2.Discuss any attempts to incorporate the solution into public policy.

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Assignment

Please make sure that your writers are properly writing the final references of the journals correctly. The last paper the writer did not write the journal reference in the right format. Example, what he/she did was

Markinsin, J. The effects of health on others. Retrieved from http://journal of health management.

THIS IS INCORRECT FORMAT!!!!!!!!!!!!!!!!!!!!!!!!!!

All journals should be written as such:

Markinson, J. (2014). The effects of health on others. The Journal of Health Management, 6(3), p. 101-120.

The writers should know this. Please let me know if anything else is needed. This upcoming assignment is straightforward paper. Let the writers know that at least TWO scholarly nursing journals should be used.

ASSIGNMENT DETAILS:

As of 2014 health care expenditures in the United States are near 17% of our gross domestic product (GDP), with a major portion of Medicare funding goes towards chronic illness and care at the last 6 months of life. The Patient Protection and Affordable Care Act has made some initial legislative changes in our health system, but not sufficient to address our growing expenditures and caring for our large aging population. In this assignment, learners will synthesize issues in aging with health policy solutions by writing a paper on one health issue for older individuals addressed in the topic and offering a policy solution. Example of issue: In 2014, over 50% of the costs of institutional long-term care for older persons are paid for with public funds from Medicaid.

Directions:

Write a 12000-1500 word paper that addresses a health issue for older individuals. Include the following:

1.Evaluate what the literature suggests as a resolution to your chosen issue.

2.Discuss any attempts to incorporate the solution into public policy.

3.Determine the barriers to implementation of the solution.

4.Analyze the options being discussed for public and/or private funding.

5.Propose your own recommendation.

· Distinguish the professional responsibilities that accompany the nursing profession.

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I need 1 page paper, this is instruction:OverviewThis week’s assignment is also related to the ANA Code of Ethics – Provision 9. You might want to review provision 9 again. Advocating for the

  I need 1 page paper, this is instruction:

Overview

This week’s assignment is also related to the ANA Code of Ethics – Provision 9. You might want to review provision 9 again. Advocating for the profession is important. Writing a letter is one of the ways a nurse can positively promote nursing and its causes. The purpose of this assignment is to write a professional letter to address the image of nursing or to promote a cause for nursing.

This assignment is worth 20 points.

Learning Objectives

· Distinguish the professional responsibilities that accompany the nursing profession.

· Define pressing issues that may arise as a nurse.

Directions

Read the letter writing handout. Then construct a professional letter using one of the two options below. Your letter will consist of proper address, correct salutation/greeting, body of the letter, proper closing, and contact information.

Option A: Write a letter on a current economic or political topic related directly to nursing. Address your letter to the appropriate person – You need to write to a person who is in a position to do something about the problem. For example, you should not write to the President to address a healthcare issue that needs to be passed in congress. You would want to address the correct Senator or representative from your state who will be voting on the issue. This is a professional letter, so letter form, grammar and punctuation is graded, too. This could be to a congressman or woman or to other legislators, to big business or corporations. Remember, there must be a close nursing link to write this letter. You might want to look at a professional organization website in order to look for options.

Option B: Write a letter to defend the image of nursing. Most often nursing is portrayed as less than professional in popular media, TV, advertising, greeting cards, etc.  Choose an example and write a professional letter to the appropriate person to tell them why you think they have portrayed nursing unprofessionally. Tell them how this affects the image of nursing and provide suggestions to change the situation. Look at popular TV shows, e-greetings, traditional cards advertising etc. to find an example. You can even “Google” to find some ideas.

Edit question’s body

Why are coding standards important for promoting consistent, high-quality care?

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Discussion – Week 3 COLLAPSE Standardized Coding Systems As a result of the fragmented nature of the health care system, professionals in various specialty areas of medicine have developed their own unique sets of terminology to communicate within that sp

For suraya

APA Format 3 scholarly references at least one from Walden University Library

Discussion – Week 3

COLLAPSE

Standardized Coding Systems

As a result of the fragmented nature of the health care system, professionals in various specialty areas of medicine have developed their own unique sets of terminology to communicate within that specialty. In the past, limited attention has been given to codifying practices in order for them to be understood and utilized across disciplines or through different information technology systems. The implementation of a federally mandated electronic medical records system, therefore, poses a challenge to nursing professionals and others who must be prepared to utilize standardized codes for the new system. Why are coding standards important for promoting consistent, high-quality care?

