Association of substance use and other psychiatric disorders with all-cause and external-cause mortality in individuals given community sentences in Sweden: a national cohort study.

Background: Consistently high rates of premature mortality have been reported in individuals who receive community sentences. However, few studies have explored potential modifiable risk factors for these rates, particularly mental health. We examined the association of substance use and other psychiatric disorders with all-cause and external-cause mortality in individuals convicted of a criminal offence and given a community sentence. Methods: We did a longitudinal cohort study of 109,751 individuals given community sentences in Sweden using population-based registers. We calculated mortality rates for all-cause and external-cause mortality, hazard ratios for the association between psychiatric disorders and mortality, and population attributable fractions to quantify the contribution of psychiatric disorders to mortality risk. Findings: During the follow-up, 5749 (5.2%) individuals died, including 2709 (2.5%) from external causes. Individuals with pre-existing substance use and other psychiatric disorders had an increased mortality risk from any cause (aHR = 2.28 [95% CI 2.15-2.42]) and from external causes (3.11 [2.85-3.40]) compared to individuals without known psychiatric or substance use disorders. Suicide was the most common cause of death in younger persons. Interpretation: In individuals given community sentences, substance use and other psychiatric disorders were associated with an increased risk of premature death with suicide being the leading cause of death. Community supervision represents an opportunity to provide sentenced individuals with access to evidence-based treatment targeting substance misuse and psychiatric disorders to prevent potentially preventable deaths. Funding: Wellcome Trust.

Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression.

This paper discusses the promising areas of research into machine learning applications for the prevention and correction of neurodegenerative and depressive disorders. These two groups of disorders are among the leading causes of decline in the quality of life in the world when estimated using disability-adjusted years. Despite decades of research, the development of new approaches for the assessment (especially pre-clinical) and correction of neurodegenerative diseases and depressive disorders remains among the priority areas of research in neurophysiology, psychology, genetics, and interdisciplinary medicine. Contemporary machine learning technologies and medical data infrastructure create new research opportunities. However, reaching a consensus on the application of new machine learning methods and their integration with the existing standards of care and assessment is still a challenge to overcome before the innovations could be widely introduced to clinics. The research on the development of clinical predictions and classification algorithms contributes towards creating a unified approach to the use of growing clinical data. This unified approach should integrate the requirements of medical professionals, researchers, and governmental regulators. In the current paper, the current state of research into neurodegenerative and depressive disorders is presented.

Psychiatric disorders and reoffending risk in individuals with community sentences in Sweden: a national cohort study.

BACKGROUND: Community sentences are widely used in many countries, often comprising the majority of criminal justice sanctions. Psychiatric disorders are highly prevalent in community-sentenced populations and are thus potential targets for treatment interventions designed to reduce reoffending. We examined the association between psychiatric disorders and reoffending in a national cohort of individuals given community sentences in Sweden, with use of a sibling control design to account for unmeasured familial confounding. METHODS: We did a longitudinal cohort study of 82 415 individuals given community sentences between Nov 1, 1991, and Dec 31, 2013, in Sweden using data from population-based registers. We calculated hazard ratios (HRs) for any reoffending and violent reoffending with Cox regression models. We compared community-sentenced siblings with and without psychiatric disorders to control for potential familial confounding. Additionally, we calculated population attributable fractions to assess the contribution of psychiatric disorders to reoffending behaviours. The primary outcomes of the study were any (general) reoffending and violent reoffending. FINDINGS: Between Nov 1, 1991, and Dec 31, 2013, those given community sentences who were diagnosed with any psychiatric disorder had an increased reoffending risk in men (adjusted HR 1·59, 95% CI 1·56-1·63 for any reoffending; 1·60, 1·54-1·66 for violent reoffending) and women (1·71, 1·61-1·82 for any reoffending; 2·19, 1·88-2·54 for violent reoffending). Risk estimates remained elevated after adjustment for familial confounding. Schizophrenia spectrum disorders, personality disorders, and substance use disorders had stronger associations with violent reoffending than did other psychiatric disorders. Assuming causality, the adjusted population attributable risk of psychiatric disorders on violent reoffending was 8·3% (95% CI 6·6-10·0) in the first 2 years of community follow-up in men and 30·9% (22·7-39·0) in women. INTERPRETATION: Psychiatric disorders were associated with an increased risk of any reoffending and violent reoffending in the community-sentenced population. The magnitude of the association between psychiatric disorders and reoffending varied by individual diagnosis. Substance use disorders had the highest absolute and relative risks. Most of the increased risk for any reoffending in individuals with psychiatric disorders could be attributed to comorbid substance misuse. Given their high prevalence, substance use disorders should be the focus of treatment programmes in community-sentenced populations. FUNDING: Wellcome Trust.

