Question Description

The Literature Reviews should not include any class readings, as reviews must be from sources that you have discovered yourself. They should be written as bullet points, and should be about two pages in length.

For each source read, you should write a Literature Review which includes the following sections:

  • Provide full citation in MLA format
  • Identify the key concepts of the piece
  • Give some information on the author(s)
  • Define unfamiliar vocabulary if any exists
  • Give three pertinent quotations, correctly cited, AND explain the significance of each quotation
  • Explicitly explain how this material helps you to answer the research questions posed
  • Explicitly state how this reading connects to previous readings that you have done in this course, and trace areas of agreement and disagreement about particular topics.
  • Identify new questions so as to delve even more deeply into the research

These Literature Reviews should be of immense use not only in contributing to your body of knowledge about the topic under investigation, but also because sections of your reviews might be able to be imported directly into your research paper.

Example literature review

Source

Sandel, Michael J. “2. The Greatest Happiness Principle/ Utilitarianism.” Justice: What’s the Right Thing to Do? New York: Farrar, Straus and Giroux, 2009. 31 57.

Summary

Michael Sandel explores utilitarianism applied by Jeremy Benthan and John Stuart Mill. Benthan’s utilitarianism says that the standard of right and wrong is determined by plain and pleasure. This expert also showed that utilitarianism can fail to respect individual rights. John Stuart Mill had a classic denfense of individual freedom. He wanted to maximize utilty in the long run and not just by a case-by-case basis like Benthan believed.

Author Information

Michael Sandel is a professor at Harvard University. He teaches a course in Justice. He is a political philosopher most famous for his critique of John Rawl’s Theory of Justice.

Unfamiliar Vocab

  • Tepid: uninterested; considering little passion or eagerness
  • Utility: whatever produces pleasure or happiness, and whatever prevents pain or suffering

Quotes and meaning

  • “The first approach says that morality of an action depends solely on the consequences it brings about; the right thing to do is whatever will produce the best state of affairs, all things considered. The second approach says that consequences are not all we should care about, morally speaking; certain duties and rights should command our respect, for reasons independent of the social consequences” (Sandel 33).

The first approach would be in favor of favoring big interest groups and the second would be in favor of considering all groups equally no matter what the social consequence would be; in the case of Congress, the social component of getting re-elected.

  • Jeremy Benthan’s philosophy “exerts a powerful hold on the thinking of policy-makers, economists, business executives, and ordinary citizens to this day” (Sandel 34).

Since Benthan’s philosophy is already considered in the field it will strengthen my ethical argument. Objection to Bentham: This is against big interest groups financial and social influence over Congress. It isn’t ethical to impose the big interest groups view in legislation because it interferes with individual liberty in order for the individual (member of congress) to get re-elected.

  • “Allowing the majority to silence dissenters or censor-free-thinkers might maximize utility today, but it will make society worse off—less happy—in the long run” (Sandel 60).

Along with actions and consequenseces, character also matters when considering morality. Politicians who favor big interest groups or wealthy interest groups for the sole reason to have a better chance of getting re-elected and not because he believes in the matter has no character, and is therefore not acting in an ethical manner.

How the material helps

This material will help because it made me think of another view of utilitarianism. It also gave important quotes that proved that government thinks of these ethical principles; whether they apply them to their actions is questionable. It also gave me important information about rights in regard to ethics. Although legality doesn’t mean ethicality this material connected the two in a way that makes constitutional values necessary when considering ethics.

Connections with other readings (mention authors and titles)

This connects with Kwame Anthony Appiah, Experiments in Ethics, as both authors consider Utilitarianism .

Newly identified questsion

  • Even though legality doesn’t mean ethicality, do we need to consider constitutional rights when considering ethics

I have 2 articles, so there will 2 reviews that I will need.

