A clinical and demographic comparison between a forensic and a general sample of female patients with schizophrenia

Differences between criminal offender versus non-offender female patients with schizophrenia spectrum disorder: a retrospective cohort study

The purpose of this study was to investigate the difference between offender female patients (OFS) and non-offender female patients (NOFS) with schizophrenia spectrum disorder (SSD).The patients in this study were admitted to the university psychiatry in Zurich Switzerland between 1982 and 2016. Demography, psychopathology, comorbidity, and treatment differences were analyzed using binary statistics to compare 31 OFS and 29 matching NOFS with SSD. The Fisher's exact test was used for categorical data variables in small size samples and the Mann-Whitney-U-Test for nonparametric test variables, adjusted with the Benjamini and Hochberg method.The results indicate that the NOFS were cognitively more impaired, they were more likely to have had antipsychotic drugs prescribed (NOFS; 100%, OFS: 71%, OR 1.41, 95% CI 1.13-1.77, p=0.022) and their medication compliance was higher (NOFS: 84.6%, OFS: 4.5%, OR 0.09, 95% CI 0.00-0.08, p=0.000). In contrast, the OFS had completed compulsory school less often and the were observed to be more often homeless and socially isolated (OFS: 72.4%, NOFS: 34.6%, OR 4.96, 95% CI 1.58-15.6, p=0.026), self-disorders (OFS: 51.6%, NOFS: 11.1%, OR 8.53, 95% CI 2.12-34.32, p=0.011), delusions (OFS: 96.8%, NOFS: 63%, OR 17.65, 95% CI 2.08-149.99, p=0.014) and substance use disorder (51.6%, OR 0.27, 95% CI 0.09-0.85, p=0.039). Clinicians treating female offender patients with SSD should focus more on the treatment for substance use disorder, medication and early recognition of the illness for preventative purposes.

When do drugs trigger criminal behavior? a machine learning analysis of offenders and non-offenders with schizophrenia and comorbid substance use disorder

Introduction

Comorbid substance use disorder (SUD) is linked to a higher risk of violence in patients with schizophrenia spectrum disorder (SSD). The objective of this study is to explore the most distinguishing factors between offending and non-offending patients diagnosed with SSD and comorbid SUD using supervised machine learning.

Methods

A total of 269 offender patients and 184 non-offender patients, all diagnosed with SSD and SUD, were assessed using supervised machine learning algorithms.

Results

Failures during opening, referring to rule violations during a permitted temporary leave from an inpatient ward or during the opening of an otherwise closed ward, was found to be the most influential distinguishing factor, closely followed by non-compliance with medication (in the psychiatric history). Following in succession were social isolation in the past, no antipsychotics prescribed (in the psychiatric history), and no outpatient psychiatric treatments before the current hospitalization.

Discussion

This research identifies critical factors distinguishing offending patients from non-offending patients with SSD and SUD. Among various risk factors considered in prior research, this study emphasizes treatment-related differences between the groups, indicating the potential for improvement regarding access and maintenance of treatment in this particular population. Further research is warranted to explore the relationship between social isolation and delinquency in this patient population.

The Relationship Between Serious Mental Illness and Criminal Offending in Persons Experiencing Homelessness: The Role of Substance Use Disorder

Individuals who live with mental illness are encumbered by related risk factors that increase the probability of legal involvement. The goal was to determine how homelessness and substance use disorder are intervening factors in the relationship between symptoms of serious mental illness (SMI) and criminal offending. A sample of 210 chronically homeless adults receiving SAMHSA-funded outreach and psychiatric rehabilitation services between 2014 and 2016 was recruited in a study of interventions to address housing in homeless persons with a SMI. Participants were interviewed and data collected were analyzed using structural equation modeling. Statistical analysis showed that homelessness severity mediated the relationship between SMI symptom severity and criminal offenses committed in the past 30 days in participants with a substance use disorder but not in those with no substance use diagnosis. Results show that homelessness and substance use are important to address to possibly alter trajectories for criminal justice involvement.

Offenders and non-offenders with schizophrenia spectrum disorders: the crime-preventive potential of sufficient embedment in the mental healthcare and support system

Background

Suffering from schizophrenia spectrum disorder (SSD) has been well-established as a risk factor for offending. However, the majority of patients with an SSD do not show aggressive or criminal behavior. Yet, there is little research on clinical key features distinguishing offender from non-offender patients. Previous results point to poorer impulse control, higher levels of excitement, tension, and hostility, and worse overall cognitive functioning in offender populations. This study aimed to detect the most indicative distinguishing clinical features between forensic and general psychiatric patients with SSD based on the course of illness and the referenced hospitalization in order to facilitate a better understanding of the relationship between violent and non-violent offenses and SSD.

Methods

Our study population consisted of forensic psychiatric patients (FPPs) with a diagnosis of F2x (ICD-10) or 295.x (ICD-9) and a control group of general psychiatric patients (GPPs) with the same diagnosis, totaling 740 patients. Patients were evaluated regarding their medical (and, if applicable, criminal) history and the referenced psychiatric hospitalization. Supervised machine learning (ML) was used to exploratively evaluate predictor variables and their interplay and rank them in accordance with their discriminative power.

Results

Out of 194 possible predictor variables, the following 6 turned out to have the highest influence on the model: olanzapine equivalent at discharge from the referenced hospitalization, a history of antipsychotic prescription, a history of antidepressant, benzodiazepine or mood stabilizer prescription, medication compliance, outpatient treatment(s) in the past, and the necessity of compulsory measures. Out of the seven algorithms applied, gradient boosting emerged as the most suitable, with an AUC of 0.86 and a balanced accuracy of 77.5%.

Discussion

Our study aimed to identify the most influential illness-related predictors, distinguishing between FPP and GPP with SSD, thus shedding light on key differences between the two groups. To our knowledge, this is the first study to compare a homogenous sample of FPP and GPP with SSD regarding their symptom severity and course of illness using highly sophisticated statistical approaches with the possibility of evaluating the interplay of all factors at play.

Examination of the Relationship between Peripheral Inflammation Markers and Impulsivity and Aggression in Schizophrenia Patients Involved and Not Involved in Crime

Aim: The aim of this study was to examine the relationship between peripheral inflammatory markers and aggression and impulsivity in schizophrenia patients with and without criminal histories. Materials and Methods: The study was conducted with patients with schizophrenia involved in crimes and hospitalized in the Forensic Psychiatry ward of Elazığ Fethi Sekin City Hospital and patients with schizophrenia not involved in crimes and hospitalized in the psychiatry ward of Elazığ Mental Health and Diseases Hospital. All participants completed the Buss–Waren Aggression Scale (BWAS), the Barratt Impulsiveness Scale-11 (BIS-11), and the Positive and Negative Symptom Scale (PANSS). Before treatment, venous blood samples were taken for laboratory measurements on the first day of hospitalization. Results: All participants were male. The mean age of those involved in a crime was 39 ± 9.7 years, while the mean age of those not involved in a crime was 41.2 ± 10.7 years. The PANSS all subscale and total scores of the patients with schizophrenia who were involved in a crime were significantly higher than the group who were not involved (p values were p < 0.001, p = 0.001, p = 0.043, p = 0.001, respectively). The BWAS—physical aggression (p = 0.007) and total scores of the scale (p = 0.046) and BIS-11—inability to plan (p = 0.002) scores of the group involved in a crime were higher than the group not involved. As for laboratory parameters, MCH, MCHC, PDW, eosinophils, basophils, RDW-CV, and RDW-SD values were significantly higher in those involved in crime, while MPV, creatinine, albumin, and LDH values were lower. CRP and CRP/albumin values were significantly higher, while neutrophil/albumin values were significantly lower in those who committed murder in the first degree than those who committed other crimes. Conclusion: Based on our results, we found that inflammatory agents were significantly increased in forensic schizophrenia patients with high aggression scores. Significant correlations between some inflammatory factors and impulsivity and aggression scores and differences in these factors according to crime types showed that these factors might be related to violence and criminal behavior. There is a need for further large-scale studies on this subject at different stages of the disease.

Suicidal Offenders and Non-Offenders with Schizophrenia Spectrum Disorders: A Retrospective Evaluation of Distinguishing Factors Using Machine Learning

Patients with schizophrenia spectrum disorders (SSD) have an elevated risk of suicidality. The same has been found for people within the penitentiary system, suggesting a cumulative effect for offender patients suffering from SSD. While there appear to be overlapping characteristics, there is little research on factors distinguishing between offenders and non-offenders with SSD regarding suicidality. Our study therefore aimed at evaluating distinguishing such factors through the application of supervised machine learning (ML) algorithms on a dataset of 232 offenders and 167 non-offender patients with SSD and history of suicidality. With an AUC of 0.81, Naïve Bayes outperformed all other ML algorithms. The following factors emerged as most powerful in their interplay in distinguishing between offender and non-offender patients with a history of suicidality: Prior outpatient psychiatric treatment, regular intake of antipsychotic medication, global cognitive deficit, a prescription of antidepressants during the referenced hospitalisation and higher levels of anxiety and a lack of spontaneity and flow of conversation measured by an adapted positive and negative syndrome scale (PANSS). Interestingly, neither aggression nor overall psychopathology emerged as distinguishers between the two groups. The present findings contribute to a better understanding of suicidality in offender and non-offender patients with SSD and their differing characteristics.

Offenders and non-offenders with schizophrenia spectrum disorders: Do they really differ in known risk factors for aggression?

Introduction

Individuals with schizophrenia spectrum disorders (SSD) have an elevated risk for aggressive behavior, and several factors contributing to this risk have been identified, e. g. comorbid substance use disorders. From this knowledge, it could be inferred that offender patients show a higher expression of said risk factors than non-offender patients. Yet, there is a lack of comparative studies between those two groups, and findings gathered from one of the two are not directly applicable to the other due to numerous structural differences. The aim of this study therefore was to identify key differences in offender patients and non-offender patients regarding aggressive behavior through application of supervised machine learning, and to quantify the performance of the model.

Methods

For this purpose, we applied seven different (ML) algorithms on a dataset comprising 370 offender patients and a comparison group of 370 non-offender patients, both with a schizophrenia spectrum disorder.

Results

With a balanced accuracy of 79.9%, an AUC of 0.87, a sensitivity of 77.3% and a specificity of 82.5%, gradient boosting emerged as best performing model and was able to correctly identify offender patients in over 4/5 the cases. Out of 69 possible predictor variables, the following emerged as the ones with the most indicative power in distinguishing between the two groups: olanzapine equivalent dose at the time of discharge from the referenced hospitalization, failures during temporary leave, being born outside of Switzerland, lack of compulsory school graduation, out- and inpatient treatment(s) prior to the referenced hospitalization, physical or neurological illness as well as medication compliance.

Discussion

Interestingly, both factors related to psychopathology and to the frequency and expression of aggression itself did not yield a high indicative power in the interplay of variables, thus suggesting that while they individually contribute to aggression as a negative outcome, they are compensable through certain interventions. The findings contribute to our understanding of differences between offenders and non-offenders with SSD, showing that previously described risk factors of aggression may be counteracted through sufficient treatment and integration in the mental health care system.

Gender Differences in the Psychopharmacological Treatment of Forensic In-Patients With Schizophrenia

Background

In forensic psychiatry, psychopharmacological treatment plays a crucial role for patients with schizophrenia in improving their medical as well as legal prognosis. However, an increase in the number of females entering forensic treatment has yet to yield empirical research on the outcome of psychopharmacological treatment of female patients with schizophrenia in terms of efficacy and tolerability.

Aims

The aim of the present study is to elucidate pharmacological treatment strategies of women with schizophrenia in forensic psychiatry in comparison with men.

Methods

This study compares psychopharmacological treatment strategies, psychopathological features, as well as neurological and metabolic side effects of treatment between 29 female and 29 male in-patients with schizophrenia in three forensic facilities in Bavaria, Germany.

Results

Results show significant differences between genders. Poorer psychopathological and neurological features were found in the female sample, while men registered worse metabolic parameters. In terms of psychopharmacological treatment strategies, female in-patients were more often prescribed second-generation depot antipsychotics. Surprisingly, the potency of the dosages did not differ between genders. The results suggest that female forensic patients with schizophrenia have more severe and refractory diseases than their male counterparts.

Conclusion

Recommendations for gender-specific treatment strategies are derived.

Demographic, clinical and social characteristics of forensic patients diagnosed with schizophrenia at the Free State Psychiatric Complex, Bloemfontein, South Africa

Schizophrenia, prevalent in forensic mental health settings, is chronic and devastating, with a generally unfavourable course and prognosis. The aim of this study was to determine the demographic, clinical and social characteristics of forensic patients diagnosed with schizophrenia at the Free State Psychiatric Complex. A data collection form was used to gather information from the clinical records of patients diagnosed with schizophrenia between 1 January 2011 and 31 December 2015. The majority of the 110 participants were young male adults aged between 18 and 35 years with a low educational level. Cognitive impairment and positive symptoms were the most prominent clinical features. Aggressive and violent behaviour was notably prevalent. The majority of our sample had committed crimes against humans, while fewer had committed other types of crimes. It was concluded that causal factors included young adulthood, male gender, substance abuse, a poor social support system and lower educational level.

Antecedents, Behaviours, and Court Case Characteristics and Their Effects on Case Outcomes in Litigation for Persons with Schizophrenia

A 10% random sample of 3543 cases litigated in the United States' civil and criminal courts were analysed using logistic regression to develop a model that can predict case outcomes for litigants with schizophrenia. Most predictors are related to case characteristics and not to the litigants' antecedents, behaviours or medication issues. Only the psychologist as an expert witness was found to be related to case outcome, but the concern is expressed that inadequate weight is given to expert testimony. Other significant findings include being represented by counsel, atypical medication and malingering.

The national trajectory project of individuals found not criminally responsible on account of mental disorder. Part 5: how essential are gender-specific forensic psychiatric services?

OBJECTIVE

To state the sociodemographic characteristics, mental health histories, index offence characteristics, and criminal histories of male and female forensic psychiatric patients. Clinicians and researchers advocate that mental health and criminal justice organizations implement gender-specific services; however, few studies have sampled forensic patients to evaluate the extent to which men's and women's treatment and management needs are different.

METHOD

Data were collected from Review Board files from May 2000 to April 2005 in the 3 largest Canadian provinces. Using official criminal records, participants were followed for 3 to 8 years, until December 2008. The final sample comprised 1800 individuals: 15.6% were women and 84.4% were men.

RESULTS

There were few demographic differences, but women had higher psychosocial functioning than men. Both men and women had extensive mental health histories; women were more likely diagnosed with mood disorders and PDs and men were more likely diagnosed with schizophrenia spectrum disorders and SUDs. The nature of the index offence did not differ by gender, except women were more likely to have perpetrated murders and attempted murders. For offences against a person, women were more likely to offend against offspring and partners and less likely to offend against strangers, compared with men. Women had significantly less extensive criminal histories than men.

CONCLUSIONS

Not criminally responsible on account of mental disorder-accused women have a distinct psychosocial, clinical, and criminological profile from their male counterparts, which may suggest gender-specific assessment, risk management, and treatment in forensic services could benefit patients. The findings are also consistent with traditional models (Risk-Need-Responsivity) and ultimately demonstrate the importance of individual assessment and client-centred services.