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Whether complex posttraumatic stress disorder (CPTSD) and borderline personality disorder (BPD) diagnoses differ substantially enough to warrant separate diagnostic classifications has been a subject of controversy for years. To contribute to the nomological network of cumulative evidence, the main goal of the present study was to explore, using network analysis, how the symptoms of ICD-11 PTSD and disturbances in self-organization (DSO) are interconnected with BPD in a clinical sample of polytraumatized individuals (N = 330). Participants completed measures of life events, CPTSD, and BPD. Overall, our study suggests that BPD and CPTSD are largely separated. The bridges between BPD and CPTSD symptom clusters were scarce, with “Affective Dysregulation” items being the only items related to BPD. The present study contributes to the growing literature on discriminant validity of CPTSD and supports its distinctiveness from BPD. Implications for treatment are discussed.

Although a negative association between socio-economic inequalities and health has been established, there is a dearth of robust longitudinal studies examining this relationship in adolescents. This study used a large, nationally representative longitudinal data set to investigate the association between socio-economic inequality, subjective health status and disabilities among young people in Northern Ireland over a ten-year period. Data were from the Northern Ireland Longitudinal Study, a census-based record linkage study (N = 46,535). Logistic regression models were estimated in which health and disability variables from the 2011 census were predicted by household deprivation in education, housing quality, housing tenure and employment from the 2001 census. Models were adjusted for health and disability status in 2001. Deprivation in employment, housing tenure and coming from a single-parent household in 2001 independently predicted poorer subjective health and disability status ten years later [ORs = 1.28–1.93]. Deprivation in education in 2001 was also associated with increased risk of disability in 2011 [OR = 1.15; 95% CI = 1.06–1.25]. These results show that there is a need to dedicate more resources and support for economically disadvantaged children and young people in Northern Ireland, where child health outcomes are poorer than in the rest of the UK.

The current paper presents a five-factor measurement model of anger summarizing scores on public-domain self-report measures of anger. Exploratory and confirmatory factor analyses of self-report measures of anger (UK

BACKGROUND: Evidence on associations between COVID-19 illness and mental health is mixed. We aimed to examine whether COVID-19 is associated with deterioration in mental health while considering pre-pandemic mental health, time since infection, subgroup differences, and confirmation of infection via self-reported test and serology data.METHODS: We obtained data from 11 UK longitudinal studies with repeated measures of mental health (psychological distress, depression, anxiety, and life satisfaction; mental health scales were standardised within each study across time) and COVID-19 status between April, 2020, and April, 2021. We included participants with information available on at least one mental health outcome measure and self-reported COVID-19 status (suspected or test-confirmed) during the pandemic, and a subset with serology-confirmed COVID-19. Furthermore, only participants who had available data on a minimum set of covariates, including age, sex, and pre-pandemic mental health were included. We investigated associations between having ever had COVID-19 and mental health outcomes using generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education, and pre-pandemic mental health, whether the strength of the association varied according to time since infection, and whether associations differed between self-reported versus confirmed (by test or serology) infection.FINDINGS: Between 21 Dec, 2021, and July 11, 2022, we analysed data from 54 442 participants (ranging from a minimum age of 16 years in one study to a maximum category of 90 years and older in another; including 33 200 [61·0%] women and 21 242 [39·0%] men) from 11 longitudinal UK studies. Of 40 819 participants with available ethnicity data, 36 802 (90·2%) were White. Pooled estimates of standardised differences in outcomes suggested associations between COVID-19 and subsequent psychological distress (0·10 [95% CI 0·06 to 0·13], I2=42·8%), depression (0·08 [0·05 to 0·10], I2=20·8%), anxiety (0·08 [0·05 to 0·10], I2=0·0%), and lower life satisfaction (-0·06 [-0·08 to -0·04], I2=29·2%). We found no evidence of interactions between COVID-19 and sex, education, ethnicity, or pre-pandemic mental health. Associations did not vary substantially between time since infection of less than 4 weeks, 4-12 weeks, and more than 12 weeks, and were present in all age groups, with some evidence of stronger effects in those aged 50 years and older. Participants who self-reported COVID-19 but had negative serology had worse mental health outcomes for all measures than those without COVID-19 based on serology and self-report. Participants who had positive serology but did not self-report COVID-19 did not show association with mental health outcomes.INTERPRETATION: Self-reporting COVID-19 was longitudinally associated with deterioration in mental health and life satisfaction. Our findings emphasise the need for greater post-infection mental health service provision, given the substantial prevalence of COVID-19 in the UK and worldwide.FUNDING: UK Medical Research Council and UK National Institute for Health and Care Research.

