Gruenewald, P.J., Freisthler, B.T., Remer, L., Lascala Term Paper

Pages: 8 (2008 words)  ·  Style: APA  ·  Bibliography Sources: 3  ·  File: .docx  ·  Topic: Sports - Drugs

Gruenewald, P.J., Freisthler, B.T., Remer, L., LaScala, E.A., a. & Treno, a. (2006). Ecological models of alcohol outlets and violent assaults: Crime potentials and geospatial analysis. Addiction, 101(5): 666-677.

In this study, Gruenewald and his colleagues sought to determine if there was a relationship between the densities of alcohol outlets in a given area with the crime potential of the same area.

In this quantitative quasi-experimental data analysis, the area used was that of locations within California whose zip codes were in the 1637 range. Assault rates were measured using cross-sectional data on hospital discharges for violent assaults, which were then related to measures of population and alcohol outlet density using Poisson modeling procedures.

The findings suggested the density of alcohol outlets was significantly related to the number of violent crimes within unstable minority areas and in rural middle-income areas.

Freisthler, B., Needell, B., & Gruenewald, P.J. (2005). Is the physical availability of alcohol and illicit drugs related to neighborhood rates of child maltreatment? Child Abuse & Neglect, 29(9): 1049-1060.

In this study, Freisthler and her colleagues sought to determine if there was a correlation between the availability of alcohol and illicit drugs, measured by alcohol outlet density and police incidents of drug possessions, and neighborhood rates of Child Abuse and neglect, as reported by police officials. This quantitative quasi-experimental test used data from 304 block groups in California.

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Following data analysis using Poisson modeling procedures, the researchers found that areas with a higher concentration of alcohol outlets and higher numbers of drug possession incidents also had higher levels of child maltreatment incidents, even after controlling for other demographic variables.

Gorman, D., Zhu, L., & Horel, S. (2005). Drug "hot spots," alcohol availability and violence. Drug and Alcohol Review, 24(6): 507-513.

TOPIC: Term Paper on Gruenewald, P.J., Freisthler, B.T., Remer, L., Lascala, Assignment

In this study, Gorman and his colleagues sought to show whether there was a relationship between the density of alcohol outlets and drug hot spots on the rates of crime. This quantitative quasi-experimental test used data from the city of Houston, Texas. A sample of 439 census tracts was used and socio-structural information, alcohol density, drug crime density, and violent crime density data was collected from archival sources and analyzed using spatial statistics and using hierarchical Bayesian modeling. The researchers found that, even when socio-structural variables were controlled for, alcohol outlet density was a significant predictor of violent crime.

The link between alcohol availability and crime has been studied for several years across a multitude of variables and using a number of different data collection and analysis techniques. Since socio-economic status, head of household, age, and neighborhood information can all affect the crime rates of a given area, researchers must account for all other variables before examining the results of their particular study. Further, the design, sampling, population, data analysis techniques, and overall methods must support a sound, valid, ethical, and overall reliable experiment in order to be truly credible.

This paper discusses three research articles pertaining to the topic of alcohol availability and crime, and will discuss the research question, data strategy, and results of each. Next, this paper will analyze one of the articles in depth according to a specific set of criteria (See Appendix a) in order to show the article is a valid and credible piece.

The first article we will examine is "Ecological models of alcohol outlets and violent assaults: Crime potentials and geospatial analysis." By Gruenewald, et al. (2006). The research question was whether the density of alcohol outlets had an effect on the crime potential of the same area. Crime potentials, according to the authors are often related to subpopulations within a given area, and thus, neighborhoods with certain subpopulations would be more likely to have higher crime potentials (Gruenewald, et al., 2006).

Their data strategy involved collecting violent assault discharge rates from hospitals in the zip code area, census data for the same area, and number of alcohol outlets within the areas. The data was then compiled using spatial statistical models, correcting for spatial autocorrelated errors (Gruenewald, et al., 2006). This is done to ensure endogenous variables included in the regressions specifications are not factored into the overall findings.

