National Psychiatric Morbidity Survey Research Articles

Disentangling heterogeneity of psychosis expression in the general population: sex-specific moderation effects of environmental risk factors on symptom networks.

Psychosis expression in the general population may reflect a behavioral manifestation of the risk for psychotic disorder. It can be conceptualized as an interconnected system of psychotic and affective experiences; a so-called 'symptom network'. Differences in demographics, as well as exposure to adversities and risk factors, may produce substantial heterogeneity in symptom networks, highlighting potential etiological divergence in psychosis risk. To explore this idea in a data-driven way, we employed a novel recursive partitioning approach in the 2007 English National Survey of Psychiatric Morbidity (N = 7242). We sought to identify 'network phenotypes' by explaining heterogeneity in symptom networks through potential moderators, including age, sex, ethnicity, deprivation, childhood abuse, separation from parents, bullying, domestic violence, cannabis use, and alcohol. Sex was the primary source of heterogeneity in symptom networks. Additional heterogeneity was explained by interpersonal trauma (childhood abuse and domestic violence) in women and domestic violence, cannabis use, ethnicity in men. Among women, especially those exposed to early interpersonal trauma, an affective loading within psychosis may have distinct relevance. Men, particularly those from minority ethnic groups, demonstrated a strong network connection between hallucinatory experiences and persecutory ideation. Symptom networks of psychosis expression in the general population are highly heterogeneous. The structure of symptom networks seems to reflect distinct sex-related adversities, etiologies, and mechanisms of symptom-expression. Disentangling the complex interplay of sex, minority ethnic group status, and other risk factors may help optimize early intervention and prevention strategies in psychosis.

The mental health of ex-prisoners: analysis of the 2014 English National Survey of Psychiatric Morbidity

PurposePrisoners experience extremely high rates of psychiatric disturbance. However, ex-prisoners have never previously been identified in representative population surveys to establish how far this excess persists after release. Our purpose was to provide the first community-based estimate of ex-prisoners’ mental health in England using the data from the 2014 Adult Psychiatric Morbidity Survey (APMS).MethodsAPMS 2014 provides cross-sectional data from a random sample (N = 7546) of England’s household population aged 16 or above. Standardised instruments categorised psychiatric disorders and social circumstances. Participants who had been in prison were compared with the rest of the sample.ResultsOne participant in seventy had been in prison (1.4%; 95% CI 1.1–1.7; n = 103). Ex-prisoners suffered an excess of current psychiatric problems, including common mental disorders (CMDs), psychosis, post-traumatic disorder, substance dependence, and suicide attempts. They were more likely to screen positive for attention-deficit/hyperactivity disorder and autistic traits, to have low verbal IQ, and to lack qualifications. They disclosed higher rates of childhood adversity, including physical and sexual abuse and local authority care. The odds (1.88; 95% CI 1.02–3.47) of CMDs were nearly doubled in ex-prisoners, even after adjusting for trauma and current socioeconomic adversity.ConclusionsPrison experience is a marker of enduring psychiatric vulnerability, identifying an important target population for intervention and support. Moreover, the psychiatric attributes of ex-prisoners provide the context for recidivism. Without effective liaison between the criminal justice system and mental health services, the vulnerability of ex-prisoners to relapse and to reoffending will continue, with consequent personal and societal costs.

