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Background: Since the beginning of the COVID-19 pandemic, a great number of papers have been published in the pediatric field. Objective: We aimed to assess research around the globe on COVID-19 in the pediatric field by bibliometric analysis, identifying publication trends and topic dissemination and showing the relevance of publishing authors, institutions, and countries. Methods: The Scopus database was comprehensively searched for all indexed documents published between January 1, 2020, and June 11, 2020, dealing with COVID-19 in the pediatric population (0-18 years). A machine learning bibliometric methodology was applied to evaluate the total number of papers and citations, journal and publication types, the top productive institutions and countries and their scientific collaboration, and core keywords. Results: A total of 2301 papers were retrieved, with an average of 4.8 citations per article. Of this, 1078 (46.9%) were research articles, 436 (18.9%) were reviews, 363 (15.8%) were letters, 186 (8.1%) were editorials, 7 (0.3%) were conference papers, and 231 (10%) were categorized as others. The studies were published in 969 differentjournals, headed by The Lancet. The retrieved papers were published by a total of 12,657 authors from 114 countries. The most productive countries were the United States, China, and Italy. The four main clusters of keywords were pathogenesis and clinical characteristics (keyword occurrences: n=2240), public health issues (n=352), mental health (n=82), and therapeutic aspects (n=70). Conclusions: In the pediatric field, a large number of articles were published within a limited period on COVID-19, testifying to the rush to spread new findings on the topic in a timely manner. The leading authors, countries, and institutions evidently belonged to the most impacted geographical areas. A focus on the pediatric population was often included in general articles, and pediatric research about COVID-19 mainly focused on the clinical features, public health issues, and psychological impact of the disease. [ABSTRACT FROM AUTHOR]

Background: Digital teaching in medical education has grown in popularity in the recent years. However, to the best of our knowledge, no bibliometric report to date has been published that analyzes this important literature set to reveal prevailing topics and trends and their impacts reflected in citation counts. Objective: We used a bibliometric approach to unveil and evaluate the scientific literature on digital teaching research in medical education, demonstrating recurring research topics, productive authors, research organizations, countries, and journals. We further aimed to discuss some of the topics and findings reported by specific highly cited works. Methods: The Web of Science electronic database was searched to identify relevant papers on digital teaching research in medical education. Basic bibliographic data were obtained by the "Analyze" and "Create Citation Report" functions of the database. Complete bibliographic data were exported to VOSviewer for further analyses. Visualization maps were generated to display the recurring author keywords and terms mentioned in the titles and abstracts of the publications. Results: The analysis was based on data from 3978 papers that were identified. The literature received worldwide contributions with the most productive countries being the United States and United Kingdom. Reviews were significantly more cited, but the citations between open access vs non--open access papers did not significantly differ. Some themes were cited more often, reflected by terms such as virtual reality, innovation, trial, effectiveness, and anatomy. Different aspects in medical education were experimented for digital teaching, such as gross anatomy education, histology, complementary medicine, medicinal chemistry, and basic life support. Some studies have shown that digital teaching could increase learning satisfaction, knowledge gain, and even cost-effectiveness. More studies were conducted on trainees than on undergraduate students. Conclusions: Digital teaching in medical education is expected to flourish in the future, especially during this era of COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: Chatbots are computer programs that present a conversation-like interface through which people can access information and services. The COVID-19 pandemic has driven a substantial increase in the use of chatbots to support and complement traditional health care systems. However, despite the uptake in their use, evidence to support the development and deployment of chatbots in public health remains limited. Recent reviews have focused on the use of chatbots during the COVID-19 pandemic and the use of conversational agents in health care more generally. This paper complements this research and addresses a gap in the literature by assessing the breadth and scope of research evidence for the use of chatbots across the domain of public health. Objective: This scoping review had 3 main objectives: (1) to identify the application domains in public health in which there is the most evidence for the development and use of chatbots; (2) to identify the types of chatbots that are being deployed in these domains; and (3) to ascertain the methods and methodologies by which chatbots are being evaluated in public health applications. This paper explored the implications for future research on the development and deployment of chatbots in public health in light of the analysis of the evidence for their use. Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines for scoping reviews, relevant studies were identified through searches conducted in the MEDLINE, PubMed, Scopus, Cochrane Central Register of Controlled Trials, IEEE Xplore, ACM Digital Library, and Open Grey databases from mid-June to August 2021. Studies were included if they used or evaluated chatbots for the purpose of prevention or intervention and for which the evidence showed a demonstrable health impact. Results: Of the 1506 studies identified, 32 were included in the review. The results show a substantial increase in the interest of chatbots in the past few years, shortly before the pandemic. Half (16/32, 50%) of the research evaluated chatbots applied to mental health or COVID-19. The studies suggest promise in the application of chatbots, especially to easily automated and repetitive tasks, but overall, the evidence for the efficacy of chatbots for prevention and intervention across all domains is limited at present. Conclusions: More research is needed to fully understand the effectiveness of using chatbots in public health. Concerns with the clinical, legal, and ethical aspects of the use of chatbots for health care are well founded given the speed with which they have been adopted in practice. Future research on their use should address these concerns through the development of expertise and best practices specific to public health, including a greater focus on user experience. [ABSTRACT FROM AUTHOR]

Background: In recent years, with the development of computer science and medical science, virtual reality (VR) technology has become a promising tool for improving cognitive function. Research on VR-based cognitive training has garnered increasing attention. Objective: This study aimed to investigate the application status, research hot spots, and emerging trends of VR in cognitive rehabilitation over the past 20 years. Methods: Articles on VR-based cognitive rehabilitation from 2001 to 2021 were retrieved from the Web of Science Core Collection. CiteSpace software was used for the visual analysis of authors and countries or regions, and Scimago Graphica software was used for the geographic visualization of published countries or regions. Keywords were clustered using the gCLUTO software. Results: A total of 1259 papers were included. In recent years, research on the application of VR in cognitive rehabilitation has been widely conducted, and the annual publication of relevant literature has shown a positive trend. The main research areas include neuroscience and neurology, psychology, computer science, and rehabilitation. The United States ranked first with 328 papers, and Italy ranked second with 140 papers. Giuseppe Riva, an Italian academic, was the most prolific author with 29 publications. The most frequently cited reference was "Using Reality to Characterize Episodic Memory Profiles in Amnestic Mild Cognitive Impairment and Alzheimer's Disease: Influence of Active and Passive Encoding." The most common keywords used by researchers include "virtual reality," "cognition," "rehabilitation," "performance," and "older adult." The largest source of research funding is from the public sector in the United States. Conclusions: The bibliometric analysis provided an overview of the application of VR in cognitive rehabilitation. VR-based cognitive rehabilitation can be integrated into multiple disciplines. We conclude that, in the context of the COVID-19 pandemic, the development of VR-based telerehabilitation is crucial, and there are still many problems that need to be addressed, such as the lack of consensus on treatment methods and the existence of safety hazards. [ABSTRACT FROM AUTHOR]

Background: The SARS-CoV-2 pandemic has resulted in an unprecedented level of worldwide testing for epidemiologic and diagnostic purposes, and due to the extreme need for tests, the gold-standard Reverse Transcription Polymerase Chain Reaction (RT-PCR) testing capacity has been unable to meet the overall worldwide testing demand. Consequently, although the current literature has shown the sensitivity of rapid antigen tests (RATs) to be inferior to RT-PCR, RATs have been implemented on a large scale without solid data on performance. Objective: This study will compare analytical and clinical sensitivities and specificities of 50 lateral flow-- or laboratory-based RATs and 3 strand invasion--based amplification (SIBA)-RT-PCR tests from 30 manufacturers to RT-PCR testing of samples obtained from the deep oropharynx. In addition, the study will compare sensitivities and specificities of the included RATs as well as RT-PCR on clinical samples obtained from the deep oropharynx, the anterior nasal cavity, saliva, the deep nasopharynx, and expired air to RT-PCR on deep oropharyngeal samples. Methods: In the prospective part of the study, 200 individuals found SARS-CoV-2 positive and 200 individuals found SARS-CoV-2 negative by routine RT-PCR testing will be retested with each RAT, applying RT-PCR as the reference method. In the retrospective part of the study, 304 deep oropharyngeal cavity swabs divided into 4 groups based on RT-PCR quantification cycle (Cq) levels will be tested with each RAT. Results: The results will be reported in several papers with different aims. The first paper will report retrospective (analytical sensitivity, overall and stratified into different Cq range groups) and prospective (clinical sensitivity) data for RATs, with RT-PCR as the reference method. The second paper will report results for RAT based on anatomical sampling location. The third paper will compare different anatomical sampling locations by RT-PCR testing. The fourth paper will focus on RATs that rely on central laboratory testing. Tests from 4 different manufacturers will be compared for analytical performance data on retrospective deep oropharyngeal swab samples. The fifth paper will report the results of 4 RATs applied both as professional use and as self-tests. The last paper will report the results from 2 breath tests in the study. A comparison of sensitivity and specificity between RATs will be conducted using the McNemar test for paired samples and the chi-squared test for unpaired samples. Comparison of the positive predictive value (PPV) and negative predictive value (NPV) between RATs will be performed by the bootstrap test, and 95% CIs for sensitivity, specificity, PPV, and NPV will be calculated as bootstrap CIs. Conclusions: The study will compare the sensitivities of a large number of RATs for SARS-CoV-2 to with those of RT-PCR and will address whether lateral flow--based RATs differ significantly from laboratory-based RATs. The anatomical test locations for both RATs and RT-PCR will also be compared. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 global pandemic pushed many rehabilitation practitioners to pivot their in-person practice to adopt telerehabilitation as their main method of delivery. In addition to documenting information on interventions used with clients, it is best practice for therapists to use reliable and validated outcome measures to inform their interventions. Objective: Through this scoping review, we aim to identify (1) which outcomes are being used remotely to assess balance, mobility, and gait in patients with neurological conditions, and (2) what psychometric data (validity, reliability, etc.) for remotely administered outcomes are available. Methods: Three main concepts will be included in our search: (1) neurological conditions; (2) administration by telerehabilitation; and (3) outcome measures for balance, mobility, and gait. Studies reporting remote assessment of neurological conditions published since 1990 will be included. The database search will be completed in MEDLINE (Ovid), CINAHL, PubMed, PsycINFO, EMBASE, and Cochrane. Gray literature including dissertations, conference papers, and protocol papers will also be sourced. Two reviewers will independently screen each title and abstract using pre-established inclusion and exclusion criteria. Manuscripts that appear to meet the criteria will be subject to further review, and full-text extraction using a pre-piloted extraction sheet if all criteria are met. The data will be categorized by assessment types describing impairments (such as balance, strength, and mobility) or activity limitations or participation restriction (such as functional mobility, ambulatory functions, and activities of daily living). Results: This scoping review will document outcome measures currently used in the remote assessment of neurological conditions. To date, 235 titles and abstracts were screened. We are in the process of finalizing the full text screening for the inclusion of articles. We expect the full screening to be completed in November 2021 and data analysis in January 2022. Our results are expected to be published in early 2022. Conclusions: The optimal use of telerehabilitation as a mode to deliver rehabilitation intervention should be coupled with the completion of validated outcome measures. Therefore, it is crucial to further our knowledge on remote outcome measures and therapeutic assessments. [ABSTRACT FROM AUTHOR]

