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The COVID-19 pandemic has impacted community mental health, but the effect on psychiatric admissions is unknown. We investigated factors contributing to acute psychiatric admissions, and whether this changed during the first UK lockdown.
A retrospective case-note review study with an exploratory mixed-methods design was used to examine factors in psychiatric admissions following the first UK 2020 lockdown compared to the same time periods in 2019 and 2018.
Themes of psychopathology, risk, social stressors, community treatment issues, and physical health concerns were generated. The mean number of codes per case was 6⋅19 (s.d. = 2⋅43), with a mean number of categories per case of 3⋅73, (s.d. = 0⋅98). Changes in routines and isolation were common factors in the study year; accommodation and substance abuse were more prominent in the control year. Relationship stressors featured strongly in both groups. There were significantly more women (χ2(1, N = 98) = 20⋅80, p < 0⋅00001) and older adults (χ2(1, N = 98) = 8⋅61, p = 0⋅0033) in the study group than the control. Single people, compared to those in a relationship (χ2(1, N = 45) = 4.46, p = 0⋅035), and people with affective disorders compared to psychotic disorders ((χ2(1, N = 28) = 5.19, p = 0⋅023), were more likely to have a COVID-19 related admission factor.
The COVID-19 pandemic amplified pre-existing psychosocial vulnerabilities with a disproportionate psychiatric admissions impact on the mental health of women, the elderly and those with affective disorders.
Recently the NHS has expanded the provision of liaison mental health services (LMHS) to ensure that every acute hospital with an emergency department in England has a liaison psychiatry service. Little work has been undertaken to explore first-hand experiences of these services. The aim of this study was to capture service users’ experiences of LMHS in both emergency departments and acute inpatient wards in the UK, with a view to adapt services to better meet the needs of its users.
This cross-sectional internet survey was initially advertised from May-July 2017 using the social media platform Facebook. Due to a paucity of male respondents, it was re-run from November 2017-February 2018, specifically targeting this demographic group. 184 people responded to the survey, of which 147 were service users and 37 were service users’ accompanying partners, friends or family members. The survey featured a structured questionnaire divided into three categories: the profile of the respondent, perceived professionalism of LMHS, and overall opinion of the service. Space was available for free-text comments in each section. Descriptive analysis of quantitative data was undertaken with R statistical software V.3.2.2. Qualitative data from free-text comments were transcribed and interpreted independently by three researchers using framework analysis; familiarisation with the data was followed by identification of a thematic framework, indexing, charting, mapping and interpretation.
Opinions of the service were mixed but predominantly negative. 31% of service users and 27% of their loved ones found their overall contact with LMHS useful. Features most frequently identified as important were the provision of a 24/7 service, assessment by a variety of healthcare professionals and national standardisation of services. Respondents indicated that the least important feature was the provision of a separate service for older people. They also expressed that a desirable LMHS would include faster assessments following referral from the parent team, clearer communication about next steps and greater knowledge of local services and third sector organisations.
Our survey identified mixed responses, however service users and their loved ones perceived LMHS more frequently as negative than positive. This may be attributed to the recent governmental drive to assess, treat and discharge 95% of all patients seen in emergency departments within four hours of initial attendance. Additionally, dissatisfied service users are more likely to volunteer their opinions. The evaluation and adaptation of LMHS should be prioritised to enhance their inherent therapeutic value and improve engagement with treatment and future psychiatric care.
Psychosis is a major mental illness with first onset in young adults. The prognosis is poor in around half of the people affected, and difficult to predict. The few tools available to predict prognosis have major weaknesses which limit their use in clinical practice. We aimed to develop and validate a risk prediction model of symptom non-remission in first-episode psychosis.
Our development cohort consisted of 1027 patients with first-episode psychosis recruited between 2005 to 2010 from 14 early intervention services across the National Health Service in England. Our validation cohort consisted of 399 patients with first-episode psychosis recruited between 2006 to 2009 from a further 11 English early intervention services. The one-year non-remission rate was 52% and 54% in the development and validation cohorts, respectively. Multivariable logistic regression was used to develop a risk prediction model for non-remission, which was externally validated.
The prediction model showed good discrimination (C-statistic of 0.74 (0.72, 0.76) and adequate calibration with intercept alpha of 0.13 (0.03, 0.23) and slope beta of 0.99 (0.87, 1.12). Our model improved the net-benefit by 16% at a risk threshold of 50%, equivalent to 16 more detected non-remitted first-episode psychosis individuals per 100 without incorrectly classifying remitted cases.
