@Article{info:doi/10.2196/17158, author="Tudor Car, Lorainne and Dhinagaran, Ardhithy Dhakshenya and Kyaw, Myint Bhone and Kowatsch, Tobias and Joty, Shafiq and Theng, Yin-Leng and Atun, Rifat", title="Conversational Agents in Health Care: Scoping Review and Conceptual Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="7", volume="22", number="8", pages="e17158", keywords="conversational agents", keywords="chatbots", keywords="artificial intelligence", keywords="machine learning", keywords="mobile phone", keywords="health care", keywords="scoping review", abstract="Background: Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. Objective: This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. Methods: We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms ``conversational agents,'' ``conversational AI,'' ``chatbots,'' and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. Results: The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. Conclusions: The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence--driven, and smartphone app--delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents' formats, focusing on their acceptability, safety, and effectiveness. ", doi="10.2196/17158", url="http://www.jmir.org/2020/8/e17158/", url="http://www.ncbi.nlm.nih.gov/pubmed/32763886" } @Article{info:doi/10.2196/16504, author="Vall{\'e}e, Alexandre and Blacher, Jacques and Cariou, Alain and Sorbets, Emmanuel", title="Blended Learning Compared to Traditional Learning in Medical Education: Systematic Review and Meta-Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e16504", keywords="blended learning", keywords="virtual patients", keywords="online learning", keywords="computer-aided instruction", keywords="traditional learning", keywords="meta-analysis", abstract="Background: Blended learning, which combines face-to-face learning and e-learning, has grown rapidly to be commonly used in education. Nevertheless, the effectiveness of this learning approach has not been completely quantitatively synthesized and evaluated using knowledge outcomes in health education. Objective: The aim of this study was to assess the effectiveness of blended learning compared to that of traditional learning in health education. Methods: We performed a systematic review of blended learning in health education in MEDLINE from January 1990 to July 2019. We independently selected studies, extracted data, assessed risk of bias, and compared overall blended learning versus traditional learning, offline blended learning versus traditional learning, online blended learning versus traditional learning, digital blended learning versus traditional learning, computer-aided instruction blended learning versus traditional learning, and virtual patient blended learning versus traditional learning. All pooled analyses were based on random-effect models, and the I2 statistic was used to quantify heterogeneity across studies. Results: A total of 56 studies (N=9943 participants) assessing several types of learning support in blended learning met our inclusion criteria; 3 studies investigated offline support, 7 studies investigated digital support, 34 studies investigated online support, 8 studies investigated computer-assisted instruction support, and 5 studies used virtual patient support for blended learning. The pooled analysis comparing all blended learning to traditional learning showed significantly better knowledge outcomes for blended learning (standardized mean difference 1.07, 95\% CI 0.85 to 1.28, I2=94.3\%). Similar results were observed for online (standardized mean difference 0.73, 95\% CI 0.60 to 0.86, I2=94.9\%), computer-assisted instruction (standardized mean difference 1.13, 95\% CI 0.47 to 1.79, I2=78.0\%), and virtual patient (standardized mean difference 0.62, 95\% CI 0.18 to 1.06, I2=78.4\%) learning support, but results for offline learning support (standardized mean difference 0.08, 95\% CI --0.63 to 0.79, I2=87.9\%) and digital learning support (standardized mean difference 0.04, 95\% CI --0.45 to 0.52, I2=93.4\%) were not significant. Conclusions: From this review, blended learning demonstrated consistently better effects on knowledge outcomes when compared with traditional learning in health education. Further studies are needed to confirm these results and to explore the utility of different design variants of blended learning. ", doi="10.2196/16504", url="https://www.jmir.org/2020/8/e16504", url="http://www.ncbi.nlm.nih.gov/pubmed/32773378" } @Article{info:doi/10.2196/17432, author="Chan, Lilian and O'Hara, Blythe and Phongsavan, Philayrath and Bauman, Adrian and Freeman, Becky", title="Review of Evaluation Metrics Used in Digital and Traditional Tobacco Control Campaigns", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17432", keywords="mass media", keywords="internet", keywords="evaluation studies as topic", keywords="smoking cessation", keywords="public health", abstract="Background: Mass media campaigns for public health are increasingly using digital media platforms, such as web-based advertising and social media; however, there is a lack of evidence on how to best use these digital platforms for public health campaigns. To generate this evidence, appropriate campaign evaluations are needed, but with the proliferation of digital media--related metrics, there is no clear consensus on which evaluation metrics should be used. Public health campaigns are diverse in nature, so to facilitate analysis, this review has selected tobacco control campaigns as the scope of the study. Objective: This literature review aimed to examine how tobacco control campaigns that use traditional and digital media platforms have been evaluated. Methods: Medicine and science databases (Medical Literature Analysis and Retrieval System Online [MEDLINE], EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature [CINAHL], and Scopus), and a marketing case study database (World Advertising Research Center) were searched for articles published between 2013 and 2018. Two authors established the eligibility criteria and reviewed articles for inclusion. Individual campaigns were identified from the articles, and information on campaigns and their evaluations were supplemented with searches on Google, Google Scholar, and social media platforms. Data about campaign evaluations were tabulated and mapped to a conceptual framework. Results: In total, 17 campaigns were included in this review, with evaluations reported on by 51 articles, 17 marketing reports, and 4 grey literature reports. Most campaigns were from English-speaking countries, with behavioral change as the primary objective. In the process evaluations, a wide range of metrics were used to assess the reach of digital campaign activities, making comparison between campaigns difficult. Every campaign in the review, except one, reported some type of engagement impact measure, with website visits being the most commonly reported metric (11 of the 17 campaigns). Other commonly reported evaluation measures identified in this review include engagement on social media, changes in attitudes, and number of people contacting smoking cessation services. Of note, only 7 of the 17 campaigns attempted to measure media platform attribution, for example, by asking participants where they recalled seeing the campaign or using unique website tracking codes for ads on different media platforms. Conclusions: One of the key findings of this review is the numerous and diverse range of measures and metrics used in tobacco control campaign evaluations. To address this issue, we propose principles to guide the selection of digital media--related metrics for campaign evaluations, and also outline a conceptual framework to provide a coherent organization to the diverse range of metrics. Future research is needed to specifically investigate whether engagement metrics are associated with desired campaign outcomes, to determine whether reporting of engagement metrics is meaningful in campaign evaluations. ", doi="10.2196/17432", url="https://www.jmir.org/2020/8/e17432", url="http://www.ncbi.nlm.nih.gov/pubmed/32348272" } @Article{info:doi/10.2196/17774, author="Bonten, N. Tobias and Rauwerdink, Anneloek and Wyatt, C. Jeremy and Kasteleyn, J. Marise and Witkamp, Leonard and Riper, Heleen and van Gemert-Pijnen, JEWC Lisette and Cresswell, Kathrin and Sheikh, Aziz and Schijven, P. Marlies and Chavannes, H. Niels and ", title="Online Guide for Electronic Health Evaluation Approaches: Systematic Scoping Review and Concept Mapping Study", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e17774", keywords="eHealth", keywords="mHealth", keywords="digital health", keywords="methodology", keywords="study design", keywords="health technology assessment", keywords="evaluation", keywords="scoping review", keywords="concept mapping", abstract="Background: Despite the increase in use and high expectations of digital health solutions, scientific evidence about the effectiveness of electronic health (eHealth) and other aspects such as usability and accuracy is lagging behind. eHealth solutions are complex interventions, which require a wide array of evaluation approaches that are capable of answering the many different questions that arise during the consecutive study phases of eHealth development and implementation. However, evaluators seem to struggle in choosing suitable evaluation approaches in relation to a specific study phase. Objective: The objective of this project was to provide a structured overview of the existing eHealth evaluation approaches, with the aim of assisting eHealth evaluators in selecting a suitable approach for evaluating their eHealth solution at a specific evaluation study phase. Methods: Three consecutive steps were followed. Step 1 was a systematic scoping review, summarizing existing eHealth evaluation approaches. Step 2 was a concept mapping study asking eHealth researchers about approaches for evaluating eHealth. In step 3, the results of step 1 and 2 were used to develop an ``eHealth evaluation cycle'' and subsequently compose the online ``eHealth methodology guide.'' Results: The scoping review yielded 57 articles describing 50 unique evaluation approaches. The concept mapping study questioned 43 eHealth researchers, resulting in 48 unique approaches. After removing duplicates, 75 unique evaluation approaches remained. Thereafter, an ``eHealth evaluation cycle'' was developed, consisting of six evaluation study phases: conceptual and planning, design, development and usability, pilot (feasibility), effectiveness (impact), uptake (implementation), and all phases. Finally, the ``eHealth methodology guide'' was composed by assigning the 75 evaluation approaches to the specific study phases of the ``eHealth evaluation cycle.'' Conclusions: Seventy-five unique evaluation approaches were found in the literature and suggested by eHealth researchers, which served as content for the online ``eHealth methodology guide.'' By assisting evaluators in selecting a suitable evaluation approach in relation to a specific study phase of the ``eHealth evaluation cycle,'' the guide aims to enhance the quality, safety, and successful long-term implementation of novel eHealth solutions. ", doi="10.2196/17774", url="https://www.jmir.org/2020/8/e17774", url="http://www.ncbi.nlm.nih.gov/pubmed/32784173" } @Article{info:doi/10.2196/18355, author="Xie, Feng Li and Itzkovitz, Alexandra and Roy-Fleming, Amelie and Da Costa, Deborah and Brazeau, Anne-Sophie", title="Understanding Self-Guided Web-Based Educational Interventions for Patients With Chronic Health Conditions: Systematic Review of Intervention Features and Adherence", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e18355", keywords="chronic disease", keywords="online learning", keywords="self-management", keywords="mobile phone", abstract="Background: Chronic diseases contribute to 71\% of deaths worldwide every year, and an estimated 15 million people between the ages of 30 and 69 years die mainly because of cardiovascular disease, cancer, chronic respiratory diseases, or diabetes. Web-based educational interventions may facilitate disease management. These are also considered to be a flexible and low-cost method to deliver tailored information to patients. Previous studies concluded that the implementation of different features and the degree of adherence to the intervention are key factors in determining the success of the intervention. However, limited research has been conducted to understand the acceptability of specific features and user adherence to self-guided web interventions. Objective: This systematic review aims to understand how web-based intervention features are evaluated, to investigate their acceptability, and to describe how adherence to web-based self-guided interventions is defined and measured. Methods: Studies published on self-guided web-based educational interventions for people (?14 years old) with chronic health conditions published between January 2005 and June 2020 were reviewed following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement protocol. The search was performed using the PubMed, Cochrane Library, and EMBASE (Excerpta Medica dataBASE) databases; the reference lists of the selected articles were also reviewed. The comparison of the interventions and analysis of the features were based on the published content from the selected articles. Results: A total of 20 studies were included. Seven principal features were identified, with goal setting, self-monitoring, and feedback being the most frequently used. The acceptability of the features was measured based on the comments collected from users, their association with clinical outcomes, or device adherence. The use of quizzes was positively reported by participants. Self-monitoring, goal setting, feedback, and discussion forums yielded mixed results. The negative acceptability was related to the choice of the discussion topic, lack of face-to-face contact, and technical issues. This review shows that the evaluation of adherence to educational interventions was inconsistent among the studies, limiting comparisons. A clear definition of adherence to an intervention is lacking. Conclusions: Although limited information was available, it appears that features related to interaction and personalization are important for improving clinical outcomes and users' experience. When designing web-based interventions, the selection of features should be based on the targeted population's needs, the balance between positive and negative impacts of having human involvement in the intervention, and the reduction of technical barriers. There is a lack of consensus on the method of evaluating adherence to an intervention. Both investigations of the acceptability features and adherence should be considered when designing and evaluating web-based interventions. A proof-of-concept or pilot study would be useful for establishing the required level of engagement needed to define adherence. ", doi="10.2196/18355", url="http://www.jmir.org/2020/8/e18355/", url="http://www.ncbi.nlm.nih.gov/pubmed/32788152" } @Article{info:doi/10.2196/20193, author="Quirch, Miguel and Lee, Jeannie and Rehman, Shabnam", title="Hazards of the Cytokine Storm and Cytokine-Targeted Therapy in Patients With COVID-19: Review", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e20193", keywords="coronavirus", keywords="COVID-19", keywords="convalescent plasma therapy", keywords="cytokine storm", keywords="SARS-CoV-2", keywords="cytokine", keywords="immunology", keywords="review", keywords="mortality", keywords="inflammation", keywords="therapy", abstract="Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has challenged medicine and health care on a global scale. Its impact and frightening mortality rate are in large part attributable to the fact that there is a lack of available treatments. It has been shown that in patients who are severely ill, SARS-CoV-2 can lead to an inflammatory response known as cytokine storm, which involves activation and release of inflammatory cytokines in a positive feedback loop of pathogen-triggered inflammation. Currently, cytokine storm is one of the leading causes of morbidity and mortality in SARS-CoV-2, but there is no proven treatment to combat this systemic response. Objective: The aim of this paper is to study the cytokine storm response in SARS-CoV-2 and to explore the early treatment options for patients who are critically ill with the coronavirus disease (COVID-19) in the early stages of the pandemic by reviewing the literature. Methods: A literature review was performed from December 1, 2000, to April 4, 2020, to explore and compare therapies that target cytokine storm among SARS-CoV-2 and prior coronavirus cases. Results: A total of 38 eligible studies including 24 systematic reviews, 5 meta-analyses, 5 experimental model studies, 7 cohort studies, and 4 case reports matched the criteria. Conclusions: The severity of the cytokine storm, measured by elevated levels of interleukin-1B, interferon-$\gamma$, interferon-inducible protein 10, and monocyte chemoattractant protein 1, was associated with COVID-19 disease severity. Many treatment options with different targets have been proposed during the early stages of the COVID-19 pandemic, ranging from targeting the virus itself to managing the systemic inflammation caused by the virus and the excessive cytokine response. Among the different agents to manage cytokine storm in patients with COVID-19, there is developing support for convalescent plasma therapy particularly for patients who are critically ill or mechanically ventilated and resistant to antivirals and supportive care. Treatment options that were proposed in the beginning phases of the pandemic were multidimensional, and further research is needed to develop a more established treatment guideline. ", doi="10.2196/20193", url="http://www.jmir.org/2020/8/e20193/", url="http://www.ncbi.nlm.nih.gov/pubmed/32707537" } @Article{info:doi/10.2196/18747, author="Thiabaud, Amaury and Triulzi, Isotta and Orel, Erol and Tal, Kali and Keiser, Olivia", title="Social, Behavioral, and Cultural factors of HIV in Malawi: Semi-Automated Systematic Review", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e18747", keywords="HIV/AIDS", keywords="topic modelling", keywords="text mining", keywords="Malawi", keywords="risk factors", keywords="machine learning", abstract="Background: Demographic and sociobehavioral factors are strong drivers of HIV infection rates in sub-Saharan Africa. These factors are often studied in qualitative research but ignored in quantitative analyses. However, they provide in-depth insight into the local behavior and may help to improve HIV prevention. Objective: To obtain a comprehensive overview of the sociobehavioral factors influencing HIV prevalence and incidence in Malawi, we systematically reviewed the literature using a newly programmed tool for automatizing part of the systematic review process. Methods: Due to the choice of broad search terms (``HIV AND Malawi''), our preliminary search revealed many thousands of articles. We, therefore, developed a Python tool to automatically extract, process, and categorize open-access articles published from January 1, 1987 to October 1, 2019 in the PubMed, PubMed Central, JSTOR, Paperity, and arXiV databases. We then used a topic modelling algorithm to classify and identify publications of interest. Results: Our tool extracted 22,709 unique articles; 16,942 could be further processed. After topic modelling, 519 of these were clustered into relevant topics, of which 20 were kept after manual screening. We retrieved 7 more publications after examining the references so that 27 publications were finally included in the review. Reducing the 16,942 articles to 519 potentially relevant articles using the software took 5 days. Several factors contributing to the risk of HIV infection were identified, including religion, gender and relationship dynamics, beliefs, and sociobehavioral attitudes. Conclusions: Our software does not replace traditional systematic reviews, but it returns useful results to broad queries of open-access literature in under a week, without a priori knowledge. This produces a ``seed dataset'' of relevance that could be further developed. It identified known factors and factors that may be specific to Malawi. In the future, we aim to expand the tool by adding more social science databases and applying it to other sub-Saharan African countries. ", doi="10.2196/18747", url="http://www.jmir.org/2020/8/e18747/", url="http://www.ncbi.nlm.nih.gov/pubmed/32795992" } @Article{info:doi/10.2196/22214, author="Mirchev, Martin and Mircheva, Iskra and Kerekovska, Albena", title="The Academic Viewpoint on Patient Data Ownership in the Context of Big Data: Scoping Review", journal="J Med Internet Res", year="2020", month="Aug", day="18", volume="22", number="8", pages="e22214", keywords="big data", keywords="ethics", keywords="legal aspects", keywords="ownership", keywords="patient-generated health data", abstract="Background: The ownership of patient information in the context of big data is a relatively new problem, which is not yet fully recognized by the medical academic community. The problem is interdisciplinary, incorporating legal, ethical, medical, and aspects of information and communication technologies, requiring a sophisticated analysis. However, no previous scoping review has mapped existing studies on the subject. Objective: This study aims to map and assess published studies on patient data ownership in the context of big data as viewed by the academic community. Methods: A scoping review was conducted based on the 5-stage framework outlined by Arksey and O'Malley and further developed by Levac, Colquhoun, and O'Brien. The organization and reporting of results of the scoping review were conducted according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses and its extensions for Scoping Reviews). A systematic and comprehensive search of 4 scientific information databases, PubMed, ScienceDirect, Scopus, and Springer, was performed for studies published between January 2000 and October 2019. Two authors independently assessed the eligibility of the studies and the extracted data. Results: The review included 32 eligible articles authored by academicians that correspond to 3 focus areas: problem (ownership), area (health care), and context (big data). Five major aspects were studied: the scientific area of publications, aspects and academicians' perception of ownership in the context of big data, proposed solutions, and practical applications for data ownership issues in the context of big data. The aspects in which publications consider ownership of medical data are not clearly distinguished but can be summarized as ethical, legal, political, and managerial. The ownership of patient data is perceived primarily as a challenge fundamental to conducting medical research, including data sales and sharing, and to a lesser degree as a means of control, problem, threat, and opportunity also in view of medical research. Although numerous solutions falling into 3 categories, technology, law, and policy, were proposed, only 3 real applications were discussed. Conclusions: The issue of ownership of patient information in the context of big data is poorly researched; it is not addressed consistently and in its integrity, and there is no consensus on policy decisions and the necessary legal regulations. Future research should investigate the issue of ownership as a core research question and not as a minor fragment among other topics. More research is needed to increase the body of knowledge regarding the development of adequate policies and relevant legal frameworks in compliance with ethical standards. The combined efforts of multidisciplinary academic teams are needed to overcome existing gaps in the perception of ownership, the aspects of ownership, and the possible solutions to patient data ownership issues in the reality of big data. ", doi="10.2196/22214", url="http://www.jmir.org/2020/8/e22214/", url="http://www.ncbi.nlm.nih.gov/pubmed/32808934" } @Article{info:doi/10.2196/17015, author="Wong, SY Zoie and Siy, Braylien and Da Silva Lopes, Katharina and Georgiou, Andrew", title="Improving Patients' Medication Adherence and Outcomes in Nonhospital Settings Through eHealth: Systematic Review of Randomized Controlled Trials", journal="J Med Internet Res", year="2020", month="Aug", day="20", volume="22", number="8", pages="e17015", keywords="eHealth", keywords="self-administered drug", keywords="self-management", keywords="medication adherence", keywords="nonhospital settings", keywords="randomized controlled trial", abstract="Background: Electronic health (eHealth) refers to the use of information and communication technologies for health. It plays an increasingly important role in patients' medication management. Objective: To assess evidence on (1) whether eHealth for patients' medication management can improve drug adherence and health outcomes in nonhospital settings and (2) which eHealth functions are commonly used and are effective in improving drug adherence. Methods: We searched for randomized controlled trials (RCTs) on PubMed, MEDLINE, CINAHL, EMBASE, EmCare, ProQuest, Scopus, Web of Science, ScienceDirect, and IEEE Xplore, in addition to other published sources between 2000 and 2018. We evaluated the studies against the primary outcome measure of medication adherence and multiple secondary health care outcome measures relating to adverse events, quality of life, patient satisfaction, and health expenditure. The quality of the studies included was assessed using the Cochrane Collaboration's Risk of Bias (RoB) tool. Results: Our initial search yielded 9909 records, and 24 studies met the selection criteria. Of these, 13 indicated improvement in medication adherence at the significance level of P<.1 and 2 indicated an improved quality of life at the significance level of P<.01. The top 3 functions that were employed included mechanisms to communicate with caregivers, monitoring health features, and reminders and alerts. eHealth functions of providing information and education, and dispensing treatment and administration support tended to favor improved medication adherence outcomes (Fisher exact test, P=.02). There were differences in the characteristics of the study population, intervention design, functionality provided, reporting adherence, and outcome measures among the included studies. RoB assessment items, including blinding of outcome assessment and method for allocation concealment, were not explicitly reported in a large number of studies. Conclusions: All the studies included were designed for patient home-based care application and provided a mechanism to communicate with caregivers. A targeted study population such as older patients should be considered to maximize the public health impact on the self-management of diseases. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42018096627; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=96627 ", doi="10.2196/17015", url="http://www.jmir.org/2020/8/e17015/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663145" } @Article{info:doi/10.2196/19985, author="Kubb, Christian and Foran, M. Heather", title="Online Health Information Seeking by Parents for Their Children: Systematic Review and Agenda for Further Research", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e19985", keywords="information seeking behavior", keywords="parents", keywords="child", keywords="internet", keywords="health behavior", keywords="digital health", abstract="Background: Parents commonly use the internet to search for information about their child's health-related symptoms and guide parental health-related decisions. Despite the impact of parental online health seeking on offline health behaviors, this area of research remains understudied. Previous literature has not adequately distinguished searched behaviors when searching for oneself or one`s child. Objective: The purpose of this review is to examine prevalences and associated variables of parent-child online health information seeking; investigate parents' health-related online behavior regarding how they find, use, and evaluate information; and identify barriers and concerns that they experience during the search. Based on this analysis, we develop a conceptual model of potentially important variables of proxy online health information seeking, with a focus on building an agenda for further research. Methods: We conducted a comprehensive systematic literature review of the PsycINFO, JMIR, and PubMed electronic databases. Studies between January 1994 and June 2018 were considered. The conceptual model was developed using an inductive mixed methods approach based on the investigated variables in the study sample. Results: A total of 33 studies met the inclusion criteria. Findings suggest that parents worldwide are heavy online users of health-related information for their children across highly diverse circumstances. A total of 6 studies found high parental health anxiety, with prevalences ranging from 14\% to 52\%. Although parents reported wishing for more guidance from their pediatrician on how to find reliable information, they rarely discussed retrieved information from the web. The conceptual model of proxy online health information seeking includes 49 variables. Conclusions: This systematic review identifies important gaps regarding the influence of health-related information on parents' health behavior and outcomes. Follow-up studies are required to offer parents guidance on how to use the web for health purposes in an effective way, as well as solutions to the multifaceted problems during or after online health information seeking for their child. The conceptual model with the number of studies in each model category listed highlights how previous studies have hardly considered relational variables between the parent and child. An agenda for future research is presented. ", doi="10.2196/19985", url="http://www.jmir.org/2020/8/e19985/", url="http://www.ncbi.nlm.nih.gov/pubmed/32840484" } @Article{info:doi/10.2196/16388, author="Arias-de la Torre, Jorge and Puigdomenech, Elisa and Garc{\'i}a, Xavier and Valderas, M. Jose and Eiroa-Orosa, Jose Francisco and Fern{\'a}ndez-Villa, Tania and Molina, J. Antonio and Mart{\'i}n, Vicente and Serrano-Blanco, Antoni and Alonso, Jordi and Espallargues, Mireia", title="Relationship Between Depression and the Use of Mobile Technologies and Social Media Among Adolescents: Umbrella Review", journal="J Med Internet Res", year="2020", month="Aug", day="26", volume="22", number="8", pages="e16388", keywords="mobile technologies and social media", keywords="depression", keywords="adolescents", keywords="review", abstract="Background: Despite the relevance of mobile technologies and social media (MTSM) for adolescents, their association with depressive disorders in this population remains unclear. While there are previous reviews that have identified the use of MTSM as a risk factor for developing depression, other reviews have indicated their possible preventive effect. Objective: The aim of this review was to synthesize the current evidence on the association between MTSM use and the development or prevention of depressive disorders in adolescents. Methods: An umbrella review was conducted using information published up to June 2019 from PubMed/MEDLINE, PsycINFO, Web of Science, and The Cochrane Library. Systematic reviews focusing on the adolescent population (up to 20 years old) and depression and its potential relationship with MTSM use were included. Screening of titles, abstracts, and full texts was performed. After selecting the reviews and given the heterogeneity of the outcome variables and exposures, a narrative synthesis of the results was carried out. Results: The search retrieved 338 documents, from which 7 systematic reviews (3 meta-analyses) were selected for data extraction. There were 11-70 studies and 5582-46,015 participants included in the 7 reviews. All reviews included quantitative research, and 2 reviews also included qualitative studies. A statistically significant association between social media and developing depressive symptoms was reported in 2 reviews, while 5 reviews reported mixed results. Conclusions: Excessive social comparison and personal involvement when using MTSM could be associated with the development of depressive symptomatology. Nevertheless, MTSM might promote social support and even become a point of assistance for people with depression. Due to the mixed results, prospective research could be valuable for providing stronger evidence. ", doi="10.2196/16388", url="http://www.jmir.org/2020/8/e16388/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663157" } @Article{info:doi/10.2196/17667, author="Spence, Tommer and Kander, In{\`e}s and Walsh, Julia and Griffiths, Frances and Ross, Jonathan", title="Perceptions and Experiences of Internet-Based Testing for Sexually Transmitted Infections: Systematic Review and Synthesis of Qualitative Research", journal="J Med Internet Res", year="2020", month="Aug", day="26", volume="22", number="8", pages="e17667", keywords="sexually transmitted infections", keywords="self-sampling", keywords="screening", keywords="testing", keywords="internet", keywords="digital health", keywords="eHealth", keywords="qualitative research", keywords="thematic synthesis", abstract="Background: Internet-based testing for sexually transmitted infections (STIs) allows asymptomatic individuals to order a self-sampling kit online and receive their results electronically, reducing the need to attend a clinic unless for treatment. This approach has become increasingly common; however, there is evidence that barriers exist to accessing it, particularly among some high-risk populations. We review the qualitative evidence on this topic, as qualitative research is well-placed to identify the complex influences that relate to accessing testing. Objective: This paper aims to explore perceptions and experiences of internet-based testing for STIs among users and potential users. Methods: Searches were run through 5 electronic databases (CINAHL, EMBASE, MEDLINE, PsycINFO, and Web of Science) to identify peer-reviewed studies published between 2005 and 2018. Search terms were drawn from 4 categories: STIs, testing or screening, digital health, and qualitative methods. Included studies were conducted in high-income countries and explored patient perceptions or experiences of internet-based testing, and data underwent thematic synthesis. Results: A total of 11 studies from the 1735 studies identified in the initial search were included in the review. The synthesis identified that internet-based testing is viewed widely as being acceptable and is preferred over clinic testing by many individuals due to perceived convenience and anonymity. However, a number of studies identified concerns relating to test accuracy and lack of communication with practitioners, particularly when receiving results. There was a lack of consensus on preferred media for results delivery, although convenience and confidentiality were again strong influencing factors. The majority of included studies were limited by the fact that they researched hypothetical services. Conclusions: Internet-based testing providers may benefit from emphasizing this testing's comparative convenience and privacy compared with face-to-face testing in order to improve uptake, as well as alleviating concerns about the self-sampling process. There is a clear need for further research exploring in depth the perceptions and experiences of people who have accessed internet-based testing and for research on internet-based testing that explicitly gathers the views of populations that are at high risk of STIs. Trial Registration: PROSPERO CRD42019146938; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=146938 ", doi="10.2196/17667", url="http://www.jmir.org/2020/8/e17667/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663151" } @Article{info:doi/10.2196/19950, author="Drissi, Nidal and Ouhbi, Sofia and Janati Idrissi, Abdou Mohammed and Fernandez-Luque, Luis and Ghogho, Mounir", title="Connected Mental Health: Systematic Mapping Study", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e19950", keywords="mental health", keywords="connected health", keywords="eHealth", keywords="mobile health", keywords="telehealth", keywords="mHealth", keywords="mobile phone", keywords="health informatics", keywords="review", keywords="interdisciplinary research", keywords="information technology", keywords="information systems", abstract="Background: Although mental health issues constitute an increasing global burden affecting a large number of people, the mental health care industry is still facing several care delivery barriers such as stigma, education, and cost. Connected mental health (CMH), which refers to the use of information and communication technologies in mental health care, can assist in overcoming these barriers. Objective: The aim of this systematic mapping study is to provide an overview and a structured understanding of CMH literature available in the Scopus database. Methods: A total of 289 selected publications were analyzed based on 8 classification criteria: publication year, publication source, research type, contribution type, empirical type, mental health issues, targeted cohort groups, and countries where the empirically evaluated studies were conducted. Results: The results showed that there was an increasing interest in CMH publications; journals were the main publication channels of the selected papers; exploratory research was the dominant research type; advantages and challenges of the use of technology for mental health care were the most investigated subjects; most of the selected studies had not been evaluated empirically; depression and anxiety were the most addressed mental disorders; young people were the most targeted cohort groups in the selected publications; and Australia, followed by the United States, was the country where most empirically evaluated studies were conducted. Conclusions: CMH is a promising research field to present novel approaches to assist in the management, treatment, and diagnosis of mental health issues that can help overcome existing mental health care delivery barriers. Future research should be shifted toward providing evidence-based studies to examine the effectiveness of CMH solutions and identify related issues. ", doi="10.2196/19950", url="http://www.jmir.org/2020/8/e19950/", url="http://www.ncbi.nlm.nih.gov/pubmed/32857055" } @Article{info:doi/10.2196/16437, author="Dening, Jedha and Islam, Shariful Sheikh Mohammed and George, Elena and Maddison, Ralph", title="Web-Based Interventions for Dietary Behavior in Adults With Type 2 Diabetes: Systematic Review of Randomized Controlled Trials", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e16437", keywords="type 2 diabetes", keywords="dietary behavior", keywords="diet", keywords="glycemic control", keywords="self-management", keywords="eHealth", keywords="web-based", keywords="HbA1c", abstract="Background: Type 2 diabetes mellitus (T2DM) is among the most prevalent noncommunicable health conditions worldwide, affecting over 500 million people globally. Diet is a key aspect of T2DM management with dietary modification shown to elicit clinically meaningful outcomes such as improved glycemic control, and reductions in weight and cardiovascular disease risk factors. Web-based interventions provide a potentially convenient and accessible method for delivering dietary education, but its effects on dietary behavior in people with T2DM are unknown. Objective: The objective of this review was to determine the effectiveness of web-based interventions on dietary behavior change and glycemic control in people with T2DM. Methods: Per PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, systematic literature searches were performed using Medline, Embase, The Cochrane Library, and CINAHL to retrieve papers from January 2013 to May 2019. Randomized controlled trials of web-based interventions in adults with T2DM with reported dietary assessment were included. Population and intervention characteristics, dietary guidelines and assessments, and significant clinical outcomes were extracted. Differences between groups and within groups were assessed for dietary behavior and clinical outcomes. Results: There were 714 records screened, and five studies comprising 1056 adults were included. Studies measured dietary changes by assessing overall diet quality, changes in specific dietary components, or dietary knowledge scores. Significant improvements in dietary behavior were reported in four out of the five studies, representing healthier food choices, improvements in eating habits, reductions in carbohydrates, added sugar, sodium, saturated fat and overall fat intake, and/or increases in dietary knowledge. Three studies found significant mean reductions for hemoglobin A1c ranging from --0.3\% to --0.8\%, and/or weight ranging from --2.3 kg to --12.7 kg, fasting blood glucose (--1 mmol/L), waist circumference (--1 cm), and triglycerides (--60.1 mg/dL). These studies provided varied dietary recommendations from standard dietary guidelines, national health program guidelines, and a very low carbohydrate ketogenic diet. Conclusions: This review provided evidence that web-based interventions may be an effective way to support dietary behavior change in people with T2DM, potentially leading to changes in glycemic control and other clinical outcomes. However, the evidence should be viewed as preliminary as there were only five studies included with considerable heterogeneity in terms of the diets recommended, the dietary assessment measures used, the complexity of the interventions, and the modes and methods of delivery. ", doi="10.2196/16437", url="http://www.jmir.org/2020/8/e16437/", url="http://www.ncbi.nlm.nih.gov/pubmed/32857059" } @Article{info:doi/10.2196/17790, author="Sequi-Dominguez, Irene and Alvarez-Bueno, Celia and Martinez-Vizcaino, Vicente and Fernandez-Rodriguez, Rub{\'e}n and del Saz Lara, Alicia and Cavero-Redondo, Iv{\'a}n", title="Effectiveness of Mobile Health Interventions Promoting Physical Activity and Lifestyle Interventions to Reduce Cardiovascular Risk Among Individuals With Metabolic Syndrome: Systematic Review and Meta-Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="31", volume="22", number="8", pages="e17790", keywords="mobile health", keywords="mobile technology", keywords="telemedicine", keywords="metabolic syndrome", keywords="physical activity", keywords="lifestyle intervention", keywords="systematic review", keywords="meta-analysis", abstract="Background: Physical activity and lifestyle interventions, such as a healthy diet, have been proven to be effective approaches to manage metabolic syndrome. However, these interventions require great commitment from patients and clinicians owing to their economic costs, time consumption, and lack of immediate results. Objective: The aim of this systematic review and meta-analysis was to analyze the effect of mobile-based health interventions for reducing cardiometabolic risk through the promotion of physical activity and healthy lifestyle behaviors. Methods: PubMed, Scopus, Web of Science, Cochrane Central Register of Controlled Trials, and SPORTdiscus databases were searched for experimental studies evaluating cardiometabolic risk indicators among individuals with metabolic syndrome who were included in technology-assisted physical activity and lifestyle interventions. Effect sizes, pooled mean changes, and their respective 95\% CIs were calculated using the DerSimonian and Laird method. Outcomes included the following clinical and biochemical parameters: body composition (waist circumference [WC] and BMI), blood pressure (systolic blood pressure [SBP] and diastolic blood pressure [DBP]), glucose tolerance (fasting plasma glucose [FPG] and glycated hemoglobin A1c [HbA1c]), and lipid profile (total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol [HDL-C], and triglycerides). Results: A total of nine studies were included in the meta-analysis. Owing to the scarcity of studies, only pooled mean pre-post changes in the intervention groups were estimated. Significant mean changes were observed for BMI (?1.70 kg/m2, 95\% CI ?3.20 to ?0.20; effect size: ?0.46; P=.03), WC (?5.77 cm, 95\% CI ?9.76 to ?1.77; effect size: ?0.54; P=.005), SBP (?7.33 mmHg, 95\% CI ?13.25 to ?1.42; effect size: ?0.43; P=.02), DBP (?3.90 mmHg, 95\% CI ?7.70 to ?0.11; effect size: ?0.44; P=.04), FPG (?3.65 mg/dL, 95\% CI ?4.79 to ?2.51; effect size: ?0.39; P<.001), and HDL-C (4.19 mg/dL, 95\% CI 2.43-5.95; effect size: 0.23; P<.001). Conclusions: Overall, mobile-based health interventions aimed at promoting physical activity and healthy lifestyle changes had a strong positive effect on cardiometabolic risk indicators among individuals with metabolic syndrome. Nevertheless, further research is required to compare this approach with usual care in order to support the incorporation of these technologies in health systems. Trial Registration: PROSPERO CRD42019125461; https://tinyurl.com/y3t4wog4. ", doi="10.2196/17790", url="http://www.jmir.org/2020/8/e17790/", url="http://www.ncbi.nlm.nih.gov/pubmed/32865503" } @Article{info:doi/10.2196/18100, author="Etzelmueller, Anne and Vis, Christiaan and Karyotaki, Eirini and Baumeister, Harald and Titov, Nickolai and Berking, Matthias and Cuijpers, Pim and Riper, Heleen and Ebert, Daniel David", title="Effects of Internet-Based Cognitive Behavioral Therapy in Routine Care for Adults in Treatment for Depression and Anxiety: Systematic Review and Meta-Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="31", volume="22", number="8", pages="e18100", keywords="internet-based interventions", keywords="depression", keywords="anxiety", keywords="effectiveness", keywords="acceptability", keywords="routine care", abstract="Background: Although there is evidence for the efficacy of internet-based cognitive behavioral therapy (iCBT), the generalizability of results to routine care is limited. Objective: This study systematically reviews effectiveness studies of guided iCBT interventions for the treatment of depression or anxiety. Methods: The acceptability (uptake, participants' characteristics, adherence, and satisfaction), effectiveness, and negative effects (deterioration) of nonrandomized pre-post designs conducted under routine care conditions were synthesized using systematic review and meta-analytic approaches. Results: A total of 19 studies including 30 groups were included in the analysis. Despite high heterogeneity, individual effect sizes of investigated studies indicate clinically relevant changes, with effect sizes ranging from Hedges' g=0.42-1.88, with a pooled effect of 1.78 for depression and 0.94 for anxiety studies. Uptake, participants' characteristics, adherence, and satisfaction indicate a moderate to high acceptability of the interventions. The average deterioration across studies was 2.9\%. Conclusions: This study provides evidence supporting the acceptability and effectiveness of guided iCBT for the treatment of depression and anxiety in routine care. Given the high heterogeneity between interventions and contexts, health care providers should select interventions that have been proven in randomized controlled clinical trials. The successful application of iCBT may be an effective way of increasing health care in multiple contexts. ", doi="10.2196/18100", url="http://www.jmir.org/2020/8/e18100/", url="http://www.ncbi.nlm.nih.gov/pubmed/32865497" } @Article{info:doi/10.2196/19311, author="Morley, Jessica and Cowls, Josh and Taddeo, Mariarosaria and Floridi, Luciano", title="Public Health in the Information Age: Recognizing the Infosphere as a Social Determinant of Health", journal="J Med Internet Res", year="2020", month="Aug", day="3", volume="22", number="8", pages="e19311", keywords="COVID-19", keywords="public health", keywords="misinformation", keywords="disinformation", keywords="infodemic", keywords="infodemiology", keywords="infosphere", keywords="social determinants of health", keywords="information ethics", doi="10.2196/19311", url="https://www.jmir.org/2020/8/e19311", url="http://www.ncbi.nlm.nih.gov/pubmed/32648850" } @Article{info:doi/10.2196/18044, author="Cahan, M. Eli and Khatri, Purvesh", title="Data Heterogeneity: The Enzyme to Catalyze Translational Bioinformatics?", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e18044", keywords="medical Informatics", keywords="health equity", keywords="health care disparities", keywords="population health", keywords="quality improvement", keywords="precision medicine", doi="10.2196/18044", url="https://www.jmir.org/2020/8/e18044", url="http://www.ncbi.nlm.nih.gov/pubmed/32784182" } @Article{info:doi/10.2196/20169, author="Cresswell, Kathrin and Ramalingam, Sandeep and Sheikh, Aziz", title="Can Robots Improve Testing Capacity for SARS-CoV-2?", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e20169", keywords="robotics", keywords="testing", keywords="SARS-CoV-2", keywords="COVID-19", keywords="pandemic", keywords="virus", keywords="infectious disease", doi="10.2196/20169", url="http://www.jmir.org/2020/8/e20169/", url="http://www.ncbi.nlm.nih.gov/pubmed/32735547" } @Article{info:doi/10.2196/18183, author="Saleh, Shadi and El Arnaout, Nour and Abdouni, Lina and Jammoul, Zeinab and Hachach, Noha and Dasgupta, Amlan", title="Sijilli: A Scalable Model of Cloud-Based Electronic Health Records for Migrating Populations in Low-Resource Settings", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e18183", keywords="eHealth", keywords="digital health", keywords="innovation", keywords="refugees", keywords="low- and middle-income countries", keywords="technology", doi="10.2196/18183", url="http://www.jmir.org/2020/8/e18183/", url="http://www.ncbi.nlm.nih.gov/pubmed/32788145" } @Article{info:doi/10.2196/20368, author="Schaub, Patrick Michael and Berman, H. Anne and L{\'o}pez Pelayo, Hugo and Boumparis, Nikolaos and Khadjesari, Zarnie and Blankers, Matthijs and Gual, Antoni and Riper, Heleen and Pas, Lodewijk", title="e-INEBRIA Special Interest Group Roadmap for Best Practices for Research on Brief Digital Interventions for Problematic Alcohol and Illicit Drug Use", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e20368", keywords="brief interventions", keywords="mobile applications", keywords="good practice", keywords="implementation research", keywords="quality assurance", doi="10.2196/20368", url="http://www.jmir.org/2020/8/e20368/", url="http://www.ncbi.nlm.nih.gov/pubmed/32586786" } @Article{info:doi/10.2196/19918, author="Lee, Joon", title="Is Artificial Intelligence Better Than Human Clinicians in Predicting Patient Outcomes?", journal="J Med Internet Res", year="2020", month="Aug", day="26", volume="22", number="8", pages="e19918", keywords="patient outcome prediction", keywords="artificial intelligence", keywords="machine learning", keywords="human-generated predictions", keywords="human-AI symbiosis", doi="10.2196/19918", url="http://www.jmir.org/2020/8/e19918/", url="http://www.ncbi.nlm.nih.gov/pubmed/32845249" } @Article{info:doi/10.2196/18150, author="Kardas, Przemyslaw and Aguilar-Palacio, Isabel and Almada, Marta and Cahir, Caitriona and Costa, Elisio and Giardini, Anna and Malo, Sara and Massot Mesquida, Mireia and Menditto, Enrica and Mid{\~a}o, Lu{\'i}s and Parra-Calder{\'o}n, Luis Carlos and Pepiol Salom, Enrique and Vrijens, Bernard", title="The Need to Develop Standard Measures of Patient Adherence for Big Data: Viewpoint", journal="J Med Internet Res", year="2020", month="Aug", day="27", volume="22", number="8", pages="e18150", keywords="patient adherence", keywords="big data", keywords="metrics", keywords="consensus", doi="10.2196/18150", url="http://www.jmir.org/2020/8/e18150/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663138" } @Article{info:doi/10.2196/22417, author="Nemetz, Anne Elisheva Tamar and Urbach, Robert David and Devon, Michelle Karen", title="The Art of Surgery: Balancing Compassionate With Virtual Care", journal="J Med Internet Res", year="2020", month="Aug", day="27", volume="22", number="8", pages="e22417", keywords="bioethics", keywords="medical ethics", keywords="virtual care", keywords="telehealth", keywords="virtual care in surgery", keywords="video care in surgery", keywords="telehealth in surgery", keywords="surgical communication", keywords="COVID-19 and virtual care", keywords="consent", keywords="privacy", keywords="medical education", keywords="surgery", doi="10.2196/22417", url="http://www.jmir.org/2020/8/e22417/", url="http://www.ncbi.nlm.nih.gov/pubmed/32852276" } @Article{info:doi/10.2196/21345, author="Bendtsen, Marcus", title="The P Value Line Dance: When Does the Music Stop?", journal="J Med Internet Res", year="2020", month="Aug", day="27", volume="22", number="8", pages="e21345", keywords="sample size", keywords="randomized controlled trial", keywords="Bayesian analysis", keywords="P value", keywords="dichotomization", keywords="dichotomy", keywords="error", keywords="uncertainty", doi="10.2196/21345", url="http://www.jmir.org/2020/8/e21345/", url="http://www.ncbi.nlm.nih.gov/pubmed/32852275" } @Article{info:doi/10.2196/18109, author="Jimenez, Geronimo and Tyagi, Shilpa and Osman, Tarig and Spinazze, Pier and van der Kleij, Rianne and Chavannes, H. Niels and Car, Josip", title="Improving the Primary Care Consultation for Diabetes and Depression Through Digital Medical Interview Assistant Systems: Narrative Review", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e18109", keywords="digital medical interview assistant, computer-assisted history taking", keywords="primary care", keywords="chronic conditions", abstract="Background: Digital medical interview assistant (DMIA) systems, also known as computer-assisted history taking (CAHT) systems, have the potential to improve the quality of care and the medical consultation by exploring more patient-related aspects without time constraints and, therefore, acquiring more and better-quality information prior to the face-to-face consultation. The consultation in primary care is the broadest in terms of the amount of topics to be covered and, at the same time, the shortest in terms of time spent with the patient. Objective: Our aim is to explore how DMIA systems may be used specifically in the context of primary care, to improve the consultations for diabetes and depression, as exemplars of chronic conditions. Methods: A narrative review was conducted focusing on (1) the characteristics of the primary care consultation in general, and for diabetes and depression specifically, and (2) the impact of DMIA and CAHT systems on the medical consultation. Through thematic analysis, we identified the characteristics of the primary care consultation that a DMIA system would be able to improve. Based on the identified primary care consultation tasks and the potential benefits of DMIA systems, we developed a sample questionnaire for diabetes and depression to illustrate how such a system may work. Results: A DMIA system, prior to the first consultation, could aid in the essential primary care tasks of case finding and screening, diagnosing, and, if needed, timely referral to specialists or urgent care. Similarly, for follow-up consultations, this system could aid with the control and monitoring of these conditions, help check for additional health issues, and update the primary care provider about visits to other providers or further testing. Successfully implementing a DMIA system for these tasks would improve the quality of the data obtained, which means earlier diagnosis and treatment. Such a system would improve the use of face-to-face consultation time, thereby streamlining the interaction and allowing the focus to be the patient's needs, which ultimately would lead to better health outcomes and patient satisfaction. However, for such a system to be successfully incorporated, there are important considerations to be taken into account, such as the language to be used and the challenges for implementing eHealth innovations in primary care and health care in general. Conclusions: Given the benefits explored here, we foresee that DMIA systems could have an important impact in the primary care consultation for diabetes and depression and, potentially, for other chronic conditions. Earlier case finding and a more accurate diagnosis, due to more and better-quality data, paired with improved monitoring of disease progress should improve the quality of care and keep the management of chronic conditions at the primary care level. A somewhat simple, easily scalable technology could go a long way to improve the health of the millions of people affected with chronic conditions, especially if working in conjunction with already-established health technologies such as electronic medical records and clinical decision support systems. ", doi="10.2196/18109", url="http://www.jmir.org/2020/8/e18109/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663144" } @Article{info:doi/10.2196/21609, author="Quinn, M. Lauren and Davies, J. Melanie and Hadjiconstantinou, Michelle", title="Virtual Consultations and the Role of Technology During the COVID-19 Pandemic for People With Type 2 Diabetes: The UK Perspective", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e21609", keywords="diabetes", keywords="virtual