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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 2018: 4.945, ranked #1 out of 26 journals in the medical informatics category) 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 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. 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 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: Pexels; Copyright: Ketut Subiyanto; URL: https://www.pexels.com/photo/man-people-woman-girl-4429149/; License: Licensed by JMIR.

    Public Engagement and Government Responsiveness in the Communications About COVID-19 During the Early Epidemic Stage in China: Infodemiology Study on Social...

    Abstract:

    Background: Effective risk communication about the outbreak of a newly emerging infectious disease in the early stage is critical for managing public anxiety and promoting behavioral compliance. China has experienced the unprecedented epidemic of the coronavirus disease (COVID-19) in an era when social media has fundamentally transformed information production and consumption patterns. Objective: This study examined public engagement and government responsiveness in the communications about COVID-19 during the early epidemic stage based on an analysis of data from Sina Weibo, a major social media platform in China. Methods: Weibo data relevant to COVID-19 from December 1, 2019, to January 31, 2020, were retrieved. Engagement data (likes, comments, shares, and followers) of posts from government agency accounts were extracted to evaluate public engagement with government posts online. Content analyses were conducted for a random subset of 644 posts from personal accounts of individuals, and 273 posts from 10 relatively more active government agency accounts and the National Health Commission of China to identify major thematic contents in online discussions. Latent class analysis further explored main content patterns, and chi-square for trend examined how proportions of main content patterns changed by time within the study time frame. Results: The public response to COVID-19 seemed to follow the spread of the disease and government actions but was earlier for Weibo than the government. Online users generally had low engagement with posts relevant to COVID-19 from government agency accounts. The common content patterns identified in personal and government posts included sharing epidemic situations; general knowledge of the new disease; and policies, guidelines, and official actions. However, personal posts were more likely to show empathy to affected people (χ21=13.3, P<.001), attribute blame to other individuals or government (χ21=28.9, P<.001), and express worry about the epidemic (χ21=32.1, P<.001), while government posts were more likely to share instrumental support (χ21=32.5, P<.001) and praise people or organizations (χ21=8.7, P=.003). As the epidemic evolved, sharing situation updates (for trend, χ21=19.7, P<.001) and policies, guidelines, and official actions (for trend, χ21=15.3, P<.001) became less frequent in personal posts but remained stable or increased significantly in government posts. Moreover, as the epidemic evolved, showing empathy and attributing blame (for trend, χ21=25.3, P<.001) became more frequent in personal posts, corresponding to a slight increase in sharing instrumental support, praising, and empathizing in government posts (for trend, χ21=9.0, P=.003). Conclusions: The government should closely monitor social media data to improve the timing of communications about an epidemic. As the epidemic evolves, merely sharing situation updates and policies may be insufficient to capture public interest in the messages. The government may adopt a more empathic communication style as more people are affected by the disease to address public concerns.

  • Visual of the DoD's Mobile Health Care Environment interface for T2DM. Source: U.S. Army Telemedicine & Advanced Technology Research Center / Placeit; Copyright: U.S. Army Telemedicine & Advanced Technology Research Center / Placeit; URL: http://www.jmir.org/2020/5/e17968/; License: Licensed by JMIR.

    Enhancing Patient Activation and Self-Management Activities in Patients With Type 2 Diabetes Using the US Department of Defense Mobile Health Care...

    Abstract:

    Background: Past mobile health (mHealth) efforts to empower type 2 diabetes (T2D) self-management include portals, text messaging, collection of biometric data, electronic coaching, email, and collection of lifestyle information. Objective: The primary objective was to enhance patient activation and self-management of T2D using the US Department of Defense’s Mobile Health Care Environment (MHCE) in a patient-centered medical home setting. Methods: A multisite study, including a user-centered design and a controlled trial, was conducted within the US Military Health System. Phase I assessed preferences regarding the enhancement of the enabling technology. Phase II was a single-blinded 12-month feasibility study that randomly assigned 240 patients to either the intervention (n=123, received mHealth technology and behavioral messages tailored to Patient Activation Measure [PAM] level at baseline) or the control group (n=117, received equipment but not messaging. The primary outcome measure was PAM scores. Secondary outcome measures included Summary of Diabetes Self-Care Activities (SDSCA) scores and cardiometabolic outcomes. We used generalized estimating equations to estimate changes in outcomes. Results: The final sample consisted of 229 patients. Participants were 61.6% (141/229) male, had a mean age of 62.9 years, mean glycated hemoglobin (HbA1c) of 7.5%, mean BMI of 32.7, and a mean duration of T2D diagnosis of 9.8 years. At month 12, the control group showed significantly greater improvements compared with the intervention group in PAM scores (control mean 7.49, intervention mean 1.77; P=.007), HbA1c (control mean −0.53, intervention mean −0.11; P=.006), and low-density lipoprotein cholesterol (control mean −7.14, intervention mean 4.38; P=.01). Both groups showed significant improvement in SDSCA, BMI, waist size, and diastolic blood pressure; between-group differences were not statistically significant. Except for patients with the highest level of activation (PAM level 4), intervention group patients exhibited significant improvements in PAM scores. For patients with the lowest level of activation (PAM level 1), the intervention group showed significantly greater improvement compared with the control group in HbA1c (control mean −0.09, intervention mean −0.52; P=.04), BMI (control mean 0.58, intervention mean −1.22; P=.01), and high-density lipoprotein cholesterol levels (control mean −4.86, intervention mean 3.56; P<.001). Significant improvements were seen in AM scores, SDSCA, and waist size for both groups and in diastolic and systolic blood pressure for the control group; the between-group differences were not statistically significant. The percentage of participants who were engaged with MHCE for ≥50% of days period was 60.7% (68/112; months 0-3), 57.4% (62/108; months 3-6), 49.5% (51/103; months 6-9), and 43% (42/98; months 9-12). Conclusions: Our study produced mixed results with improvement in PAM scores and outcomes in both the intervention and control groups. Structural design issues may have hampered the influence of tailored behavioral messaging within the intervention group. Trial Registration: ClinicalTrials.gov NCT02949037; https://clinicaltrials.gov/ct2/show/NCT02949037

  • Source: freepik; Copyright: halayalex; URL: https://www.freepik.com/free-photo/young-fashion-smiling-hipster-man-city-cafe-during-lunch-time-with-notebook-suit_6766116.htm#page=1&query=person%20using%20computer&position=23; License: Licensed by JMIR.

    Tracing the Decisions That Shaped the Development of MyChart, an Electronic Patient Portal in Alberta, Canada: Historical Research Study

    Abstract:

    Background: Understanding how health organizations decide on information technology (IT) investments is imperative to ensure successful implementation and adoption. There is a high rate of failure and a tendency to downplay the complexity of implementation progression. Alberta Health Services introduced a patient portal called MyChart. Although MyChart allows patients to view appointments and selected laboratory results and to communicate with their providers, its uptake varies. Objective: The study aimed to examine the institutional decision-making processes that shaped the development and implementation of MyChart. Methods: A historical study was conducted based on the 7-step framework, where one engages in a rigorous archival critical analysis (including internal and external criticism) of documents and analysis of interviews. We reviewed and analyzed 423 primary and secondary sources and interviewed 10 key decision makers. Results: Supportive leadership, project management, focused scope, appropriate technology and vendor selection, and quick decision making were some of the facilitators that allowed for the growth of proof of concept. The planning and implementation stages did not depend much on the technology itself but on the various actors who influenced the implementation by exerting power. The main barriers were lack of awareness about the technology, proper training, buy-in from diverse system leaders, and centralized government decision making. Conclusions: Organizational priorities and decision-making tactics influence IT investments, implementation, adoption, and outcomes. Future research could focus on improving the applicability of needs assessments and funding decisions to health care scenarios. Trial Registration:

  • Source: Shutterstock; Copyright: Gaius; URL: https://www.shutterstock.com/nl/image-photo/teamwork-concept-using-white-puzzle-pieces-274068050; License: Licensed by the authors.

    Integrating People, Context, and Technology in the Implementation of a Web-Based Intervention in Forensic Mental Health Care: Mixed-Methods Study

    Abstract:

