4
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Trajectories of Mental Distress Among U.S. Adults During the COVID-19 Pandemic

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Cross-sectional studies have found that the coronavirus disease 2019 (COVID-19) pandemic has negatively affected population-level mental health. Longitudinal studies are necessary to examine trajectories of change in mental health over time and identify sociodemographic groups at risk for persistent distress.

          Purpose

          To examine the trajectories of mental distress between March 10 and August 4, 2020, a key period during the COVID-19 pandemic.

          Methods

          Participants included 6,901 adults from the nationally representative Understanding America Study, surveyed at baseline between March 10 and 31, 2020, with nine follow-up assessments between April 1 and August 4, 2020. Mixed-effects logistic regression was used to examine the association between date and self-reported mental distress (measured with the four-item Patient Health Questionnaire) among U.S. adults overall and among sociodemographic subgroups defined by sex, age, race/ethnicity, household structure, federal poverty line, and census region.

          Results

          Compared to March 11, the odds of mental distress among U.S. adults overall were 1.84 (95% confidence interval [CI] = 1.65–2.07) times higher on April 1 and 1.92 (95% CI = 1.62–2.28) times higher on May 1; by August 1, the odds of mental distress had returned to levels comparable to March 11 (odds ratio [OR] = 0.80, 95% CI = 0.66–0.96). Females experienced a sharper increase in mental distress between March and May compared to males (females: OR = 2.29, 95% CI = 1.85–2.82; males: OR = 1.53, 95% CI = 1.15–2.02).

          Conclusions

          These findings highlight the trajectory of mental health symptoms during an unprecedented pandemic, including the identification of populations at risk for sustained mental distress.

          Related collections

          Most cited references31

          • Record: found
          • Abstract: found
          • Article: not found

          The psychological impact of quarantine and how to reduce it: rapid review of the evidence

          Summary The December, 2019 coronavirus disease outbreak has seen many countries ask people who have potentially come into contact with the infection to isolate themselves at home or in a dedicated quarantine facility. Decisions on how to apply quarantine should be based on the best available evidence. We did a Review of the psychological impact of quarantine using three electronic databases. Of 3166 papers found, 24 are included in this Review. Most reviewed studies reported negative psychological effects including post-traumatic stress symptoms, confusion, and anger. Stressors included longer quarantine duration, infection fears, frustration, boredom, inadequate supplies, inadequate information, financial loss, and stigma. Some researchers have suggested long-lasting effects. In situations where quarantine is deemed necessary, officials should quarantine individuals for no longer than required, provide clear rationale for quarantine and information about protocols, and ensure sufficient supplies are provided. Appeals to altruism by reminding the public about the benefits of quarantine to wider society can be favourable.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found

              Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science

              Summary The coronavirus disease 2019 (COVID-19) pandemic is having a profound effect on all aspects of society, including mental health and physical health. We explore the psychological, social, and neuroscientific effects of COVID-19 and set out the immediate priorities and longer-term strategies for mental health science research. These priorities were informed by surveys of the public and an expert panel convened by the UK Academy of Medical Sciences and the mental health research charity, MQ: Transforming Mental Health, in the first weeks of the pandemic in the UK in March, 2020. We urge UK research funding agencies to work with researchers, people with lived experience, and others to establish a high level coordination group to ensure that these research priorities are addressed, and to allow new ones to be identified over time. The need to maintain high-quality research standards is imperative. International collaboration and a global perspective will be beneficial. An immediate priority is collecting high-quality data on the mental health effects of the COVID-19 pandemic across the whole population and vulnerable groups, and on brain function, cognition, and mental health of patients with COVID-19. There is an urgent need for research to address how mental health consequences for vulnerable groups can be mitigated under pandemic conditions, and on the impact of repeated media consumption and health messaging around COVID-19. Discovery, evaluation, and refinement of mechanistically driven interventions to address the psychological, social, and neuroscientific aspects of the pandemic are required. Rising to this challenge will require integration across disciplines and sectors, and should be done together with people with lived experience. New funding will be required to meet these priorities, and it can be efficiently leveraged by the UK's world-leading infrastructure. This Position Paper provides a strategy that may be both adapted for, and integrated with, research efforts in other countries.
                Bookmark

                Author and article information

                Journal
                Ann Behav Med
                Ann Behav Med
                abm
                Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine
                Oxford University Press (US )
                0883-6612
                1532-4796
                08 February 2021
                : kaaa126
                Affiliations
                [1 ] Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University , 624 N Broadway, Room 798, Baltimore, MD, USA
                [2 ] Department of Neuropsychology, Kennedy Krieger Institute, Johns Hopkins University , Baltimore, MD, USA
                [3 ] Center for Economic and Social Research, University of Southern California , Los Angeles, CA, USA
                [4 ] Centre for Alcohol Policy Research, La Trobe University , Bundoora, VIC, Australia
                [5 ] Joint Program in Survey Methodology, University of Maryland, College Park , College Park, MD, USA
                [6 ] School of Social Sciences, University of Mannheim , Mannheim, Germany
                [7 ] Statistical Methods Group, Institute for Employment Research , Nuremberg, Germany
                [8 ] Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University , Baltimore, MD, USA
                [9 ] School of Nursing, Columbia University , New York, NY, USA
                Author notes
                Author information
                http://orcid.org/0000-0002-9061-0560
                http://orcid.org/0000-0001-8929-9579
                Article
                kaaa126
                10.1093/abm/kaaa126
                7929474
                33555336
                6ab4982d-5ace-4e97-ada7-26001baa2159
                © Society of Behavioral Medicine 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

                This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

                This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

                History
                Page count
                Pages: 10
                Funding
                Funded by: Social Security Administration, DOI 10.13039/100005225;
                Funded by: National Institute on Aging, DOI 10.13039/100000049;
                Award ID: 5U01AG054580
                Funded by: University of South Carolina, DOI 10.13039/100008899;
                Funded by: Bill and Melinda Gates Foundation, DOI 10.13039/100000865;
                Funded by: National Institute of Child Health and Human Development, DOI 10.13039/100000071;
                Award ID: U54 HD079123
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: 2028683
                Funded by: Capital Group;
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: F32AA025816
                Funded by: National Institute on Alcohol Abuse and Alcoholism, DOI 10.13039/100000027;
                Funded by: National Institute of Mental Health, DOI 10.13039/100000025;
                Award ID: 5T32MH109436-03
                Funded by: Canadian Institutes of Health Research, DOI 10.13039/501100000024;
                Categories
                Regular Article
                AcademicSubjects/MED00010
                AcademicSubjects/SCI02170
                Custom metadata
                PAP

                Neurology
                covid-19,mental health,sociodemographic disparities,psychiatric epidemiology
                Neurology
                covid-19, mental health, sociodemographic disparities, psychiatric epidemiology

                Comments

                Comment on this article