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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: Freepik.com; Copyright: master1305; URL: https://www.freepik.com/free-photo/doctor-advising-patient-online-with-laptop_8452110.htm; License: Licensed by JMIR.

    Rapid Utilization of Telehealth in a Comprehensive Cancer Center as a Response to COVID-19: Cross-Sectional Analysis

    Abstract:

    Background: The emergence of the coronavirus disease (COVID-19) pandemic in March 2020 created unprecedented challenges in the provision of scheduled ambulatory cancer care. As a result, there has been a renewed focus on video-based telehealth consultations as a means to continue ambulatory care. Objective: The aim of this study is to analyze the change in video visit volume at the University of California, San Francisco (UCSF) Comprehensive Cancer Center in response to COVID-19 and compare patient demographics and appointment data from January 1, 2020, and in the 11 weeks after the transition to video visits. Methods: Patient demographics and appointment data (dates, visit types, and departments) were extracted from the electronic health record reporting database. Video visits were performed using a HIPAA (Health Insurance Portability and Accountability Act)-compliant video conferencing platform with a pre-existing workflow. Results: In 17 departments and divisions at the UCSF Cancer Center, 2284 video visits were performed in the 11 weeks before COVID-19 changes were implemented (mean 208, SD 75 per week) and 12,946 video visits were performed in the 11-week post–COVID-19 period (mean 1177, SD 120 per week). The proportion of video visits increased from 7%-18% to 54%-72%, between the pre– and post–COVID-19 periods without any disparity based on race/ethnicity, primary language, or payor. Conclusions: In a remarkably brief period of time, we rapidly scaled the utilization of telehealth in response to COVID-19 and maintained access to complex oncologic care at a time of social distancing.

  • Source: Lyra Health; Copyright: Lyra Health; URL: https://www.jmir.org/2020/7/e18723; License: Licensed by the authors.

    Blended Care-Cognitive Behavioral Therapy for Depression and Anxiety in Real-World Settings: Pragmatic Retrospective Study

    Abstract:

    Background: The past few decades saw considerable advances in research and dissemination of evidence-based psychotherapies, yet available treatment resources are not able to meet the high need for care for individuals suffering from depression or anxiety. Blended care psychotherapy, which combines the strengths of therapist-led and internet interventions, can narrow this gap and be clinically effective and efficient, but has rarely been evaluated outside of controlled research settings. Objective: This study evaluated the effectiveness of a blended care intervention (video-based cognitive behavior therapy and internet intervention) under real-world conditions. Methods: This is a pragmatic retrospective cohort analysis of 385 participants with clinical range depression and/or anxiety symptoms at baseline, measured using Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), who enrolled in blended care psychotherapy treatment. Participants resided in the United States and had access to the blended care intervention as a mental health benefit offered through their employers. Levels of depression and anxiety were tracked throughout treatment. Hierarchical linear modeling was used to examine the change in symptoms over time. The effects of age, gender, and providers on participants’ symptom change trajectories were also evaluated. Paired sample t-tests were also conducted, and rates of positive clinical change and clinically significant improvement were calculated. Results: The average depression and anxiety symptoms at 6 weeks after the start of treatment were 5.94 and 6.57, respectively. There were significant linear effects of time on both symptoms of depression and anxiety (β=–.49, P<.001 and β=–.64, P<.001). The quadratic effect was also significant for both symptoms of depression and anxiety (β=.04, P<.001 for both), suggesting a decelerated decrease in symptoms over time. Approximately 73% (n=283) of all 385 participants demonstrated reliable improvement, and 83% (n=319) recovered on either the PHQ-9 or GAD-7 measures. Large effect sizes were observed on both symptoms of depression (Cohen d=1.08) and of anxiety (d=1.33). Conclusions: Video blended care cognitive behavioral therapy interventions can be effective and efficient in treating symptoms of depression and anxiety in real-world conditions. Future research should investigate the differential and interactive contribution of the therapist-led and digital components of care to patient outcomes to optimize care.

  • Source: rawpixel.com; Copyright: free image; URL: https://www.rawpixel.com/image/993378/free-image-rawpixelcom; License: Licensed by the authors.

    Use of an Unguided, Web-Based Distress Self-Management Program After Breast Cancer Diagnosis: Sub-Analysis of CaringGuidance Pilot Study

    Abstract:

    Background: Unguided, web-based psychoeducational interventions are gaining interest as a way to reach patients while reducing pressure on clinical resources. However, there has been little research on how patients with cancer use these interventions. Objective: The objective of this analysis was to evaluate how women newly diagnosed with breast cancer used the unguided web-based, psychoeducational distress self-management program CaringGuidance After Breast Cancer Diagnosis while enrolled in a pilot feasibility study. Methods: Women with stage 0 to II breast cancer diagnosed within the prior three months were recruited from clinics primarily in the Northeastern United States for participation in a 12-week pilot study of CaringGuidance plus usual care versus usual care alone. Usage prompts included sets of emails sent weekly for 12 weeks; standardized congratulatory emails after every two hours of program use, and informative emails for each cognitive-behavioral exercise. Individual user activity on the site was automatically tracked by an analytics system and recorded directly in the CaringGuidance database. Results: Complete usage data were available for 54 subjects. Ninety-eight percent of the intervention group logged into CaringGuidance independently at least once. Thirty-eight (70%) logged in during all three months, 15 (28%) were intermittent users, and one (2%) was a non-user. Users (n=53) averaged 15.6 (SD 9.85) logins. Mean logins were greatest in month 1 (7.26, SD 4.02) and declined in months 2 (4.32, SD 3.66) and month 3 (4.02, SD 3.82). Eleven (21%) used CaringGuidance with both the frequency and activity level intended at study outset, 9 (17%) exceeded intended frequency and activity (high-high users), and 10 (19%) were below expected usage on both login frequency and activity (low-low users). Low-low users and high-high users differed significantly (P<.001) in the total number of views and unique views of all program components. Change in depressive symptoms and the number of sessions (r=.351) and logins (r=.348) between study months 1 and 2 were significantly correlated (P=.018, .019). Higher baseline distress was associated with more unique views of program resources (r=.281, P=.043). Change in intrusive/avoidant thoughts from baseline to month 3, and the number of users’ unique exercise views were negatively correlated (r=–.319, P=.035) so that more unique exercise views, equated with greater decline in intrusive/avoidant thoughts from baseline to month 3. Conclusions: These findings favor the hypothesis that the key ingredient is not the amount of program use, but each user’s self-selected activity within the program. More research is needed on the ideal ways to maintain use, and capture and define engagement and enactment of behaviors by people with cancer accessing unguided, self-management web-based programs.

  • Medicine, diabetes, glycemia, health care and people concept - close up of woman hands with smartphone checking blood sugar level by glucometer at home. Source: Colourbox; Copyright: Syda Productions; URL: https://www.colourbox.com/image/close-up-of-woman-with-smartphone-doing-blood-test-image-25244831; License: Licensed by the authors.

    Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review

    Abstract:

    Background: There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients’ skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but there are few standards for this. And although there are many methods for evaluating apps and digital interventions, a more specific approach might be needed for assessing digital diabetes self-management interventions. Objective: This review aims to identify which methods and criteria are used to evaluate apps and digital interventions for diabetes self-management, and to describe how patients were involved in these evaluations. Methods: We searched CINAHL, EMBASE, MEDLINE, and Web of Science for articles published from 2015 that referred to the evaluation of apps and digital interventions for diabetes self-management and involved patients in the evaluation. We then conducted a narrative qualitative synthesis of the findings, structured around the included studies’ quality, methods of evaluation, and evaluation criteria. Results: Of 1681 articles identified, 31 fulfilled the inclusion criteria. A total of 7 articles were considered of high confidence in the evidence. Apps were the most commonly used platform for diabetes self-management (18/31, 58%), and type 2 diabetes (T2D) was the targeted health condition most studies focused on (12/31, 38%). Questionnaires, interviews, and user-group meetings were the most common methods of evaluation. Furthermore, the most evaluated criteria for apps and digital diabetes self-management interventions were cognitive impact, clinical impact, and usability. Feasibility and security and privacy were not evaluated by studies considered of high confidence in the evidence. Conclusions: There were few studies with high confidence in the evidence that involved patients in the evaluation of apps and digital interventions for diabetes self-management. Additional evaluation criteria, such as sustainability and interoperability, should be focused on more in future studies to provide a better understanding of the effects and potential of apps and digital interventions for diabetes self-management.

  • Source: pexels.com; Copyright: Andrea Piacquadio; URL: https://www.pexels.com/photo/two-adult-women-beside-each-other-3768114/; License: Licensed by JMIR.

    Diabetes-Related Topics in an Online Forum for Caregivers of Individuals Living With Alzheimer Disease and Related Dementias: Qualitative Inquiry

    Abstract:

    Background: Diabetes and Alzheimer disease and related dementias (ADRD) are the seventh and sixth leading causes of death in the United States, respectively, and they coexist in many older adults. Caring for a loved one with both ADRD and diabetes is challenging and burdensome. Objective: This study aims to explore diabetes-related topics in the Alzheimer’s Association ALZConnected caregiver forum by family caregivers of persons living with ADRD. Methods: User posts on the Alzheimer’s Association ALZConnected caregiver forum were extracted. A total of 528 posts related to diabetes were included in the analysis. Of the users who generated the 528 posts, approximately 96.1% (275/286) were relatives of the care recipient with ADRD (eg, child, grandchild, spouse, sibling, or unspecified relative). Two researchers analyzed the data independently using thematic analysis. Any divergence was discussed among the research team, and an agreement was reached with a senior researcher’s input as deemed necessary. Results: Thematic analysis revealed 7 key themes. The results showed that comorbidities of ADRD were common topics of discussions among family caregivers. Diabetes management in ADRD challenged family caregivers. Family caregivers might neglect their own health care because of the caring burden, and they reported poor health outcomes and reduced quality of life. The online forum provided a platform for family caregivers to seek support in their attempts to learn more about how to manage the ADRD of their care recipients and seek support for managing their own lives as caregivers. Conclusions: The ALZConnected forum provided a platform for caregivers to seek informational and emotional support for caring for persons living with ADRD and diabetes. The overwhelming burdens with these two health conditions were apparent for both caregivers and care recipients based on discussions from the online forum. Studies are urgently needed to provide practical guidelines and interventions for diabetes management in individuals with diabetes and ADRD. Future studies to explore delivering diabetes management interventions through online communities in caregivers and their care recipients with ADRD and diabetes are warranted.

