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Quantitative research

Introduction
This chapter describes the research design of this study. Following the introduction, this chapter is divided into sections that give detailed information on the research questions, hypothesis, and the analytical methods used in this study. The effects adolescent victimization is many. Scott (2002) stated that these effects as short and long term. Early adolescence is a crucial period of development due to many biological, cognitive, and social changes that occur during this time. Peer relationships and interactions during the middle school years greatly influence differentiation and individuation of self-concepts. It is during early adolescence that an extremely fragile sense of self begins to unfold. Adolescents in this stage of development are able to recognize contradictions in their self-concepts and in how they conceptualize others, but they are not yet able to explain or reconcile these contradictions (Harter, 1998). Experiences during this time of social development will shape eventual identity formation in later adolescence and early adulthood. Bergin and Bergin (2011, p. 391) described that scholars have managed considerable thought in understanding how victimization alters youth and influences abuse, including drugs, alcohol, and other substance use with mental health difficulties amongst youth nowadays.

1.2. Research Aims & Objectives
Research Questions: The study was guided by the following research questions:

  • What is the relationship between exposure to community violence and indicators of adolescent academic performance?

  • What are the differences in the indicators of academic performance of adolescents’ who have high perceptions of community violence and low perceptions of community violence?

  • How does the method of violence exposure (witnessing versus victimization versus both witness and victim) impact indicators of academic performance?

Study Rationale

Research Aim: The aim of this study was to examine the impact exposure to community violence had on indicators of adolescence academic performance. Moreover, this study examined whether type of exposure to community violence would result in decreased academic performance among adolescents.

Research Objective: In order to provide an in-depth analysis of the impact on adolescent development, the main objective of this research is to examine not only the experience of violence, but also the witnessing and threat of violence to gain a true picture of the impact. Study Rationale:

Research on school-based victimization in adolescence is vital if we are to understand a problem that is garnering increasing attention in the media. Without well-designed, theoretically driven, empirical work in this area, we run the risk of leaving decisions about the social well-being of a large proportion of American society in the hands of ill-informed mental health professionals. Through no fault of their own, the interventions implemented may be inadequate to address the needs of their students. Thus, addressing the challenges to conducting this research that arise from questions is essential. By examining the varying components of exposure to community violence, this study addressed the aforementioned issues that are often lacking in the research on measurement of exposure to community violence.

Research Hypothesis:

What is the relationship between exposure to community violence and indicators of adolescent academic performance?

  • Null Hypothesis: There is no statistically significant relationship between exposure to community violence, as measured by yes or no responses to 11 surveys items on the NYS, and indicators of adolescent academic performance, as measured by yes or no responses to two survey items: (a) having to repeat a school grade and (b) having at least one failing grade on the repeat card.

  • Alternative Hypothesis: There is a statistically significant relationship between exposure to community violence, as measured by yes or no responses to 11 surveys items on the NYS and indicators of adolescent academic performance, as measured by yes or no responses to two survey items: (a) having to repeat a school grade, and (b) having at least one failing grade on the report card.

2. Methodology

Research Design:

This study employs a quantitative research design. This quantitative study was designed to examine exposure levels of community violence in adolescent males and females to determine its impact on indicators of academic performance. This was a cross-sectional study design in which data were collected to help answer research questions related to impact of exposure to community violence exposure on indicators of adolescent academic performance. To address this problem, descriptive and nonparametric inferential statistic methods were used.

Unlike previous studies (Johnson et al, 2002, for example), this study did not aggregate measure of adolescent victimization. It dissected the complex relationship between victimization and offending by delineating between different types of victimization (direct or indirect), and also making distinctions within each type (personal and property and victimization by exposure to violence through the neighborhood and family (Abram et al., 2004; Warren et al, 2003). More specifically, this study sought to explore who is more likely to offend and who will potentially emerge as the most violent based on what we know about their past victimization experiences.

 

Details of Research Design:

This study was based on archival data from the NYS of adolescents in the United States (Kilpatrick, & Saunders, 1995). The data was originally gathered for a study conducted by researchers at the Medical University of South Carolina, National Crime Victims Research and Treatment Centre. The primary intent of the original study was to understand the role of victimization during adolescence in increasing the risk of psychological distress, substance abuse, and delinquent behaviour. This archived data was obtained through the Inter-Consortium for Political and Social Research’s Violence online data warehouse and used because of the content and appropriateness of the initial research in relation to the present study.

The survey was organized to capture demographic data first, and then went into questions related to exposure to violence. After the demographic questions, yes or no questions about witnessing violence were asked. Depending on responses to these questions, follow-up questions were asked related to the number of times they witnessed violence and for each episode of witnessing, who the adolescent witnessed and their relationship to the person they witnessed. Once determining frequency of witnessing, questions were asked about the emotional impact these events may had on the adolescent. Following questions related to witnessing violence, questions were asked about experiencing sexual assault. Similar pattern for witnessing, questions were then asked about frequency, age the incidents occurred, who the person who did this to them was, and the emotional impact. Following this section, questions were asked about being a victim of violence. The same pattern for follow-up questions was followed for this section. The next section asked questions about alcohol, tobacco, and other drug use. The final section of the survey asked more detailed questions about the adolescent related to place of residence and with whom they lived with most.