The researchers found that rates of assault were related to population statistics within the zip code area. Specifically, they noted a higher rate of relation in dense, low income, urban areas. Additionally, the researchers found a correlation between the density of off-premise alcohol establishments and crime, but found no relation between density of on-premise alcohol outlets and crime potential. The researchers concluded that alcohol outlets have a direct effect on crime potential within specific demographic groups (Gruenewald, et al., 2006).

The second article, that of "Is the Physical Availability of Alcohol and Illicit Drugs Related to Neighborhood Rates of Child Maltreatment?" By Freisthler, et al. (2005) was similar in content. The research question in this study was whether there was a correlation between the availability of alcohol and illicit drugs, measured by alcohol outlet density and police incidents of drug possessions, and neighborhood rates of child abuse and neglect, as reported by police officials. Three hundred four census block groups in California were examined in correlation with the number of alcohol outlets within each area, and the number of child neglect or abuse reports within each area. The data was analyzed using spatial regression techniques (Freisthler, 2005).

The researchers found that neighborhoods with higher concentration of alcohol outlets also had higher numbers of child mistreatments, even after controlling for neighborhood demographic characteristics (Freisthler, 2005). The researchers then concluded that more bars may indicate a lack of resources available for residents, may attract less desirable populations, or may increase alcohol intake (Freisthler, 2005).

The third article is that of Gorman (et, al., 2005), titled "Drug "Hot Spots," Alcohol Availability and Violence." The research question in the study was whether the density of alcohol outlets and drug hot spots had an effect on the crime rates of a given area. A sample of 439 census tracts was used and socio-structural information, alcohol density, drug crime density, and violent crime density data was collected from archival sources and analyzed using hierarchical Bayesian modeling. The researchers concluded that, even when socio-structural variables were controlled for, alcohol outlet density was a significant predictor of violent crime (Gorman et al. 2005).

The research conducted by Gorman and his colleagues is the most reliable research article of the three presented. First, Gorman was clear in his discussion of the purpose of the study, that of the "geospatial relationship between aspects of the physical and social environment and the commission of violent crime" (Gorman, et al., 2005, p. 508). The hypothesis, stated within the first two paragraphs of the article, is clear, concise, and to the point. Further, the hypothesis, whether alcohol and drug outlets are related to crime in a given area, is clearly linked to the investigation of geospatial relationships and violent crime.

Additionally, the authors make very few assumptions in their description of the issue. While they note an elevated faith in hierarchical Bayesian modeling, they also explain their reasoning, which is clear, logical, and based on mathematical principles of statistical regression and analysis (Gorman, et al., 2005). This does not constitute bias, but rather, an educated use of a specific, valuable statistical tool. Further, the authors do not, within the article, show a bias toward any specific conclusion, and their own point-of-view is not input until the discussion portion of the article.

Gorman and his colleagues also use sound methods to obtain the results of the study. First, the methods section is extremely detailed, as is the data analysis portion of the article. One could easily replicate the same study, using exactly the same data comparison techniques, as well as the same data sets, if desired. The study design, that of a quasi-experiment that relates random effect models to census tract-level high violence areas using spatial analysis extension for model fitting is highly appropriate for this form of data analysis (Gorman, et al., 2005). This test removes any possible bias from samples, since the data is in a raw form. The sample size is a massive collection of non-personal information, which allows wider generalization, at least within the state of origin, that of Texas. Confounding variables were controlled through the use of the hierarchical Bayesian model for statistical comparison. Further, the use of hierarchical Bayesian modeling produces as opposed to traditional Poisson models makes the data even more credible. According to Gorman's research, the Bayesian model is able to identify "unexplained variances" within results using "spatially correlated effects or heterogeneity effects (Gorman, et al., 2005), whereas the Poisson model, used in the other two research articles listed, can not.

Still further, Gorman and his colleagues answered the research question both through an analysis of data as well as through the verbal communication of that data. The findings clearly support their original hypothesis, and the author then uses those findings to indicate objectives for future research (Gorman, et al., 2005).

Additionally, the conclusions of the article fit… [END OF PREVIEW] . . . READ MORE

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