annotated outline 5

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The annotated outline is the framework of your final project and will include most, if not all of your reference sources. This annotated outline will give your professor a chance to see how far along you are in your project, and allow him or her to provide you feedback on ways to improve. The more you put into the annotated outline, the more feedback your professor can offer back to you. The idea here is to make sure you are on the right track so that there won’t be any surprises for you at the end.

In Doc Sharing you will find a PDF document titled Annotated Outline Format and an MS Word document titled Table of Contents for the CRJ-560 Project. These two documents provide the framework for the final project and will help you understand what is required.

On both the Annotated Outline Format and on the Table of Contents for the CRJ-560 Project documents, you will notice that some of the text appears to be a subdued gray color. Those are the things that you will not be responsible for. They appear only so you can see how your paper fits into the greater research project that you would need to do if you completed a full doctoral dissertation.

As you can see from the text in black font, in this course you will be responsible only for the title page, the abstract, the table of contents, portions of Chapter 1 and 2, and a small portion of the Chapter 5 Discussion.

Click on the Research Project Rubrics link in the Start Here menu to view the scoring rubric for all three parts of this assignment.

 

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self 2

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Stereotypes and Prejudices

1. Think about the stereotypes (both negative and positive) that you hold about various groups of people. Identity the specifically for various groups by writing them down and saying them out loud. Try to identify the origins of each stereotype. Where did it come from? Examples to consider:   a) Mexicans    b) African Americans        c) Japanese            d) Chinese e) Vietnamese  f) Native Americans    g) Central Americans    h) Middle Easterners   i) Jews      j) White Americans  k) Irish Catholic   l) Italian Americans   m) Southerners   n) men                  o) Women   p) Gay men   q) Lesbians    r) Poor people   s) wealthy people  t) The physically challenged Please feel free to include other groups. 2. For the ethnic categories, think about whether or not your stereotypes vary by gender or social class. identify those stereotypes. For the other categories, think about whether your stereotypes vary by race or ethnicity. Do you make other distinctions within groups and hold stereotypes based on those distinctions? Try to identify the origins of each stereotype that you identify. 3. Are you aware of the stereotypes that are held about the groups that you belong to? Identify them, Are they positive or negative? What impact have they had on you? 4. think about situations where your found yourself making generalizations about people. When do your stereotypes become activated. How do they impact your behavior and interactions with people. 5. Both personally and in interactions with others, are there some stereotypes that you challenge and some that you accept as “truth”?  Identify some of those that you tend to challenge and those that you tend to accept. Why do you think you challenge/accept those specific stereotypes? 6a. In what ways  do you think stereotypes and generalizations about groups of people can  impact the process of intercultural psychotherapy?   b. What are some potential implications of stereotypes for your work as a therapist?

Answer each quetion with about one paragraph. 

 

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Public Health (Large Area) Epidemiology / Bivariate Linear Regression Analysis (Correlation)

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Module Exercise 2: Public health (large area) epidemiology

 

 

 

 

The exercise:

The Australian government Department of Health (federal) produces reports each year containing data on notifiable diseases which are of great use to those studying changes in disease distributions with space or time with the aim of planning country-wide control initiatives. To facilitate similar regional operations, states and territories produce annual Public Health Bulletins, zooming-in on the data at a higher level of resolution.

Part 1:  Access a table for NSW showing disease incidence for the years 2003 to 2012, and produce labelled, computer-generated time trend graphs for giardiasis and HIV infections using an application such as Excel®.

Part 2: Briefly discuss two possible reasons why each of these diseases might have increased or decreased over this period. Reference this discussion.

 

Aims of the exercise:

i. To acquire skills in the extraction, presentation, analysis and use of quantitative information from a large-area epidemiological report.

ii. To develop early perspectives on risk factors for specific diseases, and insight as to how and why these might change with time.

 

Hints:

i. Public Health Bulletins usually include data up to the year before they were published (eg: a 2012 bulletin usually contains data up to 2011).

ii. Departments are sometimes a few years behind with their bulletins, so a bulletin for the year 2013 might not be available until 2015.

iii. For comparison of disease incidence by places or by year, rates (not absolute numbers) are always used in epidemiology. Disease notification rates are usually given per 100,000 population.

 

 

 

 

 

 

 

 

 

Module Exercise 3: Bivariate linear regression analysis (correlation)

 

 

 

 

Background to the exercise:

As a preliminary step in a large-scale study of asthma in Armidale, New South Wales, you are asked to carry out a study to identify the impact of ambient atmospheric general particulate pollution (PM10) on the incidence of asthmatic wheeze in primary school children. Thermal inversions can occur periodically in the Armidale basin, trapping pollutants from point and diffuse sources in the lower atmosphere.

 

To ensure an accurate medical diagnosis you select all primary school children attending a day clinic over a 30-day period in April.  In this month, other “confounding” risk factors (such as rainfall) are at relatively low levels, and therefore to some extent controlled.

 

From trained clinical staff you obtain a daily record of asthmatic wheeze incidence in children presenting for all medical conditions at the clinic during the study period. The daily air quality record is obtained from the Department of the Environment and a short latency period (minutes to hours) between exposure to ambient air particulates and production of symptoms is assumed. You produce the tabulated data shown on the next page.

 

The exercise:

Part 1: Plot a graph showing the relationship between asthma wheeze and ambient atmospheric particulate matter (PM10) using a recognised computer application such as Excel®. Add a computer-generated line of best fit, assuming a linear relationship. Present the graph for assessment with a comment on the type of correlation (direct or inverse), its electronically-computed strength in terms of Pearson’s Product Moment Correlation Coefficient r  (some versions of the graph on Excel also give this), and a qualitative interpretation of this result (eg: “low correlation”, “moderate correlation”, etc.)

Part 2: Using the formula and table given in the module notes, hand-calculate Pearson’s Product Moment Correlation Coefficient, r. Submit the tabulation used to generate values for the algebraic formula, along with your calculated value for r. Comment on the possible reason for any differences noted between the result obtained in parts 1 and 2.

 

 

 

Aim of the Exercise:

i. To gain an understanding of the use of bivariate linear regression analysis as a fundamental but powerful epidemiological analytical tool.

ii. To gain a conceptual idea of an industrially generated, environmental risk factor for an important health condition.

 

Day Total number of children with asthmatic wheeze Total number of children attending the clinic that day Ambient atmospheric particulates (PM10 in µg/m3) Blank column for calculated values
1 11 420 40  
2 8 230 45  
3 11 190 90  
4 24 550 60  
5 31 643 50  
6 39 710 60  
7 39 560 360  
8 26 302 320  
9 19 200 110  
10 31 587 70  
11 22 589 80  
12 21 632 64  
13 14 585 50  
14 27 602 50  
15 22 320 130  
16 16 245 220  
17 24 558 100  
18 26 570 60  
19 42 603 40  
20 36 555 40  
21 46 599 100  
22 17 197 160  
23 16 197 190  
24 26 520 80  
25 22 476 50  
26 19 600 40  
27 14 557 30  
28 17 481 40  
29 10 225 50  
30 10 190 40  

 

Hints:

i. If the question looks confusing and perplexing you probably need to go back to the module notes where the approach is clearly explained, and work through an example.

ii. When finished check your calculations thoroughly as marks are awarded for both method and the correct answer. With care it is relatively easy to score 100%.

iii. The first step when working with raw data is always to classify (ie: to construct a table). When in doubt, tabulate, when masses of numbers will always become clearer.

iv. Ensure accuracy by using one more decimal place in your calculations than you intend to give in your answer.

v. Use the formula in the module notes rather than the one given in text books, which is primarily for statisticians.

vi. When comparing health states (diseases and fitness) always use rates.

vii. Excel® does not do as much as SPSS and Minitab, but is probably the most user-friendly program to use, and links well with Word®. For example, values in the Word table can be cut and pasted into Excel®. Adding the line of best fit in Excel® involves highlighting the graph first by clicking on it, when the menu tab for this function will appear.

 

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Case 5 And 6(Knee Injury And Testicular Cancer )

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Knee Injury Case Studies A 15-year-old gymnast has noted knee pain that has become progressively worse during the past several months of intensive training for a statewide meet. Her physical examination indicated swelling in and around the left knee. She had some decreased range of motion and a clicking sound on flexion of the knee. The knee was otherwise stable. Studies Results Routine laboratory values Within normal limits (WNL) Long bone (femur, fibula, and tibia) X-ray No fracture Arthrocentesis with synovial fluid analysis Appearance Bloody (normal: clear and straw-colored) Mucin clot Good (normal: good) Fibrin clot Small (normal: none) White blood cells (WBCs) <200 WBC/mm3 (normal: <200 WBC/mm3 ) Neutrophils <25% (WNL) Glucose 100 mg/dL (normal: within 10 mg/dL of serum glucose level) Magnetic resonance imaging (MRI) of the knee Blood in the joint space. Tear in the posterior aspect of the medial meniscus. No cruciate or other ligament tears Arthroscopy Tear in posterior aspect of medial meniscus Diagnostic Analysis The radiographic studies of the long bones eliminated any possibility of fracture. Arthrocentesis indicated a bloody effusion, which was probably a result of trauma. The fibrin clot was further evidence of bleeding within the joint. Arthrography indicated a tear of the medial meniscus of the knee, a common injury for gymnasts. Arthroscopy corroborated that finding. Transarthroscopic medial meniscectomy was performed. Her postoperative course was uneventful. Critical Thinking Questions 1. One of the potential complications of arthroscopy is infection. What signs and symptoms of joint infection would you emphasize in your patient teaching? 2. Why is glucose evaluated in the synovial fluid analysis? 3. What are special tests used to differentiate type of Tendon tears in the knee ? Explain how they are performed (Always on boards)
Testicular Cancer Case Studies A 21-year-old male noted pain in his right testicle while studying hard for his midterm college examinations. On self-examination, he noted a “grape sized” mass in the right testicle. This finding was corroborated by his healthcare provider. This young man had a history of delayed descent of his right testicle until the age of 1 year old. Studies Results Routine laboratory studies Within normal limits (WNL) Ultrasound the testicle Solid mass, right testicle associated with calcifications HCG (human chorionic gonadotropin) 550mIU/mL (normal: <5) CT scan of the abdomen Enlarged retroperitoneal lymph nodes CT scan of the chest Multiple pulmonary nodules Diagnostic Analysis At semester break, this young man underwent right orchiectomy. Pathology was compatible with embryonal cell carcinoma. CT directed biopsy of the most prominent pulmonary nodule indicated embryonal cell carcinoma, compatible with metastatic testicular carcinoma. During a leave of absence from college, and after banking his sperm, this young man underwent aggressive chemotherapy. Repeat testing 12 weeks after chemotherapy showed complete resolution of the pulmonary nodules and enlarged retroperitoneal lymph nodes. Critical Thinking Questions 1. What impact did an undescended testicle have on this young man’s risk for developing testicular cancer? 2. What might be the side effects of cytotoxic chemotherapy? 3. What was the purpose of preserving his sperm before chemotherapy? 4. Is this young man’s age typical for the development of testicular carcinoma?
 
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