  • Source: Pixabay; Copyright: JoshuaWoroniecki; URL: https://pixabay.com/photos/african-american-phone-cell-black-5255393/; License: Licensed by JMIR.

    Evaluation of Adaptive Feedback in a Smartphone-Based Game on Health Care Providers’ Learning Gain: Randomized Controlled Trial

    Abstract:

    Background: Although smartphone-based emergency care training is more affordable than traditional avenues of training, it is still in its infancy, remains poorly implemented, and its current implementation modes tend to be invariant to the evolving learning needs of the intended users. In resource-limited settings, the use of such platforms coupled with gamified approaches remains largely unexplored, despite the lack of traditional training opportunities, and high mortality rates in these settings. Objective: The primary aim of this randomized experiment is to determine the effectiveness of offering adaptive versus standard feedback, on the learning gains of clinicians, through the use of a smartphone-based game that assessed their management of a simulated medical emergency. A secondary aim is to examine the effects of learner characteristics and learning spacing with repeated use of the game on the secondary outcome of individualized normalized learning gain. Methods: The experiment is aimed at clinicians who provide bedside neonatal care in low-income settings. Data were captured through an Android app installed on the study participants’ personal phones. The intervention, which was based on successful attempts at a learning task, included adaptive feedback provided within the app to the experimental arm, whereas the control arm received standardized feedback. The primary end point was completion of the second learning session. Of the 572 participants enrolled between February 2019 and July 2019, 247 (43.2%) reached the primary end point. The primary outcome was standardized relative change in learning gains between the study arms as measured by the Morris G effect size. The secondary outcomes were the participants individualized normalized learning gains. Results: The effect of adaptive feedback on care providers’ learning gain was found to be g=0.09 (95% CI −0.31 to 0.46; P=.47). In exploratory analysis, using normalized learning gains, when subject-treatment interaction and differential time effect was controlled for, this effect increased significantly to 0.644 (95% CI 0.35 to 0.94; P<.001) with immediate repetition, which is a moderate learning effect, but reduced significantly by 0.28 after a week. The overall learning change from the app use in both arms was large and may have obscured a direct effect of feedback. Conclusions: There is a considerable learning gain between the first two rounds of learning with both forms of feedback and a small added benefit of adaptive feedback after controlling for learner differences. We suggest that linking the adaptive feedback provided to care providers to how they space their repeat learning session(s) may yield higher learning gains. Future work might explore in more depth the feedback content, in particular whether or not explanatory feedback (why answers were wrong) enhances learning more than reflective feedback (information about what the right answers are). Trial Registration: Pan African Clinical Trial Registry (PACTR) 201901783811130; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=5836

  • Source: Freepik; Copyright: Freepik; URL: https://www.freepik.com/free-photo/man-speaking-with-partner-by-video_2453522.htm#query=video%20call&position=48; License: Licensed by JMIR.

    The Acceptability and Usability of Digital Health Interventions for Adults With Depression, Anxiety, and Somatoform Disorders: Qualitative Systematic Review...

    Abstract:

    Background: The prevalence of mental health disorders continues to rise, with almost 4% of the world population having an anxiety disorder and almost 3.5% having depression in 2017. Despite the high prevalence, only one-third of people with depression or anxiety receive treatment. Over the last decade, the use of digital health interventions (DHIs) has risen rapidly as a means of accessing mental health care and continues to increase. Although there is evidence supporting the effectiveness of DHIs for the treatment of mental health conditions, little is known about what aspects are valued by users and how they might be improved. Objective: This systematic review aimed to identify, appraise, and synthesize the qualitative literature available on service users’ views and experiences regarding the acceptability and usability of DHIs for depression, anxiety, and somatoform disorders. Methods: A systematic search strategy was developed, and searches were run in 7 electronic databases. Qualitative and mixed methods studies published in English were included. A meta-synthesis was used to interpret and synthesize the findings from the included studies. Results: A total of 24 studies were included in the meta-synthesis, and 3 key themes emerged with descriptive subthemes. The 3 key themes were initial motivations and approaches to DHIs, personalization of treatment, and the value of receiving personal support in DHIs. The meta-synthesis suggests that participants’ initial beliefs about DHIs can have an important effect on their engagement with these types of interventions. Personal support was valued very highly as a major component of the success of DHIs. The main reason for this was the way it enabled individual personalization of care. Conclusions: Findings from the systematic review have implications for the design of future DHIs to improve uptake, retention, and outcomes in DHIs for depression, anxiety, and somatoform disorders. DHIs need to be personalized to the specific needs of the individual. Future research should explore whether the findings could be generalized to other health conditions.

