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Background: Social prescribing is a mechanism of connecting patients with non-medical forms of support within the community and has been shown to improve mental health and wellbeing in adult populations. In the last few years, it has been used in child and youth settings with promising results. Currently, pathways are being developed for social prescribing in Child and Adolescent Mental Health Services (CAMHS) to support children and young people on treatment waiting lists. The Wellbeing While Waiting study will evaluate whether social prescribing benefits the mental health and wellbeing of children and young people. Methods: This study utilises an observational, hybrid type II implementation-effectiveness design. Up to ten CAMHS who are developing social prescribing pathways as part of a programme run across England with support from the Social Prescribing Youth Network will participate. Outcomes for children and young people receiving social prescribing whilst on CAMHS waiting lists will be compared to a control group recruited prior to the pathway roll-out. Questionnaire data will be collected at baseline, 3 months and 6 months. Primary outcomes for children and young people are mental health symptoms (including anxiety, depression, stress, emotional and behavioural difficulties). Secondary outcomes include: loneliness, resilience, happiness, whether life is worthwhile, life satisfaction, and service use. An implementation strand using questionnaires and interviews will explore the acceptability, feasibility, and suitability of the pathway, potential mechanisms of action and their moderating effects on the outcomes of interest, as well as the perceived impact of social prescribing. Questionnaire data will be analysed mainly using difference-in-differences or controlled interrupted time series analysis. Interview data will be analysed using reflexive thematic analysis. Discussion: The Wellbeing While Waiting study will provide the first rigorous evidence of the impact of social prescribing for children and young people on waiting lists for mental health treatment. Findings will help inform the prioritisation, commissioning, and running of social prescribing in other CAMHS. To maximise impact, findings will be available on the study website (https://sbbresearch.org) and disseminated via national and international networks. Trial Registration: N/A. [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]

Background: There is a growing global awareness of the psychological consequences of long COVID, supported by emerging empirical evidence. However, the emergence and long-term trajectories of psychological symptoms following the infection are still unclear.Aims: To examine when psychological symptoms first emerge following infection with SARS-CoV-2 and the long-term trajectories of psychological symptoms comparing long- and short-COVID groups.Method: We analysed longitudinal data from the UCL COVID-19 Social Study (March 2020 to November 2021). We included data from adults living in England who reported contracting SARS-CoV-2 by November 2021 (n = 3115). Of these, 15.9% reported having had long COVID (n = 495). They were matched to participants who had short COVID using propensity score matching on a variety of demographic, socioeconomic and health covariates (n = 962 individuals with 13 325 observations) and data were further analysed using growth curve modelling.Results: Depressive and anxiety symptoms increased immediately following the onset of infection in both long- and short-COVID groups. But the long-COVID group had substantially greater initial increases in depressive symptoms and heightened levels over 22 months follow-up. Initial increases in anxiety were not significantly different between groups, but only the short-COVID group experienced an improvement in anxiety over follow-up, leading to widening differences between groups.Conclusions: The findings support work on the psychobiological pathways involved in the development of psychological symptoms relating to long COVID. The results highlight the need for monitoring of mental health and provision of adequate support to be interwoven with diagnosis and treatment of the physical consequences of long COVID. [ABSTRACT FROM AUTHOR]

Background: There are concerns that keyworkers may be at a greater risk for psychological distress than non-keyworkers during the COVID-19 pandemic. However, little research has included keyworkers outside of the healthcare sector or has disaggregated keyworkers into different subgroups. Aims: To examine longitudinal changes in mental health over 12 months during the COVID-19 pandemic comparing four different groups of keyworkers with non-keyworkers. Method: Longitudinal data were from 21 874 adults living in England (21 March 2020 to 22 February 2021). Latent growth modelling was utilised to compare growth trajectories of depressive and anxiety symptoms in non-keyworkers and four types of keyworkers: (a) health and social care workers, (b) teachers and child care workers, (c) public service workers, and (d) essential services keyworkers (such as food chain or utility workers). Results: When accounting for both time-invariant and time-varying covariates, keyworkers in the essential services category had consistently higher levels of depressive and anxiety symptoms than non-keyworkers across the whole of the study period. There was little difference in the mental health trajectories between health/social care, teachers/child care and public service worker categories and non-keyworkers. Conclusions: Our findings suggest that the risk for poorer mental health during the COVID-19 pandemic varies within the broad category of keyworkers generally, and that those working in utility, food chain and transport roles are especially at risk. Future research should focus on identifying which aspects of working conditions may be contributing to occupational stress in these groups. [ABSTRACT FROM AUTHOR]