Background The Memories of Home and Family Scale (MHFS; Shevlin et al., 2022) was developed as a multidimensional measure of subjective memories of experiences at home and with family during childhood. Due to the length of the scale, a short version of the MHFS (MHFS-SF) has been developed. Data were from Wave 7 of the COVID-19 Psychological Research Consortium Study (C19PRC-UK), a population based UK survey (N = 1405). Two items with the highest factor loadings from each of the six dimensions of the original MHFS were selected for inclusion. Confirmatory factor analytic (CFA) models were estimated to test the dimensionality of the scale. Convergent and discriminant validity were tested by examining associations with criterion variables. CFA results supported the multidimensionality of the scale. MHFS-SF total and sub-scale scores were negatively correlated with measures of depression, anxiety, loneliness, and paranoia, and were positively correlated with wellbeing. Regression analyses revealed that MHFS-SF total and sub-scale scores significantly predicted loneliness, paranoia, and wellbeing, even after accounting for age, gender, and current internalising symptoms. Results from this study suggest that the MHFS-SF scores retain the excellent psychometric properties of the original scale while improving efficiency. The MHFS-SF demonstrated high levels of convergent and discriminant validity with mental health and wellbeing measures. Future research should seek to validate the MHFS-SF in different populations and assess its usefulness in clinical settings.

MotivationRetrospective questionnaire harmonisation allows researchers to pool and analyse information from multiple data sources, thereby increasing reproducibility in science. Currently, harmonisation of questionnaires relies on a multi-step process where items are manually matched based on expert opinion. Harmony, a new natural-language processing tool supports researchers with fast, reproducible and multilingual measurement harmonisation. ImplementationHarmony is a web tool which can be used from any major web-browser by non-technical users.General features Users can upload questionnaire meta-data in text, PDF or excel format. Once uploaded, Harmony extracts the relevant information from the files and presents them to the user. Users choose which items they would like to match. Harmony will use the cosine similarity to find the closest matches between items and present the findings including a percentage match-score. AvailabilityHarmony is open-source (//github.com/harmonydata/harmony) and freely available via //app.harmonydata.org/ under the MIT licence for non-commercial use.

A nationwide survey of 2,004 adult Ukrainian parents who reported on their experiences of the war, how their own mental health has changed since the invasion in February 2022, and how the mental health of their children has changed. These data were collected between July and September 2022.

Background: It is expected that the ongoing war in Ukraine will have a considerable negative impact on the mental health of the country’s population. This study aims to provide a preliminary estimate of the degree of change in the mental health problems of Ukrainian children following Russia’s invasion of Ukraine in February 2022, and identify the sociodemographic and war-related risk factors associated with these changes.Methods: A nationwide, opportunistic sample of 1,238 parents reported on a single randomly chosen child within their household as part of The Mental Health of Parents and Children in Ukraine Study. Data were collected between July 15th and September 5th 2022. Participants completed modified versions of the Pediatric Symptom Checklist (PSC-17) which was adapted to capture change in the frequency of symptoms since the Russian attack.Results: Parents reported increases across all 17 indicators of internalizing, externalizing and attention problems of the PSC-17. Increases were most pronounced within the internalizing domain, with 35% of parents reporting that their child worried more since the beginning of the war. Various individual, parental and war-related factors were associated with increases across the three domains. Exposure to war trauma, pre-existing mental health problems, and child age were amongst the strongest predictors of change. Conclusion: The Russian war on Ukraine has likely led to an increase in common mental health problems for children in the general population. Further research is required to determine the extent and outcomes of this increase, and to develop strategies to help those most in need.

ObjectivesWe investigated associations between multiple sociodemographic characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions during the early stages of the COVID-19 pandemic.DesignCoordinated analysis of prospective population surveys.SettingCommunity-dwelling participants in the UK between April 2020 and January 2021.ParticipantsOver 68 000 participants from 12 longitudinal studies.OutcomesSelf-reported healthcare disruption to medication access, procedures and appointments.ResultsPrevalence of healthcare disruption varied substantially across studies: between 6% and 32% reported any disruption, with 1%–10% experiencing disruptions in medication, 1%–17% experiencing disruption in procedures and 4%–28% experiencing disruption in clinical appointments. Females (OR 1.27; 95% CI 1.15 to 1.40; I2=54%), older persons (eg, OR 1.39; 95% CI 1.13 to 1.72; I2=77% for 65–75 years vs 45–54 years) and ethnic minorities (excluding white minorities) (OR 1.19; 95% CI 1.05 to 1.35; I2=0% vs white) were more likely to report healthcare disruptions. Those in a more disadvantaged social class were also more likely to report healthcare disruptions (eg, OR 1.17; 95% CI 1.08 to 1.27; I2=0% for manual/routine vs managerial/professional), but no clear differences were observed by education. We did not find evidence that these associations differed by shielding status.ConclusionsHealthcare disruptions during the COVID-19 pandemic could contribute to the maintenance or widening of existing health inequalities.