According to Rutherford (2008, para. 15), “Improved communication with other nurses, health care professionals, and administrators of the institution in which nurses work is a key benefit of using a standardized nursing language.” In this Discussion you consider the reasoning behind and the value of standardized codification.

To prepare:

  • Review the information in Nursing Informatics: Scope and Standards of Practice. Determine which set of terminologies are appropriate for your specialty or area of expertise.
  • Reflect on the importance of continuity in terminology and coding systems.
  • In the article, “Standardized Nursing Language: What Does It Mean for Nursing Practice?” the author recounts a visit to a local hospital to view its implementation of a new coding system. One of the nurses commented to her, “We document our care using standardized nursing languages but we don’t fully understand why we do” (Rutherford, 2008, para. 1). Consider how you would inform this nurse (and others like her) of the importance of standardized nursing terminologies.
  • Reflect on the value of using a standard language in nursing practice. Consider if standardization can be limited to a specialty area or if one standard language is needed across all nursing practice. Then, identify examples of standardization in your own specialty or area of expertise. Conduct additional research using the Walden Library that supports your thoughts on standardization of nursing terminology.

2. Identify the databases and search words you would use.

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Application: Using the Data/Information/Knowledge/Wisdom Continuum

Application: Using the Data/Information/Knowledge/Wisdom Continuum

Have you ever gone online to search for a journal article on a specific topic? It is amazing to see the large number of journals that are available in the health care field. When you view the library in its entirety, you are viewing untapped data. Until you actually research for your particular topic, there is little structure. Once you have narrowed it down, you have information and once you apply the information, you have knowledge. Eventually, after thoughtful research and diligent practice, you reach the level of wisdom—knowledge applied in meaningful ways.

Are there areas in your practice that you believe should be more fully explored? The central aims of nursing informatics are to manage and communicate data, information, knowledge, and wisdom. This continuum represents the overarching structure of nursing informatics. In this Assignment, you develop a research question relevant to your practice area and relate how you would work through the progression from data to information, knowledge, and wisdom.

To prepare:

Review the information in Figure 6–2 in Nursing Informatics and the Foundation of Knowledge.

Develop a clinical question related to your area of practice that you would like to explore.

PS: Area of Practice- PAEDIATRIC NURSING

Consider what you currently know about this topic. What additional information would you need to answer the question?

Using the continuum of data, information, knowledge, and wisdom, determine how you would go about researching your question.

Explore the available databases in the Walden Library. Identify which of these databases you would use to find the information or data you need.

Once you have identified useful databases, how would you go about finding the most relevant articles and information?

Consider how you would extract the relevant information from the articles.

How would you take the information and organize it in a way that was useful? How could you take the step from simply having useful knowledge to gaining wisdom?

Write a 3- to 4-page paper that addresses the following:

1.     Summarize the question you developed, and then relate how you would work through the four steps of the data, information, knowledge, wisdom continuum. Be specific.

2.     Identify the databases and search words you would use.

3.     Relate how you would take the information gleaned and turn it into useable knowledge.

4.     Can informatics be used to gain wisdom? Describe how you would progress from simply having useful knowledge to the wisdom to make decisions about the information you have found during your database search.

Your paper must also include a title page, an introduction, a summary, and a reference page.

Learning Resources

Required Readings

American Nurses Association. (2015). Nursing informatics: Scope & standards of practice (2nd ed.). Silver Springs, MD: Author.

“Metastructures, Concepts, and Tools of Nursing Informatics”

This chapter explores the connections between data, information, knowledge, and wisdom and how they work together in nursing informatics. It also covers the influence that concepts and tools have on the field of nursing.

McGonigle, D., & Mastrian, K. G. (2015). Nursing informatics and the foundation of knowledge (3rd ed.). Burlington, MA: Jones and Bartlett Learning.

Chapter 6, “Overview of Nursing Informatics”

This chapter defines the foundations of nursing informatics (NI). The authors specify the disciplines that are integrated to form nursing informatics, along with major NI concepts.

Brokel, J. (2010). Moving forward with NANDA-I nursing diagnoses with Health Information Technology for Economic and Clinical Health (HITECH) Act Legislation: News updates. International Journal of Nursing Terminologies & Classifications, 21(4), 182–185.

In this news brief, the author describes the initiatives that NANDA-I will implement to remain abreast of the HITECH legislation of 2009. The author explains two recommendations for the federal government’s role in managing vocabularies, value sets, and code sets throughout the health care system.