 

Sampling:

Participants for this study were part of the National Youth Survey, which were drawn from a telephonic survey of American Youth, living in the United States, aged 12-17 years. The survey was conducted between January 1995 and June 1995 and consisted of two sub samples, “a national probability household sample of 3,161 adolescents and a probability oversample of 862 adolescents residing in central city areas of the United States, for a total sample of 4,023 (Kilpatrick, & Saunders, 1995, p. 5). To determine sample size, “The United States was stratified geographically by Census region and a population-based subsample allocation was developed for each geographic stratum. In other words, the number of households drawn for the sample from each geographic stratum was allocated in proportion to the actual distribution of the population residing within each stratum, according to the most recent Census estimates (Kilpatrick, & Saunders, 1995, p. 5).

The sample was weighted to conform to 1995 Census estimates for American adolescents on age, race, and gender, in order to better generalize to the U.S. adolescent population (Kilpatrick, & Saunders, 1995). Adolescent interviews were conducted in 75% of the households eligible for the study.

The NYS (Kilpatrick, & Saunders, 1995) is a 303-item, highly structured interview which required between 45 and 150 minutes to complete. Adolescents who had been assaulted or who used substances were asked follow-up questions about these experiences (these interviews took up to 150 minutes to complete). Sample selection and interviewing were conducted by a New York-based survey research firm, Schulman, Ronca, and Bucuvalas, Inc. (SRBI) (Addison-Scott, 2008). To conduct the initial national probability sample, a multi-stage, stratified, area probability, Random Digital Dialling (RDD) 4-step sampling procedure was employed.

 

Variables/Instrumentation:

The variables that were examined in this study included indicators of academic performance, perceptions of neighbourhood violence, witnessing violence, and being a victim of violence (victimization). Furthermore, background characteristics such as race/ethnicity and gender of the participants were reported.

Table: Dependent or independent variables.

Adult Problem Outcome

(Dependent Variable)

RL2

Adolescent Experience / Characteristic

(Independent Variable)

Odds Ratio

p(lr)

Violent Victimization (n=506)

0.042

Violent Victimization

Age in 1976: 11

12

13

Victimization-age interaction

2.2513

2.3190

0.8596

0.5016

1.8335

0.0001

0.0024

 

 

0.0278

Property Victimization (n=507)

0.012

Property Victimization

1.9431

0.0045

Domestic Violence Victimization (n=491)

0.059

Violent Victimization

Violent Offending

Male

Parent’s socioeconomic status

1.7083

1.4827

1.9231

0.9780

0.0537

0.0960

0.0046

0.0022

Violent Offending (n=496)

0.148

Violent Offending

Violent Victimization

Male

Parent’s socioeconomic status

2.4893

2.8771

2.7919

2.1114

0.0034

0.0115

0.0011

0.0377

(Note: All statistics that are given in the above tables are cumulative (that is, they reveal the students’ overall experiences from their first interviews to last interviews conducted by NYS). These statistics are Pearson’s r values, which imply that each number reveals a linear relationship between the two variables (e.g., violent victimization and felony assault) (Bureau of Justice Statistics, 1994). The numbers given in brackets are neither numerically important nor marginally important (with p < .05 on behalf of numerical importance and p < .10 in place of marginal importance); all other statistics (without brackets) are at least marginally important).

No information on the reliability and validity of the instrument used were reported in any of the documentation about this survey or subsequent studies using this data. Since no information on the reliability of the instrument was reported, an internal consistency measure of reliability estimates was conducted for this study. A Chronbach’s (1951) alpha was determined for three scales: victimization, witnessing, and overall exposure to violence, which is the combination of witnessing and victimization questions (cited in Wilson, 2009). The reliability of the witnessing violence scale was calculated based on responses to six questions asked of respondents: (a) having seen someone shot, (b) having seen someone stabbed, (c) having seen someone being sexually assaulted or raped, (d) having seen someone robbed or mugged, (e) having seen someone threatened with a knife, gun or other weapon, and (f) having seen someone beaten up, kicked, hit, or punched such that they were hurt badly. The victimization scale was based on responses to five questions: (a) having or ever been attacked with a weapon, (b) having ever been attacked without a weapon, (c) having ever been threatened with gum or knife, (d) having ever been beaten up with an object and hurt badly, and (e) having ever been beaten up with fists and hurt badly. The overall exposure to violence scale was assessed based on responses to the six questions for witnessing and the five questions for victimization. Although no information on validity was reported, the survey did appear to have face validity. Furthermore, since its development, this survey has been used to examine exposure to community violence and role is exacts upon adolescents’ behavioural and psychological lives.