clinic", keywords="technology", keywords="COVID-19", keywords="United Kingdom", keywords="pandemic", keywords="feasibility", keywords="effective", keywords="telehealth", doi="10.2196/21609", url="http://www.jmir.org/2020/8/e21609/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716898" } @Article{info:doi/10.2196/16725, author="Lopez, Cristina and Gilmore, K. Amanda and Moreland, Angela and Danielson, Kmett Carla and Acierno, Ron", title="Meeting Kids Where They Are At--A Substance Use and Sexual Risk Prevention Program via Telemedicine for African American Girls: Usability and Acceptability Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e16725", keywords="adolescents", keywords="substance use", keywords="sexual risk reduction", keywords="telehealth", keywords="prevention programs", keywords="mobile phone", abstract="Background: Rural African American youth lack access to drug and sexual risk--taking prevention programs available in more urban areas. Recent data indicate that rural youth now use substances at higher rates and at younger ages than their urban peers. Objective: This study aims to evaluate the initial usability and acceptability of a low-cost, technology-based approach to delivering effective, culturally tailored, integrated substance use disorder (SUD) and HIV risk behavior prevention programs to African American female youth to inform the use of this intervention via telemedicine for rural youth. Methods: Effective SUD prevention strategies and emotion regulation skills were integrated into an existing evidence-based HIV risk reduction program culturally tailored for African American female adolescents---Sisters Informing, Healing, Living, and Empowering (SIHLE)---and delivered to 39 African American female youth via group telehealth. The evaluation of the resulting program, 12-session SIHLEplus, was completed by 27 girls who also completed self-report measures that assessed sexual risk behaviors (eg, number of partners and age of sex initiation), substance use, exposure to traumatic events, and emotion regulation. Results: The descriptive and qualitative results of the pilot study demonstrate the initial usability and acceptability of delivering evidence-based prevention successfully via telehealth to help address health disparities in this vulnerable population. Conclusions: Although more research is needed, the findings from this study suggest that SIHLEplus has demonstrated initial usability and acceptability. ", doi="10.2196/16725", url="http://www.jmir.org/2020/8/e16725/", url="http://www.ncbi.nlm.nih.gov/pubmed/32780022" } @Article{info:doi/10.2196/17593, author="Goetz, Maren and Schiele, Claudia and M{\"u}ller, Mitho and Matthies, M. Lina and Deutsch, M. Thomas and Spano, Claudio and Graf, Johanna and Zipfel, Stephan and Bauer, Armin and Brucker, Y. Sara and Wallwiener, Markus and Wallwiener, Stephanie", title="Effects of a Brief Electronic Mindfulness-Based Intervention on Relieving Prenatal Depression and Anxiety in Hospitalized High-Risk Pregnant Women: Exploratory Pilot Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17593", keywords="pregnancy", keywords="high-risk pregnancy", keywords="hospitalization", keywords="preterm labor", keywords="anxiety", keywords="depression", keywords="psychological stress", keywords="mindfulness", keywords="stress reduction", keywords="mobile app", abstract="Background: Peripartum depression and anxiety disorders are highly prevalent and are correlated with adverse maternal and neonatal outcomes. Antenatal care in Germany does not yet include structured screening and effective low-threshold treatment options for women facing peripartum depression and anxiety disorders. Mindfulness-based interventions (MBIs) are increasingly becoming a focus of interest for the management of such patients. Studies have shown a decrease in pregnancy-related stress and anxiety in expectant mothers following mindfulness programs. Objective: The aim of this study was to explore the clinical effectiveness of a 1-week electronic course of mindfulness on prenatal depression and anxiety in hospitalized, high-risk pregnant women. We hypothesized that participating in a 1-week electronic MBI (eMBI) could alleviate symptoms of depression and anxiety during the hospital stay. Methods: A prospective pilot study with an explorative study design was conducted from January to May 2019 in a sample of 68 women hospitalized due to high-risk pregnancies. After enrolling into the study, the participants were given access to an eMBI app on how to deal with stress, anxiety, and symptoms of depression. Psychometric parameters were assessed via electronic questionnaires comprising the Edinburgh Postnatal Depression Scale (EPDS), State-Trait Anxiety Inventory (STAI-S), and abridged version of the Pregnancy-Related Anxiety Questionnaire (PRAQ-R). Results: We observed a high prevalence of peripartum depression and anxiety among hospitalized high-risk pregnant women: 39\% (26/67) of the study participants in the first assessment and 41\% (16/39) of the participants in the second assessment achieved EPDS scores above the cutoff value for minor/major depression. The number of participants with anxiety levels above the cutoff value (66\% [45/68] of the participants in the first assessment and 67\% [26/39] of the participants in the second assessment) was significantly more than that of the participants with anxiety levels below the cutoff value, as measured with the STAI-S. After completing the 1-week electronic course on mindfulness, the participants showed a significant reduction in the mean state anxiety levels (P<.03). Regarding pregnancy-related anxiety, participants who completed more than 50\% of the 1-week course showed lower scores in PRAQ-R in the second assessment (P<.05). No significant changes in the EPDS scores were found after completing the intervention. Conclusions: Peripartum anxiety and depression represent a relevant health issue in hospitalized pregnant patients. Short-term eMBIs could have the potential to reduce anxiety levels and pregnancy-related anxiety. However, we observed that compliance to eMBI seems to be related to lower symptoms of pregnancy-related stress among high-risk patients. eMBIs represent accessible mental health resources at reduced costs and can be adapted for hospitalized patients during pregnancy. ", doi="10.2196/17593", url="https://www.jmir.org/2020/8/e17593", url="http://www.ncbi.nlm.nih.gov/pubmed/32780023" } @Article{info:doi/10.2196/19882, author="Buis, R. Lorraine and Roberson, N. Dana and Kadri, Reema and Rockey, G. Nicole and Plegue, A. Melissa and Danak, U. Shivang and Guetterman, C. Timothy and Johnson, G. Melanie and Choe, Mi Hae and Richardson, R. Caroline", title="Understanding the Feasibility, Acceptability, and Efficacy of a Clinical Pharmacist-led Mobile Approach (BPTrack) to Hypertension Management: Mixed Methods Pilot Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e19882", keywords="cell phone", keywords="mobile phone", keywords="hypertension", keywords="blood pressure", keywords="medication adherence", keywords="telemedicine", keywords="pharmacists", abstract="Background: Hypertension is a prevalent and costly burden in the United States. Clinical pharmacists within care teams provide effective management of hypertension, as does home blood pressure monitoring; however, concerns about data quality and latency are widespread. One approach to close the gap between clinical pharmacist intervention and home blood pressure monitoring is the use of mobile health (mHealth) technology. Objective: We sought to investigate the feasibility, acceptability, and preliminary effectiveness of BPTrack, a clinical pharmacist-led intervention that incorporates patient- and clinician-facing apps to make electronically collected, patient-generated data available to providers in real time for hypertension management. The patient app also included customizable daily medication reminders and educational messages. Additionally, this study sought to understand barriers to adoption and areas for improvement identified by key stakeholders, so more widespread use of such interventions may be achieved. Methods: We conducted a mixed methods pilot study of BPTrack, to improve blood pressure control in patients with uncontrolled hypertension through a 12-week pre-post intervention. All patients were recruited from a primary care setting where they worked with a clinical pharmacist for hypertension management. Participants completed a baseline visit, then spent 12 weeks utilizing BPTrack before returning to the clinic for follow-up. Collected data from patient participants included surveys pre- and postintervention, clinical measures (for establishing effectiveness, with the primary outcome being a change in blood pressure and the secondary outcome being a change in medication adherence), utilization of the BPTrack app, interviews at follow-up, and chart review. We also conducted interviews with key stakeholders. Results: A total of 15 patient participants were included (13 remained through follow-up for an 86.7\% retention rate) in a single group, pre-post assessment pilot study. Data supported the hypothesis that BPTrack was feasible and acceptable for use by patient and provider participants and was effective at reducing patient blood pressure. At the 12-week follow-up, patients exhibited significant reductions in both systolic blood pressure (baseline mean 137.3 mm Hg, SD 11.1 mm Hg; follow-up mean 131.0 mm Hg, SD 9.9 mm Hg; P=.02) and diastolic blood pressure (baseline mean 89.4 mm Hg, SD 7.7 mm Hg; follow-up mean 82.5 mm Hg, SD 8.2 mm Hg; P<.001). On average, patients uploaded at least one blood pressure measurement on 75\% (SD 25\%) of study days. No improvements in medication adherence were noted. Interview data revealed areas of improvement and refinement for the patient experience. Furthermore, stakeholders require integration into the electronic health record and a modified clinical workflow for BPTrack to be truly useful; however, both patients and stakeholders perceived benefits of BPTrack when used within the context of a clinical relationship. Conclusions: Results demonstrate that a pharmacist-led mHealth intervention promoting home blood pressure monitoring and clinical pharmacist management of hypertension can be effective at reducing blood pressure in primary care patients with uncontrolled hypertension. Our data also support the feasibility and acceptability of these types of interventions for patients and providers. Trial Registration: ClinicalTrials.gov NCT02898584; https://clinicaltrials.gov/ct2/show/NCT02898584 International Registered Report Identifier (IRRID): RR2-10.2196/resprot.8059 ", doi="10.2196/19882", url="https://www.jmir.org/2020/8/e19882", url="http://www.ncbi.nlm.nih.gov/pubmed/32780026" } @Article{info:doi/10.2196/17768, author="Anderson, Emma and Parslow, Roxanne and Hollingworth, William and Mills, Nicola and Beasant, Lucy and Gaunt, Daisy and Metcalfe, Chris and Kessler, David and Macleod, John and Pywell, Susan and Pitts, Kieren and Price, Simon and Stallard, Paul and Knoop, Hans and Van de Putte, Elise and Nijhof, Sanne and Bleijenberg, Gijs and Crawley, Esther", title="Recruiting Adolescents With Chronic Fatigue Syndrome/Myalgic Encephalomyelitis to Internet-Delivered Therapy: Internal Pilot Within a Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e17768", keywords="pediatrics", keywords="chronic fatigue syndrome", keywords="myalgic encephalomyelitis", keywords="cognitive behavioral therapy", keywords="eHealth", keywords="online systems", keywords="e-therapy", keywords="e-counseling", keywords="pilot projects", keywords="qualitative research", abstract="Background: Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) in adolescents is common and disabling. Teenagers in the United Kingdom are more likely to recover if they access specialist care, but most do not have access to a local specialist CFS/ME service. Delivering treatment remotely via the internet could improve access to treatment. Objective: This study aims to assess (1) the feasibility of recruitment and retention into a trial of internet-delivered specialist treatment for adolescents with CFS/ME and (2) the acceptability of trial processes and 2 web-based treatments (to inform continuation to full trial). Methods: This study is an internal pilot for the initial 12 months of a full randomized controlled trial (RCT), with integrated qualitative methods (analysis of recruitment consultations and participant and clinician interviews). Recruitment and treatment were delivered remotely from a specialist pediatric CFS/ME treatment service within a hospital in South West United Kingdom. Adolescents (aged 11-17 years) from across the United Kingdom with a diagnosis of CFS/ME and no access to local specialist treatment were referred by their general practitioner to the treatment center. Eligibility assessment and recruitment were conducted via remote methods (telephone and on the web), and participants were randomized (via a computer-automated system) to 1 of 2 web-based treatments. The trial intervention was Fatigue in Teenagers on the InterNET in the National Health Service, a web-based modular CFS/ME-specific cognitive behavioral therapy program (designed to be used by young people and their parents or caregivers) supported by individualized clinical psychologist electronic consultations (regular, scheduled therapeutic message exchanges between participants and therapist within the platform). The comparator was Skype-delivered activity management with a CFS/ME clinician (mainly a physiotherapist or occupational therapist). Both treatments were intended to last for up to 6 months. The primary outcomes were (1) the number of participants recruited (per out-of-area referrals received between November 1, 2016, to October 31, 2017) and the proportion providing 6-month outcome data (web-based self-report questionnaire assessing functioning) and (2) the qualitative outcomes indicating the acceptability of trial processes and treatments. Results: A total of 89 out of 150 (59.3\% of potentially eligible referrals) young people and their parents or caregivers were recruited, with 75 out of 89 (84.2\%) providing 6-month outcome data. Overall, web-based treatment was acceptable; however, participants and clinicians described both the advantages and disadvantages of remote methods. No serious adverse events were reported. Conclusions: Recruiting young people (and their parents or caregivers) into an RCT of web-based treatment via remote methods is feasible and acceptable. Delivering specialist treatment at home via the internet is feasible and acceptable, although some families prefer to travel across the United Kingdom for face-to-face treatment. Trial Registration: ISRCTN 18020851; http://www.isrctn.com/ISRCTN18020851 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-018-2500-3 ", doi="10.2196/17768", url="https://www.jmir.org/2020/8/e17768", url="http://www.ncbi.nlm.nih.gov/pubmed/32784188" } @Article{info:doi/10.2196/17834, author="Wiecek, Elyssa and Torres-Robles, Andrea and Cutler, Louise Rachelle and Benrimoj, Isaac Shalom and Garcia-Cardenas, Victoria", title="Impact of a Multicomponent Digital Therapeutic Mobile App on Medication Adherence in Patients with Chronic Conditions: Retrospective Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e17834", keywords="medication adherence", keywords="medication compliance", keywords="mobile phone", keywords="mobile apps", keywords="mHealth", keywords="gamification", abstract="Background: Strategies to improve medication adherence are widespread in the literature; however, their impact is limited in real practice. Few patients persistently engage long-term to improve health outcomes, even when they are aware of the consequences of poor adherence. Despite the potential of mobile phone apps as a tool to manage medication adherence, there is still limited evidence of the impact of these innovative interventions. Real-world evidence can assist in minimizing this evidence gap. Objective: The objective of this study was to analyze the impact over time of a previously implemented digital therapeutic mobile app on medication adherence rates in adults with any chronic condition. Methods: A retrospective observational study was performed to assess the adherence rates of patients with any chronic condition using Perx Health, a digital therapeutic that uses multiple components within a mobile health app to improve medication adherence. These components include gamification, dosage reminders, incentives, educational components, and social community components. Adherence was measured through mobile direct observation of therapy (MDOT) over 3-month and 6-month time periods. Implementation adherence, defined as the percentage of doses in which the correct dose of a medication was taken, was assessed across the study periods, in addition to timing adherence or percentage of doses taken at the appropriate time ({\textpm}1 hour). The Friedman test was used to compare differences in adherence rates over time. Results: We analyzed 243 and 130 patients who used the app for 3 months and 6 months, respectively. The average age of the 243 patients was 43.8 years (SD 15.5), and 156 (64.2\%) were female. The most common medications prescribed were varenicline, rosuvastatin, and cholecalciferol. The median implementation adherence was 96.6\% (IQR 82.1\%-100\%) over 3 months and 96.8\% (IQR 87.1\%-100\%) over 6 months. Nonsignificant differences in adherence rates over time were observed in the 6-month analysis (Fr(2)=4.314, P=.505) and 3-month analysis (Fr(2)=0.635, P=.728). Similarly, the timing adherence analysis revealed stable trends with no significant changes over time. Conclusions: Retrospective analysis of users of a medication adherence management mobile app revealed a positive trend in maintaining optimal medication adherence over time. Mobile technology utilizing gamification, dosage reminders, incentives, education, and social community interventions appears to be a promising strategy to manage medication adherence in real practice. ", doi="10.2196/17834", url="http://www.jmir.org/2020/8/e17834/", url="http://www.ncbi.nlm.nih.gov/pubmed/32784183" } @Article{info:doi/10.2196/17155, author="Alvarez-Jimenez, Mario and Rice, Simon and D'Alfonso, Simon and Leicester, Steven and Bendall, Sarah and Pryor, Ingrid and Russon, Penni and McEnery, Carla and Santesteban-Echarri, Olga and Da Costa, Gustavo and Gilbertson, Tamsyn and Valentine, Lee and Solves, Laia and Ratheesh, Aswin and McGorry, D. Patrick and Gleeson, John", title="A Novel Multimodal Digital Service (Moderated Online Social Therapy+) for Help-Seeking Young People Experiencing Mental Ill-Health: Pilot Evaluation Within a National Youth E-Mental Health Service", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e17155", keywords="mHealth", keywords="youth", keywords="social media", keywords="social networking", keywords="mobile phone", keywords="internet-based intervention", abstract="Background: Mental ill-health is the leading cause of disability worldwide. Moreover, 75\% of mental health conditions emerge between the ages of 12 and 25 years. Unfortunately, due to lack of resources and limited engagement with services, a majority of young people affected by mental ill-health do not access evidence-based support. To address this gap, our team has developed a multimodal, scalable digital mental health service (Enhanced Moderated Online Social Therapy [MOST+]) merging real-time, clinician-delivered web chat counseling; interactive user-directed online therapy; expert and peer moderation; and peer-to-peer social networking. Objective: The primary aim of this study is to ascertain the feasibility, acceptability, and safety of MOST+. The secondary aims are to assess pre-post changes in clinical, psychosocial, and well-being outcomes and to explore the correlations between system use, perceived helpfulness, and secondary outcome variables. Methods: Overall, 157 young people seeking help from a national youth e-mental health service were recruited over 5 weeks. MOST+ was active for 9 weeks. All participants had access to interactive online therapy and integrated web chat counseling. Additional access to peer-to-peer social networking was granted to 73 participants (46.5\%) for whom it was deemed safe. The intervention was evaluated via an uncontrolled single-group study. Results: Overall, 93 participants completed the follow-up assessment. Most participants had moderate (52/157, 33\%) to severe (96/157, 61\%) mental health conditions. All a priori feasibility, acceptability, and safety criteria were met. Participants provided mean scores of ?3.5 (out of 5) on ease of use (mean 3.7, SD 1.1), relevancy (mean 3.9, SD 1.0), helpfulness (mean 3.5, SD 0.9), and overall experience (mean 3.9, SD 0.8). Moreover, 98\% (91/93) of participants reported a positive experience using MOST+, 82\% (70/93) reported that using MOST+ helped them feel better, 86\% (76/93) felt more socially connected using it, and 92\% (86/93) said they would recommend it to others. No serious adverse events or inappropriate use were detected, and 97\% (90/93) of participants reported feeling safe. There were statistically significant improvements in 8 of the 11 secondary outcomes assessed: psychological distress (d=?0.39; P<.001), perceived stress (d=?0.44; P<.001), psychological well-being (d=0.51; P<.001), depression (d=?0.29; P<.001), loneliness (d=?0.23; P=.04), social support (d=0.30; P<.001), autonomy (d=0.36; P=.001), and self-competence (d=0.30; P<.001). There were significant correlations between system use, perceived helpfulness, and a number of secondary outcome variables. Conclusions: MOST+ is a feasible, acceptable, and safe online clinical service for young people with mental ill-health. The high level of perceived helpfulness, the significant improvements in secondary outcomes, and the correlations between indicators of system use and secondary outcome variables provide initial support for the therapeutic potential of MOST+. MOST+ is a promising and scalable platform to deliver standalone e-mental health services as well as enhance the growing international network of face-to-face youth mental health services. ", doi="10.2196/17155", url="https://www.jmir.org/2020/8/e17155", url="http://www.ncbi.nlm.nih.gov/pubmed/32788151" } @Article{info:doi/10.2196/19861, author="Eaton, Cyd and Comer, Margaret and Pruette, Cozumel and Psoter, Kevin and Riekert, Kristin", title="Text Messaging Adherence Intervention for Adolescents and Young Adults with Chronic Kidney Disease: Pilot Randomized Controlled Trial and Stakeholder Interviews", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e19861", keywords="medication adherence", keywords="mobile health", keywords="pediatrics", keywords="kidney diseases", keywords="kidney", keywords="mHealth", keywords="adherence", keywords="adolescent", keywords="young adult", keywords="intervention", abstract="Background: Up to one-third of adolescents and young adults (11-21 years old) with chronic kidney disease exhibit suboptimal rates of adherence to renal-protective antihypertensive medications. Mobile health interventions may promote higher adherence to these medicines in these individuals, but empirical research is needed to inform best practices for applying these modalities. Objective: In this multiphase investigation, we developed and tested a theoretically informed text messaging intervention based on the COM-B model, a well-established health intervention framework stating that capability, opportunity, and motivation interactively modify health behaviors, to improve participants' antihypertensive medication adherence in a pilot randomized controlled trial. Qualitative data on user experiences were obtained. Methods: In phase 1, intervention messages (Reminder+COM-B Message) were developed via stakeholder engagement of participants and pediatric nephrologists. In phase 2, the Reminder+COM-B Message intervention was tested against a Reminder-only Message active control condition in an 8-week pilot randomized controlled trial. The primary outcome was daily electronically monitored antihypertensive medication adherence and secondary outcomes included pre-post participant surveys of adherence self-efficacy, adherence barriers, outcome expectancies for taking medicine, and motivation for and importance of taking medicine. In phase 3, qualitative interviews related to user experiences were conducted with participants in the Reminder+COM-B Message intervention group. Results: Following phase 1, 34 participants (mean age 16.59 years, 41\% female, 38\% African American/Black, 35\% hypertension diagnosis) completed the phase 2 pilot randomized controlled trial (n=18 in the Reminder+COM-B Message intervention group, n=16 in the Reminder-only Message active control group). All participants in the Reminder+COM-B Message intervention group completed a phase 3 qualitative interview. Overall, study procedures were feasible and the Reminder+COM-B Message intervention was acceptable to the participants (eg, 15/18 participants reported reading the majority of messages sent to them, 0/18 reported that the messages reduced their desire to take medicine). Prerandomization, there were no significant group differences in the rate of change in daily adherence over time. However, postrandomization, there was a significant group by time interaction (B=.01, P=.04) in which daily adherence decreased significantly over time in the Reminder-only Message active control group but remained stable in the Reminder+COM-B Message intervention group. There were no significant differences between groups in pre-post changes in survey responses. Qualitative interviews revealed participants' perceptions of how the Reminder+COM-B Message intervention changed adherence behavior and highlighted several areas for improving the intervention (eg, adapt messaging timing, intensity, and content to match daily adherence, send praise when medicine is taken). Conclusions: The Reminder+COM-B Message intervention was feasible and acceptable to adolescents/young adults and demonstrated potential to promote participants' daily medication adherence beyond simple reminders. Further research is needed to determine the Reminder+COM-B Message intervention's mechanisms of adherence behavior change and to incorporate qualitative participant feedback into a modified version of this intervention to enhance its acceptability. Trial Registration: ClinicalTrials.gov NCT03651596; https://clinicaltrials.gov/ct2/show/NCT03651596 ", doi="10.2196/19861", url="http://www.jmir.org/2020/8/e19861/", url="http://www.ncbi.nlm.nih.gov/pubmed/32795983" } @Article{info:doi/10.2196/19500, author="Jukic, Tomislav and Ihan, Alojz and Petek {\vS}ter, Marija and Strojnik, Vojko and Stubljar, David and Starc, Andrej", title="Adherence of Female Health Care Workers to the Use a Web-Based Tool for Improving and Modifying Lifestyle: Prospective Target Group Pilot Study", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e19500", keywords="mHealth", keywords="eHealth", keywords="health care workers", keywords="occupational stress", keywords="burnout", keywords="adherence", keywords="web-based tool", abstract="Background: Health care professionals are exposed to the psychological and physiological effects of stress, which is a well-known risk factor for various mental and physical health problems. Objective: The aims of this study were to assess the adherence of female health care workers to use a web-based tool for improving and modifying lifestyle and to identify the potential factors influencing their adherence. Methods: A prospective, observational study was performed. A total of 80 female health care workers (physicians and gradated nurses) from 2 university medical centers and female members of a family medicine society participated. Participants completed a questionnaire that inquired about their basic demographic data and physical fitness. Physical fitness was assessed by the Rockport Fitness Walking Test. Adherence to a web-based application (24@life) was followed for 3 months and the number of log-ins into the application was counted. Results: The study was conducted from March to October 2019. Significantly high workload has been detected in all groups (P<.05), except in the general practitioner with normal workload group. The graduated nurse working in the surgery room group showed chronic stress with elevated S-cortisol levels (>690 nmol/L); activated cellular immune system with elevated concentrations of lymphocytes (reference 1.1-2.5 {\texttimes} 109 cells/L), CD3 cells (reference 0.7-1.9 {\texttimes} 109 cells/L), CD8 cells (reference 0.2-0.7 {\texttimes} 109 cells/L), and HLA-DR/CD3 cells (reference 0.04-0.2 {\texttimes} 109 cells/L); and the worst quality of sleep (mean 2.8 [SD 1.2]). Only 32 of 80 participants (40\%) were adherent to the web-based application. Participants most frequently viewed web pages on areas of physical activity (497 times) and nutrition (332 times). No factors or participant's characteristics such as weight (odds ratio [OR] 1.026, 95\% CI 0.977-1.078), BMI (OR 0.993, 95\% CI 0.834-1.184), age (OR 0.970, 95\% CI 0.910-1.034), or stress level (OR 0.997, 95\% CI 0.995-1.000) were identified to affect the adherence rates. Conclusions: Female health care workers exposed to high workload did not find the web-based application useful for improving and modifying their lifestyle. Therefore, other strategies that might help health care workers facing stress and improve their lifestyle should be identified. ", doi="10.2196/19500", url="https://www.jmir.org/2020/8/e19500", url="http://www.ncbi.nlm.nih.gov/pubmed/32687475" } @Article{info:doi/10.2196/16239, author="Dauphin, Cassy and Clark, Nikia and Cadzow, Renee and Saad-Harfouche, Frances and Rodriguez, Elisa and Glaser, Kathryn and Kiviniemi, Marc and Keller, Maria and Erwin, Deborah", title="\#BlackBreastsMatter: Process Evaluation of Recruitment and Engagement of Pregnant African American Women for a Social Media Intervention Study to Increase Breastfeeding", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e16239", keywords="breastfeeding", keywords="breast cancer education", keywords="African American mothers", keywords="Facebook", keywords="mobile phone, social media", abstract="Background: In the United States, there are lower rates of breastfeeding among African American mothers, particularly those who are younger women. Recent epidemiological studies have shown a strong association of more aggressive types of breast cancer (estrogen receptor negative) among African American women, with a higher risk in African American women who did not breastfeed their children. Objective: This study aims to describe the process evaluation of recruitment and educational strategies to engage pregnant African American participants for a pilot study designed to determine whether social media messaging about breast cancer risk reduction through breastfeeding may positively influence breastfeeding rates. Methods: This pilot study is conducted in collaboration with a local Women, Infants, and Children (WIC) organization and hospital and prenatal clinics of a local health care network. To engage African American women to enroll in the study, several methods and monitoring processes were explored, including WIC electronic text-based messages sent out to all phones of current WIC recipients (referred to as e-blasts); keyword responses to texts from flyers and posters in local community-based organizations, hospitals, and prenatal clinics; keyword responses using electronic links posted in established Facebook groups; and snowball recruitment of other pregnant women by current participants through Facebook. Once enrolled, participants were randomized to 2 study conditions: (1) an intervention group receiving messages about breast cancer risk reduction and breastfeeding or (2) a control group receiving breastfeeding-only messages. Data were obtained through electronic monitoring, SurveyMonkey, qualitative responses on Facebook, focus groups, and interviews. Results: More than 3000 text messages were sent and received through WIC e-blasts and keyword responses from flyers. A total of 472 women were recruited through WIC e-blast, and 161 responded to flyers and contacts through the local health care network, community-based organizations, Facebook, and friend referrals. A total of 633 women were assessed for eligibility to participate in the study. A total of 288 pregnant African American women were enrolled, consented, and completed presurvey assessments (102.8\% of the goal), and 22 participants attended focus groups or interviews reporting on their experiences with Facebook and the educational messages. Conclusions: This process evaluation suggests that using electronic, smartphone apps with social media holds promise for both recruitment and conduct of health education intervention studies for pregnant African American women. Providing messaging and resources through social media to reinforce and educate women about breastfeeding and potentially provide lactation support is intriguing. Convenience (for researchers and participants) is an attribute of social media for this demographic of women and worthy of further research as an educational tool. Trial Registration: ClinicalTrials.gov NCT03680235; https://clinicaltrials.gov/ct2/show/NCT03680235 ", doi="10.2196/16239", url="https://www.jmir.org/2020/8/e16239", url="http://www.ncbi.nlm.nih.gov/pubmed/32773377" } @Article{info:doi/10.2196/17019, author="Lewis, Shon and Ainsworth, John and Sanders, Caroline and Stockton-Powdrell, Charlotte and Machin, Matthew and Whelan, Pauline and Hopkins, Richard and He, Zhimin and Applegate, Eve and Drake, Richard and Bamford, Charlie and Roberts, Chris and Wykes, Til", title="Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e17019", keywords="digital", keywords="smartphone", keywords="m-health", keywords="psychosis", keywords="mental health", keywords="self management", abstract="Background: Improving recovery from acute symptoms and preventing relapse are two significant challenges in severe mental illness. We developed a personalized smartphone-based app to monitor symptoms in real time and validated its acceptance, reliability, and validity. Objective: To assess (i) acceptability of continuous monitoring to SMI patients and health professionals over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; and (iii) the feasibility of detecting early warning signs of relapse. Methods: The active symptom monitoring smartphone app was built into an end-to-end system in two NHS Trusts to enable real-time symptom self-monitoring and detection by the clinical team of early signs of relapse in people with severe mental illness. We conducted an open randomized controlled trial of active symptom monitoring compared to usual management to assess: (i) acceptability and safety of continuous monitoring over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; (iii) feasibility of detecting early warning signs of relapse communicated to the healthcare staff via an app streaming data to the electronic health record. Eligible participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) diagnosis of schizophrenia and related disorders, and a history of relapse within the previous two years were enrolled from an early intervention team and a community mental health team. Results: Of 181 eligible patients, 81 (45\%) consented and were randomized to either active symptom monitoring or management as usual. At 12 weeks, 90\% (33/36) of those in the active monitoring group continued to use the system and exhibited an adherence rate (defined as responding to >33\% of alerts) of 84\% (30/36\}. Active symptom monitoring was associated with no difference on the empowerment scale in comparison to the usual management group at 12 weeks. The pre-planned intent-to-treat analysis of the primary outcome, a positive score on the Positive and Negative Syndrome Scale (PANSS) scale, showed a significant reduction in the active symptom monitoring group over 12 weeks in the early intervention center. Alerts for personalized early warning signs of relapse were built into the workflows of both NHS Trusts, and 100\% of health professional staff used the system in a new digital workflow. Qualitative analyses supported the acceptability of the system to participants and staff. Conclusions: The active smartphone monitoring system is feasible and was accepted by users in a 3-month study of people with severe mental illness, with surprisingly high levels of adherence. App use was associated with psychotic symptom improvement in recent-onset participants, but not those with longstanding illness, supporting the notion of improved self-management. When built into clinical management workflows to enable personalized alerts of symptom deterioration, the app has demonstrated utility in promoting earlier intervention for relapse. Trial Registration: ISRCTN Registry ISRCTN88145142; http://www.isrctn.com/ISRCTN88145142 ", doi="10.2196/17019", url="https://www.jmir.org/2020/8/e17019", url="http://www.ncbi.nlm.nih.gov/pubmed/32788150" } @Article{info:doi/10.2196/16797, author="Brower, Jacob and LaBarge, C. Monica and White, Lauren and Mitchell, S. Marc", title="Examining Responsiveness to an Incentive-Based Mobile Health App: Longitudinal Observational Study", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e16797", keywords="mHealth", keywords="behavioral economics", keywords="public health", keywords="incentives", keywords="mobile apps", keywords="mobile phone", abstract="Background: The Carrot Rewards app was developed as part of a public-private partnership to reward Canadians with loyalty points for downloading the app, referring friends, completing educational health quizzes, and health-related behaviors with long-term objectives of increasing health knowledge and encouraging healthy behaviors. During the first 3 months after program rollout in British Columbia, a number of program design elements were adjusted, creating observed differences between groups of users with respect to the potential impact of program features on user engagement levels. Objective: This study examines the impact of reducing reward size over time and explored the influence of other program features such as quiz timing, health intervention content, and type of reward program on user engagement with a mobile health (mHealth) app. Methods: Participants in this longitudinal, nonexperimental observational study included British Columbia citizens who downloaded the app between March and July 2016. A regression methodology was used to examine the impact of changes to several program design features on quiz offer acceptance and engagement with this mHealth app. Results: Our results, based on the longitudinal app use of 54,917 users (mean age 35, SD 13.2 years; 65.03\% [35,647/54,917] female), indicated that the key drivers of the likelihood of continued user engagement, in order of greatest to least impact, were (1) type of rewards earned by users (eg, movies [+355\%; P<.001], air travel [+210\%; P<.001], and grocery [+140\%; P<.001] relative to gas), (2) time delay between early offers (?64\%; P<.001), (3) the content of the health intervention (eg, healthy eating [?10\%; P<.001] vs exercise [+20\%, P<.001] relative to health risk assessments), and (4) changes in the number of points offered. Our results demonstrate that reducing the number of points associated with a particular quiz by 10\% only led to a 1\% decrease in the likelihood of offer response (P<.001) and that each of the other design features had larger impacts on participant retention than did changes in the number of points. Conclusions: The results of this study demonstrate that this program, built around the principles of behavioral economics in the form of the ongoing awarding of a small number of reward points instantly following the completion of health interventions, was able to drive significantly higher engagement levels than those demonstrated in previous literature exploring the intersection of mHealth apps and financial incentives. Previous studies have demonstrated the presence of incentive matters to user engagement; however, our results indicate that the number of points offered for these reward point--based health interventions is less important than other program design features such as the type of reward points being offered, the timing of intervention and reward offers, and the content of the health interventions in driving continued engagement by users. ", doi="10.2196/16797", url="https://www.jmir.org/2020/8/e16797", url="http://www.ncbi.nlm.nih.gov/pubmed/32773371" } @Article{info:doi/10.2196/17058, author="Crafoord, Marie-Ther{\'e}se and Fjell, Maria and Sundberg, Kay and Nilsson, Marie and Langius-Ekl{\"o}f, Ann", title="Engagement in an Interactive App for Symptom Self-Management during Treatment in Patients With Breast or Prostate Cancer: Mixed Methods Study", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e17058", keywords="engagement", keywords="adherence", keywords="mHealth", keywords="mobile app", keywords="cancer supportive care", keywords="symptom management", keywords="usage metrics", keywords="breast cancer", keywords="prostate cancer", abstract="Background: Using mobile technology for symptom management and self-care can improve patient-clinician communication and clinical outcomes in patients with cancer. The interactive app Interaktor has been shown to reduce symptom burden during cancer treatment. It includes symptom assessment, an alert system for contact with health care professionals, access to self-care advice, and visualization of symptom history. It is essential to understand how digital interventions operate; one approach is to examine engagement by assessing usage and exploring user experiences. Actual usage in relation to the intended use---adherence---is an essential factor of engagement. Objective: This study aimed to describe engagement with the Interaktor app among patients with breast or prostate cancer during treatment. Methods: Patients from the intervention groups of two separate randomized controlled trials were included: patients with breast cancer receiving neoadjuvant chemotherapy (n=74) and patients with locally advanced prostate cancer receiving treatment with radiotherapy (n=75). The patients reported their symptoms daily. Sociodemographic and clinical data were obtained from baseline questionnaires and medical records. Logged data usage was retrieved from the server and analyzed descriptively and with multiple regression analysis. Telephone interviews were conducted with patients about their perceptions of using the app and analyzed using content analysis. Results: The median adherence percentage to daily symptom reporting was 83\%. Most patients used the self-care advice and free text message component. Among the patients treated for breast cancer, higher age predicted a lower total number of free text messages sent (P=.04). Among the patients treated for prostate cancer, higher age (P=.01) and higher education level (P=.04), predicted an increase in total views on self-care advice, while higher comorbidity (P=.004) predicted a decrease in total views on self-care advice. Being married or living with a partner predicted a higher adherence to daily symptom reporting (P=.02). Daily symptom reporting created feelings of having continuous contact with health care professionals, being acknowledged, and safe. Being contacted by a nurse after a symptom alert was considered convenient and highly valued. Treatment and time-related aspects influenced engagement. Daily symptom reporting was perceived as particularly meaningful at the beginning of treatment. Requests were made for advice on diet and psychological symptoms, as well as for more comprehensive and detailed information as the patient progressed through treatment. Conclusions: Patient engagement in the interactive app Interaktor was high. The app promoted patient participation in their care through continuous and convenient contact with health care professionals. The predictive ability of demographic variables differed between patient groups, but higher age and a higher educational level predicted usage of specific app functions for both patient groups. Patients' experience of relevance and interactivity influenced their engagement positively. ", doi="10.2196/17058", url="https://www.jmir.org/2020/8/e17058", url="http://www.ncbi.nlm.nih.gov/pubmed/32663140" } @Article{info:doi/10.2196/15506, author="Betthauser, M. Lisa and Stearns-Yoder, A. Kelly and McGarity, Suzanne and Smith, Victoria and Place, Skyler and Brenner, A. Lisa", title="Mobile App for Mental Health Monitoring and Clinical Outreach in Veterans: Mixed Methods Feasibility and Acceptability Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e15506", keywords="veterans", keywords="mobile app", keywords="smartphone", keywords="mental health", keywords="acceptability", keywords="feasibility", abstract="Background: Advances in mobile health (mHealth) technology have made it possible for patients and health care providers to monitor and track behavioral health symptoms in real time. Ideally, mHealth apps include both passive and interactive monitoring and demonstrate high levels of patient engagement. Digital phenotyping, the measurement of individual technology usage, provides insight into individual behaviors associated with mental health. Objective: Researchers at a Veterans Affairs Medical Center and Cogito Corporation sought to explore the feasibility and acceptability of an mHealth app, the Cogito Companion. Methods: A mixed methodological approach was used to investigate the feasibility and acceptability of the app. Veterans completed clinical interviews and self-report measures, at baseline and at a 3-month follow-up. During the data collection period, participants were provided access to the Cogito Companion smartphone app. The mobile app gathered passive and active behavioral health indicators. Data collected (eg, vocal features and digital phenotyping of everyday social signals) are analyzed in real time. Passive data collected include location via global positioning system (GPS), phone calls, and SMS text message metadata. Four primary model scores were identified as being predictive of the presence or absence of depression or posttraumatic stress disorder (PTSD). Veterans Affairs clinicians monitored a provider dashboard and conducted clinical outreach when indicated. Results: Findings suggest that use of the Cogito Companion app was feasible and acceptable. Veterans (n=83) were interested in and used the app; however, active use declined over time. Nonetheless, data were passively collected, and outreach occurred throughout the study period. On the Client Satisfaction Questionnaire--8, 79\% (53/67) of the sample reported scores demonstrating acceptability of the app (mean 26.2, SD 4.3). Many veterans reported liking specific app features (day-to-day monitoring) and the sense of connection they felt with the study clinicians who conducted outreach. Only a small percentage (4/67, 6\%) reported concerns regarding personal privacy. Conclusions: Feasibility and acceptability of the Cogito Corporation platform to monitor mental health symptoms, behaviors, and facilitate follow-up in a sample of veterans were supported. Clinically, platforms such as the Cogito Companion system may serve as useful methods to promote monitoring, thereby facilitating early identification of risk and mitigating negative psychiatric outcomes, such as suicide. ", doi="10.2196/15506", url="https://www.jmir.org/2020/8/e15506", url="http://www.ncbi.nlm.nih.gov/pubmed/32779572" } @Article{info:doi/10.2196/19006, author="Harada, Norihiro and Harada, Sonoko and Ito, Jun and Atsuta, Ryo and Hori, Satoshi and Takahashi, Kazuhisa", title="Mobile Health App for Japanese Adult Patients With Asthma: Clinical Observational Study", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e19006", keywords="asthma", keywords="cough variant asthma", keywords="mobile health", keywords="ResearchKit", abstract="Background: Inappropriate asthma control reduces quality of life and causes increased exacerbations. Mobile health (mHealth) employs information and communication technology for surveying health-related issues. Objective: This noninterventional, observational study assessed current real-world asthma control levels among Japanese patients with asthma and cough variant asthma (CVA) using the Zensoku-Log app. Methods: We developed the app using the ResearchKit platform and conducted a mobile-based, self-reporting, observational survey among patients with asthma and CVA. The app was downloaded 7855 times between February 2016 and February 2018, and enabled collection of data on symptoms, comorbidities, quality of life, medications, asthma control, and adherence. Results: Of the 1744 eligible participants (median age 33 years; range 20-74 years; male-to-female ratio 38.7:61.3), 50.97\% (889/1744) reported unscheduled visits, 62.84\% (1096/1744) reported regularly scheduled visits, 23.14\% (402/1737) smoked, and 40.75\% (705/1730) had pets. In addition, 91.89\% (1598/1739) of participants had atopic predisposition, including allergic rhinitis and atopic dermatitis. Daily inhaled corticosteroid and oral corticosteroid treatment had been prescribed for 89.45\% (1552/1735) and 22.07\% (383/1735) of participants, respectively. Although an asthma control questionnaire demonstrated poor asthma control in 58.48\% (1010/1727), a leukotriene receptor antagonist, theophylline, and a long-acting muscarinic antagonist had been prescribed for only 30.66\% (532/1735), 15.91\% (276/1735), and 4.38\% (76/1735), respectively. The Adherence Starts with Knowledge 12 total score was 29. In the 421 participants who repeated the questionnaire, asthma control increased significantly between the initial and last rounds (P=.002). Conclusions: Users of this mHealth app in Japan had poorly controlled asthma and may need more treatment for asthma and their comorbidities. Repeated app users demonstrated improved asthma control. Trial Registration: UMIN Clinical Trial Registry UMIN000021043; https://upload.umin.ac.jp/cgi-open-bin/ctr\_e/ctr\_view.cgi?recptno=R000023913. ", doi="10.2196/19006", url="https://www.jmir.org/2020/8/e19006", url="http://www.ncbi.nlm.nih.gov/pubmed/32795993" } @Article{info:doi/10.2196/18946, author="Cheng, Chao and Ho, Hung Rainbow Tin and Guo, Yan and Zhu, Mengting and Yang, Weixiong and Li, Yiran and Liu, Zhenguo and Zhuo, Shuyu and Liang, Qi and Chen, Zhenghong and Zeng, Yu and Yang, Jiali and Zhang, Zhanfei and Zhang, Xu and Monroe-Wise, Aliza and Yeung, Sai-Ching", title="Development and Feasibility of a Mobile Health--Supported Comprehensive Intervention Model (CIMmH) for Improving the Quality of Life of Patients With Esophageal Cancer After Esophagectomy: Prospective, Single-Arm, Nonrandomized Pilot Study", journal="J Med Internet Res", year="2020", month="Aug", day="18", volume="22", number="8", pages="e18946", keywords="esophageal cancer", keywords="quality of life", keywords="nutrition", keywords="physical exercise", keywords="psychological support", keywords="mobile health", keywords="mHealth", abstract="Background: Patients with esophageal cancer often experience clinically relevant deterioration of quality of life (QOL) after esophagectomy owing to malnutrition, lack of physical exercise, and psychological symptoms. Objective: This study aimed to evaluate the feasibility, safety, and efficacy of a comprehensive intervention model using a mobile health system (CIMmH) in patients with esophageal cancer after esophagectomy. Methods: Twenty patients with esophageal cancer undergoing the modified McKeown surgical procedure were invited to join the CIMmH program with both online and offline components for 12 weeks. The participants were assessed before surgery and again at 1 and 3 months after esophagectomy. QOL, depressive symptoms, anxiety, stress, nutrition, and physical fitness were measured. Results: Of the 20 patients, 16 (80\%) completed the program. One month after esophagectomy, patients showed significant deterioration in overall QOL (P=.02), eating (P=.005), reflux (P=.04), and trouble with talking (P<.001). At the 3-month follow-up, except for pain (P=.02), difficulty with eating (P=.03), dry mouth (P=.04), and trouble with talking (P=.003), all other QOL dimensions returned to the preoperative level. There were significant reductions in weight (P<.001) and BMI (P=.02) throughout the study, and no significant changes were observed for physical fitness measured by change in the 6-minute walk distance between baseline and the 1-month follow-up (P=.22) or between baseline and the 3-month follow-up (P=.52). Depressive symptoms significantly increased 1 month after surgery (P<.001), while other psychological measures did not show relevant changes. Although there were declines in many measures 1 month after surgery, these were much improved at the 3-month follow-up, and the recovery was more profound and faster than with traditional rehabilitation programs. Conclusions: The CIMmH was feasible and safe and demonstrated encouraging efficacy testing with a control group for enhancing recovery after surgery among patients with esophageal cancer in China. Trial Registration: Chinese Clinical Trial Registry (ChiCTR-IPR-1800019900); http://www.chictr.org.cn/showprojen.aspx?proj=32811. ", doi="10.2196/18946", url="http://www.jmir.org/2020/8/e18946/", url="http://www.ncbi.nlm.nih.gov/pubmed/32808933" } @Article{info:doi/10.2196/16761, author="Vargas Meza, Xanat and Yamanaka, Toshimasa", title="Food Communication and its Related Sentiment in Local and Organic Food Videos on YouTube", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e16761", keywords="social networks", keywords="framing", keywords="semantic analysis", keywords="sentiment analysis", keywords="organic", keywords="local", keywords="food", keywords="YouTube", abstract="Background: Local and organic foods have shown increased importance and market size in recent years. However, attitudes, sentiment, and habits related to such foods in the context of video social networks have not been thoroughly researched. Given that such media have become some of the most important venues of internet traffic, it is relevant to investigate how sustainable food is communicated through such video social networks. Objective: This study aimed to explore the diffusion paths of local and organic foods on YouTube, providing a review of trends, coincidences, and differences among video discourses. Methods: A combined methodology involving webometric, framing, semantic, and sentiment analyses was employed. Results: We reported the results for the following two groups: organic and local organic videos. Although the content of 923 videos mostly included the ``Good Mother'' (organic and local organic: 282/808, 34.9\% and 311/866, 35.9\%, respectively), ``Natural Goodness'' (220/808, 27.2\% and 253/866, 29.2\%), and ``Undermining of Foundations'' (153/808, 18.9\% and 180/866, 20.7\%) frames, organic videos were more framed in terms of ``Frankenstein'' food (organic and local organic: 68/808, 8.4\% and 27/866, 3.1\%, respectively), with genetically modified organisms being a frequent topic among the comments. Organic videos (N=448) were better connected in terms of network metrics than local organic videos (N=475), which were slightly more framed regarding ``Responsibility'' (organic and local organic: 42/808, 5.1\% and 57/866, 6.5\%, respectively) and expressed more positive sentiment (M ranks for organic and local organic were 521.2 and 564.54, respectively, Z=2.15, P=.03). Conclusions: The results suggest that viewers considered sustainable food as part of a complex system and in a positive light and that food framed as artificial and dangerous sometimes functions as a counterpoint to promote organic food. ", doi="10.2196/16761", url="https://www.jmir.org/2020/8/e16761", url="http://www.ncbi.nlm.nih.gov/pubmed/32773370" } @Article{info:doi/10.2196/17582, author="Zhang, Yan and Cao, Bolin and Wang, Yifan and Peng, Tai-Quan and Wang, Xiaohua", title="When Public Health Research Meets Social Media: Knowledge Mapping From 2000 to 2018", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e17582", keywords="social media", keywords="public health", keywords="infodemiology", keywords="infoveillance", keywords="topic modeling", keywords="research theme", keywords="research method", abstract="Background: Social media has substantially changed how people confront health issues. However, a comprehensive understanding of how social media has altered the foci and methods in public health research remains lacking. Objective: This study aims to examine research themes, the role of social media, and research methods in social media--based public health research published from 2000 to 2018. Methods: A dataset of 3419 valid studies was developed by searching a list of relevant keywords in the Web of Science and PubMed databases. In addition, this study employs an unsupervised text-mining technique and topic modeling to extract research themes of the published studies. Moreover, the role of social media and research methods adopted in those studies were analyzed. Results: This study identifies 25 research themes, covering different diseases, various population groups, physical and mental health, and other significant issues. Social media assumes two major roles in public health research: produce