DQ

DQ

Stakeholder support is necessary for a successful change proposal project implementation. Consider your internal stakeholders, such as the facility, unit or health care setting where the change process is situated, and your external stakeholders, like an individual or group outside the health care setting. Why is their support necessary to the success of your project, and how you will go about securing that support?

Nutrition Assignment

Nutrition Assignment

 ((ONE-PAGE BRIEFING PAPER AND QUESTIONS:  you will write a one-page briefing paper based on Dr. Ben Embarek’s presentation (posted in the attachment) and also compose 1 to 3 questions you may have asked about the presentation. The PDF of his slides were also posted together with a video he kindly recorded after we had some technical difficulties (see a summary of some draft emails I was unable to send below as the technical difficulties were ever changing). In addition, I have posted under the same folder Dr. Ben Embarek’s bio))

Morshid 4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

AAP Recommendations on Timing of Introduction of Complementary Foods and Risk of Childhood Obesity

 

Hani Morshid

NUTR522: Nutrition across the Lifespan

30 November 2018

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

To the Senator…

 

Re: AAP Recommendations on Timing of Introduction of Complementary Foods and Risk of Childhood Obesity

I hope this letter finds you well. My name is Hani Morshisd, and I am excited to write to you about an issue that is wrecking public health. The country is grappling with poor nutritional habits that result in excessive weight gain. My interest is childhood obesity that has adverse health effects that can persist into adulthood. According to the Center for Disease Control and Prevention (CDC), the burden of childhood obesity is 18.5%, and the most hit ethnic groups are Hispanics and non-Hispanics at 25.8% and 22.0% respectively. 1 An increased intake of high-calorie foods is responsible for energy imbalances that lead to weight gain. The American Academy of Pediatrics (AAP) blames poor infant nutritional habits that begin in the first year after birth. This professional association has come up with recommendations on the appropriate time to introduce complementary foods in a child’s diet.

The target population of this policy is the infants who are under the care of their mothers. Infancy is a period characterized by rapid growth both physically and cognitively. Breast milk is rich in all nutrients that are necessary for child development. An advantage of breastfeeding is that infants have a regulated energy intake that is difficult to achieve in complementary feeding. Levels of micronutrients such as iron in breast milk reduce at six months and hence, solid foods are meant to achieve a balanced diet. 2 Notably, a mother should notice the signs that a child is ready to take additional foods. They include attempts to grab food from an adult, cessation of tongue thrusting behavior, and proper head control. Most children experience these signs at around five-six months. A gradual introduction of complementary feeding is required to achieve breast comfort. Once a child starts to take solid foods, a mother should not stop breastfeeding but should reduce the weaning frequency in response to changes in an infant’s desire.

There are claims that complementary feeding at an early age enhances the growth of a child. Some mothers have relied on unconfirmed reports that introducing solid foods at four months is necessary for healthier weight gain in addition to height and head circumference. However, a randomized controlled trial by Jonsdottir et al. did not find any growth difference between exclusive feeding up to six months and the initiation of complementary feeding at an earlier age. 3 Delaying introduction of solid foods until a child is six months old does not rob him/her any health benefits, but interrupted breastfeeding at four months can lead to nutritional deficiency. While the anthropometric measurements are similar, the impact of increased energy intake is realized in later years in form of obesity.

AAP requires nursing mothers to provide exclusive breastfeeding for the first six months after birth. At this age, a child should not be given solid foods, as the body is not mature enough to achieve proper energy balance. Unfortunately, only 14% of mothers adhere to the guidelines. Hence putting their children at risk of excessive weight gain. 4 Scientific findings show feeding children on solid foods before they reach four months raises the risk of obesity by six-fold.5 The formula-fed infants are likely to be introduced to solid foods before six months and hence have a high probability of gaining unwanted weight. While mothers are willing to offer exclusive breastfeeding, the work demands make it impractical and they instead supplement milk with solid foods. Paid maternity leave is not guaranteed in the US meaning that nursing women have to continue working. 6 The implication is the adoption of improper nutritional behavior for an infant. There is a need to formulate enabling policies on maternity leave that will enhance the viability of AAP recommendations.

Further research supports AAP recommendations on regulated timing of introducing solid foods. A study conducted in Netherlands by Pluymen et al. emphasized the need to take care of the breastfeeding duration. 7 Feeding a child on solid foods before reaching four months increased the odds of excessive weight gain in their later childhood and adolescent life. Infants who depend on formulas are unable to control energy intake as mothers often include solid foods in their diet. Some people consider complementary feeding an alternative to breastfeeding and are reluctant to proceed with weaning. Similarly, Pearce et al. indicate that part of the burden of childhood obesity can be attributed to the transition period between exclusive breast milk and solid foods. 8 While developing countries emphasize breastfeeding to avoid malnutrition, the US is worried about the ever-rising burden of childhood obesity.

The government has been successful in reducing infant and maternal mortality, but there is a low emphasis on child nutritional behavior. National and international bodies such as AAP and the World Health Organization have identified the gap and have proposed measures to be taken to enhance the well-being of children. Mothers are insufficiently educated on the value of exclusive breastfeeding and the consequences of complementary feeding at an early age. They are not ready to break the tradition of introducing solid foods to infants. In most cases, the society faults fast food outlets and the government for failing to control the availability of low-nutrient foodstuff. Research has shown that mothers should take part of the blame for embracing poor nutritional behavior that puts children at the risk of excessive weight gain. AAP has stepped in to reverse the worrying trends of child obesity. It seeks to create an enabling environment that will allow healthier dietary intake.

Your influence in the Congress is instrumental in ensuring that AAP recommendations are prioritized in the government agenda. We cannot remain silent and assume that the society is progressing well. The House is responsible for protecting the future generation from obesity that has significant health and economic costs. Adequate funding of breastfeeding programs is required to reach every pregnant and nursing mother. The government should also invest in human resource to ensure that there are adequate nutritional experts to drive proper dietary behavior. However, the effectiveness of the policy can be limited by the absence of a favorable environment to facilitate uninterrupted breastfeeding. Mothers have no guarantee that they will receive salaries during the maternity leave. They are ready to introduce complementary feeding to avoid losing their jobs. Therefore, the House should work on additional policies to extend the maternity leave and ensure that nursing mothers are properly remunerated.