Background: High rates of posttraumatic stress disorder (PTSD) have been documented in war-affected populations. The prevalence of CPTSD has never been assessed in an active war zone. Here, we provide initial data on war-related experiences, and estimated prevalence rates of ICD-11 PTSD and Complex PTSD (CPTSD) in the general adult population of Ukraine during the Russian war. We also examined how war-related stressors, PTSD, and CPTSD were associated with age, sex, and living location in Ukraine. Method: Self-report data were gathered from a nationwide sample of 2,004 adult parents of children under 18 from the general population of Ukraine approximately six months after Russia’s invasion. Results: All participants were exposed to at least one war-related stressor, and the mean number of exposures was 9.07 (range = 1-26). Additionally, 25.9% (95% CI = 23.9%, 27.8%) met diagnostic requirements for probable PTSD and 14.6% (95% CI = 12.9%, 16.0%) met requirements for probable CPTSD. There was evidence of a strong dose-response relationship between war-related stressors and meeting criteria for probable PTSD and CPTSD. Participants who had the highest exposure to war-related stressors were significantly more likely to meet the requirements for probable PTSD (OR = 4.20; 95% CI = 2.96 -5.95) or CPTSD (OR = 8.12; 95% CI = 5.11 - 12.91) compared to the least exposed.Conclusions: Humanitarian responses to the mental health needs of the Ukrainian population will need to take account of posttraumatic stress reactions. Education in diagnosing and treating PTSD/CPTSD, especially in the situation of a significant lack of human resources and continuing displacement of the population, is necessary.

Background: There is currently limited information on how Russia’s war on Ukraine has affected the mental health of people living in Ukraine. Understanding the mental health effects of the war, and identifying who has been worst affected, is critical to informing mental health responses. A nationwide sample of parents in Ukraine were surveyed to (1) determine how symptoms of anxiety, depression, loneliness, and hazardous alcohol use have changed since February 24th, 2022, and (2) identify risk-factors associated with changes in mental health. Methods: A nationwide, opportunistic sample (N = 2,004) of adult parents in Ukraine were surveyed as part of The Mental Health of Parents and Children in Ukraine Study. Participants completed modified self-report measures of generalized anxiety, major depression, loneliness, and hazardous alcohol use to capture change in the frequency of these symptoms since February 24th 2022.Results: Overall increases in symptoms of anxiety, depression, loneliness, and hazardous alcohol use were observed, with most people reporting increased symptoms of anxiety (72%), depression (62%), and fewer reporting increased loneliness (47%) and hazardous drinking (8%). Demographic and war-related variables were associated with increases in mental health problems, however, exposure to a higher number of war-related stressors and caring for a child with an emotional or behavioural problem were most robustly associated with increased symptoms of all mental health problems. Conclusion: Russia’s war on Ukraine has probably led to increases in mental health problems for most adults in Ukraine. These findings suggest where limited mental health resources may be most effectively deployed.

Objective There is little evidence that posttraumatic stress disorder (PTSD) is more likely to follow traumatic events defined by Criterion A than non-Criterion A stressors. Criterion A events might have greater predictive validity for International Classification of Diseases (ICD)-11 PTSD, which is a condition more narrowly defined by core features. We evaluated the impact of using Criterion A, an expanded trauma definition in line with ICD-11 guidelines, and no exposure criterion on rates of ICD-11 PTSD and Complex PTSD (CPTSD). We also assessed whether 5 psychologically threatening events included in the expanded definition were as strongly associated with PTSD and CPTSD as standard Criterion A events. Method A nationally representative sample from Ireland (N = 1,020) completed self-report measures. Results Most participants were trauma-exposed based on Criterion A (82%) and the expanded (88%) criterion. When no exposure criterion was used, 13.7% met diagnostic requirements for PTSD or CPTSD, 13.2% when the expanded criterion was used, and 13.2% when Criterion A was used. The 5 psychologically threatening events were as strongly associated with PTSD and CPTSD as the Criterion A events. In a multivariate analysis, only the psychologically threatening events were significantly associated with PTSD (stalking) and CPTSD (bullying, emotional abuse, and neglect). Conclusions Certain non-Criterion A events involving extreme fear and horror should be considered traumatic. The ICD-11 approach of providing clinical guidance rather than a formal definition offers a viable solution to some of the problems associated with the current and previous attempts to define traumatic exposure. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

BackgroundExisting evidence on profiles of psychological distress across adulthood uses cross-sectional or longitudinal studies with short observation periods. The objective of this research was to study the profile of psychological distress within the same individuals from early adulthood to early old age across three British birth cohorts.MethodsWe used data from three British birth cohorts: born in 1946 (n= 3093), 1958 (n= 13 250) and 1970 (n= 12 019). The profile of psychological distress – expressed both as probability of being a clinical case or a count of symptoms based on comparable items within and across cohorts – was modelled using the multilevel regression framework.ResultsIn both 1958 and 1970 cohorts, there was an initial drop in the probability of being a case between ages 23–26 and 33–34. Subsequently, the predicted probability of being a case increased from 12.5% at age 36 to 19.5% at age 53 in the 1946 cohort; from 8.0% at age 33 to 13.7% at age 42 in the 1958 cohort and from 15.7% at age 34 to 19.7% at age 42 in the 1970 cohort. In the 1946 cohort, there was a drop in the probability of caseness between ages 60–64 and 69 (19.5%v.15.2%). Consistent results were obtained with the continuous version of the outcome.ConclusionsAcross three post-war British birth cohorts midlife appears to be a particularly vulnerable phase for experiencing psychological distress. Understanding the reasons for this will be important for the prevention and management of mental health problems.

