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Journal Description

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

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

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

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


Recent Articles:

  • An oncologist working with artificial intelligence. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Using Artificial Intelligence (Watson for Oncology) for Treatment Recommendations Amongst Chinese Patients with Lung Cancer: Feasibility Study


    Background: Artificial intelligence (AI) is developing quickly in the medical field and can benefit both medical staff and patients. The clinical decision support system Watson for Oncology (WFO) is an outstanding representative AI in the medical field, and it can provide to cancer patients prompt treatment recommendations comparable with ones made by expert oncologists. WFO is increasingly being used in China, but limited reports on whether WFO is suitable for Chinese patients, especially patients with lung cancer, exist. Here, we report a retrospective study based on the consistency between the lung cancer treatment recommendations made for the same patient by WFO and by the multidisciplinary team at our center. Objective: The aim of this study was to explore the feasibility of using WFO for lung cancer cases in China and to ascertain ways to make WFO more suitable for Chinese patients with lung cancer. Methods: We selected all lung cancer patients who were hospitalized and received antitumor treatment for the first time at the Second Xiangya Hospital Cancer Center from September to December 2017 (N=182). WFO made treatment recommendations for all supported cases (n=149). If the actual therapeutic regimen (administered by our multidisciplinary team) was recommended or for consideration according to WFO, we defined the recommendations as consistent; if the actual therapeutic regimen was not recommended by WFO or if WFO did not provide the same treatment option, we defined the recommendations as inconsistent. Blinded second round reviews were performed by our multidisciplinary team to reassess the incongruent cases. Results: WFO did not support 18.1% (33/182) of recommendations among all cases. Of the 149 supported cases, 65.8% (98/149) received recommendations that were consistent with the recommendations of our team. Logistic regression analysis showed that pathological type and staging had significant effects on consistency (P=.004, odds ratio [OR] 0.09, 95% CI 0.02-0.45 and P<.001, OR 9.5, 95% CI 3.4-26.1, respectively). Age, gender, and presence of epidermal growth factor receptor gene mutations had no effect on consistency. In 82% (42/51) of the inconsistent cases, our team administered two China-specific treatments, which were different from the recommendations made by WFO but led to excellent outcomes. Conclusions: In China, most of the treatment recommendations of WFO are consistent with the recommendations of the expert group, although a relatively high proportion of cases are still not supported by WFO. Therefore, WFO cannot currently replace oncologists. WFO can improve the efficiency of clinical work by providing assistance to doctors, but it needs to learn the regional characteristics of patients to improve its assistive ability.

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

    Internet-Based and Mobile-Based General Practice: Cross-Sectional Survey


    Background: Globally, mHealth is increasing as a promising technology for promoting the quality of health care. Thus, a growing number of internet hospitals have been established in China to avail all its advantages. However, no study has investigated the service scope and patient satisfaction of the internet hospital to date. Objective: The objective of our study was to explore the features of outpatients in general practice, the disease information, and the satisfaction through an internet rating site. Methods: We collected data from the internet hospital of the First Affiliated Hospital, Zhejiang University between February 2016 and February 2017. Patients visited Web-based clinic via a computer or smartphone. The data included patients’ demographic characteristics, disease information, and patients’ comments. Results: We enrolled 715 patients with 365 health-related problems. All health conditions involved diseases ranging from internal medicine, surgery, gynecology and obstetrics, pediatrics, dermatology, ophthalmology, stomatology to emergency. Among them, 63.1% patients (451/715) visited traditional hospitals for further management, 25.3% (181/715) had prescriptions, laboratory, or imaging examination appointment, 1% (9/715) used emergency service, and 10% (74/715) needed routine follow-up. All patients received health education. Almost all patients gave positive feedback and 4-5-star rating. Conclusions: The internet hospital is suitable for all health conditions with high satisfaction only when patients have the access to internet via a computer or smartphone.

  • A patient diagnosed with hypertension is using a smart blood pressure monitor at home and monitors the real-time results on his tablet. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution + Noncommercial + ShareAlike (CC-BY-NC-SA).

    A Cloud-Based Virtual Outpatient Clinic for Patient-Centered Care: Proof-of-Concept Study