S4. IDENTIFYING HETEROGENEITY IN SYMPTOM NETWORKS IN THE GENERAL POPULATION: A RECURSIVE PARTITIONING APPROACH

BackgroundNetwork models of psychopathology have gained increasing ground recently. It is suggested that psychopathology arises from the reciprocal associations between symptoms and other psycho-biological factors. Given the heterogeneity in psychopathological phenomena, it seems likely that subgroups with distinct network structures may emerge given different demographic and environmental risk factors. Thus, the identification of heterogeneity in symptom networks associated with specific variables may promote an understanding of the mechanisms that underlie the relation between environmental factors and psychopathology.MethodsWe took a recursive partitioning approach based on conditional inference trees that iteratively splits the sample of interest based on a predefined set of covariates to detect subgroups with significantly different network structures, resulting in a network tree. We used general population data from the 2000 and 2007 English National Survey of Psychiatric Morbidity, with a combined sample size of n = 15,983 (age range: 16–95 years, 55.9% female), to model networks of psychotic experiences (hallucinations, persecutory ideation) and affective symptoms (worry, mood instability, depression, anxiety, sleep problems). Split variables explored as sources of heterogeneity in networks were sex, age, and exposure to environmental risk factors (cannabis use in past month, lifetime sexual abuse, lifetime experience of bullying). We used a stop-splitting rule based on Bonferroni-adjusted p-values to determine the final tree size (α = .01).ResultsEnvironmental factors were the primary sources of heterogeneity in network structures, with exposure to these factors being linked to more densely connected networks. Globally, cannabis use was associated with particularly strong connections between hallucinations and persecutory ideation, depression and persecutory ideation, and depression and mood instability. In those participants with cannabis use and experiences of sexual abuse, the association between depression and persecutory ideation was particularly strong, and further, strong connections were present between the affective symptoms. Similarly, those with exposure to both cannabis and bullying showed stronger associations involving sleep problems than participants exposed to either bullying or cannabis alone. Exposure to either bullying or sexual abuse without concurrent cannabis use was linked to a strongly connected cluster of worry, anxiety, and depression, with only weak associations to other symptoms. Lastly, the sample was split at 60 years of age. The younger group was divided further by age, with participants younger than 26 years showing stronger associations between hallucinations and persecutory ideation and worry and depression than those older than 26 years. In participants older than 60 years, another split was made by gender: women showed a more densely connected network than men.DiscussionFindings from this exploratory analysis document substantial heterogeneity in symptom network structures in a large general population sample. Exposure to risk factors is linked to more strongly connected, probably less resilient symptom networks, with evidence for additive vulnerability given the presence of several risk factors. Exposure to sexual abuse or bullying mainly seems to relate to higher connectivity of affective symptoms, while cannabis use links to higher connection of psychotic symptoms with each other, but also with affective symptoms. The analysis also highlights demographic variables as sources of heterogeneity in symptom networks, pointing to specifically relevant symptom interactions in subgroups of age and gender.

Revisiting the one in four: the prevalence of psychiatric disorder in the population of England 2000-2014.

Mental health problems are often said to affect one in four people in Britain, although with no consistent explanation of what the figure includes. We used three English national population surveys of psychiatric morbidity from 2000, 2007 and 2014 to provide prevalence rates for recent psychiatric problems. We combined disorders progressively to demonstrate the effects of cumulation. Psychosis had a prevalence of around 1%, severe common mental disorders added about 8%, and including less-severe common mental disorders gave a value around one in six. The figure of one in four required the inclusion of various other disorders. These values were strikingly stable over the surveys.

Relationship between living alone and common mental disorders in the 1993, 2000 and 2007 National Psychiatric Morbidity Surveys.

Given the high prevalence of common mental disorders (CMDs) and individuals living alone in the United Kingdom, the goal of this study using English nationally representative data was to examine the association between living alone and CMDs, and to identify potential mediating factors of this association. The data were drawn from the 1993, 2000 and 2007 National Psychiatric Morbidity Surveys. CMDs were assessed using the Clinical Interview Schedule-Revised (CIS-R), a questionnaire focusing on past week neurotic symptoms. The presence of CMDs was defined as a CIS-R total score of 12 and above. Multivariable logistic regression and mediation analyses were conducted to analyze the association between living alone and CMDs, and to identify mediators in this association. The prevalence of CMDs was higher in individuals living alone than in those not living alone in all survey years. Multivariable analysis showed a positive association between living alone and CMDs in all survey years (1993: odds ratio [OR] = 1.69; 2000: OR = 1.63; and 2007: OR = 1.88). Overall, loneliness explained 84% of the living alone-CMD association. Living alone was positively associated with CMDs. Interventions addressing loneliness among individuals living alone may be particularly important for the mental wellbeing of this vulnerable population.

Links between psychotic and neurotic symptoms in the general population: an analysis of longitudinal British National Survey data using Directed Acyclic Graphs.