Background: Remote treatment, or telehealth, has shown promise for children with cerebral palsy (CP) prior to 2020; however, the beginning of the global COVID-19 pandemic limiting access to hospitals for face-to-face treatments has driven the need for telehealth and led to a surge in its development. Due to the recent developments, there has been limited synthesis of the available evidence of telehealth for children with CP. Objective: This study aimed to analyze and summarize the existing evidence for telehealth interventions for the treatment of children with CP and identify any areas requiring further research. Methods: A scoping review was performed. A systematic search of available literature in MEDLINE and PubMed was performed during July 2021. Inclusion criteria for articles were primary research and systematic reviews that investigated telehealth, included children with CP, were published between 2010-2021, and were written in English. Exclusion criteria were secondary research other than systematic reviews; interventions that did not meet the World Health Organization definition of telehealth; or studies where all participants were aged >18 years, children's results were not reported separately, or there were no results reported for children with CP. A scoping review was chosen due to the expected heterogeneity of the participants, as well as the expected small sample sizes and inconsistency of measured outcomes; therefore, a narrative reporting of the results was considered appropriate. Results: In all, 5 papers were identified, which included the results of 11 studies--2 of the included articles were systematic reviews, which included the results of 3 studies each. These 6 studies, together with 5 primary research articles, were included in this scoping review. The existing evidence is of low methodological quality, primarily consisting of case series. There is some evidence that the requirements of telehealth differ depending on the children's developmental stage and functional level. Telehealth is reported to reduce caregiver burden. There is mixed evidence on children's compliance with telehealth. Overall, the results of telehealth interventions for the treatment of children with CP were positive, indicating either comparable or improved results compared with children receiving usual face-to-face care. Conclusions: The evidence base is lacking in breadth and methodological quality to provide robust clinical recommendations. Most studies investigated hand function only, indicating the limited scope of existing research. However, this review shows that telehealth has demonstrated potential to improve function for children with CP while making health care services more accessible and reducing caregiver burden. Areas requiring further research include telehealth interventions for the lower limb, postural management, and pain control and the barriers to implementing telehealth. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has led to over 500 million cases and 6.2 million deaths around the world. Low- and middle-income countries (LMICs) like Armenia face unique infrastructure, financial, and capacity challenges that in many cases result in worse outcomes. Health care facilities across Armenia experienced a shortage of resources, including hospital beds and oxygen, which was further exacerbated by the war with neighboring Azerbaijan. Without a framework for home-based care, health care facilities were severely strained by COVID-19 patients who had prolonged oxygen requirements but were otherwise clinically stable. Objective: This paper describes our approach to establishing an international collaboration to develop a web app to support home monitoring of patients with COVID-19 with persistent oxygen requirements. Methods: The app was developed using a rapid, coordinated, and collaborative approach involving an international group of clinicians, developers, and collaborators. Health screening, monitoring, and discharge forms were developed into a lightweight OpenMRS web app and customized for the local Armenian context. Results: The software was designed and developed over 2 months using human-centered design and agile sprints. Once live, 5087 patient records were created for 439 unique patients. Conclusions: This project suggests a promising framework for designing and implementing remote monitoring programs in LMICs, despite pandemic and geopolitical challenges. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic required mental health services around the world to adapt quickly to the new restrictions and regulations put in place to reduce the risk of transmission. As face-to-face contact became difficult, virtual methods were implemented to continue to safely provide mental health care. However, it is unclear to what extent service provision transitioned to telemental health worldwide. Objective: We aimed to systematically review the global research literature on how mental health service provision adapted during the first year of the pandemic. Methods: We searched systematically for quantitative papers focusing on the impact of the COVID-19 pandemic on mental health services published until April 13, 2021, in the PubMed, Embase, medRxiv, and bioXriv electronic bibliographic databases, using the COVID-19 Open Access Project online platform. The screening process and data extraction were independently completed by at least two authors, and any disagreement was resolved by discussion with a senior member of the team. The findings were summarized narratively in the context of each country's COVID-19 Stringency Index, which reflects the stringency of a government's response to COVID-19 restrictions at a specific time. Results: Of the identified 24,339 records, 101 papers were included after the screening process. Reports on general services (n=72) showed that several countries' face-to-face services reduced their activities at the start of the pandemic, with reductions in the total number of delivered visits and with some services forced to close. In contrast, telemental health use rapidly increased in many countries across the world at the beginning of the pandemic (n=55), with almost complete virtualization of general and specialistic care services by the end of the first year. Considering the reported COVID-19 Stringency Index values, the increased use of virtual means seems to correspond to periods when the Stringency Index values were at their highest in several countries. However, due to specific care requirements, telemental health could not be used in certain subgroups of patients, such as those on clozapine or depot treatments and those who continued to need face-to-face visits. Conclusions: During the pandemic, mental health services had to adapt quickly in the short term, implementing or increasing the use of telemental health services across the globe. Limited access to digital means, poor digital skills, and patients' preferences and individual needs may have contributed to differences in implementing and accessing telemental health services during the pandemic. In the long term, a blended approach, combining in-person and virtual modalities, that takes into consideration the needs, preferences, and digital skills of patients may better support the future development of mental health services. It will be required to improve confidence with digital device use, training, and experience in all modalities for both clinicians and service users. [ABSTRACT FROM AUTHOR]

Background: Intensive care units (ICUs) around the world are in high demand due to patients with COVID-19 requiring hospitalization. As researchers at the University of Bristol, we were approached to develop a bespoke data visualization dashboard to assist two local ICUs during the pandemic that will centralize disparate data sources in the ICU to help reduce the cognitive load on busy ICU staff in the ever-evolving pandemic. Objective: The aim of this study was to conduct interviews with ICU staff in University Hospitals Bristol and Weston National Health Service Foundation Trust to elicit requirements for a bespoke dashboard to monitor the high volume of patients, particularly during the COVID-19 pandemic. Methods: We conducted six semistructured interviews with clinical staff to obtain an overview of their requirements for the dashboard and to ensure its ultimate suitability for end users. Interview questions aimed to understand the job roles undertaken in the ICU, potential uses of the dashboard, specific issues associated with managing COVID-19 patients, key data of interest, and any concerns about the introduction of a dashboard into the ICU. Results: From our interviews, we found the following design requirements: (1) a flexible dashboard, where the functionality can be updated quickly and effectively to respond to emerging information about the management of this new disease; (2) a mobile dashboard, which allows staff to move around on wards with a dashboard, thus potentially replacing paper forms to enable detailed and consistent data entry; (3) a customizable and intuitive dashboard, where individual users would be able to customize the appearance of the dashboard to suit their role; (4) real-time data and trend analysis via informative data visualizations that help busy ICU staff to understand a patient's clinical trajectory; and (5) the ability to manage tasks and staff, tracking both staff and patient movements, handovers, and task monitoring to ensure the highest quality of care. Conclusions: The findings of this study confirm that digital solutions for ICU use would potentially reduce the cognitive load of ICU staff and reduce clinical errors at a time of notably high demand of intensive health care. [ABSTRACT FROM AUTHOR]

Background: Telehealth has provided many researchers, especially those conducting psychosocial research, with the tools necessary to transition from in-person to remote clinical trials during the COVID-19 pandemic. A growing body of research supports the effectiveness of telemental health for a variety of psychiatric conditions, but few studies have examined telemental health for individuals with comorbid medical diagnoses. Furthermore, little is known about the remote implementation of clinical trials examining telemental health interventions. Objective: This paper outlines the procedural modifications used to facilitate conversion of an in-person randomized controlled trial of cognitive behavioral therapy (CBT) for depression in individuals with traumatic brain injury (TBI; CBT-TBI) to a telemental health study administered remotely. Methods: Given the nature of remote implementation and specific challenges experienced by individuals with TBI, considerations related to treatment delivery, remote consent, data management, neuropsychological assessment, safety monitoring, and delivery of supportive material have been discussed. Feasibility, acceptability, and safety were evaluated by examining attendance and participant responses on self-report measures of treatment satisfaction and suicidal behavior. Results: High rates of treatment attendance, assessment completion, study retention, and satisfaction with the intervention and modality were reported by participants who completed at least one telemental health CBT-TBI session. Conclusions: Study modifications are necessary when conducting a study remotely, and special attention should be paid to comorbidities and population-specific challenges (eg, cognitive impairment). Preliminary data support the feasibility, acceptability, and safety of remotely conducting a randomized controlled trial of CBT-TBI. [ABSTRACT FROM AUTHOR]

