Forensic psychiatry patients, services, and legislation in Nunavut and Greenland.

Circumpolar regions face unique challenges in establishing and maintaining mental health care systems, including forensic psychiatry services. The scarcity of data and lack of evidence concerning the forensic psychiatry patient (FPP) populations of Nunavut and Greenland exacerbates the challenges of informing best practices and healthcare planning. By comparing the prevalence of forensic psychiatry patients, the mental health care services, and the legislation in these two relatively similar but unique regions, insight may be gained that can help inform healthcare planning. This cross-sectional study includes all forensic psychiatry in- and outpatients in one year from Nunavut (2018) and on February 29, 2020, in Greenland. The Greenland sample (n = 93) was nearly four times larger than the Nunavut sample (n = 15) at the population level. Despite considerable differences in forensic legislation and service supply, the forensic psychiatry patients in the two areas share several similarities. A total of 87% (n = 13) in the Nunavut sample were diagnosed with a DSM-5 schizophrenia spectrum disorder or other psychotic disorder. In Greenland, 82% (n = 76) were diagnosed with an ICD-10 F2 diagnosis (schizophrenia, schizotypal and delusional disorders). Approximately 2/3 of the patients in both populations were diagnosed with substance use disorder, and 60% of the Nunavut FPP received long-acting antipsychotic injections versus 62% in Greenland. Nearly half of the FPPs in both populations had never been convicted prior to entering the forensic psychiatry system; Nunavut 45% versus Greenland 47%. A substantial proportion of Greenlandic FPPs were outpatients compared to Nunavut (83% versus 47%). This study is an essential first step toward describing a Model of Care for forensic psychiatry patients in circumpolar regions; furthermore, the clinical similarities between the two populations provide support for future joint Arctic research and the inclusion of artic forensic patients in international studies.

The HARM models: Predicting longitudinal physical aggression in patients with schizophrenia at an individual level.

The prediction and prevention of aggression in individuals with schizophrenia remains a top priority within forensic psychiatric settings. While risk assessment methods are well rooted in forensic psychiatry, there are no available tools to predict longitudinal physical aggression in patients with schizophrenia within forensic settings at an individual level. In the present study, we used evidence-based risk and protective factors, as well as variables related to course of treatment assessed at baseline, to predict prospective incidents of physical aggression (4-month, 12-month, and 18-month follow-up) among 151 patients with schizophrenia within the forensic mental healthcare system. Across our HARM models, the balanced accuracy (sensitivity + specificity/2) of predicting physical aggressive incidents in patients with schizophrenia ranged from 59.73 to 87.33% at 4-month follow-up, 68.31-80.10% at 12-month follow-up, and 46.22-81.63% at 18-month follow-up, respectively. Additionally, we developed separate models, using clinician rated clinical judgement of short term and immediate violent risk, as a measure of comparison. Several modifiable evidence-based predictors of prospective physical aggression in schizophrenia were identified, including impulse control, substance abuse, impulsivity, treatment non-adherence, mood and psychotic symptoms, substance abuse, and poor family support. To the best of our knowledge, our HARM models are the first to predict longitudinal physical aggression at an individual level in patients with schizophrenia in forensic settings. However, it is important to caution that since these machine learning models were developed in the context of forensic settings, they may not be generalisable to individuals with schizophrenia more broadly. Moreover, a low base rate of physical aggression was observed in the testing set (6.0-11.6% across timepoints). As such, larger cohorts will be required to determine the replicability of these findings.

Suicide attempts among Greenlandic forensic psychiatric patients - prevalence and determinants.