First one

期刊全文

Changes in a Middle School Food Environment Affect Food Behavior and Food Choices RSS 下载PDF

  • Doug Wordell RD
  • , Kenn Daratha PhD
  • , Bidisha Mandal PhD
  • , Ruth Bindler PhD, RN
  • 和 Sue Nicholson Butkus PhD, RD

Journal of the Academy of Nutrition and Dietetics, 2012-01-01, 卷号 112, 期 1, 页 137-141, Copyright © 2012 Academy of Nutrition and Dietetics

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Abstract

Increasing rates of obesity among children ages 12 to 19 years have led to recommendations to alter the school food environment. The purpose of this study was to determine whether there are associations between an altered school food environment and food choices of middle school students both in and outside of school. In a midsized western city, two of six middle schools allowed only bottled water in vending machines, only milk and fruit on à la carte menus, and offered a seasonal fruit and vegetable bar. Three years after the intervention was initiated, seventh- and eighth-grade students attending the two intervention schools and four control middle schools were surveyed about their food choices. A total of 2,292 surveys were completed. Self-reported frequency of consumption for nine food groups in the survey was low; consumption was higher outside than in school. Boys consumed more milk than girls although girls consumed more fruits and vegetables. Significant socioeconomic differences existed. Compared with students who paid the full lunch fee, students qualifying for free and reduced-price meals consumed more milk and juice in schools but less outside school; more candy and energy drinks in school; and more sweet drinks, candy, pastries, and energy drinks outside school. Students in intervention schools were 24% more likely to consume milk outside school, 27% less likely to consume juice in school, and 56% less likely to consume sweet pastries in school. There were no differences in fruit and vegetable consumption reported by children in control and intervention schools. Overall, there was a positive association between a modified school food environment and student food behavior in and outside school. Policies related to the school food environment are an important strategy to address the obesity epidemic in our country.

During the past 20 years the rate of overweight among 12- to 19-year-olds has more than tripled ( 1 ), and nearly one in three children in the United States is now overweight or obese ( 2 ). Overweight in adolescence is a greater predictor of risk for hyperlipidemia, hypertension, diabetes, and osteoporosis than overweight in adulthood, making adolescence a crucial time to encourage healthy food and physical activity habits ( 3 ). Because of their continuous and intensive contact with children during the first 2 decades of their lives, schools provide an ideal setting for obesity-related interventions ( 2456789 ). Most schools offer US Department of Agriculture (USDA) School Lunch and Breakfast Programs ( 9 ) and some form of competitive à la carte food options (ie, food sold outside the purview of a USDA meal program). Competitive foods tend to be high in energy from fat and/or sugar and low in nutrients ( 9 ) and their availability has a negative influence on nutrient consumption (810 ), particularly among students from low-income families. Availability of these foods is associated with reduced participation in USDA meal programs ( 211 ).

The school food environment, which for this study included all foods available to students in school during the school day, was targeted as a place in which to reduce adolescent obesity. Several studies have reported that restricting less-healthy foods in cafeterias and vending machines reduced consumption of low nutrient, high-energy foods ( 2612 ). However the duration and effect of changes has been studied for a relatively short period of time, often <1 year ( 3 ).

The purpose of this research was to examine the relationships between changes in the school food environment and food choices made by early adolescents. This study extends beyond others in that the intervention reduced vending machine beverages to water only, limited à la carte offerings, extended changes in the school food environment to 3 years, and assessed adolescent food consumption both in school and outside of school.

Methods

Participants

The study population was 4,113 students (grades seven and eight) enrolled in six middle schools in a midsized western city. Two schools served as intervention schools (total enrollment 1,406); one had a large proportion of students receiving free and reduced-price meals (71.3%), whereas the other had a smaller proportion receiving free and reduced-priced meals (46.2%). Four schools served as control schools (total enrollment 2,707); two control schools had a large proportion of students receiving free and reduced-price meals (81.1%), and two had a smaller proportion receiving free and reduced-price meals (37.6%). High numbers of students eligible for free and reduced-price meal status determined the study variable for low-income status.

In the two intervention schools, modification of the school food environment was initiated during fall of the 2007-2008 school year and continued through the 2008-2009 and 2009-2010 school years. A food behavior survey was administered to middle-school students in seventh and eighth grades in intervention and control schools during the 2009-2010 school year during fitness and health classes.

More than 90% of students in this school district are white. To protect the identity of nonwhite students, race was not included in the analysis. Personal identifiers were removed and a unique study-specific identification number was assigned to each participant by the school district. Approval for the project was granted by the school district Assessment Review Committee and the Washington State University Institutional Review Board. Dichotomous classification of a student’s socioeconomic status was determined by qualification for free or reduced-price meals as a part of the USDA school meal program.