Background: Vaccine hesitancy is one of the many factors impeding efforts to control the COVID-19 pandemic. Exacerbated by the COVID-19 infodemic, misinformation has undermined public trust in vaccination, led to greater polarization, and resulted in a high social cost where close social relationships have experienced conflict or disagreements about the public health response. Objective: The purpose of this paper is to describe the theory behind the development of a digital behavioral science intervention-The Good Talk!-designed to target vaccine-hesitant individuals through their close contacts (eg, family, friends, and colleagues) and to describe the methodology of a research study to evaluate its efficacy. Methods: The Good Talk! uses an educational serious game approach to boost the skills and competences of vaccine advocates to have open conversations about COVID-19 with their close contacts who are vaccine hesitant. The game teaches vaccine advocates evidence-based open conversation skills to help them speak with individuals who have opposing points of view or who may ascribe to nonscientifically supported beliefs while retaining trust, identifying common ground, and fostering acceptance and respect of divergent views. The game is currently under development and will be available on the web, free to access for participants worldwide, and accompanied by a promotional campaign to recruit participants through social media channels. This protocol describes the methodology for a randomized controlled trial that will compare participants who play The Good Talk! game with a control group that plays the widely known noneducational game Tetris. The study will evaluate a participant's open conversation skills, self-efficacy, and behavioral intentions to have an open conversation with a vaccine-hesitant individual both before and after game play. Results: Recruitment will commence in early 2023 and will cease once 450 participants complete the study (225 per group). The primary outcome is improvement in open conversation skills. Secondary outcomes are self-efficacy and behavioral intentions to have an open conversation with a vaccine-hesitant individual. Exploratory analyses will examine the effect of the game on implementation intentions as well as potential covariates or subgroup differences based on sociodemographic information or previous experiences with COVID-19 vaccination conversations. Conclusions: The outcome of the project is to promote more open conversations regarding COVID-19 vaccination. We hope that our approach will encourage more governments and public health experts to engage in their mission to reach their citizens directly with digital health solutions and to consider such interventions as an important tool in infodemic management. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic disrupted the delivery of diabetes care and worsened mental health among many patients with type 2 diabetes (T2D). This disruption puts patients with T2D at risk for poor diabetes outcomes, especially those who experience social disadvantage due to socioeconomic class, rurality, or ethnicity. The appropriate use of communication technology could reduce these gaps in diabetes care created by the pandemic and also provide support for psychological distress. Objective: The purpose of this study is to test the feasibility of an innovative co-designed Technology-Enabled Collaborative Care (TECC) model for diabetes management and mental health support among adults with T2D. Methods: We will recruit 30 adults with T2D residing in Ontario, Canada, to participate in our sequential explanatory mixed methods study. They will participate in 8 weekly web-based health coaching sessions with a registered nurse, who is a certified diabetes educator, who will be supported by a digital care team (ie, a peer mentor, an addictions specialist, a dietitian, a psychiatrist, and a psychotherapist). Assessments will be completed at baseline, 4 weeks, and 8 weeks, with a 12-week follow-up. Our primary outcome is the feasibility and acceptability of the intervention, as evident by the participant recruitment and retention rates. Key secondary outcomes include assessment completion and delivery of the intervention. Exploratory outcomes consist of changes in mental health, substance use, and physical health behaviors. Stakeholder experience and satisfaction will be explored through a qualitative descriptive study using one-on-one interviews. Results: This paper describes the protocol of the study. The recruitment commenced in June 2021. This study was registered on October 29, 2020, on ClinicalTrials.gov (Registry ID: NCT04607915). As of June 2022, all participants have been recruited. It is anticipated that data analysis will be complete by the end of 2022, with study findings available by the end of 2023. Conclusions: The development of an innovative, technology-enabled model will provide necessary support for individuals living with T2D and mental health challenges. This TECC program will determine the feasibility of TECC for patients with T2D and mental health issues. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has disrupted the health care system, limiting health care resources such as the availability of health care professionals, patient monitoring, contact tracing, and continuous surveillance. As a result of this significant burden, digital tools have become an important asset in increasing the efficiency of patient care delivery. Digital tools can help support health care institutions by tracking transmission of the virus, aiding in the screening process, and providing telemedicine support. However, digital health tools face challenges associated with barriers to accessibility, efficiency, and privacy-related ethical issues. Objective: This paper describes the study design of an open-label, noninterventional, crossover, randomized controlled trial aimed at assessing whether interactive voice response systems can screen for SARS-CoV-2 in patients as accurately as standard screening done by people. The study aims to assess the concordance and interrater reliability of symptom screening done by Amazon Alexa compared to manual screening done by research coordinators. The perceived level of comfort of patients when interacting with voice response systems and their personal experience will also be evaluated. Methods: A total of 52 patients visiting the heart failure clinic at the Royal Victoria Hospital of the McGill University Health Center, in Montreal, Quebec, will be recruited. Patients will be randomly assigned to first be screened for symptoms of SARS-CoV-2 either digitally, by Amazon Alexa, or manually, by the research coordinator. Participants will subsequently be crossed over and screened either digitally or manually. The clinical setup includes an Amazon Echo Show, a tablet, and an uninterrupted power supply mounted on a mobile cart. The primary end point will be the interrater reliability on the accuracy of randomized screening data performed by Amazon Alexa versus research coordinators. The secondary end point will be the perceived level of comfort and app engagement of patients as assessed using 5-point Likert scales and binary mode responses. Results: Data collection started in May 2021 and is expected to be completed in fall 2022. Data analysis is expected to be completed in early 2023. Conclusions: The use of voice-based assistants could improve the provision of health services and reduce the burden on health care personnel. Demonstrating a high interrater reliability between Amazon Alexa and health care coordinators may serve future digital tools to streamline the screening and delivery of care in the context of other conditions and clinical settings. The COVID-19 pandemic occurs during the first digital era using digital tools such as Amazon Alexa for disease screening, and it represents an opportunity to implement such technology in health care institutions in the long term. [ABSTRACT FROM AUTHOR]

Background: Amid all public health measures to contain COVID-19, the most challenging has been how to break the transmission chain. This has been even more challenging in low- and middle-income countries (LMICs). A public health emergency warrants a public health perspective, which comes down to prevention. Rapid mass testing has been advocated throughout the pandemic as a way to promptly deal with asymptomatic infections, but its usefulness in LMICs is yet to be fully understood. Objective: The study objectives of this paper are to (1) investigate the impact of the different rapid mass testing options for SARS-CoV-2 that have been delivered at point of care in LMICs and (2) evaluate the diagnostic safety (accuracy) of rapid mass testing for SARS-CoV-2 in LMICs. Methods: This review will systematically search records in PubMed, EBSCOhost, Cochrane library, Global Index Medicus COVID-19 Register, and Scopus. Records will be managed using Mendeley reference manager and SWIFT-Review. Risk of bias for randomized controlled trials will be assessed using the RoB 2 assessment tool, while nonrandomized interventions will be assessed using the tool developed by the Evidence Project. A narrative approach will be used to synthesize data under the first objective, and either a meta-analysis or synthesis without meta-analysis for the second objective. Tables, figures, and textual descriptions will be used to present findings. The overall body of evidence for the first objective will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach, and for the second objective using GRADE. Results: The screening of records has been finalized. We hope to finalize the synthesis by the end of February 2023 and to prepare the manuscript for publication by April 2023. The study will be reported in accordance with standard guidelines for the reporting of systematic reviews. Review results will be disseminated through conferences and their peer-reviewed publication in a relevant journal. Conclusions: This review highlights the role of a preventive approach in infection control using rapid mass testing. It also flags the overriding need to involve users and providers in the evaluation of such tests in the settings for which they are intended. This will be the first review to the best of our knowledge to generate both qualitative and quantitative evidence regarding rapid mass testing specific to LMICs. [ABSTRACT FROM AUTHOR]

An increasing number of psychological interventions are shifting to online modes of delivery. One such intervention is peer-to-peer support, which in this context may provide internet users living with mental health disorders an opportunity to connect with and support others living with similar conditions. This paper presents a call for further research into how platforms such as Facebook could be used as channels for peer support and the mechanisms that may underlie their effectiveness. We discuss the background of peer support, how it has transitioned online, and consider theories and models that may have relevance. We also consider the importance of moderation within online peer support and the development of specific social network--based online interventions. We conclude that for social network sites to be used as peer-to-peer support interventions, more research is needed to understand their effectiveness, the role of moderation in these communities, and the mechanisms that produce the benefits experienced by users. [ABSTRACT FROM AUTHOR]

Background: As a result of the COVID-19 pandemic, providing health care while maintaining social distancing has resulted in the need to provide care remotely, support quarantined or isolated individuals, monitor infected individuals and their close contacts, as well as disseminate accurate information regarding COVID-19 to the public. This has led to an unprecedented rapid expansion of digital tools to provide digitized virtual care globally, especially mobile phone-facilitated health interventions, called mHealth. To help keep abreast of different mHealth and virtual care technologies being used internationally to facilitate patient care and public health during the COVID-19 pandemic, we carried out a rapid investigation of solutions being deployed and considered in 4 countries. Objective: The aim of this paper was to describe mHealth and the digital and contact tracing technologies being used in the health care management of the COVID-19 pandemic among 2 high-income and 2 low-middle income countries. Methods: We compared virtual care interventions used for COVID-19 management among 2 high-income countries (the United Kingdom and Canada) and 2 low-middle income (Kenya and Rwanda) countries. We focused on interventions used to facilitate patient care and public health. Information regarding specific virtual care technologies was procured from a variety of resources including gray literature, government and health organization websites, and coauthors' personal experiences as implementers of COVID-19 virtual care strategies. Search engine queries were performed to find health information that would be easily accessible to the general public, with keywords including "COVID-19," "contact-tracing," "tool-kit," "telehealth," and "virtual care," in conjunction with corresponding national health authorities. Results: We identified a variety of technologies in Canada, the United Kingdom, Rwanda, and Kenya being used for patient care and public health. These countries are using both video and text message-based platforms to facilitate communication with health care providers (eg, WelTel and Zoom). Nationally developed contact tracing apps are provided free to the public, with most of them using Bluetooth-based technology. We identified that often multiple complimentary technologies are being utilized for different aspects of patient care and public health with the common purpose to disseminate information safely. There was a negligible difference among the types of technologies used in both high-income and low-middle income countries, although the latter implemented virtual care interventions earlier during the pandemic's first wave, which may account for their effective response. Conclusions: Virtual care and mHealth technologies have evolved rapidly as a tool for health care support for both patient care and public health. It is evident that, on an international level, a variety of mHealth and virtual care interventions, often in combination, are required to be able to address patient care and public health concerns during the COVID-19 pandemic, independent of a country's economic standing. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic is negatively impacting the mental health of both patients with COVID-19 and the general population. As current guidelines are limiting in-person contacts to reduce the spread of the virus, the development of a digital approach to implement in psychiatric and psychological consultations is needed. In this paper, we present the DigiCOVID protocol, a digital approach to offer remote, personalized psychological and psychiatric support to former or current patients with COVID-19 and their relatives. Objective: The main goal of this project is to evaluate the feasibility, acceptability, and usability of the DigiCOVID protocol. Furthermore, we also aim to assess the impact of the abovementioned protocol by means of pre-post changes in psychological clinical variables. Methods: Participants undergo an initial telephonic screening to ensure inclusion criteria are met. Secondly, participants complete a video-assisted neuropsychological IQ test as well as web-based self-reports of health and general well-being. Participants are then assigned to a psychotherapist who offers 8 teletherapy sessions. At the end of the therapy cycle, the web-based questionnaires are administered for a posttreatment evaluation. Results: As of April 2022, we enrolled a total of 122 participants, of which 94 have completed neuropsychological tests and web-based questionnaires. Conclusions: Our study aims at testing the feasibility and preliminary efficacy of DigiCOVID, a remote telemedicine protocol for the improvement of psychological and psychiatric health in patients with COVID-19 and their relatives. To date, the approach used seems to be feasible and highly customizable to patients' needs, and therefore, the DigiCOVID protocol might pave the way for future telepsychiatry-based interventions. [ABSTRACT FROM AUTHOR]

