518 research outputs found
Women convicted for violent offenses: Adverse childhood experiences, low level of education and poor mental health
<p>Abstract</p> <p>Background</p> <p>In past years, the female offender population has grown, leading to an increased interest in the characteristics of female offenders. The aim of this study was to assess the prevalence of female violent offending in a Swiss offender population and to compare possible socio-demographic and offense-related gender differences.</p> <p>Methods</p> <p>Descriptive and bivariate logistic regression analyses were performed for a representative sample of N = 203 violent offenders convicted in Zurich, Switzerland.</p> <p>Results</p> <p>7.9% (N = 16) of the sample were female. Significant gender differences were found: Female offenders were more likely to be married, less educated, to have suffered from adverse childhood experiences and to be in poor mental health. Female violent offending was less heterogeneous than male violent offending, in fact there were only three types of violent offenses females were convicted for in our sample: One third were convicted of murder, one third for arson and only one woman was convicted of a sex offense.</p> <p>Conclusions</p> <p>The results of our study point toward a gender-specific theory of female offending, as well as toward the importance of developing models for explaining female criminal behavior, which need to be implemented in treatment plans and intervention strategies regarding female offenders.</p
Additive and multiplicative hazards modeling for recurrent event data analysis
<p>Abstract</p> <p>Background</p> <p>Sequentially ordered multivariate failure time or recurrent event duration data are commonly observed in biomedical longitudinal studies. In general, standard hazard regression methods cannot be applied because of correlation between recurrent failure times within a subject and induced dependent censoring. Multiplicative and additive hazards models provide the two principal frameworks for studying the association between risk factors and recurrent event durations for the analysis of multivariate failure time data.</p> <p>Methods</p> <p>Using emergency department visits data, we illustrated and compared the additive and multiplicative hazards models for analysis of recurrent event durations under (i) a varying baseline with a common coefficient effect and (ii) a varying baseline with an order-specific coefficient effect.</p> <p>Results</p> <p>The analysis showed that both additive and multiplicative hazards models, with varying baseline and common coefficient effects, gave similar results with regard to covariates selected to remain in the model of our real dataset. The confidence intervals of the multiplicative hazards model were wider than the additive hazards model for each of the recurrent events. In addition, in both models, the confidence interval gets wider as the revisit order increased because the risk set decreased as the order of visit increased.</p> <p>Conclusions</p> <p>Due to the frequency of multiple failure times or recurrent event duration data in clinical and epidemiologic studies, the multiplicative and additive hazards models are widely applicable and present different information. Hence, it seems desirable to use them, not as alternatives to each other, but together as complementary methods, to provide a more comprehensive understanding of data.</p
Re-Arrest Among Juvenile Justice-Involved Youth: An Examination Of The Static And Dynamic Risk Factors
The purpose of this study is to investigate the static and dynamic risk factors for re-arrest among detained youth by examining gender, race/ethnicity, age, special education and mental health variables (i.e., anger/irritability, depression/anxiety, somatic complaints, suicide ideation, thought disturbances, and traumatic experiences). The demographic profiles of detained youth with one admit were also compared with those with multiple admits to the juvenile detention center. With regards to static risk factors, older, white, and special education were significantly at risk of re-arrest. Concerning dynamic risk factors, only anger/irritability predicted re-arrest. Practice implications are also discussed
Beyond crime statistics: the construction and application of a criminogenity monitor in Amsterdam
Criminologists have devoted a great deal of attention to risk factors - also called criminogenic factors - leading to criminal offending. This paper presents a criminogenity monitor which includes 19 risk factors that underlie crime. These factors do not themselves cause criminal behaviour; rather, they must be seen as signals that crimes may be committed. After discussing how the criminogenity monitor was constructed, we apply the risk factors we examined to the situation in Amsterdam, capital city of the Netherlands. The monitor is intended to function particularly as an instrument to rationalise policy-makers' work in targeting and preventing symptoms of crime at three geographical levels: the entire city, its boroughs and its neighbourhoods. © 2012 The Author(s)
An Information Theory Approach to Hypothesis Testing in Criminological Research
Background: This research demonstrates how the Akaike information criterion (AIC) can be an alternative to null hypothesis significance testing in selecting best fitting models. It presents an example to illustrate how AIC can be used in this way.
