Very little is known about the mental health of the adult population of Ukraine following Russia’s full-scale invasion in February 2022. In this study, we estimated the prevalence of seven mental health disorders, the proportion of adults screening positive for any disorder, and the sociodemographic factors associated with meeting requirements for each and any disorder.

A non-probability quota sample (N = 2,050) of adults living in Ukraine in September 2023 was collected online. Participants completed self-report questionnaires of the seven mental health disorders. Logistic regression was used to determine the predictors of the different disorders.

Prevalence estimates ranged from 1.5% (cannabis use disorder) to 15.2% (generalized anxiety disorder), and 36.3% screened positive for any of the seven disorders. Females were significantly more likely than males (39.0% vs. 33.8%) to screen positive for any disorder. Disruption to life due to Russia’s 2014 invasion of Ukraine, greater financial worries, and having fewer positive childhood experiences were consistent risk factors for different mental health disorders and for any or multiple disorders.

Our findings show that approximately one in three adults living in Ukraine report problems consistent with meeting diagnostic requirements for a mental health disorder 18 months after Russia’s full-scale invasion. Ukraine’s mental healthcare system has been severely compromised by the loss of infrastructure and human capital due to the war. These findings may help to identify those most vulnerable so that limited resources can be used most effectively.

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.

International Classification of Diseases, 11th revision (ICD-11) adjustment disorder (AjD) is characterized by two main symptom clusters: preoccupation with the stressor and failure to adapt to the stressor. The network analytic approach provides important information on the structural validity of a disorder and reveals which symptoms are most prominent. To date, no study compared the network structure of AjD symptoms in clinical and nonclinical samples, which could potentially inform our understanding of psychopathological mechanisms that underlie AjD and identify core targets for therapy.

A network analysis was conducted on AjD symptoms as assessed by the Adjustment Disorder—New Module (ADNM-8) using data from 330 clinical participants from the UK and a nonclinical sample of 699 participants from Switzerland.

Comparisons of network structure invariance revealed differences between the network structure of the clinical and the nonclinical samples. Results highlight that in terms of both edges strength and centrality, failure to adapt symptoms was more prominent in the clinical sample, while the preoccupation symptoms were more prominent in the nonclinical sample. Importantly, global strength was similar across networks.

Results provide evidence of the coherence of AjD in the ICD-11 as assessed by the ADNM questionnaire. They tentatively suggest that subclinical AjD may be characterized by emerging preoccupation symptoms that may result in failure to adapt and functional impairment in clinical manifestation of AjD. However, there is a need for replication and longitudinal research to further validate this hypothesis.

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.

Posttraumatic stress disorder (PTSD) is traditionally understood as a disorder that occurs more commonly in women than in men, and in younger age groups than in older age groups. The objective of this study was to determine if these patterns are also observed in relation to International Classification of Diseases (ICD-11) PTSD and complex PTSD (CPTSD).

Secondary data analysis was performed using data collected from three nationally representative samples from the Republic of Ireland (N = 1,020), the United States (N = 1,839), and Israel (N = 1,003), and one community sample from the United Kingdom (N = 1,051).

Estimated prevalence rates of ICD-11 PTSD were higher in women than in men in each sample, and at a level consistent with existing data derived from Diagnostic and Statistics Manual of Mental Disorders (DSM)-based models of PTSD. Furthermore, rates of ICD-11 PTSD were generally lower in older age groups for men and women. For CPTSD, there was inconsistent evidence of sex and age differences, and some indication of a possible interaction between these two demographic variables.

Despite considerable revisions to PTSD in ICD-11, the same sex and age profile was observed to previous DSM-based models of PTSD. CPTSD, however, does not appear to show the same sex and age differences as PTSD. Theoretical models that seek to explain sex and age differences in trauma-related psychopathology may need to be reconsidered given the distinct effects for ICD-11 PTSD and CPTSD.

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.

Adjustment disorder is one of the most widespread mental disorders worldwide. In ICD-11, adjustment disorder is characterised by two main symptom clusters: preoccupation with the stressor and failure to adapt. A network analytic approach has been applied to most ICD-11 stress-related disorders. However, no study to date has explored the relationship between symptoms of adjustment disorder using network analysis.

We aimed to explore the network structure of adjustment disorder symptoms and whether its structure replicates across questionnaire versions and samples.

A network analysis was conducted on adjustment disorder symptoms as assessed by the Adjustment Disorder–New Module (ADNM-8) and an ultra-brief version (ADNM-4) using data from 2524 participants in Nigeria (n = 1006), Kenya (n = 1018) and Ghana (n = 500).