Background: While a variety of health apps abound, less than half of adults in the United States report using a health app, despite the ubiquity of smartphones among users aged 18 to 49 years. Several studies have examined the use of breastfeeding apps; however, less is known about the types of features found on these apps and what factors might influence app ratings. Objective: This paper seeks to characterize breastfeeding apps, assess whether apps with higher user ratings differ from apps with lower user ratings in their tracking and nontracking features, and analyze whether the type and number of features predict user star ratings and whether an app is higher- or lower-rated. Methods: Using a cross-sectional design, a convenience sample of breastfeeding apps was culled from the Apple App Store (iOS) and Google Play Store (Android). Content analysis of the apps (N=82) was conducted using a schema of 87 items, which was then compiled into 9 topical indices for breastfeeding, bottle feeding, solid foods, infant health, infant care, technical characteristics, informatics, informational characteristics, and interactivity. Analysis consisted of descriptive statistics, the Mann-Whitney U test, and Spearman rank correlations. Linear regression and binary logistic regression analyses were conducted to determine which features predicted user star ratings. Results: On average, users rated breastfeeding apps 4.4 of 5 stars. Two-thirds of apps (n=54) were higher rated (=4.5 stars), and one-third (n=28) were lower rated (<4.5 stars). Higher-rated apps offered more tracking features for breastfeeding, bottle feeding, solid foods, infant health, and infant care than lower-rated apps. The breastfeeding, solid-food, and technical indices explained 17% of user star ratings. For each additional breastfeeding and solid-food feature, we can expect to see a 27% and 35% increase, respectively, in user star ratings. Additionally, as the number of solid-food features increased, the odds that the app is higher rated increased 1.58 times. Conclusions: Our findings suggest user ratings are driven in part by tracking features, specifically those related to breastfeeding and solid foods. The proliferation of mobile health apps offers opportunities for parents and caregivers to track behaviors associated with infant feeding and other health metrics in a dynamic, detailed, and comprehensive manner. Hence, breastfeeding apps have the potential to promote and support breastfeeding among users. [ABSTRACT FROM AUTHOR]

Background: There are around 1.3 million people in the United Kingdom with the devastating psychological, physical, and cognitive consequences of long COVID (LC). UK guidelines recommend that LC symptoms be managed pragmatically with holistic support for patients' biopsychosocial needs, including psychological, emotional, and physical health. Self-management strategies, such as pacing, prioritization, and goal setting, are vital for the self-management of many LC symptoms. Objective: This paper describes the codevelopment and initial testing of a digital intervention combining peer support with positive psychology approaches for self-managing the physical, emotional, psychological, and cognitive challenges associated with LC. The objectives of this study were to (1) codesign an intervention with and for people with LC; (2) test the intervention and study methods; (3) measure changes in participant well-being, self-efficacy, fatigue, and loneliness; and (4) understand the types of self-management goals and strategies used by people with LC. Methods: The study used a pre-post, mixed methods, pragmatic, uncontrolled design. Digital intervention content was codeveloped with a lived-experience group to meet the needs uncovered during the intervention development and logic mapping phase. The resulting 8-week digital intervention, Hope Programme for Long COVID, was attended by 47 participants, who completed preand postprogram measures of well-being, self-efficacy, fatigue, and loneliness. Goal-setting data were extracted from the digital platform at the end of the intervention. Results: The recruitment rate (n=47, 83.9%) and follow-up rate (n=28, 59.6%) were encouraging. Positive mental well-being (mean difference 6.5, P<.001) and self-efficacy (mean difference 1.1, P=.009) improved from baseline to postcourse. All goals set by participants mapped onto the 5 goal-oriented domains in the taxonomy of everyday self-management strategies (TEDSS). The most frequent type of goals was related to activity strategies, followed by health behavior and internal strategies. Conclusions: The bespoke self-management intervention, Hope Programme for Long COVID, was well attended, and follow-up was encouraging. The sample characteristics largely mirrored those of the wider UK population with LC. Although not powered to detect statistically significant changes, the preliminary data show improvements in self-efficacy and positive mental well-being. Our next trial (ISRCTN: 11868601) will use a nonrandomized waitlist control design to further examine intervention efficacy. [ABSTRACT FROM AUTHOR]

Background: Coronavirus continues to spread worldwide, causing various health and economic disruptions. One of the most important approaches to controlling the spread of this disease is to use an artificial intelligence (AI)-based technological intervention, such as a chatbot system. Chatbots can aid in the fight against the spread of COVID-19. Objective: This paper introduces COVID-Bot, an intelligent interactive system that can help screen students and confirm their COVID-19 vaccination status. Methods: The design and development of COVID-Bot followed the principles of the design science research (DSR) process, which is a research method for creating a new scientific artifact. COVID-Bot was developed and implemented using the SnatchBot chatbot application programming interface (API) and its predefined tools, which are driven by various natural language processing algorithms. Results: An evaluation was carried out through a survey that involved 106 university students in determining the functionality, compatibility, reliability, and usability of COVID-Bot. The findings indicated that 92 (86.8%) of the participants agreed that the chatbot functions well, 85 (80.2%) agreed that it fits well with their mobile devices and their lifestyle, 86 (81.1%) agreed that it has the potential to produce accurate and consistent responses, and 85 (80.2%) agreed that it is easy to use. The average obtained α was .87, indicating satisfactory reliability. Conclusions: This study demonstrates that incorporating chatbot technology into the educational system can combat the spread of COVID-19 among university students. The intelligent system does this by interacting with students to determine their vaccination status. [ABSTRACT FROM AUTHOR]

Background: Health literacy (HL) is an important public health goal but also crucial in individuals providing medical care. During the pandemic, COVID-19–related HL of health professionals (HPs) has gained momentum; it helps to minimize the risk of self-infection, on the one hand, and to protect patients and relatives from infection, on the other. However, comprehensive information about the levels of individual pandemic-related HL in HPs is scarce. Objective: In this paper, we aimed at describing the extent of existing research on HL (concept) conducted in HPs (population) in the COVID-19 pandemic (context). The review intends to map the literature on HL in HPs, thereby highlighting research gaps. Methods: This scoping review was conducted using the methodology of Khalil et al (2016). This involved an electronic search of PubMed (MEDLINE) and PsycInfo and a hand search. The included studies were iteratively examined to find items representing the four HL dimensions of access, understand, critically appraise, and apply COVID-19–related health information. Results: The search yielded a total of 3875 references. Only 7 (1.4%) of the 489 included studies explicitly stated to have addressed HL; 2 (0.4%) studies attempted to develop an instrument measuring COVID-19–related HL in HPs; 6 (1.2%) studies included an HL measure in an observational survey design. Of the remainder, the vast majority used a cross-sectional design. The dimensions access and understand were frequently examined, but few studies looked at the dimensions critical appraisal or apply. Very few studies reported an intervention aiming to improve a COVID-19–related HL outcome. Conclusions: High levels of COVID-19–related HL among HPs are necessary to ensure not only safe practice with necessary protection of HPs, their patients, and relatives, but also successful care delivery and subsequently improved health outcomes in the long term. To advance our understanding of how high COVID-19–related HL manifests itself in HPs, how it relates to health outcomes, and how it can be improved, more research is necessary. [ABSTRACT FROM AUTHOR]