This nationwide cross-sectional study of the lifetime prevalence and determinants of suicide attempts includes 90% of Greenlandic forensic psychiatric patients. Retrospective data were collected from electronic patient files, court documents, and forensic psychiatric assessments using a coding form from a similar study. We used unpaired t-tests and chi2 or Fisher's exact test. The lifetime prevalence of suicide attempts was 36% (n = 32), and no difference in prevalence was found between male and female patients (p = 0.95). Patients having attempted suicide had a higher rate of physical abuse in childhood (p = 0.04), family history of substance misuse (p = 0.007), and criminal convictions among family members (p = 0.03) than patients who had never attempted suicide. Women primarily used self-poisoning in their latest suicide attempts (67%), whereas men more often used sharp objects or a firearm (42%). Over a third of Greenlandic forensic patients have attempted suicide at some point in their life, and patients with traumatic childhood experiences are at higher risk of suicidal behaviour. It is not possible to conclude whether the lifetime prevalence of suicide attempts among Greenlandic forensic patients is comparable to that of other high-risk groups in other Arctic regions due to methodological differences among the very few other comparable studies.

The Ontario Forensic Mental Health System: A Population-based Review.

OBJECTIVE: The purpose of this study was to increase the understanding of the Canadian forensic psychiatry system by providing a population-based overview of the Ontario forensic mental health system. METHODS: Data were collected on 1,240 accused adults who were subject to the jurisdiction of the Ontario Review Board (ORB) between 2014 and 2015. Archival data were retrieved from annual ORB hearing hospital reports for accused supervised by all nine adult forensic psychiatry facilities across Ontario. RESULTS: The sample included not criminally responsible (NCR; 91.6%) and unfit to stand trial (UST; 8.4%) accused. The majority of the sample was male (85.7%), single (70.1%), unemployed (63.6%), with a high school education (48.8%). Most were on a detention order (78.5%) and almost half were living in the community at the time of the report (48.8%). The majority had prior contact with psychiatric services (83.1%) and/or the criminal justice system (70.6%) before entering the forensic system. A history of elopement (31.5%) and inpatient aggression was high (60.6%). Most had a psychotic spectrum disorder (81.6%) and over half had a substance use disorder (57.2%) in the reporting year. A range of index offences was observed (69.9% violent, 20.3% general, 9.8% sexual), and the majority of the sample (61.0%) had an index offence that resulted in no injury or a minor injury to the victim. CONCLUSION: The Canadian forensic psychiatry system is comprised of a unique subset of justice-involved individuals. This study provides a detailed examination of accused who are subject to the jurisdiction of the ORB and provides key insight into risk factors associated with offending behaviour in this population. The results of this study will provide a framework for future studies examining the association between mental disorder and violence and the treatment trajectories for those in the forensic psychiatry system.

Public perceptions of psychiatric, justice-involved, and elderly populations during the COVID-19 pandemic.

The novel coronavirus disease (COVID-19) has had a significant global impact, with all countries facing the challenge of mitigating its spread. An unprecedented shortage of medical resources has raised concerns regarding allocation and prioritization of supplies, which may exacerbate social discrepancies for already vulnerable populations. As public opinion can impact healthcare policies, we aimed to characterize perceptions of psychiatric, forensic psychiatry, correctional, and elderly populations regarding COVID-19-related issues. This web-based study recruited participants (n = 583) from the general population in North America. The survey included perceptions of the pandemic, hypothetical scenarios on resource prioritization, and Likert scale questions. The majority of participants were cisgender female (72.7%), aged 31-74 years (80.0%), married (48.0%), retired (52.7%), resided in Canada (73.9%), had a college/university degree (50.9%) and had never worked in healthcare (66.21%). Most respondents reported not having a criminal history (95.88%), or a psychiatric disorder (78.73%). Perceptions of vulnerable populations were significantly different for resource allocation and prioritization (e.g., ventilator and vaccine resources, all p < 0.001). Healthcare workers and the elderly were commonly ranked the highest priority for resources, while forensic psychiatry and correctional populations were given the lowest priority. A high rate of disagreement was found for the more stigmatizing questions in the survey (all p < 0.0001). Our results suggest that perception from members of the general public in North America is aligned with current practices for resource allocation. However, individuals that already face social and health disparities may face additional opposition in decision-making for COVID-19 resources.

Forensic psychiatry services in Nunavut.

