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      Community Mobility and Depressive Symptoms During the COVID-19 Pandemic in the United States

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          Key Points

          Question

          Were US adults living in communities with decreased mobility during the COVID-19 pandemic more likely to report a depressed mood?

          Findings

          In this survey study with 192 271 respondents, individuals who lived in communities where fewer individuals left home on a daily basis during the pandemic reported greater levels of depression on average. These differences were not directly attributable to COVID-19 pandemic restrictions, nor to county-level differences in COVID-19 cases or deaths, weather, or county-level economic features; the association persisted after widespread COVID-19 vaccine availability.

          Meaning

          These findings suggest that the association of depression and policies that restrict social interaction and movement requires further study to understand potential causal relationships and how to mitigate them.

          Abstract

          This survey study examines the association of depression and limited mobility during the COVID-19 pandemic in the United States using an internet-based survey of adults in all 50 US states and Washington DC.

          Abstract

          Importance

          Marked elevation in levels of depressive symptoms compared with historical norms have been described during the COVID-19 pandemic, and understanding the extent to which these are associated with diminished in-person social interaction could inform public health planning for future pandemics or other disasters.

          Objective

          To describe the association between living in a US county with diminished mobility during the COVID-19 pandemic and self-reported depressive symptoms, while accounting for potential local and state-level confounding factors.

          Design, Setting, and Participants

          This survey study used 18 waves of a nonprobability internet survey conducted in the United States between May 2020 and April 2022. Participants included respondents who were 18 years and older and lived in 1 of the 50 US states or Washington DC.

          Main Outcome and Measure

          Depressive symptoms measured by the Patient Health Questionnaire-9 (PHQ-9); county-level community mobility estimates from mobile apps; COVID-19 policies at the US state level from the Oxford stringency index.

          Results

          The 192 271 survey respondents had a mean (SD) of age 43.1 (16.5) years, and 768 (0.4%) were American Indian or Alaska Native individuals, 11 448 (6.0%) were Asian individuals, 20 277 (10.5%) were Black individuals, 15 036 (7.8%) were Hispanic individuals, 1975 (1.0%) were Pacific Islander individuals, 138 702 (72.1%) were White individuals, and 4065 (2.1%) were individuals of another race. Additionally, 126 381 respondents (65.7%) identified as female and 65 890 (34.3%) as male. Mean (SD) depression severity by PHQ-9 was 7.2 (6.8). In a mixed-effects linear regression model, the mean county-level proportion of individuals not leaving home was associated with a greater level of depression symptoms (β, 2.58; 95% CI, 1.57-3.58) after adjustment for individual sociodemographic features. Results were similar after the inclusion in regression models of local COVID-19 activity, weather, and county-level economic features, and persisted after widespread availability of COVID-19 vaccination. They were attenuated by the inclusion of state-level pandemic restrictions. Two restrictions, mandatory mask-wearing in public (β, 0.23; 95% CI, 0.15-0.30) and policies cancelling public events (β, 0.37; 95% CI, 0.22-0.51), demonstrated modest independent associations with depressive symptom severity.

          Conclusions and Relevance

          In this study, depressive symptoms were greater in locales and times with diminished community mobility. Strategies to understand the potential public health consequences of pandemic responses are needed.

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          Most cited references30

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          A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)

          COVID-19 has prompted unprecedented government action around the world. We introduce the Oxford COVID-19 Government Response Tracker (OxCGRT), a dataset that addresses the need for continuously updated, readily usable and comparable information on policy measures. From 1 January 2020, the data capture government policies related to closure and containment, health and economic policy for more than 180 countries, plus several countries' subnational jurisdictions. Policy responses are recorded on ordinal or continuous scales for 19 policy areas, capturing variation in degree of response. We present two motivating applications of the data, highlighting patterns in the timing of policy adoption and subsequent policy easing and reimposition, and illustrating how the data can be combined with behavioural and epidemiological indicators. This database enables researchers and policymakers to explore the empirical effects of policy responses on the spread of COVID-19 cases and deaths, as well as on economic and social welfare.
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            The PHQ-9: A New Depression Diagnostic and Severity Measure

