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Journal Description

The Journal of Medical Internet Research (JMIR), now in its 21st 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 2019: 5.03), ranking Q1 in the medical informatics category, and is also the largest journal in the field. The journal focuses on emerging technologies, medical devices, apps, engineering, telehealth and informatics applications for patient education, prevention, population health and clinical care. As a 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, and which together receive over 6.000 submissions a year. 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 journal but can simply transfer it between journals. 

As an open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as with 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:

  • Source: Freepik; Copyright: diana.grytsku; URL:; License: Licensed by JMIR.

    Increased Internet Searches for Insomnia as an Indicator of Global Mental Health During the COVID-19 Pandemic: Multinational Longitudinal Study


    Background: Real-time global mental health surveillance is urgently needed for tracking the long-term impact of the COVID-19 pandemic. Objective: This study aimed to use Google Trends data to investigate the impact of the pandemic on global mental health by analyzing three keywords indicative of mental distress: “insomnia,” “depression,” and “suicide.” Methods: We examined increases in search queries for 19 countries. Significant increases were defined as the actual daily search value (from March 20 to April 19, 2020) being higher than the 95% CIs of the forecast from the 3-month baseline via ARIMA (autoregressive integrated moving average) modeling. We examined the correlation between increases in COVID-19–related deaths and the number of days with significant increases in search volumes for insomnia, depression, and suicide across multiple nations. Results: The countries with the greatest increases in searches for insomnia were Iran, Spain, the United States, and Italy; these countries exhibited a significant increase in insomnia searches on more than 10 of the 31 days observed. The number of COVID-19–related deaths was positively correlated to the number of days with an increase in searches for insomnia in the 19 countries (ρ=0.64, P=.003). By contrast, there was no significant correlation between the number of deaths and increases in searches for depression (ρ=–0.12, P=.63) or suicide (ρ=–0.07, P=.79). Conclusions: Our analysis suggests that insomnia could be a part of routine mental health screening during the COVID-19 pandemic.

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

    Use of Telemedicine for Chronic Liver Disease at a Single Care Center During the COVID-19 Pandemic: Prospective Observational Study


    Background: The COVID-19 outbreak has overwhelmed and altered health care systems worldwide, with a substantial impact on patients with chronic diseases. The response strategy has involved implementing measures like social distancing, and care delivery modalities like telemedicine have been promoted to reduce the risk of transmission. Objective: The aim of this study was to analyze the benefits of using telemedicine services for patients with chronic liver disease (CLD) at a tertiary care center in Italy during the COVID-19–mandated lockdown. Methods: From March 9 to May 3, 2020, a prospective observational study was conducted in the Liver Unit of the University Hospital of Naples Federico II to evaluate the impact of (1) a fully implemented telemedicine program, partially restructured in response to COVID-19 to include video consultations; (2) extended hours of operation for helpline services; and (3) smart-working from home to facilitate follow-up visits for patients with CLD while adhering to social distancing regulations. Results: During the lockdown in Italy, almost 400 visits were conducted using telemedicine; only patients requiring urgent care were admitted to a non–COVID-19 ward of our hospital. Telemedicine services were implemented not only for follow-up visits but also to screen patients prior to hospital admission and to provide urgent evaluations during complications. Of the nearly 1700 patients with CLD who attended a follow-up visit at our Liver Unit, none contracted COVID-19, and there was no need to alter treatment schedules. Conclusions: Telemedicine was a useful tool for following up patients with CLD and for reducing the impact of the COVID-19 pandemic. This system of health care delivery was appreciated by patients since it gave them the opportunity to be in contact with physicians while respecting social distancing rules.

  • A picture with Food and Amazon Echo, smart devices. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    A Personalized Voice-Based Diet Assistant for Caregivers of Alzheimer Disease and Related Dementias: System Development and Validation


    Background: The world’s aging population is increasing, with an expected increase in the prevalence of Alzheimer disease and related dementias (ADRD). Proper nutrition and good eating behavior show promise for preventing and slowing the progression of ADRD and consequently improving patients with ADRD’s health status and quality of life. Most ADRD care is provided by informal caregivers, so assisting caregivers to manage patients with ADRD’s diet is important. Objective: This study aims to design, develop, and test an artificial intelligence–powered voice assistant to help informal caregivers manage the daily diet of patients with ADRD and learn food and nutrition-related knowledge. Methods: The voice assistant is being implemented in several steps: construction of a comprehensive knowledge base with ontologies that define ADRD diet care and user profiles, and is extended with external knowledge graphs; management of conversation between users and the voice assistant; personalized ADRD diet services provided through a semantics-based knowledge graph search and reasoning engine; and system evaluation in use cases with additional qualitative evaluations. Results: A prototype voice assistant was evaluated in the lab using various use cases. Preliminary qualitative test results demonstrate reasonable rates of dialogue success and recommendation correctness. Conclusions: The voice assistant provides a natural, interactive interface for users, and it does not require the user to have a technical background, which may facilitate senior caregivers’ use in their daily care tasks. This study suggests the feasibility of using the intelligent voice assistant to help caregivers manage patients with ADRD’s diet.

