Search Results (7)

As the demand for more accurate crime prediction and risk assessment grows, researchers have been developing smarter models that blend statistical methods with machine learning. This study compares a hybrid ARIMA-ANN model with traditional classification techniques to see which best forecast monthly crime risk levels in Galați County, Romania. The analysis is based on a newly compiled dataset of 132 monthly observations from January 2014 to December 2024, which combines a broad array of social, economic, and environmental data points. The main variable, ‘Crime risk’, is based on normalized counts of offenses per capita and divided into five balanced levels: very low, low, moderate, high, and very high. The hybrid ARIMA-ANN model merges the strengths of statistical time series analysis with the flexible learning ability of artificial neural networks. Performance is evaluated against multinomial logistic regression, decision trees, random forests, and support vector machines. Overall, the results show that an ARIMA-ANN model consistently outperforms traditional methods, especially in recognizing patterns over time, seasonal trends, and complex nonlinear relationships in crime data. This study not only sets a new benchmark for crime analytics in Romania but also offers a flexible, scalable framework for classifying crime risk levels across different regions. Full article

Child-to-parent violence occurs when children engage in violent behaviour towards family members; the principal victim is often the mother. The risk assessment instruments used to identify the risk and protective factors in youth offenders who perpetrate child-to-parent violence are not specific to this type of offense. This study aims to describe the child-to-parent violence group in relation to the risk and protective factors they present in comparison with the group of young people who committed an assault offence. The sample for this study consists of two groups of youth offenders. The first group committed child-to-parent violence, and the second group has committed a violent crime against individuals to whom they are not related. Young people who commit child-to-parent violence have higher scores on the SAVRY risk factors and lower scores on the SAVRY protective factor than young people who have committed an assault offence. The results reveal the importance of identifying the risk and protective factors presented by youth offenders who commit child-to-parent violence in order to create specific intervention programs for the needs and strengths presented by this group of young people. Full article

Long-acting buprenorphine formulations have been recently marketed for the Opioid Agonist Treatment (OAT) of opioid use disorder (OUD) associated with medical, social, and psychological support. Their duration of action ranges from one week up to 6 months. The non-medical use of opioids is increasing with a parallel rise in lethal overdoses. Methadone and buprenorphine are the standard treatment for opioid dependence. Methadone Maintenance Treatment (MMT) is widely recognized as one of the most effective ways of reducing the risks of overdose, crime, and transmission of HIV (Human Immunodeficiency Virus) in people who use opioids; however, its effectiveness has been hindered by low rates of uptake and retention in treatment. Furthermore, both methadone and buprenorphine are widely diverted and misused. Thus, a crucial aspect of treating OUD is facilitating patients’ access to treatment while minimizing substance-related harm and improving quality of life. The newly developed long-acting buprenorphine formulations represent a significant change in the paradigm of OUD treatment, allowing an approach individualized to patients’ needs. Strengths of this individualized approach are improved adherence (lack of peaks and troughs in blood concentrations) and a reduced stigma since the patient doesn’t need to attend their clinic daily or nearly daily, thus facilitating social and occupational integrations as the quality of life. However, less frequent attendance at the clinic should not affect the patient–physician relationship. Therefore, teleconsulting or digital therapeutic services should be developed in parallel. In addition, diversion and intravenous misuse of buprenorphine are unlikely due to the characteristics of these formulations. These features make this approach of interest for treating OUD in particular settings, such as subjects staying or when released from prison or those receiving long-term residential treatment for OUD in the therapeutic communities. The long-lasting formulations of buprenorphine can positively impact the OUD treatment and suggest future medical and logistic developments to maximize their personalized management and impact. Full article

Augmented intelligence—as the fusion of human and artificial intelligence—is effectively being employed in response to a spectrum of risks and crimes that stem from the online sexual exploitation marketplace. As part of a study that was sponsored by the National Institute of Justice, the National Center on Sexual Exploitation has documented 15 tactics that have been used in more than 2650 US cities and counties to deter sex buyers from engaging with prostitution and sex trafficking systems. One of these tactics, technology-based enforcement and deterrence methods, has been used in more than 78 locations in the United States. This paper explores the issue of technology-facilitated trafficking in the online sexual exploitation marketplace and juxtaposes this with the use of augmented intelligence in collaborative responses to these crimes. Illustrative case studies are presented that describe how two organizations employ technology that utilizes the complementary strengths of humans and machines to deter sex buyers at the point of purchase. The human(e) touch of these organizations, combined with artificial intelligence, natural language processing, constructed websites, photos, and mobile technology, show significant potential for operational scaling, and provide a template for consideration by law enforcement agencies, criminal justice systems, and the larger multidisciplinary counter-trafficking community for collaborative replication in other settings. Full article