Criminal recidivism rates globally: A 6-year systematic review update.

Objectives: Previous work has shown that direct comparison of recidivism rates between jurisdictions without accounting for potential sources of their variation can be misleading. We aimed to systemically review data on recidivism rate internationally and explore sources of between-country variation. Methods: We reviewed recidivism rates in individuals released from prison and given community sentences. We systematically searched peer-reviewed and gray literature focusing on publications since a systematic review in mid-2019. We extracted data on reoffending, reimprisonment, and re-arrests. To examine the association between index offences and recidivism rates, we calculated risk ratios. We used meta-regression to estimate the association between recidivism in released prisoners and country-level variables. We also summarised reported effects of the COVID-19 pandemic on recidivism rates. Results: Recidivism data were found for 33 countries. Released prisoners had 2-year reconviction rates between 18% and 55%, while individuals given community sentences had rates between 10% and 47%. Recidivism rates varied based on proportions of index offences. Country-level factors like homicide, robbery, and imprisonment rates were associated with prisoner recidivism. Lower rates during COVID-19 were linked to disruptions in criminal justice processes, reduced prison populations, and fewer crime opportunities. Conclusions: Interpreting recidivism rates requires considering individual and country-level factors. Transparent reporting of these factors is needed.

Prediction of reoffending risk in men convicted of sexual offences: development and validation of novel and scalable risk assessment tools (OxRIS).

Background: Current risk assessment tools have a limited evidence base with few validations, poor reporting of outcomes, and rarely include modifiable factors. Methods: We examined a national cohort of men convicted of sexual crimes in Sweden. We developed prediction models for three outcomes: violent (including sexual), any, and sexual reoffending. We used Cox proportional hazard regression to develop multivariable prediction models and validated these in an external sample. We reported discrimination and calibration statistics at prespecified cut-offs. Findings: We identified 16,231 men convicted of sexual offences, of whom 14.8% violently reoffended during a mean follow up of 38 months, 31.4% for any crime (34 months), and 3.6% for sexual crimes (42 months). Models for violent and any reoffending showed good discrimination and calibration. At 1, 3, and 5 years, the area under the curve (AUC) was 0.75-0.76 for violent reoffending and 0.74-0.75 for any reoffending. The prediction model for sexual reoffending showed modest discrimination (AUC = 0.67) and good calibration. We have generated three simple and web-based risk calculators, which are freely available. Interpretation: Scalable evidence-based risk assessment tools for sexual offenders in the criminal justice system and forensic mental health could assist decision-making and treatment allocation by identifying those at higher risk, and screening out low risk persons.

Risk factors for recidivism in individuals receiving community sentences: a systematic review and meta-analysis.