Non-psychotic affective symptoms are important components of psychotic syndromes. They are frequent and are now thought to influence the emergence of paranoia and hallucinations. Evidence supporting this model of psychosis comes from recent cross-fertilising epidemiological and intervention studies. Epidemiological studies identify plausible targets for intervention but must be interpreted cautiously. Nevertheless, causal inference can be strengthened substantially using modern statistical methods. Directed Acyclic Graphs were used in a dynamic Bayesian network approach to learn the overall dependence structure of chosen variables. DAG-based inference identifies the most likely directional links between multiple variables, thereby locating them in a putative causal cascade. We used initial and 18-month follow-up data from the 2000 British National Psychiatric Morbidity survey (N = 8580 and N = 2406). We analysed persecutory ideation, hallucinations, a range of affective symptoms and the effects of cannabis and problematic alcohol use. Worry was central to the links between symptoms, with plausible direct effects on insomnia, depressed mood and generalised anxiety, and recent cannabis use. Worry linked the other affective phenomena with paranoia. Hallucinations were connected only to worry and persecutory ideation. General anxiety, worry, sleep problems, and persecutory ideation were strongly self-predicting. Worry and persecutory ideation were connected over the 18-month interval in an apparent feedback loop. These results have implications for understanding dynamic processes in psychosis and for targeting psychological interventions. The reciprocal influence of worry and paranoia implies that treating either symptom is likely to ameliorate the other.

The network structure of paranoia in the general population

PurposeBebbington and colleagues’ influential study on ‘the structure of paranoia in the general population’ used data from the British National Psychiatric Morbidity Survey and latent variable analysis methods. Network analysis is a relatively new approach in psychopathology research that considers mental disorders to be emergent phenomena from causal interactions among symptoms. This study re-analysed the British National Psychiatric Morbidity Survey data using network analysis to examine the network structure of paranoia in the general population.MethodsWe used a Graphical Least Absolute Shrinkage and Selection Operator (glasso) method that estimated an optimal network structure based on the Extended Bayesian Information Criterion. Network sub-communities were identified by spinglass and EGA algorithms and centrality metrics were calculated per item and per sub-community.ResultsWe replicated Bebbington’s four component structure of paranoia, identifying ‘interpersonal sensitivities’, ‘mistrust’, ‘ideas of reference’ and ‘ideas of persecution’ as sub-communities in the network. In line with previous experimental findings, worry was the most central item in the network. However, ‘mistrust’ and ‘ideas of reference’ were the most central sub-communities.ConclusionsRather than a strict hierarchy, we argue that the structure of paranoia is best thought of as a heterarchy, where the activation of high-centrality nodes and communities is most likely to lead to steady state paranoia. We also highlight the novel methodological approach used by this study: namely, using network analysis to re-examine a population structure of psychopathology previously identified by latent variable approaches.

Paid employment and common mental disorders in 50–64-year olds: analysis of three cross-sectional nationally representative survey samples in 1993, 2000 and 2007

Associations between employment status and mental health are well recognised, but evidence is sparse on the relationship between paid employment and mental health in the years running up to statutory retirement ages using robust mental health measures. In addition, there has been no investigation into the stability over time in this relationship: an important consideration if survey findings are used to inform future policy. The aim of this study is to investigate the association between employment status and common mental disorder (CMD) in 50-64-year old residents in England and its stability over time, taking advantage of three national mental health surveys carried out over a 14-year period. Data were analysed from the British National Surveys of Psychiatric Morbidity of 1993, 2000 and 2007. Paid employment status was the primary exposure of interest and CMD the primary outcome - both ascertained identically in all three surveys (CMD from the revised Clinical Interview Schedule). Multivariable logistic regression models were used. The prevalence of CMD was higher in people not in paid employment across all survey years; however, this association was only present for non-employment related to poor health as an outcome and was not apparent in those citing other reasons for non-employment. Odds ratios for the association between non-employment due to ill health and CMD were 3.05 in 1993, 3.56 in 2000, and 2.80 in 2007, after adjustment for age, gender, marital status, education, social class, housing tenure, financial difficulties, smoking status, recent physical health consultation and activities of daily living impairment. The prevalence of CMD was higher in people not in paid employment for health reasons, but was not associated with non-employment for other reasons. Associations had been relatively stable in strength from 1993 to 2007 in those three cross-sectional nationally representative samples.