Purpose: There are multiple studies illustrating how benevolent childhood experiences (BCEs) are associated with more favorable health outcomes across the life-course, even in the context of adverse childhood experiences (ACEs). Despite this, few measures are available to assess BCEs. Existing measures include a narrow spectrum of objective BCEs and are limited by the use of binary response categories while few investigate BCEs specifically related to the family and home environment. Thus, the current study sought to develop and validate a measure which assesses positive recollections of experiences and emotions at home and with family during childhood called the ‘Memories of Home and Family Scale’(MHFS). Methods: Items were generated which captured a diverse range of positive emotions and experiences related to home and family life during childhood. Confirmatory factor analysis (CFA) was employed to test the latent structure of the preliminary MHFS item scores in a sample of university students from the United Kingdom (N=624). Following selection of the best-fitting model and final items for inclusion in the scale, total and subscale scores were correlated with a range of mental health outcomes. Results: The results from the CFA indicated that the latent structure of the MHFS items was best represented by a correlated six-factor first-order model. The final MHFS demonstrated high levels of internal reliability and convergent validity. Conclusion: The MHFS is a 28-item multidimensional measure which assesses positive memories of home and family during childhood across six dimensions including valued, independence, support, security, wellness, growth and meaning.

BackgroundEvidence on associations between COVID-19 illness and mental health is mixed. We examined longitudinal associations between COVID-19 and mental health while considering: 1) pre-pandemic mental health, 2) time since infection; 3) subgroup differences; and 4) confirmation of infection via self-reported test, and serology data.MethodsUsing data from 11 UK longitudinal studies, involving 54,442 participants, with 2 to 8 repeated measures of mental health and COVID-19 between April 2020 and April 2021, we standardised continuous mental health scales within each study across time. We investigated associations between COVID-19 (self-report, test-confirmed, serology-confirmed) and mental health using multilevel generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education and pre-pandemic mental health. Effect-sizes were pooled in random-effects meta-analyses.OutcomesPooled estimates of the standardized difference in outcome between those with and without self-reported COVID-19 suggested associations with subsequent psychological distress (0.10 [95%CI: 0.06; 0.13], I2=42.8%), depression (0.08 [0.05; 0.10], I2=20.8%), anxiety (0.08 [0.05; 0.10], I2=0%), and lower life satisfaction (−0.06 [-0.08; -0.04], I2=29.2%). Associations did not vary by time since infection until 3+ months and were present in all age groups, with some evidence of stronger effects in those aged 50+. Self-reported COVID-19, whether suspected or test-confirmed and irrespective of serology status, was associated with poorer mental health.InterpretationSelf-reporting COVID-19 was longitudinally associated with deterioration in mental health and life satisfaction. Our findings have important implications for mental health service provision, given the substantial prevalence of COVID-19 in the UK and worldwide.FundingMRC and NIHR

In the present study, we employed network analysis that conceptualizes internet addiction (IA) as a complex network of mutually influencing symptoms in 108 adolescents with autism spectrum disorder (ASD) to examine the network architecture of IA symptoms and identify central/influential symptoms. Our analysis revealed that defensive and secretive behaviors and concealment of internet use were identified as central symptoms in this population, suggesting that mitigating these symptoms potentially prevent the development and/or maintenance of IA in adolescents with ASD. Providing adolescents and their caregivers with psychoeducation on the role of central symptoms above in IA can be a salient intervention. Doing so may facilitate nonconflicting conversations between them about adolescents' internet use and promote more healthy adolescents' internet use behavior.

General and specific dimensions of psychosis have been identified in both clinical and general population samples. Demographic and clinical correlates, however, have only been explored within models derived from clinical data. Data were drawn from Wave 3 of the National Epidemiological Survey on Alcohol and Related Conditions (N = 36,309). Confirmatory factor analysis and confirmatory bifactor modelling were used to determine the optimal measurement model of psychosis symptoms among this sample. Structural equation modelling was used to identify variables correlated with the different psychosis dimensions, as per the best fitting measurement model. Measurement modelling results indicated that the latent structure of psychosis was best represented by a bifactor model including a general dimension orthogonal to four specific dimensions representing “Positive”, “Negative”, “Mania”, and “Disorganized” symptoms. Childhood interpersonal trauma, lack of social support, lower socio-economic status and suicidal attempts were associated with higher scores on the general dimension. These results provide further support for the validity of a bifactor model of psychosis in the general population and identify unique risk correlates of specific and general factors of psychosis