Once prospectively validated, our first episode psychosis prediction model could help identify patients at increased risk of non-remission at initial clinical contact.
Perceived discrimination is associated with worse mental health. Few studies have assessed whether perceived discrimination (i) is associated with the risk of psychotic disorders and (ii) contributes to an increased risk among minority ethnic groups relative to the ethnic majority.
We used data from the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions Work Package 2, a population-based case−control study of incident psychotic disorders in 17 catchment sites across six countries. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) for the associations between perceived discrimination and psychosis using mixed-effects logistic regression models. We used stratified and mediation analyses to explore differences for minority ethnic groups.
Reporting any perceived experience of major discrimination (e.g. unfair treatment by police, not getting hired) was higher in cases than controls (41.8% v. 34.2%). Pervasive experiences of discrimination (≥3 types) were also higher in cases than controls (11.3% v. 5.5%). In fully adjusted models, the odds of psychosis were 1.20 (95% CI 0.91–1.59) for any discrimination and 1.79 (95% CI 1.19–1.59) for pervasive discrimination compared with no discrimination. In stratified analyses, the magnitude of association for pervasive experiences of discrimination appeared stronger for minority ethnic groups (OR = 1.73, 95% CI 1.12–2.68) than the ethnic majority (OR = 1.42, 95% CI 0.65–3.10). In exploratory mediation analysis, pervasive discrimination minimally explained excess risk among minority ethnic groups (5.1%).
Pervasive experiences of discrimination are associated with slightly increased odds of psychotic disorders and may minimally help explain excess risk for minority ethnic groups.
Psychosis rates are higher among some migrant groups. We hypothesized that psychosis in migrants is associated with cumulative social disadvantage during different phases of migration.
We used data from the EUropean Network of National Schizophrenia Networks studying Gene-Environment Interactions (EU-GEI) case–control study. We defined a set of three indicators of social disadvantage for each phase: pre-migration, migration and post-migration. We examined whether social disadvantage in the pre- and post-migration phases, migration adversities, and mismatch between achievements and expectations differed between first-generation migrants with first-episode psychosis and healthy first-generation migrants, and tested whether this accounted for differences in odds of psychosis in multivariable logistic regression models.
In total, 249 cases and 219 controls were assessed. Pre-migration (OR 1.61, 95% CI 1.06–2.44, p = 0.027) and post-migration social disadvantages (OR 1.89, 95% CI 1.02–3.51, p = 0.044), along with expectations/achievements mismatch (OR 1.14, 95% CI 1.03–1.26, p = 0.014) were all significantly associated with psychosis. Migration adversities (OR 1.18, 95% CI 0.672–2.06, p = 0.568) were not significantly related to the outcome. Finally, we found a dose–response effect between the number of adversities across all phases and odds of psychosis (⩾6: OR 14.09, 95% CI 2.06–96.47, p = 0.007).
The cumulative effect of social disadvantages before, during and after migration was associated with increased odds of psychosis in migrants, independently of ethnicity or length of stay in the country of arrival. Public health initiatives that address the social disadvantages that many migrants face during the whole migration process and post-migration psychological support may reduce the excess of psychosis in migrants.
The clinical course of psychotic disorders is highly variable. Typically, researchers have captured different course types using broad pre-defined categories. However, whether these adequately capture symptom trajectories of psychotic disorders has not been fully assessed. Using data from AESOP-10, we sought to identify classes of individuals with specific symptom trajectories over a 10-year follow-up using a data-driven approach.
AESOP-10 is a follow-up, at 10 years, of 532 incident cases with a first episode of psychosis initially identified in south-east London and Nottingham, UK. Using extensive information on fluctuations in the presence of psychotic symptoms, we fitted growth mixture models to identify latent trajectory classes that accounted for heterogeneity in the patterns of change in psychotic symptoms over time.
We had sufficient data on psychotic symptoms during the follow-up on 326 incident patients. A four-class quadratic growth mixture model identified four trajectories of psychotic symptoms: (1) remitting-improving (58.5%); (2) late decline (5.6%); (3) late improvement (5.4%); (4) persistent (30.6%). A persistent trajectory, compared with remitting-improving, was associated with gender (more men), black Caribbean ethnicity, low baseline education and high disadvantage, low premorbid IQ, a baseline diagnosis of non-affective psychosis and long DUP. Numbers were small, but there were indications that those with a late decline trajectory more closely resembled those with a persistent trajectory.
