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      Trends of Prevalence Estimates and Risk Factors of Depressive Symptoms among Healthcare Workers Over one Year of the COVID-19 Pandemic

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          Abstract

          Background:

          COVID-19 pandemic has an overwhelming psychologic burden on healthcare workers (HCWs). This study aims to investigate the changes in the prevalence, estimates, severity, and risk factors of depressive symptoms among HCWs within the first year of the COVID-19 pandemic.

          Methods:

          An observational e-survey collected data on HCWs’ socio-demographic characteristics, occupational situation, and depressive symptoms as measured by Patient Health Questionnaire–9 (PHQ-9). The e-survey was distributed one month after the onset of the COVID-19 pandemic (onset group) and again after one year (one-year group).

          Results:

          A total of 422 HCWs were included (Mean (SD) age, 35.3 (9.9) years; 71.3% males), with 211 (50%) participants in each group. In the total cohort, the mean PHQ-9 score was 8.5, and 36.7% reported clinically significant levels of depressive symptoms with a PHQ-9 score of ≥10. Compared to the onset group, the one-year group reported a higher risk of major depressive disorder (41.7% vs. 31.8%; OR 1.538; 95%CI 1.032–2.291; p=0.034), a higher mean PHQ-9 score (9.5 (6.8) vs. 7.4 (5.3), p<0.001), and more severe depressive symptoms (p<0.005). Participants who were younger, unmarried, underwent testing for COVID-19, reported lower monthly income, did not receive special COVID-19 education, or had lower satisfaction with institutional preparedness had significantly higher depression scores and symptoms in both onset and one-year groups ( p<0.05 for each category). Female gender and direct contact with COVID-19 patients or samples were significant risk factors within the onset group. Occupation as a physician, history of COVID-19 testing or infection, and perception of significant changes in work schedule or intensity were significantly associated with higher depression scores and symptoms among the one-year group.

          Conclusion:

          This study sheds light on an unspoken but significant rise in prevalence estimates and severity of depressive symptoms among HCWs over a year of the COVID-19 pandemic and shows the vulnerable subgroups for whom a psychological intervention might be warranted.

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          The PHQ-9: validity of a brief depression severity measure.

          K Kroenke, R L Spitzer, J B Williams (2001)
          While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.
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            An interactive web-based dashboard to track COVID-19 in real time

            Ensheng Dong, Hongru Du, Lauren Gardner (2020)
            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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              Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019

              Jianbo Lai, Simeng Ma, Ying Wang … (2020)
              Key Points Question What factors are associated with mental health outcomes among health care workers in China who are treating patients with coronavirus disease 2019 (COVID-19)? Findings In this cross-sectional study of 1257 health care workers in 34 hospitals equipped with fever clinics or wards for patients with COVID-19 in multiple regions of China, a considerable proportion of health care workers reported experiencing symptoms of depression, anxiety, insomnia, and distress, especially women, nurses, those in Wuhan, and front-line health care workers directly engaged in diagnosing, treating, or providing nursing care to patients with suspected or confirmed COVID-19. Meaning These findings suggest that, among Chinese health care workers exposed to COVID-19, women, nurses, those in Wuhan, and front-line health care workers have a high risk of developing unfavorable mental health outcomes and may need psychological support or interventions.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Clin Pract Epidemiol Ment Health
                Journal ID (iso-abbrev): Clin Pract Epidemiol Ment Health
                Journal ID (publisher-id): CPEMH
                Title: Clinical Practice and Epidemiology in Mental Health : CP & EMH
                Publisher: Bentham Science Publishers
                ISSN (Electronic): 1745-0179
                Publication date (Electronic): 30 June 2022
                Publication date Collection: 2022
                Volume: 18
                Electronic Location Identifier: e174501792206160
                Affiliations
                [1 ]Department of Neurology, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan
                [2 ] deptDepartment of Public Health and Family Medicine, Faculty of Medicine , Jordan University of Science and Technology , Irbid, , Jordan
                [3 ] deptDepartment of Basic Medical Sciences, Faculty of Medicine , Yarmouk University , Irbid, , Jordan
                [4 ] deptDepartment of Clinical Pharmacy , Jordan University of Science and Technology , Irbid, , Jordan
                [5 ] deptFaculty of Medicine , Jordan University of Science and Technology , Irbid, , Jordan
                [6 ]Department of Psychiatry, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan
                Author notes
                [* ]Address correspondence to this author at the Department of Neurology, School of Medicine, Jordan University of Science and Technology, P.O.Box: (630001) Irbid (22110) Jordan; E-mail: amyassin@ 123456just.edu.jo
                Article
                Publisher ID: CPEMH-18-e174501792206160
                DOI: 10.2174/17450179-v18-e2206160
                PMC ID: 10158079
                PubMed ID: 37274865
                SO-VID: f05617c7-ed76-4390-8c8b-fe9c396ed559
                Copyright © © 2022 Al Yassin et al.
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 3 March 2022
                Date revision received : 21 April 2022
                Date accepted : 27 April 2022
                Categories
                Subject: Article

                ScienceOpen disciplines: Neurology
                Keywords: covid-19,depression,healthcare workers,health providers,physicians,one-year
                Data availability:
                ScienceOpen disciplines: Neurology
                Keywords: covid-19, depression, healthcare workers, health providers, physicians, one-year

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