substantial research interest for public health research and furnish a research context for public health research. Social media provides substantial research interest for public health research when used for health intervention, human-computer interaction, as a platform of social influence, and for disease surveillance, risk assessment, or prevention. Social media acts as a research context for public health research when it is mere reference, used as a platform to recruit participants, and as a platform for data collection. While both qualitative and quantitative methods are frequently used in this emerging area, cutting edge computational methods play a marginal role. Conclusions: Social media enables scholars to study new phenomena and propose new research questions in public health research. Meanwhile, the methodological potential of social media in public health research needs to be further explored. ", doi="10.2196/17582", url="http://www.jmir.org/2020/8/e17582/", url="http://www.ncbi.nlm.nih.gov/pubmed/32788156" } @Article{info:doi/10.2196/19222, author="Min, Kyoung-Bok and Song, Sung-Hee and Min, Jin-Young", title="Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e19222", keywords="topic modeling", keywords="occupational accident", keywords="social media", keywords="knowledge", keywords="workplace", keywords="accident", keywords="model", keywords="analysis", keywords="safety", abstract="Background: In most industrialized societies, regulations, inspections, insurance, and legal options are established to support workers who suffer injury, disease, or death in relation to their work; in practice, these resources are imperfect or even unavailable due to workplace or employer obstruction. Thus, limitations exist to identify unmet needs in occupational safety and health information. Objective: The aim of this study was to explore hidden issues related to occupational accidents by examining social network services (SNS) data using topic modeling. Methods: Based on the results of a Google search for the phrases occupational accident, industrial accident and occupational diseases, a total of 145 websites were selected. From among these websites, we collected 15,244 documents on queries related to occupational accidents between 2002 and 2018. To transform unstructured text into structure data, natural language processing of the Korean language was conducted. We performed the latent Dirichlet allocation (LDA) as a topic model using a Python library. A time-series linear regression analysis was also conducted to identify yearly trends for the given documents. Results: The results of the LDA model showed 14 topics with 3 themes: workers' compensation benefits (Theme 1), illicit agreements with the employer (Theme 2), and fatal and non-fatal injuries and vulnerable workers (Theme 3). Theme 1 represented the largest cluster (52.2\%) of the collected documents and included keywords related to workers' compensation (ie, company, occupational injury, insurance, accident, approval, and compensation) and keywords describing specific compensation benefits such as medical expense benefits, temporary incapacity benefits, and disability benefits. In the yearly trend, Theme 1 gradually decreased; however, other themes showed an overall increasing pattern. Certain queries (ie, musculoskeletal system, critical care, and foreign workers) showed no significant variation in the number of queries. Conclusions: We conducted LDA analysis of SNS data of occupational accident--related queries and discovered that the primary concerns of workers posting about occupational injuries and diseases were workers' compensation benefits, fatal and non-fatal injuries, vulnerable workers, and illicit agreements with employers. While traditional systems focus mainly on quantitative monitoring of occupational accidents, qualitative aspects formulated by topic modeling from unstructured SNS queries may be valuable to address inequalities and improve occupational health and safety. ", doi="10.2196/19222", url="http://www.jmir.org/2020/8/e19222/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663156" } @Article{info:doi/10.2196/18350, author="Nasralah, Tareq and El-Gayar, Omar and Wang, Yong", title="Social Media Text Mining Framework for Drug Abuse: Development and Validation Study With an Opioid Crisis Case Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e18350", keywords="drug abuse", keywords="social media", keywords="infodemiology", keywords="infoveillance", keywords="text mining", keywords="opioid crisis", abstract="Background: Social media are considered promising and viable sources of data for gaining insights into various disease conditions and patients' attitudes, behaviors, and medications. They can be used to recognize communication and behavioral themes of problematic use of prescription drugs. However, mining and analyzing social media data have challenges and limitations related to topic deduction and data quality. As a result, we need a structured approach to analyze social media content related to drug abuse in a manner that can mitigate the challenges and limitations surrounding the use of such data. Objective: This study aimed to develop and evaluate a framework for mining and analyzing social media content related to drug abuse. The framework is designed to mitigate challenges and limitations related to topic deduction and data quality in social media data analytics for drug abuse. Methods: The proposed framework started with defining different terms related to the keywords, categories, and characteristics of the topic of interest. We then used the Crimson Hexagon platform to collect data based on a search query informed by a drug abuse ontology developed using the identified terms. We subsequently preprocessed the data and examined the quality using an evaluation matrix. Finally, a suitable data analysis approach could be used to analyze the collected data. Results: The framework was evaluated using the opioid epidemic as a drug abuse case analysis. We demonstrated the applicability of the proposed framework to identify public concerns toward the opioid epidemic and the most discussed topics on social media related to opioids. The results from the case analysis showed that the framework could improve the discovery and identification of topics in social media domains characterized by a plethora of highly diverse terms and lack of a commonly available dictionary or language by the community, such as in the case of opioid and drug abuse. Conclusions: The proposed framework addressed the challenges related to topic detection and data quality. We demonstrated the applicability of the proposed framework to identify the common concerns toward the opioid epidemic and the most discussed topics on social media related to opioids. ", doi="10.2196/18350", url="https://www.jmir.org/2020/8/e18350", url="http://www.ncbi.nlm.nih.gov/pubmed/32788147" } @Article{info:doi/10.2196/18401, author="Zhu, M. Jane and Sarker, Abeed and Gollust, Sarah and Merchant, Raina and Grande, David", title="Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach", journal="J Med Internet Res", year="2020", month="Aug", day="17", volume="22", number="8", pages="e18401", keywords="medicaid", keywords="public health", keywords="health communication", keywords="community engagement", keywords="social media", abstract="Background: Twitter is a potentially valuable tool for public health officials and state Medicaid programs in the United States, which provide public health insurance to 72 million Americans. Objective: We aim to characterize how Medicaid agencies and managed care organization (MCO) health plans are using Twitter to communicate with the public. Methods: Using Twitter's public application programming interface, we collected 158,714 public posts (``tweets'') from active Twitter profiles of state Medicaid agencies and MCOs, spanning March 2014 through June 2019. Manual content analyses identified 5 broad categories of content, and these coded tweets were used to train supervised machine learning algorithms to classify all collected posts. Results: We identified 15 state Medicaid agencies and 81 Medicaid MCOs on Twitter. The mean number of followers was 1784, the mean number of those followed was 542, and the mean number of posts was 2476. Approximately 39\% of tweets came from just 10 accounts. Of all posts, 39.8\% (63,168/158,714) were classified as general public health education and outreach; 23.5\% (n=37,298) were about specific Medicaid policies, programs, services, or events; 18.4\% (n=29,203) were organizational promotion of staff and activities; and 11.6\% (n=18,411) contained general news and news links. Only 4.5\% (n=7142) of posts were responses to specific questions, concerns, or complaints from the public. Conclusions: Twitter has the potential to enhance community building, beneficiary engagement, and public health outreach, but appears to be underutilized by the Medicaid program. ", doi="10.2196/18401", url="http://www.jmir.org/2020/8/e18401/", url="http://www.ncbi.nlm.nih.gov/pubmed/32804085" } @Article{info:doi/10.2196/15697, author="Eke, Ransome and Li, Tong and Bond, Kiersten and Ho, Arlene and Graves, Lisa", title="Viewing Trends and Users' Perceptions of the Effect of Sleep-Aiding Music on YouTube: Quantification and Thematic Content Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="24", volume="22", number="8", pages="e15697", keywords="insomnia", keywords="sleep deprivation", keywords="YouTube", keywords="utilization", keywords="pattern", keywords="perception", keywords="content analysis", abstract="Background: Sleep plays an essential role in the psychological and physiological functioning of humans. A report from the Centers for Disease Control and Prevention (CDC) found that sleep duration was significantly reduced among US adults in 2012 compared to 1985. Studies have described a significant association between listening to soothing music and an improvement in sleep quality and sleep duration. YouTube is a platform where users can access sleep-aiding music videos. No literature exists pertaining to the use of sleep-aiding music on YouTube. Objective: This study aimed to examine the patterns of viewing sleep-aiding music videos on YouTube. We also performed a content analysis of the comments left on sleep-aiding music video posts, to describe the perception of users regarding the effects of these music videos on their sleep quality. Methods: We searched for sleep-aiding music videos published on YouTube between January 1, 2012, and December 31, 2017. We sorted videos by view number (highest to lowest) and used a targeted sampling approach to select eligible videos for qualitative content analysis. To perform the content analysis, we imported comments into a mixed-method analytical software. We summarized variables including total views, likes, dislikes, play duration, and age of published music videos. All descriptive statistics were completed with SAS statistical software. Results: We found a total of 238 sleep-aiding music videos on YouTube that met the inclusion criteria. The total view count was 1,467,747,018 and the total playtime was 84,252 minutes. The median play length was 186 minutes (IQR 122 to 480 minutes) and the like to dislike ratio was approximately 9 to 1. In total, 135 (56.7\%) videos had over 1 million views, and 124 (52.1\%) of the published sleep-aiding music videos had stayed active for 1 to 2 years. Overall, 4023 comments were extracted from 20 selected sleep-aiding music videos. Five overarching themes emerged in the reviewed comments, including viewers experiencing a sleep problem, perspective on the positive impact of the sleep-aiding music videos, no effect of the sleep-aiding music videos, time to initiation of sleep or sleep duration, and location of viewers. The overall $\kappa$ statistic for the codes was 0.87 (range 0.85-0.96). Conclusions: This is the first study to examine the patterns of viewing sleep-aiding music videos on YouTube. We observed a substantial increase in the number of people using sleep-aiding music videos, with a wide variation in viewer location. This study supports the hypothesis that listening to soothing music has a positive impact on sleep habits. ", doi="10.2196/15697", url="http://www.jmir.org/2020/8/e15697/", url="http://www.ncbi.nlm.nih.gov/pubmed/32831182" } @Article{info:doi/10.2196/17560, author="Guo, Wanjun and Tao, Yujie and Li, Xiaojing and Lin, Xia and Meng, Yajing and Yang, Xia and Wang, Huiyao and Zhang, Yamin and Tang, Wanjie and Wang, Qiang and Deng, Wei and Zhao, Liansheng and Ma, Xiaohong and Li, Mingli and Chen, Ting and Xu, Jiajun and Li, Jing and Hao, Wei and Lee, Sing and Coid, W. Jeremy and Greenshaw, J. Andrew and Li, Tao", title="Associations of Internet Addiction Severity With Psychopathology, Serious Mental Illness, and Suicidality: Large-Sample Cross-Sectional Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17560", keywords="internet", keywords="addiction", keywords="psychopathology", keywords="suicidality", keywords="serious mental illness", abstract="Background: Internet addiction has become a major global concern and a burden on mental health. However, there is a lack of consensus on its link to mental health outcomes. Objective: The aim of this study was to investigate the associations between internet addiction severity and adverse mental health outcomes. Methods: First-year undergraduates enrolled at Sichuan University during September 2015, 2016, 2017, and 2018 were invited to participate in the current study survey, 85.13\% (31,659/37,187) of whom fully responded. Young's 20-item Internet Addiction Test, Patient Health Questionnaire-15, Patient Health Questionnaire-9, Symptom Checklist 90, Six-Item Kessler Psychological Distress Scale, and Suicidal Behaviors Questionnaire-Revised were used to evaluate internet addiction, four psychopathologies (high somatic symptom severity, clinically significant depression, psychoticism, and paranoia), serious mental illness, and lifetime suicidality. Results: The prevalence of students with mild, moderate, and severe internet addiction was 37.93\% (12,009/31,659), 6.33\% (2003/31,659), and 0.20\% (63/31,659), respectively. The prevalence rates of high somatic symptom severity, clinically significant depression, psychoticism, paranoid ideation, and serious mental illness were 6.54\% (2072/31,659), 4.09\% (1294/31,659), 0.51\% (160/31,659), 0.52\% (165/31,659), and 1.88\% (594/31,659), respectively, and the lifetime prevalence rates of suicidal ideation, suicidal plan, and suicidal attempt were 36.31\% (11,495/31,659), 5.13\% (1624/31,659), and 1.00\% (315/31,659), respectively. The prevalence rates and odds ratios (ORs) of the four psychopathologies and their comorbidities, screened serious mental illness, and suicidalities in the group without internet addiction were much lower than the average levels of the surveyed population. Most of these metrics in the group with mild internet addiction were similar to or slightly higher than the average rates; however, these rates sharply increased in the moderate and severe internet addiction groups. Among the four psychopathologies, clinically significant depression was most strongly associated with internet addiction after adjusting for the confounding effects of demographics and other psychopathologies, and its prevalence increased from 1.01\% (178/17,584) in the students with no addiction to 4.85\% (582/12,009), 24.81\% (497/2,003), and 58.73\% (37/63) in the students with mild, moderate, and severe internet addiction, respectively. The proportions of those with any of the four psychopathologies increased from 4.05\% (713/17,584) to 11.72\% (1408/12,009), 36.89\% (739/2003), and 68.25\% (43/63); those with lifetime suicidal ideation increased from 24.92\% (4382/17,584) to 47.56\% (5711/12,009), 67.70\% (1356/2003), and 73.02\% (46/63); those with a suicidal plan increased from 2.59\% (456/17,584) to 6.77\% (813/12,009), 16.72\% (335/2003), and 31.75\% (20/63); and those with a suicidal attempt increased from 0.50\% (88/17,584) to 1.23\% (148/12,009), 3.54\% (71/2003), and 12.70\% (8/63), respectively. Conclusions: Moderate and severe internet addiction were strongly associated with a broad group of adverse mental health outcomes, including somatic symptoms that are the core features of many medical illnesses, although clinically significant depression showed the strongest association. This finding supports the illness validity of moderate and severe internet addiction in contrast to mild internet addiction. These results are important for informing health policymakers and service suppliers from the perspective of resolving the overall human health burden in the current era of ``Internet Plus'' and artificial intelligence. ", doi="10.2196/17560", url="https://www.jmir.org/2020/8/e17560", url="http://www.ncbi.nlm.nih.gov/pubmed/32780029" } @Article{info:doi/10.2196/17675, author="Challet-Bouju, Ga{\"e}lle and Hardouin, Jean-Benoit and Thiabaud, Elsa and Saillard, Ana{\"i}s and Donnio, Yann and Grall-Bronnec, Marie and Perrot, Bastien", title="Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e17675", keywords="gambling", keywords="internet", keywords="trajectory", keywords="latent class analysis", keywords="growth mixture modeling", keywords="gambling tracking data", keywords="early detection", abstract="Background: Individuals who gamble online may be at risk of gambling excessively, but internet gambling also provides a unique opportunity to monitor gambling behavior in real environments which may allow intervention for those who encounter difficulties. Objective: The objective of this study was to model the early gambling trajectories of individuals who play online lottery. Methods: Anonymized gambling?related records of the initial 6 months of 1152 clients of the French national lottery who created their internet gambling accounts between September 2015 and February 2016 were analyzed using a two-step approach that combined growth mixture modeling and latent class analysis. The analysis was based upon behavior indicators of gambling activity (money wagered and number of gambling days) and indicators of gambling problems (breadth of involvement and chasing). Profiles were described based upon the probabilities of following the trajectories that were identified for the four indicators, and upon several covariates (age, gender, deposits, type of play, net losses, voluntary self-exclusion, and Playscan classification---a responsible gambling tool that provides each player with a risk assessment: green for low risk, orange for medium risk and red for high risk). Net losses, voluntary self-exclusion, and Playscan classification were used as external verification of problem gambling. Results: We identified 5 distinct profiles of online lottery gambling. Classes 1 (56.8\%), 2 (14.8\%) and 3 (13.9\%) were characterized by low to medium gambling activity and low values for markers of problem gambling. They displayed low net losses, did not use the voluntary self-exclusion measure, and were classified predominantly with green Playscan tags (range 90\%-98\%). Class 4 (9.7\%) was characterized by medium to high gambling activity, played a higher breadth of game types (range 1-6), and had zero to few chasing episodes. They had high net losses but were classified with green (66\%) or orange (25\%) Playscan tags and did not use the voluntary self-exclusion measure. Class 5 (4.8\%) was characterized by medium to very high gambling activity, played a higher breadth of game types (range 1-17), and had a high number of chasing episodes (range 0-5). They experienced the highest net losses, the highest proportion of orange (32\%) and red (39\%) tags within the Playscan classification system and represented the only class in which voluntary self-exclusion was present. Conclusions: Classes 1, 2, 3 may be considered to represent recreational gambling. Class 4 had higher gambling activity and higher breadth of involvement and may be representative of players at risk for future gambling problems. Class 5 stood out in terms of much higher gambling activity and breadth of involvement, and the presence of chasing behavior. Individuals in classes 4 and 5 may benefit from early preventive measures. ", doi="10.2196/17675", url="http://www.jmir.org/2020/8/e17675/", url="http://www.ncbi.nlm.nih.gov/pubmed/32254041" } @Article{info:doi/10.2196/17478, author="Visweswaran, Shyam and Colditz, B. Jason and O'Halloran, Patrick and Han, Na-Rae and Taneja, B. Sanya and Welling, Joel and Chu, Kar-Hai and Sidani, E. Jaime and Primack, A. Brian", title="Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e17478", keywords="vaping", keywords="social media", keywords="infodemiology", keywords="infoveillance", keywords="machine learning", keywords="deep learning", abstract="Background: Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. Machine learning classifiers that identify vaping-relevant tweets and characterize sentiments in them can underpin a Twitter-based vaping surveillance system. Compared with traditional machine learning classifiers that are reliant on annotations that are expensive to obtain, deep learning classifiers offer the advantage of requiring fewer annotated tweets by leveraging the large numbers of readily available unannotated tweets. Objective: This study aims to derive and evaluate traditional and deep learning classifiers that can identify tweets relevant to vaping, tweets of a commercial nature, and tweets with provape sentiments. Methods: We continuously collected tweets that matched vaping-related keywords over 2 months from August 2018 to October 2018. From this data set of tweets, a set of 4000 tweets was selected, and each tweet was manually annotated for relevance (vape relevant or not), commercial nature (commercial or not), and sentiment (provape or not). Using the annotated data, we derived traditional classifiers that included logistic regression, random forest, linear support vector machine, and multinomial naive Bayes. In addition, using the annotated data set and a larger unannotated data set of tweets, we derived deep learning classifiers that included a convolutional neural network (CNN), long short-term memory (LSTM) network, LSTM-CNN network, and bidirectional LSTM (BiLSTM) network. The unannotated tweet data were used to derive word vectors that deep learning classifiers can leverage to improve performance. Results: LSTM-CNN performed the best with the highest area under the receiver operating characteristic curve (AUC) of 0.96 (95\% CI 0.93-0.98) for relevance, all deep learning classifiers including LSTM-CNN performed better than the traditional classifiers with an AUC of 0.99 (95\% CI 0.98-0.99) for distinguishing commercial from noncommercial tweets, and BiLSTM performed the best with an AUC of 0.83 (95\% CI 0.78-0.89) for provape sentiment. Overall, LSTM-CNN performed the best across all 3 classification tasks. Conclusions: We derived and evaluated traditional machine learning and deep learning classifiers to identify vaping-related relevant, commercial, and provape tweets. Overall, deep learning classifiers such as LSTM-CNN had superior performance and had the added advantage of requiring no preprocessing. The performance of these classifiers supports the development of a vaping surveillance system. ", doi="10.2196/17478", url="https://www.jmir.org/2020/8/e17478", url="http://www.ncbi.nlm.nih.gov/pubmed/32784184" } @Article{info:doi/10.2196/18943, author="Struik, L. Laura and Dow-Fleisner, Sarah and Belliveau, Michelle and Thompson, Desiree and Janke, Robert", title="Tactics for Drawing Youth to Vaping: Content Analysis of Electronic Cigarette Advertisements", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e18943", keywords="qualitative research", keywords="electronic nicotine delivery systems", keywords="marketing", keywords="advertisement", keywords="youth", keywords="vaping", abstract="Background: The use of electronic cigarettes (e-cigarettes), also known as vaping, has risen exponentially among North American youth in recent years and has become a critical public health concern. The marketing strategies used by e-cigarette companies have been associated with the uptick in use among youth, with video advertisements on television and other electronic platforms being the most pervasive strategy. It is unknown how these advertisements may be tapping into youth needs and preferences. Objective: The aim of this 2-phase study was to examine the marketing strategies that underpin e-cigarette advertisements, specifically in the context of television. Methods: In phase 1, a scoping review was conducted to identify various influences on e-cigarette uptake among youth. Results of this scoping review informed the development of a coding framework. In phase 2, this framework was used to analyze the content of e-cigarette advertisements as seen on 2 popular television channels (Discovery and AMC). Results: In phase 1, a total of 20 articles met the inclusion criteria. The resultant framework consisted of 16 key influences on e-cigarette uptake among youth, which were categorized under 4 headings: personal, relational, environmental, and product-related. In phase 2, 38 e-cigarette advertisements were collected from iSpot.tv and represented 11 popular e-cigarette brands. All of the advertisements tapped into the cited influences of youth e-cigarette uptake, with the most commonly cited influences (product and relational) tapping into the most, at 97\% (37/38) and 53\% (20/38), respectively. Conclusions: The findings highlight the multidimensional influences on youth uptake of e-cigarettes, which has important implications for developing effective antivaping messages, and assist public health professionals in providing more comprehensive prevention and cessation support as it relates to e-cigarette use. The findings also bring forward tangible strategies employed by e-cigarette companies to recruit youth into vaping. Understanding this is vital to the development of cohesive strategies that combat these provaping messages. ", doi="10.2196/18943", url="https://www.jmir.org/2020/8/e18943", url="http://www.ncbi.nlm.nih.gov/pubmed/32663163" } @Article{info:doi/10.2196/17048, author="Hswen, Yulin and Hawkins, B. Jared and Sewalk, Kara and Tuli, Gaurav and Williams, R. David and Viswanath, K. and Subramanian, V. S. and Brownstein, S. John", title="Racial and Ethnic Disparities in Patient Experiences in the United States: 4-Year Content Analysis of Twitter", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e17048", keywords="racial disparities", keywords="race", keywords="patient experience", keywords="policy", keywords="social media", keywords="digital epidemiology", keywords="social determinants of health", keywords="health disparities", keywords="health inequities", abstract="Background: Racial and ethnic minority groups often face worse patient experiences compared with the general population, which is directly related to poorer health outcomes within these minority populations. Evaluation of patient experience among racial and ethnic minority groups has been difficult due to lack of representation in traditional health care surveys. Objective: This study aims to assess the feasibility of Twitter for identifying racial and ethnic disparities in patient experience across the United States from 2013 to 2016. Methods: In total, 851,973 patient experience tweets with geographic location information from the United States were collected from 2013 to 2016. Patient experience tweets included discussions related to care received in a hospital, urgent care, or any other health institution. Ordinary least squares multiple regression was used to model patient experience sentiment and racial and ethnic groups over the 2013 to 2016 period and in relation to the implementation of the Patient Protection and Affordable Care Act (ACA) in 2014. Results: Racial and ethnic distribution of users on Twitter was highly correlated with population estimates from the United States Census Bureau's 5-year survey from 2016 (r2=0.99; P<.001). From 2013 to 2016, the average patient experience sentiment was highest for White patients, followed by Asian/Pacific Islander, Hispanic/Latino, and American Indian/Alaska Native patients. A reduction in negative patient experience sentiment on Twitter for all racial and ethnic groups was seen from 2013 to 2016. Twitter users who identified as Hispanic/Latino showed the greatest improvement in patient experience, with a 1.5 times greater increase (P<.001) than Twitter users who identified as White. Twitter users who identified as Black had the highest increase in patient experience postimplementation of the ACA (2014-2016) compared with preimplementation of the ACA (2013), and this change was 2.2 times (P<.001) greater than Twitter users who identified as White. Conclusions: The ACA mandated the implementation of the measurement of patient experience of care delivery. Considering that quality assessment of care is required, Twitter may offer the ability to monitor patient experiences across diverse racial and ethnic groups and inform the evaluation of health policies like the ACA. ", doi="10.2196/17048", url="http://www.jmir.org/2020/8/e17048/", url="http://www.ncbi.nlm.nih.gov/pubmed/32821062" } @Article{info:doi/10.2196/20673, author="Rovetta, Alessandro and Bhagavathula, Srikanth Akshaya", title="Global Infodemiology of COVID-19: Analysis of Google Web Searches and Instagram Hashtags", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e20673", keywords="COVID-19", keywords="coronavirus", keywords="Google", keywords="Instagram", keywords="infodemiology", keywords="infodemic", keywords="social media", abstract="Background: Although ``infodemiological'' methods have been used in research on coronavirus disease (COVID-19), an examination of the extent of infodemic moniker (misinformation) use on the internet remains limited. Objective: The aim of this paper is to investigate internet search behaviors related to COVID-19 and examine the circulation of infodemic monikers through two platforms---Google and Instagram---during the current global pandemic. Methods: We have defined infodemic moniker as a term, query, hashtag, or phrase that generates or feeds fake news, misinterpretations, or discriminatory phenomena. Using Google Trends and Instagram hashtags, we explored internet search activities and behaviors related to the COVID-19 pandemic from February 20, 2020, to May 6, 2020. We investigated the names used to identify the virus, health and risk perception, life during the lockdown, and information related to the adoption of COVID-19 infodemic monikers. We computed the average peak volume with a 95\% CI for the monikers. Results: The top six COVID-19--related terms searched in Google were ``coronavirus,'' ``corona,'' ``COVID,'' ``virus,'' ``corona virus,'' and ``COVID-19.'' Countries with a higher number of COVID-19 cases had a higher number of COVID-19 queries on Google. The monikers ``coronavirus ozone,'' ``coronavirus laboratory,'' ``coronavirus 5G,'' ``coronavirus conspiracy,'' and ``coronavirus bill gates'' were widely circulated on the internet. Searches on ``tips and cures'' for COVID-19 spiked in relation to the US president speculating about a ``miracle cure'' and suggesting an injection of disinfectant to treat the virus. Around two thirds (n=48,700,000, 66.1\%) of Instagram users used the hashtags ``COVID-19'' and ``coronavirus'' to disperse virus-related information. Conclusions: Globally, there is a growing interest in COVID-19, and numerous infodemic monikers continue to circulate on the internet. Based on our findings, we hope to encourage mass media regulators and health organizers to be vigilant and diminish the use and circulation of these infodemic monikers to decrease the spread of misinformation. ", doi="10.2196/20673", url="http://www.jmir.org/2020/8/e20673/", url="http://www.ncbi.nlm.nih.gov/pubmed/32748790" } @Article{info:doi/10.2196/17830, author="M{\"u}ller, Martin and Schneider, Manuel and Salath{\'e}, Marcel and Vayena, Effy", title="Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning", journal="J Med Internet Res", year="2020", month="Aug", day="31", volume="22", number="8", pages="e17830", keywords="CRISPR", keywords="natural language processing", keywords="sentiment analysis", keywords="digital methods", keywords="infodemiology", keywords="infoveillace", keywords="empirical bioethics", keywords="social media", abstract="Background: The discovery of the CRISPR-Cas9--based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the speed of technology development and the almost instantaneous global spread of news, it is important to follow evolving debates without much delay and in sufficient detail, as certain events may have a major long-term impact on public opinion and later influence policy decisions. Objective: Social media networks such as Twitter have shown to be major drivers of news dissemination and public discourse. They provide a vast amount of semistructured data in almost real-time and give direct access to the content of the conversations. We can now mine and analyze such data quickly because of recent developments in machine learning and natural language processing. Methods: Here, we used Bidirectional Encoder Representations from Transformers (BERT), an attention-based transformer model, in combination with statistical methods to analyze the entirety of all tweets ever published on CRISPR since the publication of the first gene editing application in 2013. Results: We show that the mean sentiment of tweets was initially very positive, but began to decrease over time, and that this decline was driven by rare peaks of strong negative sentiments. Due to the high temporal resolution of the data, we were able to associate these peaks with specific events and to observe how trending topics changed over time. Conclusions: Overall, this type of analysis can provide valuable and complementary insights into ongoing public debates, extending the traditional empirical bioethics toolset. ", doi="10.2196/17830", url="http://www.jmir.org/2020/8/e17830/", url="http://www.ncbi.nlm.nih.gov/pubmed/32865499" } @Article{info:doi/10.2196/16441, author="Hamakawa, Nao and Nakano, Rumiko and Kogetsu, Atsushi and Coathup, Victoria and Kaye, Jane and Yamamoto, Anne Beverley and Kato, Kazuto", title="Landscape of Participant-Centric Initiatives for Medical Research in the United States, the United Kingdom, and Japan: Scoping Review", journal="J Med Internet Res", year="2020", month="Aug", day="4", volume="22", number="8", pages="e16441", keywords="participant-centric initiatives", keywords="patient involvement", keywords="patient engagement", keywords="participatory research", keywords="participatory medicine", keywords="information and communication technology", keywords="patient participation", abstract="Background: Information and communication technology (ICT) has made remarkable progress in recent years and is being increasingly applied to medical research. This technology has the potential to facilitate the active involvement of research participants. Digital platforms that enable participants to be involved in the research process are called participant-centric initiatives (PCIs). Several PCIs have been reported in the literature, but no scoping reviews have been carried out. Moreover, detailed methods and features to aid in developing a clear definition of PCIs have not been sufficiently elucidated to date. Objective: The objective of this scoping review is to describe the recent trends in, and features of, PCIs across the United States, the United Kingdom, and Japan. Methods: We applied a methodology suggested by Levac et al to conduct this scoping review. We searched electronic databases---MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase (Excerpta Medica Database), CINAHL (Cumulative Index of Nursing and Allied Health Literature), PsycINFO, and Ichushi-Web---and sources of grey literature, as well as internet search engines---Google and Bing. We hand-searched through key journals and reference lists of the relevant articles. Medical research using ICT was eligible for inclusion if there was a description of the active involvement of the participants. Results: Ultimately, 21 PCIs were identified that have implemented practical methods and modes of various communication activities, such as patient forums and use of social media, in the field of medical research. Various methods of decision making that enable participants to become involved in setting the agenda were also evident. Conclusions: This scoping review is the first study to analyze the detailed features of PCIs and how they are being implemented. By clarifying the modes and methods of various forms of communication and decision making with patients, this review contributes to a better understanding of patient-centric involvement, which can be facilitated by PCIs. International Registered Report Identifier (IRRID): RR2-10.2196/resprot.7407 ", doi="10.2196/16441", url="https://www.jmir.org/2020/8/e16441", url="http://www.ncbi.nlm.nih.gov/pubmed/32749228" } @Article{info:doi/10.2196/19745, author="Peine, Arne and Paffenholz, Pia and Martin, Lukas and Dohmen, Sandra and Marx, Gernot and Loosen, H. Sven", title="Telemedicine in Germany During the COVID-19 Pandemic: Multi-Professional National Survey", journal="J Med Internet Res", year="2020", month="Aug", day="5", volume="22", number="8", pages="e19745", keywords="telemedicine", keywords="coronavirus", keywords="COVID-19", keywords="telehealth", keywords="SARS-CoV-2", keywords="pandemic", keywords="survey", keywords="medical professional", keywords="availability", keywords="acceptance", keywords="burden", abstract="Background: In an effort to contain the effects of the coronavirus disease (COVID-19) pandemic, health care systems worldwide implemented telemedical solutions to overcome staffing, technical, and infrastructural limitations. In Germany, a multitude of telemedical systems are already being used, while new approaches are rapidly being developed in response to the crisis. However, the extent of the current implementation within different health care settings, the user's acceptance and perception, as well as the hindering technical and regulatory obstacles remain unclear. Objective: The aim of this paper is to assess the current status quo of the availability and routine use of telemedical solutions, user acceptance, and the subjectively perceived burdens on telemedical approaches. Furthermore, we seek to assess the perception of public information quality among professional groups and their preferred communication channels. Methods: A national online survey was conducted on 14 consecutive days in March and April 2020, and distributed to doctors, nurses, and other medical professionals in the German language. Results: A total of 2827 medical professionals participated in the study. Doctors accounted for 65.6\% (n=1855) of the professionals, 29.5\% (n=833) were nursing staff, and 4.9\% (n=139) were identified as others such as therapeutic staff. A majority of participants rated the significance of telemedicine within the crisis as high (1065/2730, 39\%) or neutral (n=720, 26.4\%); however, there were significant differences between doctors and nurses (P=.01) as well as between the stationary sector compared to the ambulatory sector (P<.001). Telemedicine was already in routine use for 19.6\% (532/2711) of German health care providers and in partial use for 40.2\% (n=1090). Participants working in private practices (239/594, 40.2\%) or private clinics (23/59, 39.0\%) experienced less regulatory or technical obstacles compared to university hospitals (586/1190, 49.2\%). A majority of doctors rated the public information quality on COVID-19 as good (942/1855, 50.8\%) or very good (213/1855, 11.5\%); nurses rated the quality of public information significantly lower (P<.001). Participant's age negatively correlated with the perception of telemedicine's significance ($\rho$=--0.23; P<.001). Conclusions: Telemedicine has a broad acceptance among German medical professionals. However, to establish telemedical structures within routine care, technical and regulatory burdens must be overcome. ", doi="10.2196/19745", url="https://www.jmir.org/2020/8/e19745", url="http://www.ncbi.nlm.nih.gov/pubmed/32568724" } @Article{info:doi/10.2196/18178, author="D'Haeseleer, Miguel and Eelen, Piet and Sadeghi, Nima and D'Hooghe, B. Marie and Van Schependom, Jeroen and Nagels, Guy", title="Feasibility of Real Time Internet-Based Teleconsultation in Patients With Multiple Sclerosis: Interventional Pilot Study", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e18178", keywords="multiple sclerosis", keywords="teleconsultation", keywords="internet", keywords="feasibility", keywords="eHealth", abstract="Background: Telemedicine (TM) is currently flourishing in rural and emergency settings, but its implementation in the routine management of chronic neurological disorders has developed with more hesitation. Limited access to specialized care facilities and expanding patient populations, combined with unprecedented mobility restrictions imposed by the coronavirus disease pandemic, are currently stressing the need for remote solutions in this field. Studies in patients with multiple sclerosis (MS) have been heterogeneous in objectives and methodology but generally support the concept that TM interventions produce clinical benefits, cost-effectiveness, and user satisfaction. Nonetheless, data on live interaction between patients and health care providers for MS teleconsultation purposes remain scarce. Objective: The aim of this study is to demonstrate the feasibility of planned real time audiovisual teleconsultation over the internet for patients with MS. Methods: A total of 20 patients with MS presenting at a specialized MS center in Belgium were recruited for this study. One teleconsultation was scheduled for each participant. Patients were provided a unique hyperlink by mail in advance, leading them automatically and directly to the virtual waiting room, where they could accept or decline our incoming call. All teleconsultations were performed by a trained medical student with the intention to keep the conversation similar to what is usually discussed during a classic face-to-face MS consultation; no remote physical exams were performed. The approach was considered feasible if at least 80\% of the planned TM visits could be successfully completed at the foreseen moment. Patient satisfaction (technical quality, convenience, and overall quality of care) was evaluated at the end of each teleconsultation by means of 5-point Likert scales containing the categories very unsatisfied, unsatisfied, neutral, satisfied, and highly satisfied. Results: Out of 20 consultations, 17 were successfully completed (85\%). Failures were due to patients not responding (n=2) and technical issues (n=1). Out of the 17 consultations, 17 patients declared themselves satisfied or highly satisfied for technical quality, 15 patients for convenience, and 16 patients for overall quality of care. Conclusions: Planned real time audiovisual teleconsultation over the internet is feasible and highly appreciated in patients with MS. Incorporation of such services in routine clinical MS practice is expected to improve access to specialized care facilities for affected patients. ", doi="10.2196/18178", url="https://www.jmir.org/2020/8/e18178", url="http://www.ncbi.nlm.nih.gov/pubmed/32447274" } @Article{info:doi/10.2196/21778, author="Majithia, R. Amit and Kusiak, M. Coco and Armento Lee, Amy and Colangelo, R. Francis and Romanelli, J. Robert and Robertson, Scott and Miller, P. David and Erani, M. David and Layne, E. Jennifer and Dixon, F. Ronald and Zisser, Howard", title="Glycemic Outcomes in Adults With Type 2 Diabetes Participating in a Continuous Glucose Monitor--Driven Virtual Diabetes Clinic: Prospective Trial", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e21778", keywords="continuous glucose monitoring", keywords="telemedicine", keywords="telehealth", keywords="digital health", keywords="type 2 diabetes", keywords="HbA1c", abstract="Background: The Onduo virtual diabetes clinic (VDC) for people with type 2 diabetes (T2D) combines a mobile app, remote personalized lifestyle coaching, connected devices, and live video consultations with board-certified endocrinologists for medication management and prescription of real-time continuous glucose monitoring (RT-CGM) devices for intermittent use. Objective: This prospective single-arm study evaluated glycemic outcomes associated with participation in the Onduo VDC for 4 months. Methods: Adults aged ?18 years with T2D and a baseline glycated hemoglobin (HbA1c) of ?8\% to ?12\% were enrolled from 2 primary care centers from February 2019 to October 2019. Participants were asked to engage at ?1 time per week with their care team and to participate in a telemedicine consultation with a clinic endocrinologist for diabetes medication review. Participants were asked to use a RT-CGM device and wear six 10-day sensors (total 60 days of sensor wear) intermittently over the course of 4 months. The primary outcome was change in HbA1c at 4 months from baseline. Other endpoints included change in weight and in RT-CGM glycemic metrics, including percent time <70, 70-180, 181-250, and >250 mg/dL. Changes in blood pressure and serum lipids at 4 months were also evaluated. Results: Participants (n=55) were 57.3 (SD 11.6) years of age, body mass index 33.7 (SD 7.2), and 40\% (22/55) female. HbA1c decreased significantly by 1.6\% (SD 1\%; P<.001). When stratified by baseline HbA1c of 8.0\% to 9.0\% (n=36) and >9.0\% (n=19), HbA1c decreased by 1.2\% (SD 0.6\%; P<.001) and 2.4\% (SD 1.3\%; P<.001), respectively. Continuous glucose monitoring--measured (n=43) percent time in range (TIR) 70-180 mg/dL increased by 10.2\% (SD 20.5\%; P=.002), from 65.4\% (SD 23.2\%) to 75.5\% (SD 22.7\%), which was equivalent to a mean increase of 2.4 hours TIR per day. Percent time 181-250 mg/dL and >250 mg/dL decreased by 7.2\% (SD 15.4; P=.005) and 3.0\% (SD 9.4; P=.01), respectively. There was no change in percent time <70 mg/dL. Mean weight decreased by 9.0 lb (SD 10.4; P<.001). Significant improvements were also observed in systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, and triglycerides (P=.04 to P=<.001). Conclusions: Participants in the Onduo VDC experienced significant improvement in HbA1c, increased TIR, decreased time in hyperglycemia, and no increase in hypoglycemia at 4 months. Improvements in other metabolic health parameters including weight and blood pressure were also observed. In conclusion, the Onduo VDC has potential to support people with T2D and their clinicians between office visits by increasing access to specialty care and advanced diabetes technology including RT-CGM. Trial Registration: ClinicalTrials.gov NCT03865381; https://clinicaltrials.gov/ct2/show/NCT03865381 ", doi="10.2196/21778", url="https://www.jmir.org/2020/8/e21778", url="http://www.ncbi.nlm.nih.gov/pubmed/32856597" } @Article{info:doi/10.2196/17686, author="Liao, Chien-Hung and Wu, Yu-Tung and Cheng, Chi-Tung and Ooyang, Chun-Hsiang and Kang, Shih-Ching and Fu, Chih-Yuan and Hsu, Yu-Pao and Hsieh, Chi-Hsun and Chen, Chih-Chi", title="An Image-Based Mobile Health App for Postdrainage Monitoring: Usability Study", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e17686", keywords="telemedicine", keywords="smartphone", keywords="surgical drainage", keywords="postdrainage care, mHealth", abstract="Background: The application of mobile health (mHealth) platforms to monitor recovery in the postdischarge period has increased in recent years. Despite widespread enthusiasm for mHealth, few studies have evaluated the usability and user experience of mHealth in patients with surgical drainage. Objective: Our objectives were to (1) develop an image-based smartphone app, SurgCare, for postdrainage monitoring and (2) determine the feasibility and clinical value of the use of SurgCare by patients with drainage. Methods: We enrolled 80 patients with biliary or peritoneal drainage in this study. A total of 50 patients were assigned to the SurgCare group, who recorded drainage monitoring data with the smartphone app; and 30 patients who manually recorded the data were assigned to the conventional group. The patients continued to record data until drain removal. The primary aim was to validate feasibility for the user, which was defined as the proportion of patients using each element of the system. Moreover, the secondary aim was to evaluate the association of compliance with SurgCare and the occurrence of unexpected events. Results: The average submission duration was 14.98 days, and the overall daily submission rate was 84.2\%. The average system usability scale was 83.7 (SD 3.5). This system met the definition of ``definitely feasible'' in 34 patients, ``possibly feasible'' in 10 patients, and ``not feasible'' in 3 patients. We found that the occurrence rates of complications in the SurgCare group and the conventional group were 6\% and 26\%, respectively, with statistically significant differences P=.03. The rate of unexpected hospital return was lower in the SurgCare group (6\%) than in the conventional groups (26\%) (P=.03). Conclusions: Patients can learn to use a smartphone app for postdischarge drainage monitoring with high levels of user satisfaction. We also identified a high degree of compliance with app-based drainage-recording design features, which is an aspect of mHealth that can improve surgical care. ", doi="10.2196/17686", url="http://www.jmir.org/2020/8/e17686/", url="http://www.ncbi.nlm.nih.gov/pubmed/32857060" } @Article{info:doi/10.2196/17504, author="Eeg-Olofsson, Katarina and Johansson, Unn-Britt and Linder, Ebba and Leksell, Janeth", title="Patients' and Health Care Professionals' Perceptions of the Potential of Using the Digital Diabetes Questionnaire to Prepare for Diabetes Care Meetings: Qualitative Focus Group Interview Study", journal="J Med Internet Res", year="2020", month="Aug", day="19", volume="22", number="8", pages="e17504", keywords="Digital questionnaire", keywords="health care professionals", keywords="diabetes care", keywords="focus group interview", keywords="qualitative research", keywords="eHealth\emspace", abstract="Background: In effective diabetes management, it is important that providers and health care systems prioritize the delivery of patient-centered care and that they are respectful of and responsive to individual patient preferences and barriers. Objective: The objective of the study was to conduct focus group interviews to capture patients' and health care professionals' perceptions and attitudes regarding digital technology and to explore how the digital Diabetes Questionnaire can be used to support patient participation in diabetes care, as a basis for an implementation study. Methods: A qualitative study was conducted with six focus group discussions with diabetes specialist nurses and medical doctors (n=29) and four focus group discussions with individuals with diabetes (n=23). A semistructured focus group interview guide was developed, including probing questions. The data were transcribed verbatim, and qualitative content analysis was performed using an inductive approach. Results: Two main categories were revealed by the qualitative analysis: perceptions of digital technology and the digital questionnaire in diabetes management and care and perceptions of participation in diabetes care. An overarching theme that emerged from the focus group interviews was patients' and professionals' involvement in diabetes care using digital tools. Conclusions: The analysis identified important factors to consider when introducing the digital Diabetes Questionnaire in clinical use. Both professionals and patients need support and training in the practical implementation of the digital questionnaire, as well as the opportunity to provide feedback on the questionnaire answers. ", doi="10.2196/17504", url="https://www.jmir.org/2020/8/e17504", url="http://www.ncbi.nlm.nih.gov/pubmed/32812884" } @Article{info:doi/10.2196/19350, author="Fern{\'a}ndez, C{\'e}sar and Vicente, Asunci{\'o}n Mar{\'i}a and Carrillo, Irene and Guilabert, Mercedes and Mira, Joaqu{\'i}n Jos{\'e}", title="Factors Influencing the Smartphone Usage Behavior of Pedestrians: Observational Study on ``Spanish Smombies''", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e19350", keywords="smartphone addiction", keywords="smartphone overuse", keywords="smombies", keywords="pedestrian safety", keywords="mobile phone", abstract="Background: Smartphone addiction has become a reality accepted by all. Some previous studies have shown that the use of smartphones on public roads while walking is very common among the young population. The term ``smombie'' or smartphone zombie has been coined for this behavior. Such behavior causes a reduction in the attention given to other pedestrians and drivers and may result in accidents or collisions. However, there are no precise data about how many people use the phone while they are walking on the street. Smartphone usage habits are evolving rapidly, and more in-depth information is required, particularly about how users interact with their devices while walking: traditional phone conversations (phone close to the ear), voice chats (phone in front of the head), waiting for notifications (phone in hand), text chats (user touching the screen), etc. This in-depth information may be useful for carrying out specific preventive actions in both the education field (raising awareness about the risks) and in the infrastructure field (redesigning the cities to increase safety). Objective: This study aimed to gather information about pedestrians' smartphone usage and to identify population groups wherein interventions should be focused to prevent accidents. The main hypothesis was that gender, age, and city area can significantly influence the smartphone usage of the pedestrians while walking. Methods: An observational study of pedestrians in the street was carried out in Elche, a medium-sized Spanish city of 230,000 inhabitants. The following data were gathered: gender, age group, location, and type of smartphone interaction. A specific smartphone app was developed to acquire data with high reliability. The statistical significance of each variable was evaluated using chi-squared tests, and Cram{\'e}r's V statistic was used to measure the effect sizes. Observer agreement was checked by the Cohen kappa analysis. Results: The behavior of 3301 pedestrians was analyzed, of which 1770 (53.6\%) were females. As expected, the effect of the main variables studied was statistically significant, although with a small effect size: gender (P<.001, V=0.12), age (P<.001, V=0.18), and city area (P<.001, V=0.16). The phone in hand or ``holding'' behavior was particularly dependent on gender for all age groups (P<.001, V=0.09) and to a greater extent in young people (P<.001, V=0.16). Approximately 39.7\% (222/559) of the young women observed showed ``holding'' or ``smombie'' behavior, and they comprised the highest proportion among all age and gender groups. Conclusions: An in-depth analysis of smartphone usage while walking revealed that certain population groups (especially young women) have a high risk of being involved in accidents due to smartphone usage. Interventions aimed at reducing the risk of falls and collisions should be focused in these groups. ", doi="10.2196/19350", url="http://www.jmir.org/2020/8/e19350/", url="http://www.ncbi.nlm.nih.gov/pubmed/32667896" } @Article{info:doi/10.2196/20261, author="Wang, Hsin-Yao and Lin, Ting-Wei and Chiu, Yueh-Hsia Sherry and Lin, Wan-Ying and Huang, Song-Bin and Hsieh, Chia-Hsun Jason and Chen, Cheng Hsieh and Lu, Jang-Jih and Wu, Min-Hsien", title="Novel Toilet Paper--Based Point-Of-Care Test for the Rapid Detection of Fecal Occult Blood: Instrument Validation Study", journal="J Med Internet Res", year="2020", month="Aug", day="7", volume="22", number="8", pages="e20261", keywords="fecal occult blood test", keywords="point-of-care diagnostics", keywords="paper-based analytical devices", keywords="diagnostic", keywords="testing", keywords="detection", keywords="validation", keywords="cancer", keywords="public health", abstract="Background: Colorectal cancer screening by fecal occult blood testing has been an important public health test and shown to reduce colorectal cancer--related mortality. However, the low participation rate in colorectal cancer screening by the general public remains a problematic public health issue. This fact could be attributed to the complex and unpleasant operation of the screening tool. Objective: This study aimed to validate a novel toilet paper--based point-of-care test (ie, JustWipe) as a public health instrument to detect fecal occult blood and provide detailed results from the evaluation of the analytic characteristics in the clinical validation. Methods: The mechanism of fecal specimen collection by the toilet-paper device was verified with repeatability and reproducibility tests. We also evaluated the analytical characteristics of the test reagents. For clinical validation, we conducted comparisons between JustWipe and other fecal occult blood tests. The first comparison was between JustWipe and typical fecal occult blood testing in a central laboratory setting with 70 fecal specimens from the hospital. For the second comparison, a total of 58 volunteers