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High risk of mental health problems is associated with loneliness resulting from social distancing measures and "lockdowns" that have been imposed globally due to the COVID-19 pandemic. This study explores the interconnectedness of loneliness, anxiety and depression on a symptom level using network analysis. A representative sample of participants (N = 1041), who were of at least 18 years of age, was recruited from the Republic of Ireland (ROI). Loneliness, anxiety and depression were assessed using validated instruments. Network analysis was used to identify the network structure of loneliness, anxiety and depression. Loneliness was found to be largely isolated from anxiety and depression nodes in the network. Anxiety and depression were largely interconnected. "Trouble relaxing," "feeling bad about oneself" and "not being able to stop or control worrying" were suggested as the most influential nodes of the network. Despite the expectation that loneliness would be implicated more robustly in the anxiety and depression network of symptoms, the results suggest loneliness as a distinct construct that is not interwoven with anxiety and depression.

Two theoretical perspectives have been proffered to explain changes in alcohol use during the pandemic: the 'affordability-availability' mechanism (i.e., drinking decreases due to changes in physical availability and/or reduced disposable income) and the 'psychological-coping' mechanism (i.e., drinking increases as adults attempt to cope with pandemic-related distress). We tested these alternative perspectives via longitudinal analyses of the COVID-19 Psychological Consortium (C19PRC) Study data (spanning three timepoints during March to July 2020). Respondents provided data on psychological measures (e.g., anxiety, depression, posttraumatic stress, paranoia, extraversion, neuroticism, death anxiety, COVID-19 anxiety, intolerance of uncertainty, resilience), changes in socio-economic circumstances (e.g., income loss, reduced working hours), drinking motives, solitary drinking, and 'at-risk' drinking (assessed using a modified version of the AUDIT-C). Structural equation modelling was used to determine (i) whether 'at-risk' drinking during the pandemic differed from that recalled before the pandemic, (ii) dimensions of drinking motives and the psychosocial correlates of these dimensions, (iii) if increased alcohol consumption was predicted by drinking motives, solitary drinking, and socio-economic changes. The proportion of adults who recalled engaging in 'at-risk' drinking decreased significantly from 35.9% pre-pandemic to 32.0% during the pandemic. Drinking to cope was uniquely predicted by experiences of anxiety and/or depression and low resilience levels. Income loss or reduced working hours were not associated with coping, social enhancement, or conformity drinking motives, nor changes in drinking during lockdown. In the earliest stage of the pandemic, psychological-coping mechanisms may have been a stronger driver to changes in adults' alcohol use than 'affordability-availability' alone.

Objectives This study examined the association between perceived manageability of debt and risk of depression, anxiety, and mental health help-seeking among a nationally representative sample of adults living in the United Kingdom (UK). Methods Data was derived from the COVID-19 Psychological Research Consortium (C19PRC) Study Wave 6 (August/September 2021) which examined the psychological, social, and economic effects of the COVID-19 pandemic on the UK adult population. Bivariate and logistic regression analyses were conducted to determine the association between different levels of perceived debt manageability (i.e., “easily manageable”, “some problems”, “quite serious problems”, “very serious problems”, “cannot manage at all”) and mental health related outcomes. Results Almost a quarter of the sample (24%, n = 494) reported debt management problems, and debt manageability associated with higher levels of anxiety, depression, and mental health help-seeking. After adjusting for demographic variables (e.g. income, receipt of benefits), logistic regression analysis demonstrated a dose-response association between increasing levels of debt manageability problems and mental health outcomes. Specifically, adjusted odds ratios for anxiety ranged from 2.28 (‘some problems’) to 11.18 (‘very serious problems’), for depression ranged from 2.80 (‘some problems’) to 16.21 (‘cannot manage at all’), and for mental health help-seeking ranged from 1.69 (‘some problems’) to 3.18 (‘quite serious problems’, ‘very serious problems’). Conclusion This study highlights that debt manageability problems represent a robust predictor of depression, anxiety, and mental-health help seeking.