    Background: Most electronic health (eHealth) interventions offered to patients serve a single purpose and lack integration with other tools or systems. This is problematic because the majority of patients experience comorbidity and chronic disease, see multiple specialists, and therefore have different needs regarding access to patient data, communication with peers or providers, and self-monitoring of vital signs. A multicomponent digital health cloud service that integrates data sharing, collection, and communication could facilitate patient-centered care in combination with a hospital patient portal and care professionals. Objective: This study aimed to assess the feasibility and functionality of a new cloud-based and multicomponent outpatient clinic, the “Virtual Outpatient Clinic” (VOC). Methods: The VOC consists of 6 digital tools that facilitate self-monitoring (blood pressure, weight, and pain) and communication with peers and providers (chat and videoconferencing) connected to a cloud-based platform and the hospital patient portal to facilitate access to (self-collected) medical data. In this proof-of-concept study, 10 patients from both Departments of Internal Medicine and Dermatology (N=20) used all options of the VOC for 6 weeks. An eNurse offered support to participants during the study. We assessed the feasibility, usage statistics, content, adherence, and identified technical issues. Moreover, we conducted qualitative interviews with all participants by following a standard interview guide to identify user experiences, including barriers, facilitators, and potential effects. Results: Most participants successfully used all options of the VOC and were positive about different tools and apps and the integral availability of their information. The adherence was 37% (7/19) for weight scale, 58% (11/19) for blood pressure monitor, and 70% (14/20) and 85% (17/20) for pain score and daily questions, respectively. The adherence for personal health record was 65% (13/20) and 60% (12/20) for the patient portal system. Qualitative data showed that performance and effort expectancy scored high among participants, indicating that using the VOC is convenient, easy, and time-saving. Conclusions: The VOC is a promising integrated Web-based technology that combines self-management, data sharing, and communication between patients and professionals. The system can be personalized by connecting various numbers of components, which could make it a relevant tool for other patient groups. Before a system, such as the VOC, can be implemented in daily practice, prospective studies focused on evaluating outcomes, costs, and patient-centeredness are needed.

  • Women in São Paulo, Brazil. Source: Flickr; Copyright: Cássio Abreu; URL:; License: Creative Commons Attribution (CC-BY).

    Experience With the Use of an Online Community on Facebook for Brazilian Patients With Gestational Trophoblastic Disease: Netnography Study


    Background: The term gestational trophoblastic disease (GTD) includes both complete and partial moles, which are uncommon nonviable pregnancies with the potential to evolve into a malignancy known as gestational trophoblastic neoplasia. While highly curable, the potential for malignancy associated with molar pregnancies worries the patients, leading them to seek information on the internet. A Facebook page headed by Brazilian specialized physicians in GTD was created in 2013 to provide online support for GTD patients. Objective: The objective of our study was to describe the netnography of Brazilian patients with GTD on Facebook (FBGTD) and to evaluate whether their experiences differed depending on whether they received care in a Brazilian gestational trophoblastic disease reference center (BRC) or elsewhere. Methods: This was a cross-sectional study using G Suite Google Platform. The members of FBGTD were invited to participate in a survey from March 6 to October 5, 2017, and a netnographic analysis of interactions among the members was performed. Results: The survey was answered by 356 Brazilian GTD patients: 176 reference center patients (RCP) treated at a BRC and 180 nonreference center patients (NRCP) treated elsewhere. On comparing the groups, we found that RCP felt safer and more confident at the time of diagnosis of GTD (P=.001). RCP were more likely to utilize FBGTD subsequent to a referral by health assistants (P<.001), whereas NRCP more commonly discovered FBGTD through Web searches (P<.001). NRCP had higher educational levels (P=.009) and were more commonly on FBGTD for ≥ 6 months (P=.03). NRCP were more likely to report that doctors did not adequately explain GTD at diagnosis (P=.007), had more doubts about GTD treatment (P=.01), and were less likely to use hormonal contraception (P<.001). Overall, 89% (317/356) patients accessed the internet preferentially from home and using mobile phones, and 98% (349/354) patients declared that they felt safe reading the recommendations posted by FBGTD physicians. Conclusions: This netnographic analysis of GTD patients on FBGTD shows that an Web-based doctor-patient relationship can supplement the care for women with GTD. This resource is particularly valuable for women being cared for outside of established reference centers.

  • Interventional cardiology simulator. Source: Image created by the Authors; Copyright: Quentin Fischer; URL:; License: Licensed by JMIR.

    Use of Simulator-Based Teaching to Improve Medical Students’ Knowledge and Competencies: Randomized Controlled Trial


    Background: Simulator-based teaching for coronary angiography (CA) is an attractive educational tool for medical students to improve their knowledge and skills. Its pedagogical impact has not been fully evaluated yet. Objective: The aim of this study was to compare traditional face-to-face teaching with a simulator-based teaching for the acquisition of coronary anatomy knowledge and CAs interpretation. Methods: A total of 118 medical school students in their fourth to sixth year were prospectively randomized in 2 groups: (1) a control teaching group (n=59, CONT group) and (2) a simulator group (using the Mentice VIST-Lab CA simulator; n=59, SIM group). The CONT group received a PowerPoint-based course, whereas the SIM group received a simulator-based course including the same information. After the course, all students were evaluated by 40 multiple choice questions (maximum of 100 points), including questions on coronary anatomy (part 1), angiographic projections (part 2), and real CAs interpretation (part 3). Satisfaction of the students was also evaluated by a simple questionnaire. Results: Student characteristics were identical in both the groups: 62/118 (52.5%) were female and age was 22.6 (SD 1.4) years. Moreover, 35.6% (42/118) were in their fourth year, 35.6% (42/118) were in the fifth year, and 28.8% (34/118) in the sixth year. During the evaluation, SIM students had higher global scores compared with CONT students, irrespective of their year of medical school (59.5 [SD 10.8] points vs 43.7 [SD 11.3] points, P<.001). The same observations were noted for each part of the test (36.9 [SD 6.6] points vs 29.6 [SD 6.9] points, P<.001; 5.9 [SD 3.0] points vs 3.1 [SD 2.8] points, P<.001; and 16.8 [SD 6.9] points vs 10.9 [SD 6.5] points, P<.001; for parts 1, 2, and 3, respectively). Student satisfaction was higher in the SIM group compared with the CONT group (98% vs 75%, P<.001). Conclusions: This study suggests that simulator-based teaching could potentially improve students’ knowledge of coronary anatomy, angiography projections, and interpretation of real clinical cases, suggesting better clinical skills. These results should encourage further evaluation of simulator-based teaching in other medical specialties and how they can translate into clinical practice.