were recruited, and JustWipe was compared with the commercially available Hemoccult SENSA in a point-of-care setting. Results: Adequate amounts of fecal specimens were collected using the toilet-paper device with small day-to-day and person-to-person variations. The limit of detection of the test reagent was evaluated to be 3.75 {\textmu}g of hemoglobin per milliliter of reagent. Moreover, the test reagent also showed high repeatability (100\%) on different days and high reproducibility (>96\%) among different users. The overall agreement between JustWipe and a typical fecal occult blood test in a central laboratory setting was 82.9\%. In the setting of point-of-care tests, the overall agreement between JustWipe and Hemoccult SENSA was 89.7\%. Moreover, the usability questionnaire showed that the novel test tool had high scores in operation friendliness (87.3/100), ease of reading results (97.4/100), and information usefulness (96.1/100). Conclusions: We developed and validated a toilet paper--based fecal occult blood test for use as a point-of-care test for the rapid (in 60 seconds) and easy testing of fecal occult blood. These favorable characteristics render it a promising tool for colorectal cancer screening as a public health instrument. ", doi="10.2196/20261", url="https://www.jmir.org/2020/8/e20261", url="http://www.ncbi.nlm.nih.gov/pubmed/32763879" } @Article{info:doi/10.2196/18911, author="Woldaregay, Zebene Ashenafi and Launonen, Kalervo Ilkka and {\AA}rsand, Eirik and Albers, David and Holubov{\'a}, Anna and Hartvigsen, Gunnar", title="Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e18911", keywords="type 1 diabetes", keywords="self-recorded health data", keywords="infection incidence", keywords="decision making", keywords="infectious disease outbreaks", keywords="public health surveillance", abstract="Background: Type 1 diabetes is a chronic condition of blood glucose metabolic disorder caused by a lack of insulin secretion from pancreas cells. In people with type 1 diabetes, hyperglycemia often occurs upon infection incidences. Despite the fact that patients increasingly gather data about themselves, there are no solid findings that uncover the effect of infection incidences on key parameters of blood glucose dynamics to support the effort toward developing a digital infectious disease detection system. Objective: The study aims to retrospectively analyze the effect of infection incidence and pinpoint optimal parameters that can effectively be used as input variables for developing an infection detection algorithm and to provide a general framework regarding how a digital infectious disease detection system can be designed and developed using self-recorded data from people with type 1 diabetes as a secondary source of information. Methods: We retrospectively analyzed high precision self-recorded data of 10 patient-years captured within the longitudinal records of three people with type 1 diabetes. Obtaining such a rich and large data set from a large number of participants is extremely expensive and difficult to acquire, if not impossible. The data set incorporates blood glucose, insulin, carbohydrate, and self-reported events of infections. We investigated the temporal evolution and probability distribution of the key blood glucose parameters within a specified timeframe (weekly, daily, and hourly). Results: Our analysis demonstrated that upon infection incidence, there is a dramatic shift in the operating point of the individual blood glucose dynamics in all the timeframes (weekly, daily, and hourly), which clearly violates the usual norm of blood glucose dynamics. During regular or normal situations, higher insulin and reduced carbohydrate intake usually results in lower blood glucose levels. However, in all infection cases as opposed to the regular or normal days, blood glucose levels were elevated for a prolonged period despite higher insulin and reduced carbohydrates intake. For instance, compared with the preinfection and postinfection weeks, on average, blood glucose levels were elevated by 6.1\% and 16\%, insulin (bolus) was increased by 42\% and 39.3\%, and carbohydrate consumption was reduced by 19\% and 28.1\%, respectively. Conclusions: We presented the effect of infection incidence on key parameters of blood glucose dynamics along with the necessary framework to exploit the information for realizing a digital infectious disease detection system. The results demonstrated that compared with regular or normal days, infection incidence substantially alters the norm of blood glucose dynamics, which are quite significant changes that could possibly be detected through personalized modeling, for example, prediction models and anomaly detection algorithms. Generally, we foresee that these findings can benefit the efforts toward building next generation digital infectious disease detection systems and provoke further thoughts in this challenging field. ", doi="10.2196/18911", url="https://www.jmir.org/2020/8/e18911", url="http://www.ncbi.nlm.nih.gov/pubmed/32784178" } @Article{info:doi/10.2196/18912, author="Woldaregay, Zebene Ashenafi and Launonen, Kalervo Ilkka and Albers, David and Igual, Jorge and {\AA}rsand, Eirik and Hartvigsen, Gunnar", title="A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e18912", keywords="type 1 diabetes", keywords="self-recorded health data", keywords="infection detection", keywords="decision support techniques", keywords="outbreak detection system", keywords="syndromic surveillance", abstract="Background: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a given data set. Specifically, these methods are popular in the medical domain because of their suitability for applications where there is a lack of a sufficient data set for the other classes. Infection incidence often brings prolonged hyperglycemia and frequent insulin injections in people with type 1 diabetes, which are significant anomalies. Despite these potentials, there have been very few studies that focused on detecting infection incidences in individuals with type 1 diabetes using a dedicated personalized health model. Objective: This study aims to develop a personalized health model that can automatically detect the incidence of infection in people with type 1 diabetes using blood glucose levels and insulin-to-carbohydrate ratio as input variables. The model is expected to detect deviations from the norm because of infection incidences considering elevated blood glucose levels coupled with unusual changes in the insulin-to-carbohydrate ratio. Methods: Three groups of one-class classifiers were trained on target data sets (regular days) and tested on a data set containing both the target and the nontarget (infection days). For comparison, two unsupervised models were also tested. The data set consists of high-precision self-recorded data collected from three real subjects with type 1 diabetes incorporating blood glucose, insulin, diet, and events of infection. The models were evaluated on two groups of data: raw and filtered data and compared based on their performance, computational time, and number of samples required. Results: The one-class classifiers achieved excellent performance. In comparison, the unsupervised models suffered from performance degradation mainly because of the atypical nature of the data. Among the one-class classifiers, the boundary and domain-based method produced a better description of the data. Regarding the computational time, nearest neighbor, support vector data description, and self-organizing map took considerable training time, which typically increased as the sample size increased, and only local outlier factor and connectivity-based outlier factor took considerable testing time. Conclusions: We demonstrated the applicability of one-class classifiers and unsupervised models for the detection of infection incidence in people with type 1 diabetes. In this patient group, detecting infection can provide an opportunity to devise tailored services and also to detect potential public health threats. The proposed approaches achieved excellent performance; in particular, the boundary and domain-based method performed better. Among the respective groups, particular models such as one-class support vector machine, K-nearest neighbor, and K-means achieved excellent performance in all the sample sizes and infection cases. Overall, we foresee that the results could encourage researchers to examine beyond the presented features into other additional features of the self-recorded data, for example, continuous glucose monitoring features and physical activity data, on a large scale. ", doi="10.2196/18912", url="https://www.jmir.org/2020/8/e18912", url="http://www.ncbi.nlm.nih.gov/pubmed/32784179" } @Article{info:doi/10.2196/18136, author="Kim, Woon Ko and Lee, Yun Sung and Choi, Jongdoo and Chin, Juhee and Lee, Hwa Byung and Na, L. Duk and Choi, Hyun Jee", title="A Comprehensive Evaluation of the Process of Copying a Complex Figure in Early- and Late-Onset Alzheimer Disease: A Quantitative Analysis of Digital Pen Data", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e18136", keywords="alzheimer disease", keywords="Rey-Osterrieth Complex Figure", keywords="digital biomarkers", keywords="copying process", abstract="Background: The Rey-Osterrieth Complex Figure Test (RCFT) is a neuropsychological test that is widely used to assess visual memory and visuoconstructional deficits in patients with cognitive impairment, including Alzheimer disease (AD). Patients with AD have an increased tendency for exhibiting extraordinary behaviors in the RCFT for selecting the drawing area, organizing the figure, and deciding the order of images, among other activities. However, the conventional scoring system based on pen and paper has a limited ability to reflect these detailed behaviors. Objective: This study aims to establish a scoring system that addresses not only the spatial arrangement of the finished drawing but also the drawing process of patients with AD by using digital pen data. Methods: A digital pen and tablet were used to copy complex figures. The stroke patterns and kinetics of normal controls (NCs) and patients with early-onset AD (EOAD) and late-onset AD (LOAD) were analyzed by comparing the pen tip trajectory, spatial arrangement, and similarity of the finished drawings. Results: Patients with AD copied the figure in a more fragmented way with a longer pause than NCs (EOAD: P=.045; LOAD: P=.01). Patients with AD showed an increased tendency to draw the figures closer toward the target image in comparison with the NCs (EOAD: P=.005; LOAD: P=.01) Patients with AD showed the lower accuracy than NCs (EOAD: P=.004; LOAD: P=.002). Patients with EOAD and LOAD showed similar but slightly different drawing behaviors, especially in space use and in the initial stage of drawing. Conclusions: The digitalized complex figure test evaluated copying performance quantitatively and further elucidated the patients' ongoing process during copying. We believe that this novel approach can be used as a digital biomarker of AD. In addition, the repeatability of the test will delineate the process of executive functions and constructional organization abilities with disease progression. ", doi="10.2196/18136", url="https://www.jmir.org/2020/8/e18136", url="http://www.ncbi.nlm.nih.gov/pubmed/32491988" } @Article{info:doi/10.2196/17719, author="Grima-Murcia, D. M. and Sanchez-Ferrer, Francisco and Ramos-Rinc{\'o}n, Manuel Jose and Fern{\'a}ndez, Eduardo", title="Use of Eye-Tracking Technology by Medical Students Taking the Objective Structured Clinical Examination: Descriptive Study", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e17719", keywords="visual perception", keywords="medical education", keywords="eye tracking", keywords="objective structured clinical examination", keywords="medical evaluation", abstract="Background: The objective structured clinical examination (OSCE) is a test used throughout Spain to evaluate the clinical competencies, decision making, problem solving, and other skills of sixth-year medical students. Objective: The main goal of this study is to explore the possible applications and utility of portable eye-tracking systems in the setting of the OSCE, particularly questions associated with attention and engagement. Methods: We used a portable Tobii Glasses 2 eye tracker, which allows real-time monitoring of where the students were looking and records the voice and ambient sounds. We then performed a qualitative and a quantitative analysis of the fields of vision and gaze points attracting attention as well as the visual itinerary. Results: Eye-tracking technology was used in the OSCE with no major issues. This portable system was of the greatest value in the patient simulators and mannequin stations, where interaction with the simulated patient or areas of interest in the mannequin can be quantified. This technology proved useful to better identify the areas of interest in the medical images provided. Conclusions: Portable eye trackers offer the opportunity to improve the objective evaluation of candidates and the self-evaluation of the stations used as well as medical simulations by examiners. We suggest that this technology has enough resolution to identify where a student is looking at and could be useful for developing new approaches for evaluating specific aspects of clinical competencies. ", doi="10.2196/17719", url="http://www.jmir.org/2020/8/e17719/", url="http://www.ncbi.nlm.nih.gov/pubmed/32821060" } @Article{info:doi/10.2196/17718, author="Jurkeviciute, Monika and Eriksson, Henrik", title="Exploring the Use of Evidence From the Development and Evaluation of an Electronic Health (eHealth) Trial: Case Study", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e17718", keywords="evidence-based practice", keywords="evidence use", keywords="eHealth", keywords="evaluation", keywords="evaluation use", abstract="Background: Evidence-based practice refers to building clinical decisions on credible research evidence, professional experience, and patient preferences. However, there is a growing concern that evidence in the context of electronic health (eHealth) is not sufficiently used when forming policies and practice of health care. In this context, using evaluation and research evidence in clinical or policy decisions dominates the discourse. However, the use of additional types of evidence, such as professional experience, is underexplored. Moreover, there might be other ways of using evidence than in clinical or policy decisions. Objective: This study aimed to analyze how different types of evidence (such as evaluation outcomes [including patient preferences], professional experiences, and existing scientific evidence from other research) obtained within the development and evaluation of an eHealth trial are used by diverse stakeholders. An additional aim was to identify barriers to the use of evidence and ways to support its use. Methods: This study was built on a case of an eHealth trial funded by the European Union. The project included 4 care centers, 2 research and development companies that provided the web-based physical exercise program and an activity monitoring device, and 2 science institutions. The qualitative data collection included 9 semistructured interviews conducted 8 months after the evaluation was concluded. The data analysis concerned (1) activities and decisions that were made based on evidence after the project ended, (2) evidence used for those activities and decisions, (3) in what way the evidence was used, and (4) barriers to the use of evidence. Results: Evidence generated from eHealth trials can be used by various stakeholders for decisions regarding clinical integration of eHealth solutions, policy making, scientific publishing, research funding applications, eHealth technology, and teaching. Evaluation evidence has less value than professional experiences to local decision making regarding eHealth integration into clinical practice. Professional experiences constitute the evidence that is valuable to the highest variety of activities and decisions in relation to eHealth trials. When using existing scientific evidence related to eHealth trials, it is important to consider contextual relevance, such as location or disease. To support the use of evidence, it is suggested to create possibilities for health care professionals to gain experience, assess a few rather than a large number of variables, and design for shorter iterative cycles of evaluation. Conclusions: Initiatives to support and standardize evidence-based practice in the context of eHealth should consider the complexities in how the evidence is used in order to achieve better uptake of evidence in practice. However, one should be aware that the assumption of fact-based decision making in organizations is misleading. In order to create better chances that the evidence produced would be used, this should be addressed through the design of eHealth trials. ", doi="10.2196/17718", url="http://www.jmir.org/2020/8/e17718/", url="http://www.ncbi.nlm.nih.gov/pubmed/32857057" } @Article{info:doi/10.2196/19028, author="Bonner, Carissa and Raffoul, Natalie and Battaglia, Tanya and Mitchell, Anne Julie and Batcup, Carys and Stavreski, Bill", title="Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey", journal="J Med Internet Res", year="2020", month="Aug", day="7", volume="22", number="8", pages="e19028", keywords="heart age", keywords="risk communication", keywords="cardiovascular disease prevention", keywords="eHealth", keywords="behavior change", abstract="Background: Heart age calculators are used worldwide to engage the public in cardiovascular disease (CVD) prevention. Experimental studies with small samples have found mixed effects of these tools, and previous reports of population samples that used web-based heart age tools have not evaluated psychological and behavioral outcomes. Objective: This study aims to report on national users of the Australian heart age calculator and the follow-up of a sample of users. Methods: The heart age calculator was launched in 2019 by the National Heart Foundation of Australia. Heart age results were calculated for all users and recorded for those who signed up for a heart age report and an email follow-up over 10 weeks, after which a survey was conducted. CVD risk factors, heart age results, and psychological and behavioral questions were analyzed using descriptive statistics and chi-square tests. Open responses were thematically coded. Results: There were 361,044 anonymous users over 5 months, of which 30,279 signed up to receive a heart age report and 1303 completed the survey. There were more women (19,840/30,279, 65.52\%), with an average age of 55.67 (SD 11.43) years, and most users knew blood pressure levels (20,279/30,279, 66.97\%) but not cholesterol levels (12,267/30,279, 40.51\%). The average heart age result was 4.61 (SD 4.71) years older than the current age, including (23,840/30,279, 78.73\%) with an older heart age. For the survey, most users recalled their heart age category (892/1303, 68.46\%), and many reported lifestyle improvements (diet 821/1303, 63.01\% and physical activity 809/1303, 62.09\%). People with an older heart age result were more likely to report a doctor visit (538/1055, 51.00\%). Participants indicated strong emotional responses to heart age, both positive and negative. Conclusions: Most Australian users received an older heart age as per international and UK heart age tools. Heart age reports with follow-up over 10 weeks prompted strong emotional responses, high recall rates, and self-reported lifestyle changes and clinical checks for more than half of the survey respondents. These findings are based on a more engaged user sample than previous research, who were more likely to know blood pressure and cholesterol values. Further research is needed to determine which aspects are most effective in initiating and maintaining lifestyle changes. The results confirm high public interest in heart age tools, but additional support is needed to help users understand the results and take appropriate action. ", doi="10.2196/19028", url="https://www.jmir.org/2020/8/e19028", url="http://www.ncbi.nlm.nih.gov/pubmed/32763875" } @Article{info:doi/10.2196/15899, author="B{\"u}chter, B. Roland and Betsch, Cornelia and Ehrlich, Martina and Fechtelpeter, Dennis and Grouven, Ulrich and Keller, Sabine and Meuer, Regina and Rossmann, Constanze and Waltering, Andreas", title="Communicating Uncertainty in Written Consumer Health Information to the Public: Parallel-Group, Web-Based Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e15899", keywords="uncertainty", keywords="consumer health information", keywords="decision making", abstract="Background: Uncertainty is integral to evidence-informed decision making and is of particular importance for preference-sensitive decisions. Communicating uncertainty to patients and the public has long been identified as a goal in the informed and shared decision-making movement. Despite this, there is little quantitative research on how uncertainty in health information is perceived by readers. Objective: The aim of this study was to examine the impact of different uncertainty descriptions regarding the evidence for a treatment effect in a written research summary for the public. Methods: We developed 8 versions of a research summary on a fictitious drug for tinnitus with varying degrees (Q1), sources (Q2), and magnitudes of uncertainty (Q3). We recruited 2099 members of the German public from a web-based research panel. Of these, 1727 fulfilled the inclusion criteria and were randomly presented with one of these research summaries. Randomization was conducted by using a centralized computer with a random number generator. Web-based recruitment and data collection were fully automated. Participants were not aware of the purpose of the study and alternative presentations. We measured the following outcomes: perception of the treatment effectiveness (primary), certainty in the judgement of treatment effectiveness, perception of the body of evidence, text quality, and intended decision. The outcomes were self-assessed. Results: For the primary outcome, we did not find a global effect for Q1 and Q2 (P=.25 and P=.73), but we found a global effect for Q3 (P=.048). Pairwise comparisons showed a weaker perception of treatment effectiveness for the research summary with 3 sources of uncertainty compared to the version with 2 sources of uncertainty (P=.04). Specifically, the proportion of the participants in the group with 3 sources of uncertainty that perceived the drug as possibly beneficial was 9\% lower than that of the participants in the group with 2 sources of uncertainty (92/195, 47.2\% vs 111/197, 56.3\%, respectively). The proportion of the participants in the group with 3 sources of uncertainty that considered the drug to be of unclear benefit was 8\% higher than that of the participants in the group with 2 sources of uncertainty (72/195, 36.9\% vs 57/197, 28.9\%, respectively). However, there was no significant difference compared to the version with 1 source of uncertainty (P=.31). We did not find any meaningful differences between the research summaries for the secondary outcomes. Conclusions: Communicating even a large magnitude of uncertainty for a treatment effect had little impact on the perceived effectiveness. Efforts to improve public understanding of research are needed to improve the understanding of evidence-based health information. Trial Registration: German Clinical Trials Register DRKS00015911, https://www.drks.de/drks\_web/navigate.do?navigationId=trial.HTML\&TRIAL\_ID=DRKS00015911 International Registered Report Identifier (IRRID): RR2-10.2196/13425 ", doi="10.2196/15899", url="http://www.jmir.org/2020/8/e15899/", url="http://www.ncbi.nlm.nih.gov/pubmed/32773375" } @Article{info:doi/10.2196/18684, author="Yamaguchi, Yoichiro and Lee, Deokcheol and Nagai, Takuya and Funamoto, Taro and Tajima, Takuya and Chosa, Etsuo", title="Googling Musculoskeletal-Related Pain and Ranking of Medical Associations' Patient Information Pages: Google Ads Keyword Planner Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e18684", keywords="Google", keywords="ad words", keywords="infodemiology", keywords="musculoskeletal-related pain", keywords="patient education", keywords="medical information", abstract="Background: Most people currently use the internet to obtain information about many subjects, including health information. Thus, medical associations need to provide accurate medical information websites. Although medical associations have their own patient education pages, it is not clear if these websites actually show up in search results. Objective: The aim of this study was to evaluate how well medical associations function as online information providers by searching for information about musculoskeletal-related pain online and determining the ranking of the websites of medical associations. Methods: We conducted a Google search for frequently searched keywords. Keywords were extracted using Google Ads Keyword Planner associated with ``pain'' relevant to the musculoskeletal system from June 2016 to December 2019. The top 20 search queries were extracted and searched using the Google search engine in Japan and the United States. Results: The number of suggested queries for ``pain'' provided by Google Ads Keyword Planner was 930 in the United States and 2400 in Japan. Among the top 20 musculoskeletal-related pain queries chosen, the probability that the medical associations' websites would appear in the top 10 results was 30\% in the United States and 45\% in Japan. In five queries each, the associations' websites did not appear among the top 100 results. No significant difference was found in the rank of the associations' website search results (P=.28). Conclusions: To provide accurate medical information to patients, it is essential to undertake effective measures for search engine optimization. For orthopedic associations, it is necessary that their websites should appear among the top search results. ", doi="10.2196/18684", url="https://www.jmir.org/2020/8/e18684", url="http://www.ncbi.nlm.nih.gov/pubmed/32795991" } @Article{info:doi/10.2196/17406, author="Bogza, Laura-Mihaela and Patry-Lebeau, Cassandra and Farmanova, Elina and Witteman, O. Holly and Elliott, Jacobi and Stolee, Paul and Hudon, Carol and Giguere, C. Anik M.", title="User-Centered Design and Evaluation of a Web-Based Decision Aid for Older Adults Living With Mild Cognitive Impairment and Their Health Care Providers: Mixed Methods Study", journal="J Med Internet Res", year="2020", month="Aug", day="19", volume="22", number="8", pages="e17406", keywords="decision aid", keywords="mild cognitive impairment", keywords="elderly", keywords="decision support technique", keywords="aging", abstract="Background: Mild cognitive impairment (MCI) is often considered a transitional state between normal and pathologic (eg, dementia) cognitive aging. Although its prognosis varies largely, the diagnosis carries the risk of causing uncertainty and overtreatment of older adults with MCI who may never progress to dementia. Decision aids help people become better informed and more involved in decision making by providing evidence-based information about options and possible outcomes and by assisting them in clarifying their personal values in relation to the decision to be made. Objective: This study aimed to incorporate features that best support values clarification and adjust the level of detail of a web-based decision aid for individuals with MCI. Methods: We conducted a rapid review to identify options to maintain or improve cognitive functions in individuals with MCI. The evidence was structured into a novel web-based decision aid designed in collaboration with digital specialists and graphic designers. Qualitative and user-centered evaluations were used to draw on users' knowledge, clarify values, and inform potential adoption in routine clinical practice. We invited clinicians, older adults with MCI, and their caregivers to evaluate the decision aid in 6 consecutive rounds, with new participants in each round. Quantitative data were collected using the Values Clarity and Informed subscales of the Decisional Conflict Scale, the System Usability Scale, the Ottawa Acceptability questionnaire, and a 5-point satisfaction rating scale. We verified their comprehension using a teach-back method and recorded usability issues. We recorded the audio and computer screen during the session. An inductive thematic qualitative analysis approach was used to identify and describe the issues that arose. After each round, an expert panel met to prioritize and find solutions to mitigate the issues. An integrated analysis was conducted to confirm our choices. Results: A total of 7 clinicians (social workers, nurses, family physicians, psychologists) and 12 older (?60 years) community-dwelling individuals with MCI, half of them women, with education levels going from none to university diploma, were recruited and completed testing. The thematic analysis revealed 3 major issues. First, the user should be guided through the decision-making process by tailoring the presentation of options to users' priorities using the values clarification exercise. Second, its content should be simple, but not simplistic, notably by using information layering, plain language, and pictograms. Third, the interface should be intuitive and user friendly, utilize pop-up windows and information tips, avoid drop-down menus, and limit the need to scroll down. The quantitative assessments corroborated the qualitative findings. Conclusions: This project resulted in a promising web-based decision aid that can support decision making for MCI intervention, based on the personal values and preferences of the users. Further ongoing research will allow its implementation to be tested in clinical settings. ", doi="10.2196/17406", url="https://www.jmir.org/2020/8/e17406", url="http://www.ncbi.nlm.nih.gov/pubmed/32442151" } @Article{info:doi/10.2196/21385, author="Portz, D. Jennifer and Brungardt, Adreanne and Shanbhag, Prajakta and Staton, W. Elizabeth and Bose-Brill, Seuli and Lin, Chen-Tan and Kutner, S. Jean and Lum, D. Hillary", title="Advance Care Planning Among Users of a Patient Portal During the COVID-19 Pandemic: Retrospective Observational Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e21385", keywords="advance care planning", keywords="electronic health records", keywords="pandemic", keywords="COVID-19", keywords="advance directives", keywords="patient portal", keywords="planning", keywords="web-based tool", keywords="health system", abstract="Background: Advance care planning is the process of discussing health care treatment preferences based on patients' personal values, and it often involves the completion of advance directives. In the first months of 2020, a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began circulating widely in the American state of Colorado, leading to widespread diagnosis of coronavirus disease (COVID-19), hospitalizations, and deaths. In this context, the importance of technology-based, non--face-to-face methods to conduct advance care planning via patient portals has increased. Objective: The aim of this study was to determine the rates of use of a web-based advance care planning tool through a health system--based electronic patient portal both before and in the early months of the COVID-19 pandemic. Methods: In 2017, we implemented web-based tools through the patient portal of UCHealth's electronic health record (EHR) for patients to learn about advance care planning and complete an electronically signed medical durable power of attorney (MDPOA) to legally appoint a medical decision maker. Patients accessing the portal can complete and submit a legally valid MDPOA, which becomes part of their medical record. We collected data on the patients' date of MDPOA completion, use of advance care planning messaging, age, sex, and geographic location during the early phase of the COVID-19 pandemic (December 29, 2019, to May 30, 2020). Results: Over a 5-month period that includes the early phase of the COVID-19 pandemic in Colorado, total monthly use of the advance care planning portal tool increased from 418 users in January to 1037 users in April and then decreased slightly to 815 users in May. The number of MDPOA forms submitted per week increased 2.4-fold after the stay-at-home order was issued in Colorado on March 26, 2020 (P<.001). The mean age of the advance care planning portal users was 47.7 years (SD 16.1), and 2206/3292 (67.0\%) were female. Women were more likely than men to complete an MDPOA, particularly in younger age groups (P<.001). The primary use of the advance care planning portal tools was the completion of an MDPOA (3138/3292, 95.3\%), compared to sending an electronic message (148/3292, 4.5\%). Over 50\% of patients who completed an MDPOA did not have a prior agent in the EHR. Conclusions: Use of a web-based patient portal to complete an MDPOA increased substantially during the first months of the COVID-19 pandemic in Colorado. There was an increase in advance care planning that corresponded with state government shelter-in-place orders as well as public health reports of increased numbers of COVID-19 cases and deaths. Patient portals are an important tool for providing advance care planning resources and documenting medical decision makers during the pandemic to ensure that medical treatment aligns with patient goals and values. ", doi="10.2196/21385", url="http://www.jmir.org/2020/8/e21385/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716900" } @Article{info:doi/10.2196/16792, author="Backx, Rosa and Skirrow, Caroline and Dente, Pasquale and Barnett, H. Jennifer and Cormack, K. Francesca", title="Comparing Web-Based and Lab-Based Cognitive Assessment Using the Cambridge Neuropsychological Test Automated Battery: A Within-Subjects Counterbalanced Study", journal="J Med Internet Res", year="2020", month="Aug", day="4", volume="22", number="8", pages="e16792", keywords="reliability", keywords="mobile health", keywords="neuropsychological tests", keywords="CANTAB", keywords="cognition", abstract="Background: Computerized assessments are already used to derive accurate and reliable measures of cognitive function. Web-based cognitive assessment could improve the accessibility and flexibility of research and clinical assessment, widen participation, and promote research recruitment while simultaneously reducing costs. However, differences in context may influence task performance. Objective: This study aims to determine the comparability of an unsupervised, web-based administration of the Cambridge Neuropsychological Test Automated Battery (CANTAB) against a typical in-person lab-based assessment, using a within-subjects counterbalanced design. The study aims to test (1) reliability, quantifying the relationship between measurements across settings using correlational approaches; (2) equivalence, the extent to which test results in different settings produce similar overall results; and (3) agreement, by quantifying acceptable limits to bias and differences between measurement environments. Methods: A total of 51 healthy adults (32 women and 19 men; mean age 36.8, SD 15.6 years) completed 2 testing sessions, which were completed on average 1 week apart (SD 4.5 days). Assessments included equivalent tests of emotion recognition (emotion recognition task [ERT]), visual recognition (pattern recognition memory [PRM]), episodic memory (paired associate learning [PAL]), working memory and spatial planning (spatial working memory [SWM] and one touch stockings of Cambridge), and sustained attention (rapid visual information processing [RVP]). Participants were randomly allocated to one of the two groups, either assessed in-person in the laboratory first (n=33) or with unsupervised web-based assessments on their personal computing systems first (n=18). Performance indices (errors, correct trials, and response sensitivity) and median reaction times were extracted. Intraclass and bivariate correlations examined intersetting reliability, linear mixed models and Bayesian paired sample t tests tested for equivalence, and Bland-Altman plots examined agreement. Results: Intraclass correlation (ICC) coefficients ranged from $\rho$=0.23-0.67, with high correlations in 3 performance indices (from PAL, SWM, and RVP tasks; $\rho$?0.60). High ICC values were also seen for reaction time measures from 2 tasks (PRM and ERT tasks; $\rho$?0.60). However, reaction times were slower during web-based assessments, which undermined both equivalence and agreement for reaction time measures. Performance indices did not differ between assessment settings and generally showed satisfactory agreement. Conclusions: Our findings support the comparability of CANTAB performance indices (errors, correct trials, and response sensitivity) in unsupervised, web-based assessments with in-person and laboratory tests. Reaction times are not as easily translatable from in-person to web-based testing, likely due to variations in computer hardware. The results underline the importance of examining more than one index to ascertain comparability, as high correlations can present in the context of systematic differences, which are a product of differences between measurement environments. Further work is now needed to examine web-based assessments in clinical populations and in larger samples to improve sensitivity for detecting subtler differences between test settings. ", doi="10.2196/16792", url="https://www.jmir.org/2020/8/e16792", url="http://www.ncbi.nlm.nih.gov/pubmed/32749999" } @Article{info:doi/10.2196/18637, author="Muangpoon, Theerapat and Haghighi Osgouei, Reza and Escobar-Castillejos, David and Kontovounisios, Christos and Bello, Fernando", title="Augmented Reality System for Digital Rectal Examination Training and Assessment: System Validation", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e18637", keywords="Augmented Reality", keywords="Digital Rectal Examination (DRE)", keywords="Magnetic Tracker", keywords="Pressure Sensor", keywords="Medical Education", keywords="Usability", abstract="Background: Digital rectal examination is a difficult examination to learn and teach because of limited opportunities for practice; however, the main challenge is that students and tutors cannot see the finger when it is palpating the anal canal and prostate gland inside the patients. Objective: This paper presents an augmented reality system to be used with benchtop models commonly available in medical schools with the aim of addressing the problem of lack of visualization. The system enables visualization of the examining finger, as well as of the internal organs when performing digital rectal examinations. Magnetic tracking sensors are used to track the movement of the finger, and a pressure sensor is used to monitor the applied pressure. By overlaying a virtual finger on the real finger and a virtual model on the benchtop model, students can see through the examination and finger maneuvers. Methods: The system was implemented in the Unity game engine (Unity Technologies) and uses a first-generation HoloLens (Microsoft Inc) as an augmented reality device. To evaluate the system, 19 participants (9 clinicians who routinely performed digital rectal examinations and 10 medical students) were asked to use the system and answer 12 questions regarding the usefulness of the system. Results: The system showed the movement of an examining finger in real time with a frame rate of 60 fps on the HoloLens and accurately aligned the virtual and real models with a mean error of 3.9 mm. Users found the movement of the finger was realistic (mean 3.9, SD 1.2); moreover, they found the visualization of the finger and internal organs were useful for teaching, learning, and assessment of digital rectal examinations (finger: mean 4.1, SD 1.1; organs: mean 4.6, SD 0.8), mainly targeting a novice group. Conclusions: The proposed augmented reality system was designed to improve teaching and learning of digital rectal examination skills by providing visualization of the finger and internal organs. The initial user study proved its applicability and usefulness. ", doi="10.2196/18637", url="https://www.jmir.org/2020/8/e18637", url="http://www.ncbi.nlm.nih.gov/pubmed/32788146" } @Article{info:doi/10.2196/19827, author="Machleid, Felix and Kaczmarczyk, Robert and Johann, Doreen and Bal{\v c}i?nas, Justinas and Atienza-Carbonell, Beatriz and von Maltzahn, Finn and Mosch, Lina", title="Perceptions of Digital Health Education Among European Medical Students: Mixed Methods Survey", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e19827", keywords="medical students", keywords="medical education", keywords="eHealth", keywords="mixed method", keywords="health workforce", keywords="digital literacy", keywords="curriculum", abstract="Background: Digital health technologies hold promise to enhance patient-related outcomes, to support health care staff by reducing their workload, and to improve the coordination of care. As key users of digital health technologies, health care workers are crucial to enable a meaningful digital transformation of health care. Digital health literacy and digital skills should become prerequisite competencies for health professionals to facilitate the implementation and leverage the potential of digital technologies to improve health. Objective: We aimed to assess European medical students' perceived knowledge and opinions toward digital health, the status of digital health implementation in medical education, and the students' most pressing needs. Methods: The explanatory design of our mixed methods study was based on an online, anonymous, self-administered survey targeted toward European medical students. A linear regression analysis was used to identify the influence of the year of medical studies on the responses. Additional analysis was performed by grouping the responses by the self-evaluated frequency of eHealth technology use. Written responses to four qualitative questions in the survey were analyzed using an inductive approach. Results: The survey received a total of 451 responses from 39 European countries, and there were respondents for every year of medical studies. The majority of respondents saw advantages in the use of digital health. While 40.6\% (183/451) felt prepared to work in a digitized health care system, more than half (240/451, 53.2\%) evaluated their eHealth skills as poor or very poor. Medical students considered lack of education to be the reason for this, with 84.9\% (383/451) agreeing or strongly agreeing that more digital health education should be implemented in the medical curriculum. Students demanded introductory and specific eHealth courses covering data management, ethical aspects, legal frameworks, research and entrepreneurial opportunities, role in public health and health systems, communication skills, and practical training. The emphasis lay on tailoring learning to future job requirements and interprofessional education. Conclusions: This study shows a lack of digital health-related formats in medical education and a perceived lack of digital health literacy among European medical students. Our findings indicate a gap between the willingness of medical students to take an active role by becoming key players in the digital transformation of health care and the education that they receive through their faculties. ", doi="10.2196/19827", url="http://www.jmir.org/2020/8/e19827/", url="http://www.ncbi.nlm.nih.gov/pubmed/32667899" } @Article{info:doi/10.2196/17367, author="Bray, Lucy and Sharpe, Ashley and Gichuru, Phillip and Fortune, Peter-Marc and Blake, Lucy and Appleton, Victoria", title="The Acceptability and Impact of the Xploro Digital Therapeutic Platform to Inform and Prepare Children for Planned Procedures in a Hospital: Before and After Evaluation Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17367", keywords="health literacy", keywords="augmented reality", keywords="children", keywords="procedure", keywords="health", keywords="artificial intelligence", abstract="Background: There is increasing interest in finding novel approaches to improve the preparation of children for hospital procedures such as surgery, x-rays, and blood tests. Well-prepared and informed children have better outcomes (less procedural anxiety and higher satisfaction). A digital therapeutic (DTx) platform (Xploro) was developed with children to provide health information through gamification, serious games, a chatbot, and an augmented reality avatar. Objective: This before and after evaluation study aims to assess the acceptability of the Xploro DTx and examine its impact on children and their parent's procedural knowledge, procedural anxiety, and reported experiences when attending a hospital for a planned procedure. Methods: We used a mixed methods design with quantitative measures and qualitative data collected sequentially from a group of children who received standard hospital information (before group) and a group of children who received the DTx intervention (after group). Participants were children aged between 8 and 14 years and their parents who attended a hospital for a planned clinical procedure at a children's hospital in North West England. Children and their parents completed self-report measures (perceived knowledge, procedural anxiety, procedural satisfaction, and procedural involvement) at baseline, preprocedure, and postprocedure. Results: A total of 80 children (n=40 standard care group and n=40 intervention group) and their parents participated in the study; the children were aged between 8 and 14 years (average 10.4, SD 2.27 years) and were attending a hospital for a range of procedures. The children in the intervention group reported significantly lower levels of procedural anxiety before the procedure than those in the standard group (two-tailed t63.64=2.740; P=.008). The children in the intervention group also felt more involved in their procedure than those in the standard group (t75=?2.238; P=.03). The children in the intervention group also reported significantly higher levels of perceived procedural knowledge preprocedure (t59.98=?4.892; P=.001) than those in the standard group. As for parents, those with access to the Xploro intervention reported significantly lower levels of procedural anxiety preprocedure than those who did not (t68.51=1.985; P=.05). During the semistructured write and tell interviews, children stated that they enjoyed using the intervention, it was fun and easy to use, and they felt that it had positively influenced their experiences of coming to the hospital for a procedure. Conclusions: This study has shown that the DTx platform, Xploro, has a positive impact on children attending a hospital for a procedure by reducing levels of procedural anxiety. The children and parents in the intervention group described Xploro as improving their experiences and being easy and fun to use. ", doi="10.2196/17367", url="http://www.jmir.org/2020/8/e17367/", url="http://www.ncbi.nlm.nih.gov/pubmed/32780025" } @Article{info:doi/10.2196/20623, author="Chen, Qin and Yan, Xiangbin and Zhang, Tingting", title="Converting Visitors of Physicians' Personal Websites to Customers in Online Health Communities: Longitudinal Study", journal="J Med Internet Res", year="2020", month="Aug", day="26", volume="22", number="8", pages="e20623", keywords="online health communities", keywords="conversion rate", keywords="multisource information", keywords="physician-generated information", keywords="patient-generated information", keywords="system-generated information", keywords="usage time", abstract="Background: With the dramatic development of Web 2.0, increasing numbers of patients and physicians are actively involved in online health communities. Despite extensive research on online health communities, the conversion rate from visitor to customer and its driving factors have not been discussed. Objective: The aim of this study was to analyze the conversion rate of online health communities and to explore the effects of multisource online health community information, including physician-generated information, patient-generated information, and system-generated information. Methods: An empirical study was conducted to examine the effects of physician-generated, patient-generated, and system-generated information on the conversion rate of physicians' personal websites by analyzing short panel data from 2112 physicians over five time periods in a Chinese online health community. Results: Multisource online health community information (ie, physician-generated, patient-generated, and system-generated information) positively affected the conversion rate. Physician-generated and patient-generated information showed a substitute relationship rather than a complementary relationship. In addition, the usage time of a personal website positively moderated patient-generated information, but negatively moderated physician-generated information. Conclusions: This study contributes to the electronic health literature by investigating the conversion rate of online health communities and the effect of multisource online health community information. This study also contributes to understanding the drivers of conversion rate on service websites, which can help to successfully improve the efficiency of online health communities. ", doi="10.2196/20623", url="http://www.jmir.org/2020/8/e20623/", url="http://www.ncbi.nlm.nih.gov/pubmed/32845248" } @Article{info:doi/10.2196/16903, author="Hsu, Chien-Ning and Liu, Chien-Liang and Tain, You-Lin and Kuo, Chin-Yu and Lin, Yun-Chun", title="Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study", journal="J Med Internet Res", year="2020", month="Aug", day="4", volume="22", number="8", pages="e16903", keywords="community-acquired acute kidney injury (CA-AKI)", keywords="hospitalization", keywords="treatment decision making", keywords="clinical decision support system", keywords="machine learning", keywords="feature selection with extreme gradient boost (XGBoost)", keywords="least absolute shrinkage and selection operator (LASSO)", keywords="risk prediction", abstract="Background: Community-acquired acute kidney injury (CA-AKI)-associated hospitalizations impose significant health care needs and contribute to in-hospital mortality. However, most risk prediction models developed to date have focused on AKI in a specific group of patients during hospitalization, and there is limited knowledge on the baseline risk in the general population for preventing CA-AKI-associated hospitalization. Objective: To gain further insight into risk exploration, the aim of this study was to develop, validate, and establish a scoring system to facilitate health professionals in enabling early recognition and intervention of CA-AKI to prevent permanent kidney damage using different machine-learning techniques. Methods: A nested case-control study design was employed using electronic health records derived from a group of Chang Gung Memorial Hospitals in Taiwan from 2010 to 2017 to identify 234,867 adults with at least two measures of serum creatinine at hospital admission. Patients were classified into a derivation cohort (2010-2016) and a temporal validation cohort (2017). Patients with the first episode of CA-AKI at hospital admission were classified into the case group and those without CA-AKI were classified in the control group. A total of 47 potential candidate variables, including age, gender, prior use of nephrotoxic medications, Charlson comorbid conditions, commonly measured laboratory results, and recent use of health services, were tested to develop a CA-AKI hospitalization risk model. Permutation-based selection with both the extreme gradient boost (XGBoost) and least absolute shrinkage and selection operator (LASSO) algorithms was performed to determine the top 10 important features for scoring function development. Results: The discriminative ability of the risk model was assessed by the area under the receiver operating characteristic curve (AUC), and the predictive CA-AKI risk model derived by the logistic regression algorithm achieved an AUC of 0.767 (95\% CI 0.764-0.770) on derivation and 0.761 on validation for any stage of AKI, with positive and negative predictive values of 19.2\% and 96.1\%, respectively. The risk model for prediction of CA-AKI stages 2 and 3 had an AUC value of 0.818 for the validation cohort with positive and negative predictive values of 13.3\% and 98.4\%, respectively. These metrics were evaluated at a cut-off value of 7.993, which was determined as the threshold to discriminate the risk of AKI. Conclusions: A machine learning--generated risk score model can identify patients at risk of developing CA-AKI-related hospitalization through a routine care data-driven approach. The validated multivariate risk assessment tool could help clinicians to stratify patients in primary care, and to provide monitoring and early intervention for preventing AKI while improving the quality of AKI care in the general population. ", doi="10.2196/16903", url="https://www.jmir.org/2020/8/e16903", url="http://www.ncbi.nlm.nih.gov/pubmed/32749223" } @Article{info:doi/10.2196/19512, author="Park, Jun Hyung and Jung, Yon Dae and Ji, Wonjun and Choi, Chang-Min", title="Detection of Bacteremia in Surgical In-Patients Using Recurrent Neural Network Based on Time Series Records: Development and Validation Study", journal="J Med Internet Res", year="2020", month="Aug", day="4", volume="22", number="8", pages="e19512", keywords="deep learning", keywords="bacteremia", keywords="early detection", keywords="time series", keywords="recurrent neural network", keywords="neural network", keywords="informatics", keywords="surgery", keywords="sepsis", keywords="modeling", abstract="Background: Detecting bacteremia among surgical in-patients is more obscure than other patients due to the inflammatory condition caused by the surgery. The previous criteria such as systemic inflammatory response syndrome or Sepsis-3 are not available for use in general wards, and thus, many clinicians usually rely on practical senses to diagnose postoperative infection. Objective: This study aims to evaluate the performance of continuous monitoring with a deep learning model for early detection of bacteremia for surgical in-patients in the general ward and the intensive care unit (ICU). Methods: In this retrospective cohort study, we included 36,023 consecutive patients who underwent general surgery between October and December 2017 at a tertiary referral hospital in South Korea. The primary outcome was the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC) for detecting bacteremia by the deep learning model, and the secondary outcome was the feature explainability of the model by occlusion analysis. Results: Out of the 36,023 patients in the data set, 720 cases of bacteremia were included. Our deep learning--based model showed an AUROC of 0.97 (95\% CI 0.974-0.981) and an AUPRC of 0.17 (95\% CI 0.147-0.203) for detecting bacteremia in surgical in-patients. For predicting bacteremia within the previous 24-hour period, the AUROC and AUPRC values were 0.93 and 0.15, respectively. Occlusion analysis showed that vital signs and laboratory measurements (eg, kidney function test and white blood cell group) were the most important variables for detecting bacteremia. Conclusions: A deep learning model based on time series electronic health records data had a high detective ability for bacteremia for surgical in-patients in the general ward and the ICU. The model may be able to assist clinicians in evaluating infection among in-patients, ordering blood cultures, and prescribing antibiotics with real-time monitoring. ", doi="10.2196/19512", url="https://www.jmir.org/2020/8/e19512", url="http://www.ncbi.nlm.nih.gov/pubmed/32669261" } @Article{info:doi/10.2196/16709, author="Yu, Kun-Hsing and Lee, Michael Tsung-Lu and Yen, Ming-Hsuan and Kou, C. S. and Rosen, Bruce and Chiang, Jung-Hsien and Kohane, S. Isaac", title="Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation", journal="J Med Internet Res", year="2020", month="Aug", day="5", volume="22", number="8", pages="e16709", keywords="computed tomography, spiral", keywords="lung cancer", keywords="machine learning", keywords="early detection of cancer", keywords="reproducibility of results", abstract="Background: Chest computed tomography (CT) is crucial for the detection of lung cancer, and many automated CT evaluation methods have been proposed. Due to the divergent software dependencies of the reported approaches, the developed methods are rarely compared or reproduced. Objective: The goal of the research was to generate reproducible machine learning modules for lung cancer detection and compare the approaches and performances of the award-winning algorithms developed in the Kaggle Data Science Bowl. Methods: We obtained the source codes of all award-winning solutions of the Kaggle Data Science Bowl Challenge, where participants developed automated CT evaluation methods to detect lung cancer (training set n=1397, public test set n=198, final test set n=506). The performance of the algorithms was evaluated by the log-loss function, and the Spearman correlation coefficient of the performance in the public and final test sets was computed. Results: Most solutions implemented distinct image