Correction to: The prospective relationship between loneliness, life satisfaction and psychological distress before and during the COVID-19 pandemic in the UK.

[This corrects the article DOI: 10.1007/s10389-022-01719-x.].

The prospective relationship between loneliness, life satisfaction and psychological distress before and during the COVID-19 pandemic in the UK.

Aim: Mental wellbeing in the UK seems to have deteriorated significantly during the COVID-19 pandemic, with the rates of loneliness, life satisfaction and psychological distress taking longer to return to the pre-pandemic levels than elsewhere. Nevertheless, there is little knowledge about the interactions between these outcomes, or the factors that played a role in the rates of change. The current study aims to address this gap by simultaneously investigating changes in loneliness, life satisfaction and psychological distress in the UK from pre-pandemic levels to those between April and November 2020, while critically assessing the role of a range of social ecological influencing factors. Subject and Methods: Longitudinal data from Understanding Society (N=3475) were used to explore the changes in loneliness, life satisfaction and psychological distress from pre-pandemic levels (2017-2019) through November 2020, the interactions between these outcomes, and the role of individual, social, community and geographic factors in the rates of change, using multivariate latent growth curve model. Results: Loneliness, life satisfaction and psychological distress deteriorated minimally between April and November 2020, compared to the pre-pandemic levels (2017-2019), while the rate of change in each outcome influenced the rates of change in the other two. Key individual (age, gender, physical health), social (number of friends and similarity to them), and environmental (neighbourhood quality) variables influenced baseline scores and the rates of change. Conclusion: Considering significant dynamic associations between loneliness, life satisfaction and psychological distress, we argue that interventions to tackle any one of the outcomes may have beneficial effects on others, while highlighting malleable factors and individual and community-level interventions to tackle loneliness.

A qualitative exploration of weight management during COVID-19.

COVID-19 has been associated with worse outcomes in people living with obesity and has altered how people can engage with weight management. However, the impact of risk perceptions and changes to daily life on weight loss has not been explored. This study aimed to examine how COVID-19 and perception of risk interacted with weight loss attempts in adults participating in a behavioural weight management programme. Forty-eight participants completed a semi-structured interview exploring the impact of COVID-19 on their weight management experience. Interviews were completed via telephone and analysed using a thematic approach. Reaction to perceived risk varied, but most participants reported the knowledge of increased risk promoted anxiety and avoidance behaviours. Despite this, many reported it as a motivating factor for weight loss. Restrictions both helped (e.g., reduced temptation) and hindered their weight loss (e.g., less support). However, there was consensus that the changes to everyday life meant participants had more time to engage with and take control of their weight loss. To the authors' knowledge, this is the first study to explore the impact of COVID-19 on participation in a weight management programme started during the pandemic in the United Kingdom. Restrictions had varying impacts on participant's weight loss. How risk is perceived and reported to participants is an important factor influencing engagement with weight management. The framing of health information needs to be considered carefully to encourage engagement with weight management to mitigate risk. Additionally, the impact of restrictions and personal well-being are key considerations for weight management programmes.

Loneliness and personal wellbeing in young people: the moderating effects of social wellbeing and socio-demographic factors

