Theories explaining the relationship between neighbourhood stressors and depressive symptoms

This study synthesizes the current theoretical knowledge to explain the relationship between neighbourhood stressors and depressive symptoms. The two most relevant sociological theories, social disorganization theory and stress process theory, are identified. The current study carefully reviewed the two theories regarding their historical development and key conceptual aspects, beginning with the theoretical evolution of research on neighbourhood stressors and mental health. This study also provides detailed critiques on each theory and suggests how researchers can apply both theories to their empirical testing. For example, social disorganization theory points out the application of both objective and subjective aspects of neighbourhood stressors. Also, the stress process theory emphasizes the mediating or moderating role of psychosocial resources. In conclusion, this study suggests a conceptual model of neighbourhood stressors, psychosocial resources, and depressive symptoms.

A spatial Analysis of Crime and Neighborhood Characteristics in Detroit Census Block Groups

Crime has an inherent geographical quality and when a crime occurs, it happens within a particular space making spatiality essential component in crime studies. To prevent and respond to crimes, it is first essential to identify the factors that trigger crimes and then design policy and strategy based on each factor. This project investigates the spatial dimension of violent crime rates in the city of Detroit for 2019. Crime data were obtained from the City of Detroit Data Portal and demographic data relating to social disorganization theory were obtained from the Census Bureau. In the presence of spatial spill over and spatial dependence, the assumptions of classical statistics are violated, and Ordinary Least Squares estimations are inefficient in explaining spatial dimensions of crime. This paper uses explanatory variables relating to the social disorganization theory of crime and spatial autoregressive models to determine the predictors of violent crime in the City for the period. Using GeoDa 1.18 and ArcGIS Desktop 10.7.1 software package, Spatial Lag Models (SLM) and Spatial Error Models were carried out to determine which model has high performance in identifying predictors of violent crime. SLM outperformed SEM in terms of efficiency with (AIC:5268.52; Breusch-Pagan test: 9.8402; R2: 16% & Log Likelihood: −2627.26) > SEM (AIC: 5275.24; Breusch-Pagan test: 9.7601; R2: 15% & Log Likelihood: −2630.6194). Strong support is found for the spatial disorganization theory of crime. High percent ethnic heterogeneity (% black) and high college graduates are the strongest predictors of violent crime in the study area.

The Multilevel Effects of Changes in Disadvantage on Changes in Crime

While social disorganization theory suggests the importance of change, most prior research examining macro-level criminological associations uses cross-sectional data. The current study examines the multilevel relationship between changes in disadvantage and changes in crime over time using four data sources: the National Neighborhood Crime Study, the 2000 U.S. Census, crime-incidents occurring between 2005 and 2009, and the 2005–2009 American Community Survey. Analyzing 6,068 census tracts within 53 large U.S. cities using multilevel models with time nested within tracts nested within cities, I parse out the contribution of changes in tract-level disadvantage from city-level disadvantage to changes in robbery and burglary rates. Results indicate the importance of both static and dynamic associations between disadvantage and crime, at both the neighborhood and city level.

(Re)conceptualizing Neighborhood Ecology in Social Disorganization Theory: From a Variable-Centered Approach to a Neighborhood-Centered Approach

Shaw and McKay advanced social disorganization theory in the 1930s, kick-starting a large body of research on communities and crime. Studies emphasize individual impacts of poverty, residential instability, and racial/ethnic heterogeneity by examining their independent effects on crime, adopting a variable-centered approach. We use a “neighborhood-centered” approach that considers how structural forces combine into unique constellations that vary across communities, with consequences for crime. Examining neighborhoods in Southern California we: (1) identify neighborhood typologies based on levels of poverty, instability, and heterogeneity; (2) explore how these typologies fit within a disorganization framework and are spatially distributed across the region; and (3) examine how these typologies are differentially associated with crime. Results reveal nine neighborhood types with varying relationships to crime.

A Tale of Two Theories: Whither Social Disorganization Theory and the Routine Activities Approach?

Social disorganization theory and the routine activities approach have been extensively applied separately as theoretical frameworks for the spatial analysis of crime, with general support. As hypothetical explanations for complex social phenomena, criminological theories can impact how studies are framed and how the crime problem is approached. Thus, it is important to evaluate theories continuously in various geographical, as well as contemporary contexts. This study uses both theories in tandem to examine their ability to explain 2016 property crime in Vancouver, Canada, using 2016 census data. Both theories found moderate support. Of particular note is that all of the variables designated as proxies for ethnic heterogeneity in social disorganization theory were either not statistically significant or negative, consistent with the immigration and crime literature. Additionally, almost all variables, when statistically significant, were found to have consistent results across crime types. These results bode well for the continued use of social disorganization theory and the routine activity approach in spatial analyses of crime.

Individual- and School-level Predictors of Latent Profiles of Bullying Victimization: Comparing South Korea and the United States

This cross-national research investigated nationally representative adolescents from South Korea and the United States, explored similarities and differences in latent profiles of bullying victimization between countries, and examined individual- and school-level variables that predict such latent profiles supported by the Social Disorganization Theory. The fourth-grade sample of the 2015 Trends in International Mathematics and Science Study from South Korea ( N = 4,669) and the United States ( N = 10,029) was used to conduct a latent profile analysis based on eight items of the bullying victimization questionnaire. Multilevel logistic regression was conducted using latent profiles as dependent variables. Independent variables include individual-level (material goods, school absence, academic interest, school belonging) and school-level (concentration of affluent families, school resources, the severity of delinquency, academic commitment) factors. More similarities existed than differences in the latent groups of bullying victimization between South Korea ( rare, low-moderate, verbal-relational-physical, and multi-risk) and the United States ( rare, low-moderate, verbal-relational, and multi-risk). Evidence for school-level variables as predictors of bullying victimization profiles was stronger for adolescents in the United States, with a concentration of affluent families and severity of delinquency being significant in four of the six models. For the South Korean sample, the severity of delinquency predicted bullying victimization in only one model. Examination of both individual- and school-level factors that predict unique bullying victimization experiences grounded in Social Disorganization Theory may be informative for addressing key areas of intervention—especially at the school-level context in which victimization primarily takes place and where anti-bullying intervention programs are often provided.

Testing the Systemic Model of Social Disorganization Theory in South Korean Neighborhoods: A Latent Class Growth Analysis Approach to Specifying Pathways to Homicide

This study examines the relationship between structural characteristics and homicide trajectories in South Korean neighborhoods utilizing the systemic model of social disorganization theory as an analytical lens. Group-based trajectory modeling of Korean homicide data across 229 municipal-level sub-national regions between 2008 and 2013 yielded three groups: high-decrease, moderate, and low-stable. The odds of belonging to the high and moderate groups compared to the low-stable group were significantly increased for communities with a higher-level divorce rate and residential instability rate. Social control was significant in the high-decrease group compared to the low-stable group, but had no mediating effect on this relationship.