Using Directed Acyclic Graphs in Epidemiological Research in Psychosis: An Analysis of the Role of Bullying in Psychosis.

Modern psychiatric epidemiology researches complex interactions between multiple variables in large datasets. This creates difficulties for causal inference. We argue for the use of probabilistic models represented by directed acyclic graphs (DAGs). These capture the dependence structure of multiple variables and, used appropriately, allow more robust conclusions about the direction of causation. We analyzed British national survey data to assess putative mediators of the association between bullying victimization and persecutory ideation. We compared results using DAGs and the Karlson–Holm–Breen (KHB) logistic regression commands in STATA. We analyzed data from the 2007 English National Survey of Psychiatric Morbidity, using the equivalent 2000 survey in an instant replication. Additional details of methods and results are provided in the supplementary material. DAG analysis revealed a richer structure of relationships than could be inferred using the KHB logistic regression commands. Thus, bullying had direct effects on worry, persecutory ideation, mood instability, and drug use. Depression, sleep and anxiety lay downstream, and therefore did not mediate the link between bullying and persecutory ideation. Mediation by worry and mood instability could not be definitively ascertained. Bullying led to hallucinations indirectly, via persecutory ideation and depression. DAG analysis of the 2000 dataset suggested the technique generates stable results. While causality cannot be fully determined from cross-sectional data, DAGs indicate the relationships providing the best fit. They thereby advance investigation of the complex interactions seen in psychiatry, including the mechanisms underpinning psychiatric symptoms. It may consequently be used to optimize the choice of intervention targets.

Affective instability and impulsivity predict nonsuicidal self-injury in the general population: a longitudinal analysis.

BackgroundImpulsivity and affective instability are related traits known to be associated with nonsuicidal self-injury, although few longitudinal studies have examined this relationship. The purpose of this study was to determine if impulsivity and affective instability predict future nonsuicidal self-injury in the general population while accounting for the overlap between these traits.MethodsLogistic regression analyses were conducted on data from 2344 participants who completed an 18-month follow-up of the 2000 British National Psychiatric Morbidity Survey. Affective instability and impulsivity were assessed at baseline with the Structured Clinical Interview for DSM-IV Axis II Personality Disorders. Nonsuicidal self-injury was assessed at baseline and follow-up during semi-structured interviews.ResultsAffective instability and impulsivity predicted the onset of nonsuicidal self-injury during the follow-up period. Affective instability, but not impulsivity, predicted the continuation of nonsuicidal self-injury during the follow-up period. Affective instability accounted for part of the relationship between impulsivity and nonsuicidal self-injury.ConclusionsAffective instability and impulsivity are important predictors of nonsuicidal self-injury in the general population. It may be more useful to target affective instability over impulsivity for the treatment of nonsuicidal self-injury.

Prevalence and treatment of common mental disorders in the English national population, 1993-2007.

The National Psychiatric Morbidity Surveys include English cross-sectional household samples surveyed in 1993, 2000 and 2007. To evaluate frequency of common mental disorders (CMDs), service contact and treatment. Common mental disorders were identified with the Clinical Interview Schedule - Revised (CIS-R). Service contact and treatment were established in structured interviews. There were 8615, 6126 and 5385 participants aged 16-64. Prevalence of CMDs was consistent (1993: 14.3%; 2000: 16.0%; 2007: 16.0%), as was past-year primary care physician contact for psychological problems (1993: 11.3%; 2000: 12.0%; 2007: 11.7%). Antidepressant receipt in people with CMDs more than doubled between 1993 (5.7%) and 2000 (14.5%), with little further increase by 2007 (15.9%). Psychological treatments increased in successive surveys. Many with CMDs received no treatment. Reduction in prevalence did not follow increased treatment uptake, and may require universal public health measures together with individual pharmacological, psychological and computer-based interventions.

Ethnic inequalities in severe mental disorders: where is the harm?