  • Untitled. Source: Freepik; Copyright: freepik; URL: https://www.freepik.com/free-photo/person-s-hand-using-digital-tablet-with-blocks-social-media-applications_2593441.htm; License: Licensed by JMIR.

    The Use of Social Media to Increase the Impact of Health Research: Systematic Review

    Abstract:

    Background: Academics in all disciplines increasingly use social media to share their publications on the internet, reaching out to different audiences. In the last few years, specific indicators of social media impact have been developed (eg, Altmetrics), to complement traditional bibliometric indicators (eg, citation count and h-index). In health research, it is unclear whether social media impact also translates into research impact. Objective: The primary aim of this study was to systematically review the literature on the impact of using social media on the dissemination of health research. The secondary aim was to assess the correlation between Altmetrics and traditional citation-based metrics. Methods: We conducted a systematic review to identify studies that evaluated the use of social media to disseminate research published in health-related journals. We specifically looked at studies that described experimental or correlational studies linking the use of social media with outcomes related to bibliometrics. We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases using a predefined search strategy (International Prospective Register of Systematic Reviews: CRD42017057709). We conducted independent and duplicate study selection and data extraction. Given the heterogeneity of the included studies, we summarized the findings through a narrative synthesis. Results: Of a total of 18,624 retrieved citations, we included 51 studies: 7 (14%) impact studies (answering the primary aim) and 44 (86%) correlational studies (answering the secondary aim). Impact studies reported mixed results with several limitations, including the use of interventions of inappropriately low intensity and short duration. The majority of correlational studies suggested a positive association between traditional bibliometrics and social media metrics (eg, number of mentions) in health research. Conclusions: We have identified suggestive yet inconclusive evidence on the impact of using social media to increase the number of citations in health research. Further studies with better design are needed to assess the causal link between social media impact and bibliometrics.

  • Source: Image created by the Authors/Placeit; Copyright: The Authors/Placeit; URL: http://www.jmir.org/2020/6/e15605/; License: Licensed by JMIR.

    A Precision Medicine Tool for Patients With Multiple Sclerosis (the Open MS BioScreen): Human-Centered Design and Development

    Abstract:

    Background: Patients with multiple sclerosis (MS) face several challenges in accessing clinical tools to help them monitor, understand, and make meaningful decisions about their disease course. The University of California San Francisco MS BioScreen is a web-based precision medicine tool initially designed to be clinician facing. We aimed to design a second, openly available tool, Open MS BioScreen, that would be accessible, understandable, and actionable by people with MS. Objective: This study aimed to describe the human-centered design and development approach (inspiration, ideation, and implementation) for creating the Open MS BioScreen platform. Methods: We planned an iterative and cyclical development process that included stakeholder engagement and iterative feedback from users. Stakeholders included patients with MS along with their caregivers and family members, MS experts, generalist clinicians, industry representatives, and advocacy experts. Users consisted of anyone who wants to track MS measurements over time and access openly available tools for people with MS. Phase I (inspiration) consisted of empathizing with users and defining the problem. We sought to understand the main challenges faced by patients and clinicians and what they would want to see in a web-based app. In phase II (ideation), our multidisciplinary team discussed approaches to capture, display, and make sense of user data. Then, we prototyped a series of mock-ups to solicit feedback from clinicians and people with MS. In phase III (implementation), we incorporated all concepts to test and iterate a minimally viable product. We then gathered feedback through an agile development process. The design and development were cyclical—many times throughout the process, we went back to the drawing board. Results: This human-centered approach generated an openly available, web-based app through which patients with MS, their clinicians, and their caregivers can access the site and create an account. Users can enter information about their MS (basic level as well as more advanced concepts), visualize their data longitudinally, access a series of algorithms designed to empower them to make decisions about their treatments, and enter data from wearable devices to encourage realistic goal setting about their ambulatory activity. Agile development will allow us to continue to incorporate precision medicine tools, as these are validated in the clinical research arena. Conclusions: After engaging intended users into the iterative human-centered design of the Open MS BioScreen, we will now monitor the adaptation and dissemination of the tool as we expand its functionality and reach. The insights generated from this approach can be applied to the development of a number of self-tracking, self-management, and user engagement tools for patients with chronic conditions.

  • Source: Adobe Stock; Copyright: Seventyfour; URL: https://stock.adobe.com/ca/images/portrait-of-young-middle-eastern-woman-wearing-hijab-working-as-nurse-in-medical-clinic-and-using-computer-at-workplace-copy-space/289855567?asset_id=289855567; License: Licensed by JMIR.