I hope that you have found AAP recommendations important to deserve the attention of the government. In case of any query, I will be glad to have a face-to-face conversation with you.

 

Sincerely,

 

 

 

 

 

 

 

 

 

Reference List

1. Childhood Obesity Facts | Overweight & Obesity | CDC. Cdc.gov. https://www.cdc.gov/obesity/data/childhood.html. Published 2018. Accessed November 9, 2018.

2. Working Together: Breastfeeding and Solid Foods. HealthyChildren.org. https://www.healthychildren.org/English/ages-stages/baby/breastfeeding/Pages/Working-Together-Breastfeeding-and-Solid-Foods.aspx. Published 2018. Accessed November 9, 2018.

3. Jonsdottir O, Thorsdottir I, Hibberd P, et al. Timing of the introduction of complementary foods in infancy: A randomized controlled trial.  Pediatrics. 2012; 130(6):1038-1045. doi:10.1542/peds.2011-3838

4. Infant Food and Feeding. Aap.org. https://www.aap.org/en-us/advocacy-and-policy/aap-health-initiatives/HALF-Implementation-Guide/Age-Specific-Content/Pages/Infant-Food-and-Feeding.aspx. Published 2018. Accessed November 9, 2018.

5. Huh S, Rifas-Shiman S, Taveras E, Oken E, Gillman M. Timing of solid food introduction and risk of obesity in preschool-aged children. Pediatrics. 2011; 127(3):e544-e551. doi:10.1542/peds.2010-0740

6. Beckerman J, Alike Q, Lovin E, Tamez M, Mattei J. The development and public health implications of food preferences in children. Front Nutr. 2017; 4. doi:10.3389/fnut.2017.00066

7. Pluymen L, Wijga A, Gehring U, Koppelman G, Smit H, van Rossem L. Early introduction of complementary foods and childhood overweight in breastfed and formula-fed infants in the Netherlands: The PIAMA birth cohort study. Eur J Nutr. 2018; 57(5):1985-1993. doi:10.1007/s00394-018-1639-8

8. Pearce J, Taylor M, Langley-Evans S. Timing of the introduction of complementary feeding and risk of childhood obesity: A systematic review. Int J Obes. 2013; 37(10):1295-1306. doi:10.1038/ijo.2013.99

 

 

 

 

Morshid

 

1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

AAP Recommendations on Timing

 

of Introduct

ion of Complementary Foods and Risk of

Childhood Obesity

 

 

Hani Morshid

 

NUTR522

:

Nutrition across

 

the Lifespan

 

30

 

November 2018

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Morshid 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

AAP Recommendations on Timing of Introduction of Complementary Foods and Risk of

Childhood Obesity

 

Hani Morshid

NUTR522: Nutrition across the Lifespan

30 November 2018

Research Proposal And Combination Of 2 Previous Papers

Research Proposal And Combination Of 2 Previous Papers
You are not conducting original research; you will only be developing a proposal for future research. You identified a model to promote EBP clinical research on Narcolepsy & Cataplexy. Please use model to organize your final proposal. In addition, integrate the Part 1 PICO(T) paper, Part 2 Literature review and this Part 3 to synthesize your findings and draw conclusions. Include in Part 3 how you might apply for funding for this project. Please use the Proposal paper outline provided for you during the first week as a guide for your paper.

This assignment requires proper APA format. This includes a title page, reference page, and proper headings. An abstract is required for this final proposal. The Final EBPG proposal requires 7 pages in addition to the title page, abstract page, and reference page.

Chapter 6 Understanding Frequencies And Percentages

Chapter 6 Understanding Frequencies And Percentages

Topic :  Subject Area :  Number of Pages :  Type of Document :  Spacing :  Style :  Academic Level :  Preferred Language : Assignment Description:

Details:

Complete Exercises 6, 8, and 9 in Statistics for Nursing Research: A Workbook for Evidence-Based Practice, and submit as directed by the instructor.]

please see email to follow

 

chapter 6

Understanding Frequencies

and Percentages

STATISTICAL TECHNIQUE IN REVIEW

Frequency is the number of times a score or value for a variable occurs in a set of data.

Frequency distribution is a statistical procedure that involves listing all the possible

values or scores for a variable in a study. Frequency distributions are used to organize

study data for a detailed examination to help determine the presence of errors in coding

or computer programming ( Grove, Burns, & Gray, 2013 ). In addition, frequencies and

percentages are used to describe demographic and study variables measured at the nominal

or ordinal levels.

Percentage can be defi ned as a portion or part of the whole or a named amount in

every hundred measures. For example, a sample of 100 subjects might include 40 females

and 60 males. In this example, the whole is the sample of 100 subjects, and gender is

described as including two parts, 40 females and 60 males. A percentage is calculated

by dividing the smaller number, which would be a part of the whole, by the larger

number, which represents the whole. The result of this calculation is then multiplied

by 100%. For example, if 14 nurses out of a total of 62 are working on a given day, you

can divide 14 by 62 and multiply by 100% to calculate the percentage of nurses working

that day. Calculations: (14 ÷ 62) × 100% = 0.2258 × 100% = 22.58% = 22.6%. The answer

also might be expressed as a whole percentage, which would be 23% in this example.

cumulative percentage distribution involves the summing of percentages from the

top of a table to the bottom. Therefore the bottom category has a cumulative percentage

of 100% (Grove, Gray, & Burns, 2015). Cumulative percentages can also be used to determine

percentile ranks, especially when discussing standardized scores. For example, if 75%

of a group scored equal to or lower than a particular examinee ’ s score, then that examinee ’ s

rank is at the 75 th percentile. When reported as a percentile rank, the percentage is often

rounded to the nearest whole number. Percentile ranks can be used to analyze ordinal

data that can be assigned to categories that can be ranked. Percentile ranks and cumulative

percentages might also be used in any frequency distribution where subjects have only one

value for a variable. For example, demographic characteristics are usually reported with the

frequency ( ) or number ( ) of subjects and percentage (%) of subjects for each level of a

demographic variable. Income level is presented as an example for 200 subjects:

Income Level Frequency ( ) Percentage (%) Cumulative %

1. < $40,000 20 10% 10%

2. $40,000–$59,999 50 25% 35%

3. $60,000–$79,999 80 40% 75%

4. $80,000–$100,000 40 20% 95%

5. > $100,000 10 5% 100%

EXERCISE

6

60 EXERCISE 6 • Understanding Frequencies and Percentages

Copyright © 2017, Elsevier Inc. All rights reserved.