Our current approach to categorising the course of psychotic disorders may misclassify patients. This may confound efforts to elucidate the predictors of long-term course and related biomarkers.
In Europe, the incidence of psychotic disorder is high in certain migrant and minority ethnic groups (hence: ‘minorities’). However, it is unknown how the incidence pattern for these groups varies within this continent. Our objective was to compare, across sites in France, Italy, Spain, the UK and the Netherlands, the incidence rates for minorities and the incidence rate ratios (IRRs, minorities v. the local reference population).
The European Network of National Schizophrenia Networks Studying Gene–Environment Interactions (EU-GEI) study was conducted between 2010 and 2015. We analyzed data on incident cases of non-organic psychosis (International Classification of Diseases, 10th edition, codes F20–F33) from 13 sites.
The standardized incidence rates for minorities, combined into one category, varied from 12.2 in Valencia to 82.5 per 100 000 in Paris. These rates were generally high at sites with high rates for the reference population, and low at sites with low rates for the reference population. IRRs for minorities (combined into one category) varied from 0.70 (95% CI 0.32–1.53) in Valencia to 2.47 (95% CI 1.66–3.69) in Paris (test for interaction: p = 0.031). At most sites, IRRs were higher for persons from non-Western countries than for those from Western countries, with the highest IRRs for individuals from sub-Saharan Africa (adjusted IRR = 3.23, 95% CI 2.66–3.93).
Incidence rates vary by region of origin, region of destination and their combination. This suggests that they are strongly influenced by the social context.
First episode psychosis (FEP) patients who use cannabis experience more frequent psychotic and euphoric intoxication experiences compared to controls. It is not clear whether this is consequent to patients being more vulnerable to the effects of cannabis use or to their heavier pattern of use. We aimed to determine whether extent of use predicted psychotic-like and euphoric intoxication experiences in patients and controls and whether this differs between groups.
We analysed data on patients who had ever used cannabis (n = 655) and controls who had ever used cannabis (n = 654) across 15 sites from six countries in the EU-GEI study (2010–2015). We used multiple regression to model predictors of cannabis-induced experiences and to determine if there was an interaction between caseness and extent of use.
Caseness, frequency of cannabis use and money spent on cannabis predicted psychotic-like and euphoric experiences (p ⩽ 0.001). For psychotic-like experiences (PEs) there was a significant interaction for caseness × frequency of use (p < 0.001) and caseness × money spent on cannabis (p = 0.001) such that FEP patients had increased experiences at increased levels of use compared to controls. There was no significant interaction for euphoric experiences (p > 0.5).
FEP patients are particularly sensitive to increased psychotic-like, but not euphoric experiences, at higher levels of cannabis use compared to controls. This suggests a specific psychotomimetic response in FEP patients related to heavy cannabis use. Clinicians should enquire regarding cannabis related PEs and advise that lower levels of cannabis use are associated with less frequent PEs.
The ‘jumping to conclusions’ (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.
A total of 817 first episode psychosis patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC, and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.
The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia polygenic risk score was non-significantly associated with a higher number of beads drawn (B = 0.47, 95% CI −0.21 to 1.16, p = 0.17); whereas IQ PRS (B = 0.51, 95% CI 0.25–0.76, p < 0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with the higher level of psychotic-like experiences (PLEs) in controls, including after controlling for IQ (B = −1.7, 95% CI −2.8 to −0.5, p = 0.006), but did not relate to delusions in patients.
Our findings suggest that the JTC reasoning bias in psychosis might not be a specific cognitive deficit but rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to PLEs, independent of IQ. The work has the potential to inform interventions targeting cognitive biases in early psychosis.
Increasing evidence suggests psychosis may be more meaningfully viewed in dimensional terms rather than as discrete categorical states and that specific symptom clusters may be identified. If so, particular risk factors and premorbid factors may predict these symptom clusters.
(i) To explore, using principal component analysis, whether specific factors for psychotic symptoms can be isolated. (ii) To establish the predictors of the different symptom factors using multiple regression techniques.
One hundred and eighty-nine inpatients with psychotic illness were recruited and information on family history, premorbid factors and current symptoms obtained from them and their mothers.