Matney, S., Brewster, P. J., Sward, K. A., Cloyes, K. G., & Staggers, N. (2011). Philosophical approaches to the nursing informatics data-information-knowledge-wisdom framework. Advances in Nursing Science, 34(1), 6–18.

This article proposes a philosophical foundation for nursing informatics in which data, information, and knowledge can be synthesized by computer systems to support wisdom development. The authors describe how wisdom can add value to nursing informatics and to the nursing profession as a whole.

 Rutherford, M. A. (2008). Standardized nursing language: What does it mean for nursing practice? OJIN: The Online Journal of Issues in Nursing, 13(1). Retrieved from http://www.nursingworld.org/MainMenuCategories/ANAMarketplace/ANAPeriodicals/OJIN/TableofContents/vol132008/No1Jan08/ArticlePreviousTopic/StandardizedNursingLanguage.html

The author of this article provides justification for the use of a standardized nursing language, which will be necessary for incorporating electronic documentation into the health care field. The author defines standardized language in nursing, describes how such a language can be applied in a practice setting, and discusses the benefits of using a standardized language.

Westra, B. L., Subramanian, A., Hart, C. M., Matney, S. A., Wilson, P. S., Huff, S. M., … Delaney, C. W. (2010). Achieving “meaningful use” of electronic health records through the integration of the Nursing Management Minimum Data Set. The Journal of Nursing Administration, 40(7–8), 336–343.

This article explains the nursing management minimum data set (NMMDS), which is a research-based minimum set of standard data for nursing management and administration. The article describes how the NMMDS can be used to minimize the burden on health care administrators and increase the value of electronic health records within the health care system.

Required Media

Laureate Education (Producer). (2012a). Data, information, knowledge, and wisdom continuum. Baltimore, MD: Author.

McGonigle, D., & Mastrian, K. G. (2012). Nursing informatics and the foundation of knowledge (2nd ed.). Burlington, MA: Jones & Bartlett Learning. (p. 98, Chapter 6, Figure 6)

The continuum of data, information, knowledge, and wisdom is used in the health care field to describe discrete levels of understanding related to patient care and decision making. This video provides an overview of the continuum from data to wisdom.

Optional Resources

Truran, D., Saad, P., Zhang, M., & Innes, K. (2010). SNOMED CT and its place in health information management practice. Health Information Management Journal, 39(2), 37–39.

Brown, B. (2011). ICD-10-CM: What is it, and why are we switching? Journal of Health Care Compliance, 13(3), 51–79.

Which of the following affects drug distribution throughout the body?

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NURS6521 WEEK 1 QUIZ LATEST 2017 (Score 100%)

