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      Coping with COVID-19: a prospective cohort study on young Australians' anxiety and depression symptoms from 2020–2021

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          Abstract

          Background

          Studies have shown that the coronavirus (COVID-19) pandemic negatively impacted the mental health of young Australians. However, there is limited longitudinal research exploring how individual factors and COVID-19 related public-health restrictions influenced mental health in young people over the acute phase of the COVID-19 pandemic. This study aimed to identify risk and protective factors associated with changes in individual symptoms of anxiety and depression among young Australians during the COVID-19 pandemic.

          Methods

          This prospective cohort study collected data on anxiety and depression symptoms of young Australians aged 15–29 years old using the Depression, Anxiety and Stress Scale short form (DASS-21). We delivered four online questionnaires from April 2020 to August 2021 at intervals of 3, 6, and 12 months after the initial survey. We implemented linear mixed-effects regression models to determine the association among demographic, socioeconomic, lifestyle and COVID–19 public health restrictions related factors and the severity of anxiety and depression symptoms over time.

          Results

          Analyses included 1936 young Australians eligible at baseline. There was a slight increase in DASS-21 anxiety mean scores from timepoint 3 to timepoint 4. DASS-21 depression scores showed slight fluctuations across timepoints with the highest mean score observed in timepoint 2. Factors associated with increases in anxiety and depression severity symptoms included LGBTQIA + identity, financial insecurity both before and during the pandemic, higher levels of loneliness, withdrawal or deferral of studies, spending more time on social media, and difficulties to sleep. Risk factors for only depression symptoms include unemployment during COVID-19 pandemic and being in lockdown. Living with someone was a protective factor for both anxiety and depression symptoms, pre-COVID-19 unemployment for depression symptoms, and older age and unemployment during the pandemic for anxiety symptoms.

          Conclusion

          These findings indicate that during the first year of the pandemic in Australia, there were significant changes in young people’s mental health which were associated with multiple demographic, socioeconomic, lifestyle, and lockdown factors. Hence, in future public health crises, we suggest more inclusive guidelines that involve young people in their development and implementation ensuring that their unique perspectives and needs are adequately considered.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13690-024-01397-z.

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          Most cited references66

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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 structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories

            The psychometric properties of the Depression Anxiety Stress Scales (DASS) were evaluated in a normal sample of N = 717 who were also administered the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI). The DASS was shown to possess satisfactory psychometric properties, and the factor structure was substantiated both by exploratory and confirmatory factor analysis. In comparison to the BDI and BAI, the DASS scales showed greater separation in factor loadings. The DASS Anxiety scale correlated 0.81 with the BAI, and the DASS Depression scale correlated 0.74 with the BDI. Factor analyses suggested that the BDI differs from the DASS Depression scale primarily in that the BDI includes items such as weight loss, insomnia, somatic preoccupation and irritability, which fail to discriminate between depression and other affective states. The factor structure of the combined BDI and BAI items was virtually identical to that reported by Beck for a sample of diagnosed depressed and anxious patients, supporting the view that these clinical states are more severe expressions of the same states that may be discerned in normals. Implications of the results for the conceptualisation of depression, anxiety and tension/stress are considered, and the utility of the DASS scales in discriminating between these constructs is discussed.
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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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                Author and article information

                Contributors
                Megan.lim@burnet.edu.au
                Journal
                Arch Public Health
                Arch Public Health
                Archives of Public Health
                BioMed Central (London )
                0778-7367
                2049-3258
                26 September 2024
                26 September 2024
                2024
                : 82
                : 166
                Affiliations
                [1 ]Disease Elimination Program, Burnet Institute, ( https://ror.org/05ktbsm52) Melbourne, Australia
                [2 ]Monash School of Public Health and Preventive Medicine, Monash University, ( https://ror.org/02bfwt286) Melbourne, Australia
                [3 ]Melbourne School of Population and Global Health, University of Melbourne, ( https://ror.org/01ej9dk98) Melbourne, Australia
                [4 ]Menzies School of Health Research, ( https://ror.org/006mbby82) Darwin, Australia
                [5 ]Centre for Alcohol Policy Research, Melbourne, Australia
                Article
                1397
                10.1186/s13690-024-01397-z
                11426065
                39327590
                689c8446-57fb-477c-8a2d-1efb1edccf43
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 November 2023
                : 10 September 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100007220, VicHealth;
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Public health
                coronavirus,mental health,young people,depression,anxiety,lockdown,pandemic
                Public health
                coronavirus, mental health, young people, depression, anxiety, lockdown, pandemic

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