Background: Virtual reality can play an important role during the COVID-19 pandemic in the health care sector. This technology has the potential to supplement the traditional in-hospital medical training and treatment, and may increase access to training and therapies in various health care settings. Objective: This systematic review aimed to describe the literature on health care--targeted virtual reality applications during the COVID-19 crisis. Methods: We conducted a systematic search of the literature on the PsycINFO, Web of Science, and MEDLINE databases, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The search string was as follows: "[(virtual reality)] AND [(COVID-19) OR (coronavirus) OR (SARS-CoV-2) OR (healthcare)]." Papers published in English after December 2019 in peer-reviewed journals were selected and subjected to the inclusion and exclusion criteria. We used the Mixed Methods Appraisal Tool to assess the quality of studies and the risk of bias. Results: Thirty-nine studies met the inclusion criteria. Seventeen studies showed the usefulness of virtual reality during the COVID-19 crisis for reducing stress, anxiety, depression, and pain, and promoting physical activity. Twenty-two studies revealed that virtual reality was a helpful learning and training tool during the COVID-19 crisis in several areas, including emergency medicine, nursing, and pediatrics. This technology was also used as an educational tool for increasing public understanding of the COVID-19 pandemic. Different levels of immersion (ie, immersive and desktop virtual reality), types of head-mounted displays (ie, PC-based, mobile, and standalone), and content (ie, 360° videos and photos, virtual environments, virtual reality video games, and embodied virtual agents) have been successfully used. Virtual reality was helpful in both face-to-face and remote trials. Conclusions: Virtual reality has been applied frequently in medicine during the COVID-19 pandemic, with positive effects for treating several health conditions and for medical education and training. Some barriers need to be overcome for the broader adoption of virtual reality in the health care panorama. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic represents the most unprecedented global challenge in recent times. As the global community attempts to manage the pandemic in the long term, it is pivotal to understand what factors drive prevalence rates and to predict the future trajectory of the virus. Objective: This study had 2 objectives. First, it tested the statistical relationship between socioeconomic status and COVID-19 prevalence. Second, it used machine learning techniques to predict cumulative COVID-19 cases in a multicountry sample of 182 countries. Taken together, these objectives will shed light on socioeconomic status as a global risk factor of the COVID-19 pandemic. Methods: This research used exploratory data analysis and supervised machine learning methods. Exploratory analysis included variable distribution, variable correlations, and outlier detection. Following this, the following 3 supervised regression techniques were applied: linear regression, random forest, and adaptive boosting (AdaBoost). Results were evaluated using k-fold cross-validation and subsequently compared to analyze algorithmic suitability. The analysis involved 2 models. First, the algorithms were trained to predict 2021 COVID-19 prevalence using only 2020 reported case data. Following this, socioeconomic indicators were added as features and the algorithms were trained again. The Human Development Index (HDI) metrics of life expectancy, mean years of schooling, expected years of schooling, and gross national income were used to approximate socioeconomic status. Results: All variables correlated positively with the 2021 COVID-19 prevalence, with R 2 values ranging from 0.55 to 0.85. Using socioeconomic indicators, COVID-19 prevalence was predicted with a reasonable degree of accuracy. Using 2020 reported case rates as a lone predictor to predict 2021 prevalence rates, the average predictive accuracy of the algorithms was low (R2 =0.543). When socioeconomic indicators were added alongside 2020 prevalence rates as features, the average predictive performance improved considerably (R2 =0.721) and all error statistics decreased. Thus, adding socioeconomic indicators alongside 2020 reported case data optimized the prediction of COVID-19 prevalence to a considerable degree. Linear regression was the strongest learner with R 2 =0.693 on the first model and R 2 =0.763 on the second model, followed by random forest (0.481 and 0.722) and AdaBoost (0.454 and 0.679). Following this, the second model was retrained using a selection of additional COVID-19 risk factors (population density, median age, and vaccination uptake) instead of the HDI metrics. However, average accuracy dropped to 0.649, which highlights the value of socioeconomic status as a predictor of COVID-19 cases in the chosen sample. Conclusions: The results show that socioeconomic status is an important variable to consider in future epidemiological modeling, and highlights the reality of the COVID-19 pandemic as a social phenomenon and a health care phenomenon. This paper also puts forward new considerations about the application of statistical and machine learning techniques to understand and combat the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: In-person directly observed therapy (DOT) is standard of care for tuberculosis (TB) treatment adherence monitoring in the US, with increasing use of video-DOT (vDOT). In Minneapolis, vDOT became available in 2019. Objective: In this paper, we aimed to evaluate the use and effectiveness of vDOT in a program setting, including comparison of verified adherence among those receiving vDOT and in-person DOT. We also sought to understand the impact of COVID-19 on TB treatment adherence and technology adoption. Methods: We abstracted routinely collected data on individuals receiving therapy for TB in Minneapolis, MN, between September 2019 and June 2021. Our primary outcomes were to assess vDOT use and treatment adherence, defined as the proportion of prescribed doses (7 days per week) verified by observation (in person versus video-DOT), and to compare individuals receiving therapy in the pre-COVID-19 (before March 2020), and post-COVID-19 (after March 2020) periods; within the post-COVID-19 period, we evaluated early COVID-19 (March-August 2020), and intra-COVID-19 (after August 2020) periods. Results: Among 49 patients with TB (mean age 41, SD 19; n=27, 55% female and n=47, 96% non-US born), 18 (36.7%) received treatment during the post-COVID-19 period. Overall, verified adherence (proportion of observed doses) was significantly higher when using vDOT (mean 81%, SD 17.4) compared to in-person DOT (mean 54.5%, SD 10.9; P=.001). The adoption of vDOT increased significantly from 35% (11/31) of patients with TB in the pre-COVID-19 period to 67% (12/18) in the post-COVID-19 period (P=.04). Consequently, overall verified (ie, observed) adherence among all patients with TB in the clinic improved across the study periods (56%, 67%, and 79%, P=.001 for the pre-, early, and intra-COVID-19 periods, respectively). Conclusions: vDOT use increased after the COVID-19 period, was more effective than in-person DOT at verifying ingestion of prescribed treatment, and led to overall increased verified adherence in the clinic despite the onset of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: COVID-19 restrictions severely curtailed empirical endeavors that involved in-person interaction, such as usability testing sessions for technology development. Researchers and developers found themselves using web-based moderation for usability testing. Skilled remote moderators and observers are fundamental in this approach. However, to date, more empirical work is needed that captures the perceptions and support needs of moderators and observers in testing situations. Objective: The aim of this paper was to identify remote moderator and observer participant experiences and their use of certain tools to capture feedback of users as they interact with the web browser application. Methods: This research is part of a broader study on an educational web browser application for nursing students to learn perspective taking and enhance their perceptual understanding of a dialogue partner's thoughts and feelings. The broader study used a quantitative and think-aloud qualitative problem-discovery usability study design. This case study explored written accounts of the remote moderator and observer participants regarding their roles, experiences, and reactions to the testing protocol and their suggestions for improved techniques and strategies for conducting remote usability testing. Content analysis was used to analyze participants' experiences in the usability testing sessions. Results: We collected data from 1 remote moderator and 2 remote observers. Five themes were identified: dealing with personal stressors, dealing with user anxiety, maintaining social presence, ethical response to the study protocol, and communication during sessions. The participants offered recommendations for the design of future remote testing activities as well as evidence-informed training materials for usability project personnel. Conclusions: This study's findings contribute to a growing body of endeavors to understand human-computer interaction and its impact on remote moderator and observer roles. As technology rapidly advances, more remote usability testing will occur where the knowledge gleaned in this study can have an impact. Recommendations based on moderator and observer participant perspectives identify the need for more evidence-informed training materials for their roles that focus on web-based interpersonal communication skills, execution of user testing protocols, troubleshooting technology and test user issues, proficiency in web conferencing platforms, behavior analysis and feedback technologies, and time management. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has drawn attention to various inequalities in global societies, highlighting discrepancies in terms of safety, accessibility, and overall health. In particular, sex workers are disproportionately at risk due to the nature of their work and the social stigma that comes alongside it. Objective: This study examines how public social media can be used as a tool of professional and personal expression by sex workers during the COVID-19 pandemic. We aimed to explore an underresearched topic by focusing on sex workers' experiences with the ongoing COVID-19 pandemic on the social media platform Twitter. In particular, we aimed to find the main issues that sex workers discuss on social media in relation to the COVID-19 pandemic. Methods: A literature review followed by a qualitative analysis of 1458 (re)tweets from 22 sex worker Twitter accounts was used for this study. The tweets were qualitatively coded by theme through the use of intercoder reliability. Empirical, experimental, and observational studies were included in this review to provide context and support for our findings. Results: In total, 5 major categories were identified as a result of the content analysis used for this study: concerns (n=542, 37.2%), solicitation (n=336, 23.0%), herd mentality (n=231, 15.8%), humor (n=190, 13.0%), and blame (n=146, 10.0%). The concerns category was the most prominent category, which could be due to its multifaceted nature of including individual concerns, health issues, concerns for essential workers and businesses, as well as concerns about inequalities or intersectionality. When using gender as a control factor, the majority of the results were not noteworthy, save for the blame category, in which sexual and gender minorities (SGMs) were more likely to post content. Conclusions: Though there has been an increase in the literature related to the experiences of sex workers, this paper recommends that future studies could benefit from further examining these 5 major categories through mixed methods research. Examining this phenomenon could recognize the challenges unique to this working community during the COVID-19 pandemic and potentially reduce the widespread stigma associated with sex work in general. [ABSTRACT FROM AUTHOR]

Background: A large body of research has identified modifiable cognitions and behaviors (actions) associated with psychological health. However, little is known regarding the actions that are most strongly associated with psychological health or the frequency with which they should be performed. Objective: This paper described 2 studies that used survey methodology to create the Things You Do Questionnaire (TYDQ), which aims to identify and rank actions (items) and domains of actions (factors) most strongly associated with psychological health. Methods: We used digital marketing strategies to recruit Australian adult participants, who were asked to complete 2 web-based surveys comprising versions of the TYDQ; validated measures of depression, anxiety, and satisfaction with life; and demographic questions. In study 1, a total of 3040 participants rated how often they performed each of the 96 items comprising the TYDQ. This design was replicated in study 2, in which a 59-item version of the TYDQ was completed by 3160 participants. In both studies, the factor structure and validity were examined, as were the associations between individual TYDQ items and 3 mental health outcomes: depression, anxiety, and satisfaction with life. Results: In study 1, factor analyses revealed that a 5-factor model comprising 27 items achieved an optimum balance between brevity and variance and accounted for 38.1%, 31.4%, and 33.2% of the variance in scores on measures of depression, anxiety, and satisfaction with life, respectively. The factors were interpreted as realistic thinking, meaningful activities, goals and plans, healthy habits, and social connections. These 5 factors were more strongly associated with psychological health than those such as practicing kindness, exercising gratitude, and practicing spirituality. This pattern of results was replicated across gender, age groups, and depression severity. The 5-factor solution found in study 1 was replicated in study 2. Analyses revealed that a 21-item version accounted for 46.8%, 38.2%, and 38.1% of the variance in scores on measures of depression, anxiety, and satisfaction with life, respectively. Conclusions: These findings indicate that some actions are more strongly associated with psychological health than others and that these activities fall within 5 broad domains, which represent skills often taught in psychological treatments. Subsequent studies are planned to explore the reliability of these items and results in other samples and to examine patterns of change in scores during treatment for anxiety and depression. If replicated, these efforts will assist in the development of new psychological interventions and provide an evidence base for public mental health campaigns designed to promote good mental health and prevent the emergence of common mental disorders. [ABSTRACT FROM AUTHOR]

Background: There is an increasing need to organize the care around the patient and not the disease, while considering the complex realities of multiple physical and psychosocial conditions, and polypharmacy. Integrated patient-centered care delivery platforms have been developed for both patients and clinicians. These platforms could provide a promising way to achieve a collaborative environment that improves the provision of integrated care for patients via enhanced information and communication technology solutions for semiautomated clinical decision support. Objective: The Collaborative Care and Cure Cloud project (C3-Cloud) has developed 2 collaborative computer platforms for patients and members of the multidisciplinary team (MDT) and deployed these in 3 different European settings. The objective of this study is to pilot test the platforms and evaluate their impact on patients with 2 or more chronic conditions (diabetes mellitus type 2, heart failure, kidney failure, depression), their informal caregivers, health care professionals, and, to some extent, health care systems. Methods: This paper describes the protocol for conducting an evaluation of user experience, acceptability, and usefulness of the platforms. For this, 2 "testing and evaluation" phases have been defined, involving multiple qualitative methods (focus groups and surveys) and advanced impact modeling (predictive modeling and cost-benefit analysis). Patients and health care professionals were identified and recruited from 3 partnering regions in Spain, Sweden, and the United Kingdom via electronic health record screening. Results: The technology trial in this 4-year funded project (2016-2020) concluded in April 2020. The pilot technology trial for evaluation phases 3 and 4 was launched in November 2019 and carried out until April 2020. Data collection for these phases is completed with promising results on platform acceptance and socioeconomic impact. We believe that the phased, iterative approach taken is useful as it involves relevant stakeholders at crucial stages in the platform development and allows for a sound user acceptance assessment of the final product. Conclusions: Patients with multiple chronic conditions often experience shortcomings in the care they receive. It is hoped that personalized care plan platforms for patients and collaboration platforms for members of MDTs can help tackle the specific challenges of clinical guideline reconciliation for patients with multimorbidity and improve the management of polypharmacy. The initial evaluative phases have indicated promising results of platform usability. Results of phases 3 and 4 were methodologically useful, yet limited due to the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: People living with rarer dementias face considerable difficulty accessing tailored information, advice, and peer and professional support. Web-based meeting platforms offer a critical opportunity to connect with others through shared lived experiences, even if they are geographically dispersed, particularly during the COVID-19 pandemic. Objective: We aim to develop facilitated videoconferencing support groups (VSGs) tailored to people living with or caring for someone with familial or sporadic frontotemporal dementia or young-onset Alzheimer disease, primary progressive aphasia, posterior cortical atrophy, or Lewy body dementia. This paper describes the development, coproduction, field testing, and evaluation plan for these groups. Methods: We describe a 3-phase approach to development. First, information and knowledge were gathered as part of a coproduction process with members of the Rare Dementia Support service. This information, together with literature searches and consultation with experts by experience, clinicians, and academics, shaped the design of the VSGs and session themes. Second, field testing involved 154 Rare Dementia Support members (people living with dementia and carers) participating in 2 rounds of facilitated sessions across 7 themes (health and social care professionals, advance care planning, independence and identity, grief and loss, empowering your identity, couples, and hope and dementia). Third, a detailed evaluation plan for future rounds of VSGs was developed. Results: The development of the small groups program yielded content and structure for 9 themed VSGs (the 7 piloted themes plus a later stages program and creativity club for implementation in rounds 3 and beyond) to be delivered over 4 to 8 sessions. The evaluation plan incorporated a range of quantitative (attendance, demographics, and geography; pre-post well-being ratings and surveys; psycholinguistic analysis of conversation; facial emotion recognition; facilitator ratings; and economic analysis of program delivery) and qualitative (content and thematic analysis) approaches. Pilot data from round 2 groups on the pre-post 3-word surveys indicated an increase in the emotional valence of words selected after the sessions. Conclusions: The involvement of people with lived experience of a rare dementia was critical to the design, development, and delivery of the small virtual support group program, and evaluation of this program will yield convergent data about the impact of tailored support delivered to geographically dispersed communities. This is the first study to design and plan an evaluation of VSGs specifically for people affected by rare dementias, including both people living with a rare dementia and their carers, and the outcome of the evaluation will be hugely beneficial in shaping specific and targeted support, which is often lacking in this population. [ABSTRACT FROM AUTHOR]