Modifications to School Food Environment

Three school years before this study, the school district implemented a wellness policy in all schools that eliminated sugared beverages and only allowed 100% juice products and flavored nonenergy-providing water to be sold during the school day. Competitive à la carte items were limited to 250 kcal and 9 g fat.

The intervention reported here further modified the school food environment in two middle schools by removing juice products and allowing only nonflavored bottled water in vending machines, restricting à la carte items to only milk and fruit and removing all other items, and making a seasonal fruit and vegetable bar available to all students. The research hypothesis was that when compared to middle school students in control schools, the middle school students in the intervention schools with altered school food environments would report healthier food choices.

Measures of Food Behaviors

A revised beverage and snack questionnaire developed by Neuhouser and colleagues ( 13 ) was used to assess the previous week’s food choices of students in school and outside of school. The food frequency questionnaire was originally developed to assess the food behavior of middle school students in Washington State and to evaluate the effectiveness of school district wellness policies. The previously established validity coefficients for the individual food items ranged from 0.56 to 0.87. The original 19 food items were reduced to a total of nine food categories that focused on items commonly found in the school environment. The revised survey instrument was selected and modified to ensure completion within 5 to 7 minutes and to identify food frequency differences between intervention and control schools. The nine food categories included on the revised instrument were juice, milk, sweet-drink, energy drinks, chips, candy, pastries, vegetables, and fruits. In the modified version of the survey used in this study, reliability was confirmed with Cronbach’s α, which ranged from .55 to .79. Food and beverage consumption during the previous week both in school and outside of school were assessed. Students chose among seven consumption frequency options from “zero servings per week” up to “four or more servings per day.” Responses were condensed in the analysis to three categories: high (at least two to three servings per day), medium (five or six servings per week or one serving per day), and low (at most four servings per week) consumption, to avoid low cell counts while preserving the monotonicity of the responses.

Statistical Analyses

Wilcoxon matched-pairs signed rank test was used to evaluate whether there were differences in frequency of consumption of various food and drink products in school and outside school. Kruskal-Wallis equality-of-populations rank test was used to evaluate whether there were sex differences and income differences in frequency of consumption of various food and drink products in school and outside of school. To determine whether consumption of the various food products and drinks, both in and outside of school, varied between intervention and control schools, ordered logistic regression analyses were conducted. Covariates in the regression models included sex and income status of the students. In addition, while conducting the analysis for the consumption patterns in school, the consumption behavior outside school was controlled to capture individuals’ overall preference for certain food items. The number of observations in the ordered logistic regression model was 1,975.

Results and Discussion

A total of 2,292 surveys (response rate 55.6%) were returned from seventh- and eighth-grade students in intervention and control schools. Intervention schools represented 26% of respondents, whereas the control schools (four of six middle schools) represented 74%. Response rates for control (87.4%) and intervention (82.4%) schools were similar. Boys (51%) and girls (49%) were equally represented among respondents.

Overall, students self-reported low consumption for all nine categories of food on the food frequency survey and reported higher frequency of food consumption outside school than inside school ( Table 1 ). This is consistent with reports that children in this age group under-report food consumption ( 14 ) and consume more food outside school than in school ( 1 ). The food most frequently consumed was milk; however, only one fourth reported at least two servings of milk per day outside of school; 14% reported consuming at least two servings of milk daily in school. Sweetened drink consumption was lower in this survey than reported in other studies ( 12): medium to high frequency of consumption of sweetened beverages was reported by 12% to 18% of students in school and 20% to 30% outside school. More than three fourths of students in this study reported low consumption (less than one serving per day) of chips, candy, pastries, and energy drinks; this may be a reflection of the school wellness policies that the school district implemented before our study.

Table 1

Seventh- and eighth-grade children’s differences in food choices in and outside school, by sex and meal status a