Seven distinct symptom components were identified. Regression analysis failed to identify any developmental predictors of depression or mania. Delusions/hallucinations were predicted by a family history of schizophrenia and by poor school functioning in spite of normal premorbid IQ (F = 6.5; P < 0.001); negative symptoms by early onset of illness, developmental delay and a family history of psychosis (F = 4.1; P = 0.04). Interestingly disorganisation was predicted by the combination of family history of bipolar disorder and low premorbid IQ (F = 4.9; P = 0.003), and paranoia by obstetric complications (OCs) and poor school functioning (F = 4.2; P = 0.01).
Delusions and hallucinations, negative symptoms and paranoia all appeared to have a developmental origin though they were associated with different childhood problems. On the other hand, neither mania nor depression was associated with childhood dysfunction. Our most striking finding was that disorganisation appeared to arise when a familial predisposition to mania was compounded by low premorbid IQ.
To test the hypothesis that recent onset psychotic patients who use cannabis will have psychotic symptoms that are more severe and more persistent than those who do not use cannabis.
Subjects and methods
We carried out a 4-year follow-up study of a cohort of 119 patients with recent onset of psychosis. The patients were divided into four groups according to duration of cannabis use, taking index admission and follow-up as reference points.
Those subjects who persisted in the use of cannabis had more positive (but not negative) symptoms and a more continuous illness at follow-up.
The main limitations of the study were: the relatively small sample size, and that the excess of male subjects and the presence of cannabis induced psychosis could have a confusing impact on the interpretation of the results.
It is possible that psychotic patients who use cannabis are at a greater risk of a more continuous illness with more positive symptoms than those who do not.
While it is known that patients with schizophrenia recognize facial emotions, specifically negative emotions, less accurately, little is known about how they misattribute these emotions to other emotions and whether such misattribution biases are associated with symptoms, course of the disorder, or certain cognitive functions.
Outpatients with schizophrenia or schizoaffective disorder (n = 73) and healthy controls (n = 30) performed a computerised Facial Emotion Attribution Test and Wisconsin Card Sorting Test (WCST). Patients were also rated on the Positive and Negative Syndrome Scale (PANSS).
Patients were poor at recognizing fearful and angry emotions and attributed fear to angry and angry to neutral expressions. Fear-as-anger misattributions were predicted independently by a longer duration of illness and WCST perseverative errors.
The findings show a bias towards misattributing fearful and angry facial emotions. The propensity for fear-as-anger misattribution biases increases as the length of time that the disorder is experienced increases and a more rigid style of information processing is used. This, at least in part, may be perpetuated by subtle fearfulness expressed by others while interacting with people with schizophrenia.
Daily use of high-potency cannabis has been reported to carry a high risk for developing a psychotic disorder. However, the evidence is mixed on whether any pattern of cannabis use is associated with a particular symptomatology in first-episode psychosis (FEP) patients.
We analysed data from 901 FEP patients and 1235 controls recruited across six countries, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. We used item response modelling to estimate two bifactor models, which included general and specific dimensions of psychotic symptoms in patients and psychotic experiences in controls. The associations between these dimensions and cannabis use were evaluated using linear mixed-effects models analyses.
In patients, there was a linear relationship between the positive symptom dimension and the extent of lifetime exposure to cannabis, with daily users of high-potency cannabis having the highest score (B = 0.35; 95% CI 0.14–0.56). Moreover, negative symptoms were more common among patients who never used cannabis compared with those with any pattern of use (B = −0.22; 95% CI −0.37 to −0.07). In controls, psychotic experiences were associated with current use of cannabis but not with the extent of lifetime use. Neither patients nor controls presented differences in depressive dimension related to cannabis use.
Our findings provide the first large-scale evidence that FEP patients with a history of daily use of high-potency cannabis present with more positive and less negative symptoms, compared with those who never used cannabis or used low-potency types.
Ethnic minority groups in Western countries face an increased risk of psychotic disorders. Causes of this long-standing public health inequality remain poorly understood. We investigated whether social disadvantage, linguistic distance and discrimination contributed to these patterns.
We used case–control data from the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study, carried out in 16 centres in six countries. We recruited 1130 cases and 1497 population-based controls. Our main outcome measure was first-episode ICD-10 psychotic disorder (F20–F33), and exposures were ethnicity (white majority, black, mixed, Asian, North-African, white minority and other), generational status, social disadvantage, linguistic distance and discrimination. Age, sex, paternal age, cannabis use, childhood trauma and parental history of psychosis were included as a priori confounders. Exposures and confounders were added sequentially to multivariable logistic models, following multiple imputation for missing data.