In data analysis, percentage distributions can be used to compare fi ndings from different

studies that have different sample sizes, and these distributions are usually arranged in

tables in order either from greatest to least or least to greatest percentages ( Plichta &

Kelvin, 2013 ).

RESEARCH ARTICLE

Source

Eckerblad, J., Tödt, K., Jakobsson, P., Unosson, M., Skargren, E., Kentsson, M., & Theander,

K. (2014). Symptom burden in stable COPD patients with moderate to severe airfl ow

limitation. Heart & Lung, 43 (4), 351–357.

Introduction

Eckerblad and colleagues (2014 , p. 351) conducted a comparative descriptive study to

examine the symptoms of “patients with stable chronic obstructive pulmonary disease

(COPD) and determine whether symptom experience differed between patients with moderate

or severe airfl ow limitations.” The Memorial Symptom Assessment Scale (MSAS)

was used to measure the symptoms of 42 outpatients with moderate airfl ow limitations

and 49 patients with severe airfl ow limitations. The results indicated that the mean

number of symptoms was 7.9 ( } 4.3) for both groups combined, with no signifi cant differences

found in symptoms between the patients with moderate and severe airfl ow limitations.

For patients with the highest MSAS symptom burden scores in both the moderate

and the severe limitations groups, the symptoms most frequently experienced included

shortness of breath, dry mouth, cough, sleep problems, and lack of energy. The researchers

concluded that patients with moderate or severe airfl ow limitations experienced multiple

severe symptoms that caused high levels of distress. Quality assessment of COPD

patients ’ physical and psychological symptoms is needed to improve the management of

their symptoms.

Relevant Study Results

Eckerblad et al. (2014 , p. 353) noted in their research report that “In total, 91 patients

assessed with MSAS met the criteria for moderate ( = 42) or severe airfl ow limitations

= 49). Of those 91 patients, 47% were men, and 53% were women, with a mean age of

68 ( } 7) years for men and 67 ( } 8) years for women. The majority (70%) of patients were

married or cohabitating. In addition, 61% were retired, and 15% were on sick leave.

Twenty-eight percent of the patients still smoked, and 69% had stopped smoking. The

mean BMI (kg/m 2 ) was 26.8 ( } 5.7).

There were no signifi cant differences in demographic characteristics, smoking history,

or BMI between patients with moderate and severe airfl ow limitations ( Table 1 ). A lower

proportion of patients with moderate airfl ow limitation used inhalation treatment with

glucocorticosteroids, long-acting β 2 -agonists and short-acting β 2 -agonists, but a higher

proportion used analgesics compared with patients with severe airfl ow limitation.

Symptom prevalence and symptom experience

The patients reported multiple symptoms with a mean number of 7.9 ( } 4.3) symptoms

(median = 7, range 0–32) for the total sample, 8.1 ( } 4.4) for moderate airfl ow limitation

and 7.7 ( } 4.3) for severe airfl ow limitation ( = 0.36) . . . . Highly prevalent physical symptoms

( ≥ 50% of the total sample) were shortness of breath (90%), cough (65%), dry mouth

(65%), and lack of energy (55%). Five additional physical symptoms, feeling drowsy, pain,

Understanding Frequencies and Percentages • EXERCISE 6 61

Copyright © 2017, Elsevier Inc. All rights reserved.

TABLE 1 BACKGROUND CHARACTERISTICS AND USE OF MEDICATION FOR PATIENTS WITH

STABLE CHRONIC OBSTRUCTIVE LUNG DISEASE CLASSIFIED IN PATIENTS WITH

MODERATE AND SEVERE AIRFLOW LIMITATION

Moderate

= 42

Severe

= 49 Value

Sex, (%) 0.607

Women 19 (45) 29 (59)

Men 23 (55) 20 (41)

Age (yrs), mean ( SD 66.5 (8.6) 67.9 (6.8) 0.396

Married/cohabitant (%) 29 (69) 34 (71) 0.854

Employed, (%) 7 (17) 7 (14) 0.754

Smoking, 0.789

Smoking 13 (31) 12 (24)

Former smokers 28 (67) 35 (71)

Never smokers 1 (2) 2 (4)

Pack years smoking, mean ( SD 29.1 (13.5) 34.0 (19.5) 0.177

BMI (kg/m 2 ), mean ( SD 27.2 (5.2) 26.5 (6.1) 0.555

FEV 1 % of predicted, mean ( SD 61.6 (8.4) 42.2 (5.8) < 0.001

SpO 2 % mean ( SD 95.8 (2.4) 94.5 (3.0) 0.009

Physical health, mean ( SD 3.2 (0.8) 3.0 (0.8) 0.120

Mental health, mean ( SD 3.7 (0.9) 3.6 (1.0) 0.628

Exacerbation previous 6 months, (%) 14 (33) 15 (31) 0.781

Admitted to hospital previous year, (%) 10 (24) 14 (29) 0.607

Medication use, (%)

Inhaled glucocorticosteroids 30 (71) 44 (90) 0.025

Systemic glucocorticosteroids 3 (6.3) 0 (0) 0.094

Anticholinergic 32 (76) 42 (86) 0.245

Long-acting β 2 -agonists 30 (71) 45 (92) 0.011

Short-acting β 2 -agonists 13 (31) 32 (65) 0.001

Analgesics 11 (26) 5 (10) 0.046

Statins 8 (19) 11 (23) 0.691

Eckerblad, J., Tödt, K., Jakobsson, P., Unosson, M., Skargren, E., Kentsson, M., & Theander, K. (2014). Symptom burden in stable

COPD patients with moderate to severe airfl ow limitation. Heart & Lung, 43 (4), p. 353.

numbness/tingling in hands/feet, feeling irritable, and dizziness, were reported by between

25% and 50% of the patients. The most commonly reported psychological symptom was

diffi culty sleeping (52%), followed by worrying (33%), feeling irritable (28%) and feeling

sad (22%). There were no signifi cant differences in the occurrence of physical and psychological

symptoms between patients with moderate and severe airfl ow limitations”

( Eckerblad et al., 2014 , p. 353).