In this issue, Qassem et al. [1] report novel findings on the relative prevalence of psychotic illness for Black (Caribbean and African) and white people in the UK, using data drawn from three large national surveys of psychiatric morbidity covering the period 1993–2007. The key finding, at least for this reader, is that the odds ratio to have a psychotic illness for Black compared with white people is estimated at 2.7 (albeit with relatively wide confidence intervals of 1.3–5.6). This is the key finding, because, although worryingly high, it is considerably lower than estimates of increased rates of incident psychotic illness among Black Caribbean and Black African people in the UK. One recent study estimated these to be nine and six times higher, respectively [2]. Such high estimates are not exceptional; they have been reported consistently in clinical incidence studies since the early 1970s. However, they are a puzzle, because, as noted by the authors of the current paper [1], two other national surveys, both directed by this author, have also produced relatively low estimates of severe psychotic illness in the Black Caribbean population—odds ratios of 1.8 and 2.0 compared with the white population [3, 4]. Not only is there an inconsistency in estimates of risk between clinical incidence studies and community survey studies, but also an inconsistency when considering rates in the UK and those in the Caribbean, with the much higher rates of first diagnosis being only present in the UK [5]. This suggests that the driver for higher risk (regardless of the extent of that increased risk) is to be found in the postmigration context, a suggestion supported by evidence from other countries. It is not clear how to make sense of such findings. Almost all of the research undertaken points to the greater risk of psychotic illnesses among Black people in the UK (and elsewhere), but the extent and the origins of this difference are in dispute. Disputes about extent of difference point directly to questions of methodology. So how robust are these findings?

Mood instability as a precursor to depressive illness: A prospective and mediational analysis.

Mood instability levels are high in depression, but temporal precedence and potential mechanisms are unknown. Hypotheses tested were as follows: (1) mood instability is associated with depression cross-sectionally, (2) mood instability predicts new onset and maintenance of depression prospectively and (3) the mood instability and depression link are mediated by sleep problems, alcohol abuse and life events. Data from the National Psychiatric Morbidity Survey 2000 at baseline (N = 8580) and 18-month follow-up (N = 2413) were used. Regression modeling controlling for socio-demographic factors, anxiety and hypomanic mood was conducted. Multiple mediational analyses were used to test our conceptual path model. Mood instability was associated with depression cross-sectionally (odds ratio: 5.28; 95% confidence interval: [3.67, 7.59]; p < 0.001) and predicted depression inception (odds ratio: 2.43; 95% confidence interval: [1.03-5.76]; p = 0.042) after controlling for important confounders. Mood instability did not predict maintenance of depression. Sleep difficulties and severe problems with close friends and family significantly mediated the link between mood instability and new onset depression (23.05% and 6.19% of the link, respectively). Alcohol abuse and divorce were not important mediators in the model. Mood instability is a precursor of a depressive episode, predicting its onset. Difficulties in sleep are a significant part of the pathway. Interventions targeting mood instability and sleep problems have the potential to reduce the risk of depression.

Mood Instability as a Precursor to Depressive Illness: Analysis of Data From a Population Survey in Great Britain.

Introduction Levels of mood instability (MI) appear to be high in people with depression, but temporal precedence and possible mechanisms are unknown. Objective We tested hypotheses that: i] MI will be associated with a diagnosis of depression cross-sectionally; ii] MI will predict new onset and maintenance of depression prospectively; iii] the association between MI and depression will be mediated by sleep problems at baseline, new onset alcohol abuse and life events 6 months preceding new onset depression. Method We used data from the National Psychiatric Morbidity Survey 2000 at baseline (N=8580) and 18 month follow-up (N=2413). Regression modelling controlling for socio-demographic factors, anxiety and hypomanic mood was conducted. Multiple mediational analyses were used to test our conceptual path model. Results MI was strongly associated with a diagnosis of depression cross-sectionally (OR: 5.28 (95% CI, 3.67-7.59) p Conclusion Mood instability is a precursor of a depressive episode but does not worsen the course. Interventions targeting mood instability and sleep problems have the potential to reduce the risk of depressio

EPA-0746 – Mood instability and psychosis: analyses of british national survey data