BackgroundLoneliness a growing public health concern. This is particularly so in light of the Covid-19 pandemic which has highlighted the detrimental psychosocial consequences of loneliness. Loneliness is a particularly pervasive problem among young adults, but despite this, most research examining loneliness is among older adults. Loneliness is a known risk factor for poor health and personal wellbeing. However, the extent to which other aspects of social wellbeing (e.g., isolation, social support) may mitigate the relationship between loneliness and personal wellbeing is unclear. Loneliness is often used interchangeably with related, yet distinct aspects of social wellbeing, such as isolation. Therefore, it is difficult to differentiate factors that relate to loneliness, factors that relate to other components of social wellbeing, and the possible interactions between these constructs. Consequently, we aim to examine the interplay of loneliness and isolation on personal wellbeing.MethodsWe make use of cross-sectional sample of 965 young people aged 16–24 from the 2018 wave of the Community Life Survey to conduct regression-based analyses. This allows us to evaluate for a direct effect of loneliness on personal wellbeing, and for an interaction effect between loneliness and isolation to determine if the presence of both loneliness and isolation is predictive of poorer wellbeing. Finally, we use moderated regression to assess whether individual, social, and community level factors influence the relationship between loneliness and personal wellbeing.ResultsPreliminary results identify that loneliness is consistently associated with poorer personal wellbeing among young people. Isolation neither predicts wellbeing, nor moderates associations between loneliness and wellbeing. Factors such as trust in one’s neighbourhood, not acting as a carer, and being a fulltime student were associated with greater wellbeing. At the individual level, a moderating effect of sex was found, and social factors (e.g., being able to count on friends) moderated the association between loneliness and wellbeing.ConclusionResults suggests that the presence of both loneliness and isolation does not increase risk of poor personal wellbeing among young people. Rather, the subjective experience of loneliness is independently detrimental to wellbeing. Our results also identified that being of female gender was associated with increased risk of loneliness impacting on personal wellbeing, but that strong emotional support may act as a protective factor against loneliness, and therefore improve personal wellbeing. It is also important to foster community trust and engagement to improve wellbeing, and that young people with caring responsibilities may be particularly at risk of low personal wellbeing.

COVID-19 pandemic and its impact on social relationships and health.

This essay examines key aspects of social relationships that were disrupted by the COVID-19 pandemic. It focuses explicitly on relational mechanisms of health and brings together theory and emerging evidence on the effects of the COVID-19 pandemic to make recommendations for future public health policy and recovery. We first provide an overview of the pandemic in the UK context, outlining the nature of the public health response. We then introduce four distinct domains of social relationships: social networks, social support, social interaction and intimacy, highlighting the mechanisms through which the pandemic and associated public health response drastically altered social interactions in each domain. Throughout the essay, the lens of health inequalities, and perspective of relationships as interconnecting elements in a broader system, is used to explore the varying impact of these disruptions. The essay concludes by providing recommendations for longer term recovery ensuring that the social relational cost of COVID-19 is adequately considered in efforts to rebuild.

Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning.

Expression of CCR5 and its cognate ligands have been implicated in COVID-19 pathogenesis, consequently therapeutics directed against CCR5 are being investigated. Here, we explored the role of CCR5 and its ligands across the immunologic spectrum of COVID-19. We used a bioinformatics approach to predict and model the immunologic phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 224 individuals including healthy controls and patients spanning the COVID-19 disease continuum. We assessed the plasma and isolated peripheral blood mononuclear cells (PBMCs) from 29 healthy controls, 26 Mild-Moderate COVID-19 individuals, 48 Severe COVID-19 individuals, and 121 individuals with post-acute sequelae of COVID-19 (PASC) symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients from each group. B-cells were significantly elevated compared to healthy control individuals (P<0.001) as was the CD14+, CD16+, CCR5+ monocytic subset (P<0.001). CD4 and CD8 positive T-cells expressing PD-1 as well as T-regulatory cells were significantly lower than healthy controls (P<0.001 and P=0.01 respectively). CCL5/RANTES, IL-2, IL-4, CCL3, IL-6, IL-10, IFN-γ, and VEGF were all significantly elevated compared to healthy controls (all P<0.001). Conversely GM-CSF and CCL4 were in significantly lower levels than healthy controls (P=0.01). Data were further analyzed and the classes were balanced using SMOTE. With a balanced working dataset, we constructed 3 random forest classifiers: a multi-class predictor, a Severe disease group binary classifier and a PASC binary classifier. Models were also analyzed for feature importance to identify relevant cytokines to generate a disease score. Multi-class models generated a score specific for the PASC patients and defined as S1 = (IFN-γ + IL-2)/CCL4-MIP-1ß. Second, a score for the Severe COVID-19 patients was defined as S2 = (IL-6+sCD40L/1000 + VEGF/10 + 10*IL-10)/(IL-2 + IL-8). Severe COVID-19 patients are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While PASC patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells.