A better understanding of the functioning of the brain, particularly executive functions, of the prison population could aid in reducing crime rates through the reduction of recidivism rates. Indeed, reoffending appears to be related to executive dysfunction and it is known that executive functions are crucial for self-regulation. In the current paper, studies to executive functions in regular adult prisoners compared to non-offender controls were reviewed. Seven studies were found. Specific executive functions were found to be impaired in the general prison population, i.e., attention and set-shifting, as well as in separate subgroups of violent (i.e., set-shifting and working memory) and non-violent offenders (i.e., inhibition, working memory and problem solving). We conclude that the limited number of studies is remarkable, considering the high impact of this population on society and elaborate on the implications of these specific impairments that were found. Further empirical research is suggested, measuring executive functioning within subjects over time for a group of detainees as well as a control group.

Violent offenders show worse response inhibition compared to non-violent offenders, suggesting a more pronounced prefrontal deficit in violent offenders than in non-violent offenders.

Background: Prison can be characterized as an impoverished environment encouraging a sedentary lifestyle with limited autonomy and social interaction, which may negatively affect self-control and executive function. Here, we aim to study the effects of imprisonment on self-control and executive functions, and we report the change in neuropsychological outcome after 3 months of imprisonment.Materials and Methods: Participants were 37 male inmates in a remand prison in Amsterdam, Netherlands, who completed six tests of a computerized neuropsychological test battery (the Cambridge Automated Neuropsychological Test Battery) in the first week of arrival. Participants were retested after 3 months of imprisonment. Change in performance was tested using the Wilcoxon Signed-Rank test.Results: After 3 months of imprisonment, risk taking significantly increased (measured as an increase in the proportion of available points used for betting) and attention significantly deteriorated (measured as increased variability in reaction times on a sustained attention task), with large to medium effect sizes. In contrast, planning significantly improved (measured with a task analog to the Tower of London) with a medium effect size.Discussion: Our study suggests that 3 months of imprisonment in an impoverished environment may lead to reduced self-control, measured as increased risk taking and reduced attentional performance. This is a significant and societally relevant finding, as released prisoners may be less capable of living a lawful life than they were prior to their imprisonment, and may be more prone to impulsive risk-taking behavior. In other words, the impoverished environment may contribute to an enhanced risk of reoffending.

Abstract Background. Comorbidity has profound implications in both the clinical field and research, yet little is known about the prevalence and structure of comorbid mental disorders. This article aims not only to present data on the prevalence of mental disorders and comorbidity, but also to explore relationships between comorbid mental disorders by using a network approach. Methods. Data used in this cross-sectional study are part of a prospective cohort study within penitentiary psychiatric centers (PPCs) in the Netherlands. It includes DSM diagnoses of 5,257 unique male patients incarcerated in one of the PPC's. Prevalence rates of mental disorders and comorbidity were calculated, the network of comorbid DSM diagnoses was constructed using regression coefficients. Results. Schizophrenia spectrum and substance-related disorders were most prevalent within this sample (56.7 and 43.1%, respectively), and over half of all patients were diagnosed with a comorbid disorder (56.9%). Four distinctive groups of disorders emerged from the network analysis of DSM diagnoses: substance use, impulsivity, poor social skills, and disruptive behaviors. Psychotic disorders were considered as a separate group as it was unconnected to other disorders. Conclusions. Comorbid mental disorders can be described, at least in part, as connected networks. Underlying attributes as well as direct influences of mental disorders on one another seem to be affecting the presence of comorbidity. Results could contribute to the understanding of a possible causal relation between psychopathology and criminal behavior and the development of treatment programs targeting groups of disorders.

Introduction: Previous studies suggest an association between poor mastication and cognitive impairment. The role of chewing efficiency and dentition in this relation is unclear. The aim was to examine global cognitive functioning and dentition as predictors for chewing efficiency, in older people with mild cognitive impairment (MCI) or dementia. Methods: In this observational cross-sectional study, 136 people with MCI or dementia were included. The chewing efficiency was assessed with a two-colored chewing gum and analyzed with the Chewing Efficiency Analysis software. The level of global cognitive functioning was measured with the Mini Mental State Examination (MMSE) by trained clinical staff. An oral examination was performed by a dentist and included the number of present teeth, the number of occluding pairs, and the presence of prostheses. Age, gender, and educational years were derived from the medical records. Univariate and multivariate backward stepwise linear regression analyses were used to evaluate global cognitive functioning and dentition as predictors for chewing efficiency. Results: The mean age of the participants was 82.1 (SD 5.8) years, and 74 (54.4%) were female. The participants had a median MMSE score of 22.4 (IQR 18.0-26.0) and a median Chewing Efficiency Analysis score of 0.46 (IQR 0.14-0.59). The median number of teeth was 13.0 (IQR 0.0-23.0), and the median number of occluding pairs was 0.0 (IQR 0.0-7.0). Sixty-four (47.4%) of the participants wore full prosthesis in the upper jaw. In univariate linear regression analyses, predictive factors for the Chewing Efficiency Analysis score were age, MMSE score, full prosthesis in the