 

Dependent or Independent Variables:

The dependent variables in this study are the witness and exposure to violence, and perceptions of community violence at schools. This is believed to be dependent on the management of the independent variable in that the allocation of income is based on area and gender has an impact on student’s academic performance at schools. The control variable is also based on gender as either male or female, however this was not identified as an independent or dependent variable because the research is not based on gender, instead it is based on the student’s academic performance at schools.

 

Data Collection

Babbie (1992) defines secondary analysis as “the analysis of data collected earlier by another researcher for some purpose other than the topic of the current study” (p. 282). There are some advantages to using secondary data analysis in that it is unobtrusive, less expensive, and allows for access to data from large, national samples (Kiecolt, & Nathan, 1985). Hofferth (2005) iterates that larger sample size allow for “greater precision of estimates of subgroups of the US population” (p. 893). However, there are few drawbacks as well. One is that sometimes data quality can be a concern. However, for nationally representative samples this is not typically an issue because these types of datasets typically have properly designed questionnaires and have employed rigorous procedures for interviewing and coding (Kiecolt, & Nathan, 1985).

All interviews were conducted by telephone. Interviews were initially conducted with parents to determine the number of eligible adolescence in the household. Where feasible, adolescents were interviewed immediately following parents. If this was not possible, appointments were scheduled for call-backs. Interviews with both parents and adolescents were conducted using Computer-Assisted Telephone Interviewing (CATI) technology. Using this method helped to ensure that all questions were asked, as interviewers could not proceed to the next item in the computer recording sheet without entering responses (Kilpatrick, & Saunders, 1995).

 

3. Limitations of the study

Survey research and other quantitative methods also employed inferential statistics to assess statistical relationships. Survey research also demonstrated other potential limitations, such as most often relying on self-reports and being susceptible to the adverse impact of social desirability, with respondents responding to questions in ways designed to please others or to follow acceptable social norms. Another potential concern is that members of a target population may not be very familiar or comfortable with the format of a survey procedure. A final concern is that survey research can impose, to some extent, investigator priorities and values on matters that may not be as germane to the population being studied. Survey procedures also typically compel respondents to use numerical values to indicate their beliefs, attitudes, values, and practices rather than obtaining their native language terms.

 

Assignment 1_Part 2

Types of Variables

In the analysis predicting the case study or control groups, the mediating variables (i.e., distribution of risk factors among the cancer patients) were the dependent variables. Any demographic covariate (e.g. sex, age, education, living area, living with other people, socio-economic status) are generally independent variables for the purpose of clinical treatment. This is because other variables depend on them. Of course, sometimes there could be a relationship of dependence between two demographic variables themselves. For instance, income may depend on the levels of education, or age of the cancer patients, in some cases.

 

Data Management and Data Cleaning

Data cleaning was conducted on all four samples: the two halves of the cross-sectional sample, and the full longitudinal sample. All data management and data cleaning were conducted in SPSS 19.0. Data cleaning consisted of removing duplicate, missing, and out-of-range data as well as data from univariate analysis.

During data cleaning, pilot data and duplicate records were first removed. Next, likewise deletion was employed to create datasets containing only records in which the examinee responded to every item. Importantly, the use of likewise deletion caused a substantial decrease in the number of usable records. All out-of-range responses were coded as missing and these data were removed from the dataset along with other cases that had missing data.

 

Descriptive Analysis Results

The multivariate analysis will be used for prediction and support of the hypothesis based on the regression model. The data sets used for the statistical analysis are considered appropriate and valid because they reflect the primary outcome of cancer patients and are derived from accumulative research in England hospital. The reliability of the information is also strong, because it is assumed that the educational establishments provided unaltered data sets.

Ordinal scale is used to measure variables. An ordinal scale contains distinct ordered qualitative categories. Labels, numbers, or other symbols are used to distinguish ordered categories. Observations that differ from category to category can be ranked accordingly to whether the observation is more or less of some criterion. The categories are qualitative in the sense that the distance between and among them is not measurable numerically. However, the number or percentage of observations in each category can be described. Duke’s (Duke, & Bussey, 1958) classification of colorectal cancer (stages A through D) is an ordinal scale. Stage A represents cancer limited to the mucosa and submucosa. Stage B denotes cancer that extends into the muscularis or serosa. Stage C signifies cancer that involves the regional lymph nodes. Stage D represents cancer that has metastasized to the liver, bone, and/or lung. The categories are ordered because the extent of the disease is more limited and prognosis more favorable in stage A than in stage D. In fact, approximately 90% of patients with cancer limited to the mucosa and submucosa (stage A) survive 5 years. In contrast, approximately 5% of patients whose cancer has metastasized to the liver, bone and lung survive 5 years (stage D).

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