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Commonly identified patterns of psychological distress in response to adverse events are characterized by resilience (i.e., little to no distress), delayed (i.e., distress that increases over time), recovery (i.e., distress followed by a gradual decrease over time), and sustained (i.e., distress remaining stable over time). This study aimed to examine these response patterns during the COVID‐19 pandemic. Anxiety and depressive symptom data collected across four European countries over the first year of the pandemic were analyzed (N = 3,594). Participants were first categorized into groups based on the four described patterns. Network connectivity and symptom clustering were then estimated for each group and compared. Two thirds (63.6%) of the sample displayed a resilience pattern. The sustained distress network (16.3%) showed higher connectivity than the recovery network (10.0%) group, p =.031; however, the resilient network showed higher connectivity than the delayed network (10.1%) group, p =.016. Regarding symptom clustering, more clusters emerged in the recovery network (i.e., three) than the sustained network (i.e., two). These results replicate findings that resilience was the most common mental health pattern over the first pandemic year. Moreover, they suggest that high network connectivity may be indicative of a stable mental health response over time, whereas fewer clusters may be indicative of a sustained distress pattern. Although exploratory, the network perspective provides a useful tool for examining the complexity of psychological responses to adverse events and, if replicated, could be useful in identifying indicators of protection against or vulnerability to future psychological distress. [ABSTRACT FROM AUTHOR]

Following the 2016 EU referendum on Britain's membership in the European Union, many people described themselves as "Leavers" or "Remainers." Here, we examine the emotional responses associated with Brexit identities using survey data collected from two nationally representative samples of the British public in 2019 (N = 638) and 2021 (N = 2,058). Confirmatory factor analysis indicated that many in both samples had coherent Leave or Remain identities. Remain and, to a lesser extent, Leave identities (regardless of how people actually voted in the referendum) predicted distress about Brexit‐related events and clinical symptoms of depression and anxiety at both time points. Structural equation models suggested that the effect of identities on symptoms was largely mediated by distress about Brexit‐related events. We demonstrate a lasting impact of Brexit on the mental health of UK citizens and show that the formation of novel political identities has been more important in this process than voting behavior. [ABSTRACT FROM AUTHOR]

The International Classification of Diseases has recently defined Prolonged Grief Disorder (PGD) with symptoms such as longing, worry, and intense emotional pain that exceed sociocultural norms more than 6 months after the loss. This study aims to (a) estimate the prevalence of this new diagnostic category, (b) identify its sociodemographic and loss‐related predictors, and (c) assess the co‐occurrence of PGD with other psychological disorders and substance abuse. A large representative sample of Spanish adults (N = 1498) participated. Several multivariate binary logistic regression and multivariate logistic regression models were used. Results showed a 9.95% prevalence in the total sample. Catholic beliefs were a positive predictor, while higher income and more time since loss significantly decreased the odds of PGD. PGD significantly increased the likelihood of anxiety, depression, somatisation, post‐traumatic stress disorder, loneliness and substance use. Our study contributes to assessing the multicultural PGD validity, as our results from a large representative sample are comparable to those in other countries with the PGDS. Our findings have direct implications for the assessment and treatment of bereavement, identifying for practitioners variables that make individuals more vulnerable to PGD. Results highlighted the high co‐occurrence of PGD with other psychological illnesses and increased drug use. [ABSTRACT FROM AUTHOR]

Given the highly infectious nature of COVID-19, social distancing practices are key in stemming the spread of the virus. We aimed to assess the complex interplay among psychological factors, socio-demographic characteristics and social distancing behaviours within the framework of the widely used Capability, Opportunity, Motivation-Behaviour (COM-B) model. The present research employed network psychometrics on data collected during the first UK lockdown in April 2020 as part of the COVID-19 Psychological Research Consortium (C19PRC) Study. Using a network approach, we examined the predictions of psychological and demographic variables onto social distancing practices at two levels of analysis: macro and micro. Our findings revealed several factors that influenced social distancing behaviour during the first UK lockdown. The COM-B model was successful in predicting particular aspects of social-distancing via the influence of psychological capability and motivation at the macro-and micro-levels, respectively. Notably, demographic variables, such as education, income, and age, were directly and uniquely predictive of certain social distancing behaviours. Our findings reveal psychological factors that are key predictors of social distancing behaviour and also illustrate how demographic variables directly influence such behaviour. Our research has implications for the design of empirically-driven interventions to promote adherence to social distancing practices in this and future pandemics. Supplemental data for this article is available online at [ABSTRACT FROM AUTHOR]

Background: The psychosis continuum implies that subclinical psychotic experiences (PEs) can be differentiated from clinically relevant expressions since they are not accompanied by a 'need for care'. Methods: Using data from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N = 34 653), the current study examined variation in functioning, symptomology and aetiological risk across the psychosis phenotype [i.e. variation from (i) no PEs, 'No PEs' to (ii) non-distressing PEs, 'PE-Experienced Only' to (iii) distressing PEs, 'PE-Impaired' to (iv) clinically defined psychotic disorder, 'Diagnosed']. Results: A graded trend was present such that, compared to those with no PEs, the Diagnosed group had the poorest functioning, followed by the PE-Impaired then PE-Experienced Only groups. In relation to symptom expression, the PE-Impaired group were more likely than the PE-Experienced Only and the Diagnosed groups to endorse most PEs. Predictors of group membership tended to vary quantitatively rather than qualitatively. Trauma, current mental health diagnoses (anxiety and depression) and drug use variables differentiated between all levels of the continuum, with the exception of the extreme end (PE-Impaired v. Diagnosed). Only a few variables distinguished groups at the upper end of the continuum: female sex, older age, unemployment, parental mental health hospitalisation and lower likelihood of having experienced physical assault. Conclusions: The findings highlight the importance of continuum-based interpretations of the psychosis phenotype and afford valuable opportunities to consider if and how impairment, symptom expression and risk change along the continuum. [ABSTRACT FROM AUTHOR]

