Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their predictive efficacies for violence. The effect sizes were extracted from 28 original reports published between 1999 and 2008, which assessed the predictive accuracy of more than one tool. We used a within-subject design to improve statistical power and multilevel regression models to disentangle random effects of variation between studies and tools and to adjust for study features. All 9 tools and their subscales predicted violence at about the same moderate level of predictive efficacy with the exception of Psychopathy Checklist--Revised (PCL-R) Factor 1, which predicted violence only at chance level among men. Approximately 25% of the total variance was due to differences between tools, whereas approximately 85% of heterogeneity between studies was explained by methodological features (age, length of follow-up, different types of violent outcome, sex, and sex-related interactions). Sex-differentiated efficacy was found for a small number of the tools. If the intention is only to predict future violence, then the 9 tools are essentially interchangeable; the selection of which tool to use in practice should depend on what other functions the tool can perform rather than on its efficacy in predicting violence. The moderate level of predictive accuracy of these tools suggests that they should not be used solely for some criminal justice decision making that requires a very high level of accuracy such as preventive detention.

Personality disorder is common in the community, especially in urban areas. Services are normally restricted to symptomatic, help-seeking individuals, but a vulnerable group with cluster B disorders can be identified early, are in care during childhood and enter the criminal justice system when young. This suggests the need for preventive interventions at the public mental health level.

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The Home Office Research Studies are reports on research undertaken by or on behalf of the Home Office. They cover the range of subjects for which the Home Secre t a ry has re s p o n s i b i l i t y. Other publications produced by the Research, Development and Statistics include Findings, Statistical Bulletins and Statistical Papers. RDS is part of the Home Office. RDS staff are embedded within delivery groups working closely with front-line staff. The HO Chief Scientific Advisor, who is also Director of RDS, oversees p rofessional development for RDS teams, quality assurance and strategic R & D issues. The Home Off i c e 's purpose is to build a safe, just and tolerant society in which the rights and responsibilities of individuals, families and communities are properly balanced and the p rotection and security of the public are maintained. RDS includes staff within the Government Statistical Service (GSS). One of the GSS aims is to i n f o rm Parliament and the members of the public about the state of the nation and provide a window on the work and perf o rmance of government, allowing the impact of govern m e n t policies and actions to be assessed. T h e re f o re-R e s e a rch Development and Statistics in the Home Office improves policy making, decision taking and practice in support of the Home Office purpose and aims, to provide the public and Parliament with information necessary for informed debate and to publish information for future use.

Although urban birth, upbringing, and living are associated with increased risk of nonaffective psychotic disorders, few studies have used appropriate multilevel techniques accounting for spatial dependency in risk to investigate social, economic, or physical determinants of psychosis incidence. We adopted Bayesian hierarchical modeling to investigate the sociospatial distribution of psychosis risk in East London for DSM-IV nonaffective and affective psychotic disorders, ascertained over a 2-year period in the East London first-episode psychosis study. We included individual and environmental data on 427 subjects experiencing first-episode psychosis to estimate the incidence of disorder across 56 neighborhoods, having standardized for age, sex, ethnicity, and socioeconomic status. A Bayesian model that included spatially structured neighborhood-level random effects identified substantial unexplained variation in nonaffective psychosis risk after controlling for individual-level factors. This variation was independently associated with greater levels of neighborhood income inequality (SD increase in inequality: Bayesian relative risks [RR]: 1.25; 95% CI: 1.04–1.49), absolute deprivation (RR: 1.28; 95% CI: 1.08–1.51) and population density (RR: 1.18; 95% CI: 1.00–1.41). Neighborhood ethnic composition effects were associated with incidence of nonaffective psychosis for people of black Caribbean and black African origin. No variation in the spatial distribution of the affective psychoses was identified, consistent with the possibility of differing etiological origins of affective and nonaffective psychoses. Our data suggest that both absolute and relative measures of neighborhood social composition are associated with the incidence of nonaffective psychosis. We suggest these associations are consistent with a role for social stressors in psychosis risk, particularly when people live in more unequal communities.

BackgroundThe association between poor mental health and poverty is well known but its mechanism is not fully understood. This study tests the hypothesis that the association between low income and mental disorder is mediated by debt and its attendant financial hardship.MethodThe study is a cross-sectional nationally representative survey of private households in England, Scotland and Wales, which assessed 8580 participants aged 16–74 years living in general households. Psychosis, neurosis, alcohol abuse and drug abuse were identified by the Clinical Interview Schedule – Revised, the Schedule for Assessment in Neuropsychiatry (SCAN), the Alcohol Use Disorder Identification Test (AUDIT) and other measures. Detailed questions were asked about income, debt and financial hardship.ResultsThose with low income were more likely to have mental disorder [odds ratio (OR) 2.09, 95% confidence interval (CI) 1.68–2.59] but this relationship was attenuated after adjustment for debt (OR 1.58, 95% CI 1.25–1.97) and vanished when other sociodemographic variables were also controlled (OR 1.07, 95% CI 0.77–1.48). Of those with mental disorder, 23% were in debt (compared with 8% of those without disorder), and 10% had had a utility disconnected (compared with 3%). The more debts people had, the more likely they were to have some form of mental disorder, even after adjustment for income and other sociodemographic variables. People with six or more separate debts had a six-fold increase in mental disorder after adjustment for income (OR 6.0, 95% CI 3.5–10.3).ConclusionsBoth low income and debt are associated with mental illness, but the effect of income appears to be mediated largely by debt.

Objectives To measure the prevalence of domestic violence among women attending general practice; test the association between experience of domestic violence and demographic factors; evaluate the extent of recording of domestic violence in records held by general practices; and assess acceptability to women of screening for domestic violence by general practitioners or practice nurses. Design Self administered questionnaire survey. Review of medical records. Setting General practices in Hackney, London. Participants 1207 women ( > 15 years) attending selected practices. Main outcome measures Prevalence of domestic violence against women. Association between demographic factors and domestic violence reported in questionnaire. Comparison of recording of domestic violence in medical records with that reported in questionnaire. Attitudes of women towards being questioned about domestic violence by general practitioners or practice nurses. Results 425/1035 women (41%, 95% confidence interval 38% to 44%) had ever experienced physical violence from a partner or former partner and 160/949 (17%, 14% to 19%) had experienced it within the past year. Pregnancy in the past year was associated with an increased risk of current violence (adjusted odds ratio 2.11, 1.39 to 3.19). Physical violence was recorded in the medical records of 15/90 (17%) women who reported it on the questionnaire. At least 202/1010 (20%) women objected to screening for domestic violence. Conclusions With the high prevalence of domestic violence, health professionals should maintain a high level of awareness of the possibility of domestic violence, especially affecting pregnant women, but the case for screening is not yet convincing.