QuestionWeek 1 QuizQuestion 1 A patient has a blood serum drug level of 50 units/mL. The drug’s half-life is 1 hour. If concentrations above 25 units/mL are toxic and no more of the drug is given, how long will it take for the blood level to reach the nontoxic range?Question 2 During a clinic visit, a patient complains of having frequent muscle cramps in her legs. The nurse’s assessment reveals that the patient has been taking over-the-counter laxatives for the past 7 years. The nurse informed the patient that prolonged use of laxativesQuestion 3 Which of the following affects drug distribution throughout the body?Question 4 An unconscious patient has been brought to the hospital, and the physician has prescribed a life-saving drug to be administered parenterally. Which of the following methods would be the most appropriate for the nurse to use when administering the medication?Question 5 An older adult patient with a history of Alzheimer’s disease and numerous chronic health problems has been prescribed several medications during his current admission to hospital and recent declines in the patient’s cognition have impaired his ability to swallow pills. Which of the following medications may the nurse crush before administering them to this patient?Question 6 A nurse has been administering a drug to a patient intramuscularly (IM). The physician discontinued the IM dose and wrote an order for the drug to be given orally. The nurse notices that the oral dosage is considerably higher than the parenteral dose and understands that this due toQuestion 7 A patient who has ongoing pain issues has been prescribed meperidine (Demerol) IM. How should the nurse best administer this medication?Question 8 A 56-year-old female patient has been admitted to the hospital with chronic muscle spasms and has been prescribed a new medication to treat the spasms. She has a poorly documented allergy to eggs, synthetic clothes, and perfumes. What is the priority action of the nurse to ensure that prescribed medication does not experience an allergic reaction?Question 9 The nurse is caring for a patient receiving an aminoglycoside (antibiotic) that can be nephrotoxic. Which of the following will alert the nurse that the patient may be experiencing nephrotoxicity?Question 10 A nurse is caring for a patient who has recently moved from Vermont to south Florida. The patient has been on the same antihypertensive drug for 6 years and has had stable blood pressures and no adverse effects. Since her move, however, she reports “dizzy spells and weakness” and feels that the drug is no longer effective. The nurse suspects that the change in the effectiveness of the drug is related toQuestion 11 A patient with a recent diagnosis of acute renal failure has a long-standing seizure disorder which has been successfully controlled for several years with antiseizure medications. The nurse should recognize that the patient’s compromised renal function will likelyQuestion 12 A nurse is caring for a patient who has had part of her small intestine removed due to cancer. She has also now developed hypertension and has been prescribed a new medication to decrease her blood pressure. While planning the patient’s care, the nurse should consider a possible alteration in which of the following aspects of pharmacokinetics?Question 13 A nurse who is responsible for administering medications should understand that the goals of the MedWatch program are to (Select all that apply.)Question 14 The nurse’s assessment of a community-dwelling adult suggests that the client may have drug allergies that have not been previously documented. What statement by the client would confirm this?Question 15 A patient with a variety of chronic health problems is being seen by her nurse practitioner, who is currently reviewing the patient’s medication regimen. Which of the patient’s medications should prompt the nurse to teach her to avoid drinking grapefruit juice?Question 16 On the 1 a.m. rounds, the nurse finds a patient awake and frustrated that she cannot go to sleep. The nurse administers an ordered hypnotic to help the patient sleep. Two hours later, the nurse finds the patient out of bed, full of energy and cleaning her room. The nurse evaluates the patient’s response to the hypnotic asQuestion 17 Which of the following statements best defines how a chemical becomes termed a drug?Question 18 In light of her recent high blood pressure readings, a patient has been started on a thiazide diuretic and metoprolol (Lopressor), which is a beta-adrenergic blocker. What is the most likely rationale for using two medications to address the patient’s hypertension?Question 19 In which of the following patients would a nurse expect to experience alterations in drug metabolism?Question 20 30 ml = _______________tbspQuestion 21 Tylenol 325 mg/tablet, patient needs 650 mg; how many tables should patient take?Question 22 A patient who has been admitted to the hospital for a mastectomy has stated that she has experienced adverse drug effects at various times during her life. Which of the following strategies should the nurse prioritize in order to minimize the potential of adverse drug effects during the patient’s stay in the hospital?Question 23 A patient has been prescribed several drugs and fluids to be given intravenously. Before the nurse starts the intravenous administration, a priority assessment of the patient will be to note theQuestion 24 A nurse is discussing with a patient the efficacy of a drug that his physician has suggested, and he begin taking. Efficacy of a drug means which of the following?Question 25 A patient has been prescribed 1 mg lorazepam (Ativan) sublingual prior to the scheduled insertion of a peripherally inserted central (PIC) line. How should the nurse direct the patient when administering this medication?Question 26 A 79-year-old woman with a medical history that includes osteoporosis has recently moved to a long-term care facility. Medication reconciliation indicates that the woman has been taking calcitonin, salmon for several years. The nurse should recognize that the most likely route for the administration of this drug isQuestion 27 Mrs. Houston is a 78-year-old woman who resides in an assisted living facility. Her doctor prescribed digoxin at her last visit to the clinic and she has approached the nurse who makes regular visits to the assisted-living facility about this new drug. What teaching point should the nurse emphasize to Mrs. Houston?Question 28 A nurse is caring for an 81-year-old patient in a long-term care facility who takes nine different medications each day. The patient has a recent diagnosis of seizure disorder and has begun treatment with phenytoin (Dilantin), a highly protein-bound drug. After 1 month of Dilantin therapy, the patient is still extremely drowsy and sluggish. The nurse determines that the prolonged adverse effect is likely due toQuestion 29 A 72-year-old man who is unable to sleep since admission into the hospital is given a hypnotic medication at 9 p.m. The nurse finds the patient drowsy and confused at 10 a.m. the next day. The nurse is aware that this behavior is most likely due toQuestion 30 An 80-year-old man has been prescribed oxycodone for severe, noncancer, chronic pain. He tells the nurse that he has difficulty swallowing and asks if he can crush the tablet before swallowing. The nurse will advise the patient thatQuestion 31 A 72-year-old man with pain issues is being given a drug by the intramuscular route. His serum blood level concentrations have been erratic. The nurse suspects that this may be due toQuestion 32 An older adult who lives in a long-term care facility has recently begun taking losartan (Cozaar) for the treatment of hypertension. The nurse who provides care for this resident should recognize  that this change in the resident’s medication regimen make create a risk forQuestion 33 A 77-year-old man with a long history of absence seizures has been treated with ethosuximide for many years. The man is now in the process of moving to a long-term care facility and a nurse is creating a plan of care. The nurse understands the potential adverse effects of this drug and would consequently prioritize which of the following nursing diagnoses?Question 34 A 70-year-old woman with a history of a trial fibrillation has been admitted with a lower gastrointestinal bleed. During the nurse’s admission assessment, the nurse realizes that the patient has been taking ginkgo biloba supplements in addition to her prescribed warfarin, a combination that has resulted in bleeding. What nursing diagnosis should the nurse identify when planning this patient’s care?Question 35 A 67-year-old man is admitted to the hospital with pneumonia. He reports to the nurse that he has chronic arthritis and circulation problems. Further assessment by the nurse reveals that the patient has a history of mild hypertension. He explains that he owns a business and lives alone. The nurse determines that he is within the normal weight range for his height and age but has a fondness for spicy foods and sweets. Which of the mentioned patient variables will have the greatest impact on the effectiveness  of the patient’s drug therapy?Question 36 Mr. Lacuna is an 83-year-old resident of a long-term care facility who has a diagnosis of moderate Alzheimer disease. Mr. Lacuna’s physician recently prescribed oral rivastigmine, but he was unable to tolerate the drug due to its gastrointestinal effects. As a result, he has been ordered the transdermal patch form of the medication. When administering this form of rivastigmine, the nurse shouldQuestion 37 Frequent episodes of exercise-related chest pain have caused a 79-year-old woman to use her prescribed nitroglycerin spray several times in recent weeks. This patient’s age will have what effect on her use of nitroglycerin?Question 38 A nurse notes new drug orders for a patient who is already getting several medications. Which of the following is the most important consideration when preparing to administer the new drugs?Question 39 A 79-year-old woman who takes several medications for a variety of chronic health problems has been prescribed an oral ant platelet aggregator that is to be taken once daily. The nurse has encouraged the woman to take the pill at the same time of day that she takes some of her other medications. What is the most likely rationale for the nurse’s advice?Question 40 A home health nurse is performing a home visit to an elderly client who has early-stage dementia. The nurse observes that some of the client’s pill bottles are empty, even though the client is not due for refills for 2 weeks. What nursing diagnosis should the nurse prioritize when planning this client’s care?