62 EXERCISE 6 • Understanding Frequencies and Percentages

Copyright © 2017, Elsevier Inc. All rights reserved.

STUDY QUESTIONS

1. What are the frequency and percentage of women in the moderate airfl ow limitation group?

2. What were the frequencies and percentages of the moderate and the severe airfl ow limitation

groups who experienced an exacerbation in the previous 6 months?

3. What is the total sample size of COPD patients included in this study? What number or frequency

of the subjects is married/cohabitating? What percentage of the total sample is married

or cohabitating?

4. Were the moderate and severe airfl ow limitation groups signifi cantly different regarding married/

cohabitating status? Provide a rationale for your answer.

5. List at least three other relevant demographic variables the researchers might have gathered data

on to describe this study sample.

6. For the total sample, what physical symptoms were experienced by ≥ 50% of the subjects? Identify

the physical symptoms and the percentages of the total sample experiencing each symptom.

Understanding Frequencies and Percentages • EXERCISE 6 63

Copyright © 2017, Elsevier Inc. All rights reserved.

7. Were the physical symptoms identifi ed in the study what you might expect for patients with

moderate to severe COPD? Provide a rationale for your answer with documentation.

8. What frequency and percentage of the total sample used inhaled glucocorticosteroids? Show

your calculations and round to the nearest tenth of a percent.

9. Is there a signifi cant difference between the moderate and severe airfl ow limitation groups

regarding the use of inhaled glucocorticosteriods? Provide a rationale for your answer.

10. Was the percentage of COPD patients with moderate and severe airfl ow limitations using

inhaled glucocorticosteriods what you expected? Provide a rationale for your answer with

documentation.

64 Copyright © 2017, Elsevier Inc. All rights reserved.

Answers to Study Questions

1. The moderate airfl ow limitation group included 19 women, which means 45% of this group

was female (see Table 1 ).

2. A frequency of 14 (33%) of the moderate airfl ow limitation group and a frequency of 15 (31%)

of the severe airfl ow limitation group experienced an exacerbation in the previous 6 months

(see Table 1 ).

3. The total sample was = 91 patients with COPD in the Eckerblad et al. (2014) study (see the

narrative of study results). The number or frequency of subjects ’ who were married/cohabitating

is calculated by adding the frequencies from the two groups in Table 1 .

Calculation: Frequency married/cohabitating = 29 moderate group + 34 severe group = 63.

The percentage of the sample married/cohabitating is 70% (see narrative of study results) or

can be calculated by (frequency married/cohabitating ÷ sample size) × 100% = (63 ÷ 91) ×

100% = 69.23% = 69%. The researchers might have rounded to next higher whole percent of

70%, but 69% is a more accurate percentage of the married/cohabitating for the sample.

4. No, the moderate and severe airfl ow limitation groups were not signifi cantly different regarding

married/cohabitating status as indicated by = 0.854 (see Table 1 ). The level of signifi –

cance or alpha ( α ) in most nursing studies is set at α = 0.05 ( Grove et al., 2015 ). Since the

value is > 0.05, the two groups were not signifi cantly different in this study.

5. Additional demographic variables that might have been described in this study include race/

ethnicity, socioeconomic status or income level, years diagnosed with COPD, and other comorbid

medical diagnoses of these study participants. You might have identifi ed other relevant

demographic variables to be included in this study.

6. “Highly prevalent physical symptoms ( ≥ 50% of the total sample) were shortness of breath

(90%), cough (65%), dry mouth (65%), and lack of energy (55%)” ( Eckerblad et al., 2014 ,

p. 353; see study narrative of results).

7. Yes, the physical symptoms of shortness of breath, cough, dry mouth, and lack of energy or

fatigue are extremely common in patients with COPD who have moderate to severe airfl ow

limitations. Evidence-based guidelines for many chronic diseases can be found on the Agency

for Healthcare Research and Quality (AHRQ) website at www.guidelines.gov . Specifi c evidence-

based guidelines for the assessment, diagnosis, and management of COPD can be

found at the following AHRQ website: http://www.guideline.gov/content.aspx?id = 23801

&search = copd . The Global Initiative for Chronic Obstructive Lung Disease website is also an

excellent resource at http://www.goldcopd.org/Guidelines/guidelines-resources.html . You

might document with other websites, research articles, or textbooks.

Understanding Frequencies and Percentages • EXERCISE 6 65

Copyright © 2017, Elsevier Inc. All rights reserved.

8. Frequency = 74 and percent = 81.3%. In this study, 30 of the moderate airfl ow limitation group

and 44 of the severe group used inhaled glucocorticosteroids. Calculations: Frequency = 30

+ 44 = 74. Percentage total sample = (74 ÷ 91) × 100% = 0.8132 × 100% = 81.32% = 81.3%,

rounded to the nearest tenth of a percent.

9. Yes, the moderate and severe airfl ow limitation groups were signifi cantly different regarding

the use of inhaled glucocorticosteroids as indicated by = 0.025 (see Table 1 ). The level of

signifi cance or alpha ( α ) in most nursing studies is set at 0.05. Since the value is < 0.05, the

two groups were signifi cantly different for the use of inhaled glucocorticosteroids in this

study ( Grove et al., 2013 ; Shadish, Cook, & Campbell, 2002 ).

10. In this study, 30 (71%) of the patients with moderate airfl ow limitation and 44 (90%) of the

patients with severe airfl ow limitation were treated with glucocorticosteroids. The mean percentage

for the total sample who used glucocorticosteroids is (71% + 90%) ÷ 2 = 161 ÷ 2 =

80.5%, or 81%. The use of inhaled glucocorticosteroids is very common for patients with

moderate to severe COPD, in fact, recommended by national evidence-based guidelines, particularly

for those with severe airfl ow limitation. Thus, you might expect that a large number

of COPD patients in this study were using inhaled glucocorticosteroids. The Gold Standard

for the management of COPD can be found at the AHRQ (2015) website at: http://www

.guideline.gov/content.aspx?id = 23801&search = copd or at the Global Initiative for Chronic

Obstructive Lung Disease website at: http://www.goldcopd.org/Guidelines/guidelinesresources.

html .

