Objectives Loneliness is a significant public health issue. The COVID-19 pandemic has resulted in lockdown measures limiting social contact. The UK public are worried about the impact of these measures on mental health outcomes. Understanding the prevalence and predictors of loneliness at this time is a priority issue for research. Method The study employed a cross-sectional online survey design. Baseline data collected between March 23rd and April 24th 2020 from UK adults in the COVID-19 Psychological Wellbeing Study were analysed (N = 1964, 18-87 years, M = 37.11, SD = 12.86, 70% female). Logistic regression analysis examined the influence of sociodemographic, social, health and COVID-19 specific factors on loneliness. Results The prevalence of loneliness was 27% (530/1964). Risk factors for loneliness were younger age group (OR: 4.67-5.31), being separated or divorced (OR: 2.29), scores meeting clinical criteria for depression (OR: 1.74), greater emotion regulation difficulties (OR: 1.04), and poor quality sleep due to the COVID-19 crisis (OR: 1.30). Higher levels of social support (OR: 0.92), being married/co-habiting (OR: 0.35) and living with a greater number of adults (OR: 0.87) were protective factors. Conclusions Rates of loneliness during the initial phase of lockdown were high. Risk factors were not specific to the COVID-19 crisis. Findings suggest that supportive interventions to reduce loneliness should prioritise younger people and those with mental health symptoms. Improving emotion regulation and sleep quality, and increasing social support may be optimal initial targets to reduce the impact of COVID-19 regulations on mental health outcomes.

The growing literature conceptualizing mental disorders like posttraumatic stress disorder (PTSD) as networks of interacting symptoms faces three key challenges. Prior studies predominantly used (a) small samples with low power for precise estimation, (b) nonclinical samples, and (c) single samples. This renders network structures in clinical data, and the extent to which networks replicate across data sets, unknown. To overcome these limitations, the present cross-cultural multisite study estimated regularized partial correlation networks of 16 PTSD symptoms across four data sets of traumatized patients receiving treatment for PTSD (total N = 2,782). Despite differences in culture, trauma type, and severity of the samples, considerable similarities emerged, with moderate to high correlations between symptom profiles (0.43–0.82), network structures (0.62–0.74), and centrality estimates (0.63–0.75). We discuss the importance of future replicability efforts to improve clinical psychological science and provide code, model output, and correlation matrices to make the results of this article fully reproducible.

BackgroundIntimate partner violence (IPV) has been known to adversely affect the mental health of victims. Research has tended to focus on the mental health impact of physical violence rather than considering other forms of violence.ObjectiveTo systematically review the literature in order to identify the impact of all types of IPV victimisation on various mental health outcomes.MethodA systematic review of 11 electronic databases (2004–2014) was conducted. Fifty eight papers were identified and later described and reviewed in relation to the main objective.ResultsMain findings suggest that IPV can have increasing adverse effects on the mental health of victims in comparison with those who have never experienced IPV or those experiencing other traumatic events. The most significant outcomes were associations between IPV experiences with depression, posttraumatic stress disorder, and anxiety. Findings confirm previous observations that the severity and extent of IPV exposure can increase mental health symptoms. The effect of psychological violence on mental health is more prominent than originally thought. Individual differences such as gender and childhood experience of violence also increase IPV risk and affect mental health outcomes in diverse ways.ConclusionsPsychological violence should be considered as a more serious form of IPV which can affect the mental health of victims. Experiencing more than one form of IPV can increase severity of outcomes. Researchers should look at IPV as a multi-dimensional experience. A uniformed definition and measure of IPV could help advance knowledge and understanding of this disparaging global issue.