Following the PICOT format, write a PICOT statement in your selected practice problem area of interest, which is applicable to your proposed capstone project.

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PICOT

The first step of the EBP process is to develop a question from the nursing practice problem of interest.

Select a practice problem of interest to use as the focus of your research.

Start with the patient and identify the clinical problems or issues that arise from clinical care.

Following the PICOT format, write a PICOT statement in your selected practice problem area of interest, which is applicable to your proposed capstone project.

The PICOT statement will provide a framework for your capstone project (the project students must complete during their final course in the RN-BSN program of study).

Conduct a literature search to locate research articles focused on your selected practice problem of interest. This literature search should include both quantitative and qualitative peer-reviewed research articles to support your practice problem.

Select six peer-reviewed research articles which will be utilized through the next 5 weeks as reference sources. Be sure that some of the articles use qualitative research and that some use quantitative research. Create a reference list in which the six articles are listed. Beneath each reference include the article’s abstract. The completed assignment should have a title page and a reference list with abstracts.

Suggestions for locating qualitative and quantitative research articles from credible sources:

  1. Use a library database such as CINAHL Complete for your search.
  2. Using the advanced search page check the box beside “Research Article” in the “Limit Your Results” section.
  3. When setting up the search you can type your topic in the top box, then add quantitative or qualitative as a search term in one of the lower boxes. Research articles often are described as qualitative or quantitative.

To narrow/broaden your search, remove the words qualitative and quantitative and include words that narrow or broaden your main topic. For example: Diabetes and pediatric and dialysis. To determine what research design was used, review the abstract and the methods section of the article. The author will provide a description of data collection using qualitative or quantitative methods.