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

    Automated Fall Detection Algorithm With Global Trigger Tool, Incident Reports, Manual Chart Review, and Patient-Reported Falls: Algorithm Development and...


    Background: Falls are common adverse events in hospitals, frequently leading to additional health costs due to prolonged stays and extra care. Therefore, reliable fall detection is vital to develop and test fall prevention strategies. However, conventional methods—voluntary incident reports and manual chart reviews—are error-prone and time consuming, respectively. Using a search algorithm to examine patients’ electronic health record data and flag fall indicators offers an inexpensive, sensitive, cost-effective alternative. Objective: This study’s purpose was to develop a fall detection algorithm for use with electronic health record data, then to evaluate it alongside the Global Trigger Tool, incident reports, a manual chart review, and patient-reported falls. Methods: Conducted on 2 campuses of a large hospital system in Switzerland, this retrospective diagnostic accuracy study consisted of 2 substudies: the first, targeting 240 patients, for algorithm development and the second, targeting 298 patients, for validation. In the development study, we compared the new algorithm’s in-hospital fall rates with those indicated by the Global Trigger Tool and incident reports; in the validation study, we compared the algorithm’s in-hospital fall rates with those from patient-reported falls and manual chart review. We compared the various methods by calculating sensitivity, specificity, and predictive values. Results: Twenty in-hospital falls were discovered in the development study sample. Of these, the algorithm detected 19 (sensitivity 95%), the Global Trigger Tool detected 18 (90%), and incident reports detected 14 (67%). Of the 15 falls found in the validation sample, the algorithm identified all 15 (100%), the manual chart review identified 14 (93%), and the patient-reported fall measure identified 5 (33%). Owing to relatively high numbers of false positives based on falls present on admission, the algorithm’s positive predictive values were 50% (development sample) and 47% (validation sample). Instead of requiring 10 minutes per case for a full manual review or 20 minutes to apply the Global Trigger Tool, the algorithm requires only a few seconds, after which only the positive results (roughly 11% of the full case number) require review. Conclusions: The newly developed electronic health record algorithm demonstrated very high sensitivity for fall detection. Applied in near real time, the algorithm can record in-hospital falls events effectively and help to develop and test fall prevention measures.

  • Illustration of the co-design process. Moderator rearranges participants' note cards on canvas. Source: Image created by the authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    How People with Parkinson's Disease and Health Care Professionals Wish to Partner in Care Using eHealth: Co-Design Study


    Background: Worldwide, the number of people with Parkinson’s disease (PD) is predicted to double between the years 2005 and 2030. Chronic care management requires active collaboration and knowledge exchange between patients and health care professionals (HCPs) for best possible health outcomes, which we describe as co-care. eHealth services have the potential to support the realization of co-care between people with PD (PwP) and HCPs. Objective: This study aimed to explore how co-care could be operationalized in PD care, supported by eHealth. More specifically, this study explores PwP's and HCPs' expectations and desired eHealth functionalities to achieve co-care. Methods: Principles of participatory design were used to enable the identification of co-care needs and design ideas, in a series of 4 half-day co-design workshops. The sample included 7 (4 women) PwP and 9 (4 women) HCPs, including 4 neurologists, 3 nurses, and 2 physiotherapists. The co-design process resulted in a functional prototype that was evaluated by the co-design participants in the last workshop. Data were collected through note cards produced by the participants during the first 3 workshops and focus group discussions during the 3rd and 4th workshops. The data were analyzed using qualitative thematic analysis. After the workshop series, the prototype was demonstrated at a Mini Fair for ongoing PD research and evaluated using a self-developed questionnaire with 37 respondents: 31 PwP (14 women) and 6 informal caregivers (3 women). Descriptive statistics are reported. Results: The qualitative analysis of data resulted in 2 main themes. The first theme, core eHealth functionalities and their expected values, describes 6 desired eHealth functionalities for supporting PD co-care between PwP and HCPs: (1) self-tracking, (2) previsit forms, (3) graphical visualization, (4) clinical decision support, (5) self-care recommendations, and (6) asynchronous communication. The second theme, individual and organizational constraints, describes constraints that need to be addressed to succeed with an eHealth service for co-care. Individual constraints include eHealth literacy and acceptance; organizational constraints include teamwork and administrative workload. The majority of the questionnaire respondents (31/37, 84%) perceived that they would benefit from an eHealth service similar to the demonstrated prototype. All prototype functionalities were rated as very important or important by the majority of respondents (ranging from 86% to 97% per functionality). Conclusions: This study adds to our knowledge on how PD co-care could be operationalized. Co-care implies a shift from episodic routine-driven care to more flexible care management that is driven by the mutual needs of patients and HCPs and supported by active information exchange between them, as well as automated information processing to generate patient-specific advice. More research is needed to further explore the concept of co-care in chronic care management and what it means for self-care and health care.