BackgroundDimensional models of psychopathology are increasingly common and there is evidence for the existence of a general dimension of psychopathology (‘p’). The existing literature presents two ways to model p: as a bifactor or as a higher-order dimension. Bifactor models typically fit sample data better than higher-order models, and are often selected as better fitting alternatives but there are reasons to be cautious of such an approach to model selection. In this study the bifactor and higher-order models of p were compared in relation to associations with established risk variables for mental illness.MethodsA trauma exposed community sample from the United Kingdom (N = 1051) completed self-report measures of 49 symptoms of psychopathology.ResultsA higher-order model with four first-order dimensions (Fear, Distress, Externalising and Thought Disorder) and a higher-order p dimension provided satisfactory model fit, and a bifactor representation provided superior model fit. Bifactor p and higher-order p were highly correlated (r = 0.97) indicating that both parametrisations produce near equivalent general dimensions of psychopathology. Latent variable models including predictor variables showed that the risk variables explained more variance in higher-order p than bifactor p. The higher-order model produced more interpretable associations for the first-order/specific dimensions compared to the bifactor model.ConclusionsThe higher-order representation of p, as described in the Hierarchical Taxonomy of Psychopathology, appears to be a more appropriate way to conceptualise the general dimension of psychopathology than the bifactor approach. The research and clinical implications of these discrepant ways of modelling p are discussed.

Irritability and aggression (IA) are highly prevalent in individuals with autism spectrum disorder (ASD). Although clinical correlates of IA in this population have been previously examined, findings from existing studies capturing symptoms as a set of latent variables do not fully explain meaningful associations between the symptoms themselves. In the present study, we conducted network analysis which conceptualizes mental health difficulties as a complex network of directly associated symptoms in 2612 individuals who were diagnosed with ASD through rigorous diagnostic assessment and who were enrolled in the Simons Simplex Collection. Using the Aberrant Behavior Checklist, a validated scale, we investigated the network structure of IA and tried to identify bridge symptoms that link IA and other symptom domains. In our analysis, irritability symptoms had stronger and more direct associations with other nodes than aggression symptoms did. Additionally, depressed mood and oppositionality were identified to function as bridge symptoms. The network structures did not differ between individuals with and without intellectual disability. Our findings indicate that addressing these bridge symptoms through integrated care combining different modalities of treatment could ease the complicated symptom network and thereby reduce IA symptoms in individuals with ASD.

ImportanceHow population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, with impacts on health inequalities unclear.ObjectiveWe investigated changes in mental health and sociodemographic inequalities from before and across the first year of the COVID-19 pandemic in 11 longitudinal studies.Design, Setting and ParticipantsData from 11 UK longitudinal population-based studies with pre-pandemic measures of psychological distress were jointly analysed and estimates pooled. Multi-level regression was used to examine changes in psychological distress from pre-pandemic to during the first year of the COVID-19 pandemic.ExposuresTrends in the prevalence of poor mental health were assessed pre-pandemic (TP0) and at three pandemic time periods: initial lockdown (TP1, Mar-June 20); easing of restrictions (TP2, July-Oct 20); and a subsequent lockdown (TP3, Nov 20-Mar 21). We stratified analyses by sex, ethnicity, education, age, and UK country.Main Outcomes and MeasuresPsychological distress was assessed using the General Health Questionnaire 12 (GHQ-12), Kessler-6, 9-item Malaise Inventory, Short Mood and Feelings Questionnaire (SMFQ), Patient Health Questionnaire-8 and 9 (PHQ-8/9), Hospital Anxiety and Depression Scale (HADS) and Centre for Epidemiological Studies – Depression (CES-D), across different studies.ResultsIn total, 49,993 adult participants (61.2% female; 8.7% Non-White) were analysed. Across the 11 studies, mental health deteriorated from pre-pandemic scores across all three pandemic time periods, but with considerable heterogeneity across the study-specific effect sizes estimated (pooled estimate TP1 Standardised Mean Difference (SMD): 0.15 (95% CI: 0.06, 0.25); TP2 SMD: 0.18 (0.09, 0.27); TP3 SMD: 0.21 (0.10, 0.32)). Changes in psychological distress across the pandemic were higher in females (TP3 SMD: 0.23 (0.11, 0.35)) than males (TP3 SMD: 0.16 (0.06, 0.26)), and lower in below-degree level educated persons at TP3 (SMD: 0.18 (0.06, 0.30)) compared to those who held degrees (SMD: 0.26 (0.14, 0.38)). Increased psychological distress was most prominent amongst adults aged 25-34 and 35-44 years compared to other age groups. We did not find evidence of changes in distress differing by ethnicity or UK country.Conclusions and RelevanceThe substantial deterioration in mental health seen in the UK during the first lockdown did not reverse when lockdown lifted, and a sustained worsening was observed across the pandemic. Mental health declines have been unequal across the population, with females, those with higher degrees, and those aged 25-44 years more affected.

BackgroundThe COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable.AimsQuantify mental health inequalities in disruptions to healthcare, economic activity and housing.MethodWe examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies.ResultsAcross the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3–33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20–1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09–1.41) for disruption to procedures to 1.33 (95% CI 1.20–1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06–1.21) and income (OR 1.12, 95% CI 1.06 –1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00–1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18–1.32) or in one domain (OR 1.11, 95% CI 1.07–1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97–1.03).ConclusionsPeople experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities.