Background: There is increasing awareness of the importance of patient activation (knowledge, skills, and confidence for managing one's health and health care) among clinicians and policy makers, with emerging evidence showing higher levels of patient activation are associated with better health outcomes and experiences of health care. This study aimed to examine the association between patient activation and a wide range of specific types of healthcare service utilisation in England, including GP and non-GP primary care, elective and emergency hospital admissions, outpatient visits, and attendances at the Accident and Emergency department.Methods: Data were derived from linked electronic patient records collected by primary and secondary healthcare providers in North West London between January 2016 and November 2019. Our analyses focused on adults (18+) with a valid Patient Activation Measure (PAM). After excluding patients with missing data, we had an analytical sample of 15,877 patients. Data were analysed using negative binomial regression and logistic regression models depending on the outcome variable.Results: Patients had a mean activation score of 55.1 and a standard deviation (SD) of 17.7 (range: 0-100). They had an average of 5.4 GP visits (SD = 8.0), 26.8 non-GP visits (SD = 23.4) and 6.0 outpatient attendances (SD = 7.9) within a one-year follow-up. About 24.7% patients had at least one elective admission, 24.2% had one or more emergency admissions, and 42.3% had one or more A&E attendance within the follow-up. After accounting for a number of demographic and health factors, we found a linear (or proximately linear) association between patient activation and the number of GP visits, emergency admissions and A&E attendance, but a non-linear relationship between patient activation and the number of non-GP visits, the number of outpatient attendance and elective inpatient admission.Conclusions: This study has provided strong empirical evidence from England linking patient activation with healthcare service utilisation. It suggests the value of supporting patient activation as a potential pathway to ease the burden of healthcare system. [ABSTRACT FROM AUTHOR]

Recent studies have shown reduced physical activity at early stages of the COVID-19 pandemic. However, there is a lack of investigation on longitudinal changes in physical activity beyond lockdowns and stay-at-home orders. Moreover, it is unclear if there is heterogeneity in physical activity growth trajectories. This study aimed to explore longitudinal patterns of physical activity and factors associated with them. Data were from the UCL COVID-19 Social Study. The analytical sample consisted of 35,915 adults in England who were followed up for 22 weeks from 24th March to 23rd August 2020. Data were analysed using growth mixture models. Our analyses identified six classes of growth trajectories, including three stable classes showing little change over time (62.4% in total), two classes showing decreasing physical activity (28.6%), and one class showing increasing physical activity over time (9%). A range of factors were found to be associated the class membership of physical activity trajectories, such as age, gender, education, income, employment status, and health. There is substantial heterogeneity in longitudinal changes in physical activity during the COVID-19 pandemic. However, a substantial proportion of our sample showed persistent physical inactivity or decreasing physical activity. Given the well-established link between physical activity and health, persistent or increased physical inactivity is likely to have both immediate and long-term implications for people's physical and mental health, as well as general wellbeing. More efforts are needed to promote physical activity during the pandemic and beyond. [ABSTRACT FROM AUTHOR]

Loneliness and social isolation have been identified as important predictors of various health outcomes, but little research has investigated their influence on falls. This study aimed to investigate the longitudinal association between loneliness, social isolation and falls amongst older adults in England, looking at both self-reported falls and falls that require hospital admissions. This study drew on large scale, nationally representative data from the English Longitudinal Study of Ageing linked with Hospital Episode Statistics. Data were analysed using survival analysis, with self-reported falls (total sample = 4013) and falls require hospital admission being modelled separately (total sample = 9285). There was a 5% increase in the hazard of self-reported falls relative to one point increase in loneliness independent of socio-demographic factors (HR: 1.05, 95% CI: 1.02–1.08), but the association was explained away by individual differences in health and life-style measures (HR: 1.03, 95% CI: 1.00–1.07). Both living alone (HR: 1.18, 95% CI: 1.07–1.32) and low social contact (HR: 1.04, 95% CI: 1.01–1.07) were associated with a greater hazard of self-reported falls even after controlling for socio-demographic, health and life-style differences. Similar results were also found for hospital admissions following a fall. Our findings were robust to a variety of model specifications. [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]

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.