  • A user interacting with the four-person linear visualization. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Exploring Genetic Data Across Individuals: Design and Evaluation of a Novel Comparative Report Tool


    Background: The growth in the availability of personal genomic data to nonexperts poses multiple challenges to human-computer interaction research; data are highly sensitive, complex, and have health implications for individuals and families. However, there has been little research on how nonexpert users explore their genomic data. Objective: We focus on how to support nonexperts in exploring and comparing their own personal genomic report with those of other people. We designed and evaluated CrossGenomics, a novel tool for comparing personal genetic reports, which enables exploration of shared and unshared genetic variants. Focusing on communicating comparative impact, rarity, and certainty, we evaluated alternative novel interactive prototypes. Methods: We conducted 3 user studies. The first focuses on assessing the usability and understandability of a prototype that facilitates the comparison of reports from 2 family members. Following a design iteration, we studied how various prototypes support the comparison of genetic reports of a 4-person family. Finally, we evaluated the needs of early adopters—people who share their genetic reports publicly for comparing their genetic reports with that of others. Results: In the first study, sunburst- and Venn-based comparisons of two genomes led to significantly higher domain comprehension, compared with the linear comparison and with the commonly used tabular format. However, results show gaps between objective and subjective comprehension, as sunburst users reported significantly lower perceived understanding and higher levels of confusion than the users of the tabular report. In the second study, users who were allowed to switch between the different comparison views presented higher comprehension levels, as well as more complex reasoning than users who were limited to a single comparison view. In the third study, 35% (17/49) reported learning something new from comparing their own data with another person’s data. Users indicated that filtering and toggling between comparison views were the most useful features. Conclusions: Our findings (1) highlight features and visualizations that show strengths in facilitating user comprehension of genomic data, (2) demonstrate the value of affording users the flexibility to examine the same report using multiple views, and (3) emphasize users’ needs in comparison of genomic data. We conclude with design implications for engaging nonexperts with complex multidimensional genomic data.

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

    Digital Health in Melanoma Posttreatment Care in Rural and Remote Australia: Systematic Review


    Background: The melanoma incidence and mortality rates in rural and remote communities are exponentially higher than in urban areas. Digital health could be used to close the urban/rural gap for melanoma and improve access to posttreatment and support care services. Objective: The aim of this review was to understand how digital health is currently used for melanoma posttreatment care and determine the benefits for Australian rural and remote areas. Methods: A systematic search of PubMed, Medline, PsycINFO, and Scopus was conducted in March 2018. Findings were clustered per type of intervention and related direct outcomes. Results: Five studies met the inclusion criteria, but none investigated the benefits of digital health for melanoma posttreatment care in rural and remote areas of Australia. Some empirical studies demonstrated consumers’ acceptance of digital intervention for posttreatment care. The findings did not take into consideration individual, psychological, and socioeconomic factors, even though studies show their significant impacts on melanoma quality of aftercare. Conclusions: Digital interventions may be used as an adjunct service by clinicians during melanoma posttreatment care, especially in regions that are less-resourced by practitioners and health infrastructure, such as rural and remote Australia. Technology could be used to reduce the disparity in melanoma incidence, mortality rates, and accessibility to posttreatment care management between urban and rural/remote populations.

