All posts by Matthew

Proposal Example

The research proposal,“The causes of drug addiction among street children in Dhaka city,” was prepared by Sazzad Karim, of the University of Dhaka. This is a rather short proposal of six pages, including the cover page, content page, and bibliography. The content page lists elven sections: Abstract, Introduction, Aims & Objectives, Literature review, Methodology, Analysis of data, Ethical consideration, Time frame, Limitations, Anticipated result, and Reference. However, each section is limited and brief in the information provided.

The purpose of this study, according to the proposal, is to “help us to know the present scenario of drug addiction among street children in Dhaka city and suggest the way to eliminate this dangerous situation.” The study intends to gather data from three randomly selected spots that have a “high concentration of street children” in Bangladesh. The proposal lists areas that are to be randomly selected and researched by three teams of five members each to interview samples of individuals.

For the proposal, one-hundred street children from each of the three spots selected is said to be ideal. This means that total sample for the study would be three-hundred, total. The research relies on a survey and respondent method from street children, using a snowball technique. A snowball technique would require referrals from individuals being survey, to find other street children that could be potential samples. As discussed in class, this type of method could be problematic. It is difficult to survey individuals with issues involving substance abuse because they can be unreliable.

Ultimately, this proposal could use some fine tuning to be more clear to the person reviewing. Because this proposal is intended to be read by an associate professor of the University of Dhaka, it could explain the flaws, as there is a conflict of interest.

REFERENCE:

Karim, Sazzad. “A Research Proposal on “The Causes of Drug Addiction among Street Children in Dhaka City” Submitted to Prepared by.” A Research Proposal on “The Causes of Drug Addiction among Street Children in Dhaka City” Submitted to Prepared by. N.p., n.d. Web. 03 Apr. 2016.

Review: “Abuse Victimization in Childhood or Adolescence and Risk of Food Addiction in Adult Women”

This study is centered around the association between child abuse victimization and food addiction. According to the research child abuse is  somehow connected to the increase in obesity risk in adulthood. The Nurses’ Health Study II is a survey that was used to measure physical and sexual child abuse histories in the year 2001 along with the food addiction in 2009.

The study found that 8% of the participants in the sample reported physical abuse during childhood while 5.3% reported sexual abuse. Additionally, the study found that 8% of the sample met the criteria for food addiction. Severe physical and sexual abuse during childhood were associated with 90% of increases in food addiction risk.

The study concluded that a history of child abuse is strongly associated with food addiction in the sample studied. While this study reports numeric results, it lacks in-depth interviews. There is a hole in the explanation and analysis of the data. Food addiction could be a symptom of childhood abuse or something completely independent. Whether food is used as a cope mechanism for the childhood abuse and or post traumatic distress, remains unknown in this particular study. This study does not pursue this information fully. What we find is that the specific sample that was dissected and studied happens to have a portion that has a food addiction and were victims to childhood abuse. This does not mean that because of one factor, the other factor will increase, necessarily.

“Abuse Victimization in Childhood or Adolescence and Risk of Food Addiction in Adult Women.” Wiley Online Library. N.p., n.d. Web. 27 Mar. 2016. <http://onlinelibrary.wiley.com/doi/10.1002/oby.20500/full>.

Review: “Course characteristics and college students’ ratings of their teachers: What we know and what we don’t”

This study focuses on the ratings college students give for their teachers. In order to understand the ratings given for teachers, the study sought characteristics that were “associated” with the ratings. Due to existing research, the study focused on five specific characteristics: “class size, course level, the ‘electivity’ of the course, the particular subject matter of the course, and the time of day that the course is held.”

The associations draw from the study are reported to be moderate or not very strong. The teacher ratings were often higher for upper division courses and elective courses. Additionally, professors in the areas of humanities, fine arts, and languages also tended to receive higher ratings than others.

According to the study, there are many explanations for the relationships made between ratings and professors. Studies in which controlled studies are relevant are fewer  than those that only have “zero-order” relationships between characteristics and ratings. This means that the relationships aren’t dependent on one variable or another.

In my evaluation of the study, classes that offer more freedom tend to receive higher ratings. Electives are more likely to receive better ratings because the students are able to choose the course as opposed to it being required. Upper division courses I would assume have older students with more knowledge about what they are learning. Therefore, a respectable rating for a course would not be strange.

Citation:

Feldman, Kenneth A. “Course Characteristics and College Students’ Ratings of Their Teachers: What We Know and What We Don’t.” Link.springer.com. N.p., n.d. Web. 20 Mar. 2016. <http://link.springer.com/article/10.1007/BF00976997>.

Review: “US College Students’ Use of Tobacco Products”

According to the study, adults between the ages of 18 and 24 are representative of the “legal” targets for tobacco industry marketing. It is also highlighted that a large portion of these young adults being targeted are college students. While actually cigarette smoking is more common, this study seeks to find research on the usage of tobaccos products that are not cigarettes by college students or cigar use by adults regardless of their age.

The objective of this study is “to assess the prevalence of all forms of tobacco use (cigarettes, cigars, pipes, and smokeless tobacco) among US college students and to identify student- and college-level factors associated with use of each product.”