    Integrating Health Technologies in Health Services for Syrian Refugees in Lebanon: Qualitative Study

    Abstract:

    Background: Lebanon currently hosts around one million Syrian refugees. There has been an increasing interest in integrating eHealth and mHealth technologies into the provision of primary health care to refugees and Lebanese citizens. Objective: We aimed to gain a deeper understanding of the potential for technology integration in primary health care provision in the context of the protracted Syrian refugee crisis in Lebanon. Methods: A total of 17 face-to-face semistructured interviews were conducted with key informants (n=8) and health care providers (n=9) involved in the provision of health care to the Syrian refugee population in Lebanon. Interviews were audio recorded and directly translated and transcribed from Arabic to English. Thematic analysis was conducted. Results: Study participants indicated that varying resources, primarily time and the availability of technologies at primary health care centers, were the main challenges for integrating technologies for the provision of health care services for refugees. This challenge is compounded by refugees being viewed by participants as a mobile population thus making primary health care centers less willing to invest in refugee health technologies. Lastly, participant views regarding the health and technology literacies of refugees varied and that was considered to be a challenge that needs to be addressed for the successful integration of refugee health technologies. Conclusions: Our findings indicate that in the context of integrating technology into the provision of health care for refugees in a low or middle income country such as Lebanon, some barriers for technology integration related to the availability of resources are similar to those found elsewhere. However, we identified participant views of refugees’ health and technology literacies to be a challenge specific to the context of this refugee crisis. These challenges need to be addressed when considering refugee health technologies. This could be done by increasing the visibility of refugee capabilities and configuring refugee health technologies so that they may create spaces in which refugees are empowered within the health care system and can work toward debunking the views discovered in this study.

  • Source: FlickR; Copyright: Marco Verch; URL: https://www.flickr.com/photos/149561324@N03/27289577028/in/photolist-5wx88t-7JaQvb-nJ8QAF-5hygTA-caR8nd-9jX3Pw-EFkSqZ-HzuduL-57YMvg-5i8ZvA-5xP7Hs-Y3mTWM-5v4D74-bCAqhk-EuUdnm-2fsKfzW-6DPVqE-613SBd-6jNe5t-65tnNi-5eM3NG-6LejBt-6jS7DQ-5wBrCN-ymB1Q5-2hMwfk3-c8; License: Creative Commons Attribution (CC-BY).

    Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement

    Abstract:

    Background: Designing technologies that users will be interested in, start using, and keep using has long been a challenge. In the health domain, the question of technology acceptance is even more important, as the possible intrusiveness of technologies could lead to patients refusing to even try them. Developers and researchers must address this question not only in the design and evaluation of new health care technologies but also across the different stages of the user’s journey. Although a range of definitions for these stages exists, many researchers conflate related terms, and the field would benefit from a coherent set of definitions and associated measurement approaches. Objective: This review aims to explore how technology acceptance is interpreted and measured in mobile health (mHealth) literature. We seek to compare the treatment of acceptance in mHealth research with existing definitions and models, identify potential gaps, and contribute to the clarification of the process of technology acceptance. Methods: We searched the PubMed database for publications indexed under the Medical Subject Headings terms “Patient Acceptance of Health Care” and “Mobile Applications.” We included publications that (1) contained at least one of the terms “acceptability,” “acceptance,” “adoption,” “accept,” or “adopt”; and (2) defined the term. The final corpus included 68 relevant studies. Results: Several interpretations are associated with technology acceptance, few consistent with existing definitions. Although the literature has influenced the interpretation of the concept, usage is not homogeneous, and models are not adapted to populations with particular needs. The prevalence of measurement by custom surveys suggests a lack of standardized measurement tools. Conclusions: Definitions from the literature were published separately, which may contribute to inconsistent usage. A definition framework would bring coherence to the reporting of results, facilitating the replication and comparison of studies. We propose the Technology Acceptance Lifecycle, consolidating existing definitions, articulating the different stages of technology acceptance, and providing an explicit terminology. Our findings illustrate the need for a common definition and measurement framework and the importance of viewing technology acceptance as a staged process, with adapted measurement methods for each stage.

  • Source: freepik; Copyright: freepik; URL: https://www.freepik.com/free-photo/woman-checking-her-phone-outside_7534590.htm; License: Licensed by JMIR.

    Racial and Ethnic Digital Divides in Posting COVID-19 Content on Social Media Among US Adults: Secondary Survey Analysis

    Abstract:

    Background: Public health surveillance experts are leveraging user-generated content on social media to track the spread and effects of COVID-19. However, racial and ethnic digital divides, which are disparities among people who have internet access and post on social media, can bias inferences. This bias is particularly problematic in the context of the COVID-19 pandemic because due to structural inequalities, members of racial and ethnic minority groups are disproportionately vulnerable to contracting the virus and to the deleterious economic and social effects from mitigation efforts. Further, important demographic intersections with race and ethnicity, such as gender and age, are rarely investigated in work characterizing social media users; however, they reflect additional axes of inequality shaping differential exposure to COVID-19 and its effects. Objective: The aim of this study was to characterize how the race and ethnicity of US adults are associated with their odds of posting COVID-19 content on social media and how gender and age modify these odds. Methods: We performed a secondary analysis of a survey conducted by the Pew Research Center from March 19 to 24, 2020, using a national probability sample (N=10,510). Respondents were recruited from an online panel, where panelists without an internet-enabled device were given one to keep at no cost. The binary dependent variable was responses to an item asking whether respondents “used social media to share or post information about the coronavirus.” We used survey-weighted logistic regressions to estimate the odds of responding in the affirmative based on the race and ethnicity of respondents (white, black, Latino, other race/ethnicity), adjusted for covariates measuring sociodemographic background and COVID-19 experiences. We examined how gender (female, male) and age (18 to 30 years, 31 to 50 years, 51 to 64 years, and 65 years and older) intersected with race and ethnicity by estimating interactions. Results: Respondents who identified as black (odds ratio [OR] 1.29, 95% CI 1.02-1.64; P=.03), Latino (OR 1.66, 95% CI 1.36-2.04; P<.001), or other races/ethnicities (OR 1.33, 95% CI 1.02-1.72; P=.03) had higher odds than respondents who identified as white of reporting that they posted COVID-19 content on social media. Women had higher odds of posting than men regardless of race and ethnicity (OR 1.58, 95% CI 1.39-1.80; P<.001). Among men, respondents who identified as black, Latino, or members of other races/ethnicities were significantly more likely to post than respondents who identified as white. Older adults (65 years or older) had significantly lower odds (OR 0.73, 95% CI 0.57-0.94; P=.01) of posting compared to younger adults (18-29 years), particularly among those identifying as other races/ethnicities. Latino respondents were the most likely to report posting across all age groups. Conclusions: In the United States, members of racial and ethnic minority groups are most likely to contribute to COVID-19 content on social media, particularly among groups traditionally less likely to use social media (older adults and men). The next step is to ensure that data collection procedures capture this diversity by encompassing a breadth of search criteria and social media platforms.

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    Date Submitted: Jul 4, 2020

    Open Peer Review Period: Jul 4, 2020 - Aug 29, 2020

    Background: As the COVID-19 pandemic disrupted medical practice, telemedicine emerged as an alternative to outpatient visits. However, it is unknown how patients and physicians respond to an accelerat...

    Background: As the COVID-19 pandemic disrupted medical practice, telemedicine emerged as an alternative to outpatient visits. However, it is unknown how patients and physicians respond to an accelerated implementation of this model of medical care. Objective: To report the system-wide accelerated implementation of telemedicine, compare patient satisfaction between telemedicine and in-person visits, and report provider perceptions. Methods: A convergent parallel mixed-methods study design consisting of simultaneous use of both qualitative and quantitative methods. This study was conducted at the UC-Christus Health Network, a large private academic health network in Santiago, Chile. Satisfaction of patients receiving telemedicine care between March and April, 2020, was compared to those receiving in-person care during the same period (concurrent control group) and during March and April, 2019 (retrospective control group). Patient satisfaction with in-person care was measured using the Net Promoter Score (NPS) survey. Satisfaction with telemedicine was assessed by patients using an online survey assessing similar domains. Providers rated their satisfaction and responded to open-ended questions assessing challenges, strategies to address them, the diagnostic process, treatment, and the patient-provider relationship. Results: A total of 3,962 patients receiving telemedicine, 1,187 patients from the concurrent control group, and 1,848 from the retrospective control group completed the surveys. Satisfaction was very high with both telemedicine and in-person services. Overall, 263 physicians from over 41 specialties responded the survey. During telemedicine visits, most providers felt their clinical skills were challenged (61.8%). Female providers felt more challenged than male providers (70.7% vs 50.9%, P = .002). Surgeons, obstetricians and gynecologists felt their clinical skills were challenged the least, compared to providers from non-surgical specialties (P < .001). Challenges related to the delivery modality, diagnostic process, and patient-provider relationship differed according to the provider’s specialty (P = .046, P < .001, and P = .022, respectively). Conclusions: Telemedicine implemented in response to the COVID-19 pandemic produced high patient and provider satisfaction. Specialty groups perceive the impact of this new mode of clinical practice differently.

  • A COVID-19 Contact Tracing Self-Confirmation System for the General Population in Japan: Design and Implementation Evaluation

    Date Submitted: Jul 4, 2020

    Open Peer Review Period: Jul 4, 2020 - Aug 29, 2020

    Background: The global spread of coronavirus disease (COVID-19) has attracted extensive research concerns. It is an infectious disease resulting from a novel virus termed severe acute respiratory synd...