Background We used British national survey data to test specific hypotheses that mood instability 1) is associated with psychosis and individual psychotic phenomena, 2) predicts the later emergence of auditory hallucinations and paranoid ideation, and 3) mediates the link between child sexual abuse and psychosis. Methods We analysed data from the 2000 and 2007 UK national surveys of psychiatric morbidity (N=8580 and 7403 respectively). The 2000 survey included an 18-month follow-up of a subsample (N=2406). Mood instability was assessed from the Structured Clinical Interview for DSMIV Axis II (SCID-II) questionnaire. Our dependent variables comprised auditory hallucinations, paranoid ideation, the presence of psychosis overall, and a 15-item paranoia scale Results Mood Instability was strongly associated in cross-sectional analyses with psychosis (2000 OR: 7.5; 95% CI: I 4.1–13.8; 2007: OR 21.4; CI 9.7–41.2), paranoid ideation (2000: OR: 4.7; CI 4.1–5.4; 2007: OR 5.7; CI 4.9–6.7), auditory hallucinations (2000: OR: 3.4; CI 2.6–4.4; 2007: OR 3.5; CI 2.7–4.7) and paranoia total score (2000: Coefficient: 3.6;CI 3.3–3.9), remaining so after adjustment for current mood state. Baseline mood instability significantly predicted 18-month inceptions of paranoid ideation (OR: 2.3;CI 1.6–3.3) and of auditory hallucinations (OR: 2.6;CI 1.5–4.4). Finally it mediated a third of the total association of child sexual abuse with psychosis and persecutory ideation, and a quarter of that with auditory hallucinations. Conclusions Mood instability is a prominent feature of psychotic experience, and may have a role in its genesis. Targeting mood instability could lead to innovative treatments for psychosis.

Violence, mental health and violence risk factors among community women: an epidemiological study based on two national household surveys in the UK.

BackgroundFemales who perpetrated violence in the community have important mental health and public protection implications. There is a dearth of research in this area. This study investigated the prevalence of psychiatric morbidity, personality disorders as well as victim characteristics and violence risk factors of women in the community who self-reported violence against others.MethodsThe study sample consisted of 8,275 community women aged 16–74 years obtained from the 2000 and 2007 UK national psychiatric morbidity surveys. Self report incidences of violence, personality disorders and the presence of psychiatric symptoms were assessed by interviews and/or established structured psychiatric assessment protocols.ResultsWeighted prevalence of female violence, which primarily involved partners and friends, was 5.5% in 2000 and 5.1% in 2007. Violence-prone women also had significantly higher prevalence of common mental disorders and comorbidity (adjusted odds ratio 3.3 and 2.9 respectively) than non-violent women. Multivariate analyses identified eight significant risk factors that characterized violence prone women: young age, residing in social-assisted housing, presence of early conduct problems, victim of domestic violence, self-harming, excessive drinking and past criminal justice involvements.ConclusionA higher prevalence of common mental disorders and some types of personality disorder was found among violence prone women compared to their non-violence prone counterparts. The identified violence risk factors could be used to develop a quick and easily administered rating tool suitable for use by non-mental health trained frontline workers such as police and social support workers in the community to identify violence-prone women. Mental health and support services then can be provided to them for mental health care and violence prevention purposes.

Mood instability and psychosis: analyses of British national survey data.

Background: We used British national survey data to test specific hypotheses that mood instability (1) is associated with psychosis and individual psychotic phenomena, (2) predicts the later emergence of auditory hallucinations and paranoid ideation, and (3) mediates the link between child sexual abuse and psychosis. Methods: We analyzed data from the 2000 and 2007 UK national surveys of psychiatric morbidity (N = 8580 and 7403, respectively). The 2000 survey included an 18-month follow-up of a subsample (N = 2406). Mood instability was assessed from the Structured Clinical Interview for DSM-IV Axis II (SCID-II) questionnaire. Our dependent variables comprised auditory hallucinations, paranoid ideation, the presence of psychosis overall, and a 15-item paranoia scale. Results: Mood instability was strongly associated in cross-sectional analyses with psychosis (2000: OR: 7.5; 95% CI: I 4.1–13.8; 2007: OR: 21.4; CI: 9.7–41.2), paranoid ideation (2000: OR: 4.7; CI: 4.1–5.4; 2007: OR: 5.7; CI: 4.9–6.7), auditory hallucinations (2000: OR: 3.4; CI: 2.6–4.4; 2007: OR 3.5; CI: 2.7–4.7), and paranoia total score (2000: Coefficient: 3.6; CI: 3.3–3.9), remaining so after adjustment for current mood state. Baseline mood instability significantly predicted 18-month inceptions of paranoid ideation (OR: 2.3; CI: 1.6–3.3) and of auditory hallucinations (OR: 2.6; CI: 1.5–4.4). Finally, it mediated a third of the total association of child sexual abuse with psychosis and persecutory ideation and a quarter of that with auditory hallucinations. Conclusions: Mood instability is a prominent feature of psychotic experience and may have a role in its genesis. Targeting mood instability could lead to innovative treatments for psychosis.

