Geetha Suresh

Homicide Patterns and Public Housing: The Case of Louisville, KY (1989-2007):

This study examines the impact of the revitalization of low-income, public housing properties on homicide patterns. It tracks the movement of homicide clusters from the initial properties to those neighborhoods where public housing residents were displaced over a 19-year period in Louisville, Kentucky. The median-income level of residents and vacant housing emerged as important predictors of homicide clusters. This article concludes that low-income public housing and Section 8 housing properties provide an environment where homicides are likely to occur. This pattern remained in effect even when the nature of public housing changed.

Emphasizing the servant in public service: the opinions of police managers

Purpose – The purpose of this paper is to determine the opinion of 126 police managers from 23 US states regarding their ideal leadership style as expressed under the items of the leader behavior description questionnaire (LBDQ).Design/methodology/approach – Police managers attending a management course – the Administrative Officers Course at the Southern Police Institute during the academic year 2007‐2008 – were surveyed regarding their opinions of ideal leadership styles. They responded to items on the leadership behavior questionnaire. The analysis is based on this survey.Findings – Item analysis of their responses revealed the existence of three subscales (servant, autocratic, and laissez‐faire leadership), ANOVA revealed a strong preference for the style of servant leadership. These results indicate that these police managers believe that leaders should follow the tenets of servant leadership. They rejected the creeds of both the autocratic, command and control method and the hands‐off, detached sty...

Design, data analysis and sampling techniques for clinical research

Statistical analysis is an essential technique that enables a medical research practitioner to draw meaningful inference from their data analysis. Improper application of study design and data analysis may render insufficient and improper results and conclusion. Converting a medical problem into a statistical hypothesis with appropriate methodological and logical design and then back-translating the statistical results into relevant medical knowledge is a real challenge. This article explains various sampling methods that can be appropriately used in medical research with different scenarios and challenges.

Drug Abuse Treatment Training in Peru: A Social Policy Experiment

A social policy experiment is presented that was conducted from 1997 to 2000 in a setting with a high level of readiness for implementing a randomized experiment of therapeutic community (TC) drug treatment training in Peru. Seventy-six drug abuse treatment organizations were randomly assigned into three groups, and data were collected at multiple assessment periods. Staff and directors in organizations assigned to the training groups participated in either 6-week basic training or 8-week basic plus booster training sessions, which were theoretically grounded. Small- to medium-size positive effects were found on increased staff empowerment to use actual tools and principles from the training; medium and large positive effects were found on the implementation of TC methods with fidelity after the training. A follow-up with the funding and training organizations 1 year later showed use of the evaluation results in decision making in both organizations.

Evaluation of the Therapeutic Community Treatment Model in Thailand: Policy Implications for Compulsory and Prison-Based Treatment

This study, conducted in 2005 to 2007, presents results that are based on a proscriptive cohort design. The sample consisted of 769 residents in 22 drug user treatment programs who stayed in treatment for at least 30 days to one year; 510 former residents (66%) from 21 programs (95%) were interviewed again at a 6-month post-treatment follow-up assessment. A majority of the participants were male, lived with family or relatives, had completed only primary school, and had a full-time or a part-time job prior to entering treatment. The participating therapeutic community (TC) programs were a mixture of volunteer, compulsory-probation, and prison-based programs. In-person interview data and urine testing showed that the self-reported drug use prevalence rates are reliable. The results show large positive treatment effects on 30-day and 6-month illegal drug use and small to medium effects on the severity of alcohol use and related problems. A multilevel regression analysis suggests that residents’ reduced stigma, adaptation of the TC model, and frequency of alcohol and drug use-related consequences partially predict treatment success. Study limitations and policy implications are discussed.

Issues in the aggregation and spatial analysis of neighborhood crime

Prior studies of neighborhood crime have largely overlooked a border issue in the aggregation of criminal incidents to small areal units and a denominator problem arising from the use of population to normalize crime counts and have failed to discern racial disparities in crime victimization due to the use of non-race-specific crime data. This article explores the relationships between neighborhood characteristics and robbery victimization by applying an improved method for neighborhood crime aggregation and normalization to race-disaggregated incident data. Results suggest that controlling for above issues helps better explain the spatial variations of robbery victimization across urban neighborhoods. The methods and findings have implications for improving the measurement accuracy of neighborhood crime and disentangling the effects of race and other socioeconomic factors on urban crime.

Design and data analysis 1 study design

This article is intended to give the reader guidance in evaluating different study designs used in medical research for better scientific quality, reliability and validity of their research. This article explains three main types of study designs with understanding examples. Care and caution with skills and experience needed to design suitable studies and appropriate design coupled with reliable sampling techniques and appropriate statistical analysis, supported by clear objectives with decent communication of the findings, are essential for good research.

Design and data analysis case-controlled study in clinical research.

Clinicians during their training period and practice are often called upon to conduct studies to explore the association between certain exposures and disease states or interventions and outcomes. More often they need to interpret the results of research data published in the medical literature. Case-control studies are one of the most frequently used study designs for these purposes. This paper explains basic features of case control studies, rationality behind applying case control design with appropriate examples and limitations of this design. Analysis of sensitivity and specificity along with template to calculate various ratios are explained with user friendly tables and calculations in this article. The interpretation of some of the laboratory results requires sound knowledge of the various risk ratios and positive or negative predictive values for correct identification for unbiased analysis. A major advantage of case-control study is that they are small and retrospective and so they are economical than cohort studies and randomized controlled trials.