    Background: The global spread of coronavirus disease (COVID-19) has attracted extensive research concerns. It is an infectious disease resulting from a novel virus termed severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). The joint collaboration of Ministry of Health, Labor and Welfare (MHLW) in Japan and new coronavirus infection control team has led to the formal issuance of a Bluetooth-based mobile app, which integrates privacy and security protection with methodical processing required for effective contact tracing of exposure to COVID-19. Objective: Due to the demand for a contact tracing instrument that timely keeps track of exposure, teams of professionals and authority experts contributed to the design and implementation of a mobile app intended to provide the general population with updates of contacts at the individual level, including both the infected and the exposed, to manage the risk of close contacts in Japan. This study aims to evaluate the development and distribution of a Bluetooth-based mobile contact-confirming application (COCOA) for COVID-19 to integrate the efforts by healthcare practitioners, the infected and the exposed to contain the spread of COVID-19. Methods: The Exposure Notification Framework (AGF) co-provided by Apple and Google is used in the provision of service. It distributes validated incremental information of COVID-19 that is closely related but might be unware to the individuals. Great emphasis is placed on the correct understanding of seven major steps (issue and confirm process code, report infection status, request information of the infected, calculate and compare exposure summary, provision of response guidance) needed in the process. Results: COCOA consists of three major components: the two mobile apps for the infected and exposed individuals respectively and the notification system that is used to manage and broadcast the information of infection and exposure. Users can self-confirm the risk of exposure to the COVID-19 by periodically fetching the outbreak data and choose provided available response to COVID-19. Conclusions: COCOA is a mobile-based self-confirmation telehealth system developed to assist not only the government and healthcare providers, but also the infected and the exposed individuals to contain COVID-19 through rapid responses and effective non-contact cooperation. The design and the mechanism presents a desirable capacity to promote non-contact cooperation, forecast the potential risk of being infected and facilitate consequential measures to prevent further spread.

  • Evaluation of problem-based learning innovation in medical education during the COVID-19 pandemic: a qualitative study among medical students

    Date Submitted: Jul 3, 2020

    Open Peer Review Period: Jul 3, 2020 - Jul 10, 2020

    Background: Most educators affected by the COVID-19 epidemic have had to find the most appropriate teaching approach to deal with this emergency teaching situation, i.e., an approach that can make goo...

    Background: Most educators affected by the COVID-19 epidemic have had to find the most appropriate teaching approach to deal with this emergency teaching situation, i.e., an approach that can make good use of various teaching resources to achieve high adaptability. According to the characteristics of medical students and the course content of clinical clerkship, we adopted the problem-based learning (PBL) method to redesign the pedagogy of clerkship. At the end of the semester, the feasibility of the PBL teaching model in emergency remote teaching (ERT), which has an impact on students' learning experience and preference, was evaluated. Compared with other countries affected by the COVID-19 epidemic, the outbreak time and recovery time in China are both earlier; thus, the evaluation and feedback of ERT can provide the referential evidence to global educators and institutions. Objective: The objective of this study was to explore medical students' learning experience in ERT to understand how these positive and negative perceptions influence their learning preferences in different teaching modes and how the PBL model combined digital technology to influence teaching quality. Methods: Among 123 medical students from Jinan University, China, who participated in the questionnaire at the end of the ERT in the clinical clerkship course, 25 volunteered to have a further in-depth interview. We randomly select five veterinary students to participate in the one-on-one in-depth online interview, which was conducted within 30 minutes. After coding of the transcription by the NVivo 12.0 software, the collected qualitative data would undergo a thematic analysis. Results: The thematic analysis indicated two main themes. One is that the adoption of PBL is the crucial for overseas medical students to evaluate ERT positively, and is depicted by one sub-theme: positive comment contributions. The other theme is that clinical practice as the core of medical education has a decisive influence on the teaching mode preference of medical students, as depicted by two sub-themes: negative comment contributions; and preference in different teaching methods. Conclusions: Although medical students preferred an offline teaching mode due to practical requirements, they generally gave positive comments on this ERT because of the PBL method pedagogy. This indicated the feasibility of the online PBL teaching method in medical education. Moreover, medical students' preferences in the combination of the online and offline teaching mode revealed a revolutionary new direction of revolution in medical education.

  • Noncommunicable chronic disease and the risk of COVID-19: a population-based case-control study

    Date Submitted: Jul 2, 2020

    Open Peer Review Period: Jul 2, 2020 - Aug 27, 2020

    Objective: To investigate the association of the non-communicable chronic disease (NCD) with the risk of coronavirus disease 2019 (COVID-19). Methods: A case-control study was conducted. The cases we...

    Objective: To investigate the association of the non-communicable chronic disease (NCD) with the risk of coronavirus disease 2019 (COVID-19). Methods: A case-control study was conducted. The cases were laboratory-confirmed COVID-19 who were treated in the Union Hospital in Wuhan. The healthy controls were randomly selected from the participants of the Hunan Government Employee Cohort study who were not infected with COVID-19, matching by age and sex. NCDs including hypertension, diabetes, coronary heart disease, chronic pulmonary disease, and cancer were determined by self-reportings, use of medications, measurements, and/or laboratory testings. The severity of COVID-19 was determined by physicians according to the guideline. Logistic regression was used to estimate the association, in terms of odds ratio (OR). Results: A total of 468 cases and 1404 controls (1:3) were included in the analysis with a mean age of 59.1±12.8 years and 51.7% male. The case group comprised 134 moderately ill, 275 severely ill, and 59 critically ill COVID-19 patients. Patients with diabetes (OR=3.23, P<0.001), chronic pulmonary disease (OR=5.99, P<0.001), and hypertension (OR=1.45, P=0.001) showed a significantly increased risk of COVID-19 infection compared to the healthy controls. Additionally, diabetes, chronic pulmonary disease, hypertension, and the number of comorbid NCDs were associated with the severity of COVID-19 dose-dependently. Conclusions: Patients with diabetes, hypertension, and chronic pulmonary disease are at a higher risk of having COVID-19 and developing severe type of the disease.

