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      Patient experiences with SARS-CoV-2: Associations between patient experience of disease and coping profiles

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          Abstract

          Introduction

          Severe acute respiratory syndrome coronavirus 2, (SARS-CoV-2,) caused an influx of patients with acute disease characterized by a variety of symptoms termed COVID-19 disease, with some patients going on to develop post-acute COVID-19 syndrome. Individual factors like sex or coping styles are associated with a person’s disease experience and quality of life. Individual differences in coping styles used to manage COVID-19 related stress correlate with physical and mental health outcomes. Our study sought to understand the relationship between COVID-19 symptoms, severity of acute disease, and coping profiles.

          Methods

          An online survey to assess symptoms, functional status, and recovery in a large group of patients was nationally distributed online. The survey asked about symptoms, course of illness, and included the Brief-COPE and the adapted Social Relationship Inventory. We used descriptive and cluster analyses to characterize patterns of survey responses.

          Results

          976 patients were included in the analysis. The most common symptoms reported by the patients were fatigue (72%), cough (71%), body aches/joint pain (66%), headache (62%), and fever/chills (62%). 284 participants reported PACS. We described three different coping profiles: outward, inward, and dynamic copers.

          Discussion

          Fatigue, cough, and body aches/joint pains were the most frequently reported symptoms. PACS patients were sicker, more likely to have been hospitalized. Of the three coping profiles, outward copers were more likely to be admitted to the hospital and had the healthiest coping strategies. Dynamic copers activated several coping strategies both positive and negative; they were also younger and more likely to report PACS.

          Conclusion

          Cough, fatigue, and body aches/joint pain are common and most important to patients with acute COVID-19, while shortness of breath defined the experience for patients with PACS. Of the three coping profiles, dynamic copers were more likely to report PACS. Additional investigations into coping profiles in general, and the experience of COVID-19 and PACS is needed.

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          Most cited references46

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            The REDCap consortium: Building an international community of software platform partners

            The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
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              An interactive web-based dashboard to track COVID-19 in real time

              In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 November 2023
                2023
                : 18
                : 11
                : e0294201
                Affiliations
                [1 ] The Oregon Clinic, Department of Pulmonary, Critical Care, and Sleep Medicine East, Portland, Oregon, United States of America
                [2 ] Department of Psychology and Neuroscience Center, Brigham Young University, Provo, Utah, United States of America
                [3 ] Intermountain Health, Center for Humanizing Critical Care, Murray, Utah, United States of America
                [4 ] Intermountain Health, Division of Pulmonary and Critical Care, Murray, Utah, United States of America
                [5 ] Intermountain Health, Strategic Research, Salt Lake City, Utah, United States of America
                [6 ] Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States of America
                [7 ] Division of Geriatrics, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States of America
                [8 ] Informatics Decision-Enhancement and Analytic Sciences (IDEAS), Center for Innovation & Geriatrics Research, Education, and Clinical Center (GRECC), VA Salt Lake City Health Care System, Salt Lake City, UT, United States of America
                [9 ] Division of Pulmonology, School of Medicine, University of Utah, Salt Lake City, Utah, United States of America
                University of Macerata: Universita degli Studi di Macerata, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-3838-2679
                Article
                PONE-D-23-13488
                10.1371/journal.pone.0294201
                10659202
                37983278
                76c921ba-2639-4195-8b09-fbae0147c07b

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 21 May 2023
                : 27 October 2023
                Page count
                Figures: 4, Tables: 6, Pages: 18
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100005564, Gilead Sciences;
                Award ID: 2021029
                Award Recipient :
                ELH 2021029 Gilead Sciences, Inc. https://www.gilead.com/ The funders had no role in study design, data collection and analysis. The funders did influence the decision to publish and during the preparation of the manuscript they reviewed drafts.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Fatigue
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Coughing
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Coughing
                Medicine and Health Sciences
                Medical Conditions
                Respiratory Disorders
                Dyspnea
                Medicine and Health Sciences
                Pulmonology
                Respiratory Disorders
                Dyspnea
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Pain
                Abdominal Pain
                Research and Analysis Methods
                Research Design
                Survey Research
                Surveys
                Medicine and Health Sciences
                Clinical Medicine
                Signs and Symptoms
                Pain
                Social Sciences
                Anthropology
                Cultural Anthropology
                Religion
                Social Sciences
                Sociology
                Religion
                Custom metadata
                Our study protocol, IRB approval (IRB # 1051610), and patient consent preclude our ability to publicly share these data. We have appropriately presented the data in aggregate format. De-identified data may be obtained through approval from the Intermountain Health IRB. Data requests should be directed to Valerie Aston at Valerie.Aston@ 123456imail.org .
                COVID-19

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                Uncategorized

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