Objectives: Established in March 2020, the C19PRC Study monitors the psychological and socio‐economic impact of the pandemic in the UK and other countries. This paper describes the protocol for Wave 6 (August–September 2021). Methods: The survey assessed: COVID‐19 related experiences; experiences of common mental health disorders; psychological characteristics; and social and political attitudes. Adult participants from any previous wave (N = 3170) were re‐invited, and sample replenishment procedures helped manage attrition. Weights were calculated using a survey raking algorithm to ensure the on‐going original panel (from baseline) was nationally representative in terms of gender, age, and household income, amongst other factors. Results: 1643 adults were re‐interviewed at Wave 6 (51.8% retention rate). Non‐participation was higher younger adults, those born outside UK, and adults living in cities. Of the adults recruited at baseline, 54.3% (N = 1100) participated in Wave 6. New respondent (N = 415) entered the panel at this wave, resulting in cross‐sectional sample for Wave 6 of 2058 adults. The raking procedure re‐balanced the longitudinal panel to within 1.3% of population estimates for selected socio‐demographic characteristics. Conclusions: This paper outlines the growing strength of the publicly available C19PRC Study data for COVID‐19‐related interdisciplinary research. [ABSTRACT FROM AUTHOR]

Background: The new International Classification of Diseases came into effect in 2022 (ICD‐11; World Health Organization, 2022) and included updated descriptions and diagnostic rules for "Depressive Episode" and "Generalized Anxiety Disorder." No self‐report measures align with these disorders so this study reports the development and initial validation of the "International Depression Questionnaire" (IDQ) and "International Anxiety Questionnaire" (IAQ). Methods: Items were developed that aligned to the ICD‐11 descriptions and their performance was assessed using data from a community sample (N = 2058) that was representative of the United Kingdom adult population. Results: Item response theory models indicated that the two scales were unidimensional, and the items performed well in terms of difficulty and discrimination. Estimates of internal reliability were high. Based on ICD‐11 derived diagnostic algorithms, 7.4% met requirements for ICD‐11 Depressive Episode and 7.1% for Generalized Anxiety Disorder. Conclusions: The IDQ and the IAQ are short, easy to use, self‐report measures aligned to the new and updated ICD‐11 diagnostic descriptions. This study provides initial evidence that the scales produce scores that are reliable and valid. [ABSTRACT FROM AUTHOR]

Background: The current study argues that population prevalence estimates for mental health disorders, or changes in mean scores over time, may not adequately reflect the heterogeneity in mental health response to the COVID-19 pandemic within the population. Methods: The COVID-19 Psychological Research Consortium (C19PRC) Study is a longitudinal, nationally representative, online survey of UK adults. The current study analysed data from its first three waves of data collection: Wave 1 (March 2020, N = 2025), Wave 2 (April 2020, N = 1406) and Wave 3 (July 2020, N = 1166). Anxiety-depression was measured using the Patient Health Questionnaire Anxiety and Depression Scale (a composite measure of the PHQ-9 and GAD-7) and COVID-19-related posttraumatic stress disorder (PTSD) with the International Trauma Questionnaire. Changes in mental health outcomes were modelled across the three waves. Latent class growth analysis was used to identify subgroups of individuals with different trajectories of change in anxiety-depression and COVID-19 PTSD. Latent class membership was regressed on baseline characteristics. Results: Overall prevalence of anxiety-depression remained stable, while COVID-19 PTSD reduced between Waves 2 and 3. Heterogeneity in mental health response was found, and hypothesised classes reflecting (i) stability, (ii) improvement and (iii) deterioration in mental health were identified. Psychological factors were most likely to differentiate the improving, deteriorating and high-stable classes from the low-stable mental health trajectories. Conclusions: A low-stable profile characterised by little-to-no psychological distress ('resilient' class) was the most common trajectory for both anxiety-depression and COVID-19 PTSD. Monitoring these trajectories is necessary moving forward, in particular for the ~30% of individuals with increasing anxiety-depression levels. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 2019 (COVID-19) emergency has led to numerous attempts to assess the impact of the pandemic on population mental health. The findings indicate an increase in depression and anxiety but have been limited by the lack of specificity about which aspects of the pandemic (e.g. viral exposure or economic threats) have led to adverse mental health outcomes. Methods: Network analyses were conducted on data from wave 1 (N = 2025, recruited 23 March–28 March 2020) and wave 2 (N = 1406, recontacts 22 April–1 May 2020) of the COVID-19 Psychological Research Consortium Study, an online longitudinal survey of a representative sample of the UK adult population. Our models included depression (PHQ-9), generalized anxiety (GAD-7) and trauma symptoms (ITQ); and measures of COVID-specific anxiety, exposure to the virus in self and close others, as well as economic loss due to the pandemic. Results: A mixed graphical model at wave 1 identified a potential pathway from economic adversity to anxiety symptoms via COVID-specific anxiety. There was no association between viral exposure and symptoms. Ising network models using clinical cut-offs for symptom scores at each wave yielded similar findings, with the exception of a modest effect of viral exposure on trauma symptoms at wave 1 only. Anxiety and depression symptoms formed separate clusters at wave 1 but not wave 2. Conclusions: The psychological impact of the pandemic evolved in the early phase of lockdown. COVID-related anxiety may represent the mechanism through which economic consequences of the pandemic are associated with psychiatric symptoms. [ABSTRACT FROM AUTHOR]