There is a paucity of research on forensic psychiatry patients from Nunavut, including no published data concerning the prevalence and characterisation of patients in this territory. The lack of basic information hinders the evaluation of services and establishing best practices. The current paper aims to characterise forensic psychiatry patients from Nunavut and further the understanding of the challenges in organising forensic psychiatry healthcare in Nunavut. A retrospective chart review design was used to examine individuals from Nunavut who are engaged with the Ontario forensic psychiatry system. The sample included all Unfit to Stand Trial (26.7%) and Not Criminally Responsible (73.3%) patients (N = 15) under the jurisdiction of the Nunavut Review Board in a one-year period. The average distance between the patient's place of residence in Nunavut and the Ontario facilities was 2,517 km. Overall, 26.7% were living in Nunavut, 60.0% remained in Ontario, and 13.3% resided in Alberta. Results are presented for sociodemographics, forensic status, personal and familial history, psychiatric and criminal history, diagnoses, index offence characteristics, treatment, assessment tools, and aggression. The prevalence and many characteristics of forensic psychiatry patients from Nunavut differ from the rest of Canada and have important implications for the delivery of services.

Predicting offenses among individuals with psychiatric disorders - A machine learning approach.

BACKGROUND: Actuarial risk estimates are considered the gold-standard way to assess whether psychiatric patients are likely to commit prospective criminal offenses. However, these risk estimates cannot individually predict the type of criminal offense a patient will subsequently commit, and often simply assess the general likelihood of crime occurring in a group sample. In order to advance the predictive utility of risk assessments, better statistical strategies are required. AIM: To develop a machine learning model to predict the type of criminal offense committed in a large transdiagnostic sample of psychiatry patients, at an individual level. METHOD: Machine learning algorithms (Random Forest, Elastic Net, SVM), were applied to a representative and diverse sample of 1240 patients in the forensic mental health system. Clinical, historical, and sociodemographic variables were considered as potential predictors and assessed in a data-driven way. Separate models were created for each type of criminal offense, and feature selection methods were used to improve the interpretability and generalizability of our findings. RESULTS: Sexual offenses can be predicted from nonviolent and violent offenses at an individual level with a sensitivity of 82.44% and specificity of 60.00%, using only 36 variables. Furthermore, in a binary classification model, sexual and violent offenses can be predicted at an individual level with 83.26% sensitivity and 77.42% specificity using only 20 clinical variables. Likewise, non-violent and sexual offenses can be individually predicted with 74.60% sensitivity and 80.65% specificity using 30 clinical variables. CONCLUSION: The current results suggest that machine learning models can show greater accuracy than gold-standard risk assessment tools (AUCs 0.70-0.80). However, unlike existing risk tools, this approach allows for the prediction of cases at an individual level, which is more clinically useful. Despite this, it is important to note that a large subset of patients in the sample were involved in the criminal system in the past, prior to an official diagnosis. Therefore, many of the variables that predict offenses may be derived from the issues of prior offenses. Irrespective of this, the accuracy of prospective models is expected to only improve with further refinement.

Stigmatization of psychiatric and justice-involved populations during the COVID-19 pandemic.

Psychiatric and justice-involved populations are known to be stigmatized and particularly vulnerable to adverse outcomes during COVID-19. The increased attention toward vulnerable populations from healthcare authorities, the media, and the general public has made it critical to uncover any developing stigmatization toward these groups and the possible consequences. The prioritization of public safety and shift in the prioritization of resource allocation and service delivery could lead to a rise in negative perceptions toward these already stigmatized groups. Thus, it is imperative to consider how the unique characteristics of vulnerable groups may impact their physical and mental health as well as their care during this pandemic. In this paper, we describe the challenges that psychiatric, correctional, and forensic psychiatry populations have faced during COVID-19 and how a rise in stigmatization could lead to adverse outcomes. Specifically, we outline the influence of the media on public perceptions and how stigmatization may be reflected in the allocation of resources, policies, and related decision-making during COVID-19.