preprocessing, segmentation, and classification modules. Variants of U-Net, VGGNet, and residual net were commonly used in nodule segmentation, and transfer learning was used in most of the classification algorithms. Substantial performance variations in the public and final test sets were observed (Spearman correlation coefficient = .39 among the top 10 teams). To ensure the reproducibility of results, we generated a Docker container for each of the top solutions. Conclusions: We compared the award-winning algorithms for lung cancer detection and generated reproducible Docker images for the top solutions. Although convolutional neural networks achieved decent accuracy, there is plenty of room for improvement regarding model generalizability. ", doi="10.2196/16709", url="https://www.jmir.org/2020/8/e16709", url="http://www.ncbi.nlm.nih.gov/pubmed/32755895" } @Article{info:doi/10.2196/15394, author="Cheng, Hao-Yuan and Wu, Yu-Chun and Lin, Min-Hau and Liu, Yu-Lun and Tsai, Yue-Yang and Wu, Jo-Hua and Pan, Ke-Han and Ke, Chih-Jung and Chen, Chiu-Mei and Liu, Ding-Ping and Lin, I-Feng and Chuang, Jen-Hsiang", title="Applying Machine Learning Models with An Ensemble Approach for Accurate Real-Time Influenza Forecasting in Taiwan: Development and Validation Study", journal="J Med Internet Res", year="2020", month="Aug", day="5", volume="22", number="8", pages="e15394", keywords="influenza", keywords="Influenza-like illness", keywords="forecasting", keywords="machine learning", keywords="artificial intelligence", keywords="epidemic forecasting", keywords="surveillance", abstract="Background: Changeful seasonal influenza activity in subtropical areas such as Taiwan causes problems in epidemic preparedness. The Taiwan Centers for Disease Control has maintained real-time national influenza surveillance systems since 2004. Except for timely monitoring, epidemic forecasting using the national influenza surveillance data can provide pivotal information for public health response. Objective: We aimed to develop predictive models using machine learning to provide real-time influenza-like illness forecasts. Methods: Using surveillance data of influenza-like illness visits from emergency departments (from the Real-Time Outbreak and Disease Surveillance System), outpatient departments (from the National Health Insurance database), and the records of patients with severe influenza with complications (from the National Notifiable Disease Surveillance System), we developed 4 machine learning models (autoregressive integrated moving average, random forest, support vector regression, and extreme gradient boosting) to produce weekly influenza-like illness predictions for a given week and 3 subsequent weeks. We established a framework of the machine learning models and used an ensemble approach called stacking to integrate these predictions. We trained the models using historical data from 2008-2014. We evaluated their predictive ability during 2015-2017 for each of the 4-week time periods using Pearson correlation, mean absolute percentage error (MAPE), and hit rate of trend prediction. A dashboard website was built to visualize the forecasts, and the results of real-world implementation of this forecasting framework in 2018 were evaluated using the same metrics. Results: All models could accurately predict the timing and magnitudes of the seasonal peaks in the then-current week (nowcast) ($\rho$=0.802-0.965; MAPE: 5.2\%-9.2\%; hit rate: 0.577-0.756), 1-week ($\rho$=0.803-0.918; MAPE: 8.3\%-11.8\%; hit rate: 0.643-0.747), 2-week ($\rho$=0.783-0.867; MAPE: 10.1\%-15.3\%; hit rate: 0.669-0.734), and 3-week forecasts ($\rho$=0.676-0.801; MAPE: 12.0\%-18.9\%; hit rate: 0.643-0.786), especially the ensemble model. In real-world implementation in 2018, the forecasting performance was still accurate in nowcasts ($\rho$=0.875-0.969; MAPE: 5.3\%-8.0\%; hit rate: 0.582-0.782) and remained satisfactory in 3-week forecasts ($\rho$=0.721-0.908; MAPE: 7.6\%-13.5\%; hit rate: 0.596-0.904). Conclusions: This machine learning and ensemble approach can make accurate, real-time influenza-like illness forecasts for a 4-week period, and thus, facilitate decision making. ", doi="10.2196/15394", url="https://www.jmir.org/2020/8/e15394", url="http://www.ncbi.nlm.nih.gov/pubmed/32755888" } @Article{info:doi/10.2196/18388, author="Camacho, Jhon and Zanoletti-Mannello, Manuela and Landis-Lewis, Zach and Kane-Gill, L. Sandra and Boyce, D. Richard", title="A Conceptual Framework to Study the Implementation of Clinical Decision Support Systems (BEAR): Literature Review and Concept Mapping", journal="J Med Internet Res", year="2020", month="Aug", day="6", volume="22", number="8", pages="e18388", keywords="clinical decision support system", keywords="computerized decision support system", keywords="implementation science", keywords="technology acceptance", keywords="barriers", keywords="facilitators", keywords="determinants", keywords="decision support system", abstract="Background: The implementation of clinical decision support systems (CDSSs) as an intervention to foster clinical practice change is affected by many factors. Key factors include those associated with behavioral change and those associated with technology acceptance. However, the literature regarding these subjects is fragmented and originates from two traditionally separate disciplines: implementation science and technology acceptance. Objective: Our objective is to propose an integrated framework that bridges the gap between the behavioral change and technology acceptance aspects of the implementation of CDSSs. Methods: We employed an iterative process to map constructs from four contributing frameworks---the Theoretical Domains Framework (TDF); the Consolidated Framework for Implementation Research (CFIR); the Human, Organization, and Technology-fit framework (HOT-fit); and the Unified Theory of Acceptance and Use of Technology (UTAUT)---and the findings of 10 literature reviews, identified through a systematic review of reviews approach. Results: The resulting framework comprises 22 domains: agreement with the decision algorithm; attitudes; behavioral regulation; beliefs about capabilities; beliefs about consequences; contingencies; demographic characteristics; effort expectancy; emotions; environmental context and resources; goals; intentions; intervention characteristics; knowledge; memory, attention, and decision processes; patient--health professional relationship; patient's preferences; performance expectancy; role and identity; skills, ability, and competence; social influences; and system quality. We demonstrate the use of the framework providing examples from two research projects. Conclusions: We proposed BEAR (BEhavior and Acceptance fRamework), an integrated framework that bridges the gap between behavioral change and technology acceptance, thereby widening the view established by current models. ", doi="10.2196/18388", url="https://www.jmir.org/2020/8/e18388", url="http://www.ncbi.nlm.nih.gov/pubmed/32759098" } @Article{info:doi/10.2196/18855, author="Baxter, L. Sally and Klie, R. Adam and Radha Saseendrakumar, Bharanidharan and Ye, Y. Gordon and Hogarth, Michael", title="Text Processing for Detection of Fungal Ocular Involvement in Critical Care Patients: Cross-Sectional Study", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e18855", keywords="fungemia", keywords="fungal endophthalmitis", keywords="fungal ocular involvement", keywords="electronic health records", keywords="diagnosis codes", keywords="regular expressions", keywords="natural language processing", keywords="unstructured data", abstract="Background: Fungal ocular involvement can develop in patients with fungal bloodstream infections and can be vision-threatening. Ocular involvement has become less common in the current era of improved antifungal therapies. Retrospectively determining the prevalence of fungal ocular involvement is important for informing clinical guidelines, such as the need for routine ophthalmologic consultations. However, manual retrospective record review to detect cases is time-consuming. Objective: This study aimed to determine the prevalence of fungal ocular involvement in a critical care database using both structured and unstructured electronic health record (EHR) data. Methods: We queried microbiology data from 46,467 critical care patients over 12 years (2000-2012) from the Medical Information Mart for Intensive Care III (MIMIC-III) to identify 265 patients with culture-proven fungemia. For each fungemic patient, demographic data, fungal species present in blood culture, and risk factors for fungemia (eg, presence of indwelling catheters, recent major surgery, diabetes, immunosuppressed status) were ascertained. All structured diagnosis codes and free-text narrative notes associated with each patient's hospitalization were also extracted. Screening for fungal endophthalmitis was performed using two approaches: (1) by querying a wide array of eye- and vision-related diagnosis codes, and (2) by utilizing a custom regular expression pipeline to identify and collate relevant text matches pertaining to fungal ocular involvement. Both approaches were validated using manual record review. The main outcome measure was the documentation of any fungal ocular involvement. Results: In total, 265 patients had culture-proven fungemia, with Candida albicans (n=114, 43\%) and Candida glabrata (n=74, 28\%) being the most common fungal species in blood culture. The in-hospital mortality rate was 121 (46\%). In total, 7 patients were identified as having eye- or vision-related diagnosis codes, none of whom had fungal endophthalmitis based on record review. There were 26,830 free-text narrative notes associated with these 265 patients. A regular expression pipeline based on relevant terms yielded possible matches in 683 notes from 108 patients. Subsequent manual record review again demonstrated that no patients had fungal ocular involvement. Therefore, the prevalence of fungal ocular involvement in this cohort was 0\%. Conclusions: MIMIC-III contained no cases of ocular involvement among fungemic patients, consistent with prior studies reporting low rates of ocular involvement in fungemia. This study demonstrates an application of natural language processing to expedite the review of narrative notes. This approach is highly relevant for ophthalmology, where diagnoses are often based on physical examination findings that are documented within clinical notes. ", doi="10.2196/18855", url="https://www.jmir.org/2020/8/e18855", url="http://www.ncbi.nlm.nih.gov/pubmed/32795984" } @Article{info:doi/10.2196/16175, author="Guay, Manon and Latulippe, Karine and Auger, Claudine and Giroux, Dominique and S{\'e}guin-Tremblay, No{\'e}mie and Gauthier, Jos{\'e}e and Genest, Catherine and Morales, Ernesto and Vincent, Claude", title="Self-Selection of Bathroom-Assistive Technology: Development of an Electronic Decision Support System (Hygiene 2.0)", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e16175", keywords="hygiene", keywords="activities of daily living", keywords="decision aids", keywords="occupational therapy", keywords="aging", keywords="self-help devices", keywords="universal design", keywords="accidental falls", keywords="mobile phone", abstract="Background: A clinical algorithm (Algo) in paper form is used in Quebec, Canada, to allow health care workers other than occupational therapists (OTs) to make bathroom adaptation recommendations for older adults. An integrated knowledge transfer process around Algo suggested an electronic version of this decision support system (electronic decision support system [e-DSS]) to be used by older adults and their caregivers in search of information and solutions for their autonomy and safety in the bathroom. Objective: This study aims to (1) create an e-DSS for the self-selection of bathroom-assistive technology by community-dwelling older adults and their caregivers and (2) assess usability with lay users and experts to improve the design accordingly. Methods: On the basis of a user-centered design approach, the process started with content identification for the prototype through 7 semistructured interviews with key informants of various backgrounds (health care providers, assistive technology providers, and community services) and 4 focus groups (2 with older adults and 2 with caregivers). A thematic content transcript analysis was carried out and used during the creation of the prototype. The prototype was refined iteratively using think-aloud and observation methods with a clinical expert (n=1), researchers (n=3), OTs (n=3), older adults (n=3), and caregivers (n=3), who provided information on the usability of the e-DSS. Results: Overall, 4 themes served as the criteria for the prototype of the electronic Algo (Hygiene 2.0 [H2.0]): focus (safety, confidentiality, well-being, and autonomy), engage, facilitate (simplify, clarify, and illustrate), and access. For example, users first pay attention to the images (engage and illustrate) that can be used to depict safe postures (safety), illustrate questions embedded in the decision support tool (clarify and illustrate), and demonstrate the context of the use of assistive technology (safety and clarify). Conclusions: The user-centered design of H2.0 allowed the cocreation of an e-DSS in the form of a website, in line with the needs of community-dwelling older adults and their caregivers seeking bathroom-assistive technology that enables personal hygiene. Each iteration improved usability and brought more insight into the users' realities, tailoring the e-DSS to the implementation context. ", doi="10.2196/16175", url="https://www.jmir.org/2020/8/e16175", url="http://www.ncbi.nlm.nih.gov/pubmed/32773380" } @Article{info:doi/10.2196/17739, author="Sch{\"u}ttler, Christina and Huth, Verena and von Jagwitz-Biegnitz, Magdal{\'e}na and Lablans, Martin and Prokosch, Hans-Ulrich and Griebel, Lena", title="A Federated Online Search Tool for Biospecimens (Sample Locator): Usability Study", journal="J Med Internet Res", year="2020", month="Aug", day="18", volume="22", number="8", pages="e17739", keywords="software tools", keywords="biological specimen banks", keywords="user interface", keywords="evaluation", keywords="research", abstract="Background: The German Biobank Alliance (GBA) aims to establish a cross-site biobank network. For this endeavor, the so-called Sample Locator, a federated search tool for biospecimens and related data, has been developed, forming the heart of its information technology (IT) infrastructure. Objective: To ensure the sustainable use of such a tool, we included researchers as participants in an end user--based usability evaluation. Methods: To develop a prototype ready for evaluation, we needed input from GBA IT experts. Thus, we conducted a 2-day workshop with 8 GBA IT team members. The focus was on the respective steps of a user-centered design process. With the acquired knowledge, the participants designed low-fidelity mock-ups. The main ideas of these mock-ups were discussed, extracted, and summarized into a comprehensive prototype using Microsoft PowerPoint. Furthermore, we created a questionnaire concerning the usability of the prototype, including the System Usability Scale (SUS), questions on negative and positive aspects, and typical tasks to be fulfilled with the tool. Subsequently, the prototype was pretested on the basis of this questionnaire with researchers who have a biobank background. Based on this preliminary work, the usability analysis was ultimately carried out with researchers and the results were evaluated. Results: Altogether, 27 researchers familiar with sample requests evaluated the prototype. The analysis of the feedback certified a good usability, given that the Sample Locator prototype was seen as intuitive and user-friendly by 74\% (20/27) of the participants. The total SUS score by the 25 persons that completed the questionnaire was 80.4, indicating good system usability. Still, the evaluation provided useful advice on optimization potential (eg, offering a help function). Conclusions: The findings of this usability analysis indicate that the considerations regarding a user-friendly application that have been made in the development process so far strongly coincide with the perception of the study participants. Nevertheless, it was important to engage prospective end users to ensure that the previous development is going in the desired direction and that the Sample Locator will be used in the future. The user comments and suggestions for improvement will be considered in upcoming iterations for refinement. ", doi="10.2196/17739", url="http://www.jmir.org/2020/8/e17739/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663150" } @Article{info:doi/10.2196/17449, author="Ash, I. Garrett and Robledo, S. David and Ishii, Momoko and Pittman, Brian and DeMartini, S. Kelly and O'Malley, S. Stephanie and Redeker, S. Nancy and Fucito, M. Lisa", title="Using Web-Based Social Media to Recruit Heavy-Drinking Young Adults for Sleep Intervention: Prospective Observational Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17449", keywords="substance abuse", keywords="social media", keywords="alcohol drinking", keywords="sleep", keywords="mobile phone", abstract="Background: Novel alcohol prevention strategies are needed for heavy-drinking young adults. Sleep problems are common among young adults who drink heavily and are a risk factor for developing an alcohol use disorder (AUD). Young adults, interested in the connection between sleep and alcohol, are open to getting help with their sleep. Therefore, sleep interventions may offer an innovative solution. This study evaluates social media advertising for reaching young adults and recruiting them for a new alcohol prevention program focused on sleep. Objective: This study aims to evaluate the effectiveness and cost of using Facebook, Instagram, and Snapchat advertising to reach young adults who drink heavily for a sleep intervention; characterize responders' sleep, alcohol use, and related concerns and interests; and identify the most appealing advertising content. Methods: In study 1, advertisements targeting young adults with sleep concerns, heavy alcohol use, or interest in participating in a sleep program ran over 3 months. Advertisements directed volunteers to a brief web-based survey to determine initial sleep program eligibility and characterize the concerns or interests that attracted them to click the advertisement. In study 2, three advertisements ran simultaneously for 2 days to enable us to compare the effectiveness of specific advertising themes. Results: In study 1, advertisements generated 13,638 clicks, 909 surveys, and 27 enrolled volunteers in 3 months across the social media platforms. Fees averaged US \$0.27 per click, US \$3.99 per completed survey, US \$11.43 per volunteer meeting initial screening eligibility, and US \$106.59 per study enrollee. On average, those who completed the web-based survey were 21.1 (SD 2.3) years of age, and 69.4\% (631/909) were female. Most reported sleep concerns (725/909, 79.8\%) and an interest in the connection between sleep and alcohol use (547/909, 60.2\%), but few had drinking concerns (49/909, 5.4\%). About one-third (317/909, 34.9\%) were identified as being at risk for developing an AUD based on a validated alcohol screener. Among this subsample, 8.5\% (27/317) met the final criteria and were enrolled in the trial. Some volunteers also referred additional volunteers by word of mouth. In study 2, advertisements targeting sleep yielded a higher response rate than advertisements targeting alcohol use (0.91\% vs 0.56\% click rate, respectively; P<.001). Conclusions: Social media advertisements designed to target young adults with sleep concerns reached those who also drank alcohol heavily, despite few being concerned about their drinking. Moreover, advertisements focused on sleep were more effective than those focused on drinking. Compared with previous studies, cost-effectiveness was moderate for engagement (impressions to clicks), excellent for conversion (clicks to survey completion), and reasonable for enrollment. These data demonstrate the utility of social media advertising focused on sleep to reach young adults who drink heavily and recruit them for intervention. ", doi="10.2196/17449", url="https://www.jmir.org/2020/8/e17449", url="http://www.ncbi.nlm.nih.gov/pubmed/32780027" } @Article{info:doi/10.2196/19389, author="Medina-Ramirez, Patricia and Calixte-Civil, Patricia and Meltzer, R. Lauren and Brandon, O. Karen and Martinez, Ursula and Sutton, K. Steven and Meade, D. Cathy and Byrne, M. Margaret and Brandon, H. Thomas and Simmons, N. Vani", title="Comparing Methods of Recruiting Spanish-Preferring Smokers in the United States: Findings from a Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e19389", keywords="Hispanic", keywords="Latino", keywords="smoking cessation intervention", keywords="randomized controlled trial", keywords="tobacco cigarette", keywords="recruitment", keywords="social media", keywords="Facebook", keywords="web banner ad", abstract="Background: There is a pressing need to address the unacceptable disparities and underrepresentation of racial and ethnic minority groups, including Hispanics or Latinxs, in smoking cessation trials. Objective: Given the lack of research on recruitment strategies for this population, this study aims to assess effective recruitment methods based on enrollment and cost. Methods: Recruitment and enrollment data were collected from a nationwide randomized controlled trial (RCT) of a Spanish-language smoking cessation intervention (N=1417). The effectiveness of each recruitment strategy was evaluated by computing the cost per participant (CPP), which is the ratio of direct cost over the number enrolled. More effective strategies yielded lower CPPs. Demographic and smoking-related characteristics of participants recruited via the two most effective strategies were also compared (n=1307). Results: Facebook was the most effective method (CPP=US \$74.12), followed by TV advertisements (CPP=US \$191.31), whereas public bus interior card advertising was the least effective method (CPP=US \$642.50). Participants recruited via Facebook had lower average age (P=.008) and had spent fewer years in the United States (P<.001). Among the participants recruited via Facebook, a greater percentage of individuals had at least a high school education (P<.001) and an annual income above US \$10,000 (P<.001). In addition, a greater percentage of individuals were employed (P<.001) and foreign born (P=.003). In terms of subethnicity, among the subjects recruited via Facebook, a lower percentage of individuals were of Mexican origin (P<.001) and a greater percentage of individuals were of Central American (P=.02), South American (P=.01), and Cuban (P<.001) origin. Conclusions: Facebook was the most effective method for recruiting Hispanic or Latinx smokers in the United States for this RCT. However, using multiple methods was necessary to recruit a more diverse sample of Spanish-preferring Hispanic or Latinx smokers. ", doi="10.2196/19389", url="https://www.jmir.org/2020/8/e19389", url="http://www.ncbi.nlm.nih.gov/pubmed/32795986" } @Article{info:doi/10.2196/17051, author="Kopila{\vs}, Vanja and Gajovi{\'c}, Sre{\'c}ko", title="Wildfire-Like Effect of a WhatsApp Campaign to Mobilize a Group of Predominantly Health Professionals With a University Degree on a Health Issue: Infodemiology Study", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e17051", keywords="instant messaging", keywords="rumor", keywords="5G mobile networks", keywords="participatory web", keywords="virality", keywords="infodemiology", keywords="infodemic", abstract="Background: Online interactions within a closed WhatsApp group can influence the attitudes and behaviors of the users in relation to health issues. Objective: This study aimed to analyze the activity of the members of a WhatsApp group initiated to raise awareness of the possible health effects of 5G mobile networks and mobilize members to sign the related petition. Methods: We retrospectively analyzed data from the WhatsApp group of 205 members that was active during 4 consecutive days in August 2019. The messages exchanged were collected, anonymized, and analyzed according to their timing and content. Results: The WhatsApp group members were invited to the group from the administrator's contacts; 91\% (187/205) had a university degree, 68\% (140/205) were medical professionals, and 24\% (50/205) held academic positions. Approximately a quarter of the members (47/205, 23\%) declared in their messages they signed the corresponding petition. The intense message exchange had wildfire-like features, and the majority of messages (126/133, 95\%) were exchanged during the first 26 hours. Despite the viral activity and high rate of members openly declaring that they signed the petition, only 8 (8/133, 6\%) messages from the group members, excluding the administrator, referred to the health issue, which was the topic of the group. No member expressed an opposite opinion to those presented by the administrator, and there was no debate in the form of exchanging opposite opinions. Conclusions: The wildfire-like activity of the WhatsApp group and open declaration of signing the petition as a result of the mobilization campaign were not accompanied by any form of a debate related to the corresponding health issue, although the group members were predominantly health professionals, with a quarter of holding academic positions. ", doi="10.2196/17051", url="https://www.jmir.org/2020/8/e17051", url="http://www.ncbi.nlm.nih.gov/pubmed/32442138" } @Article{info:doi/10.2196/19777, author="Yokota, Rie and Okuhara, Tsuyoshi and Ueno, Haruka and Okada, Hiroko and Furukawa, Emi and Kiuchi, Takahiro", title="Online Japanese-Language Information on Lifestyle Factors Associated With Reduced Fertility: Content Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e19777", keywords="content analysis", keywords="online information", keywords="lifestyle factor", keywords="fertility", keywords="infertility", keywords="reproductive health", abstract="Background: Approximately one-third of Japanese couples currently worry or previously worried about infertility. To develop strategies for the primary prevention of infertility as a population approach, it is important for the general population to be knowledgeable about fertility and infertility. The internet may contribute to the dissemination of information regarding infertility and fertility. However, few studies have examined online information about fertility. Objective: This study aimed to quantitatively examine online Japanese-language information about lifestyle factors associated with reduced fertility. Methods: We conducted online searches, using the 10 search terms with the highest numbers of searches that people hoping to conceive are likely to input in two major search engines in Japan (Google Japan and Yahoo! Japan). From the 2200 retrieved websites, 1181 duplicates and 500 websites unrelated to our objective were excluded, resulting in a final dataset of 519 websites. Coding guidelines were developed for the following lifestyle factors associated with reduced fertility: sexually transmitted diseases, psychological stress, cigarette smoking, alcohol use, nutrition and diet, physical activity and exercise, underweight, overweight and obesity, and environmental pollutants. Results: In terms of the website author's professional expertise, 69.6\% of the coding instances for the selected lifestyle factors were mentioned by hospitals, clinics, or the media, whereas only 1.7\% were mentioned by laypersons. Psychological stress (20.1\%) and sexually transmitted diseases (18.8\%) were the most frequently mentioned lifestyle factors associated with reduced fertility. In contrast, cigarette smoking, alcohol use, nutrition and diet, physical activity and exercise, underweight, overweight and obesity, and environmental pollutants were mentioned relatively infrequently. The association between reduced fertility and sexually transmitted diseases was mentioned significantly more frequently by hospitals and clinics than by the media (P<.001). The association between reduced fertility and nutrition and diet was mentioned significantly more frequently by the media than by hospitals and clinics (P=.008). With regard to the sex of the target audience for the information, female-specific references to psychological stress, sexually transmitted diseases, nutrition and diet, underweight, physical activity and exercise, and overweight and obesity were significantly more frequent than were male-specific references to these lifestyle factors (psychological stress: P=.002, sexually transmitted diseases: P<.001, nutrition and diet: P<.001, underweight: P<.001, physical activity and exercise: P<.001, overweight and obesity: P<.001). Conclusions: Of the lifestyle factors known to be related to reduced fertility, cigarette smoking, alcohol use, and male-specific lifestyle factors are mentioned relatively infrequently in online information sources in Japan, and these factors should be discussed more in information published on websites. ", doi="10.2196/19777", url="https://www.jmir.org/2020/8/e19777/" } @Article{info:doi/10.2196/18346, author="Camacho, Erica and Hoffman, Liza and Lagan, Sarah and Rodriguez-Villa, Elena and Rauseo-Ricupero, Natali and Wisniewski, Hannah and Henson, Philip and Torous, John", title="Technology Evaluation and Assessment Criteria for Health Apps (TEACH-Apps): Pilot Study", journal="J Med Internet Res", year="2020", month="Aug", day="27", volume="22", number="8", pages="e18346", keywords="app", keywords="mobile phones", keywords="smartphones", keywords="app evaluation", keywords="technology", abstract="Background: Despite the emergence of app evaluation tools, there remains no well-defined process receptive to diverse local needs, rigorous standards, and current content. The need for such a process to assist in the implementation of app evaluation across all medical fields is evident. Such a process has the potential to increase stakeholder engagement and catalyze interest and engagement with present-day app evaluation models. Objective: This study aimed to develop and pilot test the Technology Evaluation and Assessment Criteria for Health apps (TEACH-apps). Methods: Tailoring a well-known implementation framework, Replicating Effective Programs, we present a new process to approach the challenges faced in implementing app evaluation tools today. As a culmination of our experience implementing this process and feedback from stakeholders, we present the four-part process to aid the implementation of mobile health technology. This paper outlines the theory, evidence, and initial versions of the process. Results: The TEACH-apps process is designed to be broadly usable and widely applicable across all fields of health. The process comprises four parts: (1) preconditions (eg, gathering apps and considering local needs), (2) preimplementation (eg, customizing criteria and offering digital skills training), (3) implementation (eg, evaluating apps and creating educational handouts), and (4) maintenance and evolution (eg, repeating the process every 90 days and updating content). TEACH-apps has been tested internally at our hospital, and there is growing interest in partnering health care facilities to test the system at their sites. Conclusions: This implementation framework introduces a process that equips stakeholders, clinicians, and users with the foundational tools to make informed decisions around app use and increase app evaluation engagement. The application of this process may lead to the selection of more culturally appropriate and clinically relevant tools in health care. ", doi="10.2196/18346", url="https://www.jmir.org/2020/8/e18346", url="http://www.ncbi.nlm.nih.gov/pubmed/32535548" } @Article{info:doi/10.2196/18387, author="Kweon, Solbi and Lee, Hoon Jeong and Lee, Younghee and Park, Rang Yu", title="Personal Health Information Inference Using Machine Learning on RNA Expression Data from Patients With Cancer: Algorithm Validation Study", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e18387", keywords="cancer", keywords="privacy issue", keywords="personal information", keywords="prediction", keywords="RNA sequencing", keywords="machine learning", abstract="Background: As the need for sharing genomic data grows, privacy issues and concerns, such as the ethics surrounding data sharing and disclosure of personal information, are raised. Objective: The main purpose of this study was to verify whether genomic data is sufficient to predict a patient's personal information. Methods: RNA expression data and matched patient personal information were collected from 9538 patients in The Cancer Genome Atlas program. Five personal information variables (age, gender, race, cancer type, and cancer stage) were recorded for each patient. Four different machine learning algorithms (support vector machine, decision tree, random forest, and artificial neural network) were used to determine whether a patient's personal information could be accurately predicted from RNA expression data. Performance measurement of the prediction models was based on the accuracy and area under the receiver operating characteristic curve. We selected five cancer types (breast carcinoma, kidney renal clear cell carcinoma, head and neck squamous cell carcinoma, low-grade glioma, and lung adenocarcinoma) with large samples sizes to verify whether predictive accuracy would differ between them. We also validated the efficacy of our four machine learning models in analyzing normal samples from 593 cancer patients. Results: In most samples, personal information with high genetic relevance, such as gender and cancer type, could be predicted from RNA expression data alone. The prediction accuracies for gender and cancer type, which were the best models, were 0.93-0.99 and 0.78-0.94, respectively. Other aspects of personal information, such as age, race, and cancer stage, were difficult to predict from RNA expression data, with accuracies ranging from 0.0026-0.29, 0.76-0.96, and 0.45-0.79, respectively. Among the tested machine learning methods, the highest predictive accuracy was obtained using the support vector machine algorithm (mean accuracy 0.77), while the lowest accuracy was obtained using the random forest method (mean accuracy 0.65). Gender and race were predicted more accurately than other variables in the samples. On average, the accuracy of cancer stage prediction ranged between 0.71-0.67, while the age prediction accuracy ranged between 0.18-0.23 for the five cancer types. Conclusions: We attempted to predict patient information using RNA expression data. We found that some identifiers could be predicted, but most others could not. This study showed that personal information available from RNA expression data is limited and this information cannot be used to identify specific patients. ", doi="10.2196/18387", url="https://www.jmir.org/2020/8/e18387", url="http://www.ncbi.nlm.nih.gov/pubmed/32773372" } @Article{info:doi/10.2196/20108, author="Liu, Dong and Wang, Yuyan and Wang, Juan and Liu, Jue and Yue, Yongjie and Liu, Wenjun and Zhang, Fuhai and Wang, Ziping", title="Characteristics and Outcomes of a Sample of Patients With COVID-19 Identified Through Social Media in Wuhan, China: Observational Study", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e20108", keywords="COVID-19", keywords="risk factors", keywords="web-based data", keywords="outcome", keywords="infectious disease", keywords="clinical characteristic", keywords="mortality", keywords="social media", keywords="prognosis, China", keywords="coronavirus", abstract="Background: The number of deaths worldwide caused by coronavirus disease (COVID-19) is increasing rapidly. Information about the clinical characteristics of patients with COVID-19 who were not admitted to hospital is limited. Some risk factors of mortality associated with COVID-19 are controversial (eg, smoking). Moreover, the impact of city closure on mortality and admission rates is unknown. Objective: The aim of this study was to explore the risk factors of mortality associated with COVID-19 infection among a sample of patients in Wuhan whose conditions were reported on social media. Methods: We enrolled 599 patients with COVID-19 from 67 hospitals in Wuhan in the study; 117 of the participants (19.5\%) were not admitted to hospital. The demographic, epidemiological, clinical, and radiological features of the patients were extracted from their social media posts and coded. Telephone follow-up was conducted 1 month later (between March 15 and 23, 2020) to check the clinical outcomes of the patients and acquire other relevant information. Results: The median age of patients with COVID-19 who died (72 years, IQR 66.5-82.0) was significantly higher than that of patients who recovered (61 years, IQR 53-69, P<.001). We found that lack of admission to hospital (odds ratio [OR] 5.82, 95\% CI 3.36-10.1; P<.001), older age (OR 1.08, 95\% CI 1.06-1.1; P<.001), diffuse distribution (OR 11.09, 95\% CI 0.93-132.9; P=.058), and hypoxemia (odds ratio 2.94, 95\% CI 1.32-6.6; P=.009) were associated with increasing odds of death. Smoking was not significantly associated with mortality risk (OR 0.9, 95\% CI 0.44-1.85; P=.78). Conclusions: Older age, diffuse distribution, and hypoxemia are factors that can help clinicians identify patients with COVID-19 who have poor prognosis. Our study suggests that aggregated data from social media can also be comprehensive, immediate, and informative in disease prognosis. ", doi="10.2196/20108", url="http://www.jmir.org/2020/8/e20108/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716901" } @Article{info:doi/10.2196/19996, author="Al-Dmour, Hani and Masa'deh, Ra'ed and Salman, Amer and Abuhashesh, Mohammad and Al-Dmour, Rand", title="Influence of Social Media Platforms on Public Health Protection Against the COVID-19 Pandemic via the Mediating Effects of Public Health Awareness and Behavioral Changes: Integrated Model", journal="J Med Internet Res", year="2020", month="Aug", day="19", volume="22", number="8", pages="e19996", keywords="social media platforms", keywords="Interventions", keywords="public health", keywords="awareness", keywords="public health protection", keywords="coronavirus", keywords="COVID-19", keywords="pandemic", keywords="behavioral change", keywords="Jordan", keywords="behavior", keywords="social media", abstract="Background: Despite the growing body of literature examining social media in health contexts, including public health communication, promotion, and surveillance, limited insight has been provided into how the utility of social media may vary depending on the particular public health objectives governing an intervention. For example, the extent to which social media platforms contribute to enhancing public health awareness and prevention during epidemic disease transmission is currently unknown. Doubtlessly, coronavirus disease (COVID-19) represents a great challenge at the global level, aggressively affecting large cities and public gatherings and thereby having substantial impacts on many health care systems worldwide as a result of its rapid spread. Each country has its capacity and reacts according to its perception of threat, economy, health care policy, and the health care system structure. Furthermore, we noted a lack of research focusing on the role of social media campaigns in public health awareness and public protection against the COVID-19 pandemic in Jordan as a developing country. Objective: The purpose of this study was to examine the influence of social media platforms on public health protection against the COVID-19 pandemic via public health awareness and public health behavioral changes as mediating factors in Jordan. Methods: A quantitative approach and several social media platforms were used to collect data via web questionnaires in Jordan, and a total of 2555 social media users were sampled. This study used structural equation modeling to analyze and verify the study variables. Results: The main findings revealed that the use of social media platforms had a significant positive influence on public health protection against COVID-19 as a pandemic. Public health awareness and public health behavioral changes significantly acted as partial mediators in this relationship. Therefore, a better understanding of the effects of the use of social media interventions on public health protection against COVID-19 while taking public health awareness and behavioral changes into account as mediators should be helpful when developing any health promotion strategy plan. Conclusions: Our findings suggest that the use of social media platforms can positively influence awareness of public health behavioral changes and public protection against COVID-19. Public health authorities may use social media platforms as an effective tool to increase public health awareness through dissemination of brief messages to targeted populations. However, more research is needed to validate how social media channels can be used to improve health knowledge and adoption of healthy behaviors in a cross-cultural context. ", doi="10.2196/19996", url="http://www.jmir.org/2020/8/e19996/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750004" } @Article{info:doi/10.2196/17696, author="Kujala, Sari and Ammenwerth, Elske and Kolanen, Heta and Ervast, Minna", title="Applying and Extending the FITT Framework to Identify the Challenges and Opportunities of Successful eHealth Services for Patient Self-Management: Qualitative Interview Study", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e17696", keywords="interview", keywords="implementation", keywords="adoption", keywords="patient self-management", keywords="organization", abstract="Background: The number of public eHealth services that support patient self-management is rapidly increasing. However, the implementation of these eHealth services for self-management has encountered challenges. Objective: The purpose of this paper was to analyze the challenges and opportunities of implementing eHealth services for self-management by focusing on the fit between the technical solution and clinical use. Methods: We performed in-depth interviews with 10 clinical project coordinators and managers who were responsible for developing and implementing various eHealth services for self-management interventions in five university hospitals in Finland. The results were analyzed using content analysis and open coding. The Fit between Individuals, Task, and Technology (FITT) framework was used to interpret the findings. Results: The implementation of self-management services involved many challenges related to technical problems, health professional acceptance, patient motivation, and health organization and management. The implementers identified practices to manage the identified challenges, including improving the design of the technology, supporting health professionals in the adoption of the eHealth services, changing the work processes and tasks, involving patients, and collectively planning the implementation inside an organization. The findings could be mostly attributed to the dimensions of the FITT framework. Conclusions: The FITT framework helped to analyze the challenges related to the implementation, and most of them were related to poor fit. The importance of patients as stakeholders in eHealth services for patient self-management needs to be highlighted. Thus, we propose that patients should be added as a different type of individual dimension to the FITT framework. In addition, the framework could be extended to include organization and management in a new context dimension. ", doi="10.2196/17696", url="https://www.jmir.org/2020/8/e17696", url="http://www.ncbi.nlm.nih.gov/pubmed/32784175" } @Article{info:doi/10.2196/20889, author="Dellazizzo, Laura and Potvin, St{\'e}phane and Luigi, Mimosa and Dumais, Alexandre", title="Evidence on Virtual Reality--Based Therapies for Psychiatric Disorders: Meta-Review of Meta-Analyses", journal="J Med Internet Res", year="2020", month="Aug", day="19", volume="22", number="8", pages="e20889", keywords="systematic review", keywords="virtual reality", keywords="therapy", keywords="mental disorders", keywords="meta-analysis", abstract="Background: Among all diseases globally, mental illnesses are one of the major causes of burden. As many people are resistant to conventional evidence-based treatments, there is an unmet need for the implementation of novel mental health treatments. Efforts to increase the effectiveness and benefits of evidence-based psychotherapy in psychiatry have led to the emergence of virtual reality (VR)--based interventions. These interventions have shown a wide range of advantages over conventional psychotherapies. Currently, VR-based interventions have been developed mainly for anxiety-related disorders; however, they are also used for developmental disorders, severe mental disorders, and neurocognitive disorders. Objective: This meta-review aims to summarize the current state of evidence on the efficacy of VR-based interventions for various psychiatric disorders by evaluating the quality of evidence provided by meta-analytical studies. Methods: A systematic search was performed using the following electronic databases: PubMed, PsycINFO, Web of Science, and Google Scholar (any time until February 2020). Meta-analyses were included as long as they quantitatively examined the efficacy of VR-based interventions for symptoms of a psychiatric disorder. To avoid overlap among meta-analyses, for each subanalysis included within this meta-review, only one analysis provided from one meta-analysis was selected based on the best quality of evidence. Results: The search retrieved 11 eligible meta-analyses. The quality of evidence varied from very low to moderate quality. Several reasons account for the lower quality evidence, such as a limited number of randomized controlled trials, lack of follow-up analysis or control group, and the presence of heterogeneity and publication bias. Nonetheless, evidence has shown that VR-based interventions for anxiety-related disorders display overall medium-to-large effects when compared with inactive controls but no significant difference when compared with standard evidence-based approaches. Preliminary data have highlighted that such effects appear to be sustained in time, and subjects may fare better than active controls. Neurocognitive disorders also appear to improve with VR-based approaches, with small effects being found for various clinical outcomes (eg, cognition, emotion). Finally, there are insufficient data to classify VR-based interventions as an evidence-based practice for social skills training in neurodevelopmental disorders and compliance among patients with schizophrenia. Conclusions: VR provides unlimited opportunities by tailoring approaches to specific complex problems and individualizing the intervention. However, VR-based interventions have not shown superiority compared with usual evidence-based treatments. Future VR-based interventions should focus on developing innovative approaches for complex and treatment-resistant symptoms that are difficult to address with traditional treatments. Future research should also aim to gain a better understanding of the potential factors that may mediate VR outcomes to improve treatment. ", doi="10.2196/20889", url="http://www.jmir.org/2020/8/e20889/", url="http://www.ncbi.nlm.nih.gov/pubmed/32812889" } @Article{info:doi/10.2196/19013, author="Zrubka, Zsombor and Brito Fernandes, {\'O}scar and Baji, Petra and Hajdu, Ott{\'o} and Kovacs, Levente and Kringos, Dionne and Klazinga, Niek and Gul{\'a}csi, L{\'a}szl{\'o} and Brodszky, Valentin and Rencz, Fanni and P{\'e}ntek, M{\'a}rta", title="Exploring eHealth Literacy and Patient-Reported Experiences With Outpatient Care in the Hungarian General Adult Population: Cross-Sectional Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e19013", keywords="health literacy", keywords="eHealth literacy, patient-reported experience measures", keywords="patient-reported outcome measures", keywords="ambulatory care", keywords="shared decision making", keywords="Hungary", keywords="survey", abstract="Background: Digital health, which encompasses the use of information and communications technology in support of health, is a key driving force behind the cultural transformation of medicine toward people-centeredness. Thus, eHealth literacy, assisted by innovative digital health solutions, may support better experiences of care. Objective: The purpose of this study is to explore the relationship between eHealth literacy and patient-reported experience measures (PREMs) among users of outpatient care in Hungary. Methods: In early 2019, we conducted a cross-sectional survey on a large representative online sample recruited from the Hungarian general population. eHealth literacy was measured with the eHealth Literacy Scale (eHEALS). PREMs with outpatient care were measured with a set of questions recommended by the Organisation for Economic Co-operation and Development (OECD) for respondents who attended outpatient visit within 12 months preceding the survey. Bivariate relationships were explored via polychoric correlation, the Kruskal--Wallis test, and chi-square test. To capture nonlinear associations, after controlling covariates, we analyzed the relationship between eHEALS quartiles and PREMs using multivariate probit, ordinary least squares, ordered logit, and logistic regression models. Results: From 1000 survey respondents, 666 individuals (364 females, 54.7\%) were included in the study with mean age of 48.9 (SD 17.6) years and mean eHEALS score of 29.3 (SD 4.9). Respondents with higher eHEALS scores were more likely to understand the health care professionals' (HCPs') explanations ($\chi$29=24.2, P=.002) and to be involved in decision making about care and treatment ($\chi$29=18.2, P=.03). In multivariate regression, respondents with lowest (first quartile) and moderately high (third quartile) eHEALS scores differed significantly, where the latter were more likely to have an overall positive experience (P=.02) and experience fewer problems (P=.02). In addition, those respondents had better experiences in terms of how easy it was to understand the HCPs' explanations (P<.001) and being able to ask questions during their last consultation (P=.04). Patient-reported experiences of individuals with highest (fourth quartile) and lowest (first quartile) eHEALS levels did not differ significantly in any items of the PREM instrument, and neither did composite PREM scores generated from the PREM items (P>.05 in all models). Conclusions: We demonstrated the association between eHealth literacy and PREMs. The potential patient-, physician-, and system-related factors explaining the negative experiences among people with highest levels of eHealth literacy warrant further investigation, which may contribute to the development of efficient eHealth literacy interventions. Further research is needed to establish causal relationship between eHealth literacy and patient-reported experiences. ", doi="10.2196/19013", url="https://www.jmir.org/2020/8/e19013", url="http://www.ncbi.nlm.nih.gov/pubmed/32667891" } @Article{info:doi/10.2196/18476, author="Cheng, Christina and Beauchamp, Alison and Elsworth, R. Gerald and Osborne, H. Richard", title="Applying the Electronic Health Literacy Lens: Systematic Review of Electronic Health Interventions Targeted at Socially Disadvantaged Groups", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e18476", keywords="eHealth", keywords="health literacy", keywords="internet", keywords="health care", keywords="telecommunications", keywords="digital divide", keywords="health equity", abstract="Background: Electronic health (eHealth) has the potential to improve health outcomes. However, eHealth systems need to match the eHealth literacy needs of users to be equitably adopted. Socially disadvantaged groups have lower access and skills to use technologies and are at risk of being digitally marginalized, leading to the potential widening of health disparities. Objective: This systematic review aims to explore the role of eHealth literacy and user involvement in developing eHealth interventions targeted at socially disadvantaged groups. Methods: A systematic search was conducted across 10 databases for eHealth interventions targeted at older adults, ethnic minority groups, low-income groups, low-literacy groups, and rural communities. The eHealth Literacy Framework was used to examine the eHealth literacy components of reviewed interventions. The results were analyzed using narrative synthesis. Results: A total of 51 studies reporting on the results of 48 interventions were evaluated. Most studies were targeted at older adults and ethnic minorities, with only 2 studies focusing on low-literacy groups. eHealth literacy was not considered in the development of any of the studies, and no eHealth literacy assessment was conducted. User involvement in designing interventions was limited, and eHealth intervention developmental frameworks were rarely used. Strategies to assist users in engaging with technical systems were seldom included in the interventions, and accessibility features were limited. The results of the included studies also provided inconclusive evidence on the effectiveness of eHealth interventions. Conclusions: The findings highlight that eHealth literacy is generally overlooked in developing eHealth interventions targeted at socially disadvantaged groups, whereas evidence about the effectiveness of such interventions is limited. To ensure equal access and inclusiveness in the age of eHealth, eHealth literacy of disadvantaged groups needs to be addressed to help avoid a digital divide. This will assist the realization of recent technological advancements and, importantly, improve health equity. ", doi="10.2196/18476", url="http://www.jmir.org/2020/8/e18476/", url="http://www.ncbi.nlm.nih.gov/pubmed/32788144" } @Article{info:doi/10.2196/19056, author="Yang, Ching Shu and Hsu, Wan-Chen and Chiang, Chia-Hsun", title="The Associations Among Individual Factors, Media Literacy, and Dietary Supplement Use Among College Students: Cross-Sectional Study", journal="J Med Internet Res", year="2020", month="Aug", day="31", volume="22", number="8", pages="e19056", keywords="college student", keywords="dietary supplement", keywords="media literacy", keywords="ehealth literacy", abstract="Background: The mass media have been condemned for encouraging young people to take dietary supplements (DS). Media literacy, which includes authors and audiences (AA), messages and meanings (MM), and representation and reality (RR) domains, is a new approach to teaching young adults to make better informed health decisions. However, it is not clear which domains are the most important for media literacy education. Objective: The purpose of this study is to investigate the associations among individual factors, media literacy, and DS use. Methods: The survey instrument included demographic items, the DS Media Literacy Scale (DSMLS), and DS use items (users or nonusers, types of DS, current use of DS, and intention to use DS in the future). The DSMLS is an 11-item instrument designed to assess college students' AA, MM, and RR media literacy in relation to DS. A total of 467 Taiwanese college students participated in the study. Descriptive statistical analysis, logistic regression analysis, and multiple regression analysis were conducted. Results: A total of 338/467 (72.4\%) participants reported using DS, and 176/467 (37.7\%) consumed 3 or more supplements. Moreover, the MM media literacy domain was associated with having been a DS user (odds ratio 0.63, P=.002), current DS use ($\beta$=--.10, P=.02), and intention to use DS in the future ($\beta$=--.12, P=.011). Finally, perceived importance of health was positively related to current DS use ($\beta$=.18, P=.001) and intention to use DS in the future ($\beta$=.18, P=.001). Conclusions: This study showed that the majority of Taiwanese college students were DS users and used multiple types of supplements. Moreover, students with lower MM media literacy were more likely to be DS users, to take DS more frequently, and to have higher intentions for future frequent DS use. Finally, those who placed extreme importance on health were more likely to take DS frequently and have higher intentions for future frequent DS use. ", doi="10.2196/19056", url="http://www.jmir.org/2020/8/e19056/", url="http://www.ncbi.nlm.nih.gov/pubmed/32865500" } @Article{info:doi/10.2196/18078, author="Chang, I-Chiu and Lin, Po-Jin and Chen, Ting-Hung and Chang, Chia-Hui", title="Cultural Impact on the Intention to Use Nursing Information Systems of Nurses in Taiwan and China: Survey and Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e18078", keywords="Nursing information system", keywords="intention to use", keywords="cultural differences", keywords="information literacy", abstract="Background: Nursing workforce shortage has emerged as a global problem. Foreign nurse importation is a popular strategy to address the shortage. The interactions between nursing staff on either side of the Taiwan Strait continue to increase. Since both nurses in Taiwan and nurses in China have adopted nursing information systems to improve health care processes