    Background: While eMental health interventions can have many potential benefits for mental health care, implementation outcomes are often disappointing. In order to improve these outcomes, there is a need for a better understanding of complex, dynamic interactions between a broad range of implementation-related factors. These interactions and processes should be studied holistically, paying attention to factors related to context, technology, and people. Objective: The main objective of this mixed-method study was to holistically evaluate the implementation strategies and outcomes of an eMental health intervention in an organization for forensic mental health care. Methods: First, desk research was performed on 18 documents on the implementation process. Second, the intervention’s use by 721 patients and 172 therapists was analyzed via log data. Third, semistructured interviews were conducted with all 18 therapists of one outpatient clinic to identify broad factors that influence implementation outcomes. The interviews were analyzed via a combination of deductive analysis using the nonadoption, abandonment, scale-up, spread, and sustainability framework and inductive, open coding. Results: The timeline generated via desk research showed that implementation strategies focused on technical skills training of therapists. Log data analyses demonstrated that 1019 modules were started, and 18.65% (721/3865) of patients of the forensic hospital started at least one module. Of these patients, 18.0% (130/721) completed at least one module. Of the therapists using the module, 54.1% (93/172 sent at least one feedback message to a patient. The median number of feedback messages sent per therapist was 1, with a minimum of 0 and a maximum of 460. Interviews showed that therapists did not always introduce the intervention to patients and using the intervention was not part of their daily routine. Also, therapists indicated patients often did not have the required conscientiousness and literacy levels. Furthermore, they had mixed opinions about the design of the intervention. Important organization-related factors were the need for more support and better integration in organizational structures. Finally, therapists stated that despite its current low use, the intervention had the potential to improve the quality of treatment. Conclusions: Synthesis of different types of data showed that implementation outcomes were mostly disappointing. Implementation strategies focused on technical training of therapists, while little attention was paid to changes in the organization, design of the technology, and patient awareness. A more holistic approach toward implementation strategies—with more attention to the organization, patients, technology, and training therapists—might have resulted in better implementation outcomes. Overall, adaptivity appears to be an important concept in eHealth implementation: a technology should be easily adaptable to an individual patient, therapists should be trained to deal flexibly with an eMental health intervention in their treatment, and organizations should adapt their implementation strategies and structures to embed a new eHealth intervention.

  • Source: Freepik; Copyright: tirachardz; URL: https://www.freepik.com/free-photo/asian-senior-men-using-mobile-phone-home-asian-senior-chinese-male-search-information-about-how-good-health-internet-while-lying-bed-bedroom-home-morning-concept_5820713.htm; License: Licensed by JMIR.

    Artificial Intelligence–Assisted System in Postoperative Follow-up of Orthopedic Patients: Exploratory Quantitative and Qualitative Study

    Abstract:

    Background: Patient follow-up is an essential part of hospital ward management. With the development of deep learning algorithms, individual follow-up assignments might be completed by artificial intelligence (AI). We developed an AI-assisted follow-up conversational agent that can simulate the human voice and select an appropriate follow-up time for quantitative, automatic, and personalized patient follow-up. Patient feedback and voice information could be collected and converted into text data automatically. Objective: The primary objective of this study was to compare the cost-effectiveness of AI-assisted follow-up to manual follow-up of patients after surgery. The secondary objective was to compare the feedback from AI-assisted follow-up to feedback from manual follow-up. Methods: The AI-assisted follow-up system was adopted in the Orthopedic Department of Peking Union Medical College Hospital in April 2019. A total of 270 patients were followed up through this system. Prior to that, 2656 patients were followed up by phone calls manually. Patient characteristics, telephone connection rate, follow-up rate, feedback collection rate, time spent, and feedback composition were compared between the two groups of patients. Results: There was no statistically significant difference in age, gender, or disease between the two groups. There was no significant difference in telephone connection rate (manual: 2478/2656, 93.3%; AI-assisted: 249/270, 92.2%; P=.50) or successful follow-up rate (manual: 2301/2478, 92.9%; AI-assisted: 231/249, 92.8%; P=.96) between the two groups. The time spent on 100 patients in the manual follow-up group was about 9.3 hours. In contrast, the time spent on the AI-assisted follow-up was close to 0 hours. The feedback rate in the AI-assisted follow-up group was higher than that in the manual follow-up group (manual: 68/2656, 2.5%; AI-assisted: 28/270, 10.3%; P<.001). The composition of feedback was different in the two groups. Feedback from the AI-assisted follow-up group mainly included nursing, health education, and hospital environment content, while feedback from the manual follow-up group mostly included medical consultation content. Conclusions: The effectiveness of AI-assisted follow-up was not inferior to that of manual follow-up. Human resource costs are saved by AI. AI can help obtain comprehensive feedback from patients, although its depth and pertinence of communication need to be improved.

  • Source: Unsplash.com; Copyright: National Cancer Institute; URL: https://unsplash.com/photos/L8tWZT4CcVQ; License: Licensed by JMIR.