  • A blended cognitive behavioral therapy (CBT) session. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Web-Based Cognitive Behavioral Therapy Blended With Face-to-Face Sessions for Major Depression: Randomized Controlled Trial


    Background: Meta-analyses of several randomized controlled trials have shown that cognitive behavioral therapy (CBT) has comparable efficacy to antidepressant medication, but therapist availability and cost-effectiveness is a problem. Objective: This study aimed to evaluate the effectiveness of Web-based CBT blended with face-to-face sessions that reduce therapist time in patients with major depression who were unresponsive to antidepressant medications. Methods: A 12-week, assessor-masked, parallel-group, waiting- list controlled, randomized trial was conducted at 3 medical institutions in Tokyo. Outpatients aged 20-65 years with a primary diagnosis of major depression who were taking ≥1 antidepressant medications at an adequate dose for ≥6 weeks and had a 17-item GRID-Hamilton Depression Rating Scale (HAMD) score of ≥14 were randomly assigned (1:1) to blended CBT or waiting-list groups using a computer allocation system, stratified by the study site with the minimization method, to balance age and baseline GRID-HAMD score. The CBT intervention was given in a combined format, comprising a Web-based program and 12 45-minute face-to-face sessions. Thus, across 12 weeks, a participant could receive up to 540 minutes of contact with a therapist, which is approximately two-thirds of the therapist contact time provided in the conventional CBT protocol, which typically provides 16 50-minute sessions. The primary outcome was the alleviation of depressive symptoms, as measured by a change in the total GRID-HAMD score from baseline (at randomization) to posttreatment (at 12 weeks). Moreover, in an exploratory analysis, we investigated whether the expected positive effects of the intervention were sustained during follow-up, 3 months after the posttreatment assessment. Analyses were performed on an intention-to-treat basis, and the primary outcome was analyzed using a mixed-effects model for repeated measures. Results: We randomized 40 participants to either blended CBT (n=20) or waiting-list (n=20) groups. All patients completed the 12-week treatment protocol and were included in the intention-to-treat analyses. Participants in the blended CBT group had significantly alleviated depressive symptoms at week 12, as shown by greater least squares mean changes in the GRID-HAMD score, than those in the waiting list group (−8.9 points vs −3.0 points; mean between-group difference=−5.95; 95% CI −9.53 to −2.37; P<.001). The follow-up effects within the blended CBT group, as measured by the GRID-HAMD score, were sustained at the 3-month follow-up (week 24) and posttreatment (week 12): posttreatment, 9.4 (SD 5.2), versus follow-up, 7.2 (SD 5.7); P=.009. Conclusions: Although our findings warrant confirmation in larger and longer term studies with active controls, these suggest that a combined form of CBT is effective in reducing depressive symptoms in patients with major depression who are unresponsive to antidepressant medications. Trial Registration: University Hospital Medical Information Network Clinical Trials Registry: UMIN000009242; (Archived by WebCite at http://www.webcitation. org/729VkpyYL)

  • Robotic services for older adults. Source: Image created by the Authors; Copyright: Filippo Cavallo; URL:; License: Creative Commons Attribution (CC-BY).

    Robotic Services Acceptance in Smart Environments With Older Adults: User Satisfaction and Acceptability Study


    Background: In Europe, the population of older people is increasing rapidly. Many older people prefer to remain in their homes but living alone could be a risk for their safety. In this context, robotics and other emerging technologies are increasingly proposed as potential solutions to this societal concern. However, one-third of all assistive technologies are abandoned within one year of use because the end users do not accept them. Objective: The aim of this study is to investigate the acceptance of the Robot-Era system, which provides robotic services to permit older people to remain in their homes. Methods: Six robotic services were tested by 35 older users. The experiments were conducted in three different environments: private home, condominium, and outdoor sites. The appearance questionnaire was developed to collect the users’ first impressions about the Robot-Era system, whereas the acceptance was evaluated through a questionnaire developed ad hoc for Robot-Era. Results: A total of 45 older users were recruited. The people were grouped in two samples of 35 participants, according to their availability. Participants had a positive impression of Robot-Era robots, as reflected by the mean score of 73.04 (SD 11.80) for DORO’s (domestic robot) appearance, 76.85 (SD 12.01) for CORO (condominium robot), and 75.93 (SD 11.67) for ORO (outdoor robot). Men gave ORO’s appearance an overall score higher than women (P=.02). Moreover, participants younger than 75 years understood more readily the functionalities of Robot-Era robots compared to older people (P=.007 for DORO, P=.001 for CORO, and P=.046 for ORO). For the ad hoc questionnaire, the mean overall score was higher than 80 out of 100 points for all Robot-Era services. Older persons with a high educational level gave Robot-Era services a higher score than those with a low level of education (shopping: P=.04; garbage: P=.047; reminding: P=.04; indoor walking support: P=.006; outdoor walking support: P=.03). A higher score was given by male older adults for shopping (P=.02), indoor walking support (P=.02), and outdoor walking support (P=.03). Conclusions: Based on the feedback given by the end users, the Robot-Era system has the potential to be developed as a socially acceptable and believable provider of robotic services to facilitate older people to live independently in their homes.

  • Source: Flickr; Copyright: mista stagga lee; URL:; License: Creative Commons Attribution (CC-BY).

    Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data


    Background: Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disease (COPD) exacerbations, with a view to instituting timely treatment. However, algorithms to identify exacerbations result in frequent false-positive results and increased workload. Machine learning, when applied to predictive modelling, can determine patterns of risk factors useful for improving prediction quality. Objective: Our objectives were to (1) establish whether machine learning techniques applied to telemonitoring datasets improve prediction of hospital admissions and decisions to start corticosteroids, and (2) determine whether the addition of weather data further improves such predictions. Methods: We used daily symptoms, physiological measures, and medication data, with baseline demography, COPD severity, quality of life, and hospital admissions from a pilot and large randomized controlled trial of telemonitoring in COPD. We linked weather data from the United Kingdom meteorological service. We used feature selection and extraction techniques for time series to construct up to 153 predictive patterns (features) from symptom, medication, and physiological measurements. We used the resulting variables to construct predictive models fitted to training sets of patients and compared them with common symptom-counting algorithms. Results: We had a mean 363 days of telemonitoring data from 135 patients. The two most practical traditional score-counting algorithms, restricted to cases with complete data, resulted in area under the receiver operating characteristic curve (AUC) estimates of 0.60 (95% CI 0.51-0.69) and 0.58 (95% CI 0.50-0.67) for predicting admissions based on a single day’s readings. However, in a real-world scenario allowing for missing data, with greater numbers of patient daily data and hospitalizations (N=57,150, N+=55, respectively), the performance of all the traditional algorithms fell, including those based on 2 days’ data. One of the most frequently used algorithms performed no better than chance. All considered machine learning models demonstrated significant improvements; the best machine learning algorithm based on 57,150 episodes resulted in an aggregated AUC of 0.74 (95% CI 0.67-0.80). Adding weather data measurements did not improve the predictive performance of the best model (AUC 0.74, 95% CI 0.69-0.79). To achieve an 80% true-positive rate (sensitivity), the traditional algorithms were associated with an 80% false-positive rate: our algorithm halved this rate to approximately 40% (specificity approximately 60%). The machine learning algorithm was moderately superior to the best symptom-counting algorithm (AUC 0.77, 95% CI 0.74-0.79 vs AUC 0.66, 95% CI 0.63-0.68) at predicting the need for corticosteroids. Conclusions: Early detection and management of COPD remains an important goal given its huge personal and economic costs. Machine learning approaches, which can be tailored to an individual’s baseline profile and can learn from experience of the individual patient, are superior to existing predictive algorithms and show promise in achieving this goal. Trial Registration: International Standard Randomized Controlled Trial Number ISRCTN96634935; (Archived by WebCite at

  • My UmcUtrecht patient portal (montage). Source: UMC Utrecht; Copyright: UMC Utrecht; URL:; License: Licensed by JMIR.

    Use and the Users of a Patient Portal: Cross-Sectional Study


    Background: Patient portals offer patients access to their medical information and tools to communicate with health care providers. It has been shown that patient portals have the potential to positively impact health outcomes and efficiency of health care. It is therefore important that health care organizations identify the patients who use or do not use the patient portal and explore the reasons in either case. The Unified Theory of Acceptance and Use of Technology (UTAUT) is a frequently used theory for explaining the use of information technology. It consists of the following constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention to use. Objective: This study aimed to explore the prevalence of patient portal use and the characteristics of patients who use or do not use a patient portal. The main constructs of UTAUT, together with demographics and disease- and care-related characteristics, have been measured to explore the predictive factors of portal use. Methods: A cross-sectional study was conducted in the outpatient departments for adult patients of a university hospital in the Netherlands. Following outcomes were included: self-reported portal use, characteristics of users such as demographics, disease- and care-related data, eHealth literacy (modified score), and scores of UTAUT constructs. Descriptive analyses and univariate and multivariate logistic regression were also conducted. Results: In the analysis, 439 adult patients were included. Furthermore, 32.1% (141/439) identified as being a user of the patient portal; 31.2% (137/439) indicated as nonusers, but being aware of the existence of the portal; and 36.6% (161/439) as being nonusers not aware of the existence of the portal. In the entire study population, the factors of being chronically ill (odds ratio, OR 1.62, 95% CI 1.04-2.52) and eHealth literacy (modified score; OR 1.12, 95% CI 1.07-1.18) best predicted portal use. In users and nonusers who were aware of the portal, UTAUT constructs were added to the multivariate logistic regression, with chronically ill and modified eHealth literacy sum score. Effort expectancy (OR 13.02, 95% CI 5.68-29.87) and performance expectancy (OR 2.84, 95% CI 1.65-4.90) are shown to significantly influence portal use in this group. Conclusions: Approximately one-third of the patients of a university hospital self-reported using the patient portal; most expressed satisfaction. At first sight, being chronically ill and higher scores on the modified eHealth literacy scale explained portal use. Adding UTAUT constructs to the model revealed that effort expectancy (ease of use and knowledge and skills related to portal use) and performance expectancy (perceived usefulness) influenced portal use. Interventions to improve awareness of the portal and eHealth literacy skills of patients and further integration of the patient portal in usual face-to-face care are needed to increase use and potential subsequent patient benefits.