 

Copyright © 2017, Elsevier Inc. All rights reserved. 67

EXERCISE

6

Questions to Be Graded

Follow your instructor ’ s directions to submit your answers to the following questions for grading.

Your instructor may ask you to write your answers below and submit them as a hard copy for

grading. Alternatively, your instructor may ask you to use the space below for notes and submit your

answers online at http://evolve.elsevier.com/Grove/statistics/ under “Questions to Be Graded.”

1. What are the frequency and percentage of the COPD patients in the severe airfl ow limitation

group who are employed in the Eckerblad et al. (2014) study?

2. What percentage of the total sample is retired? What percentage of the total sample is on sick

leave?

3. What is the total sample size of this study? What frequency and percentage of the total sample

were still employed? Show your calculations and round your answer to the nearest whole percent.

4. What is the total percentage of the sample with a smoking history—either still smoking or former

smokers? Is the smoking history for study participants clinically important? Provide a rationale

for your answer.

Name: _______________________________________________________ Class: _____________________

Date: ___________________________________________________________________________________

68 EXERCISE 6 • Understanding Frequencies and Percentages

Copyright © 2017, Elsevier Inc. All rights reserved.

5. What are pack years of smoking? Is there a signifi cant difference between the moderate and severe

airfl ow limitation groups regarding pack years of smoking? Provide a rationale for your answer.

6. What were the four most common psychological symptoms reported by this sample of patients

with COPD? What percentage of these subjects experienced these symptoms? Was there a signifi

cant difference between the moderate and severe airfl ow limitation groups for psychological

symptoms?

7. What frequency and percentage of the total sample used short-acting β2 -agonists? Show your

calculations and round to the nearest whole percent.

8. Is there a signifi cant difference between the moderate and severe airfl ow limitation groups

regarding the use of short-acting β 2 -agonists? Provide a rationale for your answer.

9. Was the percentage of COPD patients with moderate and severe airfl ow limitation using shortacting

β 2 -agonists what you expected? Provide a rationale with documentation for your answer.

10. Are these fi ndings ready for use in practice? Provide a rationale for your answer

 

chapter 8

Measures of Central Tendency :

Mean, Median, and Mode

EXERCISE

8

STATISTICAL TECHNIQUE IN REVIEW

Mean, median, and mode are the three measures of central tendency used to describe

study variables. These statistical techniques are calculated to determine the center of a

distribution of data, and the central tendency that is calculated is determined by the level

of measurement of the data (nominal, ordinal, interval, or ratio; see Exercise 1 ). The mode

is a category or score that occurs with the greatest frequency in a distribution of scores

in a data set. The mode is the only acceptable measure of central tendency for analyzing

nominal-level data, which are not continuous and cannot be ranked, compared, or subjected

to mathematical operations. If a distribution has two scores that occur more frequently

than others (two modes), the distribution is called bimodal . A distribution with

more than two modes is multimodal ( Grove, Burns, & Gray, 2013 ).

The median MD ) is a score that lies in the middle of a rank-ordered list of values of

a distribution. If a distribution consists of an odd number of scores, the MD is the middle

score that divides the rest of the distribution into two equal parts, with half of the values

falling above the middle score and half of the values falling below this score. In a distribution

with an even number of scores, the MD is half of the sum of the two middle numbers

of that distribution. If several scores in a distribution are of the same value, then the MD

will be the value of the middle score. The MD is the most precise measure of central tendency

for ordinal-level data and for nonnormally distributed or skewed interval- or ratiolevel

data. The following formula can be used to calculate a median in a distribution of

scores.

Median(MD) (1) 2

is the number of scores

Example: Median th score 31

31 1

2

32 2 16

Example: Median . th score 40

40 1

2

41 2 20 5

Thus in the second example, the median is halfway between the 20 th and the 21 st scores.

The mean ) is the arithmetic average of all scores of a sample, that is, the sum of its

individual scores divided by the total number of scores. The mean is the most accurate

measure of central tendency for normally distributed data measured at the interval and

ratio levels and is only appropriate for these levels of data (Grove, Gray, & Burns, 2015).

In a normal distribution, the mean, median, and mode are essentially equal (see Exercise

26 for determining the normality of a distribution). The mean is sensitive to extreme

80 EXERCISE 8 • Measures of Central Tendency: Mean, Median, and Mode

Copyright © 2017, Elsevier Inc. All rights reserved.

scores such as outliers. An outlier is a value in a sample data set that is unusually low or

unusually high in the context of the rest of the sample data. If a study has outliers, the

mean is most affected by these, so the median might be the measure of central tendency

included in the research report ( Plichta & Kelvin, 2013 ). The formula for the mean is:

MeanX

X

N

Σ is the sum of the raw scores in a study

is the sample size or number of scores in the study

Example:Raw scores 8, 9, 9,10,11,11 6 Mean 58 6 9.666 9.67

RESEARCH ARTICLE

Source

Winkler, C., Funk, M., Schindler, D. M., Hemsey, J. Z., Lampert, R., & Drew, B. J. (2013).

Arrhythmias in patients with acute coronary syndrome in the fi rst 24 hours of hospitalization.

Heart & Lung, 42 (6), 422–427.

Introduction

Winkler and colleagues (2013) conducted their study to describe the arrhythmias of a

population of patients with acute coronary syndrome (ACS) during their fi rst 24 hours

of hospitalization and to explore the link between arrhythmias and patients ’ outcomes.

The patients with ACS were admitted through the emergency department (ED), where a

Holter recorder was attached for continuous 12-lead electrocardiographic (ECG) monitoring.

The ECG data from the Holter recordings of 278 patients with ACS were analyzed.

The researchers found that “approximately 22% of patients had more than 50 premature

ventricular contractions (PVCs) per hour. Non-sustained ventricular tachycardia (VT)

occurred in 15% of the patients . . . . Only more than 50 PVCs/hour independently predicted

an increased length of stay ( < 0.0001). No arrhythmias predicted mortality. Age

greater than 65 years and a fi nal diagnosis of acute myocardial infarction (AMI) independently

predicted more than 50 PVCs per hour ( = 0.0004)” ( Winkler et al., 2013 , p. 422).