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

P.S I already formulate the PICOT question and started on the paper. I just won’t have time to finish it

P- Bedside report among nurses and patient

I-Giving handoff in patient’s rooms

C-Bedside shift report vs report at nurses station

O-To involve patient in their plan of care, and to effectively provide patient with safe and quality of care.

T-During patient stay in the hospital.

Question what is the effect of bedside shift report on patient care compare to traditional report outside patient room?

Laws, D., & Amato, S. (2010). Incorporating bedside reporting into change-of-shift report.

Rehabilitation Nursing, 35 (2), 70-74. doi:10.1002/j2048-7940.2010.tb00034.x

Background: Conventionally patients and their family/caregivers were not involved in the process of change of shift report. In the past, shift report has been held in each units conference room with all the nurses listening to report on every patient in the unit (Tidwell et al, 2011, p. E2). Now days, change of shift handoff is done in the patient room, usually at the computer in front of the EMR. Bedside nursing report allows the patient and nurse the opportunity to share information, ask questions, and plan individualized interventions. Methods: implementation of moving changes od shift report to the bedside. Implementing the change of report started with a pre-implementation survey to all the nurses. Nurses were provided with survey question, consisted 6 statement, and they were asked to circle all the statement they found to be true (Laws & Amato, 2010., p. 70-74). The questions were: (1) Bedside report can improve patient safety. (2) bedside report provides an opportunity for patient to discuss their plan of care (3) Bedside report violate patients confidentiality (4)Bedside report holds off going staff more accountable than taped report (5) Bedside report takes longer than taped report (6)Bedside report reassure patient that staff work as a team (Laws & Amato, 2010, p. 72). After bedside report was initiated the result showed that most of the nurses felt that bedside report had improved patient safety and satisfaction (70%) and gives patient opportunity to discuss their plan (78%) (Laws & Amato, 2010, p. 70-74). In addition, it showed less issues with inaccurate or missing information, because it includes actual patient visualization. Recommendation: the patient satisfaction was improved once reporting was done with the patient in the room. Moving the report to the bedside allows accurate information to be exchanged. It was found that bedside reporting works best at the start of the day and evening shift (Laws & Amato, p. 73).

Compare this case study to your nursing practice and give a similar example from your nursing experience in which you might have run into an ethical situation.

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EXCEPTIONAL GENIUS ONLY

1. 

Click on this link to complete the DNR Interactive Case Study following the readings and presentation for this week. Associate what you have learned in your weekly materials with what was presented in the case study.

After you complete the case study, click on the “Interactive Case Study Journals” link to reflect upon what you have learned from the case study and related learning materials this week. Once opened, choose the DNR Interactive Case Study Journal and follow the instructions listed within the journal. Compare this case study to your nursing practice and give a similar example from your nursing experience in which you might have run into an ethical situation.

as you can see you need the link to complete the case study. You have my login to get int to the class and just watch the video so you can do this work. 

2. After reading this week’s assigned chapters, think about your nursing philosophy. In your own words, discuss your philosophy of nursing. Reflect on the definition of the four concepts of the nursing meta-paradigm. Write your own definition for each concept of the meta-paradigm of nursing. Which concept would you add to the meta-paradigm of nursing and why? Which concept would you eliminate and why?

Your paper should be 1–2 pages in length, in APA format, typed in Times New Roman with 12-point font, and double-spaced with 1″ margins. Cite at least one outside source using APA format.

Specific examples of how both theories could be applied in your specific clinical setting

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Draft late

The purpose of this assignment is to draft and submit a comprehensive and complete rough draft of your Nursing Theory Comparison paper in APA format. Your rough draft should include all of the research paper elements of a final draft, which are listed below. This will give you an opportunity for feedback from your instructor before you submit your final draft during week 7.

Based on the reading assignment (McEwen & Wills, Theoretical Basis for Nursing, Unit II: Nursing Theories, chapters 6–9), select a grand nursing theory.

  • After studying and analyzing the approved theory, write about this theory, including an overview of the theory and specific examples of how it could be applied in your own clinical setting.

Based on the reading assignment (McEwen & Wills, Theoretical Basis for Nursing, Unit II: Nursing Theories, chapters 10 and 11), select a middle-range theory.

  • After studying and analyzing the approved theory, write about this theory, including an overview of the theory and specific examples of how it could be applied in your own clinical setting.