  • Source: Immunization Action Coalition; Copyright: Centers for Disease Control and Prevention; URL:; License: Public Domain (CC0).

    Discordance Between Human Papillomavirus Twitter Images and Disparities in Human Papillomavirus Risk and Disease in the United States: Mixed-Methods Analysis


    Background: Racial and ethnic minorities are disproportionately affected by human papillomavirus (HPV)-related cancer, many of which could have been prevented with vaccination. Yet, the initiation and completion rates of HPV vaccination remain low among these populations. Given the importance of social media platforms for health communication, we examined US-based HPV images on Twitter. We explored inconsistencies between the demographics represented in HPV images and the populations that experience the greatest burden of HPV-related disease. Objective: The objective of our study was to observe whether HPV images on Twitter reflect the actual burden of disease by select demographics and determine to what extent Twitter accounts utilized images that reflect the burden of disease in their health communication messages. Methods: We identified 456 image tweets about HPV that contained faces posted by US users between November 11, 2014 and August 8, 2016. We identified images containing at least one human face and utilized Face++ software to automatically extract the gender, age, and race of each face. We manually annotated the source accounts of these tweets into 3 types as follows: government (38/298, 12.8%), organizations (161/298, 54.0%), and individual (99/298, 33.2%) and topics (news, health, and other) to examine how images varied by message source. Results: Findings reflected the racial demographics of the US population but not the disease burden (795/1219, 65.22% white faces; 140/1219, 11.48% black faces; 71/1219, 5.82% Asian faces; and 213/1219, 17.47% racially ambiguous faces). Gender disparities were evident in the image faces; 71.70% (874/1219) represented female faces, whereas only 27.89% (340/1219) represented male faces. Among the 11-26 years age group recommended to receive HPV vaccine, HPV images contained more female-only faces (214/616, 34.3%) than males (37/616, 6.0%); the remainder of images included both male and female faces (365/616, 59.3%). Gender and racial disparities were present across different image sources. Faces from government sources were more likely to depict females (n=44) compared with males (n=16). Of male faces, 80% (12/15) of youth and 100% (1/1) of adults were white. News organization sources depicted high proportions of white faces (28/38, 97% of female youth and 12/12, 100% of adult males). Face++ identified fewer faces compared with manual annotation because of limitations with detecting multiple, small, or blurry faces. Nonetheless, Face++ achieved a high degree of accuracy with respect to gender, race, and age compared with manual annotation. Conclusions: This study reveals critical differences between the demographics reflected in HPV images and the actual burden of disease. Racial minorities are less likely to appear in HPV images despite higher rates of HPV incidence. Health communication efforts need to represent populations at risk better if we seek to reduce disparities in HPV infection.

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  • Social media coverage of scientific articles immediately after publication predicts subsequent citations: #SoMe_Impact Score

    Date Submitted: Sep 21, 2018

    Open Peer Review Period: Sep 25, 2018 - Nov 20, 2018

    Background: Social media coverage is increasingly used to spread the message of scientific publications. Traditionally, the scientific impact of an article is measured by the number of citations. At a...

    Background: Social media coverage is increasingly used to spread the message of scientific publications. Traditionally, the scientific impact of an article is measured by the number of citations. At a journal level, this conventionally matures over a two-year period and it is challenging to gauge impact around the time of publication. Objective: to assess whether online attention is associated with citations and to develop a predictive model that assigns relative importance to different elements of social media coverage: the #SoMe_Impact score. Methods: We included all original articles published in 2015 in a selection of the highest-impact journals: The New England Journal of Medicine (NEJM), The Lancet, The Journal of the American Medical Association (JAMA), Nature, Cell and Science. We first characterised the change in Altmetric score over time by taking a single month’s sample of recently published articles from the same journals and gathered Altmetric data daily from the time of publication to create a mixed-effects spline models. We then obtained the overall weighted Altmetric score for all articles from 2015, the unweighted data for each Altmetric component and the two-year citation count from Scopus for each of these articles for 2016-2017. We created a stepwise multivariable linear regression model to develop a #SoME_Score that was predictive of two-year citations. The score was validated using a dataset of articles from the same journals published in 2016. Results: In our unselected sample of 145 recently published articles, social media coverage appeared to plateau approximately 14 days after publication. A total of 3,150 articles with a median citation count of 16 (IQR 5-33) and Altmetric score of 72 (IQR 28-169) were included for analysis. On multivariable regression, compared to articles in the lowest quantile of #SoME_Score, articles in the second, third and upper quantile had 21.2, 44.2 and 99.2 more citations, respectively. On the validation dataset, #SoME_Score model outperformed the Altmetric score (adjusted R2 0.17 vs 0.06, P<.001). Conclusions: Social media attention predicts citations and could be used as an early surrogate measure of scientific impact. Due to the cross-sectional study design, we cannot determine whether correlation relates to causation. Clinical Trial: NA

  • Smartphone-based use of the photoplethysmography technique to detect atrial fibrillation in primary care: a diagnostic accuracy study of the FibriCheck application

    Date Submitted: Sep 21, 2018

    Open Peer Review Period: Sep 25, 2018 - Nov 20, 2018

    Background: Current guidelines of the European Society of Cardiology recommend opportunistic screening in people aged ≥65 years by pulse palpation and, if irregular, a 12-lead electrocardiogram (ECG...