Winkler and colleagues (2013 , p. 426) concluded: “Life-threatening arrhythmias are

rare in patients with ACS, but almost one quarter of the sample experienced isolated

PVCs. There was a signifi cant independent association between PVCs and a longer length

of stay (LOS), but PVCs were not related to other adverse outcomes. Rapid treatment of

the underlying ACS should remain the focus, rather than extended monitoring for

arrhythmias we no longer treat.”

Relevant Study Results

The demographic and clinical characteristics of the sample and the patient outcomes for

this study are presented in this exercise. “The majority of the patients ( = 229; 83%) had

a near complete Holter recording of at least 20 h and 171 (62%) had a full 24 h recorded.

We included recordings of all patients in the analysis. The mean duration of continuous

12-lead Holter recording was 21 } 6 (median 24) h.

The mean patient age was 66 years and half of the patients identifi ed White as

their race ( Table 1 ). There were more males than females and most patients (92%) experienced

chest pain as one of the presenting symptoms to the ED. Over half of the patients

Measures of Central Tendency: Mean, Median, and Mode • EXERCISE 8 81

Copyright © 2017, Elsevier Inc. All rights reserved.

TABLE 1 DEMOGRAPHIC AND CLINICAL CHARACTERISTICS OF THE SAMPLE ( = 278)

Characteristic %

Gender

Male 158 57

Female 120 43

Race

White 143 51

Asian 60 22

Black 50 18

American Indian 23 8

Pacifi c Islander 2 < 1

Presenting Symptoms to the ED (May Have > 1)

Chest pain 255 92

Shortness of breath 189 68

Jaw, neck, arm, or back pain 152 55

Diaphoresis 116 42

Nausea and vomiting 96 35

Syncope 11 4

Cardiovascular Risk Factors (May Have > 1)

Hypertension 211 76

Hypercholesterolemia 175 63

Family history of CAD 148 53

Diabetes 81 29

Smoking (current) 56 20

Cardiovascular Medical History (May Have > 1)

Personal history of CAD 176 63

History of unstable angina 124 45

Previous acute myocardial infarction 114 41

Previous percutaneous coronary intervention 85 31

Previous CABG surgery 54 19

History of arrhythmias 53 19

Final Diagnosis

Unstable angina 180 65

Non-ST elevation myocardial infarction 74 27

ST elevation myocardial infarction 24 9

Interventions during 24-h Holter Recording

PCI ≤ 90 min of ED admission 14 5

PCI > 90 min of ED admission 3 1

Thrombolytic medication 3 1

Interventions Any Time during Hospitalization

PCI 76 27

Treated with anti-arrhythmic medication 16 6

CABG surgery 22 8

Mean ( SD ) Median Range

Age (years) 66 (14) 66 30–102

ECG recording time (hours) 21 (6) 24 2–25

ED, emergency department; CAD, coronary artery disease; CABG, coronary artery bypass graft; PCI, percutaneous coronary

intervention; SD , standard deviation; ECG, electrocardiogram.

Winkler, C., Funk, M., Schindler, D. M., Hemsey, J. Z., Lampert, R., & Drew, B. J. (2013). Arrhythmias in patients with acute

coronary syndrome in the fi rst 24 hours of hospitalization. Heart & Lung, 42 (6), p. 424.

82 EXERCISE 8 • Measures of Central Tendency: Mean, Median, and Mode

Copyright © 2017, Elsevier Inc. All rights reserved.

Winkler, C., Funk, M., Schindler, D. M., Hemsey, J. Z., Lampert, R., & Drew, B. J. (2013). Arrhythmias in patients with acute

coronary syndrome in the fi rst 24 hours of hospitalization. Heart & Lung 42 (6), p. 424.

TABLE 2 OUTCOMES DURING INPATIENT STAY, AND WITHIN 30 DAYS AND 1 YEAR OF

HOSPITALIZATION ( = 278)

Outcomes %

Inpatient complications (may have > 1)

AMI post admission for patients admitted with UA 21 8

Transfer to intensive care unit 17 6

Cardiac arrest 7 3

AMI extension (detected by 2nd rise in CK-MB) 6 2

Cardiogenic shock 5 2

New severe heart failure/pulmonary edema 2 1

Readmission *

30-day

To ED for a cardiovascular reason 42 15

To hospital for ACS 13 5

1-year ( = 246)

To ED for a cardiovascular reason 108 44

To hospital for ACS 24 10

All-cause mortality †

Inpatient 10 4

30-day 13 5

1-year ( = 246) 27 11

Mean ( SD ) Median Range

Length of stay (days) 5.37 (7.02) 4 1–93

AMI, acute myocardial infarction; UA, unstable angina; CK-MB, creatinine kinase-myocardial band; ED, emergency department;

ACS, acute coronary syndrome; SD , standard deviation.

* Readmission: 1-year data include 30-day data.

† All-cause mortality: 30-day data include inpatient data; 1-year data include both 30-day and inpatient data.

experienced shortness of breath (68%) and jaw, neck, arm, or back pain (55%). Hypertension

was the most frequently occurring cardiovascular risk factor (76%), followed by

hypercholesterolemia (63%) and family history of coronary artery disease (53%). A majority

had a personal history of coronary artery disease (63%) and 19% had a history of

arrhythmias” ( Winkler et al., 2013 , pp. 423–424).

Winkler et al. (2013 , p. 424) also reported: “We categorized patient outcomes into four

groups: 1) inpatient complications (of which some patients may have experienced more

than one); 2) inpatient length of stay; 3) readmission to either the ED or the hospital

within 30-days and 1-year of initial hospitalization; and 4) death during hospitalization,

within 30-days, and 1-year after discharge ( Table 2 ). These are outcomes that are reported

in many contemporary studies of patients with ACS. Thirty-two patients (11.5%) were lost

to 1-year follow-up, resulting in a sample size for the analysis of 1-year outcomes of 246

patients” ( Winkler et al., 2013 , p. 424).

Measures of Central Tendency: Mean, Median, and Mode • EXERCISE 8 83

Copyright © 2017, Elsevier Inc. All rights reserved.

STUDY QUESTIONS

1. In Table 1 , what is the mode for cardiovascular risk factors? Provide a rationale for your answer.

What percentage of the patients experienced this risk factor?

