Individual, family and offence characteristics of high risk childhood offenders: comparing non-offending, one-time offending and re-offending Dutch-Moroccan migrant children in the Netherlands

<p>Abstract</p> <p>Background</p> <p>Childhood offenders are at an increased risk for developing mental health, social and educational problems later in life. An early onset of offending is a strong predictor for future persistent offending. Childhood offenders from ethnic minority groups are a vulnerable at-risk group. However, up until now, no studies have focused on them.</p> <p>Aims</p> <p>To investigate which risk factors are associated with (re-)offending of childhood offenders from an ethnic minority.</p> <p>Method</p> <p>Dutch-Moroccan boys, who were registered by the police in the year 2006-2007, and their parents as well as a control group (n = 40) were interviewed regarding their individual and family characteristics. Two years later a follow-up analysis of police data was conducted to identify one-time offenders (n = 65) and re-offenders (n = 35).</p> <p>Results</p> <p>All groups, including the controls, showed substantial problems. Single parenthood (OR 6.0) and financial problems (OR 3.9) distinguished one-time offenders from controls. Reading problems (OR 3.8), having an older brother (OR 5.5) and a parent having Dutch friends (OR 4.3) distinguished re-offenders from one-time offenders. First offence characteristics were not predictive for re-offending. The control group reported high levels of emotional problems (33.3%). Parents reported not needing help for their children but half of the re-offender's families were known to the Child Welfare Agency, mostly in a juridical framework.</p> <p>Conclusion</p> <p>The Moroccan subgroup of childhood offenders has substantial problems that might hamper healthy development. Interventions should focus on reaching these families tailored to their needs and expectations using a multi-system approach.</p

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models