    Background: Current guidelines of the European Society of Cardiology recommend opportunistic screening in people aged ≥65 years by pulse palpation and, if irregular, a 12-lead electrocardiogram (ECG). However, evolving technology may offer new opportunities to allow a better penetrance of screening in the general population at relatively low cost and with minimal logistic efforts, which may further lower the threshold for screening. Smartphones may offer an interesting modality to aid AF diagnosis, as their use has exponentially increased in recent years and is continuing to grow. Objective: This study tested the diagnostic accuracy of the FibriCheck AF algorithm for the detection of atrial fibrillation (AF) based on smartphone photoplethysmography (PPG) and single-lead electrocardiography (ECG) signals. Methods: A convenience sample of patients, aged 65 and older, with and without a known history of AF, was recruited from 17 primary care facilities. Patients with an active pacemaker rhythm were excluded. A PPG signal was obtained with the backside camera of an iPhone 5S. Simultaneously, a single‑lead ECG was registered using a dermal patch with a wireless connection to the same smartphone. PPG and single-lead ECG signals were analysed using the FibriCheck AF algorithm. At the same time, a 12‑lead ECG was obtained and interpreted off-line by independent cardiologists to determine the presence of AF. Results: A total of 102/223 subjects (46%) were in AF. PPG signal quality was sufficient for analysis in 93%, and single‑lead ECG quality was sufficient in 94% of the participants. After removing insufficient quality measurements, the sensitivity and specificity were 96% (95% CI 89-99%) and 97% (95% CI 91-99%) for the PPG signal versus 95% (95% CI 88-98%) and 97% (95% CI 91-99%) for the single‑lead ECG, respectively. False-positive results were mainly due to premature ectopic beats. In 196 subjects where the signal quality of both techniques was adequate, PPG and single‑lead ECG yielded a similar diagnosis in 192 subjects (98%). Conclusions: The FibriCheck AF algorithm had a very good sensitivity and specificity to detect AF based on both the smartphone PPG and the single-lead ECG signals in a primary care convenience sample.

  • An ethical framework for the regulation of participatory disease surveillance systems

    Date Submitted: Sep 20, 2018

    Open Peer Review Period: Sep 25, 2018 - Nov 20, 2018

    Advances made in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging Web-based communi...

    Advances made in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging Web-based communities of volunteer citizens to report symptoms of public health threats and also by empowering individuals to promptly respond to them. However, such Web-based model raises its own set of ethical issues, on top of those inherent to more traditional forms of public health surveillance. Research ethics is undergoing significant changes in the digital era where it is not sufficient to consider only participants’ physical and psychological well-being, but also the protection of their sensitive data. In this paper, the Web-based platform of Influenzanet is used as a case study to illustrate those ethical challenges which participant-surveillance-systems involving the use of Web-based platforms and mobile apps have to deal with. These ethical challenges include the issues of electronic consent, the protection of participants’ privacy and the promotion of justice. Our analysis is followed by recommendations to strengthen ethical approaches in the field of Web-based public health surveillance, with a particular focus on the role of research ethics committees.

  • Design and Implementation of a Novel System for Correcting Posture through the Use of a Wearable Necklace Sensor

    Date Submitted: Sep 21, 2018

    Open Peer Review Period: Sep 25, 2018 - Nov 20, 2018

    Background: To our knowledge, few studies have examined the use of wearable sensing devices to effectively integrate information communication technologies and apply them to health care issues (partic...

    Background: To our knowledge, few studies have examined the use of wearable sensing devices to effectively integrate information communication technologies and apply them to health care issues (particularly those pertaining to posture correction). Objective: A novel system for posture correction involving the application of wearable sensing technology was developed in this study. Methods: The newly developed system consists of the combination of three subsystems, namely, a smart necklace, smart phone, and notebook computer. The gravitational acceleration data of a user is collected and analyzed by an MPU-6050 sensor housed in the smart necklace when the necklace is worn, with that data being used by the necklace to determine the user's upper body posture. When poor posture is detected by the necklace, the necklace sends the user’s smart phone a reminder to correct his or her posture; a mobile app that was also developed as part of the study allows the necklace to transmit such messages to the phone. The standard values (base values for posture assessment) of the necklace can also be set through the app, as can the timing of the aforementioned reminders and the activation of the posture image calibration function on the notebook computer. The notebook computer is enabled to use a depth camera to read the relevant data, to identify the skeletal structure and joint reference points of the user, and to compute calculations relating to those reference points, after which the computer then sends signals to the necklace to enable calibration of the necklace's standard values. Results: The system effectively enables a user to monitor and correct his or her own posture, which in turn will assist the user in preventing spine-related diseases and, consequently, living a more effective and healthy life. Conclusions: The proposed system makes it possible for: 1) the user to self-correct his or her posture without resorting to the use of heavy, thick, or stuffy corrective clothing; 2) the necklace's standard values to be quickly calibrated via the use of posture imaging; and 3) the need for complex wiring to be eliminated through the effective application of the Internet of Things, as well as by implementing wireless communication between the smart necklace, smart phone, and notebook computer.