Static indicators may fail to capture spatiotemporal differences in the spatial influence of urban features on different crime types. In this study, with a base station analogy, we introduced crime risk stations that conceptualize the spatial influence of urban features as crime risk signals broadcasted throughout a coverage area. We operationalized these risk signals with two novel risk scores, risk strength and risk intensity, obtained from novel distance-aware risk signal functions. With a crime-specific spatiotemporal approach, through a spatiotemporal influence analysis we examined and compared these risk scores for different crime types across various spatiotemporal models. Using a correlation analysis, we examined their relationships with concentrated disadvantage. The results showed that bus stops had relatively lower risk intensity, but higher risk strength, while fast-food restaurants had a higher risk intensity, but a lower risk strength. The correlation analysis identified elevated risk intensity and strength around gas stations in disadvantaged areas during late-night hours and weekends. The results provided empirical evidence for a dynamic spatial influence that changes across space, time, and crime type. The proposed risk functions and risk scores could help in the creation of spatiotemporal crime hotspot maps across cities by accurately quantifying crime risk around urban features. Full article

Southern Italy suffers from a high poverty rate, unemployment, emigration flows, and a strong presence of organized crime in the field of agriculture. This study seeks to investigate the potential of social enterprises as driving forces for the legal and eco-social development of fragile Southern Italian areas. To work in such challenging contexts requires the development of a high level of resilience, which implies the ability to adapt to difficulties and to overcome crises by coming out stronger than before. The initiatives we detected in Southern Italy are examples for the strength that can come from ideal motivations. In the case of social agriculture initiatives in Southern Italy counteracting organized crime, these motivations are an indispensable condition for their survival and growth. The accumulation of problems and difficulties, however, risks corroding motivations of the actors. This can lead to the withdrawal of members, which can have a serious impact on these small organizations. Thus, idealism is a necessary condition to face the challenges of legal and social environmental development, but it is not sufficient on its own, except in the short term, to allow social enterprises to emerge from extremely precarious conditions. Idealism can support resilience, but by itself, it cannot create a sustainable change. There is, therefore, the need to invest in these social enterprises, in the training of the actors involved, and in the selection and acquisition of the skills for strengthening the efficiency and sustainability of businesses and to foster horizontal structures of mutuality and solidarity to create a supportive environment for these social enterprises and their mission. Full article

Background: Resiliency is the ability to prepare for, recover from, and adapt to stressors from adverse events. Social vulnerabilities (limited access to resources, political power, and representation; lack of social capital; aspects of the built environment; health inequities; and being in certain demographic categories) can impact resiliency. The Vietnamese population living along the Mississippi Gulf Coast is a community that has unique social vulnerabilities that impact their ability to be resilient to adverse events. Objectives: The purpose of this project was to address social vulnerability by implementing and evaluating a volunteer Community Health Advisor (CHA) project to enhance community resiliency in this community. Methods: A program implemented over eight three-hour sessions was adapted from the Community Health Advisor Network curriculum that focused on healthy eating, preventing chronic conditions (hyperlipidemia, diabetes, hypertension, cancer, and poor mental health). Topics also included leadership and capacity development skills. Results: Participants (n = 22) ranged from 35 to 84 years of age. Most were female (63.6%), married (45.5%), unemployed (63.6%), had annual incomes of <$10,000, and had high school diplomas (68.2%). Community concerns were crime (50.0%), volunteerism (40.0%), language barriers (35.0%), and food insecurity (30.0%). Approximately 75% had experienced war trauma and/or refugee camps, and 10% had experienced domestic violence. Scores on the Community Health Advisor Core Competency Assessment increased from pre-test to post-test (t = −5.962, df = 11, p < 0.0001), as did SF-8 scores (t = 5.759, df = 17, p < 0.0001). Conclusions: Strategies to reduce vulnerabilities in the Vietnamese community should include developing interventions that address health risks and strengths and focus on root causes of vulnerability. Full article