OBJECTIVE: We aimed to systematically review risk factors for criminal recidivism in individuals given community sentences. METHODS: We searched seven bibliographic databases and additionally conducted targeted searches for studies that investigated risk factors for any repeat offending in individuals who had received community (non-custodial) sentences. We included investigations that reported data on at least one risk factor and allowed calculations of odds ratios (ORs). If a similar risk factor was reported in three or more primary studies, they were grouped into domains, and pooled ORs were calculated. RESULTS: We identified 15 studies from 5 countries, which reported data on 14 independent samples and 246,608 individuals. We found that several dynamic (modifiable) risk factors were associated with criminal recidivism in community-sentenced populations, including mental health needs (OR = 1.4, 95% confidence interval (CI): 1.2-1.6), substance misuse (OR = 2.3, 95% CI: 1.1-4.9), association with antisocial peers (OR = 2.2, 95% CI: 1.3-3.7), employment problems (OR = 1.8, 95% CI: 1.3-2.5), marital status (OR = 1.6, 95%: 1.4-1.8), and low income (OR = 2.0, 95% CI: 1.1-3.4). The strength of these associations was comparable to that of static (non-modifiable) risk factors, such as age, gender, and criminal history. CONCLUSION: Assessing dynamic (modifiable) risk factors should be considered in all individuals given community sentences. The further integration of mental health, substance misuse, and criminal justice services may reduce reoffending risk in community-sentenced populations.

Recidivism rates in individuals receiving community sentences: A systematic review.

OBJECTIVE: We aimed to systematically review recidivism rates in individuals given community sentences internationally. We sought to explore sources of variation between these rates and how reporting practices may limit their comparability across jurisdictions. Finally, we aimed to adapt previously published guidelines on recidivism reporting to include community sentenced populations. METHODS: We searched MEDLINE, PsycINFO, SAGE and Google Scholar for reports and studies of recidivism rates using non-specific and targeted searches for the 20 countries with the largest prison populations worldwide. We identified 28 studies with data from 19 countries. Of the 20 countries with the largest prison populations, only 2 reported recidivism rates for individuals given community sentences. RESULTS: The most commonly reported recidivism information between countries was for 2-year reconviction, which ranged widely from 14% to 43% in men, and 9% to 35% in women. Explanations for recidivism rate variations between countries include when the follow-up period started and whether technical violations were taken into account. CONCLUSION: Recidivism rates in individuals receiving community sentences are typically lower in comparison to those reported in released prisoners, although these two populations differ in terms of their baseline characteristics. Direct comparisons of the recidivism rates in community sentenced cohorts across jurisdictions are currently not possible, but simple changes to existing reporting practices can facilitate these. We propose recommendations to improve reporting practices.

A systematic review of criminal recidivism rates worldwide: 3-year update.

Background: Comparing recidivism rates between countries may provide useful information about the relative effectiveness of different criminal justice policies. A previous 2015 review identified criminal recidivism data for 18 countries and found little consistency in outcome definitions and time periods. We aimed to update recidivism rates in prisoners internationally. Methods: We conducted a systematic review of criminal recidivism rates in prisoners and followed PRISMA guidelines. Using five bibliographic indexes, we carried out non-country-specific and targeted searches for 50 countries with the largest total prison populations. We included reports and studies of released prisoners that reported re-arrest, reconviction and reincarceration rates. Meta-analysis was not possible due to multiple sources of heterogeneity. Results: We identified criminal recidivism information for 23 countries. Of the 50 countries with the largest prison populations, 10 reported recidivism rates for prisoners. The most commonly reported outcome was the 2-year reconviction rate. We were able to examine reconviction between different time periods for 11 countries and found that most reported small changes in official recidivism rates. Overall, for 2-year follow-up period, reported re-arrest rates were between 26% and 60%, reconviction rates ranged from 20% to 63%, and reimprisonment rates varied from 14 to 45%. Conclusions: Although some countries have made efforts to improve reporting, recidivism rates are not comparable between countries. Criminal justice agencies should consider using reporting guidelines described here to update their data.

Bootstrapping the P300 in diagnostic psychophysiology: How many iterations are needed?

In psychophysiological research, bootstrapping procedures are often used to classify individual participants. How many iterations are required for a reliable bootstrap test is not universally agreed upon. To investigate the number of iterations needed for a stable bootstrap estimate, we reanalyzed P300 data collected in concealed information test paradigms. We also distinguished between the bootstrap and permutations approaches. We compared results in several studies using 100 versus 1,000 versus 10,000 iterations in the bootstrap, and we concluded that 100 iterations were adequate as results from all three iteration numbers correlated highly.