  • Development and Usability Testing of a Smartphone Technology for the Self-Management of Pediatric Concussion

    Date Submitted: Sep 20, 2018

    Open Peer Review Period: Sep 24, 2018 - Nov 19, 2018

    Background: Concussion is a common injury amongst Canadian children and adolescents that leads to a range of neurobehavioral deficits. However, noticeable gaps continue to exist in the management of p...

    Background: Concussion is a common injury amongst Canadian children and adolescents that leads to a range of neurobehavioral deficits. However, noticeable gaps continue to exist in the management of pediatric concussion with inadequate application of best practice guidelines that can lead to poor health outcomes. Objective: To describe the development and assess the usability of a smartphone application to aid youth in self-managing concussion. A secondary objective was to assess the usefulness of the application. Methods: An agile user-centered design approach was used to develop the technology, followed by a formative lab-based usability study for assessment and improvement proposals. Youth ages 10 to 18 years with a history of concussion and healthcare professionals involved in concussion management were recruited. The study included participants performing 12 tasks with the smartphone application while using the ‘think aloud’ protocol, administration of the System Usability Scale (SUS), post-test questionnaire, and a semi-structured interview. Results: Developed a smartphone application prototype ‘NeuroCare’ that is an easily accessible pediatric concussion management intervention which provides easy access to expert informed concussion management strategies and helps guide youth in self-managing and tracking their concussion recovery. Seven youth ages 10 to 18 years with a history of concussion and seven healthcare professionals were recruited. The mean SUS score was 81.9, mean task success rates were greater than 90% for 92% (11/12) of tasks, 92% (11/12) of tasks had a total error frequency of less than 11 errors, and mean task completion times were less than 2 minutes for 100% of tasks. Conclusions: Results suggest this application has high usability, is acceptable to users, and may be useful in helping youth self-manage concussion.

  • Designing a Conversational Sequence for a Brief Motivational Interview for Stress Management on a Web-Based Text Messaging App: Qualitative Case Study with Graduate Students

    Date Submitted: Sep 19, 2018

    Open Peer Review Period: Sep 22, 2018 - Nov 17, 2018

    Background: In addition to addiction and substance abuse, motivational interviewing (MI) is increasingly being integrated in treating other clinical issues such as mental health problems. Despite many...

    Background: In addition to addiction and substance abuse, motivational interviewing (MI) is increasingly being integrated in treating other clinical issues such as mental health problems. Despite many technological adaptations of MI, most of them have focused on delivering the action-oriented treatment, leaving its relational component unexplored or vaguely described. This study intends an early design of a conversational sequence of both technical and relational components of MI for a mental health concern. Objective: This case study aims to design a conversational sequence for a brief motivational interview to be delivered by a Web-based text messaging application (“chatbot”) and investigate its conversational experience for stress management with graduate students. Methods: A brief conversational sequence was designed by incorporating both technical (change talk) and relational (O-A-R-S) components of MI, inspired by the summons-answer sequence by Schegloff. A Web-based text messaging app, Bonobot, was built as a research prototype to deliver the sequence in an online conversation. A total of 30 full-time graduate students who self-reported stress in regard of their school life were recruited for a survey of demographic information and perceived stress (PSS-10), and a semi-structured interview. Interviews were transcribed verbatim and analyzed by Braun and Clarke’s thematic method. Themes that reflect the process, impact of, and needs for the conversational experience are reported. Results: Participants had a high level of perceived stress (M=22.5, SD=5.0). Our findings include themes as follows: Evocative Questions and Clichéd Feedback; Self-Reflection and Potential Consolation; and Need for Information and Contextualized Feedback. Participants particularly favored the relay of change talk questions, but were less satisfied with the emotional responses that filled in-between. Change talk was a good means of reflecting on themselves, and some of Bonobot’s encouragements related to graduate school life were appreciated. Participants suggested the conversation provide informational support, as well as more personalized emotional feedback. Conclusions: A conversational sequence that incorporates technical and relational components of MI was presented in this case study. Participant feedback suggests sequencing change talk questions and emotional responses can facilitate a conversation for stress management, with change talk possibly offering a chance of self-reflection. More diversified sequences, along with more contextualized emotional feedback, should follow to offer better conversational experience and to confirm any empirical effect. Clinical Trial: n/a