    Exploring the Characteristics and Behaviors of Nurses Who Have Attained Microcelebrity Status on Instagram: Content Analysis

    Abstract:

    Background: Instagram is a social media platform that enables users to share images and videos worldwide. Some nurses have used Instagram to document their experiences as a nurse and have subsequently gained microcelebrity status—that is, a user who purposefully seeks to amass a substantive Web-based following and has become recognized as a niche area of interest. Objective: This study aimed to identify the characteristics and behaviors of microcelebrity nurses who act as influencers on Instagram and use their nursing profile to gain attention and presence on the Web. Methods: A qualitative, exploratory, nonparticipatory content analysis of media and text generated by a purposeful sample of 10 registered nurses who use Instagram and sustain a definable microcelebrity status was conducted. In this study, manifest and latent data were examined to gain an understanding of the characteristics and behaviors of nurses who have attained microcelebrity status on Instagram. Results: Data analysis revealed 5 themes of Instagram posts: (1) engaging Instagram users, (2) educational opportunities and insights, (3) nursing-related humor, (4) emotions experienced by nurses, and (5) media and narratives including patient details or work context. Messages were primarily positive in nature; however, multiple potential privacy, ethical, and professional issues were noted throughout the posted content. Conclusions: The findings of this study help to expand the current knowledge related to the use of social media platforms such as Instagram, especially in regard to the emergence of nurses who use this form of technology to achieve or maintain a microcelebrity status. This study calls for additional research on nurses’ attainment of microcelebrity status on social media as well as further policy development to adequately prepare nurses to navigate social media.

  • Source: freepik; Copyright: racool_studio; URL: https://www.freepik.com/free-photo/teenagers-using-mobile-phones_7901877.htm#page=1&query=teen%20using%20smartphone&position=4; License: Licensed by JMIR.

    Internet-Based Health Information–Seeking Behavior of Students Aged 12 to 14 Years: Mixed Methods Study

    Abstract:

    Background: Many children and adolescents are surrounded by smartphones, tablets, and computers and know how to search the internet for almost any information. However, very few of them know how to select proper information from reliable sources. This can become a problem when health issues are concerned, where it is vital to identify incorrect or misleading information. The competence to critically evaluate digital information on health issues is of increasing importance for adolescents. Objective: The aim of this study was to assess how children and adolescents rate their internet-based health literacy and how their actual literacy differs from their ratings. In addition, there was a question on how their search performance is related to their self-efficacy. To evaluate these questions, a criteria-based analysis of the quality of the websites they visited was performed. Finally, the possibility to increase their internet-based health literacy in a 3-day workshop was explored. Methods: A workshop with a focus on health literacy was attended by 14 children and adolescents in an Austrian secondary school. After prior assessments (Culture Fair Intelligence Test, revised German version; Reading Speed and Reading Comprehension Test for Grades 6 to 12, German; electronic health literacy scale [eHEALS]; and General Self-Efficacy Scale, Reversed Version, German), the students were asked to perform an internet-based search on a health-related issue. Browser histories and screenshots of all internet searches were gathered, clustered, and analyzed. After the workshop, the health literacy of the students was assessed again by using the eHEALS. Results: The 14 students opened a total of 85 homepages, but only eight of these homepages were rated as good or fair by two experts (independent rating) based on specific criteria. The analysis showed that the students judged their own internet-based health literacy much higher than the actual value, and students who had rated themselves better did not visit websites of high quality. Internet-based health literacy correlated significantly with the self-efficacy of the students (rs=0.794, P=.002). Conclusions: Our study showed that it is possible to draw the attention of students to critical aspects of internet search and to slightly improve their search competence in a workshop. Targeted improvement of health literacy is urgently required, and students need special instruction for this purpose. Further investigations in this area with larger sets of data, which could be feasible with the help of a computer program, are urgently needed.

  • Source: Freepik; Copyright: phduet; URL: https://www.freepik.com/free-photo/man-with-back-pain_966458.htm; License: Licensed by JMIR.

    Occupational Health Needs and Predicted Well-Being in Office Workers Undergoing Web-Based Health Promotion Training: Cross-Sectional Study

    Abstract:

    Background: Office workers face workplace-related health issues, including stress and back pain, resulting in considerable cost to businesses and health care systems. Workplace health promotion attempts to prevent these health issues, and the internet can be used to deliver workplace health promotion interventions to office workers. Data were provided by Fitbase GmbH, a German company, which specializes in workplace health promotion via the internet (Web-based health). The Web-based health intervention allowed workers to focus on different health categories by using information modules (reading health information) and/or completing practical exercises (guided, interactive health tutorials). Objective: This study aimed to identify the extent to which office workers have workplace-related health issues, assess whether office workers who differ in their health focus also differ in their improved well-being, and assess whether completing practical exercises is associated with improved well-being compared with reading information modules. Methods: Fitbase GmbH collected data for the period of February 2016 to May 2017 from health insurance employees undergoing Web-based health training in Hamburg, Germany. The data consisted of a needs assessment examining health issues faced by office workers, a wellness questionnaire regarding one’s perception of the Web-based health intervention, and activity logs of information modules and practical exercises completed. Through logistic regression, we determined associations between improved well-being from Web-based health training and differences in a worker’s health focus and a worker’s preferred intervention method. Results: Nearly half of the office workers had chronic back pain (1532/3354) and felt tense or irritated (1680/3348). Over four-fifth (645/766) of the office workers indicated that the Web-based health training improved their well-being (P<.001). Office workers who preferred practical exercises compared with information modules had 2.22 times greater odds of reporting improved well-being from the Web-based health intervention (P=.01; 95% CI 1.20-4.11). Office workers with a focus on practical exercises for back health had higher odds of improved well-being compared with other health foci. Office workers focused on practical exercises for back pain had at least two times the odds of having their well-being improved from the Web-based health intervention compared with those focused on stress management (P<.001), mindfulness (P=.02), stress management/mindfulness (P=.005), and eye health (P=.003). No particular health focus was associated with improved well-being for the information modules. Conclusions: Office workers frequently report having back pain and stress. A focus on Web-based health training via practical exercises and practical exercises for back health predict an improvement in office workers’ reported well-being. Trial Registration:

  • Source: Flickr; Copyright: Alex E. Proimos; URL: http://www.flickr.com/photos/34120957@N04/6870109454; License: Creative Commons Attribution + Noncommercial (CC-BY-NC).

    Classification and Prediction of Violence Against Chinese Medical Staff on the Sina Microblog Based on a Self-Organizing Map: Quantitative Study

    Abstract:

    Background: For the last decade, doctor-patient contradiction in China has remained prominent, and workplace violence toward medical staff still occurs frequently. However, little is known about the types and laws of propagation of violence against medical staff online. Objective: By using a self-organizing map (SOM), we aimed to explore the microblog propagation law for violent incidents in China that involve medical staff, to classify the types of incidents and provide a basis for rapidly and accurately predicting trends in public opinion and developing corresponding measures to improve the relationship between doctors and patients. Methods: For this study, we selected 60 cases of violent incidents in China involving medical staff that led to heated discussions on the Sina microblog from 2011 to 2018, searched the web data of the microblog using crawler software, recorded the amount of new tweets every 2 hours, and used the SOM neural network to cluster the number of tweets. Polynomial and exponential functions in MATLAB software were applied to predict and analyze the data. Results: Trends in the propagation of online public opinion regarding the violent incidents were categorized into 8 types: bluff, waterfall, zigzag, steep, abrupt, wave, steep slope, and long slope. The communications exhibited different characteristics. The prediction effect of 4 types of incidents (ie, bluff, waterfall, zigzag, and steep slope) was good and accorded with actual spreading trends. Conclusions: Our study found that the more serious the consequences of a violent incident, such as a serious injury or death, the more attention it drew on the microblog, the faster was its propagation speed, and the longer was its duration. In these cases, the propagation types were mostly steep slope, long slope, and zigzag. In addition, the more serious the consequences of a violent incident, the higher popularity it exhibited on the microblog. The popularity within a week was significantly higher for acts resulting from patients’ dissatisfaction with treatments than for acts resulting from nontherapeutic incidents.

  • Source: The Authors / Placeit; Copyright: The Authors / Placeit; URL: http://www.jmir.org/2020/5/e15589/; License: Licensed by JMIR.

    An Exploration Into the Use of a Chatbot for Patients With Inflammatory Bowel Diseases: Retrospective Cohort Study

    Abstract:

    Background: The emergence of chatbots in health care is fast approaching. Data on the feasibility of chatbots for chronic disease management are scarce. Objective: This study aimed to explore the feasibility of utilizing natural language processing (NLP) for the categorization of electronic dialog data of patients with inflammatory bowel diseases (IBD) for use in the development of a chatbot. Methods: Electronic dialog data collected between 2013 and 2018 from a care management platform (UCLA eIBD) at a tertiary referral center for IBD at the University of California, Los Angeles, were used. Part of the data was manually reviewed, and an algorithm for categorization was created. The algorithm categorized all relevant dialogs into a set number of categories using NLP. In addition, 3 independent physicians evaluated the appropriateness of the categorization. Results: A total of 16,453 lines of dialog were collected and analyzed. We categorized 8324 messages from 424 patients into seven categories. As there was an overlap in these categories, their frequencies were measured independently as symptoms (2033/6193, 32.83%), medications (2397/6193, 38.70%), appointments (1518/6193, 24.51%), laboratory investigations (2106/6193, 34.01%), finance or insurance (447/6193, 7.22%), communications (2161/6193, 34.89%), procedures (617/6193, 9.96%), and miscellaneous (624/6193, 10.08%). Furthermore, in 95.0% (285/300) of cases, there were minor or no differences in categorization between the algorithm and the three independent physicians. Conclusions: With increased adaptation of electronic health technologies, chatbots could have great potential in interacting with patients, collecting data, and increasing efficiency. Our categorization showcases the feasibility of using NLP in large amounts of electronic dialog for the development of a chatbot algorithm. Chatbots could allow for the monitoring of patients beyond consultations and potentially empower and educate patients and improve clinical outcomes.