Participants from any ethnic minority background had crude excess odds of psychosis [odds ratio (OR) 2.03, 95% confidence interval (CI) 1.69–2.43], which remained after adjustment for confounders (OR 1.61, 95% CI 1.31–1.98). This was progressively attenuated following further adjustment for social disadvantage (OR 1.52, 95% CI 1.22–1.89) and linguistic distance (OR 1.22, 95% CI 0.95–1.57), a pattern mirrored in several specific ethnic groups. Linguistic distance and social disadvantage had stronger effects for first- and later-generation groups, respectively.
Social disadvantage and linguistic distance, two potential markers of sociocultural exclusion, were associated with increased odds of psychotic disorder, and adjusting for these led to equivocal risk between several ethnic minority groups and the white majority.
Explanations for the successes or failures of militaries in both war and peace have traditionally focused on key factors such as technology, leadership, personnel, training, or a combination of all of these. A more recent addition to the list of possible variables contributing to military effectiveness is the concept of organizational culture – the pattern of shared assumptions that an organization learns as it solves problems, that has worked well enough to be considered valid, and that is therefore taught to new members as the correct way to approach those problems. This chapter combines the organizational culture concepts of Edgar Schein with the nine cultural dimensions of the GLOBE research program. The resulting model provides a useful framework to analyze a military’s organizational culture. Perhaps more importantly, the model also provides prescriptive actions leaders can take to align a military’s organizational culture with its mission and environment.
Culture has enormous influence on military organizations. One can broadly define organizational culture as the assumptions, ideas, norms, and beliefs, expressed or reflected in symbols, rituals, myths, and practices, that shape how an organization functions and adapts to external stimuli and that give meaning to its members. Except in unique circumstances, culture grows slowly, embedding itself so deeply that members often act unconsciously according to its dictates. Because culture lies hidden under more visible organizational doctrine and symbols, one can easily overlook its power. Culture creates organizational identity and establishes expectations of how group members will act. Three important external factors impact military culture: geography, history, and the environment in which navies, armies, and air forces exist. Of all the factors involved in military effectiveness, culture is perhaps the most important. Yet it also remains the most difficult to understand, because it involves so many external factors that distort its formation and continuities, even in different military organizations within the same nation. Organizational culture will shape how military organizations respond to challenges. The hardship is that changing military culture represents an extraordinarily difficult task that may require years, if not decades, to accomplish.
Culture is a key determinant in organizational effectiveness and plays an enormous role in the lives of military organizations. Cultural biases often result in unstated assumptions that have a deep impact on strategy, operational planning, doctrinal creation, and organization and training of armed forces. The impact of culture on military affairs often remains opaque for years, if not decades, after the events it has affected. Leadership is essential to creating and maintaining organizational culture. Leaders who can shape an organization’s culture from its inception have an outsized influence on its future orientation. Leaders, therefore, must be discriminating when establishing the initial culture of an organization, for once embedded, that culture will prove extraordinarily difficult to change. But even superb leaders are limited. Selection of the right subordinate leaders is critical if an organization’s culture is to survive a leadership transition. Some military organizations do change, assisted by cultures that embrace innovation and a reasonable degree of risk-taking. Organizational culture takes on the characteristics of wider societal culture, but when the military becomes a caste apart, the result can be the degradation of its ethical foundations. Military organizations often have subcultures with significant influence on the larger organization. Technology-centric forces must not allow a culture focused on technological excellence to turn into one centered on technological determinism. Professional military education is critical in sustaining organizational culture.
Dissatisfaction with the Royal Navy’s World War I performance led a generation of officers to analyze the fleet’s wartime record. This analysis revealed three problems: over-centralization of authority, a reluctance to fight night actions, and an overly defensive use of destroyers. In an effort to correct these issues, the Royal Navy made changes to its doctrine, training, and professional military education that improved the Navy’s World War II performance, especially in surface warfare. Reforms flowed from a variety of sources, including First Sea Lord Adm. David Beatty, contributors to the Naval Review, and Mediterranean Fleet exercise. The interwar reforms reflected an organizational culture that pursued improvement and learning in response to the perception that in World War I, the Navy failed to live up to historical standards of success.