  • Source: Rawpixel; Copyright: Karolina / Kaboompics; URL:; License: Creative Commons Attribution (CC-BY).

    An Ovarian Reserve Assessment Model Based on Anti-Müllerian Hormone Levels, Follicle-Stimulating Hormone Levels, and Age: Retrospective Cohort Study


    Background: Previously, we reported a model for assessing ovarian reserves using 4 predictors: anti-Müllerian hormone (AMH) level, antral follicle count (AFC), follicle-stimulating hormone (FSH) level, and female age. This model is referred as the AAFA (anti-Müllerian hormone level–antral follicle count–follicle-stimulating hormone level–age) model. Objective: This study aims to explore the possibility of establishing a model for predicting ovarian reserves using only 3 factors: AMH level, FSH level, and age. The proposed model is referred to as the AFA (anti-Müllerian hormone level–follicle-stimulating hormone level–age) model. Methods: Oocytes from ovarian cycles stimulated by gonadotropin-releasing hormone antagonist were collected retrospectively at our reproductive center. Poor ovarian response (<5 oocytes retrieved) was defined as an outcome variable. The AFA model was built using a multivariable logistic regression analysis on data from 2017; data from 2018 were used to validate the performance of AFA model. Measurements of the area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predicative value were used to evaluate the performance of the model. To rank the ovarian reserves of the whole population, we ranked the subgroups according to the predicted probability of poor ovarian response and further divided the 60 subgroups into 4 clusters, A-D, according to cut-off values consistent with the AAFA model. Results: The AUCs of the AFA and AAFA models were similar for the same validation set, with values of 0.853 (95% CI 0.841-0.865) and 0.850 (95% CI 0.838-0.862), respectively. We further ranked the ovarian reserves according to their predicted probability of poor ovarian response, which was calculated using our AFA model. The actual incidences of poor ovarian response in groups from A-D in the AFA model were 0.037 (95% CI 0.029-0.046), 0.128 (95% CI 0.099-0.165), 0.294 (95% CI 0.250-0.341), and 0.624 (95% CI 0.577-0.669), respectively. The order of ovarian reserve from adequate to poor followed the order from A to D. The clinical pregnancy rate, live-birth rate, and specific differences in groups A-D were similar when predicted using the AFA and AAFA models. Conclusions: This AFA model for assessing the true ovarian reserve was more convenient, cost-effective, and objective than our original AAFA model.

  • Source: Shutterstock; Copyright: Tero Vesalainen; URL:; License: Licensed by the authors.

    Social Media Listening to Understand the Lived Experience of Presbyopia: Systematic Search and Content Analysis Study


    Background: Presbyopia is defined as the age-related deterioration of near vision over time which is experienced in over 80% of people aged 40 years or older. Individuals with presbyopia have difficulty with tasks that rely on near vision. It is not currently possible to stop or reverse the aging process that causes presbyopia; generally, it is corrected with glasses, contact lenses, surgery, or the use of a magnifying glass. Objective: This study aimed to explore how individuals used social media to describe their experience of presbyopia with regard to the symptoms experienced and the impacts of presbyopia on their quality of life. Methods: Social media sources including Twitter, forums, blogs, and news outlets were searched using a predefined search string relating to symptoms and impacts of presbyopia. The data that were downloaded, based on the keywords, underwent manual review to identify relevant data points. Relevant posts were further manually analyzed through a process of data tagging, categorization, and clustering. Key themes relating to symptoms, impacts, treatment, and lived experiences were identified. Results: A total of 4456 social media posts related to presbyopia were identified between May 2017 and August 2017. Using a random sampling methodology, we selected 2229 (50.0%) posts for manual review, with 1470 (65.9%) of these 2229 posts identified as relevant to the study objectives. Twitter was the most commonly used channel for discussions on presbyopia compared to forums and blogs. The majority of relevant posts originated in Spain (559/1470, 38.0%) and the United States (426/1470, 29.0%). Of the relevant posts, 270/1470 (18.4%) were categorized as posts written by individuals who have presbyopia, of which 37 of the 270 posts (13.7%) discussed symptoms. On social media, individuals with presbyopia most frequently reported experiencing difficulty reading small print (24/37, 64.9%), difficulty focusing on near objects (15/37, 40.5%), eye strain (12/37, 32.4%), headaches (9/37, 24.3%), and blurred vision (8/37, 21.6%). 81 of the 270 posts (30.0%) discussed impacts of presbyopia—emotional burden (57/81, 70.4%), functional or daily living impacts (46/81, 56.8%), such as difficulty reading (46/81, 56.8%) and using electronic devices (21/81, 25.9%), and impacts on work (3/81, 3.7%). Conclusions: Findings from this social media listening study provided insight into how people with presbyopia discuss their condition online and highlight the impact of presbyopia on individuals’ quality of life. The social media listening methodology can be used to generate insights into the lived experience of a condition, but it is recommended that this research be combined with prospective qualitative research for added rigor and for confirmation of the relevance of the findings.