To gather data, the Harvard College Alcohol Survey, was utilized. This is a self-administered survey that was conducted in 1999. The sites for this study were one-hundred nineteen “nationally representative US 4-year colleges.” From these colleges, a total of 14,138 students were randomly selected, which indicated a sixty-percent response rate.

The variables tested consisted of self-reported use of any and all tobacco products within the past 30 days, past-year, and lifetime.

The study concludes that the use of tobacco products is not limited to cigarettes. For this particular study, it is important to note the percentage of survey response. For the class study, we must keep in mind the types of questions that we ask in order to receive the most responses possible while conducting a research with accurate, genuine results. In this survey, maybe some students were not comfortable admitting their use of tobacco due to social repercussions or whatever the reasonings may be.

Citation:

“US College Students’ Use of Tobacco Products.” JAMA Network. N.p., n.d. Web. 13 Mar. 2016. <http://jama.jamanetwork.com/article.aspx?articleid=192969&resultclick=1>.

“Racial Discrimination and Alcohol-Related Behavior in Urban Transit Operators” Analysis

The study “Racial Discrimination and Alcohol-Related Behavior in Urban Transit Operators” analyzes findings from the San Francisco Muni Health and Safety Study. The objective of the study was to determine if there is a trend between racial discrimination and alcohol-related behaviors. For this study, a sample of urban transit operators was used.

The data gathered was used to conduct a cross-sectional study. Data from transit operators in San Francisco, California (1993-1995) consisted of a survey approach. In the survey, the responses to two sets of questions relating to racial discrimination, were closely examined. The first set of questions focused on “reaction to unfair treatment.” On the other hand, the second set focused on “arenas, or domains,of discrimination.” The variables that were considered in the study consisted of “number of drinks per month, heavy drinking, alcohol dependence, and negative consequences of alcohol consumption.”

According to the study, operators who reported five or more domains of discrimination also drank an average of 13.4 more drinks per month than those who reported no domains of discrimination (P= 0.01). Operators who reported more domains of discrimination were also found to be more likely to be heavy drinkers than those who reported none.

The study concludes that the data collected from the sample of urban transit operators revealed a correlation between the amount/number of domains of discrimination and a fraction of alcohol-related outcomes. However, there was no correlation for many of variables tested.

This conclusion could be pursued further. However, due to the lack of information gathered, it is difficult to draw conclusions about number of domains of discrimination reported, the operators, and link the results with alcohol use. It links two things that may or may not be dependent on one another.

Citation

Yen, I. H., D. R. Ragland, B. A. Greiner, and J. M. Fisher. “Racial Discrimination and Alcohol-Related Behavior in Urban Transit Operators: Findings from the San Francisco Muni Health and Safety Study.” Public Health Reports. U.S. National Library of Medicine, n.d. Web. 06 Mar. 2016. <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1308517/>.

“Alcohol Retail Density and Demographic Predictors of Health Disparities: A Geographic Analysis”

This study gave a geographic analysis of “Alcohol Retail Density and Demographic Predictors of Health Disparities.” The purpose of the research was to determine whether there is a correlation between the geographic density of alcohol retailers and higher levels of “demographic characteristics that predict health disparities.”

In order to carry this experiment out, the researchers gathered information on the alcohol retailers in the United States and organized the data on a map. The displayed the level of alcohol outlet density at the US Census tract level. US Census data was able to reveal “tract-level” measures on characteristics such as poverty, education, crowding, and race/ethnicity of the population samples. The method used was a multiple linear regression in order to compare the relationship between the factors considered along with the retail alcohol density.

The results revealed a strong nonlinear relationship between alcohol outlet density with race, poverty and education. In “urban” areas, high-proportions of black and latino populations tended to have higher alcohol-outlet densities. In particular, in places with high Latino communities, the alcohol density was found to be “twice as high as the median density.” However, in places with small populations of inhabitants, the factors researched tended to lack relationships.

Ultimately, the study concluded that “a greater density of alcohol retailers was associated with higher levels of poverty and with higher proportions of Blacks and Latinos in urban census tracts.” While there may be a relationship between alcohol outlet-density levels and “demographic characteristics that predict health disparities” does not mean that one factor necessarily affects the rise in the other. This means that it happens that places with higher alcohol-outlet densities also have populations with certain demographic characteristics are common. This could also mean that the areas researched could have a history of conditions such as alcoholism and other characteristics that make them give these kind of results.

Citation:

Berke, Ethan M., Susanne E. Tanski, Eugene Demidenko, Jennifer Alford-Teaster, Xun Shi, and James D. Sargent. “Alcohol Retail Density and Demographic Predictors of Health Disparities: A Geographic Analysis.” American Journal of Public Health. U.S. National Library of Medicine, n.d. Web. 21 Feb. 2016. <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2936987/>.

“The Risk of Assaultive Violence And Alcohol Availability In Los Angeles County”

In a study done by Richard A. Scribner, David P. MacKinnon, and James H. Dwyer, researchers sought to find to what extent alcohol outlets in a community influence assaultive violence. An ecologic analysis of the 74 larger cities in Los Angeles County was performed for the year 1990. This method was used in order to determine whether there was a correlation between alcohol outlet density and assaultive violence rates in terms of geography.