The following should be included:

  1. An introduction, including an overview of both selected nursing theories
  2. Background of the theories
  3. Philosophical underpinnings of the theories
  4. Major assumptions, concepts, and relationships
  5. Clinical applications/usefulness/value to extending nursing science testability
  6. Comparison of the use of both theories in nursing practice
  7. Specific examples of how both theories could be applied in your specific clinical setting
  8. Parsimony
  9. Conclusion/summary
  10. References: Use the course text and a minimum of three additional sources, listed in APA format

The paper should be 8–10 pages long and based on instructor-approved theories. It should be typed in Times New Roman with 12-point font, and double-spaced with 1″ margins. APA format must be used, including a properly formatted cover page, in-text citations, and a reference list. The proper use of headings in APA format is also required.

Quantitative Research Critique

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FOR PHYLLIS YOUNG

Quantitative Research Critique

Some of the most significant current information on patient care in nursing comes from scholarly, peer-reviewed journals and articles. Within this category of information sources, we can further divide studies into qualitative and quantitative sources, each with their own set of methods and standards. Within each of these categories, nurses must be able to differentiate between sources of published data that are used to develop evidence-based practice.

The topic I would like for you to use is: Promoting adequate staffing and safe nurse-to-patient ratios within all healthcare institutions.

For this assignment, you will:

  • Write on the topic or issue that informs nursing practice and has been researched quantitatively. (Note: Meta-analysis and systematic review of literature studies may not be used for this assignment).
  • Select one nursing quantitative research article, published in a peer-reviewed journal, on your chosen topic and follow the steps below.
    • Summarize the research study to include the following:
      • Problem or purpose for the study.
      • Study design.
      • Setting.
      • Data collection.
      • Data analysis.
    • Critique the study in a narrative format addressing each of the following questions:
      • Is the problem significant to nursing and health care?
      • How will it generate or refine knowledge in nursing practice?
      • Was the review of background literature provided?
      • What topics or concepts were discussed in the review of literature?
      • Were ethical standards for research followed and how?
      • What do the findings of the study add to the current body of knowledge?
    • Conclusion:
      • Explain how the study will inform your practice or the practice of professional nursing.
      • Prepare the critique.
      • Follow APA style guidelines- also for referencing authors throughout the paper that you’ve quoted (ie: Roberts, 2015)
      • Use 12-point Times New Roman font.
      • Include a title and reference page.
      • Use the following subheadings:
        1. Summary.
        2. Critique.
        3. Conclusion.
      • Cite all references using APA style and formatting guidelines
      • CriteriaNon-performanceBasicProficientDistinguished Discuss the professional perspective for selection of the quantitative research study. 19% Does not discuss the professional perspective for selection of the quantitative research study.Identifies the topic used for the quantitative research study selected.Discusses the professional perspective for selection of the quantitative research study.Discusses the professional perspective for selection of the quantitative study and the anticipated application to the profession. Summarize the purpose, study design, data collection and analysis methods for the quantitative research study. 19% Does not summarize the purpose, study design, data collection and analysis methods for the quantitative research study.Summarizes some of the basic elements of the selected quantitative research study.Summarizes the purpose, study design, data collection and analysis methods for the quantitative research study.Summarizes the purpose, study design, data collection and analysis methods for the quantitative research study including how the literature review was conducted.Critically analyze the significance of the study and the contribution to nursing and health care. 19% Does not critically analyze the significance of the study and the contribution to nursing and health care.Provides a basic overview of the study and relation to nursing and health care.Critically analyzes the significance of the study and the contribution to nursing and health care.Critically analyzes the significance of the study and the contribution to nursing and health care including actual and potential populations served. Discuss the review of literature, ethical standards and findings of the study. 19% Does not discuss the review of literature, ethical standards and findings of the study.Provides a basic overview of literature review, ethical standards and findings of the study.Discusses the review of literature, ethical standards and findings of the study.Discusses the review of literature, ethical standards and findings of the study including limitations and potential alternate explanations for the findings.Explain how the study will inform current practice and the future of nursing practice. 19% Does not explain how the study will inform current practice and the future of nursing practice.Explains how the study relates to nursing practice.Explains how the study will inform current practice and the future of nursing practice.Explain how the study will inform current practice and the future of nursing practice and inter-professional collaboration. Effectively communicates by integrating research into written documents that follow APA format, as well as the consistent use of grammar, punctuation, and mechanics expected of a nursing professional. 5% Does not effectively communicate by integrating research into written documents that follow APA format, as well as the consistent use of grammar, punctuation, and mechanics expected of a nursing professional.Communicates by integrating research into written documents that lack consistency in APA format, grammar, punctuation, and mechanics expected of a nursing professional.Effectively communicates by integrating research into written documents that follow APA format, as well as the consistent use of grammar, punctuation, and mechanics expected of a nursing professional.Effectively communicates by integrating research into written documents that follow APA format, as well as the consistent use of grammar, punctuation, and mechanics expected of a nursing professional and leader.