  • TOC. Source: Unsplash.com; Copyright: Alina Grubnyak; URL: https://unsplash.com/photos/R84Oy89aNKs; License: Licensed by JMIR.

    A Global Digital Citizen Science Policy to Tackle Pandemics Like COVID-19

    Authors List:

    Abstract:

    The coronavirus disease (COVID-19) pandemic is an extremely complex existential threat that requires cohesive societal effort to address health system inefficiencies. When our society has faced existential crises in the past, we have banded together by using the technology at hand to overcome them. The COVID-19 pandemic is one such threat that requires not only a cohesive effort, but also enormous trust to follow public health guidelines, maintain social distance, and share necessities. However, are democratic societies with civil liberties capable of doing this? Mobile technology has immense potential for addressing pandemics like COVID-19, as it gives us access to big data in terms of volume, velocity, veracity, and variety. These data are particularly relevant to understand and mitigate the spread of pandemics such as COVID-19. In order for such intensive and potentially intrusive data collection measures to succeed, we need a cohesive societal effort with full buy-in from citizens and their representatives. This article outlines an evidence-based global digital citizen science policy that provides the theoretical and methodological foundation for ethically sourcing big data from citizens to tackle pandemics such as COVID-19.

  • RTLS tags at the NCID. Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2020/5/e19437/; License: Creative Commons Attribution (CC-BY).

    Use of a Real-Time Locating System for Contact Tracing of Health Care Workers During the COVID-19 Pandemic at an Infectious Disease Center in Singapore:...

    Abstract:

    Background: In early 2020, coronavirus disease (COVID-19) emerged and spread by community and nosocomial transmission. Effective contact tracing of potentially exposed health care workers is crucial for the prevention and control of infectious disease outbreaks in the health care setting. Objective: This study aimed to evaluate the comparative effectiveness of contact tracing during the COVID-19 pandemic through the real-time locating system (RTLS) and review of the electronic medical record (EMR) at the designated hospital for COVID-19 response in Singapore. Methods: Over a 2-day study period, all admitted patients with COVID-19, their ward locations, and the health care workers rostered to each ward were identified to determine the total number of potential contacts between patients with COVID-19 and health care workers. The numbers of staff-patient contacts determined by EMR reviews, RTLS-based contact tracing, and a combination of both methods were evaluated. The use of EMR-based and RTLS-based contact tracing methods was further validated by comparing their sensitivity and specificity against self-reported staff-patient contacts by health care workers. Results: Of 796 potential staff-patient contacts (between 17 patients and 162 staff members), 104 (13.1%) were identified by both the RTLS and EMR, 54 (6.8%) by the RTLS alone, and 99 (12.4%) by the EMR alone; 539 (67.7%) were not identified through either method. Compared to self-reported contacts, EMR reviews had a sensitivity of 47.2% and a specificity of 77.9%, while the RTLS had a sensitivity of 72.2% and a specificity of 87.7%. The highest sensitivity was obtained by including all contacts identified by either the RTLS or the EMR (sensitivity 77.8%, specificity 73.4%). Conclusions: RTLS-based contact tracing showed higher sensitivity and specificity than EMR review. Integration of both methods provided the best performance for rapid contact tracing, although technical adjustments to the RTLS and increasing user compliance with wearing of RTLS tags remain necessary.

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  • Global Infodemiology of COVID-19: Focus on Google web searches and Instagram hashtags

    Date Submitted: May 25, 2020

    Open Peer Review Period: May 25, 2020 - Jul 20, 2020

    Background: Several studies have been conducted using 'infodemiological' methods in COVID-19 research, but studies focusing to examine the extent of infodemic monikers (misinformation) on the internet...