Background The COVID-19 pandemic with its associated virus suppression measures have disrupted many domains of life for many people. Increasingly it is recognised that negative disruptive impacts of the pandemic are not experienced equally and may exacerbate existing inequalities. People already suffering from psychological distress may have been especially vulnerable to disruptions. We investigated associations between pre-pandemic psychological distress and disruptions to healthcare, economic activity, and housing, and whether these associations were moderated by age, sex, ethnicity or education. Methods Data were from 59,482 participants in 12 UK longitudinal adult population surveys with both pre-pandemic and COVID-19 surveys. Participants self-reported disruptions since the start of the pandemic to: healthcare (medication access, procedures, or appointments); economic activity (negative changes in employment, income or working hours); and housing (change of address or household composition). These were also combined into a cumulative measure indicating how many of these three domains had been disrupted. Logistic regression models were used within each study to estimate associations between pre-pandemic standardised psychological distress scores and disruption outcomes. Analyses were weighted for sampling design and attrition, and adjusted for age, sex, education, ethnicity, and UK country. Findings were synthesised using a random effects meta-analysis with restricted maximum likelihood. Effect modification by sex, education, ethnicity and age was assessed using group-difference tests during meta-analysis. Results While exact prevalence varied between studies, pre-pandemic psychological distress was generally more common among women, ethnic minorities, younger age groups, and those with less education. One standard deviation higher psychological distress was associated with raised odds of health care disruptions (OR 1.40; 95% CI: 1.29–1.51; Heterogeneity I2: 79.4%) and with experiencing disruptions in two or more of the three domains examined (OR 1.22; 95% CI: 1.14–1.31; Heterogeneity I2: 75.8%), but not specifically with disruptions to economic activity (OR 1.03; 95% CI: 0.95–1.13; Heterogeneity I2: 89.5%) or housing (OR 1.00; 95% CI: 0.97–1.03; Heterogeneity I2: 0.0%). We did not find evidence of these associations differing by sex, ethnicity, education, or age group. Conclusion Those suffering from psychological distress before the pandemic have been more likely to experience healthcare disruptions during the pandemic, and clusters of disruptions across multiple life domains. Individuals suffering from distress may need additional support to manage these disruptions, especially in relation to healthcare. Otherwise, considering psychological distress was already unequally distributed, the pandemic may exacerbate existing inequalities related to gender, ethnicity, education and age.

Background While research demonstrates that somatisation is highly correlated with post-traumatic stress disorder (PTSD), the relationship between International Classification of Diseases 11th edition (ICD-11) PTSD, complex PTSD (CPTSD) and somatisation has not previously been determined. Objective To determine the relationship between frequency and severity of somatisation and ICD-11 PTSD/CPTSD. Method This cross-sectional study included 222 individuals recruited to the National Centre for Mental Health (NCMH) PTSD cohort. We assessed rates of Patient Health Questionnaire 15 (PHQ-15) somatisation stratified by ICD-11 PTSD/CPTSD status. Path analysis was used to explore the relationship between PTSD/CPTSD and somatisation, including number of traumatic events, age, and gender as controls. Results 70% (58/83) of individuals with CPTSD had high PHQ-15 somatisation symptom severity compared with 48% (12/25) of those with PTSD (chi-square: 95.1, p value, Highlights • People with CPTSD had a higher prevalence of co-morbid somatisation. • People with CPTSD had a worse somatisation symptom severity. • The core features of PTSD predicted somatisation.

Cross-study research initiatives to understand change across time are an increasingly prominent component of social and health sciences, yet they present considerable practical, analytical and conceptual challenges. First, we discuss the key challenges to comparative research as a basis for detecting societal change, as well as possible solutions. We focus on studies which investigate changes across time in outcome occurrence or the magnitude and/or direction of associations. We discuss the use and importance of such research, study inclusion, sources of bias and mitigation, and interpretation. Second, we propose a structured framework (a checklist) that is intended to provide guidance for future authors and reviewers. Third, we outline a new open-access teaching resource that offers detailed instruction and reusable analytical syntax to guide newcomers on techniques for conducting comparative analysis and data visualisation (in both R and Stata formats).The online version contains supplementary material available at 10.1007/s44155-022-00021-1.

Valid inference from the investigation of mental health relies – among others – on the assumption of no measurement error. However, it is well known that data from self-reported measures are likely to be biased by some process that is driven by the respondent’s personality and/or circumstances. We capitalised on data available in two nationally representative birth cohorts, the National Child Development Study (1958 birth cohort) and the 1970 British Cohort Study to formally test the longitudinal measurement equivalence of the nine-item version of the Malaise Inventory, a measure of psychological distress. The inclusion of identical assessments of mental health in adulthood in both cohorts allowed us to evaluate their measurement properties and investigate whether the passage of time has differentially affected the interpretation of mental health assessments. To do so, we employed methods within the generalised latent variable measurement modelling framework and related extensions for formally testing measurement invariance. We found that the passage of two decades and more in both cohorts have not influenced how participants respond to the short version of the Malaise Inventory. The observed scalar invariance of the short version of the Malaise Inventory implies that potential sources of bias such as age effects, survey design, period effects, or cohort specific effects did not influence the way participants in the two cohorts respond to the symptoms described in the Malaise Inventory. Our results offer some reassurance for the extent to which self-reported mental health survey questions are affected by systematic sources of error.