Between March 2020 and March 2021, the United Kingdom (UK) experienced three lockdowns due to the COVID-19 pandemic. Given the evident association between arts engagement and wellbeing, this study was designed to compare the predictors and patterns of home-based arts engagement during these lockdowns. Data analysed in this study were from the UK COVID-19 Social Study run by University College London. Multinomial logistic regression was used to identify predictors of arts engagement and compare (i) respondents' engagement levels during the first lockdown in April/May 2020 and their levels in pre-pandemic times (N = 23,086), (ii) their engagement levels during the second lockdown in November/December 2020 with their levels during the first lockdown (N = 11,481), and (iii) their engagement levels during the third lockdown in January/February 2021 with their levels during the first lockdown (N = 13,270). During first lockdown, 1 in 4 increased their arts engagement and 1 in 6 decreased it. Of those who increased, 2 in 5 maintained or further increased their engagement in subsequent lockdowns, but just 7% of those who had decreased their engagement increased it. Younger adults (aged 18-29) showed initial increases in first lockdown, whilst people who were not employed and those with a physical health condition showed decreases and people with a mental health condition showed changes during the first lockdown (both increases and decreases). Females and people with higher education showed continuous changes across the three lockdowns, with women being more likely to increase their engagement and those with higher education being less likely to decrease. People of ethnic minorities and those with higher income declined their engagement in the third lockdown. This study provides insight into levels of arts engagement across the three national lockdowns in the UK and suggests that the pandemic may have affected long-term cultural behaviours for some groups., Competing Interests: The authors have declared that no competing interests exist.

Background: There is major concern about the impact of the global COVID-19 outbreak on mental health. Several studies suggest that mental health deteriorated in many countries before and during enforced isolation (ie, lockdown), but it remains unknown how mental health has changed week by week over the course of the COVID-19 pandemic. This study aimed to explore the trajectories of anxiety and depression over the 20 weeks after lockdown was announced in England, and compare the growth trajectories by individual characteristics., Methods: In this prospective longitudinal observational study, we analysed data from the UCL COVID-19 Social Study, a panel study weighted to population proportions, which collects information on anxiety (using the Generalised Anxiety Disorder assessment) and depressive symptoms (using the Patient Health Questionnaire) weekly in the UK since March 21, 2020. We included data from adults living in England who had at least three repeated measures between March 23 and Aug 9, 2020. Analyses were done using latent growth models, which were fitted to account for sociodemographic and health covariates., Findings: Between March 23, and Aug 9, data from over 70 000 adults were collected in the UCL COVID-19 Social Study. When including participants living in England with three follow-up measures and no missing values, our analytic sample consisted of 36 520 participants. The average depression score was 6·6 (SD=6·0, range 0-27) and the average anxiety score 5·7 (SD=5·6, range 0-21) in week 1. Anxiety and depression levels both declined across the first 20 weeks following the introduction of lockdown in England (b=-1·93, SE=0·26, p<0·0001 for anxiety; b=-2·52, SE=0·28, p<0·0001 for depressive symptoms). The fastest decreases were seen across the strict lockdown period (between weeks 2 and 5), with symptoms plateauing as further lockdown easing measures were introduced (between weeks 16 and 20). Being a woman or younger, having lower educational attainment, lower income, or pre-existing mental health conditions, and living alone or with children were all risk factors for higher levels of anxiety and depression at the start of lockdown. Many of these inequalities in experiences were reduced as lockdown continued, but differences were still evident 20 weeks after the start of lockdown., Interpretation: These data suggest that the highest levels of depression and anxiety occurred in the early stages of lockdown but declined fairly rapidly, possibly because individuals adapted to circumstances. Our findings emphasise the importance of supporting individuals in the lead-up to future lockdowns to try to reduce distress, and highlight that groups already at risk for poor mental health before the pandemic have remained at risk throughout lockdown and its aftermath., Funding: Nuffield Foundation, UK Research and Innovation, Wellcome Trust., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC-BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objective: This study aimed to examine the association between loneliness, social isolation and cardiovascular disease (CVD), looking at both self-reported CVD diagnosis and CVD-related hospital admissions., Methods: Data were derived from the English Longitudinal Study of Ageing linked with administrative hospital records and mortality registry data. The analytical sample size was 5850 for the analysis of self-reported CVD and 4587 of CVD derived from hospital records, with a follow-up up to 9.6 years. Data were analysed using survival analysis, accounting for competing risks events., Results: The mean age was 64 years (SD 8.3). About 44%-45% were men. Within the follow-up, 17% participants reported having newly diagnosed CVD and 16% had a CVD-related hospital admission. We found that loneliness was associated with an increased risk of CVD events independent of potential confounders and risk factors. The hazard of people with the highest level of loneliness was about 30% higher for onset CVD diagnosis (HR: 1.05, 95% CI: 1.01 to 1.09) and 48% higher for CVD-related hospital admissions (HR: 1.08, 95% CI: 1.03 to 1.14), compared with the least lonely. There was little evidence that social isolation was independently associated with the risk of either CVD diagnosis or admission., Conclusions: Our findings provided strong evidence for the relationship between loneliness and cardiovascular events. Loneliness should be considered as a psychosocial risk factor for CVD in both research and interventions for cardiovascular prevention., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)