Self-reported intake frequency In School Outside School
Boys (n=1,176) Girls (n=1,116) Paid meals (n=997) Free/reduced-price meals (n=1,022) Boys (n=1,176) Girls (n=1,116) Paid meals (n=997) Free/reduced-price meals (n=1,022)
%
Milk
Low 42.77 55.00 60.83 39.13 47.59 52.48 45.27 52.58
Medium 40.12 33.66 28.90 44.44 27.11 26.51 27.87 26.19
High 17.11 11.34 10.27 16.43 25.30 21.01 26.86 21.23
Rank test 37.10 ⁎⁎ 87.46 ⁎⁎ 7.03 ⁎⁎ 12.55 ⁎⁎
Fruits
Low 59.59 57.72 59.44 58.04 45.67 38.94 40.60 43.18
Medium 27.20 30.43 30.62 27.94 33.05 35.25 35.18 34.49
High 13.21 11.85 9.94 14.02 21.29 25.81 24.44 22.33
Rank test 0.25 1.67 11.77 ⁎⁎ 1.63
Vegetables
Low 67.95 69.90 71.60 67.29 47.21 40.27 42.71 44.46
Medium 22.37 22.28 20.75 22.99 36.11 40.36 38.99 38.02
High 9.68 7.82 7.65 9.72 16.68 19.37 18.30 17.52
Rank test 1.44 4.81 ⁎ 10.33 ⁎⁎ 0.61
Juice
Low 71.20 76.98 80.30 68.73 61.60 64.90 62.47 63.24
Medium 19.15 18.08 15.38 21.63 21.65 21.15 23.04 20.85
High 9.65 4.94 4.32 9.64 16.75 13.95 14.49 15.91
Rank test 12.60 ⁎⁎ 38.14 ⁎⁎ 3.39 0.003
Sweet drinks
Low 81.21 86.43 84.72 83.20 70.54 73.78 76.48 68.78
Medium 12.30 8.89 11.86 9.63 18.09 16.94 16.78 18.53
High 6.49 4.68 3.42 7.17 11.37 9.28 6.74 12.69
Rank test 11.36 ⁎⁎ 1.55 3.35 18.11 ⁎⁎
Chips
Low 85.36 85.35 84.21 85.74 78.07 78.58 79.12 77.21
Medium 11.22 11.77 13.48 10.82 15.74 14.94 15.76 15.76
High 3.42 2.88 2.31 3.44 6.19 6.48 5.12 7.03
Rank test 0.003 0.69 0.06 1.42
Candy
Low 88.24 89.40 91.84 86.21 82.46 79.84 84.82 78.04
Medium 7.64 7.37 6.14 8.67 11.26 13.50 10.35 14.05
High 4.12 3.23 2.02 5.12 6.28 6.66 4.83 7.91
Rank test 0.84 17.04 ⁎⁎ 2.35 15.7 ⁎⁎
Pastries
Low 89.77 94.32 93.74 90.72 85.97 86.13 88.99 83.70
Medium 7.05 4.06 4.84 6.22 9.44 9.91 7.88 11.43
High 3.18 1.62 1.42 3.06 4.59 3.96 3.13 4.87
Rank test 16.03 ⁎⁎ 6.62 ⁎ 0.02 11.89 ⁎⁎
Energy drinks
Low 93.91 95.96 96.87 93.61 89.41 92.07 94.27 88.50
Medium 3.18 2.69 1.52 3.83 6.02 5.59 3.42 7.53
High 2.91 1.35 1.61 2.55 4.57 2.34 2.31 3.97
Rank test 5.17 ⁎ 11.49 ⁎⁎ 5.17 ⁎ 20.74 ⁎⁎

查看原图

a The numbers of observations reported in the second row are approximate because they might vary due to missing data across different food items. Results are from Kruskal-Wallis equality-of-proportions rank tests. Low=0-4 servings/wk (less than 1/d); Medium=5-6 servings/wk (1/d); High=2-3 servings/d.

P <0.05.

⁎⁎ P <0.01.

For the combined control and intervention group clear sex differences in the frequency of self-reported food choices were identified ( Table 1 ). Boys consistently reported more frequent milk consumption in and outside school compared with girls. In school 17.1% of boys consumed two or more daily servings of milk compared with 11.3% of girls, and outside school 25.3% of boys consumed two or more daily servings compared with 21.0% of girls. Girls reported more frequent consumption of fruits and vegetables than boys outside school. Nearly 26% of girls consumed at least two fruits per day outside school compared to 21.3% of boys, and 19.4% of girls consumed at least two vegetables per day outside school compared with 16.7% of boys. Boys consumed more juice, sweet drinks, and pastries at school than girls.

For the combined groups significant income differences were noted for student frequency of consumption of several food items in and outside of school ( Table 1 ). Milk consumption by students receiving free and reduced-price meals was higher than that by students receiving fully-paid meals in school; however, students with fully-paid meals consumed more milk outside of school. Students receiving free and reduced-price meals reported consuming more juice at school than students who paid for their meals; they also consumed more candy and energy drinks in school and more sweet drink, candy, pastries, and energy drinks outside of school. This may support the conclusion drawn by Drewenoski and Darmon ( 15 ) that lower-income families choose foods that provide high energy return for the cost.

Significant differences were identified between intervention and control schools ( Table 2 ). The ordered logistic regression that controlled for sex, meal status, and location of food item consumption showed that students in intervention schools were 56% less likely to consume pastries and 27% less likely to consume juice, which was the only energy-dense vended beverage in control schools. This demonstrates that modifying the school food environment likely has a positive influence on the foods that students consume. Students at intervention schools were 24% more likely to consume milk outside of school. It may be because the limited beverage options at intervention schools created a taste preference for milk at home. It was surprising that fruit and vegetable consumption reported by students at the intervention schools was not significantly better than those students in the control schools because seasonal fruit and vegetable bars were available to all students in intervention schools regardless of whether they purchased a school meal. Fresh fruits and vegetables were available to all students in control schools on the meal line. Van Cauwenberghe and colleagues ( 16 ) also reported that fruit and vegetable intake was not affected by changes in school food environment.

Table 2

Consumption differences by seventh- and eighth-grade children (n=2,000) between intervention and control schools a b

Dependent variable a In School Outside School
Odds ratio Standard error P value Odds ratio Standard error P value
Milk 0.97 0.10 0.77 1.24 0.13 0.04
Fruit 1.01 0.12 0.95 1.21 0.13 0.09
Vegetables 1.08 0.14 0.56 0.94 0.10 0.58
Juice 0.73 0.10 0.02 0.82 0.10 0.10
Sweet drinks 0.87 0.15 0.77 0.94 0.13 0.64
Chips 0.87 0.15 0.41 1.17 0.17 0.29
Candy 0.97 0.20 0.88 0.99 0.16 0.96
Pastries 0.44 0.12 0.00 1.40 0.25 0.06
Energy drinks 1.03 0.35 0.92 0.84 0.20 0.48

查看原图

a The numbers of observations reported in the first row are approximate because they might vary due to missing data across different food items. Results are from ordered logistic regressions. The ordered logistic regression analysis was conducted using STATA 10 (2007, Stata Corp, College Station, TX).

b Independent variables in each regression analysis are sex, school meal status, and consumption of the same food item in the complementary location.

The findings of this study present a conundrum for school administrators. Findings demonstrated that healthful modifications in the school food environment are associated with positive food behaviors in early adolescents, but there was a cost associated with those changes. Each intervention school spent 49% more on produce per student than control schools during the 2008-2009 and 2009-2010 school years (spending about $2,500 more per school per year), and annually both schools together lost approximately $24,000 in gross school meal sales due to lost à la carte sales and a $9,000 annual loss in vending sales. The pressures to provide more nutritious, often more costly foods to students in the midst of shrinking budgets and unfunded mandates makes it difficult to eliminate profitable competitive foods.

Conclusions

This study identified a positive association between reported student food choices and a modified food environment. School food polices and the food environment can be part of a long-term solution to the youth obesity problem. Practitioners in school nutrition need to work with key decision makers to offer a healthful school food environment. Especially school meal programs in lower income areas need to be encouraged and promoted because of the key nutrients provided by school meals.

Findings of this study are limited due to lack of ethnic/racial diversity among respondents, the fact that the study relied on self-reported frequency of food choices, and knowledge that it was administered in a health and fitness class. Future research should include more objective measures of food behavior. In addition, longitudinal research is needed to assess food behaviors before and after a school food environment intervention to determine the causal effect of changes in the school food environment on food behaviors among adolescents.

STATEMENT OF POTENTIAL CONFLICT OF INTEREST: No potential conflict of interest was reported by the authors.

FUNDING/SUPPORT: This project was supported by National Research Initiative grant no. 2006-04637 from the US Department of Agriculture’s National Institute for Food and Agriculture Teen Eating and Activity Mentoring in Schools program .

ACKNOWLEDGEMENTS: The authors thank Washington State University, especially the team at the College of Nursing, whose commitment to excellence in research and support of partnerships and scholarly work made this article possible.

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Second one will be attached