating technology into healthcare. Despite perceived widespread use of the Internet, a persistent “digital...

    Background: Internet use for health information is important given the rise of eHealth integrating technology into healthcare. Despite perceived widespread use of the Internet, a persistent “digital divide” exists in which many individuals have ready access to the Internet and others do not. To date, most published reports have compared characteristics of Internet users seeking health information vs. non-users. However, there is little understanding of the differences between Internet users seeking health information online and users who do not. Understanding these differences could enable targeted outreach for health interventions and promotion of eHealth technologies. Objective: This study aims to assess population-level characteristics associated with types of Internet use, particularly for seeking online health information. Methods: The 2015-2016 California Health Interview Survey (CHIS) datasets were used for this study. Internet use was classified as: those who have never used the Internet (Never use), those who have ever used the Internet but not to search for health information in the last 12-months (Use not for health), and those who have ever used the Internet and have used it to search for health information in the last 12-months (Use for health). Weighted multinomial logistic regression was used to assess sociodemographic and health characteristics associated with types of Internet use. Findings are reported as odds ratios (OR) with 95% confidence intervals (CI). Results: Among 42,087 participants (weighted sample of 29,236,426), 19% reported Never Use of the Internet, 27.9% reported Use not for health, and 53.1% reported Use for health. Compared to Never Use, Use for health individuals were more likely to be younger (OR: 0.1 [CI: 0.1, 0.2] for ≥60 years vs <60 years), female (OR: 1.6 [CI: 1.3, 1.9] compared to males), non-Hispanic White (OR: 0.54 [CI: 0.4, 0.7] and OR: 0.2 [CI: 0.2, 0.4] for Latinos and African Americans, respectively), and have a higher socioeconomic status (400%+ Federal Poverty Guidelines OR: 1.3 [CI: 1.4, 2.4]). Overall, characteristics for the Use not for health and Use for health groups were similar, except for those with lower levels of education and respondents not having visited a physician in the last year. For these two characteristics Use not for health were more similar to Never Use. Conclusions: Findings indicate that a digital divide characterized by sociodemographic and health information exists across three types of users. Results reflect previous studies about the divide specifically with regards to disparities in use and access related to age, race/ ethnicity, and socioeconomic status. Disparities in health seeking online may reflect existing disparities in healthcare access extending into a new era of health technology. Findings support the need for interventions to target Internet access and health literacy among Never Use and Use not for health groups.

  • Data mining in the development of mHealth apps: assessing in-app navigation through Markov Chain analysis

    Date Submitted: Aug 16, 2018

    Open Peer Review Period: Aug 16, 2018 - Oct 11, 2018

    Background: Background: Mobile applications generate vast amounts of user data. In the mHealth domain, researchers are increasingly discovering the opportunities of these data to assess the engagement...

    Background: Background: Mobile applications generate vast amounts of user data. In the mHealth domain, researchers are increasingly discovering the opportunities of these data to assess the engagement levels of their developed mobile applications. To date however, the analysis of these data is often limited to descriptive statistics. Using the right data mining techniques, application log data can offer significantly deeper insights. Objective: Objective: The purpose of this study was to assess how more advanced data mining techniques offer an opportunity to dig deeper into the data and afford to discover application mHealth app usage patterns using Markov Chain and sequence clustering analysis. Methods: Methods: A transition matrix between the nine pages of the app was composed from which a Markov Chain was constructed, enabling intuitive user behavior analysis. Results: Results: Five session types of app use were distinguished through the analysis, two of which represented usage of the main intended functions as envisioned by the developers. The two main functions were further automatically reconstructed by means of sequence clustering. Conclusions: Conclusions: Using Markov Chains to assess in-app navigation presents an innovative method to evaluate mHealth interventions. The insights can be used to improve the navigation in the app, the flow between behavior change techniques and placement of features in the app. 

  • History Repeating Itself? Concerns about [Genetic] Testing in Primary Care

    Date Submitted: Aug 13, 2018

    Open Peer Review Period: Aug 15, 2018 - Oct 10, 2018

    Primary care physicians report low confidence in their genetic testing knowledge. Practitioners in the early 20th century similarly reported hesitations towards now-routine chemistry-based blood tests...

    Primary care physicians report low confidence in their genetic testing knowledge. Practitioners in the early 20th century similarly reported hesitations towards now-routine chemistry-based blood tests, e.g. counts, glucose, and cholesterol measurement. Physicians in 2017 say the same things about genetic testing: it is hard to incorporate into daily practice, not consistently useful, less important than other priorities, and technically difficult. Technologies that are now commonplace in clinical practice were approached overcautiously at inception, similar to genetic testing today.

  • Technical Support by Smart Glasses During a Mass Casualty Incident: A Randomized Controlled Simulation Trial for Technically Assisted Triage and Telemedical Application in Disaster Medicine

    Date Submitted: Aug 14, 2018

    Open Peer Review Period: Aug 15, 2018 - Oct 10, 2018

    Background: In order to treat many patients despite lacking personnel resources, triage is important in disaster medicine. Various triage algorithms help, but often are used incorrectly or not at all....