    Background: Several studies have been conducted using 'infodemiological' methods in COVID-19 research, but studies focusing to examine the extent of infodemic monikers (misinformation) on the internet is very limited. Objective: We aimed to investigate the internet search behavior related to COVID-19 and the extent of infodemic monikers circulating in Google and Instagram during the pandemic period in the world. Methods: Using Google Trends and Instagram hashtags (#), we explored the internet search activities and behaviors related to COVID-19 pandemic all over the world from February 20, 2020, to May 06, 2020. Briefly, we investigated the names used to identify the virus, health and risk perception, life during the lockdown, and also information related to the adoption of infodemic monikers related to COVID-19. We computed the average peak volume (APC) with a 95% confidence interval (CI) during the study period. Results: The top five COVID-19 related terms used in Google searches were "coronavirus", "corona", "COVID", "virus", "corona virus", and "COVID-19". Countries with a higher number of COVID-19 cases have greater Google searches queries related to COVID-19. "coronavirus ozone", "coronavirus laboratory", "coronavirus 5G", "coronavirus conspiracy" and "coronavirus bill gates" are widely circulated infodemic monikers on the internet. Searches related to 'tips and cures' to COVID-19 spiked when the US president suggested an unproven drug as a 'miracle cure' and suggested injecting disinfectant to treat COVID-19. Around two-thirds (66.1%) of the Instagram users use "COVID-19", and "coronavirus" hashtags to disperse the information related to COVID-19. Conclusions: Globally, there is a growing interest in COVID-19 and a large number of infodemic monikers are circulating on the internet. Therefore, mass media regulators and health organizers should be vigilant to diminish the infodemic monikers dispersing on the internet and also should take serious actions against those spreading misinformation in social media.

  • Systematic and Statistical Review of COVID19 Treatment Trials

    Date Submitted: May 25, 2020

    Open Peer Review Period: May 25, 2020 - Jul 20, 2020

    Background: The COVID-19 pandemic produced multiple trials trying to promote certain treatments. However, the amount of studies having human controlled or randomized trials is scarce despite being im...

    Background: The COVID-19 pandemic produced multiple trials trying to promote certain treatments. However, the amount of studies having human controlled or randomized trials is scarce despite being important. Objective: The following systematic review and meta-analysis compiles the current data regarding human controlled COVID-19 treatment trials. Methods: An electronic search of the literature compiled studies pertaining to human controlled treatment trials with COVID-19. Medications assessed included lopinavir/ritonavir, arbidol, hydroxychloroquine, favipiravir, and heparin. Statistical analyzes were performed for common viral clearance endpoints whenever possible. Results: Lopinavir/ritonavir showed no significant effect on viral clearance for COVID-19 cases (OR 0.95 [95% CI 0.50-1.83]). Hydroxychloroquine also showed no significant effect on COVID-19 viral clearance rates (OR 2.16 [95% CI 0.80-5.84]). Arbidol showed no seven-day (OR 1.63 [95% CI 0.76-3.50]) or 14-day viral (OR 5.37 [95% CI 0.35-83.30]) clearance difference compared to lopinavir/ritonavir. Review of literature showed no significant clinical improvement with lopinavir/ritonavir, arbidol, hydroxychloroquine, or remdesivir. Favipiravir showed quicker symptom improvement compared to lopinavir/ritonavir and arbidol. Heparin showed improvement with severe COVID-19 cases. Conclusions: Current medications do not show significant effect on COVID-19 viral clearance rates. Favipiravir shows favorable results compared to other tested medications. Heparin shows benefit for severe cases of COVID-19.

  • Manifestations of mortality based global data of COVID-19; unifying global model through single parameter

    Date Submitted: May 22, 2020

    Open Peer Review Period: May 22, 2020 - Jul 17, 2020

    Critical inspection of the world data of COVID-19 mortality rates per population number has been made and used to express extensive variations in mortality over the globe in terms of a powered paramet...

    Critical inspection of the world data of COVID-19 mortality rates per population number has been made and used to express extensive variations in mortality over the globe in terms of a powered parameter λ varying from 0 to 1.2 expressed as a measure of strength of primary infection, originating from China source. The copying process is degenerating successively while infection is passed on to secondary subjects. We have been able to correlate global data through this parameter; any value close to or less than 1 shows significant impact of diluted multiple secondary effect. Further, the scatter diagram shows no effect of temperature of the geographical location and so is likely as the virus is only being spread from either contact or close proximity; the virus does not need to face highs and lows of temperatures of the environment. It stays only in the range of human body temperature and appears to be stable in 36 to 40C range. If it faces the environmental temperatures it is possible for its quicker deactivation but that situation never arises for this virus except when it spreads from surfaces.

  • Personalization in digital interventions for behavior change

    Date Submitted: May 22, 2020

    Open Peer Review Period: May 22, 2020 - Jul 17, 2020

    Effective behavior change interventions may require ongoing personalized support for users. Rapid developments in digital technology and artificial intelligence are giving rise to more advanced types...