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

    Nonprofessional Peer Support to Improve Mental Health: Randomized Trial of a Scalable Web-Based Peer Counseling Course


    Background: Millions of people worldwide are underserved by the mental health care system. Indeed, most mental health problems go untreated, often because of resource constraints (eg, limited provider availability and cost) or lack of interest or faith in professional help. Furthermore, subclinical symptoms and chronic stress in the absence of a mental illness diagnosis often go unaddressed, despite their substantial health impact. Innovative and scalable treatment delivery methods are needed to supplement traditional therapies to fill these gaps in the mental health care system. Objective: This study aims to investigate whether a self-guided web-based course can teach pairs of nonprofessional peers to deliver psychological support to each other. Methods: In this experimental study, a community sample of 30 dyads (60 participants, mostly friends), many of whom presented with mild to moderate psychological distress, were recruited to complete a web-based counseling skills course. Dyads were randomized to either immediate or delayed access to training. Before and after training, dyads were recorded taking turns discussing stressors. Participants’ skills in the helper role were assessed before and after taking the course: the first author and a team of trained research assistants coded recordings for the presence of specific counseling behaviors. When in the client role, participants rated the session on helpfulness in resolving their stressors and supportiveness of their peers. We hypothesized that participants would increase the use of skills taught by the course and decrease the use of skills discouraged by the course, would increase their overall adherence to the guidelines taught in the course, and would perceive posttraining counseling sessions as more helpful and their peers as more supportive. Results: The course had large effects on most helper-role speech behaviors: helpers decreased total speaking time, used more restatements, made fewer efforts to influence the speaker, and decreased self-focused and off-topic utterances (ds=0.8-1.6). When rating the portion of the session in which they served as clients, participants indicated that they made more progress in addressing their stressors during posttraining counseling sessions compared with pretraining sessions (d=1.1), but they did not report substantive changes in feelings of closeness and supportiveness of their peers (d=0.3). Conclusions: The results provide proof of concept that nonprofessionals can learn basic counseling skills from a scalable web-based course. The course serves as a promising model for the development of web-based counseling skills training, which could provide accessible mental health support to some of those underserved by traditional psychotherapy.

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

    New York Inner City Hospital COVID-19 Experience and Current Data: Retrospective Analysis at the Epicenter of the American Coronavirus Outbreak


    Background: In the midst of the coronavirus disease pandemic, emerging clinical data across the world has equipped frontline health care workers, policy makers, and researchers to better understand and combat the illness. Objective: The aim of this study is to report the correlation of clinical and laboratory parameters with patients requiring mechanical ventilation and the mortality in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: We did a review of patients with SARS-CoV-2 confirmed infection admitted and managed by our institution during the last month. Patients were grouped into intubated and nonintubated, and subgrouped to alive and deceased. A comprehensive analysis using the following parameters were performed: age, sex, ethnicity, BMI, comorbidities, inflammatory markers, laboratory values, cardiac and renal function, electrocardiogram (EKG), chest x-ray findings, temperature, treatment groups, and hospital-acquired patients with SARS-CoV-2. Results: A total of 184 patients were included in our study with ages ranging from 28-97 years (mean 64.72 years) and including 73 females (39.67%) and 111 males (60.33%) with a mean BMI of 29.10. We had 114 African Americans (61.96%), 58 Hispanics (31.52%), 11 Asians (5.98%), and 1 Caucasian (0.54%), with a mean of 1.70 comorbidities. Overall, the mortality rate was 17.39% (n=32), 16.30% (n=30) of our patients required mechanical ventilation, and 11.41% (n=21) had hospital-acquired SARS-CoV-2 infection. Pertinent and statistically significant results were found in the intubated versus nonintubated patients with confirmed SARS-CoV-2 for the following parameters: age (P=.01), BMI (P=.07), African American ethnicity (P<.001), Hispanic ethnicity (P=.02), diabetes mellitus (P=.001), creatinine (P=.29), blood urea nitrogen (BUN; P=.001), procalcitonin (P=.03), C-reactive protein (CRP; P=.007), lactate dehydrogenase (LDH; P=.001), glucose (P=.01), temperature (P=.004), bilateral pulmonary infiltrates in chest x-rays (P<.001), and bilateral patchy opacity (P=.02). The results between the living and deceased subgroups of patients with confirmed SARS-CoV-2 (linking to or against mortality) were BMI (P=.04), length of stay (P<.001), hypertension (P=.02), multiple comorbidity (P=.045), BUN (P=.04), and EKG findings with arrhythmias or blocks (P=.02). Conclusions: We arrived at the following conclusions based on a comprehensive review of our study group, data collection, and statistical analysis. Parameters that were strongly correlated with the need for mechanical ventilation were younger age group, overweight, Hispanic ethnicity, higher core body temperature, EKG findings with sinus tachycardia, and bilateral diffuse pulmonary infiltrates on the chest x-rays. Those intubated exhibited increased disease severity with significantly elevated levels of serum procalcitonin, CRP, LDH, mean glucose, creatinine, and BUN. Mortality was strongly correlated with BMI, African American ethnicity, hypertension, presence of multiple comorbidities (with a mean of 2.32), worsening renal function with acute kidney injury or acute chronic kidney injury, and EKG findings of arrhythmias and heart blocks.

