Social and Behavioral Sciences Commons^™

How Do Food Shopping Behaviors Differ Between High-Income And Low-Income Shoppers In The Grand Rapids Metropolitan Area?, Alison M. Cooney

Masters Theses

Background: The social determinants of health and health equity are influenced by access, environment, and socioeconomic status (SES). Health inequities are preventable and can be avoided with systemic policy change surrounding the distribution of wealth and resources. Few studies have researched the differences in different income levels and the influence income has on food shopping behaviors.

Objective: The purpose of this study was to investigate the differences in food shopping behaviors between high-income and low-income shoppers living in the same zip code. Subjects Sixty-eight individuals who live in the 49341 zip code which represents a small city in Kent County, …

The Analysis Of Trauma-Informed Risk Assessments Within A Juvenile Justice System In A Midwest State, Kayla M. Bates

Masters Theses

With approximately 90% of justice-involved youth experiencing at least one traumatic event before entering the justice system, trauma-informed care has moved to the forefront of juvenile justice in recent years (Dierkhising et al., 2013). Trauma-informed care aims to capture and address the impact trauma has on youth. One area within the juvenile justice system that is critical to capturing these events in justice-involved youth are risk assessments. The current study aimed to address whether a Midwest state is using trauma-informed questions and incorporating aspects of intersectionality (gender identity, sexual orientation, race, ethnicity, and class) within practices directed at justice-involved youth. …

Recidivism, Gender, And Race: An Analysis Of The Los Angeles County Probation Department’S Risk And Needs Assessment Instruments, Robert V. Howard

Masters Theses

This study assesses the predictive validity of an adult risk need assessment, the Los Angeles Probation Department’s Risk and Needs Assessment Instruments, on 793 clients using several logistic regression models. Models were generated to look for a relationship between risk score and recidivism. This relationship is further explored across gender and race. There are two separate risk assessment instruments used in this study and the sample is separated into two separate groups. The first risk assessment instrument was based on static risk factors such as history of drug or alcohol use, age of first conviction, and conviction history. This assessment …