    Background: In order to treat many patients despite lacking personnel resources, triage is important in disaster medicine. Various triage algorithms help, but often are used incorrectly or not at all. One potential problem-solving approach is to support triage with Smart Glasses. Objective: In this study, augmented reality was used to display a triage algorithm and telemedicine assistance was enabled to compare the duration and quality of triage with a conventional one. Methods: A specific Android-app was designed for use with Smart Glasses, that add information in terms of augmented reality with two different methods: through the display of a triage algorithm in data glasses and a telemedical connection to a senior emergency physician realized by the integrated camera. A scenario was created as randomized simulation study in which 31 paramedics carried out a triage of 12 patients in three groups: without technical support (control group), with display of a triage algorithm, and with telemedical contact. Results: A total of 362 assessments were performed. Although being quick (16.6 s), in control group the accuracy was only 58.3%. By contrast, accuracy of 91.7% (p = 0.036) was achieved when using technical support via displaying the triage algorithm. Such triage took an average of 37.0 s. The triage wearing data glasses and being telemedically connected achieved 89.6% accuracy (p = 0.01) in 35.0 s. Conclusions: However, triage with data glasses required significantly more time. Whereas in the control group only a tally was recorded, Smart Glasses led to a digital capture of the triage results, which has many tactical advantages. We expect a high potential in the application of Smart Glasses in disaster scenarios when using telemedicine and augmented reality features to improve the quality of triage.

  • Using exploratory trials to identify relevant contexts and mechanisms in complex eHealth interventions: the ePRO example.

    Date Submitted: Aug 15, 2018

    Open Peer Review Period: Aug 15, 2018 - Oct 10, 2018

    Background: Designing appropriate studies for evaluating complex interventions, like eHealth solutions to support integrated care, remains a methodological challenge. With the many moving parts of com...

    Background: Designing appropriate studies for evaluating complex interventions, like eHealth solutions to support integrated care, remains a methodological challenge. With the many moving parts of complex interventions, it is not always clear how program activities are connected to anticipated and unanticipated outcomes. Exploratory trials can be used to uncover determinants (or mechanisms) to inform content theory that underpins complex interventions prior to designing a full evaluation plan. Objective: A multi-method exploratory trial of the electronic Patient Reported Outcome (ePRO) tool was conducted to uncover contexts, processes, and outcomes variables, and the mechanisms that link these variables prior to full-scale evaluation. ePRO is a mobile application and portal designed to support goal-oriented care in inter-disciplinary primary health care practices (clinical level integration). This paper offers methodological insight on how to use exploratory trial data to identify relevant context, process and outcome variables, as well as central (necessary to achieving outcomes) vs. peripheral (less critical and potentially context dependent) mechanisms at play. Methods: The four month trial was conducted in two primary health care practices in Toronto, Canada. Patients were randomized into control and intervention groups and compared pre and post on quality of life and activation outcome measures. Semi-structured interviews were conducted with providers and patients in the intervention group. Narrative analysis was used to uncover dominant mechanisms of the intervention to inform the interventions content theory (how context and process variables are linked to outcomes). Results: Seven providers, one administrator, and 16 patients (7-control, 9-intervention) participated in the study. Our study uncovered 33 context, process and outcome variables at play in the intervention. Narrative analysis of patient and provider interviews revealed dominant story lines that help to tease apart central and peripheral mechanisms driving the intervention. Provider and patient storylines centered-around fitting the new intervention into everyday work and life of patients and providers, and meaningfulness of the intervention. These themes were moderated by patient-provider relationships going into and throughout the intervention, their comfort with technology, and the research process. Conclusions: Identifying dominant storylines using narrative analysis helps to identify the most relevant context and process variables likely to influence on study outcomes. Normalization Process Theory emerges as a useful theory to uncover underlying mechanisms due to its emphasis on the social production and normalization of technological, processual, and social aspects of work; all found to be critical to our intervention. The number of complex, overlapping influencing variables suggests that complex interventions like ePRO require us to pay careful attention to central vs. peripheral mechanisms underlying the intervention. The narrative methods presented here is shown to be a useful tool to help uncover these mechanisms, helping to guide subsequent larger evaluation studies.

  • Use of commercial off-the-shelf devices for detection of manual gestures in surgery. A Systematic Literature Review

    Date Submitted: Aug 12, 2018

    Open Peer Review Period: Aug 15, 2018 - Oct 10, 2018

    Background: The increasingly pervasive presence of technology in the operating room (OR) raises the need to study the interaction between the surgeon and the computer system. A new generation of tools...

    Background: The increasingly pervasive presence of technology in the operating room (OR) raises the need to study the interaction between the surgeon and the computer system. A new generation of tools known as commercial off-the-shelf (COTS) devices that enable non-contact gesture-based human-computer interaction (HCI) are currently being explored as a solution in surgical environments. Objective: The aim of this systematic review was to provide an account of the state-of-the-art of COTS devices in the detection of manual gestures in surgery, and to identify their use as a simulation tool for teaching motor skills in minimally invasive surgery (MIS). Methods: A systematic literature review was conducted in PubMed, Embase, ScienceDirect and IEEE for articles published between January 2000 and 2016 on the use of COTS devices for gesture detection in surgical environments, and in simulation for surgical skills learning in MIS Results: A total of 2709 studies were identified, 76 of which met the search selection criteria. The Microsoft KinectTM and the Leap Motion ControllerTM were the most widely used COTS devices. The most common intervention was image manipulation in surgical and interventional radiology environments, followed by interaction with virtual reality environments for educational or interventional purposes; the possibility of using this technology to develop portable, low-cost simulators for skills learning in MIS was also examined. Given that the vast majority of articles found in this systematic review were proof-of-concept or prototype user and feasibility testing, we can conclude that this is a field that is still in the exploration phase in areas that require touchless manipulation in environments and settings that must adhere to asepsis and antisepsis protocols, such as angiography suites and operating rooms. Conclusions: COTS devices applied to hand and instrument GBIs in the field of simulation for skills learning and training in MIS could open up a promising field to achieve the ubiquitous training and pre-surgical warm-up.