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

    Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling


    Background: mHealth tablet-based interventions are increasingly being studied and deployed in various health care settings, yet little knowledge exists regarding patient uptake and acceptance or how patient demographics influence these important implementation metrics. Objective: To determine which factors influence the uptake and successful completion of an mHealth tablet questionnaire by analyzing its implementation in a primary care setting. Methods: We prospectively studied a patient-facing electronic touch-tablet asthma questionnaire deployed as part of the Electronic Asthma Management System. We describe tablet uptake and completion rates and corresponding predictor models for these behaviors. Results: The tablet was offered to and accepted by patients in 891/1715 (52.0%) visits. Patients refused the tablet in 33.0% (439/1330) visits in which it was successfully offered. Patients aged older than 65 years of age (odds ratio [OR] 2.30, 95% CI 1.33-3.95) and with concurrent chronic obstructive pulmonary disease (OR 2.22, 95% CI 1.05-4.67) were more likely to refuse the tablet, and those on an asthma medication (OR 0.55, 95% CI 0.30-0.99) were less likely to refuse it. Once accepted, the questionnaire was completed in 784/891 (88.0%) instances, with those on an asthma medication (OR 0.53, 95% CI 0.32-0.88) being less likely to leave it incomplete. Conclusions: Older age predicted initial tablet refusal but not tablet questionnaire completion, suggesting that perceptions of mHealth among older adults may negatively impact uptake, independent of usability. The influence of being on an asthma medication suggests that disease severity may also mediate mHealth acceptance. Although use of mHealth questionnaires is growing rapidly across health care settings and diseases, few studies describe their real-world acceptance and its predictors. Our results should be complemented by qualitative methods to identify barriers and enablers to uptake and may inform technological and implementation strategies to drive successful usage.

  • Source: Indiegogo; Copyright: Toi Ngee Tan; URL:; License: Licensed by the authors.

    A New Approach for Detecting Sleep Apnea Using a Contactless Bed Sensor: Comparison Study


    Background: At present, there is an increased demand for accurate and personalized patient monitoring because of the various challenges facing health care systems. For instance, rising costs and lack of physicians are two serious problems affecting the patient’s care. Nonintrusive monitoring of vital signs is a potential solution to close current gaps in patient monitoring. As an example, bed-embedded ballistocardiogram (BCG) sensors can help physicians identify cardiac arrhythmia and obstructive sleep apnea (OSA) nonintrusively without interfering with the patient’s everyday activities. Detecting OSA using BCG sensors is gaining popularity among researchers because of its simple installation and accessibility, that is, their nonwearable nature. In the field of nonintrusive vital sign monitoring, a microbend fiber optic sensor (MFOS), among other sensors, has proven to be suitable. Nevertheless, few studies have examined apnea detection. Objective: This study aims to assess the capabilities of an MFOS for nonintrusive vital signs and sleep apnea detection during an in-lab sleep study. Data were collected from patients with sleep apnea in the sleep laboratory at Khoo Teck Puat Hospital. Methods: In total, 10 participants underwent full polysomnography (PSG), and the MFOS was placed under the patient’s mattress for BCG data collection. The apneic event detection algorithm was evaluated against the manually scored events obtained from the PSG study on a minute-by-minute basis. Furthermore, normalized mean absolute error (NMAE), normalized root mean square error (NRMSE), and mean absolute percentage error (MAPE) were employed to evaluate the sensor capabilities for vital sign detection, comprising heart rate (HR) and respiratory rate (RR). Vital signs were evaluated based on a 30-second time window, with an overlap of 15 seconds. In this study, electrocardiogram and thoracic effort signals were used as references to estimate the performance of the proposed vital sign detection algorithms. Results: For the 10 patients recruited for the study, the proposed system achieved reasonable results compared with PSG for sleep apnea detection, such as an accuracy of 49.96% (SD 6.39), a sensitivity of 57.07% (SD 12.63), and a specificity of 45.26% (SD 9.51). In addition, the system achieved close results for HR and RR estimation, such as an NMAE of 5.42% (SD 0.57), an NRMSE of 6.54% (SD 0.56), and an MAPE of 5.41% (SD 0.58) for HR, whereas an NMAE of 11.42% (SD 2.62), an NRMSE of 13.85% (SD 2.78), and an MAPE of 11.60% (SD 2.84) for RR. Conclusions: Overall, the recommended system produced reasonably good results for apneic event detection, considering the fact that we are using a single-channel BCG sensor. Conversely, satisfactory results were obtained for vital sign detection when compared with the PSG outcomes. These results provide preliminary support for the potential use of the MFOS for sleep apnea detection. Trial Registration:

  • Patients talk to their doctors on WeChat. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    New Path to Recovery and Well-Being: Cross-Sectional Study on WeChat Use and Endorsement of WeChat-Based mHealth Among People Living With Schizophrenia in China


    Background: The past few decades have seen an exponential increase in using mobile phones to support medical care (mobile health [mHealth]) among people living with psychosis worldwide, yet little is known about WeChat use and WeChat-based mHealth among people living with schizophrenia (PLS) in China. Objective: This study aims to assess WeChat use, endorsement of WeChat-based mHealth programs, and health related to WeChat use among PLS. Methods: We recruited a random sample of 400 PLS from 12 communities in Changsha City of Hunan Province, China. WeChat use was assessed using the adapted WeChat Use Intensity Questionnaire (WUIQ). We also compared psychiatric symptoms, functioning, disability, recovery, quality of life, and general well-being between WeChat users and nonusers using one-to-one propensity-score matching. Results: The WeChat use rate was 40.8% in this sample (163/400); 30.7% (50/163) had more than 50 WeChat friends and nearly half (81/163, 49.7%) spent more than half an hour on WeChat, a pattern similar to college students and the elderly. PLS also showed higher emotional connectedness to WeChat use than college students. About 80.4% (131/163) of PLS were willing to participate in a WeChat-based mHealth program, including psychoeducation (91/163, 55.8%), professional support (82/163, 50.3%), and peer support (67/163, 41.1%). Compared with nonusers, WeChat users were younger, better educated, and more likely to be employed. WeChat use was associated with improved health outcomes, including lower psychiatric symptoms, lower depression, higher functioning, better recovery, and higher quality of life. Conclusions: WeChat-based mHealth programs hold promise as an empowering tool to provide cost-effective interventions, to foster global recovery, and to improve both physical and mental well-being among PLS. WeChat and WeChat-based mHealth programs have the potential to offer a new path to recovery and well-being for PLS in China.

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  • Public Engagement in Officials’ Stories about COVID-19 across Social Media, an Iraqi Case Study

    Date Submitted: Sep 18, 2020

    Open Peer Review Period: Sep 18, 2020 - Nov 13, 2020

    Background: Background: The world has not attended a major challenge like coronavirus disease (COVID-19) pandemic for several decades. Effective two-way communication across social media facilitates p...

    Background: Background: The world has not attended a major challenge like coronavirus disease (COVID-19) pandemic for several decades. Effective two-way communication across social media facilitates public engagement in health authorities and officials in a positive way which contributes to minimizing damage, impacts, and victims. Objective: Objective: This study examines public engagement in officials’ stories about COVID-19 on social media. This examination is to realize public responses and engagement particularly during the lockdown which allows us to understand the efforts and contributions of health authorities and officials on social media to give instructions and preventive measures to the public and how the public engage. Methods: Method: This study adopted a survey method through an online questionnaire using 'Google Forms' (N= 511) with responses from adults aged 18 and over. The data collection was carried out from the first week of March until the mid of April 2020. This period was in the quarantine days ordered by the Iraqi government (the first week of March to the end of May). The duration of data collection was very important because the officials were focusing on the measures to prevent the disease and giving instructions across social media to communicate and interact with the public. Results: Result: We revealed that the fear of the pandemic led people to change their perception of the government authorities and officials, and this argument was statistically approved (r=0.171**, p < 0.000). We revealed that the fear of the pandemic led people to change their perception of the government authorities and officials because before the outbreak of COVID-19 the public was not satisfied with the government authorities and officials performance, but during the outbreak, the public engaged with the officials positively, (r= 0.156**, p <0.000), (r=0.127**, p <0.000). Conclusions: Conclusion: The pandemic can be invested in restructuring the relationship between the government and the public positively, particularly to raise the public awareness of diseases, prevention, hygiene, and the practice of healthy behaviors. We found that only 191 (%38.2) of the participants did not try to consult the information from global sources about COVID-19. This indicates that through the internet and social media the public can potentially engage with global parties not only the local authorities.

  • Utilization of Electronic Medical Records Data for Medical Research in a Hospital in China: A Cross-Sectional Study

    Date Submitted: Sep 17, 2020

    Open Peer Review Period: Sep 17, 2020 - Nov 12, 2020

    Background: With the proliferation of electronic medical records systems (EMRs), there is an increasing interest in utilizing EMRs data for medical research, yet there is no quantitative research on E...