Background The impact of COVID-19 on physical and mental health and employment after hospitalisation with acute disease is not well understood. The aim of this study was to determine the effects of COVID-19-related hospitalisation on health and employment, to identify factors associated with recovery, and to describe recovery phenotypes. MethodsThe Post-hospitalisation COVID-19 study (PHOSP-COVID) is a multicentre, long-term follow-up study of adults (aged ≥18 years) discharged from hospital in the UK with a clinical diagnosis of COVID-19, involving an assessment between 2 and 7 months after discharge, including detailed recording of symptoms, and physiological and biochemical testing. Multivariable logistic regression was done for the primary outcome of patient-perceived recovery, with age, sex, ethnicity, body-mass index, comorbidities, and severity of acute illness as covariates. A posthoc cluster analysis of outcomes for breathlessness, fatigue, mental health, cognitive impairment, and physical performance was done using the clustering large applications k-medoids approach. The study is registered on the ISRCTN Registry (ISRCTN10980107). Findings We report findings for 1077 patients discharged from hospital between March 5 and Nov 30, 2020, who underwent assessment at a median of 5•9 months (IQR 4•9-6•5) after discharge. Participants had a mean age of 58 years (SD 13); 384 (36%) were female, 710 (69%) were of white ethnicity, 288 (27%) had received mechanical ventilation, and 540 (50%) had at least two comorbidities. At follow-up, only 239 (29%) of 830 participants felt fully recovered, 158 (20%) of 806 had a new disability (assessed by the Washington Group Short Set on Functioning), and 124 (19%) of 641 experienced a health-related change in occupation. Factors associated with not recovering were female sex, middle age (40-59 years), two or more comorbidities, and more severe acute illness. The magnitude of the persistent health burden was substantial but only weakly associated with the severity of acute illness. Four clusters were identified with different severities of mental and physical health impairment (n=767): very severe (131 patients, 17%), severe (159, 21%), moderate along with cognitive impairment (127, 17%), and mild (350, 46%). Of the outcomes used in the cluster analysis, all were closely related except for cognitive impairment. Three (3%) of 113 patients in the very severe cluster, nine (7%) of 129 in the severe cluster, 36 (36%) of 99 in the moderate cluster, and 114 (43%) of 267 in the mild cluster reported feeling fully recovered. Persistently elevated serum C-reactive protein was positively associated with cluster severity.Interpretation We identified factors related to not recovering after hospital admission with COVID-19 at 6 months after discharge (eg, female sex, middle age, two or more comorbidities, and more acute severe illness), and four different recovery phenotypes. The severity of physical and mental health impairments were closely related, whereas cognitive health impairments w...

Two models of posttraumatic stress disorder (PTSD) have received the most empirical support in confirmatory factor analytic studies: King, Leskin, King, and Weathers' (1998) Emotional Numbing model of reexperiencing, avoidance, emotional numbing and hyperarousal; and Simms, Watson, and Doebbeling's (2002) Dysphoria model of reexperiencing, avoidance, dysphoria and hyperarousal. These models only differ in placement of three PTSD symptoms: sleep problems (D1), irritability (D2), and concentration problems (D3). In the present study, we recruited 252 women victims of domestic violence and tested whether there is empirical support to separate these three PTSD symptoms into a fifth factor, while retaining the Emotional Numbing and Dysphoria models' remaining four factors. Confirmatory factor analytic findings demonstrated that separating the three symptoms into a separate factor significantly enhanced model fit for the Emotional Numbing and Dysphoria models. These three symptoms may represent a unique latent construct. Implications are discussed.

Several revisions to the symptom clusters of posttraumatic stress disorder (PTSD) have been made in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Central to the focus of this study was the revision of PTSD's tripartite structure in DSM-IV into four symptom clusters in DSM-5. Emerging confirmatory factor analytic (CFA) studies have suggested that DSM-5 PTSD symptoms may be best represented by one of two 6-factor models: (1) an Externalizing Behaviors model characterized by a factor which combines the irritability/anger and self-destructive/reckless behavior items; and (2) an Anhedonia model characterized by items of loss of interest, detachment, and restricted affect. The current study conducted CFAs of DSM-5 PTSD symptoms assessed using the PTSD Checklist for DSM-5 (PCL-5) in two independent and diverse trauma-exposed samples of a nationally representative sample of 1484 U.S. veterans and a sample of 497 Midwestern U.S. university undergraduate students. Relative fits of the DSM-5 model, the DSM-5 Dysphoria model, the DSM-5 Dysphoric Arousal model, the two 6-factor models, and a newly proposed 7-factor Hybrid model, which consolidates the two 6-factor models, were evaluated. Results revealed that, in both samples, both 6-factor models provided significantly better fit than the 4-factor DSM-5 model, the DSM-5 Dysphoria model and the DSM-5 Dysphoric Arousal model. Further, the 7-factor Hybrid model, which incorporates key features of both 6-factor models and is comprised of re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal symptom clusters, provided superior fit to the data in both samples. Results are discussed in light of theoretical and empirical support for the latent structure of DSM-5 PTSD symptoms.

These results demonstrate the utility of a network approach in modeling the structure of DSM-5 PTSD symptoms, and suggest differential associations between specific DSM-5 PTSD symptoms and clinical outcomes in trauma survivors. Implications of these results for informing the assessment and treatment of this disorder, are discussed.

Findings demonstrate that a full understanding of the link between personality and health requires consideration of trait change as well as trait level.