Methods: Using data from Milwaukee, Wisconsin, we test models of place-based predictor variables on street robbery and commercial robbery. We build models to balance explanatory power and parsimony. Measures include the presence of different kinds of businesses, together with selected age groups and social disadvantage.
Results: Models including place-based measures of land use emerged as the best models among the set of tested models. These were superior to models that included measures of age and socioeconomic status. The best models for commercial and street robbery include three measures of ordinary businesses, liquor stores, and spatial lag.
Conclusions: Models based on information theory offer a useful alternative to significance testing when a strong theoretical framework guides the selection of model sets. Theoretically relevant ‘ordinary businesses’ have a greater influence on robbery than socioeconomic variables and most measures of discretionary businesses
Separate and combined analysis of successive dependent outcomes after breast-conservation surgery: recurrence, metastases, second cancer and death
<p>Abstract</p> <p>Background</p> <p>In the setting of recurrent events, research studies commonly count only the first occurrence of an outcome in a subject. However this approach does not correctly reflect the natural history of the disease. The objective is to jointly identify prognostic factors associated with locoregional recurrences (LRR), contralateral breast cancer, distant metastases (DM), other primary cancer than breast and breast cancer death and to evaluate the correlation between these events.</p> <p>Methods</p> <p>Patients (n = 919) with a primary invasive breast cancer and treated in a cancer center in South-Western France with breast-conserving surgery from 1990 to 1994 and followed up to January 2006 were included. Several types of non-independent events could be observed for the same patient: a LRR, a contralateral breast cancer, DM, other primary cancer than breast and breast cancer death. Data were analyzed separately and together using a random-effects survival model.</p> <p>Results</p> <p>LRR represent the most frequent type of first failure (14.6%). The risk of any event is higher for young women (less than 40 years old) and in the first 10 years of follow-up after the surgery. In the combined analysis histological tumor size, grade, number of positive nodes, progesterone receptor status and treatment combination are prognostic factors of any event. The results show a significant dependence between these events with a successively increasing risk of a new event after the first and second event. The risk of developing a new failure is greatly increased (RR = 4.25; 95%CI: 2.51-7.21) after developing a LRR, but also after developing DM (RR = 3.94; 95%CI: 2.23-6.96) as compared to patients who did not develop a first event.</p> <p>Conclusion</p> <p>We illustrated that the random effects survival model is a more satisfactory method to evaluate the natural history of a disease with multiple type of events.</p
Constructing meaning about the delinquency of young girls in public-housing neighbourhoods
UID/SOC/04647/2013
SFRH/BPD/116119/2016Rooted in the theoretical approaches of social ecology and in childhood studies, the Ph.D. research project on which this paper is based aimed to achieve a better understanding of children’s socialization processes in multi-problematic spaces, particularly concerning their involvement in violence and delinquency. A case study based on ethnographic research and child-centred methods was carried out in six public-housing neighbourhoods in Portugal, which were chosen because they had relatively high levels of social deprivation, violence and crime. The specificity of the social group under study—children aged from 6 to 12 years old—and their living conditions, led us to extend the data collected by trying to learn, from the girls, the reasoning and the meanings they assign to their own actions in daily social practices. The intention was to study the features of girls’ socialization in the field through their own accounts of their lives and to examine their perspectives on offending behaviours. The genderized process of social learning in delinquency identified in the girls’ conversation is an important variable, as familial and social experiences tend to facilitate their entry into delinquency. The transmission of delinquent values takes place essentially within the female family circle or via female peers, rather than from the influence of male individuals.authorsversionpublishe
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