and quality, it is necessary to investigate factors influencing nursing information system usage in nursing practice. Objective: This study examined the effects of cultural and other related factors on nurses' intentions to use nursing information systems. The findings were expected to serve as an empirical base for further benchmarking and management of cross-strait nurses. Methods: This survey was conducted in two case hospitals (one in Taiwan and one in China). A total of 880 questionnaires were distributed (n=440 in each hospital). Results: The results showed effort expectancy had a significant effect on the intention to use nursing information systems of nurses in China (P=.003) but not nurses in Taiwan (P=.16). Conclusions: Findings suggest nursing managers should adopt different strategies to motivate cross-strait nurses to use nursing information systems. Promoting effort expectancy is more likely to motivate nurses in China than in Taiwan. This discrepancy is probably due to the less hierarchical and more feminine society in Taiwan. ", doi="10.2196/18078", url="https://www.jmir.org/2020/8/e18078", url="http://www.ncbi.nlm.nih.gov/pubmed/32784174" } @Article{info:doi/10.2196/15630, author="De Leeuw, A. Jacqueline and Woltjer, Hetty and Kool, B. Rudolf", title="Identification of Factors Influencing the Adoption of Health Information Technology by Nurses Who Are Digitally Lagging: In-Depth Interview Study", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e15630", keywords="qualitative research", keywords="semi-structured interview", keywords="purposive sampling", keywords="health information systems", keywords="computer user training", keywords="professional education", keywords="professional competence", keywords="registered nurses", keywords="nursing informatics", abstract="Background: The introduction of health information technology (HIT) has drastically changed health care organizations and the way health care professionals work. Some health care professionals have trouble coping efficiently with the demands of HIT and the personal and professional changes it requires. Lagging in digital knowledge and skills hampers health care professionals from adhering to professional standards regarding the use of HIT and may cause professional performance problems, especially in the older professional population. It is important to gain more insight into the reasons and motivations behind the technology issues experienced by these professionals, as well as to explore what could be done to solve them. Objective: Our primary research objective was to identify factors that influence the adoption of HIT in a sample of nurses who describe themselves as digitally lagging behind the majority of their colleagues in their workplaces. Furthermore, we aimed to formulate recommendations for practice and leadership on how to help and guide these nurses through ongoing digital transformations in their health care work settings. Methods: In a Dutch university medical center, 10 face-to-face semi-structured interviews were performed with registered nurses (RN). Ammenwerth's FITT-framework (fit between the Individual, Task, and Technology) was used to guide the interview topic list and to formulate themes to explore. Thematic analysis was used to analyze the interview data. The FITT-framework was also used to further interpret and clarify the interview findings. Results: Analyses of the interview data uncovered 5 main categories and 12 subthemes. The main categories were: (1) experience with digital working, (2) perception and meaning, (3) barriers, (4) facilitators, and (5) future perspectives. All participants used electronic devices and digital systems, including the electronic health record. The latter was experienced by some as user-unfriendly, time-consuming, and not supportive in daily professional practice. Most of the interviewees described digital working as ``no fun at all,'' ``working in a fake world,'' ``stressful,'' and ``annoying.'' There was a lack of general digital knowledge and little or no formal basic digital training or education. A negative attitude toward computer use and a lack of digital skills contributed to feelings of increased incompetency and postponement or avoidance of the use of HIT, both privately and professionally. Learning conditions of digital training and education did not meet personal learning needs and learning styles. A positive impact was seen in the work environment when colleagues and nurse managers were aware and sensitive to the difficulties participants experienced in developing digital skills, and when there was continuous training on the job and peer support from digitally savvy colleagues. The availability of a digital play environment combined with learning on the job and support of knowledgeable peers was experienced as helpful and motivating by participants. Conclusions: Nurses who are digitally lagging often have had insufficient and ineffective digital education. This leads to stress, frustration, feelings of incompetency, and postponement or avoidance of HIT use. A digital training approach tailored to the learning needs and styles of these nurses is needed, as well as an on-the-job training structure and adequate peer support. Hospital management and nurse leadership should be informed about the importance of the fit between technology, task, and the individual for adequate adoption of HIT. ", doi="10.2196/15630", url="http://www.jmir.org/2020/8/e15630/", url="http://www.ncbi.nlm.nih.gov/pubmed/32663142" } @Article{info:doi/10.2196/18374, author="McLennan, Stuart", title="Rejected Online Feedback From a Swiss Physician Rating Website Between 2008 and 2017: Analysis of 2352 Ratings", journal="J Med Internet Res", year="2020", month="Aug", day="3", volume="22", number="8", pages="e18374", keywords="physician rating websites", keywords="patient satisfaction", keywords="participatory medicine", keywords="patient feedback", abstract="Background: Previous research internationally has only analyzed publicly available feedback on physician rating websites (PRWs). However, it appears that many PRWs are not publishing all the feedback they receive. Analysis of this rejected feedback could provide a better understanding of the types of feedback that are currently not published and whether this is appropriate. Objective: The aim of this study was to examine (1) the number of patient feedback rejected from the Swiss PRW Medicosearch, (2) the evaluation tendencies of the rejected patient feedback, and (3) the types of issues raised in the rejected narrative comments. Methods: The Swiss PRW Medicosearch provided all the feedback that had been rejected between September 16, 2008, and September 22, 2017. The feedback were analyzed and classified according to a theoretical categorization framework of physician-, staff-, and practice-related issues. Results: Between September 16, 2008, and September 22, 2017, Medicosearch rejected a total of 2352 patient feedback. The majority of feedback rejected (1754/2352, 74.6\%) had narrative comments in the German language. However, 11.9\% (279/2352) of the rejected feedback only provided a quantitative rating with no narrative comment. Overall, 25\% (588/2352) of the rejected feedback were positive, 18.7\% (440/2352) were neutral, and 56\% (1316/2352) were negative. The average rating of the rejected feedback was 2.8 (SD 1.4). In total, 44 subcategories addressing the physician (n=20), staff (n=9), and practice (n=15) were identified. In total, 3804 distinct issues were identified within the 44 subcategories of the categorization framework; 75\% (2854/3804) of the issues were related to the physician, 6.4\% (242/3804) were related to the staff, and 18.6\% (708/3804) were related to the practice. Frequently mentioned issues identified from the rejected feedback included (1) satisfaction with treatment (533/1903, 28\%); (2) the overall assessment of the physician (392/1903, 20.6\%); (3) recommending the physician (345/1903, 18.1\%); (4) the physician's communication (261/1903, 13.7\%); (5) the physician's caring attitude (220/1903, 11.6\%); and (6) the physician's friendliness (203/1903, 10.6\%). Conclusions: It is unclear why the majority of the feedback were rejected. This is problematic and raises concerns that online patient feedback are being inappropriately manipulated. If online patient feedback is going to be collected, there needs to be clear policies and practices about how this is handled. It cannot be left to the whims of PRWs, who may have financial incentives to suppress negative feedback, to decide which feedback is or is not published online. Further research is needed to examine how many PRWs are using criteria for determining which feedback is published or not, what those criteria are, and what measures PRWs are using to address the manipulation of online patient feedback. ", doi="10.2196/18374", url="https://www.jmir.org/2020/8/e18374", url="http://www.ncbi.nlm.nih.gov/pubmed/32687479" } @Article{info:doi/10.2196/19216, author="Damschroder, J. Laura and Buis, R. Lorraine and McCant, A. Felicia and Kim, Myra Hyungjin and Evans, Richard and Oddone, Z. Eugene and Bastian, A. Lori and Hooks, Gwendolyn and Kadri, Reema and White-Clark, Courtney and Richardson, R. Caroline and Gierisch, M. Jennifer", title="Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="Aug", day="4", volume="22", number="8", pages="e19216", keywords="exercise", keywords="veterans", keywords="smartphones", keywords="wearable physical activity tracker", keywords="behavior change", keywords="mobile phone", keywords="online", keywords="app", keywords="mobile app", keywords="wearable", abstract="Background: Though maintaining physical conditioning and a healthy weight are requirements of active military duty, many US veterans lose conditioning and rapidly gain weight after discharge from active duty service. Mobile health (mHealth) interventions using wearable devices are appealing to users and can be effective especially with personalized coaching support. We developed Stay Strong, a mobile app tailored to US veterans, to promote physical activity using a wrist-worn physical activity tracker, a Bluetooth-enabled scale, and an app-based dashboard. We tested whether adding personalized coaching components (Stay Strong+Coaching) would improve physical activity compared to Stay Strong alone. Objective: The goal of this study is to compare 12-month outcomes from Stay Strong alone versus Stay Strong+Coaching. Methods: Participants (n=357) were recruited from a national random sample of US veterans of recent wars and randomly assigned to the Stay Strong app alone (n=179) or Stay Strong+Coaching (n=178); both programs lasted 12 months. Personalized coaching components for Stay Strong+Coaching comprised of automated in-app motivational messages (3 per week), telephone-based human health coaching (up to 3 calls), and personalized weekly goal setting. All aspects of the enrollment process and program delivery were accomplished virtually for both groups, except for the telephone-based coaching. The primary outcome was change in physical activity at 12 months postbaseline, measured by average weekly Active Minutes, captured by the Fitbit Charge 2 device. Secondary outcomes included changes in step counts, weight, and patient activation. Results: The average age of participants was 39.8 (SD 8.7) years, and 25.2\% (90/357) were female. Active Minutes decreased from baseline to 12 months for both groups (P<.001) with no between-group differences at 6 months (P=.82) or 12 months (P=.98). However, at 12 months, many participants in both groups did not record Active Minutes, leading to missing data in 67.0\% (120/179) for Stay Strong and 61.8\% (110/178) for Stay Strong+Coaching. Average baseline weight for participants in Stay Strong and Stay Strong+Coaching was 214 lbs and 198 lbs, respectively, with no difference at baseline (P=.54) or at 6 months (P=.28) or 12 months (P=.18) postbaseline based on administrative weights, which had lower rates of missing data. Changes in the number of steps recorded and patient activation also did not differ by arm. Conclusions: Adding personalized health coaching comprised of in-app automated messages, up to 3 coaching calls, plus automated weekly personalized goals, did not improve levels of physical activity compared to using a smartphone app alone. Physical activity in both groups decreased over time. Sustaining long-term adherence and engagement in this mHealth intervention proved difficult; approximately two-thirds of the trial's 357 participants failed to sync their Fitbit device at 12 months and, thus, were lost to follow-up. Trial Registration: ClinicalTrials.gov NCT02360293; https://clinicaltrials.gov/ct2/show/NCT02360293 International Registered Report Identifier (IRRID): RR2-10.2196/12526 ", doi="10.2196/19216", url="http://www.jmir.org/2020/8/e19216/", url="http://www.ncbi.nlm.nih.gov/pubmed/32687474" } @Article{info:doi/10.2196/15335, author="Rossen, Sine and Kayser, Lars and Vibe-Petersen, Jette and Christensen, Frank Jesper and Ried-Larsen, Mathias", title="Cancer Survivors' Receptiveness to Digital Technology--Supported Physical Rehabilitation and the Implications for Design: Qualitative Study", journal="J Med Internet Res", year="2020", month="Aug", day="5", volume="22", number="8", pages="e15335", keywords="cancer", keywords="rehabilitation", keywords="physical activity", keywords="digital technology", abstract="Background: Physical activity is associated with a positive prognosis in cancer survivors and may decrease the risk of adverse effects of treatment. Accordingly, physical activity programs are recommended as a part of cancer rehabilitation services. Digital technology may support cancer survivors in increasing their level of physical activity and increase the reach or efficiency of cancer rehabilitation services, yet it also comes with a range of challenges. Objective: The aim of this qualitative study was to explore cancer survivors' receptiveness to using digital technology as a mode of support to increase their physical activity in a municipality-based cancer rehabilitation setting. Methods: Semistructured interviews were conducted with 11 cancer survivors (3 males, 8 females, age range 32-82 years) who were referred for cancer rehabilitation and had participated in a questionnaire survey using the Readiness and Enablement Index for Health Technology (READHY) questionnaire. Data analysis was based on the content analysis method. Results: Two themes were identified as important for the interviewees' receptiveness to using digital technology services in connection with their physical activity during rehabilitation: their attitude toward physical activity and their attitude toward digital technology--assisted physical activity. Our results indicated that it is important to address the cancer survivors' motivation for using technology for physical activity and their individual preferences in terms of the following: (1) incidental or structured (eg, cardiovascular and strength exercises or disease-specific rehabilitative exercises) physical activity; (2) social or individual context; and (3) instruction (know-how) or information (know-why). Conclusions: The identified preferences provide new insight that complements the cancer survivors' readiness level and can likely help designers, service providers, and caregivers provide solutions that increase patient receptiveness toward technology-assisted physical activity. Combining digital technology informed by cancer survivors' needs, preferences, and readiness with the capacity building of the workforce can aid in tailoring digital solutions to suit not only individuals who are receptive to using such technologies but also those reluctant to do so. ", doi="10.2196/15335", url="https://www.jmir.org/2020/8/e15335", url="http://www.ncbi.nlm.nih.gov/pubmed/32755892" } @Article{info:doi/10.2196/13573, author="Koorts, Harriet and Salmon, Jo and Timperio, Anna and Ball, Kylie and Macfarlane, Susie and Lai, K. Samuel and Brown, Helen and Chappel, E. Stephanie and Lewis, Marina and Ridgers, D. Nicola", title="Translatability of a Wearable Technology Intervention to Increase Adolescent Physical Activity: Mixed Methods Implementation Evaluation", journal="J Med Internet Res", year="2020", month="Aug", day="7", volume="22", number="8", pages="e13573", keywords="wearable technology", keywords="social media", keywords="implementation science", keywords="adolescent", keywords="physical activity", keywords="awareness", abstract="Background: Wearable technology interventions combined with digital behavior change resources provide opportunities to increase physical activity in adolescents. The implementation of such interventions in real-world settings is unknown. The Raising Awareness of Physical Activity (RAW-PA) study was a 12-week cluster randomized controlled trial targeting inactive adolescents attending schools in socioeconomically disadvantaged areas of Melbourne, Australia. The aim was to increase moderate- to vigorous-intensity physical activity using (1) a wrist-worn Fitbit Flex and app, (2) weekly challenges, (3) digital behavior change resources, and (4) email or text message alerts. Objective: This paper presents adolescents' and teachers' perceptions of RAW-PA in relation to program acceptability, feasibility and perceived impact, adolescent engagement and adherence, and the potential for future scale-up. Methods: A mixed methods evaluation of the RAW-PA study assessed acceptability, engagement, feasibility, adherence, and perceived impact. A total of 9 intervention schools and 144 intervention adolescents were recruited. Only adolescents and teachers (n=17) in the intervention group were included in the analysis. Adolescents completed web-based surveys at baseline and surveys and focus groups postintervention. Teachers participated in interviews postintervention. Facebook data tracked engagement with web-based resources. Descriptive statistics were reported by sex. Qualitative data were analyzed thematically. Results: Survey data were collected from 142 adolescents at baseline (mean age 13.7 years, SD 0.4 years; 51\% males) and 132 adolescents postintervention. A total of 15 focus groups (n=124) and 9 interviews (n=17) were conducted. RAW-PA had good acceptability among adolescents and teachers. Adolescents perceived the intervention content as easy to understand (100/120, 83.3\%) and the Fitbit easy to use (112/120; 93.3\%). Half of the adolescents perceived the text messages to be useful (61/120; 50.8\%), whereas 47.5\% (57/120) liked the weekly challenges and 38.3\% (46/120) liked the Facebook videos. Facebook engagement declined over time; only 18.6\% (22/118) of adolescents self-reported wearing the Fitbit Flex daily postintervention. Adolescents perceived the Fitbit Flex to increase their physical activity motivation (85/120, 70.8\%) and awareness (93/119, 78.2\%). The web-based delivery facilitated implementation of the intervention, although school-level policies restricting phone use were perceived as potential inhibitors to program roll-out. Conclusions: RAW-PA showed good acceptability among adolescents attending schools in socioeconomically disadvantaged areas and their teachers. Low levels of teacher burden enhanced their perceptions concerning the feasibility of intervention delivery. Although adolescents perceived that RAW-PA had short-term positive effects on their motivation to be physically active, adolescent adherence and engagement were low. Future research exploring the feasibility of different strategies to engage adolescents with wearable technology interventions and ways of maximizing system-level embeddedness of interventions in practice would greatly advance the field. ", doi="10.2196/13573", url="https://www.jmir.org/2020/8/e13573", url="http://www.ncbi.nlm.nih.gov/pubmed/32763872" } @Article{info:doi/10.2196/17459, author="Karni, Liran and Dalal, Koustuv and Memedi, Mevludin and Kalra, Dipak and Klein, Oskar Gunnar", title="Information and Communications Technology--Based Interventions Targeting Patient Empowerment: Framework Development", journal="J Med Internet Res", year="2020", month="Aug", day="26", volume="22", number="8", pages="e17459", keywords="empowerment", keywords="ICT intervention", keywords="digital health", keywords="eHealth", keywords="framework model", keywords="ICT patient empowerment model (ICT4PEM)", abstract="Background: Empowerment of patients is often an explicit goal of various information and communications technology (ICT) (electronic, digital) interventions where the patients themselves use ICT tools via the internet. Although several models of empowerment exist, a comprehensive and pragmatic framework is lacking for the development of such interventions. Objective: This study proposes a framework for digital interventions aiming to empower patients that includes a methodology that links objectives, strategies, and evaluation. Methods: This study is based on a literature review and iterated expert discussions including a focus group to formulate the proposed model. Our model is based on a review of various models of empowerment and models of technology intervention. Results: Our framework includes the core characteristics of the empowerment concept (control, psychological coping, self-efficacy, understanding, legitimacy, and support) as well as a set of empowerment consequences: expressed patient perceptions, behavior, clinical outcomes, and health systems effects. The framework for designing interventions includes strategies to achieve empowerment goals using different ICT services. Finally, the intervention model can be used to define project evaluations where the aim is to demonstrate empowerment. The study also included example indicators and associated measurement instruments. Conclusions: This framework, which includes definitions, can be useful for the design and evaluation of digital interventions targeting patient empowerment and assist in the development of methods to measure results in this dimension. Further evaluation in the form of interventional studies will be needed to assess the generalizability of the model. ", doi="10.2196/17459", url="http://www.jmir.org/2020/8/e17459/", url="http://www.ncbi.nlm.nih.gov/pubmed/32845245" } @Article{info:doi/10.2196/16778, author="Loo, Stephanie and Grasso, Chris and Glushkina, Jessica and McReynolds, Justin and Lober, William and Crane, Heidi and Mayer, H. Kenneth", title="Capturing Relevant Patient Data in Clinical Encounters Through Integration of an Electronic Patient-Reported Outcome System Into Routine Primary Care in a Boston Community Health Center: Development and Implementation Study", journal="J Med Internet Res", year="2020", month="Aug", day="19", volume="22", number="8", pages="e16778", keywords="information technology in health", keywords="primary care", keywords="technology adoption", keywords="technology diffusion", abstract="Background: Electronic patient-reported outcome (ePRO) systems can improve health outcomes by detecting health issues or risk behaviors that may be missed when relying on provider elicitation. Objective: This study aimed to implement an ePRO system that administers key health questionnaires in an urban community health center in Boston, Massachusetts. Methods: An ePRO system that administers key health questionnaires was implemented in an urban community health center in Boston, Massachusetts. The system was integrated with the electronic health record so that medical providers could review and adjudicate patient responses in real-time during the course of the patient visit. This implementation project was accomplished through careful examination of clinical workflows and a graduated rollout process that was mindful of patient and clinical staff time and burden. Patients responded to questionnaires using a tablet at the beginning of their visit. Results: Our program demonstrates that implementation of an ePRO system in a primary care setting is feasible, allowing for facilitation of patient-provider communication and care. Other community health centers can learn from our model in terms of applying technological innovation to streamline clinical processes and improve patient care. Conclusions: Our program demonstrates that implementation of an ePRO system in a primary care setting is feasible, allowing for facilitation of patient-provider communication and care. Other community health centers can learn from our model for application of technological innovation to streamline clinical processes and improve patient care. ", doi="10.2196/16778", url="http://www.jmir.org/2020/8/e16778/", url="http://www.ncbi.nlm.nih.gov/pubmed/32554372" } @Article{info:doi/10.2196/17186, author="Benis, Arriel and Barak Barkan, Refael and Sela, Tomer and Harel, Nissim", title="Communication Behavior Changes Between Patients With Diabetes and Healthcare Providers Over 9 Years: Retrospective Cohort Study", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17186", keywords="population characteristics", keywords="eHealth", keywords="mHealth", keywords="consumer health informatics", keywords="delivery of health care", keywords="machine learning", keywords="clustering", keywords="quality of health care", keywords="point-of-care systems", keywords="physician-patient relations", abstract="Background: Health organizations and patients interact over different communication channels and are harnessing digital communications for this purpose. Assisting health organizations to improve, adapt, and introduce new patient--health care practitioner communication channels (such as patient portals, mobile apps, and text messaging) enhances health care services access. Objective: This retrospective data study aims to assist health care administrators and policy makers to improve and personalize communication between patients and health care professionals by expanding the capabilities of current communication channels and introducing new ones. Our main hypothesis is that patient follow-up and clinical outcomes are influenced by their preferred communication channels with the health care organization. Methods: This study analyzes data stored in electronic medical records and logs documenting access to various communication channels between patients and a health organization (Clalit Health Services, Israel). Data were collected between 2008 and 2016 from records of 311,168 patients diagnosed with diabetes, aged 21 years and over, members of Clalit at least since 2007, and still alive in 2016. The analysis consisted of characterizing the use profiles of communication channels over time and used clustering for discretization purposes and patient profile building and then a hierarchical clustering and heatmaps to visualize the different communication profiles. Results: A total of 13 profiles of patients were identified and characterized. We have shown how the communication channels provided by the health organization influence the communication behavior of patients. We observed how different patients respond differently to technological means of communication and change or don't change their communication patterns with the health care organization based on the communication channels available to them. Conclusions: Identifying the channels of communication within the health organization and which are preferred by each patient creates an opportunity to convey messages adapted to the patient in the most appropriate way. The greater the likelihood that the therapeutic message is received by the patient, the greater the patient's response and proactiveness to the treatment will be. International Registered Report Identifier (IRRID): RR2-10.2196/10734 ", doi="10.2196/17186", url="http://www.jmir.org/2020/8/e17186/", url="http://www.ncbi.nlm.nih.gov/pubmed/32648555" } @Article{info:doi/10.2196/17211, author="Iqbal, Usman and Celi, Anthony Leo and Li, Jack Yu-Chuan", title="How Can Artificial Intelligence Make Medicine More Preemptive?", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17211", keywords="artificial intelligence", keywords="digital health", keywords="eHealth", keywords="health care technology", keywords="medical innovations", keywords="health information technology", keywords="advanced care systems", doi="10.2196/17211", url="https://www.jmir.org/2020/8/e17211", url="http://www.ncbi.nlm.nih.gov/pubmed/32780024" } @Article{info:doi/10.2196/20007, author="Michelson, Matthew and Chow, Tiffany and Martin, A. Neil and Ross, Mike and Tee Qiao Ying, Amelia and Minton, Steven", title="Artificial Intelligence for Rapid Meta-Analysis: Case Study on Ocular Toxicity of Hydroxychloroquine", journal="J Med Internet Res", year="2020", month="Aug", day="17", volume="22", number="8", pages="e20007", keywords="meta-analysis", keywords="rapid meta-analysis", keywords="artificial intelligence", keywords="drug", keywords="analysis", keywords="hydroxychloroquine", keywords="toxic", keywords="COVID-19", keywords="treatment", keywords="side effect", keywords="ocular", keywords="eye", abstract="Background: Rapid access to evidence is crucial in times of an evolving clinical crisis. To that end, we propose a novel approach to answer clinical queries, termed rapid meta-analysis (RMA). Unlike traditional meta-analysis, RMA balances a quick time to production with reasonable data quality assurances, leveraging artificial intelligence (AI) to strike this balance. Objective: We aimed to evaluate whether RMA can generate meaningful clinical insights, but crucially, in a much faster processing time than traditional meta-analysis, using a relevant, real-world example. Methods: The development of our RMA approach was motivated by a currently relevant clinical question: is ocular toxicity and vision compromise a side effect of hydroxychloroquine therapy? At the time of designing this study, hydroxychloroquine was a leading candidate in the treatment of coronavirus disease (COVID-19). We then leveraged AI to pull and screen articles, automatically extract their results, review the studies, and analyze the data with standard statistical methods. Results: By combining AI with human analysis in our RMA, we generated a meaningful, clinical result in less than 30 minutes. The RMA identified 11 studies considering ocular toxicity as a side effect of hydroxychloroquine and estimated the incidence to be 3.4\% (95\% CI 1.11\%-9.96\%). The heterogeneity across individual study findings was high, which should be taken into account in interpretation of the result. Conclusions: We demonstrate that a novel approach to meta-analysis using AI can generate meaningful clinical insights in a much shorter time period than traditional meta-analysis. ", doi="10.2196/20007", url="http://www.jmir.org/2020/8/e20007/", url="http://www.ncbi.nlm.nih.gov/pubmed/32804086" } @Article{info:doi/10.2196/19018, author="Ferrand, John and Hockensmith, Ryli and Houghton, Fagen Rebecca and Walsh-Buhi, R. Eric", title="Evaluating Smart Assistant Responses for Accuracy and Misinformation Regarding Human Papillomavirus Vaccination: Content Analysis Study", journal="J Med Internet Res", year="2020", month="Aug", day="3", volume="22", number="8", pages="e19018", keywords="digital health", keywords="human papillomavirus", keywords="smart assistants", keywords="chatbots", keywords="conversational agents", keywords="misinformation", keywords="infodemiology", keywords="vaccination", abstract="Background: Almost half (46\%) of Americans have used a smart assistant of some kind (eg, Apple Siri), and 25\% have used a stand-alone smart assistant (eg, Amazon Echo). This positions smart assistants as potentially useful modalities for retrieving health-related information; however, the accuracy of smart assistant responses lacks rigorous evaluation. Objective: This study aimed to evaluate the levels of accuracy, misinformation, and sentiment in smart assistant responses to human papillomavirus (HPV) vaccination--related questions. Methods: We systematically examined responses to questions about the HPV vaccine from the following four most popular smart assistants: Apple Siri, Google Assistant, Amazon Alexa, and Microsoft Cortana. One team member posed 10 questions to each smart assistant and recorded all queries and responses. Two raters independently coded all responses ($\kappa$=0.85). We then assessed differences among the smart assistants in terms of response accuracy, presence of misinformation, and sentiment regarding the HPV vaccine. Results: A total of 103 responses were obtained from the 10 questions posed across the smart assistants. Google Assistant data were excluded owing to nonresponse. Over half (n=63, 61\%) of the responses of the remaining three smart assistants were accurate. We found statistically significant differences across the smart assistants (N=103, $\chi$22=7.807, P=.02), with Cortana yielding the greatest proportion of misinformation. Siri yielded the greatest proportion of accurate responses (n=26, 72\%), whereas Cortana yielded the lowest proportion of accurate responses (n=33, 54\%). Most response sentiments across smart assistants were positive (n=65, 64\%) or neutral (n=18, 18\%), but Cortana's responses yielded the largest proportion of negative sentiment (n=7, 12\%). Conclusions: Smart assistants appear to be average-quality sources for HPV vaccination information, with Alexa responding most reliably. Cortana returned the largest proportion of inaccurate responses, the most misinformation, and the greatest proportion of results with negative sentiments. More collaboration between technology companies and public health entities is necessary to improve the retrieval of accurate health information via smart assistants. ", doi="10.2196/19018", url="https://www.jmir.org/2020/8/e19018", url="http://www.ncbi.nlm.nih.gov/pubmed/32744508" } @Article{info:doi/10.2196/17521, author="Kim, Junetae and Kam, Jin Hye and Kim, Youngin and Lee, Yura and Lee, Jae-Ho", title="Understanding Time Series Patterns of Weight and Meal History Reports in Mobile Weight Loss Intervention Programs: Data-Driven Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e17521", keywords="weight loss", keywords="self-reporting", keywords="adherence", keywords="mobile weight loss intervention", keywords="diet", abstract="Background: Mobile apps for weight loss provide users with convenient features for recording lifestyle and health indicators; they have been widely used for weight loss recently. Previous studies in this field generally focused on the relationship between the cumulative nature of self-reported data and the results in weight loss at the end of the diet period. Therefore, we conducted an in-depth study to explore the relationships between adherence to self-reporting and weight loss outcomes during the weight reduction process. Objective: We explored the relationship between adherence to self-reporting and weight loss outcomes during the time series weight reduction process with the following 3 research questions: ``How does adherence to self-reporting of body weight and meal history change over time?'', ``How do weight loss outcomes depend on weight changes over time?'', and ``How does adherence to the weight loss intervention change over time by gender?'' Methods: We analyzed self-reported data collected weekly for 16 weeks (January 2017 to March 2018) from 684 Korean men and women who participated in a mobile weight loss intervention program provided by a mobile diet app called Noom. Analysis of variance (ANOVA) and chi-squared tests were employed to determine whether the baseline characteristics among the groups of weight loss results were different. Based on the ANOVA results and slope analysis of the trend indicating participant behavior along the time axis, we explored the relationship between adherence to self-reporting and weight loss results. Results: Adherence to self-reporting levels decreased over time, as previous studies have found. BMI change patterns (ie, absolute BMI values and change in BMI values within a week) changed over time and were characterized in 3 time series periods. The relationships between the weight loss outcome and both meal history and self-reporting patterns were gender-dependent. There was no statistical association between adherence to self-reporting and weight loss outcomes in the male participants. Conclusions: Although mobile technology has increased the convenience of self-reporting when dieting, it should be noted that technology itself is not the essence of weight loss. The in-depth understanding of the relationship between adherence to self-reporting and weight loss outcome found in this study may contribute to the development of better weight loss interventions in mobile environments. ", doi="10.2196/17521", url="https://www.jmir.org/2020/8/e17521", url="http://www.ncbi.nlm.nih.gov/pubmed/32780028" } @Article{info:doi/10.2196/18003, author="?ukasik, Sylwia and Tobis, S?awomir and Kropi?ska, Sylwia and Suwalska, Aleksandra", title="Role of Assistive Robots in the Care of Older People: Survey Study Among Medical and Nursing Students", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e18003", keywords="assistive robots", keywords="older adults", keywords="acceptance", keywords="medical students", keywords="nursing students", abstract="Background: Populations are aging at an alarming rate in many countries around the world. There has been not only a decrease in the number of births and an increase in the percentage of older people, but also an increase in the number of people living alone. There is growing demand for specialist medical care and daily care with the number of people who can act as caregivers reducing. The use of assistive robots can, at least partially, solve these problems. Objective: The purpose of this study was to examine the opinions of future health care professionals (medical and nursing students) regarding the use of assistive robots in the care of older people. Methods: The study was conducted with a group of 178 students from Poznan University of Medical Sciences, Pozna?, Poland (110 nursing students and 68 medical students), using the Users' Needs, Requirements, and Abilities Questionnaire. Results: The participants of this study believed that assistive robots should, first of all, remind older people to take medication regularly, ensure their safety, monitor their health status and environment, provide cognitive training, and encourage them to maintain physical activity. In the students' opinion, the robot should not be an older person's companion but only act as an assistant. Nursing students had significantly higher scores than medical students in several statements concerning everyday use of robots, including reminding about meals (P=.03), monitoring the environment (P=.001), providing advice about a healthy diet (P=.04), monitoring the intake of food and fluids (P=.02), and automatic ``switch on'' function (P=.02). Nursing students were more focused on the social functions of robots, including encouraging contact with friends (P=.003) and reducing the sense of loneliness and improving mood (P=.008). Medical students were more aware of privacy issues in the statement concerning the possibility of switching off the robot in specific situations (P=.01). Conclusions: Our study revealed a generally positive attitude of future doctors and nurses toward assistive robots, which can have an impact on their acceptance by older adults. In the future, medical professionals could help their patients to choose the right robots (and necessary functions) that are best suited to their needs. However, this would require expanding the curriculum to include the issues of gerontechnology. ", doi="10.2196/18003", url="https://www.jmir.org/2020/8/e18003", url="http://www.ncbi.nlm.nih.gov/pubmed/32784187" } @Article{info:doi/10.2196/19657, author="Sung, MinDong and Park, SungJun and Jung, Sungjae and Lee, Eunsol and Lee, Jaehoon and Park, Rang Yu", title="Developing a Mobile App for Monitoring Medical Record Changes Using Blockchain: Development and Usability Study", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e19657", keywords="blockchain", keywords="monitoring app", keywords="clinical documents", abstract="Background: Although we are living in an era of transparency, medical documents are often still difficult to access. Blockchain technology allows records to be both immutable and transparent. Objective: Using blockchain technology, the aim of this study was to develop a medical document monitoring system that informs patients of changes to their medical documents. We then examined whether patients can effectively verify the monitoring of their primary care clinical medical records in a system based on blockchain technology. Methods: We enrolled participants who visited two primary care clinics in Korea. Three substudies were performed: (1) a survey of the recognition of blockchain medical records changes and the digital literacy of participants; (2) an observational study on participants using the blockchain-based mobile alert app; and (3) a usability survey study. The participants' medical documents were profiled with HL7 Fast Healthcare Interoperability Resources, hashed, and transacted to the blockchain. The app checked the changes in the documents by querying the blockchain. Results: A total of 70 participants were enrolled in this study. Considering their recognition of changes to their medical records, participants tended to not allow these changes. Participants also generally expressed a desire for a medical record monitoring system. Concerning digital literacy, most questions were answered with ``good,'' indicating fair digital literacy. In the second survey, only 44 participants---those who logged into the app more than once and used the app for more than 28 days---were included in the analysis to determine whether they exhibited usage patterns. The app was accessed a mean of 5.1 (SD 2.6) times for 33.6 (SD 10.0) days. The mean System Usability Scale score was 63.21 (SD 25.06), which indicated satisfactory usability. Conclusions: Patients showed great interest in a blockchain-based system to monitor changes in their medical records. The blockchain system is useful for informing patients of changes in their records via the app without uploading the medical record itself to the network. This ensures the transparency of medical records as well as patient empowerment. ", doi="10.2196/19657", url="http://www.jmir.org/2020/8/e19657/", url="http://www.ncbi.nlm.nih.gov/pubmed/32795988" } @Article{info:doi/10.2196/19480, author="Chang, Ernest Shuchih and Chen, YiChian", title="Blockchain in Health Care Innovation: Literature Review and Case Study From a Business Ecosystem Perspective", journal="J Med Internet Res", year="2020", month="Aug", day="31", volume="22", number="8", pages="e19480", keywords="blockchain", keywords="health care industry", keywords="business ecosystem", keywords="smart contract", keywords="paradigm shift", abstract="Background: Blockchain technology is leveraging its innovative potential in various sectors and its transformation of business-related processes has drawn much attention. Topics of research interest have focused on medical and health care applications, while research implications have generally concluded in system design, literature reviews, and case studies. However, a general overview and knowledge about the impact on the health care ecosystem is limited. Objective: This paper explores a potential paradigm shift and ecosystem evolution in health care utilizing blockchain technology. Methods: A literature review with a case study on a pioneering initiative was conducted. With a systematic life cycle analysis, this study sheds light on the evolutionary development of blockchain in health care scenarios and its interactive relationship among stakeholders. Results: Four stages---birth, expansion, leadership, and self-renewal or death---in the life cycle of the business ecosystem were explored to elucidate the evolving trajectories of blockchain-based health care implementation. Focused impacts on the traditional health care industry are highlighted within each stage to further support the potential health care paradigm shift in the future. Conclusions: This paper enriches the existing body of literature in this field by illustrating the potential of blockchain in fulfilling stakeholders' needs and elucidating the phenomenon of coevolution within the health care ecosystem. Blockchain not only catalyzes the interactions among players but also facilitates the formation of the ecosystem life cycle. The collaborative network linked by blockchain may play a critical role on value creation, transfer, and sharing among the health care community. Future efforts may focus on empirical or case studies to validate the proposed evolution of the health care ecosystem. ", doi="10.2196/19480", url="http://www.jmir.org/2020/8/e19480/", url="http://www.ncbi.nlm.nih.gov/pubmed/32865501" } @Article{info:doi/10.2196/17022, author="Krasuska, Marta and Williams, Robin and Sheikh, Aziz and Franklin, Dean Bryony and Heeney, Catherine and Lane, Wendy and Mozaffar, Hajar and Mason, Kathy and Eason, Sally and Hinder, Susan and Dunscombe, Rachel and Potts, W. Henry W. and Cresswell, Kathrin", title="Technological Capabilities to Assess Digital Excellence in Hospitals in High Performing Health Care Systems: International eDelphi Exercise", journal="J Med Internet Res", year="2020", month="Aug", day="18", volume="22", number="8", pages="e17022", keywords="digital excellence", keywords="digital maturity", keywords="Delphi technique", keywords="hospitals, eHealth", abstract="Background: Hospitals worldwide are developing ambitious digital transformation programs as part of broader efforts to create digitally advanced health care systems. However, there is as yet no consensus on how best to characterize and assess digital excellence in hospitals. Objective: Our aim was to develop an international agreement on a defined set of technological capabilities to assess digital excellence in hospitals. Methods: We conducted a two-stage international modified electronic Delphi (eDelphi) consensus-building exercise, which included a qualitative analysis of free-text responses. In total, 31 international health informatics experts participated, representing clinical, academic, public, and vendor organizations. Results: We identified 35 technological capabilities that indicate digital excellence in hospitals. These are divided into two categories: (a) capabilities within a hospital (n=20) and (b) capabilities enabling communication with other parts of the health and social care system, and with patients and carers (n=15). The analysis of free-text responses pointed to the importance of nontechnological aspects of digitally enabled change, including social and organizational factors. Examples included an institutional culture characterized by a willingness to transform established ways of working and openness to risk-taking. The availability of a range of skills within digitization teams, including technological, project management and business expertise, and availability of resources to support hospital staff, were also highlighted. Conclusions: We have identified a set of criteria for assessing digital excellence in hospitals. Our findings highlight the need to broaden the focus from technical functionalities to wider digital transformation capabilities. ", doi="10.2196/17022", url="https://www.jmir.org/2020/8/e17022", url="http://www.ncbi.nlm.nih.gov/pubmed/32808938" } @Article{info:doi/10.2196/17239, author="Zhao, Hui and Muthupandi, Sowmyasri and Kumara, Soundar", title="Managing Illicit Online Pharmacies: Web Analytics and Predictive Models Study", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e17239", keywords="online pharmacy", keywords="web analytics", keywords="classification", keywords="illicit online pharmacies", keywords="online traffic analysis", abstract="Background: Online pharmacies have grown significantly in recent years, from US \$29.35 billion in 2014 to an expected US \$128 billion in 2023 worldwide. Although legitimate online pharmacies (LOPs) provide a channel of convenience and potentially lower costs for patients, illicit online pharmacies (IOPs) open the doors to unfettered access to prescription drugs, controlled substances (eg, opioids), and potentially counterfeits, posing a dramatic risk to the drug supply chain and the health of the patient. Unfortunately, we know little about IOPs, and even identifying and monitoring IOPs is challenging because of the large number of online pharmacies (at least 30,000-35,000) and the dynamic nature of the online channel (online pharmacies open and shut down easily). Objective: This study aims to increase our understanding of IOPs through web data traffic analysis and propose a novel framework using referral links to predict and identify IOPs, the first step in fighting IOPs. Methods: We first collected web traffic and engagement data to study and compare how consumers access and engage with LOPs and IOPs. We then proposed a simple but novel framework for predicting the status of online pharmacies (legitimate or illicit) through the referral links between websites. Under this framework, we developed 2 prediction models, the reference rating prediction method (RRPM) and the reference-based K-nearest neighbor. Results: We found that direct (typing URL), search, and referral are the 3 major traffic sources, representing more than 95\% traffic to both LOPs and IOPs. It is alarming to see that direct represents the second-highest traffic source (34.32\%) to IOPs. When tested on a data set with 763 online pharmacies, both RRPM and R2NN performed well, achieving an accuracy above 95\% in their predictions of the status for the online pharmacies. R2NN outperformed RRPM in full performance metrics (accuracy, kappa, specificity, and sensitivity). On implementing the 2 models on Google search results for popular drugs (Xanax [alprazolam], OxyContin, and opioids), they produced an error rate of only 7.96\% (R2NN) and 6.20\% (RRPM). Conclusions: Our prediction models use what we know (referral links) to tackle the many unknown aspects of IOPs. They have many potential applications for patients, search engines, social media, payment companies, policy makers or government agencies, and drug manufacturers to help fight IOPs. With scarce work in this area, we hope to help address the current opioid crisis from this perspective and inspire future research in the critical area of drug safety. ", doi="10.2196/17239", url="http://www.jmir.org/2020/8/e17239/", url="http://www.ncbi.nlm.nih.gov/pubmed/32840485" } @Article{info:doi/10.2196/18033, author="Brantnell, Anders and Woodford, Joanne and Baraldi, Enrico and van Achterberg, Theo and von Essen, Louise", title="Views of Implementers and Nonimplementers of Internet-Administered Cognitive Behavioral Therapy for Depression and Anxiety: Survey of Primary Care Decision Makers in Sweden", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e18033", keywords="mental health", keywords="internet-administered CBT", keywords="self-management", keywords="implementation", keywords="barriers and facilitators", keywords="decision-making", keywords="eHealth", keywords="primary care", abstract="Background: Internet-administered cognitive behavioral therapy (ICBT) has been demonstrated to be an effective intervention for adults with depression and/or anxiety and is recommended in national guidelines for provision within Swedish primary care. However, the number and type of organizations that have implemented ICBT within primary care in Sweden is currently unclear. Further, there is a lack of knowledge concerning barriers and facilitators to ICBT implementation. Objective: The two primary objectives were to identify and describe primary care organizations providing ICBT in Sweden and compare decision makers' (ie, directors of primary care organizations) views on barriers and facilitators to implementation of ICBT among ICBT implementers (ie, organizations that offered ICBT) and nonimplementers (ie, organizations that did not offer ICBT). Methods: An online survey based on a checklist for identifying barriers and facilitators to implementation was developed and made accessible to decision makers from all primary care organizations in Sweden. The survey consisted of background questions (eg, provision of ICBT and number of persons working with ICBT) and barriers and facilitators relating to the following categories: users, therapists, ICBT programs, organizations, and wider society. Results: The participation rate was 35.75\% (404/1130). The majority (250/404, 61.8\%) of participants were health care center directors and had backgrounds in nursing. Altogether, 89.8\% (363/404) of the participating organizations provided CBT. A minority (83/404, 20.5\%) of organizations offered ICBT. Most professionals delivering ICBT were psychologists (67/83, 80\%) and social workers (31/83, 37\%). The majority (61/83, 73\%) of organizations had 1 to 2 persons delivering ICBT interventions. The number of patients treated with ICBT during the last 12 months was 1 to 10 in 65\% (54/83) of the organizations, ranging between 1 and 400 treated patients across the whole sample. There were 9 significant (P<.05) differences out of 37 possible between implementers and nonimplementers. For example, more implementers (48/51, 94\%) than nonimplementers (107/139, 76.9\%) perceived few technical problems (P<.001), and more implementers (53/77, 68\%) than nonimplementers (103/215, 47.9\%) considered that their organization has resources to offer ICBT programs (P<.001). Conclusions: Despite research demonstrating the effectiveness of ICBT for depression and anxiety and national guidelines recommending its use, ICBT is implemented in few primary care organizations in Sweden. Several interesting differences between implementers and nonimplementers were identified, which may help inform interventions focusing on facilitating the implementation of ICBT. ", doi="10.2196/18033", url="https://www.jmir.org/2020/8/e18033", url="http://www.ncbi.nlm.nih.gov/pubmed/32784186" } @Article{info:doi/10.2196/15040, author="Ryu, Borim and Shin, Soo-Yong and Baek, Rong-Min and Kim, Jeong-Whun and Heo, Eunyoung and Kang, Inchul and Yang, SungWoo Joshua and Yoo, Sooyoung", title="Clinical Genomic Sequencing Reports in Electronic Health Record Systems Based on International Standards: Implementation Study", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e15040", keywords="standardization", keywords="genomics", keywords="electronic health record", keywords="information system", keywords="data exchange", abstract="Background: To implement standardized machine-processable clinical sequencing reports in an electronic health record (EHR) system, the International Organization for Standardization Technical Specification (ISO/TS) 20428 international standard was proposed for a structured template. However, there are no standard implementation guidelines for data items from the proposed standard at the clinical site and no guidelines or references for implementing gene sequencing data results for clinical use. This is a significant challenge for implementation and application of these standards at individual sites. Objective: This study examines the field utilization of genetic test reports by designing the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) for genomic data elements based on the ISO/TS 20428 standard published as the standard for genomic test reports. The goal of this pilot is to facilitate the reporting and viewing of genomic data for clinical applications. FHIR Genomics resources predominantly focus on transmitting or representing sequencing data, which is of less clinical value. Methods: In this study, we describe the practical implementation of ISO/TS 20428 using HL7 FHIR Genomics implementation guidance to efficiently deliver the required genomic sequencing results to clinicians through an EHR system. Results: We successfully administered a structured genomic sequencing report in a tertiary hospital in Korea based on international standards. In total, 90 FHIR resources were used. Among 41 resources for the required fields, 26 were reused and 15 were extended. For the optional fields, 28 were reused and 21 were extended. Conclusions: To share and apply genomic sequencing data in both clinical practice and translational research, it is essential to identify the applicability of the standard-based information system in a practical setting. This prototyping work shows that reporting data from clinical genomics sequencing can be effectively implemented into an EHR system using the existing ISO/TS 20428 standard and FHIR resources. ", doi="10.2196/15040", url="https://www.jmir.org/2020/8/e15040", url="http://www.ncbi.nlm.nih.gov/pubmed/32773368" } @Article{info:doi/10.2196/13598, author="Dubovitskaya, Alevtina and Baig, Furqan and Xu, Zhigang and Shukla, Rohit and Zambani, Sushil Pratik and Swaminathan, Arun and Jahangir, Majid Md and Chowdhry, Khadija and Lachhani, Rahul and Idnani, Nitesh and Schumacher, Michael and Aberer, Karl and Stoller, D. Scott and Ryu, Samuel and Wang, Fusheng", title="ACTION-EHR: Patient-Centric Blockchain-Based Electronic Health Record Data Management for Cancer Care", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e13598", keywords="electronic health records", keywords="data sharing", keywords="blockchain", keywords="Hyperledger Fabric", keywords="privacy", keywords="security", abstract="Background: With increased specialization of health