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.