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Background: The coronavirus disease 2019 (COVID-19) pandemic has brought about significant behavioural changes, one of which is increased time spent at home. This could have important public health implications. This study aimed to explore longitudinal patterns of 'home confinement' (defined as not leaving the house/garden) during the COVID-19 pandemic, and the associated predictors and mental health outcomes. Methods: Data were from the UCL COVID-19 Social Study. The analytical sample consisted of 25 390 adults in England who were followed up for 17 months (March 2020–July 2021). Data were analysed using growth mixture models. Results: Our analyses identified three classes of growth trajectories, including one class showing a high level of persistent home confinement (the home-confined, 24.8%), one changing class with clear alignment with national containment measures (the adaptive, 32.0%), and one class with a persistently low level of confinement (the unconfined, 43.1%). A range of factors were associated with the class membership of home-confinement trajectories, such as age, gender, income, employment status, social relationships and health. The home-confined class had the highest number of depressive (diff = 1.34–1.68, p < 0.001) and anxiety symptoms (diff = 0.84–1.05, p < 0.001) at the end of the follow-up than the other two classes. Conclusions: There was substantial heterogeneity in longitudinal patterns of home confinement during the COVID-19 pandemic. People with a persistent high level of confinement had the worst mental health outcomes, calling for special attention in mental health action plans, in particular targeted interventions for at-risk groups. [ABSTRACT FROM AUTHOR]

Background: There has been much research into the mental health impact of the Coronavirus Disease 2019 (COVID-19) pandemic and how it is related to time-invariant individual characteristics. However, there is still a lack of research showing long-term trajectories of mental health across different stages of the pandemic. And little is known regarding the longitudinal association of time-varying factors with mental health outcomes. This study aimed to provide a longitudinal profile of how mental health in adults changed across different stages of the COVID-19 pandemic and to examine their longitudinal associations with time-varying contextual (e.g., COVID-19 policy response and pandemic intensity) and individual level factors. Methods and findings: This study used data from a large panel study of over 57,000 adults living in England, who were followed up regularly for 2 years between March 2020 and April 2022. Mental health outcomes were depressive and anxiety symptoms. Depressive symptoms were assessed by the Patient Health Questionnaire (PHQ-9) and anxiety symptoms by the Generalized Anxiety Disorder assessment (GAD-7). Entropy balancing weights were applied to restore sample representativeness. After weighting, approximately 50% of participants were female, 14% from ethnic minority backgrounds, with a mean age of 48 years. Descriptive analyses showed that mental health changes were largely in line with changes in COVID-19 policy response and pandemic intensity. Further, data were analysed using fixed-effects (FE) models, which controlled for all time-invariant confounders (observed or not). FE models were fitted separately across 3 stages of the COVID-19 pandemic, including the first national lockdown (21/03/2020–23/08/2020), second and third national lockdowns (21/09/2020–11/04/2021), and "freedom" period (12/04/2021–14/11/2021). We found that more stringent policy response (measured by stringency index) was associated with increased depressive symptoms, in particular, during lockdown periods (β = 0.23, 95% confidence interval (CI) = [0.18 to 0.28], p < 0.001; β = 0.30, 95% CI = [0.21 to 0.39], p < 0.001; β = 0.04, 95% CI = [−0.03 to 0.12], p = 0.262). Higher COVID-19 deaths were also associated with increased depressive symptoms, but this association weakened over time (β = 0.29, 95% CI = [0.25 to 0.32], p < 0.001; β = 0.09, 95% CI = [0.05 to 0.13], p < 0.001; β = −0.06, 95% CI = [−0.30 to 0.19], p = 0.655). Similar results were also found for anxiety symptoms, for example, stringency index (β = 0.17, 95% CI = [0.12 to 0.21], p < 0.001; β = 0.13, 95% CI = [0.06 to 0.21], p = 0.001; β = 0.10, 95% CI = [0.03 to 0.17], p = 0.005), COVID-19 deaths (β = 0.07, 95% CI = [0.04 to 0.10], p < 0.001; β = 0.04, 95% CI = [0.00 to 0.07], p = 0.03; β = 0.16, 95% CI = [−0.08 to 0.39], p = 0.192). Finally, there was also evidence for the longitudinal association of mental health with individual level factors, including confidence in government/healthcare/essentials, COVID-19 knowledge, COVID-19 stress, COVID-19 infection, and social support. However, it is worth noting that the magnitudes of these longitudinal associations were generally small. The main limitation of the study was its non-probability sample design. Conclusions: Our results provided empirical evidence on how changes in contextual and individual level factors were related to changes in depressive and anxiety symptoms. While some factors (e.g., confidence in healthcare, social support) clearly acted as consistent predictors of depressive and/or anxiety symptoms, other factors (e.g., stringency index, COVID-19 knowledge) were dependent on the specific situations occurring within society. This could provide important implications for policy making and for a better understanding of mental health of the general public during a national or global health crisis. Author summary: Why was this study done?: There is increasing research showing worsening mental health during the Coronavirus Disease 2019 (COVID-19) pandemic. There is some evidence for mental health changes across different stages of the pandemic, but there is a lack of long-term longitudinal research with regular follow-ups. Few studies have examined how changes in contextual and individual factors are related to mental health outcomes. What did the researchers do and find?: Drawing data from over 57,000 participants, we showed descriptively how depressive and anxiety symptoms changed over time between March 2020 and April 2022. Using fixed-effects (FE) analyses, we found evidence for longitudinal associations of depressive and anxiety symptom with both contextual (e.g., stringency index, COVID-19 cases) and individual factors (e.g., COVID-19 knowledge, social support). Some of these longitudinal associations (e.g., stringency index, COVID-19 knowledge) differed across different stages of the COVID-19 pandemic, and differential relationships were also found between depressive and anxiety symptoms. What do these findings mean?: These findings from observational data provide empirical evidence for the longitudinal association between contextual factors and people's mental health, offering important implications for policy making. Our study highlights the importance of individual level factors such as confidence in healthcare services and perceived social support in supporting better mental health. Further research is needed to monitor mental health changes over longer periods and to use alternative mental health assessment tools. [ABSTRACT FROM AUTHOR]