2. Which measure of central tendency always represents an actual score of the distribution?

a. Mean

b. Median

c. Mode

d. Range

3. What is the mode for the variable presenting symptoms to the ED? What percentage of the

patients had this symptom? Do the presenting symptoms have a single mode or is this distribution

bimodal or multimodal? Provide a rationale for your answer.

4. What are the three most common presenting symptoms to the ED, and why is this clinically

important?

5. For this study, what are the mean and median ages in years for the study participants?

6. Are the mean and median ages similar or different? What does this indicate about the distribution

of the sample?

84 EXERCISE 8 • Measures of Central Tendency: Mean, Median, and Mode

Copyright © 2017, Elsevier Inc. All rights reserved.

7. What are the mean and median ECG recording times in hours? What is the range for ECG

recordings? Does this distribution of data include an outlier? Provide a rationale for your answer.

8. What is the effect of outliers on the mean? If the study data have extreme outliers (either high

or low scores) in the data, what measure(s) of central tendency might be reported in a study?

Provide a rationale for your answer.

9. In the following example, 10 ACS patients were asked to rate their pain in their jaw and neck

on a 0–10 scale: 3, 4, 7, 7, 8, 5, 6, 8, 7, 9. What are the range and median for the pain scores?

10. Calculate the mean ( ) for the pain scores in Question 9. Does this distribution of scores appear

to be normal? Provide a rationale for your answer.

Copyright © 2017, Elsevier Inc. All rights reserved. 85

Answers to Study Questions

1. Hypertension (HTN) is the mode for the cardiovascular risk factors since it is the most frequent

risk factor experienced by 211 of the study participants. A total of 76% of the study

participants had HTN.

2. Answer: c. Mode. The mode is the most frequently occurring score in a distribution; thus, it

will always be an actual score of the distribution. The mean is the average of all scores, so it

may not be an actual score of the distribution. Median is the middle score of the distribution,

which, with an even number of items, may not be an actual score in the distribution. The

range is a measure of dispersion, not a measure of central tendency.

3. Chest pain was the mode for the variable presenting symptoms to the ED, with 255 or 92%

of the participants experiencing it (see Table 1 ). The variable presenting symptoms to the ED

has one mode, chest pain, which was the most reported symptom.

4. Chest pain (92%); shortness of breath (68%); and jaw, neck, arm, or back pain (55%) are the

three most commonly reported presenting symptoms to the ED by study participants. This

is clinically important because nurses and other healthcare providers need to assess for these

symptoms, diagnose the problem, and appropriately manage patients presenting with ACS

at the ED. Since 92% of the participants had chest pain, it is clinically important to note this

symptom is common for both males and females in this study.

5. Both the mean ( ) and median ( MD ) values were equal to 66 years.

6. In this study, the age = MD age = 66 years, so they are the same value. In a normal distribution

of scores, the mode = MD ( Grove et al., 2013 ). Since the MD = 66 years, age seems

to be normally distributed in this sample.

7. ECG recording time has = 21 hours and MD = 24 hours, with a range of 2–25 hours (see

Table 1 ). The 2 hours of ECG Holter monitoring seems to be an outlier, which resulted in

the difference between the mean and median ( = 21 hours and MD = 24 hours) numbers of

monitoring hours. Winkler et al. (2013) reported that 83% of the study participants had a

near complete Holter recording of at least 20 hours, and 62% of the participants had a full

24 hours recorded, which supports the 2 hours as an outlier. You would need to examine the

study data to determine more about possible outliers. All ECG data were analyzed regardless

of the monitoring time, and more explanation is needed about outliers and the reasons for

including all recordings in the study analyses.

8. An unusually low score or outlier decreases the value of the mean as in this study (see the

answer to Question 7), and an unusually high score increases the mean value. The mean in a

study is most affected by outliers ( Grove et al., 2013 ). If the outliers cause the data to be

skewed or not normally distributed, it is best to report the median. If the data are normally

distributed, then the mean is the best measure of central tendency to report.

86 EXERCISE 8 • Measures of Central Tendency: Mean, Median, and Mode

Copyright © 2017, Elsevier Inc. All rights reserved.

9. Place the pain scores in order from the least to the greatest score = 3, 4, 5, 6, 7, 7, 7, 8,

8, 9. In this example, the range of pain scores = 3–9. The mode = 7 and the MD or middle

score = 7.

10. = (3 + 4 + 5 + 6 + 7 + 7 + 7 + 8 + 8 + 9) ÷ 10 = 64 ÷ 10 = 6.4. The mode = median = approximately

the mean, so this is a normal distribution of scores. Exercise 26 provides the steps for

determining the normality of a distribution of scores.

Copyright © 2017, Elsevier Inc. All rights reserved. 87

Questions to Be Graded EXERCISE

8

Discussion Question Min 150 Words

Discussion Question Min 150 Words

  • Review Chapter 7 in The Future of Nursing: Leading Change, Advancing Health report provided in the Learning Resources. Focus on the information in Box 7.3, “Research Priorities for Transforming Nursing Leadership.”
  • Select one of the research priorities listed in Box 7.3 that is of particular interest to you and applicable to your career interests. Consider the benefits and challenges of researching and addressing this priority in nursing.
  • Using the Walden library, identify two to three current articles that address your selected research priority. Consider the current state of research efforts on this priority.
  • Reflect on how the research findings for your area of priority impact nurses as leaders in organizations and health care reform. Why is research on this priority important?

Discussion – The Employer’s View

Discussion – The Employer’s View

Employers are making an effort to involve employees more in their health care. This is evidenced by the increase in consumer-directed health plans being offered by employers today. Employers feel that the more informed and engaged an employee is, the lower their health care costs will be. Employee engagement is a way for employers to battle rising health care costs and outlook on managed care plans.

What managed care trends do you think affect employers today and which do you think has the greatest impact on employers? Explain your perspective with examples. Do these trends impact small and large employers the same or not?