    Effective behavior change interventions may require ongoing personalized support for users. Rapid developments in digital technology and artificial intelligence are giving rise to more advanced types of personalized interventions that can analyze large amounts of data to provide real-time, contextualized support. Despite growing research attention, there is still a lack of consensus in the literature about what is considered a personalized system, and how to design such system. This paper provides a definition of personalization and proposes a set of building blocks to design and implement personalized behavior change interventions, drawing on concepts from control systems engineering. We also discuss existing challenges in evaluating the net effects of personalized interventions and outline future directions in this field.

  • Information Regarding COVID-19 on the Internet: A Cross-sectional Study of Concerns

    Date Submitted: May 20, 2020

    Open Peer Review Period: May 20, 2020 - Jul 15, 2020

    Background: The Internet is one of the main sources of information about COVID-19. However, scant research has addressed the public’s disease-related concerns nor the relationships between concerns,...

    Background: The Internet is one of the main sources of information about COVID-19. However, scant research has addressed the public’s disease-related concerns nor the relationships between concerns, knowledge, and behavior related to COVID-19 prevention. Objective: Our objectives were to determine Chinese netizens’ concerns related to COVID-19 and its relationship with Internet information; and to elucidate the association between individuals’ concerns, knowledge, and behavior related to COVID-19. Methods: In this study, the questionnaire was designed to investigate Chinese netizens’ concerns, knowledge, and behavior related to COVID-19 during the rapid rise period of the outbreak. An online sample of Chinese residents was successfully recruited via Dingxiangyisheng WeChat. The questionnaire consisted of 15 closed-ended questions. Results: In total, 10,304 respondents were surveyed on the Internet (response rate = 1.75%, 10,304/590,000). Nearly all (95.30%) participants were concerned about “confirmed cases” and 87.70% received information about the outbreak through social media websites. There were significant differences in participants’ concerns by sex (P = .018), age (P < .001), educational attainment (P < .007), and occupation (P < .001). For all knowledge questions, including “incubation period (P < .001),” “transmission route (P = .001),” “symptoms (P < .001),” and “personal preventive knowledge (P < .001)”, participants who had higher concerns about COVID-19 were significantly more likely to answer questions correctly than were those who had less concerns. Surprisingly, people who were less concerned were more likely to avoid public places and public transportation than those who were more concerned. Conclusions: This study elucidated the concerns, information sources, and preventive behaviors of Chinese netizens related to the COVID-19 pandemic. People who were more concerned were more likely to obtain knowledge and take preventive measures than were their less concerned counterparts.

  • Application of the Online Big Data Platform in Monitoring Chinese Public Attention to the Outbreak of COVID-19

    Date Submitted: May 19, 2020

    Open Peer Review Period: May 19, 2020 - Jul 14, 2020

    Background: The outbreak of the COVID-19 epidemic in 2019 exerted an enormous global public reaction. Objective: The online big data reflects public attention of hot issues. This study aimed to use th...

    Background: The outbreak of the COVID-19 epidemic in 2019 exerted an enormous global public reaction. Objective: The online big data reflects public attention of hot issues. This study aimed to use the Baidu Index (BDI) and Sina Micro Index (SMI) to confirm the primitive correlation between COVID-19 related data and Chinese online data. Methods: Bivariate correlation statistics was used to check the relationship between epidemic trends of the BDI and SMI, and identify the difference of public concerns about COVID-19 between the epidemic area (Hubei province) and non-epidemic area (all other provinces). Results: The public's usage trend of the Baidu search engine and Sina Weibo was consistent during the COVID-19 outbreak (Pearson correlation coefficient =0.807, P<0.001). But compared with the SMI, the BDI was more closely related to the actual epidemic. The BDI and SMI had correlations with new confirmed cases (P<0.01), cumulative confirmed cases (P<0.01), cumulative death cases (P<0.01), new cured discharged cases (P<0.01), and cumulative cured discharged cases (P<0.01), but not with new death cases. Besides, the public's demand for information on COVID-19 was consistent and urgent across the country (Spearman correlation coefficient=0.930, P<0.001), regardless of the location of the epidemic area. Conclusions: The public paid more attention to indicators of confirmed cases due to numerous irresistible factors and cured circumstances with positive outcomes. But the public had a lag in the attention of COVID-19 in the non-epidemic area. In the risk communication of public health emergencies, relevant departments can effectively use the information dissemination characteristics of the Baidu search engine and Sina Weibo, to convey front-line information to the public timely and accurately, and improve the effectiveness of risk communication.

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