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has put a great strain on people's mental health. A growing number of studies have shown worsening mental health measures globally during the pandemic. However, there is a lack of empirical study on how people support their mental health during the COVID-19 pandemic. This study aimed to examine a number of formal and informal mental health support. Further, it explored factors that might be associated with the use of different types mental health support. Methods: Data from 26,720 adults in the UCL COVID-19 Social Study were analysed between 13th April 2020 and 3rd July 2020. Data were analysed using logistic and Poisson regression models. Results: About 45% of people reported talking to friends or family members to support their mental health, 43% engaging in self-care activities, 20% taking medication, 9% speaking to mental health professionals, 8% talking to a GP or other health professional, and another 8% using helpline or online services. Gender, education, living status, loneliness, pre-existing mental health conditions, general depression and anxiety, coping and personality were found to be associated with the use of mental health support. Conclusion: While the negative impacts caused by the COVID-19 pandemic are inevitable, people can play an active role in managing their mental health. Understanding the patterns and predictors of various kinds of mental health support during the pandemic is crucial for future service planning and delivery through recognising potential barriers to mental health care faced by certain groups. [ABSTRACT FROM AUTHOR]

This study examined the association between greenspace and the growth trajectories of anxiety symptoms during the COVID-19 pandemic. Using data from 19,848 urban residents in England who were followed for 20 months between March 2020 and October 2021, we found that living in an area with higher greenspace coverage (exposure) was associated with fewer anxiety symptoms independent of population density, area deprivation levels, socio-demographics, and health profiles. There was limited evidence that greenspace was related to the change of anxiety symptoms over time. No association with anxiety trajectories was found when considering distance to nearest greenspace (proximity), highlighting potentially differential mental health effects of simply having access to local parks and recreation areas versus living in areas of greater natural environment land cover. These findings have important implications for mental health intervention and policymaking. [ABSTRACT FROM AUTHOR]

The negative impact of the COVID-19 pandemic on mental health is well evidenced. However, there is little research on how individuals' coping strategies were related to changes in mental health over time. The current study used data from the COVID-19 Social Study in the United Kingdom (N = 26,505) to explore whether coping strategies (problem-focused, emotion-focused, avoidant, and socially-supportive) were associated with (i) better mental health as lockdown was introduced, and (ii) faster recovery over time. People with greater use of problem-focused, avoidant, and supportive coping displayed more mental health symptoms, while greater use of emotion-focused coping was associated with fewer mental health symptoms. Symptoms decreased over time for all coping strategies, but only socially-supportive coping was associated with a faster decrease in anxiety and depressive symptoms, indicating a potential protective effect of social support on psychological distress. Problem-, avoidant- and emotion-focused coping strategies were not associated with faster improvements in mental health. Suggesting the adoption of one of these coping styles in itself is not necessarily a driver of improvements in mental health; rather, specific attributes of the behaviours expressed as part of this coping style appear to be important in and of themselves. • Used data from the COVID-19 Social Study in the United Kingdom (N = 26,505). • Mental health symptoms decreased over time for all coping styles. • Supportive-coping associated with faster decrease in depression and anxiety symptoms. • Women using avoidant coping displayed faster decrease in mental health symptoms. [ABSTRACT FROM AUTHOR]

There are increasing worries that lockdowns and 'stay-at-home' orders due to the COVID-19 pandemic could lead to a rise in loneliness, which is recognised as a major public health concern. But profiles of loneliness during the pandemic and risk factors remain unclear. The current study aimed to examine if and how loneliness levels changed during the strict lockdown and to explore the clustering of loneliness growth trajectories. Data from 38,217 UK adults in the UCL COVID -19 Social Study (a panel study collecting data weekly during the pandemic) were analysed during the strict lockdown period in the UK (23/03/2020–10/05/2020). The sample was well-stratified and weighted to population proportions of gender, age, ethnicity, education and geographical location. Growth mixture modelling was used to identify the latent classes of loneliness growth trajectories and their predictors. Analyses revealed four classes, with the baseline loneliness level ranging from low to high. In the first a few weeks of lockdown, loneliness levels increased in the highest loneliness group, decreased in the lowest loneliness group, and stayed relatively constant in the middle two groups. Younger adults (OR = 2.17–6.81), women (OR = 1.59), people with low income (OR = 1.3), the economically inactive (OR = 1.3–2.04) and people with mental health conditions (OR = 5.32) were more likely to be in highest loneliness class relative to the lowest. Further, living with others or in a rural area, and having more close friends or greater social support were protective. Perceived levels of loneliness under strict lockdown measures due to COVID-19 were relatively stable in the UK, but for many people these levels were high with no signs of improvement. Results suggest that more efforts are needed to address loneliness. • Our analyses revealed four distinctive latent classes of loneliness trajectories. • During the seven weeks of strict lockdown, loneliness levels were relatively stable. • There is a slight increase in the highest loneliness class and decrease in the lowest class. • A range of demographic, health, and social factors were related to latent classes. [ABSTRACT FROM AUTHOR]