Background: The global health crisis caused by COVID-19 has drastically changed human society in a relatively short time. However, this crisis has offered insights into the different roles that such a worldwide virus plays in the lives of people and how those have been affected, as well as eventually proposing new solutions. From the beginning of the pandemic, technology solutions have featured prominently in virus control and in the frame of reference for international travel, especially contact tracing and passenger locator applications. Objective: The objective of this paper is to study specific areas of technology acceptance and adoption following a unified theory of acceptance and use of technology (UTAUT) research model. Methods: We presented a research model based on UTAUT constructs to study the determinants for adoption of COVID-19–related apps using a questionnaire. We tested the model via confirmatory factor analysis (CFA) and structural equation modeling (SEM) using travelers’ data from an insular tourist region. Results: Our model explained 90.3% of the intention to use (N=9555) and showed an increased understanding of the vital role of safety, security, privacy, and trust in the usage intention of safety apps. Results also showed how the impact of COVID-19 is not a strong predictor of adoption, while age, education level, and social capital are essential moderators of behavioral intention. Conclusions: In terms of scientific impact, the results described here provide important insights and contributions not only for researchers but also for policy and decision makers by explaining the reasons behind the adoption and usage of apps designed for COVID-19. [ABSTRACT FROM AUTHOR]

Background: Symptom checkers have been widely used during the COVID-19 pandemic to alleviate strain on health systems and offer patients a 24-7 self-service triage option. Although studies suggest that users may positively perceive web-based symptom checkers, no studies have quantified user feedback after use of an electronic health record–integrated COVID-19 symptom checker with self-scheduling functionality. Objective: In this paper, we aimed to understand user experience, user satisfaction, and user-reported alternatives to the use of a COVID-19 symptom checker with self-triage and self-scheduling functionality. Methods: We launched a patient-portal–based self-triage and self-scheduling tool in March 2020 for patients with COVID-19 symptoms, exposures, or questions. We made an optional, anonymous Qualtrics survey available to patients immediately after they completed the symptom checker. Results: Between December 16, 2021, and March 28, 2022, there were 395 unique responses to the survey. Overall, the respondents reported high satisfaction across all demographics, with a median rating of 8 out of 10 and 288/395 (47.6%) of the respondents giving a rating of 9 or 10 out of 10. User satisfaction scores were not associated with any demographic factors. The most common user-reported alternatives had the web-based tool not been available were calling the COVID-19 telephone hotline and sending a patient-portal message to their physician for advice. The ability to schedule a test online was the most important symptom checker feature for the respondents. The most common categories of user feedback were regarding other COVID-19 services (eg, telephone hotline), policies, or procedures, and requesting additional features or functionality. Conclusions: This analysis suggests that COVID-19 symptom checkers with self-triage and self-scheduling functionality may have high overall user satisfaction, regardless of user demographics. By allowing users to self-triage and self-schedule tests and visits, tools such as this may prevent unnecessary calls and messages to clinicians. Individual feedback suggested that the user experience for this type of tool is highly dependent on the organization's operational workflows for COVID-19 testing and care. This study provides insight for the implementation and improvement of COVID-19 symptom checkers to ensure high user satisfaction. [ABSTRACT FROM AUTHOR]

Background: The use of telemedicine has increased dramatically through the COVID-19 pandemic. Although data are available about patient satisfaction with telemedicine, little is known about immigrant patients’ experience. Objective: We sought to investigate patients’ experiences with telehealth compared to in- person visits between immigrants and nonimmigrants. We wanted to identify and describe next visit preferences within the Farmington University of Connecticut Internal Medicine practice to ultimately guide suggestions for more equitable use and accessibility of visit options. Methods: A total of 270 patients including 122 immigrants and 148 nonimmigrants were seen by 4 Internal Medicine providers in an in-person (n=132) or telemedicine (n=138) university practice setting. Patients were queried between February and April 2021, using an adaptation of a previously validated patient satisfaction survey that contained standard questions developed by the Consumer Assessment of Healthcare Providers and Systems Program. Patients seen via in-person visits completed a paper copy of the survey. The same survey was administered by a follow-up phone call for telemedicine visits. Patients surveyed spoke English, Spanish, or Arabic and were surveyed in their preferred language. For televisits, the same survey was read to the patient by a certified translator. The survey consisted of 10 questions on a Likert scale of 1-5. Of them, 9 questions assessed patient satisfaction under the categories of access to care, interpersonal interaction, and quality of care. An additional question asked patients to describe and explain the reasons behind next visit preferences. Survey question responses were compared by paired t tests. Results: Across both immigrant and nonimmigrant patient populations, satisfaction with perceived quality of care was high, regardless of visit type (P=.80, P=.60 for televisits and P=.76, P=.37 for in-person visits). During televisits, immigrants were more likely to feel providers spent sufficient time with them (P<.001). Different perceptions were noted among nonimmigrant patients. Nonimmigrants tended to perceive more provider time during in-person visits (P=.006). When asked to comment on reasons behind next televisit preference, nonimmigrant patients prioritized convenience, whereas immigrants noted not having to navigate office logistics. For those who chose in-person visits, both groups prioritized the need for a physical exam. Conclusions: Although satisfaction was high for both telemedicine and in-person visits across immigrant and nonimmigrant populations, significant differences in patient priorities were identified. Immigrants found televisits desirable because they felt they spent more time with providers and were able to avoid additional office logistics that are often challenging barriers for non-English speakers. This suggests opportunities to use information technology to provide cultural and language-appropriate information throughout immigrants’in-person and telemedicine visit experience. A focus on diminishing these barriers will help reduce health care inequities among immigrant patients. [ABSTRACT FROM AUTHOR]

Background: The use of teletherapy has exponentially increased in the context of the ongoing COVID-19 pandemic. Studies on teletherapy documented substantial benefits of accessibility and convenience even before the start of the pandemic. Although recent studies show that this modality of therapy delivery is here to stay, few have studied who will most benefit from this trend. Objective: In this paper, we report predictors of continued teletherapy usage in a sample of licensed mental health professionals in the United States during a time period when pandemic-related restrictions began diminishing. As such, it is one of the first studies to examine factors related to continued benefits of teletherapy postpandemic. Methods: Participation from licensed mental health professionals was sought on listservs of national organizations of multiple mental health organizations. Data were collected via an anonymous link to a survey on Qualtrics between January 2021 and April 2021. Participants responded to questions on therapist demographics, practice setting, experiences of shifting to teletherapy, perspectives on continued use of teletherapy, and their client characteristics. Findings related to client characteristics that predicted continued teletherapy usage are presented here. Results: A total of 186 individuals consented to participate in the survey, with a final sample of 114 with complete data. A majority of participants identified as female (92/114, 80.7%), White (94/114, 82.5%), and having a master's degree (75/114, 65.5%) from a nationally accredited program (106/114, 93%). Data were analyzed using heteroskedastic regression modeling with client-related factors as predictors. Two models were run with and without distance travelled by clients as a control variable. Model estimates from both models showed that continued use of teletherapy postpandemic was predicted by the following factors: higher percentage of clients from rural areas, younger and older adult clients, clients with Medicare, and clients with marginalized gender and religious/spiritual identities. Significantly, having a higher percentage of clients from lower socioeconomic status, a higher percentage of those with Medicaid coverage, and a higher percentage of couples and families as clients predicted decreased use of teletherapy postpandemic. Conclusions: Findings from the study suggest that while some groups of clients are more likely to continue to receive benefits of teletherapy, vulnerable groups such as those in lower socioeconomic conditions, Medicaid beneficiaries, and those who seek couple and family therapy may be less likely to be served by it. These differences point to a need to address factors driving telehealth care disparities such as access to technology, housing, and childcare issues, as well as the need for continued training for licensed professionals. [ABSTRACT FROM AUTHOR]

Background: To provide effective care for inpatients with COVID-19, clinical practitioners need systems that monitor patient health and subsequently allow for risk scoring. Existing approaches for risk scoring in patients with COVID-19 focus primarily on intensive care units (ICUs) with specialized medical measurement devices but not on hospital general wards. Objective: In this paper, we aim to develop a risk score for inpatients with COVID-19 in general wards based on consumer-grade wearables (smartwatches). Methods: Patients wore consumer-grade wearables to record physiological measurements, such as the heart rate (HR), heart rate variability (HRV), and respiration frequency (RF). Based on Bayesian survival analysis, we validated the association between these measurements and patient outcomes (ie, discharge or ICU admission). To build our risk score, we generated a low-dimensional representation of the physiological features. Subsequently, a pooled ordinal regression with time-dependent covariates inferred the probability of either hospital discharge or ICU admission. We evaluated the predictive performance of our developed system for risk scoring in a single-center, prospective study based on 40 inpatients with COVID-19 in a general ward of a tertiary referral center in Switzerland. Results: First, Bayesian survival analysis showed that physiological measurements from consumer-grade wearables are significantly associated with patient outcomes (ie, discharge or ICU admission). Second, our risk score achieved a time-dependent area under the receiver operating characteristic curve (AUROC) of 0.73-0.90 based on leave-one-subject-out cross-validation. Conclusions: Our results demonstrate the effectiveness of consumer-grade wearables for risk scoring in inpatients with COVID-19. Due to their low cost and ease of use, consumer-grade wearables could enable a scalable monitoring system. [ABSTRACT FROM AUTHOR]