Revised Paper

Revised Paper
Francis Marion Admission Letter

Hi, my name is Zyaria Fulmore. I’m from Myrtle Beach, South Carolina. I graduated from Carolina Forest High School in June of 2018 with a 3.4 gpa. While in high school I attended many events and was also very athletic. My freshman year I was on the JV cheerleading team. I also ran track my freshman until junior year. My sophomore year I ran for student council, from there I became treasure of my sophomore class, I also did the same for my junior year. With me trying new things and observing everything in school I still managed to score A’s and B’s.

My goal in life is to help others and work with kids that’s why I would love to become a pediatrician . After doing research I found that Francis Marion University has one of the top nursing programs in South Carolina. I see Francis Marion bettering my education therefore I will become one of the best pediatricians. I’ve spoke with a few people that graduated from Francis Marion and I heard nothing but great things, also after seeing people that graduated from Francis Marion I see nothing but success coming from them.

Once I attend Francis Marion my plan is to be very active with my college experience. I plan to be very active with my academics also on campus. Keeping up with my grades maintaining a 3.0 or higher gpa, I would like to try for many things such as track and field and getting engaged with many other things. My education journey at Francis Marion will lead me to a great life with success.

Discussion Post Response

Discussion Post Response

Questions asked:

Discuss some common causes for coding errors and the preventative measures you can use to avoid them.

2) What are some other measures you can add to the list that might not be in the course materials?

3) What is the Fraud and Abuse Control Program? What is the HHS OIG and what is it’s major concern?

Halle Pietras Week 3 :

OIG stands for the office of inspector general, they are an oversite agency that works for the United States department of Health and Human Services (HHS.) There goal is to promote and protect our healthcare programs. That also means they look out for things like fraud and abuse when it comes everything, even coding and billing.

When it comes to coding there is a lot to remember, but there’s also a lot left up to assumptions which is where people can get into trouble. There’s also a lot of “gray area’s” according to our book, which leaves things open to different interpretations. Those are hard things to combat but some suggestions and or rules help to eliminate them the best they can. One mandate to remember is that coding MUST be supported by a health record. Another one to prevent fraud would be to use outside auditors to review the claims and make sure things check out. Other basic things would be to monitor and double check the claims, to make sure everything is the most correct you can make it. Make sure you understand what you’re doing and if not ask someone who could advise you.

Reference

Aalseth, P. (2015). Medical Coding: What Is it and How It Works (2nd ed.). Burlington, MA: Jones & Bartlett Learning

Post 2

Richard Matos Week 3 – Discussion forumCOLLAPSE

Richard Matos

Professor J. Pryor

CPT Coding for Health Services Administration

Coders generally make two types of errors when making coding decisions; Performance errors and Systematic errors. Performance errors include misreading words, missing important details to the code assignment, failing to pull together details from various parts of the record and transposing digits in code numbers. Systematic errors include lack of sufficient medical knowledge to understand the documentation, lack of knowledge of or misapplication of coding rules.

To avoid errors coding departments should verify the patient’s insurance benefits and personal information, double check diagnosis and procedures codes, write clearly and implement an EHR billing system.  Conducting charts audits are also a good way to avoid submitting claims twice.  Proper training, care and attention to details is the best policy to avoid coding errors. also, managers should implement policies and programs to help staff better understand the importance of avoiding errors.

The U.S. Department of Health and Human Services established a Fraud and Abuse Control Program, effective January 1, 1997, to fight health care fraud, waste, and abuse.  The Office of Inspector General (OIG) carries nationwide audits, investigations, and inspections in order to protect the integrity of the HHS.  The OIG also has the authority to investigate hospitals, pharmaceutical manufacturers, third-party billing companies, ambulance companies, physicians practices, nursing facilities, home health agencies, clinical laboratories, hospices and companies that supply durable medical equipment, prosthetics, and orthotics.  The OIG also works with the FBI and other federal agencies in the investigation of fraud and abuse.

WC-262

Reference

https://www.m-scribe.com/blog/bid/291707/5-Tips-to-Help-Your-Practice-Avoid-Medical-Billing-Errors

https://www.cms.gov/newsroom/fact-sheets/health-care-fraud-and-abuse-control-program-protects-consumers-and-taxpayers-combating-health-care-0

Developmental Assessment Of School Age Child.

Developmental Assessment Of School Age Child.

The needs of the pediatric patient differ depending on age, as do the stages of development and the expected assessment findings for each stage. In a 1000-word paper, examine the needs of a school-aged child between the ages of 5 and 12 years old and discuss the following:

1. Compare the physical assessments among school-aged children. 2.Describe how you would modify assessment techniques to match the age and developmental stage of the child.
2. Choose a child between the ages of 5 and 12 years old. Identify the age of the child and describe the typical developmental stages of children that age.
3. Applying developmental theory based on Erickson, Piaget, or Kohlberg, explain how you would developmentally assess the child. Include how you would offer explanations during the assessment, strategies you would use to gain cooperation, and potential findings from the assessment.
Prepare assignment in APA Style Guide, NO plagiarism, 5 References in APA format.

Comment

Comment

comment1

Every organization has its stakeholders, irrespective of its size, nature, structure and purpose. The stakeholders can be any person or entity, who influence and can be influenced by the organization’s activities. Stakeholders can be categorized as internal and external stakeholders. Those who works with in the organization are known as internal stakeholder. Physicians, nurses and hospital management in my case are internal stakeholders. External stakeholders are those not employed by hospital but they have a say in hospital operations such as Licensing or Accreditation agencies like (Joint Commission), patients,policy makers, labor unions and care givers. Change is often difficult to implement because of inertia and so many competing interests. Certain elements must be in place in an organization for change to take hold: an agreed-on direction for the practice, a functional and effective leadership structure, and a culture that promotes and rewards change.

Comment2

Stakeholder buy-in is the glue that binds all elements of a project together and ensures that the change will actually happen”.( May, 2016). It is important to have the backing of the decision makers/stakeholders both within and outside of an organization to successfully push a change project through because:

  1. They will provide expertise from their wealth of knowledge about current process, historical information and way forward, thereby, bringing value to the project.
  2. They will help reduce or uncover risks involved in change project process in terms of project needs, constraints and plans to mitigate those problems as they arise to increase the chances of project success.
  3. They help to increase the success of the project by speeding up the process, providing resources and creating the support needed to move change forward.
  4. Finally, they have the power and authority to grant the project acceptance. (Schoenhard, 2017).