    Background: With the proliferation of electronic medical records systems (EMRs), there is an increasing interest in utilizing EMRs data for medical research, yet there is no quantitative research on EMRs data utilization for medical research purposes. Objective: Understand the current status of clinical data utilization in clinical research activities, including trends in recent years and differences between different populations, to find out the present problems in the use of EMR data for research, and provide a reference for promoting the utilization of EMR data in scientific research. Methods: For this descriptive, cross-sectional study, the utilization of EMRs data by staff at Xuanwu Hospital in Beijing, China between 2016 and 2019 was analyzed. The utilization of EMRs data was described as the number of requests, the proportion of requesters, and the frequency of requests per capita. The comparison by year, professional title, and age was conducted by double-sided chi square test. Results: From 2016 to 2019, EMRs data utilization was poor, as the proportion of requesters was 5.8% and the frequency was 0.1 times / person / year. The frequency per capita gradually slowed and more older, senior level staff used EMRs data compared to younger staff. Conclusions: The value of using EMRs data for research purposes does not get enough attention among researchers in Chinese hospitals. Ensuring equal availability of EMRs data and highlighting the benefits of such systems can help promote its use in research settings. Future research should focus on mechanisms that encourage data utilization, ensure fair data availability, and promote data sharing.

  • Implementing remote collaboration in a virtual patient platform – enabling students and physicians to learn collaborative clinical reasoning

    Date Submitted: Sep 14, 2020

    Open Peer Review Period: Sep 14, 2020 - Nov 9, 2020

    Background: Learning with virtual patients is highly popular for fostering clinical reasoning in medical education. However, little learning with virtual patients is done collaboratively, despite the...

    Background: Learning with virtual patients is highly popular for fostering clinical reasoning in medical education. However, little learning with virtual patients is done collaboratively, despite the potential learning benefits of collaborative vs. individual learning. Objective: In this article, we describe the rationale behind the implementation of student collaboration in the CASUS virtual patient platform. Methods: The SimpleWebRTC library of andYet was used to implement the collaborative tool. It provided a basis for the conferencing platform and could be adapted to include features such as video communication and screensharing. An additional text chat was created based on the message protocol of the SimpleWebRTC library. We implemented a user interface for educators to set up and configure the collaboration. Educators can configure video, audio, and text-based chat communication, which are known to promote effective learning. Results: We tested the tool in a sample of 137 students working on virtual patients. The study results indicate that students successfully diagnosed 53% (SD = 26%) of the patients when working alone and 71% (SD= 20%) when collaborating using the tool (p < .05, eta2=.12). A usability questionnaire for the study sample shows a usability score of 82.16 (SD = 1.31), a B+ grade. Conclusions: The approach provides a technical framework for collaboration that can be used with the CASUS virtual patient system. Additionally, the application programming interface is generic, so that the setup can also be used with other learning management systems. The collaborative tool helps students diagnose virtual patients and results in a good overall usability of CASUS. Using learning analytics, we are able to track students’ progress in content knowledge and collaborative knowledge and guide them through a virtual patient curriculum designed to teach both. More broadly, the collaborative tool provides an array of new possibilities for researchers and educators alike to design courses, collaborative homework assignments, and research questions for collaborative learning.

  • Understanding barriers to linking novel consumer and lifestyle data for health research, results from the LifeInfo Survey: a topic modelling approach

    Date Submitted: Sep 18, 2020

    Open Peer Review Period: Sep 11, 2020 - Nov 6, 2020

    Background: Novel consumer and lifestyle data, for example those collected by supermarket loyalty cards or mobile phone exercise tracking apps, offer numerous benefits for researchers wishing to under...

    Background: Novel consumer and lifestyle data, for example those collected by supermarket loyalty cards or mobile phone exercise tracking apps, offer numerous benefits for researchers wishing to understand diet and exercise related risk factors for diseases. Yet, limited research has addressed public attitudes towards linking these data with individual health records for research purposes. Objective: The aim of this research was to identify key barriers for data linkage and recommend safeguards and procedures that would encourage individuals to share these data for potential future research. Methods: The LifeInfo Survey consulted the public on their attitudes towards sharing consumer and lifestyle data for research purposes. Where barriers to data sharing existed, participants provided unstructured survey responses detailing what would make them more likely to share data for linkage with their health record in the future. The topic modelling technique Latent Dirichlet Allocation (LDA) was used to analyse these textual responses to uncover common thematic topics within the texts. Results: Participants provided responses related to sharing their store loyalty card data (n = 2,338) and health/fitness app data (n = 1,531). Key barriers to data sharing identified through topic modelling included: data safety and security, personal privacy, requirements of further information, fear of data being accessed by others, problems with data accuracy, not understanding the reason for data linkage and not using data production services. We provide recommendations for addressing these issues to establish best practice for future researchers wishing to utilise these data. Conclusions: This study formulates large-scale consultation of public attitudes towards data linkage of this kind, as such, it is an important first step in understanding and addressing barriers to participation for research utilising novel consumer and lifestyle data.