Background: Internet-based interventions (IBIs) are as efficient as face-to-face psychotherapy for a variety of mental health disorders, including complicated grief. Most evidence stems from guided IBIs. However, recent research indicates that the benefit of guidance is lower in more interactive IBIs. As such, providing guidance only to people requiring it (guidance on demand) appears a cost-effective solution. This is particularly important to develop given the recent rise in grief symptoms in the context of the COVID-19 pandemic. This paper presents the protocol of a randomized controlled trial comparing the efficacy and adherence rate of 2 IBIs for grief-related symptoms after the loss a close one following death or romantic separation, using a guidance on demand framework. LIVIA 2.0 was developed based on theoretical and empirical findings on grief processes and IBIs, and it will be compared to LIVIA 1 that has already demonstrated its efficacy. Objective: Our main hypotheses are that LIVIA 1 (control condition) and LIVIA 2.0 (experimental condition) increase participants' well-being and decrease their distress at posttest and at follow-up, that LIVIA 2.0 is more efficient than LIVIA 1 for all outcomes, and that LIVIA 2.0 has less dropouts than LIVIA 1. Methods: Outcomes will be assessed at pretest, posttest (12 weeks later), and follow-up (24 weeks later). We will recruit 234 participants through a variety of means, including social media and contacts with the press. Primary outcomes are grief symptoms, depressive symptoms, and eudemonic well-being. Secondary outcomes are anxiety symptoms, grief coping strategies, aspects related to self-identity reorganization, and program satisfaction. LIVIA 2.0 participants will additionally undergo a weekly mood and grief symptom monitoring, allowing us to explore the short-term efficacy of the sessions. Results: The creation and development of the content of LIVIA 2.0 was completed during the first phase of the project. Participant recruitment will begin in May 2022 and will last until January 2023. Conclusions: This study will emphasize the relevance of the innovations included in LIVIA 2.0 regarding the efficacy and dropout rate of IBIs for grief symptoms and will allow investigations on how these changes impact the demand for guidance. In the current postpandemic times, developing and assessing IBIs targeting grief symptoms are particularly critical given the rise in grief-related symptoms. [ABSTRACT FROM AUTHOR]

Background: Contact tracing has been globally adopted in the fight to control the infection rate of COVID-19. To this aim, several mobile apps have been developed. However, there are ever-growing concerns over the working mechanism and performance of these applications. The literature already provides some interesting exploratory studies on the community’s response to the applications by analyzing information from different sources, such as news and users’ reviews of the applications. However, to the best of our knowledge, there is no existing solution that automatically analyzes users’ reviews and extracts the evoked sentiments. We believe such solutions combined with a user-friendly interface can be used as a rapid surveillance tool to monitor how effective an application is and to make immediate changes without going through an intense participatory design method. Objective: In this paper, we aim to analyze the efficacy of AI and NLP techniques for automatically extracting and classifying the polarity of users’ sentiments by proposing a sentiment analysis framework to automatically analyze users’ reviews on COVID-19 contact tracing mobile apps. We also aim to provide a large-scale annotated benchmark data set to facilitate future research in the domain. As a proof of concept, we also developed a web application based on the proposed solutions, which is expected to help the community quickly analyze the potential of an application in the domain. Methods: We propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding with the development and training of artificial intelligence (AI) models for automatic sentiment analysis of users’ reviews. In detail, we collected and annotated a large-scale data set of user reviews on COVID-19 contact tracing applications. We used both classical and deep learning methods for classification experiments. Results: We used 8 different methods on 3 different tasks, achieving up to an average F1 score of 94.8%, indicating the feasibility of the proposed solution. The crowd-sourcing activity resulted in a large-scale benchmark data set composed of 34,534 manually annotated reviews. Conclusions: The existing literature mostly relies on the manual or exploratory analysis of users’ reviews on applications, which is tedious and time-consuming. In existing studies, generally, data from fewer applications are analyzed. In this work, we showed that AI and natural language processing techniques provide good results for analyzing and classifying users’ sentiments’ polarity and that automatic sentiment analysis can help to analyze users’ responses more accurately and quickly. We also provided a large-scale benchmark data set. We believe the presented analysis, data set, and proposed solutions combined with a user-friendly interface can be used as a rapid surveillance tool to analyze and monitor mobile apps deployed in emergency situations leading to rapid changes in the applications without going through an intense participatory design method. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic exacerbated existing racial/ethnic health disparities in the United States. Monitoring nationwide Twitter conversations about COVID-19 and race/ethnicity could shed light on the impact of the pandemic on racial/ethnic minorities and help address health disparities. Objective: This paper aims to examine the association between COVID-19 tweet volume and COVID-19 cases and deaths, stratified by race/ethnicity, in the early onset of the pandemic. Methods: This cross-sectional study used geotagged COVID-19 tweets from within the United States posted in April 2020 on Twitter to examine the association between tweet volume, COVID-19 surveillance data (total cases and deaths in April), and population size. The studied time frame was limited to April 2020 because April was the earliest month when COVID-19 surveillance data on racial/ethnic groups were collected. Racially/ethnically stratified tweets were extracted using racial/ethnic group–related keywords (Asian, Black, Latino, and White) from COVID-19 tweets. Racially/ethnically stratified tweets, COVID-19 cases, and COVID-19 deaths were mapped to reveal their spatial distribution patterns. An ordinary least squares (OLS) regression model was applied to each stratified dataset. Results: The racially/ethnically stratified tweet volume was associated with surveillance data. Specifically, an increase of 1 Asian tweet was correlated with 288 Asian cases (P<.001) and 93.4 Asian deaths (P<.001); an increase of 1 Black tweet was linked to 47.6 Black deaths (P<.001); an increase of 1 Latino tweet was linked to 719 Latino deaths (P<.001); and an increase of 1 White tweet was linked to 60.2 White deaths (P<.001). Conclusions: Using racially/ethnically stratified Twitter data as a surveillance indicator could inform epidemiologic trends to help estimate future surges of COVID-19 cases and potential future outbreaks of a pandemic among racial/ethnic groups. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has sped up the implementation of telehealth solutions in medicine. A few symptom checkers dedicated for COVID-19 have been described, but it remains unclear whether and how they can affect patients and health systems. Objective: This paper demonstrates our experiences with the COVID-19 risk assessment (CRA) tool. We tried to determine who the user of the web-based COVID-19 triage app is and compare this group with patients in the infectious diseases ward's admission room to evaluate who could benefit from implementing the COVID-19 online symptom checker as a remote triage solution. Methods: We analyzed the answers of 248,862 people interacting with an online World Health Organization-based triage tool for assessing the probability of SARS-CoV-2 infection. These users filled in an online questionnaire between April 7 and August 6, 2020. Based on the presented symptoms, risk factors, and demographics, the tool assessed whether the user's answers were suggestive of COVID-19 and recommended appropriate action. Subsequently, we compared the sociodemographic and clinical characteristics of tool users with patients admitted to the Infectious Diseases Admission Room of J. Gromkowski Hospital in Wrocław. Results: The CRA tool tended to be used by asymptomatic or oligosymptomatic individuals (171,226 [68.80%] of all users). Most users were young (162,432 [65.27%] were below 40 years of age) and without comorbidities. Only 77,645 (31.20%) of the self-assessment app users were suspected of COVID-19 based on their reported symptoms. On the contrary, most admission room patients were symptomatic--symptoms such as fever, cough, and dyspnea were prevalent in both COVID-19-positive and COVID-19-negative patients. COVID-19-suspected patients in the CRA tool group presented similar COVID-19 symptoms as those who presented to the admission room. These were cough (25,062/40,007 [62.64%] in the CRA tool group vs 138/232 [59.48%] in the admission room group), fever (23,123/40,007 [57.80%] in the CRA tool group vs 146/232 [62.93%] in the admission room group), and shortness of breath (15,157/40,007 [37.89%] in the CRA tool group vs 87/232 [37.50%] in the admission room group). Conclusions: The comparison between the symptomatology of the users interacting with the CRA tool and those visiting the admission room revealed 2 major patient groups who could have benefited from the implementation of the self-assessment app in preclinical triage settings. The primary users of the CRA tool were young, oligosymptomatic individuals looking for screening for COVID-19 and reassurance early in the COVID-19 pandemic. The other group were users presenting the typical symptoms suggestive of COVID-19 at that time. The CRA tool recognized these individuals as potentially COVID-19 positive and directed them to the proper level of care. These use cases fulfil the idea of preclinical triage; however, the accuracy and influence on health care must be examined in the clinical setting. [ABSTRACT FROM AUTHOR]

Background: Facing COVID 19, the use of telehealth solutions grows exponentially. However, despite the large investments made into telehealth solutions, the implementation process remains slow and sluggish. Moreover, during COVID-19, older people experienced difficulties and had the highest mortality rates, and those lucky enough to survive faced tremendous pressure to use QR code-based health monitoring systems. Objective: This paper aims to determine the barriers and incentives for the implementation of telehealth solutions via a case study about telehealth implementation in China. Methods: We conducted 8 semi-structured interviews following the design of the interactive learning framework (research question defining, participant recruitment, exploratory stage, consultation stage, integration stage, and follow-up interview). One interview with a government official from the National Health Commission and another interview with a government official from the China Center for Disease Control and Prevention was conducted in the exploratory stage. The consultation stage comprised one interview with a business manager from the Huawei Wearable Unit, one interview with a business manager from Alibaba Health Brain Unit, and one interview with a business manager from Xiaomi. Two interviews with doctors from Fudan University-affiliated Huashan Hospital and Fudan University-affiliated Zhongshan hospital were conducted in the integration stage. In addition, 8 focus group studies with 64 participants from rural and urban Beijing were conducted. Finally, another telephone interview with a business manager of the Xiaomi Wearable Unit was conducted in the follow-up stage. Results: Telehealth solutions are designed to assist health care providers in realizing the quadruple aim of better health outcomes, lowering health care costs, improved health care quality, and improved doctor and patient experiences. Governments have high incentives to improve health care efficiency via telehealth solutions. However, they have limited resources to make the necessary infrastructure transformation. Conclusions: To fully realize the potential of telehealth devices, heavy infrastructure investment in the telecommunication network is required beforehand to resolve the interoperability issue occurring during the data collection process for telehealth solutions. The industry also demands a mature business model incorporating collaboration between various stakeholders and industrial partners to invest in infrastructure. Governments have high interest and significant influence on building the necessary infrastructure for telehealth solution implementation in China. Industrial actors have a high interest and a medium level of power for telehealth solution implementation. Users have high interest but a lower level of power for the usage of telehealth solutions, and doctors have low interest and a medium level of power for telehealth solutions implementation. [ABSTRACT FROM AUTHOR]