The structure of paranoia in the general population

Psychotic phenomena appear to form a continuum with normal experience and beliefs, and may build on common emotional interpersonal concerns. We tested predictions that paranoid ideation is exponentially distributed and hierarchically arranged in the general population, and that persecutory ideas build on more common cognitions of mistrust, interpersonal sensitivity and ideas of reference. Items were chosen from the Structured Clinical Interview for DSM-IV Axis II Disorders (SCID-II) questionnaire and the Psychosis Screening Questionnaire in the second British National Survey of Psychiatric Morbidity (n = 8580), to test a putative hierarchy of paranoid development using confirmatory factor analysis, latent class analysis and factor mixture modelling analysis. Different types of paranoid ideation ranged in frequency from less than 2% to nearly 30%. Total scores on these items followed an almost perfect exponential distribution (r = 0.99). Our four a priori first-order factors were corroborated (interpersonal sensitivity; mistrust; ideas of reference; ideas of persecution). These mapped onto four classes of individual respondents: a rare, severe, persecutory class with high endorsement of all item factors, including persecutory ideation; a quasi-normal class with infrequent endorsement of interpersonal sensitivity, mistrust and ideas of reference, and no ideas of persecution; and two intermediate classes, characterised respectively by relatively high endorsement of items relating to mistrust and to ideas of reference. The paranoia continuum has implications for the aetiology, mechanisms and treatment of psychotic disorders, while confirming the lack of a clear distinction from normal experiences and processes.

Trends in suicidal ideation in England: the National Psychiatric Morbidity Surveys of 2000 and 2007

Recent falls in suicide rates should be accompanied by a decline in the prevalence of suicidal ideation. We used a pseudo-cohort analytic strategy to examine trends in suicidal ideation measured identically in 2000 and 2007, in nationally representative English probability samples of adults aged ≥ 16 years. Suicidal ideation included tiredness of life, death wishes and thoughts of suicide. Logistic regression models were fitted to estimate trends in age-specific prevalence of suicidal ideation in the past year and past week between 2000 and 2007. There were 6799 participants aged 16-71 years in 2000, and 6815 participants aged 16-78 years in 2007. There was little evidence of trends in prevalence of suicidal ideation, with the exception of women aged 44-50 years in 2007, whose prevalence was unusually high. Prevalence of suicidal ideation in the past year followed a W-shaped profile with age, with peaks at the transition to adulthood, in the forties, and in the oldest participants. Despite falling suicide rates, suicidal ideation did not decline overall between 2000 and 2007. This may indicate the success of the National Suicide Prevention Strategy. Women aged 44-50 years in 2007 were, however, particularly prone to suicidal ideation. As they also have the highest age-adjusted prevalence of common mental disorders and the highest female suicide rate, there are clear implications for treatment access, availability and delivery in primary care.

A model of psychosis and its relationship with impairment

Some studies suggest that positive symptoms of psychosis-clinical and sub-clinical alike-reflect a single, continuously distributed dimension in the population. It is unknown, however, whether such a spectrum of positive psychotic experiences is non-linearly related to outcomes such as daily functioning. This work aims to characterize the relationship between positive psychosis and impairment. Data from the Office of National Statistics National Psychiatric Morbidity Surveys of Great Britain were used to establish measurement models of psychosis and impairment. Competing linear and nonlinear models of the relationship between the two latent variables were evaluated using mixture structural equation models. Positive psychosis is best modeled by a continuous, normal distribution. Increases in positive psychosis correlate with roughly linear increases in impairment. Positive psychotic symptoms occur throughout the population without a discrete, pathological threshold. Functional deficits are linearly associated with the psychosis at all points along the continuum, and a significant portion of the population experiences subclinical psychosis.