  • An automated model for forecasting non-elective hospital bed demand in the entire English National Health System: retrospective process assessment study

    Date Submitted: Jun 30, 2020

    Open Peer Review Period: Jun 30, 2020 - Aug 25, 2020

    Background: From 2006/2007 to 2017/2018, there was a 26% increase in emergency department (ED) attendances and 32% increase in total admissions in the National Health Service in England (NHS). Growing...

    Background: From 2006/2007 to 2017/2018, there was a 26% increase in emergency department (ED) attendances and 32% increase in total admissions in the National Health Service in England (NHS). Growing demand puts severe strain on hospitals, resulting in bed, nursing, clinical and equipment shortages. Nevertheless, scheduling issues can still result in significant under-utilization of beds. It is imperative to optimize the allocation of existing healthcare resources, including hospital beds. More accurate and reliable long-term hospital bed occupancy rate prediction would help managers plan ahead for their population’s hospital requirements, ultimately resulting in greater efficiencies and better patient care. Objective: This study aimed to compare widely used automated time series forecasting techniques to predict short-term daily non-elective bed occupancy at all trusts in the NHS. Methods: Bed occupancy models that accounted for patterns in occupancy were created for each trust in the NHS. Daily non-elective midnight trust occupancy data from April 2011 to March 2017 for 121 NHS trusts were utilized to generate these models. Forecasts were generated using the three most widely used automated forecasting techniques: Exponential Smoothing (ES); Seasonal Autoregressive Integrated Moving Average (SARIMA); Trigonometric, Box-Cox transform, ARMA errors, Trend and Seasonal components (TBATS). The NHS Modernization Agency’s recommended forecasting method prior to 2020, was also replicated. A comparative analysis of forecast accuracy was conducted by comparing forecasted daily non-elective occupancy with actual non-elective occupancy in the out-of-sample dataset for each week forecasted. Percentage root mean squared error (RMSE) was reported. Results: The accuracy of the models varied based on the season during which occupancy was forecasted. For the summer season, percent RMSE values for each model remained relatively stable across six forecasted weeks. However, only the TBATS model (median error 2.45% for six weeks) outperformed the NHS Modernization Agency’s recommended method (median error 2.63% for six weeks). In contrast, during the winter season, percent RMSE values increased as we forecasted further into the future. ES generated the most accurate forecasts (median error 4.91% over four weeks), but all models outperformed the NHS Modernization Agency’s recommended method prior to 2020 (median 8.5% error over four weeks). Conclusions: It is possible to create automated models, similar to those recently published by the NHS, that can be used at a hospital level for a large, national healthcare system in order to predict non-elective bed admissions and thus schedule elective procedures. Clinical Trial: N/A

  • A text-mining analysis of public perceptions and topic modeling during the COVID-19 pandemic using Twitter data

    Date Submitted: Jun 30, 2020

    Open Peer Review Period: Jun 30, 2020 - Jul 8, 2020

    Background: Coronavirus disease (COVID-19) is a scientifically and medically novel disease that is not fully understood as it needs to be consistently and deeply studied. In the past, research on the...

    Background: Coronavirus disease (COVID-19) is a scientifically and medically novel disease that is not fully understood as it needs to be consistently and deeply studied. In the past, research on the COVID-19 outbreak was only able to predict quantity data such as the number of outbreaks, but not infoveillance data. Objective: This study aims to understand public perceptions on the trends of the COVID-19 pandemic and uncover meaningful themes of concern posted by Twitter users during the pandemic throughout the world. Methods: Data mining on Twitter was conducted to collect a total of 107,990 tweets between December 13 and March 9, 2020. The analysis included time series, sentiment analysis and topic modeling to identify the most common topics in the tweets as well as to categorize clusters and find themes from keyword analysis. Results: The results indicate three main aspects of public awareness and concerns regarding the COVID-19 pandemic. Firstly, the study indicated the trend of the spread and symptoms of COVID-19, which was divided into three stages. Secondly, the results of the sentiment analysis and emotional tendency showed that the people had a negative outlook toward COVID-19. Thirdly, topic modeling and themes relating to COVID-19 and the outbreak were divided into three categories, including (1) emergency of COVID-19 impact, (2) the epidemic situation and how to control it, and (3) news and social media reporting on the epidemic. Conclusions: Sentiment analysis and topic modeling can produce useful information about the trend of COVID-19 pandemic and alternative perspectives to investigate the COVID-19 crisis which has created considerable public awareness around the world. This finding shows that Twitter is a good communication channel for understanding both public concern and awareness about COVID-19 disease. These findings can help health departments to communicate information as to what the public thinks about the disease.

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