There were extensive connections between items across all samples in both ADNM versions. Results highlight that preoccupation symptoms seem to be more prominent in terms of edges strengths (i.e. connections) and had the highest centrality in all networks across samples and ADNM versions. Comparisons of network structure invariance revealed one difference between Nigeria and Ghana in both ADNM versions. Importantly, the ADNM-8 global strength was similar in all networks whereas in the ADNM-4 Kenya had a higher global strength score compared with Nigeria

Results provide evidence of the coherence of adjustment disorder in ICD-11 as assessed by the ADNM questionnaire. The prominence of preoccupation symptoms in adjustment disorder highlights a possible therapeutic target to alleviate distress. There is a need to further replicate the network structure of adjustment disorder in non-African samples.

The unprecedented occurrence of a global pandemic is accompanied by both physical and psychological burdens that may impair quality of life. Research relating to COVID-19 aims to determine the effects of the pandemic on vulnerable populations who are at high risk of developing negative health or psychosocial outcomes. Having an ongoing medical condition during a pandemic may lead to greater psychological distress. Increased psychological distress may be due to preventative public health measures (e.g. lockdown), having an ongoing medical condition, or a combination of these factors.

This study analyses data from an online cross-sectional national survey of adults in Ireland and investigates the relationship between comorbidity and psychological distress. Those with a medical condition (n = 128) were compared to a control group without a medical condition (n = 128) and matched according to age, gender, annual income, education, and work status during COVID-19. Participants and data were obtained during the first public lockdown in Ireland (27 March 2020–8 June 2020).

Individuals with existing medical conditions reported significantly higher levels of anxiety (p < .01) and felt less gratitude (p ≤ .001). Exploratory analysis indicated that anxiety levels were significantly associated with illness perceptions specific to COVID-19. Post hoc analysis revealed that psychological well-being was not significantly related to condition type (e.g. respiratory disorders).

This research supports individualised supports for people with ongoing medical conditions during the COVID-19 pandemic, and has implications for the consideration of follow-up care specifically for mental health. Findings may also inform future public health policies and post-vaccine support strategies for vulnerable populations.

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.

To determine (i) whether distinct groups of infants under 6 months old (U6M) were identifiable as malnourished based on anthropometric measures and if so to determine the probability of admittance to GOAL Ethiopia’s Management of At Risk Mothers and Infants (MAMI) programme based on group membership; (ii) whether there were discrepancies in admission using recognised anthropometric criteria, compared with group membership and (iii) the barriers and potential solutions to identifying malnutrition within U6M.

Mixed-methods approaches were used, whereby data collected by GOAL Ethiopia underwent: factor mixture modelling, χ2 analysis and logistic regression analysis. Qualitative analysis was performed through coding of key informant interviews.

Data were collected in two refugee camps in Ethiopia. Key informant interviews were conducted remotely with international MAMI programmers and nutrition experts.

Participants were 3444 South-Sudanese U6M and eleven key informants experienced in MAMI programming.

Well-nourished and malnourished groups were identified, with notable discrepancies between group membership and MAMI programme admittance. Despite weight for age z-scores (WAZ) emerging as the most discriminant measure to identify malnutrition, admittance was most strongly associated with mid-upper arm circumference (MUAC). Misconceptions surrounding malnutrition, a dearth of evidence and issues with the current identification protocol emerged as barriers to identifying malnutrition among U6M.

Our model suggests that WAZ is the most discriminating anthropometric measure for malnutrition in this population. However, the challenges of using WAZ should be weighed up against the more scalable, but potentially overly sensitive and less accurate use of MUAC among U6M.

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.

Veterans with post-traumatic stress disorder (PTSD) typically report a poorer treatment response than those who have not served in the Armed Forces. A possible explanation is that veterans often present with complex symptoms of PTSD. ICD-11 PTSD and complex PTSD (CPTSD) have not previously been explored in a military sample.

This study aimed to validate the only measure of ICD-11 PTSD and CPTSD, the International Trauma Questionnaire, and assess the rates of the disorder in a sample of treatment-seeking UK veterans.

A sample of help-seeking veterans (N = 177) was recruited from a national charity in the UK that provides clinical services to veterans. Participants completed measures of ICD-11 PTSD and CPTSD as well as childhood and adult traumatic life events. Confirmatory factor analysis was used to assess the latent structure of PTSD and CPTSD symptoms, and rates of the disorders were estimated.

The majority of the participants (70.7%) reported symptoms consistent with a diagnosis of either PTSD or CPTSD. Results indicated the presence of two separate disorders, with CPTSD being more frequently endorsed (56.7%) than PTSD (14.0%). CPTSD was more strongly associated with childhood trauma than PTSD.

The International Trauma Questionnaire can adequately distinguish between PTSD and CPTSD within clinical samples of veterans. There is a need to explore the effectiveness of existing and new treatments for CPTSD in military personnel.