  • Clinicians are Inclined to Prescribe HIV Pre-Exposure Prophylaxis for Persons at High HIV Risk but are Concerned about the Lack of Guidelines: A National Survey in China

    Date Submitted: Sep 10, 2020

    Open Peer Review Period: Sep 10, 2020 - Nov 5, 2020

    Background: Pre-exposure prophylaxis (PrEP) is an effective HIV prevention measure. Clinicians play crucial role in PrEP implementation, and their knowledge, attitudes, career experience, and related...

    Background: Pre-exposure prophylaxis (PrEP) is an effective HIV prevention measure. Clinicians play crucial role in PrEP implementation, and their knowledge, attitudes, career experience, and related structural factors may affect their willingness to prescribe PrEP. However, little is known about the attitudes and willingness of clinicians to prescribe PrEP without guidelines. Objective: We aimed to explore clinicians associated factors for their willingness to prescribe PrEP in China. Methods: Between May and June 2019, a nationwide online cross-sectional survey of clinicians was conducted on the platform of WeChat smartphone application. Multivariate logistic regression was used to assess factors associated with willingness to prescribe PrEP. Results: Overall, 777 HIV clinicians from 31 provinces in six administrative regions of China completed the survey. It was found that 72.5% of respondents had heard of PrEP, 32.9% thought that PrEP could effectively prevent HIV acquisition in key populations, and 47.2% thought that it was necessary to provide PrEP services to key populations. After adjusting for age, gender, ethnicity and education level, the following factors significantly increased the odds of PrEP prescription: having worked for more than 10 years (AOR = 2.82), having serviced more than 100 patients per month (AOR = 4.16), and often encountering key populations seeking the PrEP prescription service (AOR = 79.35). The barriers of PrEP willingness prescribing were concerning about poor adherence to PrEP (AOR = 0.66), lacking of clinical guidelines for PrEP (AOR = 0.47), and lacking of drug indications for PrEP (AOR = 0.49). Conclusions: A high proportion of clinicians are willing to prescribe PrEP, but their understanding of PrEP is poor. Lack of PrEP clinical guidelines, lack of drug indications, and employees with limited work experience are the main barriers to the willingness of PrEP prescription. The development of PrEP clinical guidelines and drug indications and the availability of PrEP training are recommended to improve understanding and the willingness to prescribe PrEP.

  • Development and External Validation of Diagnostic Model for Coronary Microvascular Obstruction: Algorithm Development and Validation

    Date Submitted: Aug 1, 2020

    Open Peer Review Period: Aug 1, 2020 - Sep 26, 2020

    Background: Prevention of coronary microvascular obstruction /no-reflow phenomenon(CMVO/NR) is a crucial step in improving prognosis of patients with acute ST segment elevation myocardial infarction (...

    Background: Prevention of coronary microvascular obstruction /no-reflow phenomenon(CMVO/NR) is a crucial step in improving prognosis of patients with acute ST segment elevation myocardial infarction (STEMI )during primary percutaneous coronary intervention (PPCI). Objective: The objective of our study was to develop and externally validate a diagnostic model of CMVO/NR in patients with acute STEMI underwent PPCI. Methods: Design: Multivariate logistic regression of a cohort of acute STEMI patients. Setting: Emergency department ward of a university hospital. Participants: Diagnostic model development: Totally 1232 acute STEMI patients who were consecutively treated with PPCI from November 2007 to December 2013. External validation: Totally 1301 acute STEMI patients who were treated with PPCI from January 2014 to June 2018. Outcomes: CMVO/NR during PPCI. We used logistic regression analysis to analyze the risk factors of CMVO/NR in the development data set. We developed a diagnostic model of CMVO/NR and constructed a nomogram.We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). Results: A total of 147 out of 1,232 participants (11.9%) presented CMVO/NR in the development dataset.The strongest predictors of CMVO/NR were age, periprocedural bradycardia, using thrombus aspiration devices during procedure and total occlusion of culprit vessel. Logistic regression analysis showed that the differences between two group with and without CMVO/NR in age( odds ratios (OR)1.031; 95% confidence interval(CI), 1.015 ~1.048 ; P <.001), periprocedural bradycardia (OR 2.151;95% CI,1.472~ 3.143 ; P <.001) , total occlusion of the culprit vessel (OR 1.842;95% CI, 1.095~ 3.1 ; P =.021) , and using thrombus aspirationdevices during procedure (OR 1.631; 95% CI, 1.029~ 2.584 ; P =.037).We developed a diagnostic model of CMVO/NR. The area under the receiver operating characteristic curve (AUC) was .6833±.023. We constructed a nomogram. CMVO/NR occurred in 120 out of 1,301 participants (9.2%) in the validation data set. The AUC was .6547±.025. Discrimination, calibration, and DCA were satisfactory. Date of approved by ethic committee:16 May 2019. Date of data collection start: 1 June 2019. Numbers recruited as of submission of the manuscript:2,533. Conclusions: We developed and externally validated a diagnostic model of CMVO/NR during PPCI. Clinical Trial: We registered this study with WHO International Clinical Trials Registry Platform on 16 May 2019. Registration number: ChiCTR1900023213.