care services and high levels of patient mobility, accessing health care services across multiple hospitals or clinics has become very common for diagnosis and treatment, particularly for patients with chronic diseases such as cancer. With informed knowledge of a patient's history, physicians can make prompt clinical decisions for smarter, safer, and more efficient care. However, due to the privacy and high sensitivity of electronic health records (EHR), most EHR data sharing still happens through fax or mail due to the lack of systematic infrastructure support for secure, trustable health data sharing, which can also cause major delays in patient care. Objective: Our goal was to develop a system that will facilitate secure, trustable management, sharing, and aggregation of EHR data. Our patient-centric system allows patients to manage their own health records across multiple hospitals. The system will ensure patient privacy protection and guarantee security with respect to the requirements for health care data management, including the access control policy specified by the patient. Methods: We propose a permissioned blockchain-based system for EHR data sharing and integration. Each hospital will provide a blockchain node integrated with its own EHR system to form the blockchain network. A web-based interface will be used for patients and doctors to initiate EHR sharing transactions. We take a hybrid data management approach, where only management metadata will be stored on the chain. Actual EHR data, on the other hand, will be encrypted and stored off-chain in Health Insurance Portability and Accountability Act--compliant cloud-based storage. The system uses public key infrastructure--based asymmetric encryption and digital signatures to secure shared EHR data. Results: In collaboration with Stony Brook University Hospital, we developed ACTION-EHR, a system for patient-centric, blockchain-based EHR data sharing and management for patient care, in particular radiation treatment for cancer. The prototype was built on Hyperledger Fabric, an open-source, permissioned blockchain framework. Data sharing transactions were implemented using chaincode and exposed as representational state transfer application programming interfaces used for the web portal for patients and users. The HL7 Fast Healthcare Interoperability Resources standard was adopted to represent shared EHR data, making it easy to interface with hospital EHR systems and integrate a patient's EHR data. We tested the system in a distributed environment at Stony Brook University using deidentified patient data. Conclusions: We studied and developed the critical technology components to enable patient-centric, blockchain-based EHR sharing to support cancer care. The prototype demonstrated the feasibility of our approach as well as some of the major challenges. The next step will be a pilot study with health care providers in both the United States and Switzerland. Our work provides an exemplar testbed to build next-generation EHR sharing infrastructures. ", doi="10.2196/13598", url="http://www.jmir.org/2020/8/e13598/", url="http://www.ncbi.nlm.nih.gov/pubmed/32821064" } @Article{info:doi/10.2196/13234, author="Zargaran, David and Walsh, Caoimhe and Koumpa, Stefania Foteini and Ashraf, Arsalan Muhammad and White, Jayne Amelia and Patel, Nikhil and Tanna, Ravina and Trepekli, Anna and Zargaran, Alexander", title="Comment on ``Internet-Based Cognitive Behavioral Therapy With Real-Time Therapist Support via Videoconference for Patients With Obsessive-Compulsive Disorder, Panic Disorder, and Social Anxiety Disorder: Pilot Single-Arm Trial''", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e13234", keywords="internet", keywords="CBT", keywords="cognitive behavioral therapy", keywords="telemedicine", keywords="telehealth", doi="10.2196/13234", url="https://www.jmir.org/2020/8/e13234", url="http://www.ncbi.nlm.nih.gov/pubmed/32784172" } @Article{info:doi/10.2196/23597, author="Chen, T. Annie", title="Correction: The Relationship Between Health Management and Information Behavior Over Time: A Study of the Illness Journeys of People Living With Fibromyalgia", journal="J Med Internet Res", year="2020", month="Aug", day="20", volume="22", number="8", pages="e23597", doi="10.2196/23597", url="http://www.jmir.org/2020/8/e23597/", url="http://www.ncbi.nlm.nih.gov/pubmed/32816686" } @Article{info:doi/10.2196/23642, author="Bonten, N. Tobias and Rauwerdink, Anneloek and Wyatt, C. Jeremy and Kasteleyn, J. Marise and Witkamp, Leonard and Riper, Heleen and van Gemert-Pijnen, JEWC Lisette and Cresswell, Kathrin and Sheikh, Aziz and Schijven, P. Marlies and Chavannes, H. Niels and ", title="Correction: Online Guide for Electronic Health Evaluation Approaches: Systematic Scoping Review and Concept Mapping Study", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e23642", doi="10.2196/23642", url="http://www.jmir.org/2020/8/e23642/", url="http://www.ncbi.nlm.nih.gov/pubmed/32822315" } @Article{info:doi/10.2196/23645, author="Iqbal, Usman and Celi, Anthony Leo and Li, Jack Yu-Chuan", title="Correction: How Can Artificial Intelligence Make Medicine More Preemptive?", journal="J Med Internet Res", year="2020", month="Aug", day="26", volume="22", number="8", pages="e23645", doi="10.2196/23645", url="http://www.jmir.org/2020/8/e23645/", url="http://www.ncbi.nlm.nih.gov/pubmed/32845851" } @Article{info:doi/10.2196/22761, author="Dai, Hengfen and Zheng, Caiyun and Lin, Chun and Zhang, Yan and Zhang, Hong and Chen, Fan and Liu, Yunchun and Xiao, Jingwen and Chen, Chaoxin", title="Correction: Technology-Based Interventions in Oral Anticoagulation Management: Meta-Analysis of Randomized Controlled Trials", journal="J Med Internet Res", year="2020", month="Aug", day="4", volume="22", number="8", pages="e22761", doi="10.2196/22761", url="http://www.jmir.org/2020/8/e22761/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750007" } @Article{info:doi/10.2196/21442, author="Crawford, Danielle Natalie and Haard{\"o}rfer, Regine and Cooper, Hannah and McKinnon, Izraelle and Jones-Harrell, Carla and Ballard, April and von Hellens, Shantel Sierra and Young, April", title="Correction: Characterizing the Rural Opioid Use Environment in Kentucky Using Google Earth: Virtual Audit", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e21442", doi="10.2196/21442", url="https://www.jmir.org/2020/8/e21442", url="http://www.ncbi.nlm.nih.gov/pubmed/32784194" } @Article{info:doi/10.2196/21143, author="Hou, Zhiyuan and Du, Fanxing and Zhou, Xinyu and Jiang, Hao and Martin, Sam and Larson, Heidi and Lin, Leesa", title="Cross-Country Comparison of Public Awareness, Rumors, and Behavioral Responses to the COVID-19 Epidemic: Infodemiology Study", journal="J Med Internet Res", year="2020", month="Aug", day="3", volume="22", number="8", pages="e21143", keywords="COVID-19", keywords="internet", keywords="surveillance", keywords="infodemic", keywords="infodemiology", keywords="infoveillance", keywords="Google Trends", keywords="public response", keywords="behavior", keywords="rumor", keywords="trend", abstract="Background: Understanding public behavioral responses to the coronavirus disease (COVID-19) epidemic and the accompanying infodemic is crucial to controlling the epidemic. Objective: The aim of this study was to assess real-time public awareness and behavioral responses to the COVID-19 epidemic across 12 selected countries. Methods: Internet surveillance was used to collect real-time data from the general public to assess public awareness and rumors (China: Baidu; worldwide: Google Trends) and behavior responses (China: Ali Index; worldwide: Google Shopping). These indices measured the daily number of searches or purchases and were compared with the numbers of daily COVID-19 cases. The trend comparisons across selected countries were observed from December 1, 2019 (prepandemic baseline) to April 11, 2020 (at least one month after the governments of selected countries took actions for the pandemic). Results: We identified missed windows of opportunity for early epidemic control in 12 countries, when public awareness was very low despite the emerging epidemic. China's epidemic and the declaration of a public health emergency of international concern did not prompt a worldwide public reaction to adopt health-protective measures; instead, most countries and regions only responded to the epidemic after their own case counts increased. Rumors and misinformation led to a surge of sales in herbal remedies in China and antimalarial drugs worldwide, and timely clarification of rumors mitigated the rush to purchase unproven remedies. Conclusions: Our comparative study highlights the urgent need for international coordination to promote mutual learning about epidemic characteristics and effective control measures as well as to trigger early and timely responses in individual countries. Early release of official guidelines and timely clarification of rumors led by governments are necessary to guide the public to take rational action. ", doi="10.2196/21143", url="https://www.jmir.org/2020/8/e21143", url="http://www.ncbi.nlm.nih.gov/pubmed/32701460" } @Article{info:doi/10.2196/21169, author="Gates, Elaine Lyndsey and Hamed, Abdeen Ahmed", title="The Anatomy of the SARS-CoV-2 Biomedical Literature: Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation", journal="J Med Internet Res", year="2020", month="Aug", day="20", volume="22", number="8", pages="e21169", keywords="health", keywords="informatics", keywords="COVID-19 treatment", keywords="drug repurposing", keywords="network algorithm", keywords="ranking", keywords="drug", keywords="biomedical", keywords="antiviral", keywords="COVID-19", abstract="Background: Driven by the COVID-19 pandemic and the dire need to discover an antiviral drug, we explored the landscape of the SARS-CoV-2 biomedical publications to identify potential treatments. Objective: The aims of this study are to identify off-label drugs that may have benefits for the coronavirus disease pandemic, present a novel ranking algorithm called CovidX to recommend existing drugs for potential repurposing, and validate the literature-based outcome with drug knowledge available in clinical trials. Methods: To achieve such objectives, we applied natural language processing techniques to identify drugs and linked entities (eg, disease, gene, protein, chemical compounds). When such entities are linked, they form a map that can be further explored using network science tools. The CovidX algorithm was based upon a notion that we called ``diversity.'' A diversity score for a given drug was calculated by measuring how ``diverse'' a drug is calculated using various biological entities (regardless of the cardinality of actual instances in each category). The algorithm validates the ranking and awards those drugs that are currently being investigated in open clinical trials. The rationale behind the open clinical trial is to provide a validating mechanism of the PubMed results. This ensures providing up to date evidence of the fast development of this disease. Results: From the analyzed biomedical literature, the algorithm identified 30 possible drug candidates for repurposing, ranked them accordingly, and validated the ranking outcomes against evidence from clinical trials. The top 10 candidates according to our algorithm are hydroxychloroquine, azithromycin, chloroquine, ritonavir, losartan, remdesivir, favipiravir, methylprednisolone, rapamycin, and tilorone dihydrochloride. Conclusions: The ranking shows both consistency and promise in identifying drugs that can be repurposed. We believe, however, the full treatment to be a multifaceted, adjuvant approach where multiple drugs may need to be taken at the same time. ", doi="10.2196/21169", url="http://www.jmir.org/2020/8/e21169/", url="http://www.ncbi.nlm.nih.gov/pubmed/32735546" } @Article{info:doi/10.2196/19551, author="Li, Lin and Liu, Gang and Xu, Weiguo and Zhang, Yun and He, Mei", title="Effects of Internet Hospital Consultations on Psychological Burdens and Disease Knowledge During the Early Outbreak of COVID-19 in China: Cross-Sectional Survey Study", journal="J Med Internet Res", year="2020", month="Aug", day="4", volume="22", number="8", pages="e19551", keywords="internet hospital", keywords="telemedicine", keywords="novel coronavirus disease", keywords="pandemic", keywords="psychological burden", keywords="disease cognition", keywords="coronavirus", keywords="COVID-19", keywords="public health", keywords="infectious disease", abstract="Background: Coronavirus disease (COVID-19) has become a global threat to human health. Internet hospitals have emerged as a critical technology to bring epidemic-related web-based services and medical support to the public. However, only a few very recent scientific literature reports have explored the effects of internet hospitals on psychological burden and disease knowledge in major public health emergencies such as the COVID-19 pandemic. Objective: The aim of this study was to explore the role of internet hospitals in relieving psychological burden and increasing disease knowledge during the early outbreak of the COVID-19 pandemic. Methods: This survey was conducted from January 26 to February 1, 2020, during the early outbreak of COVID-19 in China. The platform used for the consultation was the WeChat public account of our hospital. To participate in the study, the patient was required to answer a list of questions to exclude the possibility of COVID-19 infection and confirm their willingness to participate voluntarily. Next, the participant was directed to complete the self-report questionnaire. After the internet consultation, the participant was directed to complete the self-report questionnaire again. The questionnaire included sections on general information, the General Health Questionnaire-28 (GHQ-28), and the participant's worries, disease knowledge, and need for hospital treatment. Results: The total number of internet consultations was 4120. The consultation topics mainly included respiratory symptoms such as cough, expectoration, and fever (2489/4120, 60.4\%) and disease knowledge, anxiety, and fear (1023/4120, 24.8\%). A total of 1530 people filled out the questionnaires before and after the internet consultation. Of these people, 1398/1530 (91.4\%) experienced psychological stress before the internet consultation, which significantly decreased after consultation (260/1530, 17.0\%) ($\chi$21=1704.8, P<.001). There was no significant difference in the number of people who expressed concern about the COVID-19 pandemic before and after the internet consultation ($\chi$21=0.7, P=.43). However, the degree of concern after the internet consultation was significantly alleviated (t2699=90.638, P<.001). The main worries before and after consultation were the dangers posed by the disease and the risk of infection of family members. The scores of the self-assessment risk after the internet consultation were significantly lower than those before consultation (t3058=95.694, P<.001). After the consultation, the participants' knowledge of the symptoms, transmission routes, and preventive measures of COVID-19 was significantly higher than before the consultation (t3058=--106.105, --80.456, and --152.605, respectively; all P<.001). The hospital treatment need score after the internet consultation decreased from 3.3 (SD 1.2) to 1.6 (SD 0.8), and the difference was statistically significant (t3058=45.765, P<.001). Conclusions: During the early outbreak of COVID-19, internet hospitals could help relieve psychological burdens and increase disease awareness through timely and rapid spread of knowledge regarding COVID-19 prevention and control. Internet hospitals should be an important aspect of a new medical model in public health emergency systems. ", doi="10.2196/19551", url="https://www.jmir.org/2020/8/e19551", url="http://www.ncbi.nlm.nih.gov/pubmed/32687061" } @Article{info:doi/10.2196/19678, author="Ding, Liang and She, Qiuru and Chen, Fengxian and Chen, Zitong and Jiang, Meifang and Huang, Huasi and Li, Yujin and Liao, Chaofeng", title="The Internet Hospital Plus Drug Delivery Platform for Health Management During the COVID-19 Pandemic: Observational Study", journal="J Med Internet Res", year="2020", month="Aug", day="6", volume="22", number="8", pages="e19678", keywords="internet hospital", keywords="drug delivery", keywords="internet hospital plus drug delivery", keywords="IHDD", keywords="health management", keywords="COVID-19", abstract="Background: Widespread access to the internet has boosted the emergence of online hospitals. A new outpatient service called ``internet hospital plus drug delivery'' (IHDD) has been developed in China, but little is known about this platform. Objective: The aim of this study is to investigate the characteristics, acceptance, and initial impact of IHDD during the outbreak of COVID-19 in a tertiary hospital in South China Methods: The total number of and detailed information on online prescriptions during the first 2 months after work resumption were obtained. Patients' gender, age, residence, associated prescription department, time of prescription, payment, and drug delivery region were included in the analysis. Results: A total of 1380 prescriptions were picked up or delivered between March 2 and April 20, 2020. The largest group of patients were 36-59 years old (n=680, 49.3\%), followed by the 18-35 years age category (n=573, 41.5\%). In total, 39.4\% (n=544) of the patients chose to get their medicine by self-pickup, while 60.6\% (n=836) preferred to receive their medicine via drug delivery service. The top five online prescription departments were infectious diseases (n=572, 41.4\%), nephrology (n=264, 19.1\%), endocrinology (n=145, 10.5\%), angiocardiopathy (n=107, 7.8\%), and neurology (n=42, 3\%). Of the 836 delivered prescriptions, 440 (52.6\%) were sent to Guangdong Province (including 363 [43.4\%] to Shenzhen), and 396 (47.4\%) were sent to other provinces in China. Conclusions: The IHDD platform is efficient and convenient for various types of patients during the COVID-19 crisis. Although offline visits are essential for patients with severe conditions, IHDD can help to relieve pressure on hospitals by reducing an influx of patients with mild symptoms. Further efforts need to be made to improve the quality and acceptance of IHDD, as well as to regulate and standardize the management of this novel service. ", doi="10.2196/19678", url="http://www.jmir.org/2020/8/e19678/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716892" } @Article{info:doi/10.2196/20186, author="Pahayahay, Amber and Khalili-Mahani, Najmeh", title="What Media Helps, What Media Hurts: A Mixed Methods Survey Study of Coping with COVID-19 Using the Media Repertoire Framework and the Appraisal Theory of Stress", journal="J Med Internet Res", year="2020", month="Aug", day="6", volume="22", number="8", pages="e20186", keywords="Netflix", keywords="social network", keywords="stress", keywords="COVID-19", keywords="information and communication technologies", keywords="survey", keywords="media", keywords="coping", keywords="infodemic", keywords="infodemiology", abstract="Background: Social and physical distancing in response to the coronavirus disease (COVID-19) pandemic has made screen-mediated information and communication technologies (media) indispensable. Whether an increase in screen use is a source of or a relief for stress remains to be seen. Objective: In the immediate aftermath of the COVID-19 lockdowns, we investigated the relation between subjective stress and changes in the pattern of media use. Based on Lazarus's transactional model of appraisal and coping, and building on an earlier similar survey, we hypothesize that individual differences in the appraisal of media predict variations in approach or avoidance of media for coping with COVID-19 stress. Methods: Between March 20 and April 20, 2020, a brief snowball survey entitled: ``What media helps, what media hurts: coping with COVID19 through screens'' was distributed via Concordia University's mailing lists and social media (PERFORM Centre, EngAGE Centre, and Media Health Lab). Using a media repertoire method, we asked questions about preferences, changes in use, and personal appraisal of media experiences (approach, avoid, and ignore) as a result of the COVID-19 pandemic and investigated interindividual differences in media use by factors such as subjective stress, age, gender, and self-reported mental health. Results: More than 90\% of the survey respondents were in Canada and the east coast of the United States. From 685 completed responses, 169 respondents were ``very stressed'' and 452 were ``slightly worried'' about the pandemic. COVID-19 stress led to increased use of Facebook ($\chi$23=11.76, P=.008), television ($\chi$23=12.40, P=.006), YouTube ($\chi$23=8.577, P=.04), and streaming services such as Netflix ($\chi$23=10.71, P=.01). Respondents who considered their mental health ``not good'' were twice as likely to prefer streaming services as a coping tool for self-isolation. Women and nonbinary respondents were twice as likely than men to pick social media for coping. Individuals younger than 35 years were 3 times more likely to pick computer games, and individuals older than 55 years were more likely to pick network television or print media. Gender affected the appraisal of media (less in men than others) in terms of avoid (F1,637=5.84, P=.02) and approach scores (F1,637=14.31, P<.001). Subjective mental health affected the ignore score (less in those who said ``good'' than others; F1,637=13.88, P<.001). The appraisal score and use increase explained variations in worrying about physical and mental health stress due to increased screen time. A qualitative analysis of open-ended questions revealed that media (especially social networks) were important for coping if they provided support and connection through the dissemination of factual and positive information while avoiding the overflow of sensational and false news. Conclusions: The relationship between appraisal of media's positive and negative facets vary with demographic differences in mental health resiliency. The media repertoire approach is an important tool in studies that focus on assessing the benefits and harms of screen overuse in different populations, especially in the context of the COVID-19 pandemic. ", doi="10.2196/20186", url="https://www.jmir.org/2020/8/e20186", url="http://www.ncbi.nlm.nih.gov/pubmed/32701459" } @Article{info:doi/10.2196/20328, author="Guo, Yan and Cheng, Chao and Zeng, Yu and Li, Yiran and Zhu, Mengting and Yang, Weixiong and Xu, He and Li, Xiaohua and Leng, Jinhang and Monroe-Wise, Aliza and Wu, Shaomin", title="Mental Health Disorders and Associated Risk Factors in Quarantined Adults During the COVID-19 Outbreak in China: Cross-Sectional Study", journal="J Med Internet Res", year="2020", month="Aug", day="6", volume="22", number="8", pages="e20328", keywords="COVID-19", keywords="anxiety or depressive symptoms", keywords="quarantine", keywords="risk and protective factors", abstract="Background: People undergoing mass home- and community-based quarantine are vulnerable to mental health disorders during outbreaks of coronavirus disease (COVID-19), but few studies have evaluated the associated psychosocial factors. Objective: This study aimed to estimate the prevalence of anxiety and depressive symptoms and identify associated demographic and psychosocial factors in the general Chinese population during the COVID-19 pandemic quarantine period. Methods: Participants aged 18 years or above were recruited in a cross-sectional online survey using snowball sampling from February 26-29, 2020. The survey included questions on demographics, family relationships, chronic diseases, quarantine conditions, lifestyle, COVID-19 infection, and anxiety and depressive symptoms. Logistic regression analyses were conducted to identify factors associated with elevated anxiety or depressive symptoms. Results: Out of 2331 participants, 762 (32.7\%) experienced elevated anxiety or depressive symptoms. Nine risk factors associated with anxiety or depressive symptoms included younger age, reduced income, having cancer or other chronic diseases, having family members living with cancer, concerns related to COVID-19 infection for themselves or family members, living alone, having family conflicts, having <3 or >8 hours of sedentary time per day, and worsened sleep quality. Conclusions: The findings highlight an urgent need for psychological support for populations at high risk for elevated anxiety or depressive symptoms during the COVID-19 pandemic. ", doi="10.2196/20328", url="http://www.jmir.org/2020/8/e20328/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716899" } @Article{info:doi/10.2196/20961, author="Li, Guanjian and Tang, Dongdong and Song, Bing and Wang, Chao and Qunshan, Shen and Xu, Chuan and Geng, Hao and Wu, Huan and He, Xiaojin and Cao, Yunxia", title="Impact of the COVID-19 Pandemic on Partner Relationships and Sexual and Reproductive Health: Cross-Sectional, Online Survey Study", journal="J Med Internet Res", year="2020", month="Aug", day="6", volume="22", number="8", pages="e20961", keywords="COVID-19", keywords="survey", keywords="novel coronavirus", keywords="sexual behavior", keywords="sexual health", keywords="reproductive health", keywords="young adults", keywords="youth", keywords="China", abstract="Background: In the past few months, the coronavirus disease (COVID-19) pandemic has caused extensive economic and social damage. Objective: The purpose of this study was to assess the impact of COVID-19--related measures on partner relationships and sexual and reproductive health in China. Methods: From May 1 to 5, 2020, 3500 young Chinese individuals were recruited through WeChat or Weibo to participate in a survey to obtain information on sexual and reproductive health (eg, sexual desire, frequency of sexual intercourse, sexual satisfaction, etc). The questionnaire also collected demographic data (eg, age, race, education, current financial status, sexual orientation, relationship status, etc). Results: In total, 967 participants were included in the sexual health analysis. Due to the COVID-19 pandemic and related containment measures, 22\% of participants (n=212) reported a decrease in sexual desire; 41\% (n=396) experienced a decrease in the sexual intercourse frequency; 30\% (n=291) reported an increase in the frequency of masturbation; 20\% (n=192) reported a decrease in alcohol consumption before or during sexual activities, and 31\% (n=298) reported a deterioration in partner relationships during the pandemic. The logistic regression analysis indicated that the following influenced partner relationships: accommodations during the pandemic (P=.046; odds ratio [OR] 0.59; 95\% CI 0.30-0.86); exclusive relationship status (yes or no) (P<.001; OR 0.44; 95 \% CI\thinspace0.27-0.73); sexual desire (P=.02; OR 2.01; 95\% CI\thinspace1.38-2.97); and sexual satisfaction (P<.001; OR 1.92; 95\% CI\thinspace1.54-2.50). COVID-19 also caused disruptions in reproductive health services such as prenatal and postnatal care, childbirth and abortion services, contraception availability, and the management of sexually transmitted infections. Conclusions: Our results show that many young people have wide-ranging issues affecting their sexual and reproductive health due to the COVID-19 pandemic and related containment measures. Strategies and guidelines are needed to safeguard the sexual and reproductive health of young people during this pandemic. ", doi="10.2196/20961", url="https://www.jmir.org/2020/8/e20961", url="http://www.ncbi.nlm.nih.gov/pubmed/32716895" } @Article{info:doi/10.2196/19493, author="Liu, Na and Huang, Robin and Baldacchino, Tanya and Sud, Archana and Sud, Kamal and Khadra, Mohamed and Kim, Jinman", title="Telehealth for Noncritical Patients With Chronic Diseases During the COVID-19 Pandemic", journal="J Med Internet Res", year="2020", month="Aug", day="7", volume="22", number="8", pages="e19493", keywords="telehealth", keywords="chronic diseases", keywords="COVID-19", keywords="coronavirus", keywords="pandemic", keywords="remote monitoring", keywords="copresence", doi="10.2196/19493", url="http://www.jmir.org/2020/8/e19493/", url="http://www.ncbi.nlm.nih.gov/pubmed/32721925" } @Article{info:doi/10.2196/19104, author="Adly, Sedky Aya and Adly, Sedky Afnan and Adly, Sedky Mahmoud", title="Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e19104", keywords="SARS-CoV-2", keywords="COVID-19", keywords="novel coronavirus", keywords="artificial intelligence", keywords="internet of things", keywords="telemedicine", keywords="machine learning", keywords="modeling", keywords="simulation", keywords="robotics", abstract="Background: Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease. Objective: The objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide. Methods: We conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19. Results: Our search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine. Conclusions: We found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed. ", doi="10.2196/19104", url="https://www.jmir.org/2020/8/e19104", url="http://www.ncbi.nlm.nih.gov/pubmed/32584780" } @Article{info:doi/10.2196/19611, author="Sousa-Pinto, Bernardo and Anto, Aram and Czarlewski, Wienia and Anto, M. Josep and Fonseca, Almeida Jo{\~a}o and Bousquet, Jean", title="Assessment of the Impact of Media Coverage on COVID-19--Related Google Trends Data: Infodemiology Study", journal="J Med Internet Res", year="2020", month="Aug", day="10", volume="22", number="8", pages="e19611", keywords="COVID-19", keywords="infodemiology", keywords="infodemic", keywords="Google Trends", keywords="media coverage", keywords="media", keywords="coronavirus", keywords="symptom", keywords="monitoring", keywords="trend", keywords="pandemic", abstract="Background: The influence of media coverage on web-based searches may hinder the role of Google Trends (GT) in monitoring coronavirus disease (COVID-19). Objective: The aim of this study was to assess whether COVID-19--related GT data, particularly those related to ageusia and anosmia, were primarily related to media coverage or to epidemic trends. Methods: We retrieved GT query data for searches on coronavirus, cough, anosmia, and ageusia and plotted them over a period of 5 years. In addition, we analyzed the trends of those queries for 17 countries throughout the year 2020 with a particular focus on the rises and peaks of the searches. For anosmia and ageusia, we assessed whether the respective GT data correlated with COVID-19 cases and deaths both throughout 2020 and specifically before March 16, 2020 (ie, the date when the media started reporting that these symptoms can be associated with COVID-19). Results: Over the last five years, peaks for coronavirus searches in GT were only observed during the winter of 2020. Rises and peaks in coronavirus searches appeared at similar times in the 17 different assessed countries irrespective of their epidemic situations. In 15 of these countries, rises in anosmia and ageusia searches occurred in the same week or 1 week after they were identified in the media as symptoms of COVID-19. When data prior to March 16, 2020 were analyzed, anosmia and ageusia GT data were found to have variable correlations with COVID-19 cases and deaths in the different countries. Conclusions: Our results indicate that COVID-19--related GT data are more closely related to media coverage than to epidemic trends. ", doi="10.2196/19611", url="https://www.jmir.org/2020/8/e19611", url="http://www.ncbi.nlm.nih.gov/pubmed/32530816" } @Article{info:doi/10.2196/19615, author="Warin, Thierry", title="Global Research on Coronaviruses: An R Package", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e19615", keywords="COVID-19", keywords="SARS-CoV-2", keywords="coronavirus", keywords="R package", keywords="bibliometric", keywords="virus", keywords="infectious disease", keywords="reference", keywords="informatics", abstract="Background: In these trying times, we developed an R package about bibliographic references on coronaviruses. Working with reproducible research principles based on open science, disseminating scientific information, providing easy access to scientific production on this particular issue, and offering a rapid integration in researchers' workflows may help save time in this race against the virus, notably in terms of public health. Objective: The goal is to simplify the workflow of interested researchers, with multidisciplinary research in mind. With more than 60,500 medical bibliographic references at the time of publication, this package is among the largest about coronaviruses. Methods: This package could be of interest to epidemiologists, researchers in scientometrics, biostatisticians, as well as data scientists broadly defined. This package collects references from PubMed and organizes the data in a data frame. We then built functions to sort through this collection of references. Researchers can also integrate the data into their pipeline and implement them in R within their code libraries. Results: We provide a short use case in this paper based on a bibliometric analysis of the references made available by this package. Classification techniques can also be used to go through the large volume of references and allow researchers to save time on this part of their research. Network analysis can be used to filter the data set. Text mining techniques can also help researchers calculate similarity indices and help them focus on the parts of the literature that are relevant for their research. Conclusions: This package aims at accelerating research on coronaviruses. Epidemiologists can integrate this package into their workflow. It is also possible to add a machine learning layer on top of this package to model the latest advances in research about coronaviruses, as we update this package daily. It is also the only one of this size, to the best of our knowledge, to be built in the R language. ", doi="10.2196/19615", url="http://www.jmir.org/2020/8/e19615/", url="http://www.ncbi.nlm.nih.gov/pubmed/32730218" } @Article{info:doi/10.2196/20634, author="Al-Hasan, Abrar and Yim, Dobin and Khuntia, Jiban", title="Citizens' Adherence to COVID-19 Mitigation Recommendations by the Government: A 3-Country Comparative Evaluation Using Web-Based Cross-Sectional Survey Data", journal="J Med Internet Res", year="2020", month="Aug", day="11", volume="22", number="8", pages="e20634", keywords="COVID-19", keywords="adherence", keywords="social distancing", keywords="government perception", keywords="information sources", keywords="social media", keywords="knowledge", abstract="Background: Social distancing is an effective preventative policy for the coronavirus disease (COVID-19) that is enforced by governments worldwide. However, significant variations are observed in following the policy across individuals and countries. Arguably, differences in citizens' adherence actions will be influenced by their perceptions about government's plans and the information available to guide their behaviors---more so in the digital age in the realm of mass influence of social media on citizens. Insights into the underlying factors and dynamics involved with citizens' adherence process will inform the policy makers to follow appropriate communication and messaging approaches to influence citizens' willingness to adhere to the recommendations. Objective: The aim of this study is a comparative evaluation of citizens' adherence process to COVID-19--relevant recommendations by the government. The focus is on how three different countries' (United States, Kuwait, and South Korea) citizens, randomly sampled, respond to governments' pandemic guidance efforts. We draw insights into two categories of perceived government roles in managing the pandemic: (1) citizens' perceptions of government's role in responding to the pandemic and (2) citizens' perceptions of government's business reopening efforts. Undoubtedly, the internet and social media have burgeoned, with differing effects on shaping individuals' views and assessments of the COVID-19 situation; we argue and test for the effects of information sources, social media use, and knowledge on the adherence actions. Methods: We randomly sampled web-based survey data collected by a global firm in May 2020 from citizens of the United States, Kuwait, and South Korea. A nonlinear ordered probit regression, controlling for several counterfactuals, was used for analysis. The focal estimated effects of the study were compared across countries using the weighted distance between the parameter estimates. Results: The total sample size was 482 respondents, of which 207 (43\%) lived in the United States, 181 (38\%) lived in Kuwait, and 94 (20\%) lived in South Korea. The ordered probit estimation results suggest that overall, perception of government response efforts positively influenced self-adherence (P<.001) and others' adherence (P<.001) to social distancing and sheltering. Perception of government business reopening efforts positively influenced others' adherence (P<.001). A higher intensity of general health information source for COVID-19 had a positive effect on self-adherence (P=.003). A higher intensity of social media source use for COVID-19 positively influenced others' adherence (P=.002). A higher intensity of knowledge on COVID-19 positively influenced self-adherence (P=.008) and negatively influenced others' adherence (P<.001). There were country-level variations---broadly, the United States and Kuwait had better effects than South Korea. Conclusions: As the COVID-19 global pandemic continues to grow and governmental restrictions are ongoing, it is critical to understand people's frustration to reduce panic and promote social distancing to facilitate the control of the pandemic. This study finds that the government plays a central role in terms of adherence to restrictions. Governments need to enhance their efforts on publicizing information on the pandemic, as well as employ strategies for improved communication management to citizens through social media as well as mainstream information sources. ", doi="10.2196/20634", url="http://www.jmir.org/2020/8/e20634/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716896" } @Article{info:doi/10.2196/20775, author="Moon, Hana and Lee, Ho Geon", title="Evaluation of Korean-Language COVID-19--Related Medical Information on YouTube: Cross-Sectional Infodemiology Study", journal="J Med Internet Res", year="2020", month="Aug", day="12", volume="22", number="8", pages="e20775", keywords="COVID-19", keywords="YouTube", keywords="social media", keywords="misinformation", keywords="public health surveillance", keywords="health communication", keywords="consumer health information", keywords="health education", keywords="infectious disease outbreaks", keywords="infodemiology", keywords="infoveillance", keywords="infodemic", keywords="internet", keywords="multimedia", abstract="Background: In South Korea, the number of coronavirus disease (COVID-19) cases has declined rapidly and much sooner than in other countries. South Korea is one of the most digitalized countries in the world, and YouTube may have served as a rapid delivery mechanism for increasing public awareness of COVID-19. Thus, the platform may have helped the South Korean public fight the spread of the disease. Objective: The aim of this study is to compare the reliability, overall quality, title--content consistency, and content coverage of Korean-language YouTube videos on COVID-19, which have been uploaded by different sources. Methods: A total of 200 of the most viewed YouTube videos from January 1, 2020, to April 30, 2020, were screened, searching in Korean for the terms ``Coronavirus,'' ``COVID,'' ``Corona,'' ``Wuhan virus,'' and ``Wuhan pneumonia.'' Non-Korean videos and videos that were duplicated, irrelevant, or livestreamed were excluded. Source and video metrics were collected. The videos were scored based on the following criteria: modified DISCERN index, Journal of the American Medical Association Score (JAMAS) benchmark criteria, global quality score (GQS), title--content consistency index (TCCI), and medical information and content index (MICI). Results: Of the 105 total videos, 37.14\% (39/105) contained misleading information; independent user--generated videos showed the highest proportion of misleading information at 68.09\% (32/47), while all of the government-generated videos were useful. Government agency--generated videos achieved the highest median score of DISCERN (5.0, IQR 5.0-5.0), JAMAS (4.0, IQR 4.0-4.0), GQS (4.0, IQR 3.0-4.5), and TCCI (5.0, IQR 5.0-5.0), while independent user--generated videos achieved the lowest median score of DISCERN (2.0, IQR 1.0-3.0), JAMAS (2.0, IQR 1.5-2.0), GQS (2.0, IQR 1.5-2.0), and TCCI (3.0, IQR 3.0-4.0). However, the total MICI was not significantly different among sources. ``Transmission and precautionary measures'' were the most commonly covered content by government agencies, news agencies, and independent users. In contrast, the most mentioned content by news agencies was ``prevalence,'' followed by ``transmission and precautionary measures.'' Conclusions: Misleading videos had more likes, fewer comments, and longer running times than useful videos. Korean-language YouTube videos on COVID-19 uploaded by different sources varied significantly in terms of reliability, overall quality, and title--content consistency, but the content coverage was not significantly different. Government-generated videos had higher reliability, overall quality, and title--content consistency than independent user--generated videos. ", doi="10.2196/20775", url="http://www.jmir.org/2020/8/e20775/", url="http://www.ncbi.nlm.nih.gov/pubmed/32730221" } @Article{info:doi/10.2196/20773, author="Neuraz, Antoine and Lerner, Ivan and Digan, William and Paris, Nicolas and Tsopra, Rosy and Rogier, Alice and Baudoin, David and Cohen, Bretonnel Kevin and Burgun, Anita and Garcelon, Nicolas and Rance, Bastien and ", title="Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e20773", keywords="medication information", keywords="natural language processing", keywords="electronic health records", keywords="COVID-19", keywords="public health", keywords="response", keywords="emergent disease", keywords="informatics", abstract="Background: A novel disease poses special challenges for informatics solutions. Biomedical informatics relies for the most part on structured data, which require a preexisting data or knowledge model; however, novel diseases do not have preexisting knowledge models. In an emergent epidemic, language processing can enable rapid conversion of unstructured text to a novel knowledge model. However, although this idea has often been suggested, no opportunity has arisen to actually test it in real time. The current coronavirus disease (COVID-19) pandemic presents such an opportunity. Objective: The aim of this study was to evaluate the added value of information from clinical text in response to emergent diseases using natural language processing (NLP). Methods: We explored the effects of long-term treatment by calcium channel blockers on the outcomes of COVID-19 infection in patients with high blood pressure during in-patient hospital stays using two sources of information: data available strictly from structured electronic health records (EHRs) and data available through structured EHRs and text mining. Results: In this multicenter study involving 39 hospitals, text mining increased the statistical power sufficiently to change a negative result for an adjusted hazard ratio to a positive one. Compared to the baseline structured data, the number of patients available for inclusion in the study increased by 2.95 times, the amount of available information on medications increased by 7.2 times, and the amount of additional phenotypic information increased by 11.9 times. Conclusions: In our study, use of calcium channel blockers was associated with decreased in-hospital mortality in patients with COVID-19 infection. This finding was obtained by quickly adapting an NLP pipeline to the domain of the novel disease; the adapted pipeline still performed sufficiently to extract useful information. When that information was used to supplement existing structured data, the sample size could be increased sufficiently to see treatment effects that were not previously statistically detectable. ", doi="10.2196/20773", url="http://www.jmir.org/2020/8/e20773/", url="http://www.ncbi.nlm.nih.gov/pubmed/32759101" } @Article{info:doi/10.2196/20914, author="Qu, Hui-Qi and Cheng, Jason Zhangkai and Duan, Zhifeng and Tian, Lifeng and Hakonarson, Hakon", title="The Infection Rate of COVID-19 in Wuhan, China: Combined Analysis of Population Samples", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e20914", keywords="infectious disease", keywords="COVID-19", keywords="infection rate", keywords="China", keywords="Wuhan", keywords="fatality", keywords="public health", keywords="diagnosis", abstract="Background: The coronavirus disease (COVID-19) pandemic began in Wuhan, China, in December 2019. Wuhan had a much higher mortality rate than the rest of China. However, a large number of asymptomatic infections in Wuhan may have never been diagnosed, contributing to an overestimated mortality rate. Objective: This study aims to obtain an accurate estimate of infections in Wuhan using internet data. Methods: In this study, we performed a combined analysis of the infection rate among evacuated foreign citizens to estimate the infection rate in Wuhan in late January and early February. Results: Based on our analysis, the combined infection rate of the foreign evacuees was 0.013 (95\% CI 0.008-0.022). Therefore, we estimate the number of infected people in Wuhan to be 143,000 (range 88,000-242,000), which is significantly higher than previous estimates. Our study indicates that a large number of infections in Wuhan were not diagnosed, which has resulted in an overestimated case fatality rate. Conclusions: Increased awareness of the original infection rate of Wuhan is critical for proper public health measures at all levels, as well as to eliminate panic caused by overestimated mortality rates that may bias health policy actions by the authorities. ", doi="10.2196/20914", url="https://www.jmir.org/2020/8/e20914", url="http://www.ncbi.nlm.nih.gov/pubmed/32707538" } @Article{info:doi/10.2196/21486, author="Martin, Guy and Koizia, Louis and Kooner, Angad and Cafferkey, John and Ross, Clare and Purkayastha, Sanjay and Sivananthan, Arun and Tanna, Anisha and Pratt, Philip and Kinross, James and ", title="Use of the HoloLens2 Mixed Reality Headset for Protecting Health Care Workers During the COVID-19 Pandemic: Prospective, Observational Evaluation", journal="J Med Internet Res", year="2020", month="Aug", day="14", volume="22", number="8", pages="e21486", keywords="COVID-19", keywords="mixed reality", keywords="telemedicine", keywords="protection", keywords="acceptability", keywords="feasibility", keywords="impact", keywords="headset", keywords="virtual reality", keywords="augmented reality", keywords="pilot", abstract="Background: The coronavirus disease (COVID-19) pandemic has led to rapid acceleration in the deployment of new digital technologies to improve both accessibility to and quality of care, and to protect staff. Mixed-reality (MR) technology is the latest iteration of telemedicine innovation; it is a logical next step in the move toward the provision of digitally supported clinical care and medical education. This technology has the potential to revolutionize care both during and after the COVID-19 pandemic. Objective: This pilot project sought to deploy the HoloLens2 MR device to support the delivery of remote care in COVID-19 hospital environments. Methods: A prospective, observational, nested cohort evaluation of the HoloLens2 was undertaken across three distinct clinical clusters in a teaching hospital in the United Kingdom. Data pertaining to staff exposure to high-risk COVID-19 environments and personal protective equipment (PPE) use by clinical staff (N=28) were collected, and assessments of acceptability and feasibility were conducted. Results: The deployment of the HoloLens2 led to a 51.5\% reduction in time exposed to harm for staff looking after COVID-19 patients (3.32 vs 1.63 hours/day/staff member; P=.002), and an 83.1\% reduction in the amount of PPE used (178 vs 30 items/round/day; P=.02). This represents 222.98 hours of reduced staff exposure to COVID-19, and 3100 fewer PPE items used each week across the three clusters evaluated. The majority of staff using the device agreed it was easy to set up and comfortable to wear, improved the quality of care and decision making, and led to better teamwork and communication. In total, 89.3\% (25/28) of users felt that their clinical team was safer when using the HoloLens2. Conclusions: New technologies have a role in minimizing exposure to nosocomial infection, optimizing the use of PPE, and enhancing aspects of care. Deploying such technologies at pace requires context-specific information security, infection control, user experience, and workflow integration to be addressed at the outset and led by clinical end-users. The deployment of new telemedicine technology must be supported with objective evidence for its safety and effectiveness to ensure maximum impact. ", doi="10.2196/21486", url="http://www.jmir.org/2020/8/e21486/", url="http://www.ncbi.nlm.nih.gov/pubmed/32730222" } @Article{info:doi/10.2196/20285, author="Liu, Dianbo and Clemente, Leonardo and Poirier, Canelle and Ding, Xiyu and Chinazzi, Matteo and Davis, Jessica and Vespignani, Alessandro and Santillana, Mauricio", title="Real-Time Forecasting of the COVID-19 Outbreak in Chinese Provinces: Machine Learning Approach Using Novel Digital Data and Estimates From Mechanistic Models", journal="J Med Internet Res", year="2020", month="Aug", day="17", volume="22", number="8", pages="e20285", keywords="COVID-19", keywords="coronavirus", keywords="digital epidemiology", keywords="modeling", keywords="modeling disease outbreaks", keywords="emerging outbreak", keywords="machine learning", keywords="precision public health", keywords="machine learning in public health", keywords="forecasting", keywords="digital data", keywords="mechanistic model", keywords="hybrid simulation", keywords="hybrid model", keywords="simulation", abstract="Background: The inherent difficulty of identifying and monitoring emerging outbreaks caused by novel pathogens can lead to their rapid spread; and if left unchecked, they may become major public health threats to the planet. The ongoing coronavirus disease (COVID-19) outbreak, which has infected over 2,300,000 individuals and caused over 150,000 deaths, is an example of one of these catastrophic events. Objective: We present a timely and novel methodology that combines disease estimates from mechanistic models and digital traces, via interpretable machine learning methodologies, to reliably forecast COVID-19 activity in Chinese provinces in real time. Methods: Our method uses the following as inputs: (a) official health reports, (b) COVID-19--related internet search activity, (c) news media activity, and (d) daily forecasts of COVID-19 activity from a metapopulation mechanistic model. Our machine learning methodology uses a clustering technique that enables the exploitation of geospatial synchronicities of COVID-19 activity across Chinese provinces and a data augmentation technique to deal with the small number of historical disease observations characteristic of emerging outbreaks. Results: Our model is able to produce stable and accurate forecasts 2 days ahead of the current time and outperforms a collection of baseline models in 27 out of 32 Chinese provinces. Conclusions: Our methodology could be easily extended to other geographies currently affected by COVID-19 to aid decision makers with monitoring and possibly prevention. ", doi="10.2196/20285", url="http://www.jmir.org/2020/8/e20285/", url="http://www.ncbi.nlm.nih.gov/pubmed/32730217" } @Article{info:doi/10.2196/21413, author="Veiga e Silva, Lena and de Andrade Abi Harb, Penha Maria Da and Teixeira Barbosa dos Santos, Milene Aurea and de Mattos Teixeira, Andr{\'e} Carlos and Macedo Gomes, Hugo Vitor and Silva Cardoso, Helena Evelin and S da Silva, Marcelino and Vijaykumar, L. N. and Ven{\^a}ncio Carvalho, Solon and Ponce de Leon Ferreira de Carvalho, Andr{\'e} and Lisboa Frances, Renato Carlos", title="COVID-19 Mortality Underreporting in Brazil: Analysis of Data From Government Internet Portals", journal="J Med Internet Res", year="2020", month="Aug", day="18", volume="22", number="8", pages="e21413", keywords="Brazil", keywords="COVID-19", keywords="mortality", keywords="underreporting", keywords="respiratory system diseases", keywords="public health", keywords="pandemic", keywords="time series", keywords="forecasting", abstract="Background: In Brazil, a substantial number of coronavirus disease (COVID-19) cases and deaths have been reported. It has become the second most affected country worldwide, as of June 9, 2020. Official Brazilian government sources present contradictory data on the impact of the disease; thus, it is possible that the actual number of infected individuals and deaths in Brazil is far larger than those officially reported. It is very likely that the actual spread of the disease has been underestimated. Objective: This study investigates the underreporting of cases and deaths related to COVID-19 in the most affected cities in Brazil, based on public data available from official Brazilian government internet portals, to identify the actual impact of the pandemic. Methods: We used data from historical deaths due to respiratory problems and other natural causes from two public portals: DATASUS (Department of Informatics of the Unified Healthcare System) (2010-2018) and the Brazilian Transparency Portal of Civil Registry (2019-2020). These data were used to build time-series models (modular regressions) to predict the expected mortality patterns for 2020. The forecasts were used to estimate the possible number of deaths that were incorrectly registered during the pandemic and posted on government internet portals in the most affected cities in the country. Results: Our model found a significant difference between the real and expected values. The number of deaths due to severe acute respiratory syndrome (SARS) was considerably higher in all cities, with increases between 493\% and 5820\%. This sudden increase may be associated with errors in reporting. An average underreporting of 40.68\% (range 25.9\%-62.7\%) is estimated for COVID-19--related deaths. Conclusions: The significant rates of underreporting of deaths analyzed in our study demonstrate that officially released numbers are much lower than actual numbers, making it impossible for the authorities to implement a more effective pandemic response. Based on analyses carried out using different fatality rates, it can be inferred that Brazil's epidemic is worsening, and the actual number of infectees could already be between 1 to 5.4 million. ", doi="10.2196/21413", url="http://www.jmir.org/2020/8/e21413/", url="http://www.ncbi.nlm.nih.gov/pubmed/32730219" } @Article{info:doi/10.2196/22590, author="Hung, Man and Lauren, Evelyn and Hon, S. Eric and Birmingham, C. Wendy and Xu, Julie and Su, Sharon and Hon, D. Shirley and Park, Jungweon and Dang, Peter and Lipsky, S. Martin", title="Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence", journal="J Med Internet Res", year="2020", month="Aug", day="18", volume="22", number="8", pages="e22590", keywords="COVID-19", keywords="coronavirus", keywords="sentiment", keywords="social network", keywords="Twitter", keywords="infodemiology", keywords="infodemic", keywords="pandemic", keywords="crisis", keywords="public health", keywords="business economy", keywords="artificial intelligence", abstract="Background: The coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic. Objective: The aim of this study is to analyze discussions on Twitter related to COVID-19 and to investigate the sentiments toward COVID-19. Methods: This study applied machine learning methods in the field of artificial intelligence to analyze data collected from Twitter. Using tweets originating exclusively in the United States and written in English during the 1-month period from March 20 to April 19, 2020, the study examined COVID-19--related discussions. Social network and sentiment analyses were also conducted to determine the social network of dominant topics and whether the tweets expressed positive, neutral, or negative sentiments. Geographic analysis of the tweets was also conducted. Results: There were a total of 14,180,603 likes, 863,411 replies, 3,087,812 retweets, and 641,381 mentions in tweets during the study timeframe. Out of 902,138 tweets analyzed, sentiment analysis classified 434,254 (48.2\%) tweets as having a positive sentiment, 187,042 (20.7\%) as neutral, and 280,842 (31.1\%) as negative. The study identified 5 dominant themes among COVID-19--related tweets: health care environment, emotional support, business economy, social change, and psychological stress. Alaska, Wyoming, New Mexico, Pennsylvania, and Florida were the states expressing the most negative sentiment while Vermont, North Dakota, Utah, Colorado, Tennessee, and North Carolina conveyed the most positive sentiment. Conclusions: This study identified 5 prevalent themes of COVID-19 discussion with sentiments ranging from positive to negative. These themes and sentiments can clarify the public's response to COVID-19 and help officials navigate the pandemic. ", doi="10.2196/22590", url="http://www.jmir.org/2020/8/e22590/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750001" } @Article{info:doi/10.2196/19673, author="Aljondi, Rowa and Alghamdi, Salem", title="Diagnostic Value of Imaging Modalities for COVID-19: Scoping Review", journal="J Med Internet Res", year="2020", month="Aug", day="19", volume="22", number="8", pages="e19673", keywords="diagnostic imaging", keywords="radiology", keywords="COVID-19", keywords="respiratory infection", keywords="pneumonia", keywords="imaging", keywords="CT", keywords="infectious disease", keywords="diagnosis", keywords="review", abstract="Background: Coronavirus disease (COVID-19) is a serious infectious disease that causes severe respiratory illness. This pandemic represents a serious public health risk. Therefore, early and accurate diagnosis is essential to control disease progression. Radiological examination plays a crucial role in the early identification and management of infected patients. Objective: The aim of this review was to identify the diagnostic value of different imaging modalities used for diagnosis of COVID-19. Methods: A comprehensive literature search was conducted using the PubMed, Scopus, Web of Science, and Google Scholar databases. The keywords diagnostic imaging, radiology, respiratory infection, pneumonia, coronavirus infection and COVID-19 were used to identify radiology articles focusing on the diagnosis of COVID-19 and to determine the diagnostic value of various imaging modalities, including x-ray, computed tomography (CT), ultrasound, and nuclear medicine for identification and management of infected patients. Results: We identified 50 articles in the literature search. Studies that investigated the diagnostic roles and imaging features of patients with COVID-19, using either chest CT, lung ultrasound, chest x-ray, or positron emission topography/computed tomography (PET/CT) scan, were discussed. Of these imaging modalities, chest x-ray and CT scan are the most commonly used for diagnosis and management of COVID-19 patients, with chest CT scan being more accurate and sensitive in identifying COVID-19 at early stages. Only a few studies have investigated the roles of ultrasound and PET/CT scan in diagnosing COVID-19. Conclusions: Chest CT scan remains the most sensitive imaging modality in initial diagnosis and management of suspected and confirmed patients with COVID-19. Other diagnostic imaging modalities could add value in evaluating disease progression and monitoring critically ill patients with COVID-19. ", doi="10.2196/19673", url="http://www.jmir.org/2020/8/e19673/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716893" } @Article{info:doi/10.2196/21257, author="Chiu, Nan-Chang and Chi, Hsin and Tai, Yu-Lin and Peng, Chun-Chih and Tseng, Cheng-Yin and Chen, Chung-Chu and Tan, Fatt Boon and Lin, Chien-Yu", title="Impact of Wearing Masks, Hand Hygiene, and Social Distancing on Influenza, Enterovirus, and All-Cause Pneumonia During the Coronavirus Pandemic: Retrospective National Epidemiological Surveillance Study", journal="J Med Internet Res", year="2020", month="Aug", day="20", volume="22", number="8", pages="e21257", keywords="novel coronavirus", keywords="COVID-19", keywords="SARS-CoV-2", keywords="pandemic", keywords="influenza", keywords="pneumonia", keywords="hygiene", keywords="social distancing", keywords="prevention", keywords="incidence", keywords="surveillance", abstract="Background: The coronavirus disease (COVID-19) pandemic is an important health crisis worldwide. Several strategies were implemented to combat COVID-19, including wearing masks, hand hygiene, and social distancing. The impact of these strategies on COVID-19 and other viral infections remains largely unclear. Objective: We aim to investigate the impact of implemented infectious control strategies on the incidences of influenza, enterovirus infection, and all-cause pneumonia during the COVID-19 pandemic. Methods: We utilized the electronic database of the Taiwan National Infectious Disease Statistics System and extracted incidences of COVID-19, influenza virus, enterovirus, and all-cause pneumonia. We compared the incidences of these diseases from week 45 of 2016 to week 21 of 2020 and performed linear regression analyses. Results: The first case of COVID-19 in Taiwan was reported in late January 2020 (week 4). Infectious control strategies have been promoted since late January. The influenza virus usually peaks in winter and decreases around week 14. However, a significant decrease in influenza was observed after week 6 of 2020. Regression analyses produced the following results: 2017, R2=0.037; 2018, R2=0.021; 2019, R2=0.046; and 2020, R2=0.599. A dramatic decrease in all-cause pneumonia was also reported (R2 values for 2017-2020 were 0.435, 0.098, 0.352, and 0.82, respectively). Enterovirus had increased by week 18 in 2017-2019, but this was not observed in 2020. Conclusions: Using this national epidemiological database, we found a significant decrease in cases of influenza, enterovirus, and all-cause pneumonia during the COVID-19 pandemic. Wearing masks, hand hygiene, and social distancing may contribute not only to the prevention of COVID-19 but also to the decline of other respiratory infectious diseases. Further studies are warranted to elucidate the causal relationship. ", doi="10.2196/21257", url="http://www.jmir.org/2020/8/e21257/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750008" } @Article{info:doi/10.2196/20073, author="van Deursen, JAM Alexander", title="Digital Inequality During a Pandemic: Quantitative Study of Differences in COVID-19--Related Internet Uses and Outcomes Among the General Population", journal="J Med Internet Res", year="2020", month="Aug", day="20", volume="22", number="8", pages="e20073", keywords="COVID-19", keywords="digital inequality", keywords="internet use", keywords="survey", keywords="personality", keywords="literacy", keywords="internet skills", keywords="information", keywords="communication", abstract="Background: The World Health Organization considers coronavirus disease (COVID-19) to be a public emergency threatening global health. During the crisis, the public's need for web-based information and communication is a subject of focus. Digital inequality research has shown that internet access is not evenly distributed among the general population. Objective: The aim of this study was to provide a timely understanding of how different people use the internet to meet their information and communication needs and the outcomes they gain from their internet use in relation to the COVID-19 pandemic. We also sought to reveal the extent to which gender, age, personality, health, literacy, education, economic and social resources, internet attitude, material access, internet access, and internet skills remain important factors in obtaining internet outcomes after people engage in the corresponding uses. Methods: We used a web-based survey to draw upon a sample collected in the Netherlands. We obtained a dataset with 1733 respondents older than 18 years. Results: Men are more likely to engage in COVID-19--related communication uses. Age is positively related to COVID-19--related information uses and negatively related to information and communication outcomes. Agreeableness is negatively related to both outcomes and to information uses. Neuroticism is positively related to both uses and to communication outcomes. Conscientiousness is not related to any of the uses or outcomes. Introversion is negatively related to communication outcomes. Finally, openness relates positively to all information uses and to both outcomes. Physical health has negative relationships with both outcomes. Health perception contributes positively to information uses and both outcomes. Traditional literacy has a positive relationship with information uses and both outcomes. Education has a positive relationship with information and communication uses. Economic and social resources played no roles. Internet attitude is positively related to information uses and outcomes but negatively related to communication uses and outcomes. Material access and internet access contributed to all uses and outcomes. Finally, several of the indicators and outcomes became insignificant after accounting for engagement in internet uses. Conclusions: Digital inequality is a major concern among national and international scholars and policy makers. This contribution aimed to provide a broader understanding in the case of a major health pandemic by using the ongoing COVID-19 crisis as a context for empirical work. Several groups of people were identified as vulnerable, such as older people, less educated people, and people with physical health problems, low literacy levels, or low levels of internet skills. Generally, people who are already relatively advantaged are more likely to use the information and communication opportunities provided by the internet to their benefit in a health pandemic, while less advantaged individuals are less likely to benefit. Therefore, the COVID-19 crisis is also enforcing existing inequalities. ", doi="10.2196/20073", url="http://www.jmir.org/2020/8/e20073/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750005" } @Article{info:doi/10.2196/19706, author="Zhang, Melvyn and Smith, Elizabeth Helen", title="Digital Tools to Ameliorate Psychological Symptoms Associated With COVID-19: Scoping Review", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e19706", keywords="COVID-19", keywords="digital tool", keywords="psychiatry", keywords="mental health", keywords="digital health", keywords="psychology", keywords="distress", keywords="stress", keywords="anxiety", keywords="depression", abstract="Background: In the four months after the discovery of the index case of coronavirus disease (COVID-19), several studies highlighted the psychological impact of COVID-19 on frontline health care workers and on members of the general public. It is evident from these studies that individuals experienced elevated levels of anxiety and depression in the acute phase, when they first became aware of the pandemic, and that the psychological distress persisted into subsequent weeks. It is becoming apparent that technological tools such as SMS text messages, web-based interventions, mobile interventions, and conversational agents can help ameliorate psychological distress in the workplace and in society. To our knowledge, there are few publications describing how digital tools have been used to ameliorate psychological symptoms among individuals. Objective: The aim of this review was to identify existing SMS text message, web-based, mobile, and conversational agents that the general public can access to ameliorate the psychological symptoms they are experiencing during the COVID-19 pandemic. Methods: To identify digital tools that were published specifically for COVID-19, a search was performed in the PubMed and MEDLINE databases from the inception of the databases through June 17, 2020. The following search strings were used: ``NCOV OR 2019-nCoV OR SARS-CoV-2 OR Coronavirus OR COVID19 OR COVID'' and ``mHealth OR eHealth OR text''. Another search was conducted in PubMed and MEDLINE to identify existing digital tools for depression and anxiety disorders. A web-based search engine (Google) was used to identify if the cited web-based interventions could be accessed. A mobile app search engine, App Annie, was used to determine if the identified mobile apps were commercially available. Results: A total of 6 studies were identified. Of the 6 identified web-based interventions, 5 websites (83\%) could be accessed. Of the 32 identified mobile interventions, 7 apps (22\%) could be accessed. Of the 7 identified conversational agents, only 2 (29\%) could be accessed. Results: A total of 6 studies were identified. Of the 6 identified web-based interventions, 5 websites (83\%) could be accessed. Of the 32 identified mobile interventions, 7 apps (22\%) could be accessed. Of the 7 identified conversational agents, only 2 (29\%) could be accessed. Conclusions: The COVID-19 pandemic has caused significant psychological distress. Digital tools that are commercially available may be useful for at-risk individuals or individuals with pre-existing psychiatric symptoms. ", doi="10.2196/19706", url="http://www.jmir.org/2020/8/e19706/", url="http://www.ncbi.nlm.nih.gov/pubmed/32721922" } @Article{info:doi/10.2196/19995, author="Niu, Zhaomeng and Wang, Tingting and Hu, Pengwei and Mei, Jing and Tang, Zhihan", title="Chinese Public's Engagement in Preventive and Intervening Health Behaviors During the Early Breakout of COVID-19: Cross-Sectional Study", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e19995", keywords="COVID-19", keywords="China", keywords="preventive health behaviors", keywords="intervening health behaviors", keywords="psychosocial", keywords="health literacy", keywords="behavior", keywords="prevention", keywords="cross-sectional", abstract="Background: Since January 2020, the coronavirus disease (COVID-19) swept over China and then the world, causing a global public health crisis. People's adoption of preventive and intervening behaviors is critical in curbing the spread of the virus. Objective: The aim of this study is to evaluate Chinese people's adoption of health behaviors in responding to COVID-19 and to identify key determinants for their engagement. Methods: An anonymous online questionnaire was distributed in early February 2020 among Mainland Chinese (18 years or older) to examine their engagement in preventive behaviors (eg, frequent handwashing, wearing masks, staying at home) and intervening behaviors (eg, advising family to wash hands frequently), and to explore potential determinants for their adoption of these health behaviors. Results: Out of 2949 participants, 55.3\% (n=1629) reported frequent engagement in preventive health behaviors, and over 84\% (n=2493) performed at least one intervening health behavior. Greater engagement in preventive behaviors was found among participants who received higher education, were married, reported fewer barriers and greater benefits of engagement, reported greater self-efficacy and emotional support, had greater patient-centered communication before, had a greater media literacy level, and had greater new media and traditional media use for COVID-19 news. Greater engagement in intervening behaviors was observed among participants who were married, had lower income, reported greater benefits of health behaviors, had greater patient-centered communication before, had a lower media literacy level, and had a greater new media and traditional media use for COVID-19 news. Conclusions: Participants' engagement in coronavirus-related preventive and intervening behaviors was overall high, and the associations varied across demographic and psychosocial variables. Hence, customized health interventions that address the determinants for health behaviors are needed to improve people's adherence to coronavirus-related behavior guidelines. ", doi="10.2196/19995", url="http://www.jmir.org/2020/8/e19995/", url="http://www.ncbi.nlm.nih.gov/pubmed/32716897" } @Article{info:doi/10.2196/21173, author="Deng, Qi", title="Dynamics and Development of the COVID-19 Epidemic in the United States: A Compartmental Model Enhanced With Deep Learning Techniques", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e21173", keywords="epidemiology", keywords="COVID-19", keywords="compartmental models", keywords="deep learning", keywords="model", keywords="modeling", keywords="transmission", keywords="estimation", keywords="virus", keywords="simulate", abstract="Background: Compartmental models dominate epidemic modeling. Transmission parameters between compartments are typically estimated through stochastic parameterization processes that depends on detailed statistics of transmission characteristics, which are economically and resource-wise expensive to collect. Objective: We aim to apply deep learning techniques as a lower data dependency alternative to estimate transmission parameters of a customized compartmental model, for the purpose of simulating the dynamics of the US coronavirus disease (COVID-19) epidemic and projecting its further development. Methods: We constructed a compartmental model and developed a multistep deep learning methodology to estimate the model's transmission parameters. We then fed the estimated transmission parameters to the model to predict development of the US COVID-19 epidemic for 35 and 42 days. Epidemics are considered suppressed when the basic reproduction number (R0) is less than 1. Results: The deep learning--enhanced compartmental model predicts that R0 will fall to <1 around August 17-19, 2020, at which point the epidemic will effectively start to die out, and that the US ``infected'' population will peak around August 16-18, 2020, at 3,228,574 to 3,308,911 individual cases. The model also predicted that the number of accumulative confirmed cases will cross the 5 million mark around August 7, 2020. Conclusions: Current compartmental models require stochastic parameterization to estimate the transmission parameters. These models' effectiveness depends upon detailed statistics on transmission characteristics. As an alternative, deep learning techniques are effective in estimating these stochastic parameters with greatly reduced dependency on data particularity. ", doi="10.2196/21173", url="http://www.jmir.org/2020/8/e21173/", url="http://www.ncbi.nlm.nih.gov/pubmed/32763892" } @Article{info:doi/10.2196/21265, author="Suppan, Laurent and Abbas, Mohamed and Stuby, Loric and Cottet, Philippe and Larribau, Robert and Golay, Eric and Iten, Anne and Harbarth, Stephan and Gartner, Birgit and Suppan, M{\'e}lanie", title="Effect of an E-Learning Module on Personal Protective Equipment Proficiency Among Prehospital Personnel: Web-Based Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="Aug", day="21", volume="22", number="8", pages="e21265", keywords="personal protective equipment", keywords="COVID-19", keywords="electronic learning", keywords="prehospital", keywords="randomized controlled trial", keywords="protection", keywords="equipment", keywords="safety", keywords="gamified", keywords="online learning", keywords="communication", abstract="Background: To avoid misuse of personal protective equipment (PPE), ensure health care workers' safety, and avoid shortages, effective communication of up-to-date infection control guidelines is essential. As prehospital teams are particularly at risk of contamination given their challenging work environment, a specific gamified electronic learning (e-learning) module targeting this audience might provide significant advantages as it requires neither the presence of learners nor the repetitive use of equipment for demonstration. Objective: The aim of this study was to evaluate whether a gamified e-learning module could improve the rate of adequate PPE choice by prehospital personnel in the context of the coronavirus disease (COVID-19) pandemic. Methods: This was an individual-level randomized, controlled, quadruple-blind (investigators, participants, outcome assessors, and data analysts) closed web-based trial. All emergency prehospital personnel working in Geneva, Switzerland, were eligible for inclusion, and were invited to participate by email in April 2020. Participants were informed that the study aim was to assess their knowledge regarding PPE, and that they would be presented with both the guidelines and the e-learning module, though they were unaware that there were two different study paths. All participants first answered a preintervention quiz designed to establish their profile and baseline knowledge. The control group then accessed the guidelines before answering a second set of questions, and were then granted access to the e-learning module. The e-learning group was shown the e-learning module right after the guidelines and before answering the second set of questions. Results: Of the 291 randomized participants, 176 (60.5\%) completed the trial. There was no significant difference in baseline knowledge between groups. Though the baseline proportion of adequate PPE choice was high (75\%, IQR 50\%-75\%), participants' description of the donning sequence was in most cases incorrect. After either intervention, adequate choice of PPE increased significantly in both groups (P<.001). Though the median of the difference in the proportion of correct answers was slightly higher in the e-learning group (17\%, IQR 8\%-33\% versus 8\%, IQR 8\%-33\%), the difference was not statistically significant (P=.27). Confidence in the ability to use PPE was maintained in the e-learning group (P=.27) but significantly decreased in the control group (P=.04). Conclusions: Among prehospital personnel with an already relatively high knowledge of and experience with PPE use, both web-based study paths increased the rate of adequate choice of PPE. There was no major added value of the gamified e-learning module apart from preserving participants' confidence in their ability to correctly use PPE. ", doi="10.2196/21265", url="http://www.jmir.org/2020/8/e21265/", url="http://www.ncbi.nlm.nih.gov/pubmed/32747329" } @Article{info:doi/10.2196/19642, author="Wei, Lijie and Gao, Xuan and Chen, Suhua and Zeng, Wanjiang and Wu, Jianli and Lin, Xingguang and Zhang, Huiting and Mwamaka Sharifu, Lali and Chen, Ling and Feng, Ling and Wang, Shaoshuai", title="Clinical Characteristics and Outcomes of Childbearing-Age Women With COVID-19 in Wuhan: Retrospective, Single-Center Study", journal="J Med Internet Res", year="2020", month="Aug", day="24", volume="22", number="8", pages="e19642", keywords="COVID-19", keywords="SARS-CoV-2", keywords="childbearing age", keywords="pregnancy", keywords="clinical characteristics", keywords="outcomes", keywords="women", keywords="health information", keywords="epidemiology", keywords="diagnosis", keywords="symptom", abstract="Background: Since December 2019, an outbreak of the coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly in Wuhan and worldwide. However, previous studies on pregnant patients were limited. Objective: The aim of this study is to evaluate the clinical characteristics and outcomes of pregnant and nonpregnant women with COVID-19. Methods: This study retrospectively collected epidemiological, clinical, laboratory, imaging, management, and outcome data of 43 childbearing-age women patients (including 17 pregnant and 26 nonpregnant patients) who presented with laboratory-confirmed COVID-19 in Tongji Hospital, Wuhan, China from January 19 to March 2, 2020. Clinical outcomes were followed up to March 28, 2020. Results: Of the 43 childbearing-age women in this study, none developed a severe adverse illness or died. The median ages of pregnant and nonpregnant women were 33.0 and 33.5 years, respectively. Pregnant women had a markedly higher proportion of history exposure to hospitals within 2 weeks before onset compared to nonpregnant women (9/17, 53\% vs 5/26, 19\%, P=.02) and a lower proportion of other family members affected (4/17, 24\% vs 19/26, 73\%, P=.004). Fever (8/17, 47\% vs 18/26, 69\%) and cough (9/17, 53\% vs 12/26, 46\%) were common onsets of symptoms for the two groups. Abdominal pain (n=4, 24\%), vaginal bleeding (n=1, 6\%), reduced fetal movement (n=1, 6\%), and increased fetal movement (n=2, 13\%) were observed at onset in the 17 pregnant patients. Higher neutrophil and lower lymphocyte percent were observed in the pregnant group compared to the nonpregnant group (79\% vs 56\%, P<.001; 15\% vs 33\%, P<.001, respectively). In both groups, we observed an elevated concentration of high-sensitivity C-reactive protein, erythrocyte sedimentation rate, aminotransferase, and lactate dehydrogenase. Concentrations of alkaline phosphatase and D-dimer in the pregnant group were significantly higher than those of the nonpregnant group (119.0 vs 48.0 U/L, P<.001; 2.1 vs 0.3$\mu$g/mL, P<.001, respectively). Both pregnant (4/10, 40\%) and nonpregnant (8/15, 53\%) women tested positive for influenza A virus. A majority of pregnant and nonpregnant groups received antiviral (13/17, 76\% vs 25/26, 96\%) and antibiotic (13/17, 76\% vs 23/26, 88\%) therapy. Additionally, both pregnant (2/11, 18\%) and nonpregnant (2/19, 11\%) recovered women redetected positive for SARS-CoV-2 after discharge. Conclusions: The epidemiology and clinical and laboratory features of pregnant women with COVID-19 were diverse and atypical, which increased the difficulty of diagnosis. Most pregnant women with COVID-19 were mild and moderate, and rarely developed severe pneumonia or severe adverse outcomes. ", doi="10.2196/19642", url="http://www.jmir.org/2020/8/e19642/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750000" } @Article{info:doi/10.2196/21360, author="Ngai, Bik Cindy Sing and Singh, Gill Rita and Lu, Wenze and Koon, Chun Alex", title="Grappling With the COVID-19 Health Crisis: Content Analysis of Communication Strategies and Their Effects on Public Engagement on Social Media", journal="J Med Internet Res", year="2020", month="Aug", day="24", volume="22", number="8", pages="e21360", keywords="COVID-19", keywords="communication", keywords="public engagement", keywords="social media", keywords="infodemiology", keywords="infodemic", keywords="message style", keywords="health content frames", keywords="interactive features", keywords="framework", keywords="content analysis", abstract="Background: The coronavirus disease (COVID-19) has posed an unprecedented challenge to governments worldwide. Effective government communication of COVID-19 information with the public is of crucial importance. Objective: We investigate how the most-read state-owned newspaper in China, People's Daily, used an online social networking site, Sina Weibo, to communicate about COVID-19 and whether this could engage the public. The objective of this study is to develop an integrated framework to examine the content, message style, and interactive features of COVID-19--related posts and determine their effects on public engagement in the largest social media network in China. Methods: Content analysis was employed to scrutinize 608 COVID-19 posts, and coding was performed on three main dimensions: content, message style, and interactive features. The content dimension was coded into six subdimensions: action, new evidence, reassurance, disease prevention, health care services, and uncertainty, and the style dimension was coded into the subdimensions of narrative and nonnarrative. As for interactive features, they were coded into links to external sources, use of hashtags, use of questions to solicit feedback, and use of multimedia. Public engagement was measured in the form of the number of shares, comments, and likes on the People's Daily's Sina Weibo account from January 20, 2020, to March 11, 2020, to reveal the association between different levels of public engagement and communication strategies. A one-way analysis of variance followed by a post-hoc Tukey test and negative binomial regression analysis were employed to generate the results. Results: We found that although the content frames of action, new evidence, and reassurance delivered in a nonnarrative style were predominant in COVID-19 communication by the government, posts related to new evidence and a nonnarrative style were strong negative predictors of the number of shares. In terms of generating a high number of shares, it was found that disease prevention posts delivered in a narrative style were able to achieve this purpose. Additionally, an interaction effect was found between content and style. The use of a narrative style in disease prevention posts had a significant positive effect on generating comments and likes by the Chinese public, while links to external sources fostered sharing. Conclusions: These results have implications for governments, health organizations, medical professionals, the media, and researchers on their epidemic communication to engage the public. Selecting suitable communication strategies may foster active liking and sharing of posts on social media, which in turn, might raise the public's awareness of COVID-19 and motivate them to take preventive measures. The sharing of COVID-19 posts is particularly important because this action can reach out to a large audience, potentially helping to contain the spread of the virus. ", doi="10.2196/21360", url="http://www.jmir.org/2020/8/e21360/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750013" } @Article{info:doi/10.2196/22033, author="McRae, P. Michael and Dapkins, P. Isaac and Sharif, Iman and Anderman, Judd and Fenyo, David and Sinokrot, Odai and Kang, K. Stella and Christodoulides, J. Nicolaos and Vurmaz, Deniz and Simmons, W. Glennon and Alcorn, M. Timothy and Daoura, J. Marco and Gisburne, Stu and Zar, David and McDevitt, T. John", title="Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation", journal="J Med Internet Res", year="2020", month="Aug", day="24", volume="22", number="8", pages="e22033", keywords="COVID-19", keywords="coronavirus", keywords="clinical decision support system", keywords="point of care", keywords="mobile app", keywords="disease severity", keywords="biomarkers", keywords="artificial intelligence", keywords="app", keywords="family health center", abstract="Background: The coronavirus disease (COVID-19) pandemic has resulted in significant morbidity and mortality; large numbers of patients require intensive care, which is placing strain on health care systems worldwide. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. Objective: The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. Methods: Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, nonlaboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts the probability of mortality using biomarker measurements (C-reactive protein, procalcitonin, D-dimer) and age. Both the Tier 1 and Tier 2 models were validated using two external datasets from hospitals in Wuhan, China, comprising 160 and 375 patients, respectively. Results: All biomarkers were measured at significantly higher levels in patients who died vs those who were not hospitalized or discharged (P<.001). The Tier 1 and Tier 2 internal validations had areas under the curve (AUCs) of 0.79 (95\% CI 0.74-0.84) and 0.95 (95\% CI 0.92-0.98), respectively. The Tier 1 and Tier 2 external validations had AUCs of 0.79 (95\% CI 0.74-0.84) and 0.97 (95\% CI 0.95-0.99), respectively. Conclusions: Our results demonstrate the validity of the clinical decision support system and mobile app, which are now ready to assist health care providers in making evidence-based decisions when managing COVID-19 patient care. The deployment of these new capabilities has potential for immediate impact in community clinics and sites, where application of these tools could lead to improvements in patient outcomes and cost containment. ", doi="10.2196/22033", url="http://www.jmir.org/2020/8/e22033/", url="http://www.ncbi.nlm.nih.gov/pubmed/32750010" } @Article{info:doi/10.2196/20259, author="Abdulaal, Ahmed and Patel, Aatish and Charani, Esmita and Denny, Sarah and Mughal, Nabeela and Moore, Luke", title="Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e20259", keywords="COVID-19", keywords="coronavirus", keywords="machine learning", keywords="deep learning", keywords="modeling", keywords="artificial intelligence", keywords="neural network", keywords="prediction", abstract="Background: The current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak is a public health emergency and the case fatality rate in the United Kingdom is significant. Although there appear to be several early predictors of outcome, there are no currently validated prognostic models or scoring systems applicable specifically to patients with confirmed SARS-CoV-2. Objective: We aim to create a point-of-admission mortality risk scoring system using an artificial neural network (ANN). Methods: We present an ANN that can provide a patient-specific, point-of-admission mortality risk prediction to inform clinical management decisions at the earliest opportunity. The ANN analyzes a set of patient features including demographics, comorbidities, smoking history, and presenting symptoms and predicts patient-specific mortality risk during the current hospital admission. The model was trained and validated on data extracted from 398 patients admitted to hospital with a positive real-time reverse transcription polymerase chain reaction (RT-PCR) test for SARS-CoV-2. Results: Patient-specific mortality was predicted with 86.25\% accuracy, with a sensitivity of 87.50\% (95\% CI 61.65\%-98.45\%) and specificity of 85.94\% (95\% CI 74.98\%-93.36\%). The positive predictive value was 60.87\% (95\% CI 45.23\%-74.56\%), and the negative predictive value was 96.49\% (95\% CI 88.23\%-99.02\%). The area under the receiver operating characteristic curve was 90.12\%. Conclusions: This analysis demonstrates an adaptive ANN trained on data at a single site, which demonstrates the early utility of deep learning approaches in a rapidly evolving pandemic with no established or validated prognostic scoring systems. ", doi="10.2196/20259", url="http://www.jmir.org/2020/8/e20259/", url="http://www.ncbi.nlm.nih.gov/pubmed/32735549" } @Article{info:doi/10.2196/21176, author="Hu, Zhao and Lin, Xuhui and Chiwanda Kaminga, Atipatsa and Xu, Huilan", title="Impact of the COVID-19 Epidemic on Lifestyle Behaviors and Their Association With Subjective Well-Being Among the General Population in Mainland China: Cross-Sectional Study", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e21176", keywords="COVID-19", keywords="coronavirus disease", keywords="subjective well-being", keywords="lifestyle behaviors", abstract="Background: The world is experiencing an unprecedented challenge due to the coronavirus disease (COVID-19) pandemic. However, it is unclear whether people's lifestyles will change as a result. Objective: The aim of this study is to explore perceived lifestyle changes after the outbreak of COVID-19 and their association with subjective well-being (SWB) among the general population in Mainland China. Methods: An online survey was conducted in May 2020. Lifestyle behaviors including leisure-time physical exercise, leisure-time screen time, and dietary intake were self-reported. SWB was measured using the General Wellbeing Schedule (GWS). Other covariates including sociodemographic factors, self-rated physical health, perceived social support, and loneliness were also assessed by a structured questionnaire. A multivariate ordinal regression method was used to analyze the association between SWB and lifestyle behaviors as well as perceived lifestyle changes. Results: A total of 1033 participants aged between 18 and 60 years were included in this study. The mean GWS score was 71.7 points. About 70\% of the respondents reported spending more time looking at screens, whereas about 30\% reported an increased frequency of vegetable and fruit intake after the outbreak of COVID-19. Inactive physical exercise (odds ratio [OR] 1.16, 95\% CI 1.02-1.48), infrequent vegetable intake (OR 1.45, 95\% CI 1.10-1.90), infrequent fruit intake (OR 1.31, 95\% CI 1.01-1.70), and often skipping breakfast (OR 1.43, 95\% CI 1.08-1.91) were associated with lower SWB after adjusting for sociodemographic factors, self-rated physical health, perceived social support, and loneliness. Moreover, participants who perceived a decrease in the frequency of vegetable, fruit, and breakfast intake were more likely to report lower SWB. Conclusions: The COVID-19 pandemic may have positive and negative impacts on different aspects of lifestyle behaviors. Both unhealthy lifestyle behaviors and negative lifestyle changes were associated with lower SWB. These findings provide scientific evidence that can inform lifestyle guidelines and public mental health interventions during the COVID-19 outbreak. ", doi="10.2196/21176", url="http://www.jmir.org/2020/8/e21176/", url="http://www.ncbi.nlm.nih.gov/pubmed/32759103" } @Article{info:doi/10.2196/20334, author="Collado-Borrell, Roberto and Escudero-Vilaplana, Vicente and Villanueva-Bueno, Cristina and Herranz-Alonso, Ana and Sanjurjo-Saez, Maria", title="Features and Functionalities of Smartphone Apps Related to COVID-19: Systematic Search in App Stores and Content Analysis", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e20334", keywords="COVID-19", keywords="mobile apps", keywords="contact tracing", keywords="monitoring", keywords="telemedicine", keywords="smartphone", abstract="Background: Knowledge of the quantity and quality of apps related to coronavirus disease (COVID-19) is lacking. In addition, no directory has been established listing all the apps developed to address the COVID-19 pandemic. Objective: The aim of this study was to identify smartphone apps designed to address the COVID-19 pandemic and to analyze their characteristics. Methods: We performed an observational, cross-sectional, descriptive study of all smartphone apps associated with COVID-19. Between April 27 and May 2, 2020, we searched the App Store (iOS) and Google Play Store (Android) for COVID-19 apps. The search terms used were coronavirus, COVID-19, and SARS-COV-2. The apps were downloaded and evaluated. The variables analyzed were name, platform, country, language, category, cost, update date, size, version, number of downloads, developer, and purpose. Purpose was further classified into the following categories: news, general information, self-diagnosis, contact tracing, notices to contacts, notification of close cases, awareness, helplines, monitoring of clinical parameters, recording of symptoms and treatment, and messaging with health care professionals. Results: We identified 114 apps on the investigated platforms. Of these, 62/114 (54.4\%) were on Android and 52/114 (45.6\%) were on iOS. Of the 114 apps, 37 (32.5\%) were developed in Europe, 32 (28.1\%) in Asia, and 30 (26.3\%) in North America. The most frequent languages were English (65/114, 57.0\%), Spanish (34/114, 29.8\%), and Chinese (14/114, 12.3\%). The most common categories were health and well-being/fitness apps (41/114, 41.2\%) and medicine apps (43/114, 37.7\%). Of the 114 apps, 113 (99.1\%) were free. The mean time between the date of the analysis and the date of the last update was 11.1 days (SD 11.0). Overall, 95 of the 114 apps (83.3\%) were intended for the general population, 99 apps (7.9\%) were intended for health professionals, and 3 apps (2.6\%) were intended for both. Regarding the type of developer, 64/114 apps (56.1\%) were developed by governments; 42/114 (64.1\%) were developed by national governments, and 23/114 (35.9\%) were developed by regional governments. The apps with the highest number of downloads (100,000+) were developed by governments (P=.13), except for the World Health Organization app (500,000+). The purposes of the apps available in Western languages (107/114, 93.9\%) were determined; the most common purposes were general information about COVID-19 (66, 64.0\%), COVID-19 news (53, 51.0\%), recording of symptoms (53, 51.0\%), and contact tracing (51, 47.7\%). More than one purpose was identified for 99/107 apps (92.5\%). Conclusions: This paper offers a comprehensive and unique review of all available COVID-19 apps. Governments have adopted these tools during the pandemic, and more than half of the apps were developed by government agencies. The most common purposes of the apps are providing information on the numbers of infected, recovered, and deceased patients, recording of symptoms, and contact tracing. ", doi="10.2196/20334", url="https://www.jmir.org/2020/8/e20334", url="http://www.ncbi.nlm.nih.gov/pubmed/32614777" } @Article{info:doi/10.2196/21366, author="Evanoff, A. Bradley and Strickland, R. Jaime and Dale, Marie Ann and Hayibor, Lisa and Page, Emily and Duncan, G. Jennifer and Kannampallil, Thomas and Gray, L. Diana", title="Work-Related and Personal Factors Associated With Mental Well-Being During the COVID-19 Response: Survey of Health Care and Other Workers", journal="J Med Internet Res", year="2020", month="Aug", day="25", volume="22", number="8", pages="e21366", keywords="COVID-19", keywords="coronavirus", keywords="pandemic", keywords="mental health", keywords="health care workers", keywords="remote work", keywords="worker well-being", keywords="occupational health", abstract="Background: The response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has created an unprecedented disruption in work conditions. This study describes the mental health and well-being of workers both with and without clinical exposure to patients with coronavirus disease (COVID-19). Objective: The aim of this study is to measure the prevalence of stress, anxiety, depression, work exhaustion, burnout, and decreased well-being among faculty and staff at a university and academic medical center during the SARS-CoV-2 pandemic and describe work-related and personal factors associated with their mental health and well-being. Methods: All faculty, staff, and postdoctoral fellows of a university, including its medical school, were invited in April 2020 to complete an online questionnaire measuring stress, anxiety, depression, work exhaustion, burnout, and decreased well-being. We examined associations between these outcomes and factors including work in high-risk clinical settings and family/home stressors. Results: There were 5550 respondents (overall response rate of 34.3\%). Overall, 34\% of faculty and 14\% of staff (n=915) were providing clinical care, while 61\% of faculty and 77\% of staff were working from home. Among all workers, anxiety (prevalence ratio 1.37, 95\% CI 1.09-1.73), depression (prevalence ratio 1.28, 95\% CI 1.03-1.59), and high work exhaustion (prevalence ratio 1.24, 95\% CI 1.13-1.36) were independently associated with community or clinical exposure to COVID-19. Poor family-supportive behaviors by supervisors were also associated with these outcomes (prevalence ratio 1.40, 95\% CI 1.21-1.62; prevalence ratio 1.69, 95\% CI 1.48-1.92; and prevalence ratio 1.54, 95\% CI 1.44-1.64, respectively). Age <40 years and a greater number of family/home stressors were also associated with these poorer outcomes. Among the subset of clinicians, caring for patients with COVID-19 and working in high-risk clinical settings were additional risk factors. Conclusions: Our findings suggest that the pandemic has had negative effects on the mental health and well-being of both clinical and nonclinical employees. Mitigating exposure to COVID-19 and increasing supervisor support are modifiable risk factors that may protect mental health and well-being for all workers. ", doi="10.2196/21366", url="http://www.jmir.org/2020/8/e21366/", url="http://www.ncbi.nlm.nih.gov/pubmed/32763891" } @Article{info:doi/10.2196/19572, author="Hu, Guangyu and Li, Peiyi and Yuan, Changzheng and Tao, Chenglin and Wen, Hai and Liu, Qiannan and Qiu, Wuqi", title="Information Disclosure During the COVID-19 Epidemic in China: City-Level Observational Study", journal="J Med Internet Res", year="2020", month="Aug", day="27", volume="22", number="8", pages="e19572", keywords="information disclosure", keywords="COVID-19", keywords="website", keywords="risk", keywords="communication", keywords="China", keywords="disclosure", keywords="pandemic", keywords="health information", keywords="public health", abstract="Background: Information disclosure is a top priority for official responses to the COVID-19 pandemic. The timely and standardized information published by authorities as a response to the crisis can better inform the public and enable better preparations for the pandemic; however, there is limited evidence of any systematic analyses of the disclosed epidemic information. This in turn has important implications for risk communication. Objective: This study aimed to describe and compare the officially released content regarding local epidemic situations as well as analyze the characteristics of information disclosure through local communication in major cities in China. Methods: The 31 capital cities in mainland China were included in this city-level observational study. Data were retrieved from local municipalities and health commission websites as of March 18, 2020. A checklist was employed as a rapid qualitative assessment tool to analyze the information disclosure performance of each city. Descriptive analyses and data visualizations were produced to present and compare the comparative performances of the cities. Results: In total, 29 of 31 cities (93.5\%) established specific COVID-19 webpages to disclose information. Among them, 12 of the city webpages were added to their corresponding municipal websites. A majority of the cities (21/31, 67.7\%) published their first cases of infection in a timely manner on the actual day of confirmation. Regarding the information disclosures highlighted on the websites, news updates from local media or press briefings were the most prevalent (28/29, 96.6\%), followed by epidemic surveillance (25/29, 86.2\%), and advice for the public (25/29, 86.2\%). Clarifications of misinformation and frequently asked questions were largely overlooked as only 2 cities provided this valuable information. The median daily update frequency of epidemic surveillance summaries was 1.2 times per day (IQR 1.0-1.3 times), and the majority of these summaries (18/25, 72.0\%) also provided detailed information regarding confirmed cases. The reporting of key indicators in the epidemic surveillance summaries, as well as critical facts included in the confirmed case reports, varied substantially between cities. In general, the best performance in terms of timely reporting and the transparency of information disclosures were observed in the municipalities directly administered by the central government compared to the other cities. Conclusions: Timely and effective efforts to disclose information related to the COVID-19 epidemic have been made in major cities in China. Continued improvements to local authority reporting will contribute to more effective public communication and efficient public health research responses. The development of protocols and the standardization of epidemic message templates---as well as the use of uniform operating procedures to provide regular information updates---should be prioritized to ensure a coordinated national response. ", doi="10.2196/19572", url="http://www.jmir.org/2020/8/e19572/", url="http://www.ncbi.nlm.nih.gov/pubmed/32790640" } @Article{info:doi/10.2196/19799, author="Becker, Regina and Thorogood, Adrian and Ordish, Johan and Beauvais, J.S. Michael", title="COVID-19 Research: Navigating the European General Data Protection Regulation", journal="J Med Internet Res", year="2020", month="Aug", day="27", volume="22", number="8", pages="e19799", keywords="COVID-19", keywords="GDPR", keywords="health research", keywords="pandemic", keywords="data privacy", keywords="data protection", keywords="regulation", doi="10.2196/19799", url="http://www.jmir.org/2020/8/e19799/", url="http://www.ncbi.nlm.nih.gov/pubmed/32784191" } @Article{info:doi/10.2196/21613, author="Kaspar, Kai", title="Motivations for Social Distancing and App Use as Complementary Measures to Combat the COVID-19 Pandemic: Quantitative Survey Study", journal="J Med Internet Res", year="2020", month="Aug", day="27", volume="22", number="8", pages="e21613", keywords="COVID-19", keywords="protection motivation theory", keywords="social distancing", keywords="contact tracing app", keywords="data donation app", keywords="social trust", keywords="data security", abstract="Background: The current COVID-19 pandemic is showing negative effects on human health as well as on social and economic life. It is a critical and challenging task to revive public life while minimizing the risk of infection. Reducing interactions between people by social distancing is an effective and prevalent measure to reduce the risk of infection and spread of the virus within a community. Current developments in several countries show that this measure can be technologically accompanied by mobile apps; meanwhile, privacy concerns are being intensively discussed. Objective: The aim of this study was to examine central cognitive variables that may constitute people's motivations for social distancing, using an app, and providing health-related data requested by two apps that differ in their direct utility for the individual user. The results may increase our understanding of people's concerns and convictions, which can then be specifically addressed by public-oriented communication strategies and appropriate political decisions. Methods: This study refers to the protection motivation theory, which is adaptable to both health-related and technology-related motivations. The concept of social trust was added. The quantitative survey included answers from 406 German-speaking participants who provided assessments of data security issues, trust components, and the processes of threat and coping appraisal related to the prevention of SARS-CoV-2 infection by social distancing. With respect to apps, one central focus was on the difference between a contact tracing app and a data donation app. Results: Multiple regression analyses showed that the present model could explain 55\% of the interindividual variance in the participants' motivation for social distancing, 46\% for using a contact tracing app, 42\% for providing their own infection status to a contact tracing app, and 34\% for using a data donation app. Several cognitive components of threat and coping appraisal were related to motivation measurements. Trust in other people's social distancing behavior and general trust in official app providers also played important roles; however, the participants' age and gender did not. Motivations for using and accepting a contact tracing app were higher than those for using and accepting a data donation app. Conclusions: This study revealed some important cognitive factors that constitute people's motivation for social distancing and using apps to combat the COVID-19 pandemic. Concrete implications for future research, public-oriented communication strategies, and appropriate political decisions were identified and are discussed. ", doi="10.2196/21613", url="http://www.jmir.org/2020/8/e21613/", url="http://www.ncbi.nlm.nih.gov/pubmed/32759100" } @Article{info:doi/10.2196/19629, author="Pobiruchin, Monika and Zowalla, Richard and Wiesner, Martin", title="Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19--Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study", journal="J Med Internet Res", year="2020", month="Aug", day="28", volume="22", number="8", pages="e19629", keywords="COVID-19", keywords="SARS-CoV-2", keywords="social media", keywords="public health", keywords="Twitter", keywords="infoveillance", keywords="infodemiology", keywords="infodemic", keywords="health informatics", keywords="disease surveillance", abstract="Background: The spread of the 2019 novel coronavirus disease, COVID-19, across Asia and Europe sparked a significant increase in public interest and media coverage, including on social media platforms such as Twitter. In this context, the origin of information plays a central role in the dissemination of evidence-based information about the SARS-CoV-2 virus and COVID-19. On February 2, 2020, the World Health Organization (WHO) constituted a ``massive infodemic'' and argued that this situation ``makes it hard for people to find trustworthy sources and reliable guidance when they need it.'' Objective: This infoveillance study, conducted during the early phase of the COVID-19 pandemic, focuses on the social media platform Twitter. It allows monitoring of the dynamic pandemic situation on a global scale for different aspects and topics, languages, as well as regions and even whole countries. Of particular interest are temporal and geographical variations of COVID-19--related tweets, the situation in Europe, and the categories and origin of shared external resources. Methods: Twitter's Streaming application programming interface was used to filter tweets based on 16 prevalent hashtags related to the COVID-19 outbreak. Each tweet's text and corresponding metadata as well as the user's profile information were extracted and stored into a database. Metadata included links to external resources. A link categorization scheme---introduced in a study by Chew and Eysenbach in 2009---was applied onto the top 250 shared resources to analyze the relative proportion for each category. Moreover, temporal variations of global tweet volumes were analyzed and a specific analysis was conducted for the European region. Results: Between February 9 and April 11, 2020, a total of 21,755,802 distinct tweets were collected, posted by 4,809,842 distinct Twitter accounts. The volume of \#covid19-related tweets increased after the WHO announced the name of the new disease on February 11, 2020, and stabilized at the end of March at a high level. For the regional analysis, a higher tweet volume was observed in the vicinity of major European capitals or in densely populated areas. The most frequently shared resources originated from various social media platforms (ranks 1-7). The most prevalent category in the top 50 was ``Mainstream or Local News.'' For the category ``Government or Public Health,'' only two information sources were found in the top 50: US Centers for Disease Control and Prevention at rank 25 and the WHO at rank 27. The first occurrence of a prevalent scientific source was Nature (rank 116). Conclusions: The naming of the disease by the WHO was a major signal to address the public audience with public health response via social media platforms such as Twitter. Future studies should focus on the origin and trustworthiness of shared resources, as monitoring the spread of fake news during a pandemic situation is of particular importance. In addition, it would be beneficial to analyze and uncover bot networks spreading COVID-19--related misinformation. ", doi="10.2196/19629", url="http://www.jmir.org/2020/8/e19629/", url="http://www.ncbi.nlm.nih.gov/pubmed/32790641" } @Article{info:doi/10.2196/18580, author="Ruth, J. Caleb and Huey, Lee Samantha and Krisher, T. Jesse and Fothergill, Amy and Gannon, M. Bryan and Jones, Elyse Camille and Centeno-Tablante, Elizabeth and Hackl, S. Laura and Colt, Susannah and Finkelstein, Leigh Julia and Mehta, Saurabh", title="An Electronic Data Capture Framework (ConnEDCt) for Global and Public Health Research: Design and Implementation", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e18580", keywords="data science", keywords="data collection", keywords="database management systems", keywords="global health", keywords="public health", keywords="data management", keywords="health information management", keywords="population surveillance", keywords="longitudinal studies", keywords="randomized controlled trial", keywords="Electronic Data Capture (EDC)", abstract="Background: When we were unable to identify an electronic data capture (EDC) package that supported our requirements for clinical research in resource-limited regions, we set out to build our own reusable EDC framework. We needed to capture data when offline, synchronize data on demand, and enforce strict eligibility requirements and complex longitudinal protocols. Based on previous experience, the geographical areas in which we conduct our research often have unreliable, slow internet access that would make web-based EDC platforms impractical. We were unwilling to fall back on paper-based data capture as we wanted other benefits of EDC. Therefore, we decided to build our own reusable software platform. In this paper, we describe our customizable EDC framework and highlight how we have used it in our ongoing surveillance programs, clinic-based cross-sectional studies, and randomized controlled trials (RCTs) in various settings in India and Ecuador. Objective: This paper describes the creation of a mobile framework to support complex clinical research protocols in a variety of settings including clinical, surveillance, and RCTs. Methods: We developed ConnEDCt, a mobile EDC framework for iOS devices and personal computers, using Claris FileMaker software for electronic data capture and data storage. Results: ConnEDCt was tested in the field in our clinical, surveillance, and clinical trial research contexts in India and Ecuador and continuously refined for ease of use and optimization, including specific user roles; simultaneous synchronization across multiple locations; complex randomization schemes and informed consent processes; and collecting diverse types of data (laboratory, growth measurements, sociodemographic, health history, dietary recall and feeding practices, environmental exposures, and biological specimen collection). Conclusions: ConnEDCt is customizable, with regulatory-compliant security, data synchronization, and other useful features for data collection in a variety of settings and study designs. Furthermore, ConnEDCt is user friendly and lowers the risks for errors in data entry because of real time error checking and protocol enforcement. ", doi="10.2196/18580", url="https://www.jmir.org/2020/8/e18580", url="http://www.ncbi.nlm.nih.gov/pubmed/32788154" }