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’.

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’].

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.

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.

Current information about the prevalence of various mental health disorders in the general adult population of the Republic of Ireland is lacking. In this study, we examined the prevalence of 12 common mental disorders, the proportion of adults who screened positive for any disorder, the sociodemographic factors associated with meeting criteria for a disorder and the associations between each disorder and history of attempted suicide.

A non-probability nationally representative sample (N = 1110) of adults living in Ireland completed self-report measures of 12 mental health disorders. Effect sizes were calculated using odds ratios from logistic regression models, and population attributable risk fractions (PAFs) were estimated to quantify the associations between each disorder and attempted suicide.

Prevalence rates ranged from 15.0% (insomnia disorder) to 1.7% (histrionic personality disorder). Overall, 42.5% of the sample met criteria for a mental health disorder, and 11.1% had a lifetime history of attempted suicide. Younger age, being a shift worker and trauma exposure were independently associated with a higher likelihood of having a mental health disorder, while being in university was associated with a lower likelihood of having a disorder. ICD-11 complex posttraumatic stress disorder, borderline personality disorder and insomnia disorder had the highest PAFs for attempted suicide.

Mental health disorder prevalence in Ireland is relatively high compared to international estimates. The findings are discussed in relation to important mental health policy implications.

Prospective studies are needed to assess the influence of pre-pandemic risk factors on mental health outcomes following the COVID-19 pandemic. From direct interviews prior to (T1), and then in the same individuals after the pandemic onset (T2), we assessed the influence of personal psychiatric history on changes in symptoms and wellbeing.

Two hundred and four (19–69 years/117 female) individuals from a multigenerational family study were followed clinically up to T1. Psychiatric symptom changes (T1-to-T2), their association with lifetime psychiatric history (no, only-past, and recent psychiatric history), and pandemic-specific worries were investigated.

At T2 relative to T1, participants with recent psychopathology (in the last 2 years) had significantly fewer depressive (mean, M = 41.7 v. 47.6) and traumatic symptoms (M = 6.6 v. 8.1, p < 0.001), while those with no and only-past psychiatric history had decreased wellbeing (M = 22.6 v. 25.0, p < 0.01). Three pandemic-related worry factors were identified: Illness/death, Financial, and Social isolation. Individuals with recent psychiatric history had greater Illness/death and Financial worries than the no/only-past groups, but these worries were unrelated to depression at T2. Among individuals with no/only-past history, Illness/death worries predicted increased T2 depression [B = 0.6(0.3), p < 0.05].

As recent psychiatric history was not associated with increased depression or anxiety during the pandemic, new groups of previously unaffected persons might contribute to the increased pandemic-related depression and anxiety rates reported. These individuals likely represent incident cases that are first detected in primary care and other non-specialty clinical settings. Such settings may be useful for monitoring future illness among newly at-risk individuals.

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.

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.

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.

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.

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.

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.

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.

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.

The COVID-19 pandemic has created an unprecedented global crisis, necessitating drastic changes to living conditions, social life, personal freedom and economic activity. No study has yet examined the presence of psychiatric symptoms in the UK population under similar conditions.

We investigated the prevalence of COVID-19-related anxiety, generalised anxiety, depression and trauma symptoms in the UK population during an early phase of the pandemic, and estimated associations with variables likely to influence these symptoms.

Between 23 and 28 March 2020, a quota sample of 2025 UK adults aged 18 years and older, stratified by age, gender and household income, was recruited by online survey company Qualtrics. Participants completed standardised measures of depression, generalised anxiety and trauma symptoms relating to the pandemic. Bivariate and multivariate associations were calculated for demographic and health-related variables.

Higher levels of anxiety, depression and trauma symptoms were reported compared with previous population studies, but not dramatically so. Anxiety or depression and trauma symptoms were predicted by young age, presence of children in the home, and high estimates of personal risk. Anxiety and depression were also predicted by low income, loss of income and pre-existing health conditions in self and others. Specific anxiety about COVID-19 was greater in older participants.

This study showed a modest increase in the prevalence of mental health problems in the early stages of the pandemic, and these problems were predicted by several specific COVID-related variables. Further similar surveys, particularly of those with children at home, are required as the pandemic progresses.

