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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.
A recent suicidal drive hypothesis posits that psychotic experiences (PEs) may serve to externalize internally generated and self-directed threat (i.e., self-injurious/suicidal behavior [SIB]) in order to optimize survival; however, it must first be demonstrated that such internal threat can both precede and inform PEs. The current study conducted the first known bidirectional analysis of SIB and PEs to test whether SIB could be considered as a plausible antecedent for PEs. Prospective data were utilized from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative birth cohort of 2232 twins, that captured SIB (any self-harm or suicidal attempt) and PEs at ages 12 and 18 years. Cross-lagged panel models demonstrated that the association between SIB at age 12 and PEs at age 18 was as strong as the association between PEs at age 12 and SIB at age 18. Indeed, the best representation of the data was a model where these paths were constrained to be equal (OR = 2.48, 95% CI = 1.63–3.79). Clinical interview case notes for those who reported both SIB and PEs at age 18, revealed that PEs were explicitly characterized by SIB/threat/death-related content for 39% of cases. These findings justify further investigation of the suicidal drive hypothesis.
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.
Objectives: Down syndrome (DS) is a population with known hippocampal impairment, with studies showing that individuals with DS display difficulties in spatial navigation and remembering arbitrary bindings. Recent research has also demonstrated the importance of the hippocampus for novel word-learning. Based on these data, we aimed to determine whether individuals with DS show deficits in learning new labels and if they may benefit from encoding conditions thought to be less reliant on hippocampal function (i.e., through fast mapping). Methods: In the current study, we examined immediate, 5-min, and 1-week delayed word-learning across two learning conditions (e.g., explicit encoding vs. fast mapping). These conditions were examined across groups (twenty-six 3- to 5-year-old typically developing children and twenty-six 11- to 28-year-old individuals with DS with comparable verbal and nonverbal scores on the Kaufman Brief Intelligence Test – second edition) and in reference to sleep quality. Results: Both individuals with and without DS showed retention after a 1-week delay, and the current study found no benefit of the fast mapping condition in either group contrary to our expectations. Eye tracking data showed that preferential eye movements to target words were not present immediately but emerged after 1-week in both groups. Furthermore, sleep measures collected via actigraphy did not relate to retention in either group. Conclusions: This study presents novel data on long-term knowledge retention in reference to sleep patterns in DS and adds to a body of knowledge helping us to understand the processes of word-learning in typical and atypically developing populations. (JINS, 2018, 24, 955–965)
Background: The prevalence of mental health difficulties in Northern Ireland (NI) is significantly higher than in England. In recent years, there have been extensive consultations, and subsequent recommendations made in NI in an effort to address this. Aims: The current study aims to evaluate the effectiveness of an ‘Improving Access to Psychological Therapies’ (IAPT) stepped care service model using low-intensity cognitive behavioural therapy (LI-CBT) in primary and community care settings. Method: A pilot intervention trial design utilized two standardized outcome measures (PHQ-9 and GAD-7) before treatment (at baseline), during treatment (in every session) and at discharge (at final session). Results: Preliminary reliable change outcomes for the pilot cohorts showed a recovery rate of 47.9%, improvement rate of 76.7% and deterioration rate of 6%. Conclusions: These findings suggest that the IAPT service model is clinically effective in the NI population. Data collection for the larger study was completed in December 2017. Future analyses will include follow-up data collected at 4 months post-treatment, and will also aim to identify individual and service level factors that potentially impact treatment effectiveness.
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.
Significant new opportunities for astrophysics and cosmology have been identified at low radio frequencies. The Murchison Widefield Array is the first telescope in the southern hemisphere designed specifically to explore the low-frequency astronomical sky between 80 and 300 MHz with arcminute angular resolution and high survey efficiency. The telescope will enable new advances along four key science themes, including searching for redshifted 21-cm emission from the EoR in the early Universe; Galactic and extragalactic all-sky southern hemisphere surveys; time-domain astrophysics; and solar, heliospheric, and ionospheric science and space weather. The Murchison Widefield Array is located in Western Australia at the site of the planned Square Kilometre Array (SKA) low-band telescope and is the only low-frequency SKA precursor facility. In this paper, we review the performance properties of the Murchison Widefield Array and describe its primary scientific objectives.
This work addresses the need for thick layers of ferroelectric thin films on semiconductors for integrated optics applications. The deposition of BaTiO3 thin films with MgO buffers on patterned GaAs substrates is presented as an approach to achieve crack-free optical waveguiding structures. Cracking and peeling of the thin films are observed on patterns with lateral dimensions exceeding 60 microns and nearly crack-free thin films for patterns with lateral dimensions of a few microns. The cracking and peeling of the thin films is attributed to thermal expansion mismatch during the heating and cooling steps of the deposition process. A thin film stress and fracture model is used to analyze the phenomenon. Reduced cracking and peeling on the patterned features are attributed to strain relief on the patterned features. The inclusion of thick AlxOy buffer layers obtained through wet-oxidation of AlGaAs prior to BaTiO3/MgO deposition are presented as a means of obtaining electro-optic waveguide structures on GaAs.