Background: Recruitment of diverse populations for health research studies remains a challenge. The COVID-19 pandemic has exacerbated these challenges by limiting in-person recruitment efforts and placing additional demands on potential participants. Social media, through the use of Facebook advertisements, has the potential to address recruitment challenges. However, existing reports are inconsistent with regard to the success of this strategy. Additionally, limited information is available about processes that can be used to increase the diversity of study participants. Objective: A Qualtrics survey was fielded to ascertain women's knowledge of and health care experiences related to breast density. This paper describes the process of using Facebook advertisements for recruitment and the effectiveness of various advertisement strategies. Methods: Facebook advertisements were placed in 2 rounds between June and July 2020. During round 1, multiple combinations of headlines and interest terms were tested to determine the most cost-effective advertisement. The best performing advertisement was used in round 2 in combination with various strategies to enhance the diversity of the survey sample. Advertisement performance, cost, and survey respondent data were collected and examined. Results: In round 1, a total of 45 advertisements with 5 different headlines were placed, and the average cost per link click for each headline ranged from US $0.12 to US $0.79. Of the 164 women recruited in round 1, in total 91.62% were eligible to complete the survey. Advertisements used during recruitment in round 2 resulted in an average cost per link click of US $0.11. During the second round, 478 women attempted the survey, and 87.44% were eligible to participate. The majority of survey respondents were White (80.41%), over the age of 55 years (63.94%), and highly educated (63.71%). Conclusions: Facebook advertisements can be used to recruit respondents for health research quickly, but this strategy may yield participants who are less racially diverse, more educated, and older than the general population. Researchers should consider recruiting participants through other methods in addition to creating Facebook advertisements targeting underrepresented populations. [ABSTRACT FROM AUTHOR]

Background: The unexpected outbreak of the COVID-19 pandemic and the preventive measures of physical distancing have further necessitated the application of information and communication technologies (ICTs) to enhance the efficiency of work activities in health care. Although the interplay between human agency and technology performativity is critical to the success or failure of ICTs use in routine practice, it is rarely explored when designing health ICTs for hospital settings within the sub-Saharan Africa context. Objective: The objective of this study is to explore how the service delivery quality is being influenced by the technology-enabled activities of health care professionals at points of care using a service design strategy. Methods: An interpretivist stance was assumed to understand the socially constructed realities of health care professionals at points of care in a hospital setting. A service design strategy was identified as suitable for engaging health care professionals in co-design sessions to collect data. A purposive sampling technique was used to identify the participants. Open-ended questions were administered to gain insights into the work activities of physicians and nurses at points of care. Qualitative (textual) data were analyzed using thematic analysis. Ethical concerns about the safety and privacy of participants' data were addressed as per the university ethics review committee and provincial department of health. Results: The findings show that the attributes of human agency and technology features that drive technology performativity result in an interplay between social concepts and technical features that influence the transformation of human-machine interactions. In addition, the interplay of the double dance of agency model can be divided into 2 successive phases: intermediate and advanced. Intermediate interplay results in the perceived suitability or discomfort of health ICTs as experienced by health care professionals at initial interactions during the execution of work activities. Subsequently, the advanced interplay determines the usefulness and effectiveness of health ICTs in aiding task performance, which ultimately leads to either the satisfaction or dissatisfaction of health care professionals in the completion of their work activities at points of care. Conclusions: The adopted service design strategy revealed that the interaction moments of the tasks performed by health care professionals during the execution of their work activities at point of care determine the features of health ICTs relevant to work activities. Consequently, the ensuing experience of health care professionals at the completion of their work activities influences the use or discontinuation of health ICTs. Health care professionals consider the value-added benefits from the automation of their work activities to ultimately influence the quality of service delivery. The major knowledge contribution of this study is the awareness drawn to both the intermediate and advanced interplay of human-machine interaction when designing health ICTs. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has illuminated multiple challenges within the health care system and is unique to those living with chronic conditions. Recent advances in digital health technologies (eHealth) present opportunities to improve quality of care, self-management, and decision-making support to reduce treatment burden and the risk of chronic condition management burnout. There are limited available eHealth models that can adequately describe how this can be carried out. In this paper, we define treatment burden and the related risk of affective burnout; assess how an eHealth enhanced Chronic Care Model can help prioritize digital health solutions; and describe an emerging machine learning model as one example aimed to alleviate treatment burden and burnout risk. We propose that eHealth-driven machine learning models can be a disruptive change to optimally support persons living with chronic conditions. [ABSTRACT FROM AUTHOR]

Background: As SARS-CoV-2, the virus that causes COVID-19, spread rapidly across the United States in the spring of 2020, institutions of higher education faced numerous challenges associated with minimizing risk of exposure to COVID-19 among their students, faculty, staff, and surrounding communities. This paper describes the protocol, South Carolina (SC) Safer Together, developed by Clemson University (Clemson) to design, deploy, and evaluate multi-level communication and dissemination and implementation (D&I) strategies in line with recommendations from governmental and educational agencies to mitigate the risk of exposure to COVID-19. Safer Together was enhanced by the addition of the Google/Apple Exposure Notification app, an alternative strategy to support a recommendation of COVID-19 testing outcomes: contact tracing, isolation, and quarantine. Objective: This study aimed to (1) describe the content and intended audiences of D&I strategies used to deploy recommended COVID-19 mitigation strategies on a major college campus; (2) determine the reach, acceptability, adoption, and use of D&I strategies among target audiences among university students, faculty, and staff; and (3) characterize barriers and facilitators to the implementation and use of recommended mitigation strategies. Methods: The study team incorporated elements of the Health Belief Model, the Technology Acceptance Model, communication and social marketing models, and the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to identify and develop appropriate constructs and specific outcomes for inclusion in our approach to evaluate the communication, dissemination and implementation processes related to deployment of Safer Together at Clemson. A parallel convergent mixed methods design was used to (1) inform implementation strategies used to launch the program and (2) evaluate program reach, acceptability, adoption, and use guided by the RE-AIM framework. Data collection tools include surveys, data analytics--tracking, and focus groups or interviews with key stakeholders (students, employees, and university leadership). Results: Rigorously studying both the dissemination and implementation of Safer Together in a national public university setting is expected to yield lessons that will be valuable at many organizational and governmental settings. On a local level, broad adoption and use of the Safer Together may help reduce COVID-19 transmission and keep the university "open." On a larger scale, lessons learned on how to influence student and employee behavior with respect to the use of a public health outbreak prevention tool including Safer Together may be applicable in future pandemic and outbreak situations. Conclusions: This study proposes a structured, theory-driven approach to evaluate dissemination and implementation strategies associated with the deployment of Safer Together in a university setting from the viewpoint of students, employees, and university leadership. Our results will inform future implementation of apps such as Safer Together at major state universities in SC. [ABSTRACT FROM AUTHOR]

Background: The ubiquity of mobile phones and increasing use of wearable fitness trackers offer a wide-ranging window into people’s health and well-being. There are clear advantages in using remote monitoring technologies to gain an insight into health, particularly under the shadow of the COVID-19 pandemic. Objective: Covid Collab is a crowdsourced study that was set up to investigate the feasibility of identifying, monitoring, and understanding the stratification of SARS-CoV-2 infection and recovery through remote monitoring technologies. Additionally, we will assess the impacts of the COVID-19 pandemic and associated social measures on people’s behavior, physical health, and mental well-being. Methods: Participants will remotely enroll in the study through the Mass Science app to donate historic and prospective mobile phone data, fitness tracking wearable data, and regular COVID-19–related and mental health–related survey data. The data collection period will cover a continuous period (ie, both before and after any reported infections), so that comparisons to a participant’s own baseline can be made. We plan to carry out analyses in several areas, which will cover symptomatology; risk factors; the machine learning–based classification of illness; and trajectories of recovery, mental well-being, and activity. Results: As of June 2021, there are over 17,000 participants—largely from the United Kingdom—and enrollment is ongoing. Conclusions: This paper introduces a crowdsourced study that will include remotely enrolled participants to record mobile health data throughout the COVID-19 pandemic. The data collected may help researchers investigate a variety of areas, including COVID-19 progression; mental well-being during the pandemic; and the adherence of remote, digitally enrolled participants. [ABSTRACT FROM AUTHOR]

Background: Exposure to occupational stressors and potentially psychologically traumatic events experienced by public safety personnel (eg, paramedics, police, fire, and correctional officers), military members, and veterans can lead to the development of posttraumatic stress injuries and other mental health disorders. Providing emergency services during COVID-19 has intensified the challenges. Owing to COVID-19 restrictions, mental health service providers offering support to these populations have had to rapidly pivot to use digital versus in-person methods of service delivery. Objective: This paper aims to explore the experience of mental health service providers regarding digital health service delivery, including the current state of digital mental health service delivery, barriers to and facilitators of the use of digital health for mental health service delivery experienced during the pandemic, and recommendations for implementing and integrating digital health into regular mental health service delivery. Methods: This embedded mixed-methods study included questionnaires and focus groups with key stakeholders (N=31) with knowledge and experience in providing mental health services. Data analysis included descriptive, quantitative, and qualitative thematic analyses. Results: The following three themes emerged: being forced into change, daring to deliver mental health services using digital health, and future possibilities offered by digital health. In each theme, participants' responses reflected their perceptions of service providers, organizations, and clients. The findings offer considerations regarding for whom and at what point in treatment digital health delivery is appropriate; recommendations for training, support, resources, and guidelines for digitally delivering trauma therapy; and a better understanding of factors influencing mental health service providers' perceptions and acceptance of digital health for mental health service delivery. Conclusions: The results indicate the implementation of digital health for mental health service delivery to military members, public safety personnel, and veterans. As the COVID-19 pandemic continues, remote service delivery methods for trauma therapy are urgently needed to support the well-being of those who have served and continue to serve. [ABSTRACT FROM AUTHOR]