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      Gender-affirming care, mental health, and economic stability in the time of COVID-19: A multi-national, cross-sectional study of transgender and nonbinary people

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          Abstract

          Background

          Transgender and nonbinary people are disproportionately affected by structural barriers to quality healthcare, mental health challenges, and economic hardship. This study examined the impact of the novel coronavirus disease (COVID-19) crisis and subsequent control measures on gender-affirming care, mental health, and economic stability among transgender and nonbinary people in multiple countries.

          Methods

          We collected multi-national, cross-sectional data from 964 transgender and nonbinary adult users of the Hornet and Her apps from April to August 2020 to characterize changes in gender-affirming care, mental health, and economic stability as a result of COVID-19. We conducted Poisson regression models to assess if access to gender-affirming care and ability to live according to one’s gender were related to depressive symptoms, anxiety, and changes in suicidal ideation.

          Results

          Individuals resided in 76 countries, including Turkey (27.4%, n = 264) and Thailand (20.6%, n = 205). A majority were nonbinary (66.8%, n = 644) or transfeminine (29.4%, n = 283). Due to COVID-19, 55.0% (n = 320/582) reported reduced access to gender-affirming resources, and 38.0% (n = 327/860) reported reduced time lived according to their gender. About half screened positive for depression (50.4%,442/877) and anxiety (45.8%, n = 392/856). One in six (17.0%, n = 112/659) expected losses of health insurance, and 77.0% (n = 724/940) expected income reductions. The prevalence of depressive symptoms, anxiety, and increased suicidal ideation were 1.63 (95% CI: 1.36–1.97), 1.61 (95% CI: 1.31–1.97), and 1.74 (95% CI: 1.07–2.82) times higher for individuals whose access to gender-affirming resources was reduced versus not.

          Discussion

          The COVID-19 crisis is associated with reduced access to gender-affirming resources and the ability of transgender and nonbinary people to live according to their gender worldwide. These reductions may drive the increased depressive symptoms, anxiety, and suicidal ideation reported in this sample. To improve health of transgender and nonbinary communities, increased access to gender-affirming resources should be prioritized through policies (e.g., digital prescriptions), flexible interventions (e.g., telehealth), and support for existing transgender health initiatives.

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          Most cited references66

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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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            The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review

            The COVID-19 pandemic has resulted in over 1.4 million confirmed cases and over 83,000 deaths globally. It has also sparked fears of an impending economic crisis and recession. Social distancing, self-isolation and travel restrictions forced a decrease in the workforce across all economic sectors and caused many jobs to be lost. Schools have closed down, and the need of commodities and manufactured products has decreased. In contrast, the need for medical supplies has significantly increased. The food sector has also seen a great demand due to panic-buying and stockpiling of food products. In response to this global outbreak, we summarise the socio-economic effects of COVID-19 on individual aspects of the world economy.
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              Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis

              Background The COVID-19 pandemic has had a significant impact on public mental health. Therefore, monitoring and oversight of the population mental health during crises such as a panedmic is an immediate priority. The aim of this study is to analyze the existing research works and findings in relation to the prevalence of stress, anxiety and depression in the general population during the COVID-19 pandemic. Method In this systematic review and meta-analysis, articles that have focused on stress and anxiety prevalence among the general population during the COVID-19 pandemic were searched in the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases, without a lower time limit and until May 2020. In order to perform a meta-analysis of the collected studies, the random effects model was used, and the heterogeneity of studies was investigated using the I2 index. Moreover. data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software. Results The prevalence of stress in 5 studies with a total sample size of 9074 is obtained as 29.6% (95% confidence limit: 24.3–35.4), the prevalence of anxiety in 17 studies with a sample size of 63,439 as 31.9% (95% confidence interval: 27.5–36.7), and the prevalence of depression in 14 studies with a sample size of 44,531 people as 33.7% (95% confidence interval: 27.5–40.6). Conclusion COVID-19 not only causes physical health concerns but also results in a number of psychological disorders. The spread of the new coronavirus can impact the mental health of people in different communities. Thus, it is essential to preserve the mental health of individuals and to develop psychological interventions that can improve the mental health of vulnerable groups during the COVID-19 pandemic.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: 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
                9 July 2021
                2021
                9 July 2021
                : 16
                : 7
                : e0254215
                Affiliations
                [1 ] Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, United States of America
                [2 ] Department of Health Behavior and Biological Sciences, University of Michigan School of Nursing, Ann Arbor, Michigan, United States of America
                [3 ] Department of Health, Policy, and Management, Johns Hopkins School of Public Health, Baltimore, MD, United States of America
                [4 ] Hornet, San Francisco, CA, United States of America
                [5 ] Department of Health, Behavior, and Society, Department of International Health, Johns Hopkins School of Public Health, Baltimore, MD, United States of America
                University of California San Diego, UNITED STATES
                Author notes

                Competing Interests: SWB has received funding from Viiv Healthcare as a consultant. SH is the co-founder, chairman, and president of Hornet. Participant recruitment was conducted via the Hornet app. No other authors had competing interests to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                https://orcid.org/0000-0003-2966-3521
                https://orcid.org/0000-0003-2992-8198
                Article
                PONE-D-20-32464
                10.1371/journal.pone.0254215
                8270151
                34242317
                d3c09e1f-fdf6-4152-bb30-9b40bb6929cc
                © 2021 Jarrett et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 October 2020
                : 22 June 2021
                Page count
                Figures: 0, Tables: 5, Pages: 17
                Funding
                Funded by: national institute of mental health
                Award ID: F31MH121128
                Award Recipient :
                Funded by: national institute of mental health
                Award ID: F31MH121128
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;
                Award ID: F31MH121128
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;
                Award ID: K01MH114715
                Award Recipient :
                Funded by: national institute of mental health
                Award ID: K01MH114715
                Award Recipient :
                Funded by: national institute of mental health
                Award ID: K01MH114715
                Award Recipient :
                Funded by: national institute of mental health
                Award ID: R01MH110358
                Award Recipient :
                Funded by: national institute of mental health
                Award ID: R01MH110358
                Award Recipient :
                Funded by: national institute of mental health
                Award ID: R01MH110358
                Award Recipient :
                Funded by: viiv healthcare
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: T32AI102623
                Award Recipient :
                BAJ, SWB, and SDB were supported by the National Institute of Mental Health (F31MH121128, K01MH114715, R01MH110358 respectively). SWB also receives funding from Viiv Healthcare. AJR was supported by the National Institute of Allergy and Infectious Diseases (grant T32AI102623). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Medicine and Health Sciences
                Epidemiology
                Pandemics
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Suicide
                Social Sciences
                Economics
                Health Economics
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                Health Care
                Health Economics
                Medicine and Health Sciences
                Pharmaceutics
                Drug Therapy
                Hormonal Therapy
                Social Sciences
                Economics
                Health Economics
                Health Insurance
                Medicine and Health Sciences
                Health Care
                Health Economics
                Health Insurance
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Custom metadata
                Relevant data are available in the Zenodo repository: http://doi.org/10.5281/zenodo.4899912.
                COVID-19

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