According to the study, sociodemographic factors were responsible for the seventy-percent variance in the rate of assaultive violence when a multiple regression model was used. When the alcohol-outlet density was included in the in the model, the graph then showed a positive correlation. The results of the study revealed that for every alcohol-outlet, 3.4 assaultive violence offenses occurred. These results were based off of the general data gathered from Los Angeles County in 1990 with 50,000 residents, 100 alcohol-outlets, and 570 offenses per year.

Scribner, MacKinnon, and Dwyer concluded that a “higher levels of alcohol-outlet density are geographically associated with higher rates of assaultive violence.” This study also concluded that factors such as unemployment, income, race/ethnicity, house-hold size, and city-size were “independent” of the study. This would require further research to determine every one of these factors. However, because all of these factors vary per family and geographic location, it would be extremely difficult to make conclusions based off of one population. Further researching this data could potentially draw conclusions with all of these factors only for Los Angeles County and a generalized idea of another area.

Scribner, Richard A., MD, MPH, David P. MacKinnon, PhD, and James H. Dwyer, PhD. “The Risk of Assaultive Violence And Alcohol Availability In Los Angeles County.” <i>American Journal of Public Hea;th</i> 85.3 (1995): 335-40. Rpt. in N.p.: n.p., n.d. 335-40. Web. 14 Feb. 2016. &lt;http://ajph.aphapublications.org/doi/pdf/10.2105/AJPH.85.3.335&gt;.

“Early Disparities in Mathematics Gains Among Poor and Non-Poor Children”

“Early Disparities in Mathematics Gains Among Poor and Non-Poor Children: Examining the Role of Behavioral Engagement in Learning” by Keith Robinson, seeks a correlation between social class and mathematical performance amongst a sample of kindergarteners. The relationship between “poverty status, mathematics achievement gains, and behavioral engagement in learning” was closely examined through multilevel modeling. According to the article, research shows the students belonging to families in poverty tend to “score lower than non-poor students on standardized tests in mathematics at school entry.” Data was collected through a sample of 11,680 “poor, low-income, and non-poor” kindergarteners from the Early Childhood Longitudinal Study—Kindergarten Cohert of 1998-1999 (ECLS-K).

In analyzing the data, BE was essential in the explanation linking performance and poverty. In this study, BE is explained to be the “personal actions” of the kindergartens that demonstrate their “approaches to classroom learning.” The data gathered suggests that encouraging “classroom behavioral engagement” in impoverished students has the potential to balance disparities in mathematics achievement. These results were summarized through descriptive statistics and multi-level analysis. The descriptive analysis highlighted the means and standard deviations of students’ performance through descriptive variables such as identified race, parents’ level of education, and average age. The multilevel analysis compares hypotheses and their actual outcomes.

In analyzing the results, the study’s form of data gathering suggests unreliable results. Evaluations given by teachers of the students, suggest bias. Because their evaluations were thought to have been given with a consideration of the students’ poverty status, race, and performance, the study is unreliable.

Robinson, Keith. “Early Disparities in Mathematics Gains Among Poor and Non-Poor Children: Examining the Role of Behavioral Engagement in Learning.” The Elementary School Journal 114.1 (September 2013): 22-47. Print.

Review of “Changing Pattern and Process of High School Dropouts between 1980s and 2000s”

“Changing Pattern and Process of High School Dropouts between 1980s and 2000s” by Suhyun and Jingo Suh investigates the general decline in dropout rate and increase of school completion. According to the article, the high school drop out rate has decreased in the period between the 1980s and 2000s.

The research focused on the dropout rate and completion rate over three decades using decomposition analysis. According to the authors, cross-section analysis was insufficient for collecting the data necessary for the study. Two surveys from The National Survey of Youth (NLSY) from the 1980s and 2000s were used to track changes and or a correlation of both rates. This survey represents a sample of 9,000 to 12,500 youths who’s ages ranged from 12 to 16 from December 31, 1978 and 1996. Two surveys were used to determine the completion rate of a sample which was then compared with the surveys when the ages of the sample were between 20 and 24 years old.

The NLSY gathered data such from various aspects of the youths’ lives including behavioral, personal, educations and familial experiences. Of this information, eight factors were found to be most influential in both surveys. These categories consisted of minority race, gender, living with biological parents, mother’s permissiveness, household size, whether the you lived in a metropolitan area, whether the youth lived south or west, and school suspension at least once.

The results of the study found little correlations between the high school dropout rate and completion rate from the 1980s to the 2000s. The researchers discovered that unknown independent variables were crucial in understanding the fluctuating pattern of dropouts, long term. The authors also suggested the need for educators to be informed on which students are more likely to drop out in order to prevent it.

Suhyun Suh and Jingo Suh. “Changing Pattern and Process of High School Dropouts between 1980s and 2000s.” Educational Research Quarterly 34.4 (2011): 3-13. Print.