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              Prevalence of Depression Symptoms in US Adults Before and During the COVID-19 Pandemic

              Key Points Question What is the burden of depression symptoms among US adults during the coronavirus disease 2019 (COVID-19) pandemic compared with before COVID-19, and what are the risk factors associated with depression symptoms? Findings In this survey study that included 1441 respondents from during the COVID-19 pandemic and 5065 respondents from before the pandemic, depression symptom prevalence was more than 3-fold higher during the COVID-19 pandemic than before. Lower income, having less than $5000 in savings, and having exposure to more stressors were associated with greater risk of depression symptoms during COVID-19. Meaning These findings suggest that there is a high burden of depression symptoms in the US associated with the COVID-19 pandemic and that this burden falls disproportionately on individuals who are already at increased risk.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                27 September 2023
                September 2023
                27 September 2023
                : 6
                : 9
                : e2334945
                Affiliations
                [1 ]Massachusetts General Hospital, Boston
                [2 ]Harvard Medical School, Boston, Massachusetts
                [3 ]Northeastern University, Boston, Massachusetts
                [4 ]Rutgers University, New Brunswick, New Jersey
                [5 ]Northwestern University, Evanston, Illinois
                [6 ]Harvard University, Cambridge, Massachusetts
                [7 ]University of Pennsylvania, Philadelphia
                Author notes
                Article Information
                Accepted for Publication: August 9, 2023.
                Published: September 27, 2023. doi:10.1001/jamanetworkopen.2023.34945
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2023 Perlis RH et al. JAMA Network Open.
                Corresponding Author: Roy H. Perlis, MD, MSc, Massachusetts General Hospital, 185 Cambridge St, 6th Floor, Boston, MA 02114 ( rperlis@ 123456mgh.harvard.edu ).
                Author Contributions: Dr. R. H. Perlis had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: R. H. Perlis, Simonson.
                Acquisition, analysis, or interpretation of data: R. H. Perlis, Lunz Trujillo, Safarpour, Quintana, J. Perlis, Santillana, Ognyanova, Baum, Druckman, Lazer.
                Drafting of the manuscript: R. Perlis, Simonson.
                Critical review of the manuscript for important intellectual content: R. H. Perlis, Lunz Trujillo, Safarpour, Quintana, J. Perlis, Santillana, Ognyanova, Baum, Druckman, Lazer.
                Statistical analysis: R. H. Perlis, J. Perlis, Santillana, Baum.
                Obtained funding: R. H. Perlis, Ognyanova, Baum, Druckman, Lazer.
                Administrative, technical, or material support: R. H. Perlis, Lunz Trujillo, Quintana, Simonson, Lazer.
                Supervision: R. H. Perlis, Druckman, Lazer.
                Conflict of Interest Disclosures: Dr R. H. Perlis reported receiving personal fees from Psy Therapeutics, Genomind, Burrage Capital, Alkermes, Circular Genomics, RID Ventures, Belle Artificial Intelligence, Vault Health, and Takeda outside the submitted work. No other disclosures were reported.
                Funding/Support: Drs. Baum, Ognyanova, Druckman, and Lazer were supported by grants SES-2029292 and SES-2029792 from the National Science Foundation. Dr R. H. Perlis was supported by grant R01MH116270 from the National Institute of Mental Health. Drs R. H. Perlis and Lazer were supported by grant RF1MH132335 from the National Institute of Mental Health. The study was also supported by Northeastern University, Harvard Kennedy School of Government, and Rutgers University.
                Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Disclaimer: Dr R. H. Perlis is an associate editor of JAMA Network Open but was not involved in any of the decisions regarding review of the manuscript or its acceptance.
                Data Sharing Statement: See Supplement 2.
                Article
                zoi231005
                10.1001/jamanetworkopen.2023.34945
                10534266
                37755830
                0bb72629-cbf1-43b8-ba0a-b6915ff4675c
                Copyright 2023 Perlis RH et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 26 July 2023
                : 9 August 2023
                Categories
                Research
                Original Investigation
                Online Only
                Psychiatry

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