Loneliness is a common experience in adolescence and is related to a range of mental health problems. Such feelings may have been increased by social distancing measures introduced during the COVID-19 pandemic. We aimed to investigate the effect of loneliness, social contact, and parent relationships on adolescent mental health during lockdown in the UK. Young people aged 11–16 years (n = 894) completed measures of loneliness, social contact, parent-adolescent relationships, and mental health difficulties during the first 11 weeks of lockdown and one-month later (n = 443). We examined cross-sectional associations and longitudinal relationships between loneliness, social contact, and parent relationships and subsequent mental health. Adolescents who reported higher loneliness had significantly higher symptoms of mental health difficulties during lockdown. We found that adolescents who had closer relationships with their parents reported significantly less severe symptoms of mental health difficulties and lower levels of loneliness. We also found that adolescents who spent more time texting others reported higher symptoms of mental health difficulties. Our hypothesis that loneliness would predict poorer mental health one month later was not supported. Time spent texting others at baseline was significantly associated with higher hyperactivity at follow-up, and closeness to parents was significantly associated with lower psychological distress at follow-up. We conclude that while loneliness was associated with greater mental health difficulties at baseline, it did not predict increased mental health difficulties one month later. Moreover, existing mental health problems significantly predicted later increase, thereby highlighting the importance of continuing support for vulnerable people.

BackgroundHealth systems worldwide have faced major disruptions due to COVID-19 which could exacerbate health inequalities. The UK National Health Service (NHS) provides free healthcare and prioritises equity of delivery, but the pandemic may be hindering the achievement of these goals. We investigated associations between multiple social characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions in over 65,000 participants across twelve UK longitudinal studies.MethodsParticipants reported disruptions from March 2020 up to late January 2021. Associations between social characteristics and three types of self-reported healthcare disruption (medication access, procedures, appointments) and a composite of any of these were assessed in logistic regression models, adjusting for age, sex and ethnicity where relevant. Random-effects meta-analysis was conducted to obtain pooled estimates.ResultsPrevalence of disruption varied across studies; between 6.4% (TwinsUK) and 31.8 % (Understanding Society) of study participants reported any disruption. Females (Odd Ratio (OR): 1.27 [95%CI: 1.15,1.40]; I2=53%), older persons (e.g. OR: 1.39 [1.13,1.72]; I2=77% for 65-75y vs 45-54y), and Ethnic minorities (excluding White minorities) (OR: 1.19 [1.05,1.35]; I2=0% vs White) were more likely to report healthcare disruptions. Those in a more disadvantaged social class (e.g. OR: 1.17 [1.08, 1.27]; I2=0% for manual/routine vs managerial/professional) were also more likely to report healthcare disruptions, but no clear differences were observed by education levels.ConclusionThe COVID-19 pandemic has led to unequal healthcare disruptions, which, if unaddressed, could contribute to the maintenance or widening of existing health inequalities.

Depression and anxiety are highly comorbid constructs. However little is known about the mechanisms that underpin this comorbidity/connectivity or the divergence between constructs that seems to occur in adolescence. The current study targeted emotion regulation (ER) as a potential plausible mechanism for explaining how anxiety and depression symptoms in adolescence might begin to connect, perpetuate, and ultimately diverge from one another. Using data from a cross-sectional school-based study, of adolescent females (age 11–18 years; N = 615; majority were white (97.7%)), we modelled variation in ER using latent profile analysis. Then, using network analysis (NA), we generated separate depression-anxiety symptom networks for adolescents at varying levels of ER. Three latent classes of ER were identified (low ER 15%, intermediate ER 34%, high ER 51%). The results of the network comparison test found no significant differences in global strength between the ‘low ER’ and the ‘intermediate ER’ ability network. This study is among the first to attempt to model change in depression-anxiety symptom connectivity in adolescence in relation to a common contextual/risk factor. The current study therefore offers a unique contribution to the examination of the role of transdiagnostic factors in the study of adolescent depression and anxiety from a network perspective, and provides a promising framework for the study of ER among anxiety and depression symptomatology in adolescence.