Objectives The COVID-19 Psychological Research Consortium (C19PRC) Study was established in March 2020 to monitor the psychological and socio-economic impact of the pandemic in the UK and other countries. This paper describes the protocol for Wave 5 (March–April 2021). Methods The survey assessed: COVID-19 related experiences; experiences of common mental health disorders; psychological characteristics; and social and political attitudes. Adults who participated in any previous wave (N = 4949) were re-invited to participate. Weights were calculated using a survey raking algorithm to ensure the longitudinal panel was nationally representative in terms of gender, age, and household income, amongst other factors. Results Overall, 2520 adults participated. A total of 2377 adults who participated in the previous survey wave (November–December 2020) were re-interviewed at Wave 5 (61.5% retention rate). Attrition between these two waves was predicted by younger age, lower household income, children living in the household, and treatment for mental health difficulties. Of the adults recruited into the C19PRC study at baseline, 57.4% (N = 1162) participated in Wave 5. The raking procedure re-balanced the longitudinal panel to within 1.5% of population estimates for selected socio-demographic characteristics. Conclusion This paper outlines the growing strength of the publicly available C19PRC Study data for COVID-19-related interdisciplinary research.

Introduction: The ICD-11 includes a new grouping for “disorders specifically associated with stress” that contains revised descriptions of posttraumatic stress disorder (PTSD) and adjustment disorder (AjD) and new diagnoses in the form of complex PTSD (CPTSD) and prolonged grief disorder (PGD). These disorders are similar in that they each require a life event for the diagnosis; however, they have not yet been assessed together for validity within the same sample. We set out to test the distinctiveness of the four main ICD-11 stress disorders using a network analysis approach. Methods: A population-based, cross-sectional design. A nationally representative sample of adults from the Republic of Ireland aged 18 years and older (N = 1,020) completed standardized measures of PTSD, CPTSD, AjD, and PGD. A network analysis was conducted at the symptom level. Outcome measures included the International Trauma Questionnaire, the Inventory of Complicated Grief, and the International Adjustment Disorder Questionnaire. Results: Consistent with the taxonomic structure of the ICD-11, our results showed that although the four conditions clustered independently at the disorder level, the specific symptoms of PTSD, CPTSD, PGD, and AjD clustered together very strongly but more strongly than with symptoms of the other disorders. The majority (61%) of the variation in each symptom could be explained by its neighboring symptoms. The strongest transdiagnostically connecting symptom was “startle response.” Discussion/Conclusion: Mental health professionals caring for people who have experienced a range of stressors and traumatic life events can be confident in diagnosing these conditions that have clear diagnostic boundaries. Interventions addressing stress-associated disorders should be based on diagnostic assessment to ensure close fit between symptoms and treatment.

Background: International Classification of Diseases, 11th revision (ICD-11) adjustment disorder (AjD) is characterized by two main symptom clusters: preoccupation with the stressor and failure to adapt to the stressor. The network analytic approach provides important information on the structural validity of a disorder and reveals which symptoms are most prominent. To date, no study compared the network structure of AjD symptoms in clinical and nonclinical samples, which could potentially inform our understanding of psychopathological mechanisms that underlie AjD and identify core targets for therapy. Methods: A network analysis was conducted on AjD symptoms as assessed by the Adjustment Disorder—New Module (ADNM-8) using data from 330 clinical participants from the UK and a nonclinical sample of 699 participants from Switzerland. Results: Comparisons of network structure invariance revealed differences between the network structure of the clinical and the nonclinical samples. Results highlight that in terms of both edges strength and centrality, failure to adapt symptoms was more prominent in the clinical sample, while the preoccupation symptoms were more prominent in the nonclinical sample. Importantly, global strength was similar across networks. Conclusions: Results provide evidence of the coherence of AjD in the ICD-11 as assessed by the ADNM questionnaire. They tentatively suggest that subclinical AjD may be characterized by emerging preoccupation symptoms that may result in failure to adapt and functional impairment in clinical manifestation of AjD. However, there is a need for replication and longitudinal research to further validate this hypothesis.