Dimensional 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.

A trauma exposed community sample from the United Kingdom (N = 1051) completed self-report measures of 49 symptoms of psychopathology.

A 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.

The 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.

Research indicates that anti-depressant prescribing is higher in Northern Ireland (NI) than in the rest of the UK, and that socio-economic and area-level factors may contribute to this. The current study provides comprehensive population-based estimates of the prevalence of anti-depressant prescription prescribing in NI from 2011 to 2015, and examined the associations between socio-demographic, socio-economic, self-reported health and area-level factors and anti-depressant prescription.

Data were derived from the 2011 NI Census (N = 1 588 355) and the Enhanced Prescribing Database. Data linkage techniques were utilised through the Administrative Data Research Centre in NI. Prevalence rates were calculated and binary logistic analysis assessed the associations between contextual factors and anti-depressant prescription.

From 2011 to 2015, the percentages of the population in NI aged 16 or more receiving anti-depressant prescriptions were 12.3%, 12.9%, 13.4%, 13.9% and 14.3%, respectively, and over the 5-year period was 24.3%. The strongest predictors of anti-depressant prescription in the multivariate model specified were ‘very bad’ (OR = 4.02) or ‘Bad’ general health (OR = 3.98), and self-reported mental health problems (OR = 3.57). Other significant predictors included social renting (OR = 1.67) and unemployment (OR = 1.25). Protective factors included Catholic religious beliefs, other faith/philosophic beliefs and no faith/philosophic beliefs in comparison to reporting Protestant/other Christian religious beliefs (ORs = 0.78–0.91).

The prevalence of anti-depressant prescription in NI appears to be higher than the prevalence of depressive disorders, although this may not necessarily be attributable to over-prescribing as anti-depressants are also prescribed for conditions other than depression. Anti-depressant prescription was linked to several factors that represent socio-economic disadvantage.

Death by suicide is often preceded by attempted suicide, suicidal ideation and non-suicidal self-injury. These extreme thoughts and behaviours have been considered in terms of a continuum of suicidality. Little known research, however, has considered a suicide continuum that extends beyond these extreme thoughts and behaviours and incorporates a much wider array of phenomena that may vary in severity and may constitute a broader negative self-evaluation (NSE) continuum.

Harvesting key indicators of NSE from a British epidemiological survey (N = 8580), the current study used exploratory factor analysis, confirmatory factor analysis and factor mixture modelling to (i) identify the dimensional structure of NSE in the general population and (ii) profile the distribution of the resultant NSE dimensions. Multinomial logistic regression was then used to differentiate between classes using an array of risk variables, psychopathology outcome variables and a suicide attempt indicator.

A 4-factor model that reflected graded levels of NSE was identified; (F1) Low self-worth & subordination (F2) depression, (F3) suicidal thoughts, (F4) self-harm (SH). Seven classes suggested a clear pattern of NSE severity. Classes characterised by higher levels across the dimensions exhibited greater risk and poorer outcomes. The greatest risk for suicide attempt was associated with a class characterised by engagement in SH behaviour.

Low self-worth, subordination and depression, while representative of distinct groups in the population are also highly prevalent in those who entertain suicidal thoughts and engage in SH behaviour. The findings promote further investigation into the genesis and evolution of suicidality and internal threat.

Recent studies point to overlap between neuropsychiatric disorders in symptomatology and genetic aetiology.

To systematically investigate genomics overlap between childhood and adult attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and major depressive disorder (MDD).

Analysis of whole-genome blood gene expression and genetic risk scores of 318 individuals. Participants included individuals affected with adult ADHD (n = 93), childhood ADHD (n = 17), MDD (n = 63), ASD (n = 51), childhood dual diagnosis of ADHD–ASD (n = 16) and healthy controls (n = 78).

Weighted gene co-expression analysis results reveal disorder-specific signatures for childhood ADHD and MDD, and also highlight two immune-related gene co-expression modules correlating inversely with MDD and adult ADHD disease status. We find no significant relationship between polygenic risk scores and gene expression signatures.

Our results reveal disorder overlap and specificity at the genetic and gene expression level. They suggest new pathways contributing to distinct pathophysiology in psychiatric disorders and shed light on potential shared genomic risk factors.