Background The COVID-19 pandemic and its associated virus suppression measures have disrupted lives and livelihoods, potentially exacerbating inequalities. People already experiencing mental ill-health may have been especially vulnerable to disruptions. Aim Investigate associations between pre-pandemic psychological distress and disruptions during the pandemic to (1) healthcare, economic activity, and housing, (2) cumulative disruptions and 3) whether these differ by age, sex, ethnicity or education. Methods Data were from 59,482 participants in 12 UK longitudinal adult population surveys with data collected both prior to and during the COVID-19 pandemic. Participants self-reported disruptions since the start of the pandemic to: healthcare (medication access, procedures, or appointments); economic activity (negative changes in employment, income or working hours); and housing (change of address or household composition). Logistic regression models were used within each study to estimate associations between pre-pandemic psychological distress scores and disruption outcomes. Findings were synthesised using a random effects meta-analysis with restricted maximum likelihood. Results Between one to two-thirds of study participants experienced at least one disruption during the pandemic, with 2.3-33.2% experiencing disruptions in 2 or more of the 3 domains examined. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; 95% CI: 1.20 to 1.40) with fully adjusted ORs ranging from 1.33 [1.20 to 1.49] for disruptions to prescriptions or medication access and 1.24 [1.09 to 1.41] for disruption to procedures; (ii) loss of employment (OR=1.13 [1.06 to 1.21]) and income (OR=1.12 [1.06 to 1.19]) and reductions in working hours/furlough (OR=1.05 [1.00 to 1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97 to 1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18 to 1.32]) or in one domain (OR=1.11 [1.07 to 1.16]) relative to experiencing no disruption. We did not find evidence of these associations differing by sex, ethnicity, education level, or age. Conclusion Those suffering from psychological distress before the pandemic were more likely to experience healthcare disruptions, economic disruptions related to unemployment and loss of income, and to clusters of disruptions across multiple domains during the pandemic. Considering mental ill-health was already unequally distributed in the UK population, the pandemic may exacerbate existing mental health inequalities. Individuals with poor mental health may need additional support to manage these pandemic-associated disruptions.

Importance How population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, and the consequences for health inequalities are unclear.Objective To investigate changes in mental health and sociodemographic inequalities from before and across the first year of the COVID-19 pandemic in 11 longitudinal studies.Design, Setting, and Participants This cohort study included adult participants from 11 UK longitudinal population-based studies with prepandemic measures of psychological distress. Analyses were coordinated across these studies, and estimates were pooled. Data were collected from 2006 to 2021.Exposures Trends in the prevalence of poor mental health were assessed in the prepandemic period (time period 0 [TP 0]) and at 3 pandemic TPs: 1, initial lockdown (March to June 2020); 2, easing of restrictions (July to October 2020); and 3, a subsequent lockdown (November 2020 to March 2021). Analyses were stratified by sex, race and ethnicity, education, age, and UK country.Main Outcomes and Measures Multilevel regression was used to examine changes in psychological distress from the prepandemic period across the first year of the COVID-19 pandemic. Psychological distress was assessed using the 12-item General Health Questionnaire, the Kessler 6, the 9-item Malaise Inventory, the Short Mood and Feelings Questionnaire, the 8-item or 9-item Patient Health Questionnaire, the Hospital Anxiety and Depression Scale, and the Centre for Epidemiological Studies–Depression across different studies.Results In total, 49 993 adult participants (12 323 [24.6%] aged 55-64 years; 32 741 [61.2%] women; 4960 [8.7%] racial and ethnic minority) were analyzed. Across the 11 studies, mental health deteriorated from prepandemic scores across all 3 pandemic periods, but there was considerable heterogeneity across the study-specific estimated effect sizes (pooled estimate for TP 1: standardized mean difference [SMD], 0.15; 95% CI, 0.06-0.25; TP 2: SMD, 0.18; 95% CI, 0.09-0.27; TP 3: SMD, 0.21; 95% CI, 0.10-0.32). Changes in psychological distress across the pandemic were higher in women (TP 3: SMD, 0.23; 95% CI, 0.11, 0.35) than men (TP 3: SMD, 0.16; 95% CI, 0.06-0.26) and lower in individuals with below–degree level education at TP 3 (SMD, 0.18; 95% CI, 0.06-0.30) compared with those who held degrees (SMD, 0.26; 95% CI, 0.14-0.38). Increased psychological distress was most prominent among adults aged 25 to 34 years (SMD, 0.49; 95% CI, 0.14-0.84) and 35 to 44 years (SMD, 0.35; 95% CI, 0.10-0.60) compared with other age groups. No evidence of changes in distress differing by race and ethnicity or UK country were observed.Conclusions and Relevance In this study, the substantial deterioration in mental health seen in the UK during the first lockdown did not reverse when lockdown lifted, and a sustained worsening was observed across the pandemic period. Mental health declines have been unequal across the population, with women, those with higher degrees, and those aged 25 to 44 years more affected than other groups.

Posttraumatic stress disorder (PTSD) and physical health problems, particularly somatic symptom disorder, are highly comorbid. Studies have only examined this co-occurrence at the disorder level rather than assessing the associations between specific symptoms. Using network analysis to identify symptoms that act as bridges between these disorders may allow for the development of interventions to specifically target this comorbidity. We examined the association between somatization and PTSD symptoms via network analysis. This included 349 trauma-exposed individuals recruited through the National Centre for Mental Health PTSD cohort who completed the Clinician-Administered PTSD Scale for DSM-5 and the Patient Health Questionnaire-15. A total of 215 (61.6%) individuals met the DSM-5 diagnostic criteria for PTSD. An exploratory graph analysis identified four clusters of densely connected symptoms within the overall network: PTSD, chronic pain, gastrointestinal issues, and more general somatic complaints. Sleep difficulties played a key role in bridging PTSD and somatic symptoms. Our network analysis demonstrates the distinct nature of PTSD and somatization symptoms, with this association connected by disturbed sleep.