Paranoia is receiving increasing attention in its own right, since it is a central experience of psychotic disorders and a marker of the health of a society. Paranoia is associated with use of the most commonly taken illicit drug, cannabis. The objective was to determine whether the principal psychoactive ingredient of cannabis—∆9-tetrahydrocannabinol (THC)—causes paranoia and to use the drug as a probe to identify key cognitive mechanisms underlying paranoia. A randomized, placebo-controlled, between-groups test of the effects of intravenous THC was conducted. A total of 121 individuals with paranoid ideation were randomized to receive placebo, THC, or THC preceded by a cognitive awareness condition. Paranoia was assessed extensively via a real social situation, an immersive virtual reality experiment, and standard self-report and interviewer measures. Putative causal factors were assessed. Principal components analysis was used to create a composite paranoia score and composite causal variables to be tested in a mediation analysis. THC significantly increased paranoia, negative affect (anxiety, worry, depression, negative thoughts about the self), and a range of anomalous experiences, and reduced working memory capacity. The increase in negative affect and in anomalous experiences fully accounted for the increase in paranoia. Working memory changes did not lead to paranoia. Making participants aware of the effects of THC had little impact. In this largest study of intravenous THC, it was definitively demonstrated that the drug triggers paranoid thoughts in vulnerable individuals. The most likely mechanism of action causing paranoia was the generation of negative affect and anomalous experiences.

BackgroundCurrent approaches to assess violence risk in secure hospitals are resource intensive, limited by accuracy and authorship bias and may have reached a performance ceiling. This study seeks to develop scalable predictive models for violent offending following discharge from secure psychiatric hospitals.MethodsWe identified all patients discharged from secure hospitals in Sweden between January 1, 1992 and December 31, 2013. Using multiple Cox regression, pre-specified criminal, sociodemographic, and clinical risk factors were included in a model that was tested for discrimination and calibration in the prediction of violent crime at 12 and 24 months post-discharge. Risk cut-offs were pre-specified at 5% (low vs. medium) and 20% (medium vs. high).ResultsWe identified 2248 patients with 2933 discharges into community settings. We developed a 12-item model with good measures of calibration and discrimination (area under the curve = 0.77 at 12 and 24 months). At 24 months post-discharge, using the 5% cut-off, sensitivity was 96% and specificity was 21%. Positive and negative predictive values were 19% and 97%, respectively. Using the 20% cut-off, sensitivity was 55%, specificity 83% and the positive and negative predictive values were 37% and 91%, respectively. The model was used to develop a free online tool (FoVOx).InterpretationWe have developed a prediction score in a Swedish cohort of patients discharged from secure hospitals that can assist in clinical decision-making. Scalable predictive models for violence risk are possible in specific patient groups and can free up clinical time for treatment and management. Further evaluation in other countries is needed.FundingWellcome Trust (202836/Z/16/Z) and the Swedish Research Council. The funding sources had no involvement in writing of the manuscript or decision to submit or in data collection, analysis or interpretation or any aspect pertinent to the study.

No abstract

We describe the development and pilot testing of a novel, web-based, violence risk monitoring instrument for use in community patients with psychoses. We describe the development of the tool, including drawing on systematic reviews of the field, how item content was operationalized, the development of a user interface, and its subsequent piloting. Sixty-eight patients were included from three English counties, who had been discharged from forensic psychiatric services. Over 12 months, 310 questionnaires were completed on the sample by professionals from several disciplines and qualitative feedback collected relating to the use of the tool using an electronic survey. Strengths of this approach for risk assessment, and potential limitations and areas for future research, are discussed.

Aims: We aimed to review prison healthcare expenditure internationally.Objectives: To systematically review healthcare spending on prisoners worldwide, examine comparability between countries, and develop guidelines to improve reporting.Methods: Five bibliographic indexes (International Monetary Fund, ProQuest: Statistical Abstracts of the World, PubMed, Google Scholar, and JSTOR) were searched for the costs of prison and prison healthcare, supplemented with country-specific searches for the 20 countries with the highest prison populations. Information on overall healthcare costs, their breakdown by categories, and their proportion to overall prison expenditure was extracted. PRISMA guidelines were followed.Results: Prison healthcare expenditure data was identified for 10 countries, and overall operating costs were reported for 12 countries. The most commonly reported healthcare cost was for primary medical care. Healthcare costs reporting varied widely, and few countries were comparable. We developed a set of guidelines for consistent and transparent reporting of healthcare costs.Conclusions: Few countries report the costs of healthcare services in prison. When reported, there is a lack of clarity and consistency as to what is included. Using the proposed reporting guidelines would enable national trends and international comparisons to be investigated, and any recommended benchmarks to be monitored.