8. What percentage of patients had irritable bowel syndrome as their primary diagnosis?

/in /by

how much for help with homework

how much would it cost to do the following:

How can graphics and/or statistics be used to misrepresent data? Where have you seen this done?

What are the characteristics of a population for which it would be appropriate to use mean/median/mode? When would the characteristics of a population make them inappropriate to use?

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.”

Name: _______________________________________________________

 Class: _____________________

 Date: ___________________________________________________________________________________ 68EXERCISE 6 •

 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.

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 sig-nifi 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 β 2 -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 short-acting 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.

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. A 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 deter-mine 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 ( f ) or number ( n ) 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 ( f ) Percentage (%) Cumulative % 1. < $40,000 2010%10% 2. $40,000–$59,999 5025%35% 3. $60,000–$79,999 8040%75% 4. $80,000–$100,000 4020%95% 5. > $100,000 105%100% EXERCISE 6 60EXERCISE 6 • Understanding Frequencies and PercentagesCopyright © 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., & Thean-der, 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 mod-erate 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 dif-ferences found in symptoms between the patients with moderate and severe airfl ow limi-tations. 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 research-ers concluded that patients with moderate or severe airfl ow limitations experienced mul-tiple 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 ( n = 42) or severe airfl ow limitations ( n = 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 ( p = 0.36) . . . . Highly prevalent physical symp-toms ( ≥ 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 Understanding Frequencies and Percentages • EXERCISE 6Copyright © 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 n = 42 Severe n = 49 p Value Sex, n (%)0.607 Women19 (45)29 (59) Men23 (55)20 (41)Age (yrs), mean ( SD )66.5 (8.6)67.9 (6.8)0.396Married/cohabitant n (%)29 (69)34 (71)0.854Employed, n (%)7 (17)7 (14)0.754Smoking, n %0.789 Smoking13 (31)12 (24) Former smokers28 (67)35 (71) Never smokers1 (2)2 (4)Pack years smoking, mean ( SD )29.1 (13.5)34.0 (19.5)0.177BMI (kg/m 2 ), mean ( SD )27.2 (5.2)26.5 (6.1)0.555FEV 1 % of predicted, mean ( SD )61.6 (8.4)42.2 (5.8) < 0.001SpO 2 % mean ( SD )95.8 (2.4)94.5 (3.0)0.009Physical health, mean ( SD )3.2 (0.8)3.0 (0.8)0.120Mental health, mean ( SD )3.7 (0.9)3.6 (1.0)0.628Exacerbation previous 6 months, n (%)14 (33)15 (31)0.781Admitted to hospital previous year, n (%)10 (24)14 (29)0.607Medication use, n (%) Inhaled glucocorticosteroids30 (71)44 (90)0.025 Systemic glucocorticosteroids3 (6.3)0 (0)0.094 Anticholinergic32 (76)42 (86)0.245 Long-acting β 2 -agonists30 (71)45 (92)0.011 Short-acting β 2 -agonists13 (31)32 (65)0.001 Analgesics11 (26)5 (10)0.046 Statins8 (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 psy-chological symptoms between patients with moderate and severe airfl ow limitations” ( Eckerblad et al., 2014 , p. 353). 62EXERCISE 6 • Understanding Frequencies and PercentagesCopyright © 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 fre-quency 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.

Interpreting Line Graphs EXERCISE 7

69 Interpreting Line Graphs STATISTICAL TECHNIQUE IN REVIEW Tables and fi gures are commonly used to present fi ndings from studies or to provide a way for researchers to become familiar with research data. Using fi gures, researchers are able to illustrate the results from descriptive data analyses, assist in identifying patterns in data, identify changes over time, and interpret exploratory fi ndings. A line graph is a fi gure that is developed by joining a series of plotted points with a line to illustrate how a variable changes over time. A line graph fi gure includes a horizontal scale, or x -axis, and a vertical scale, or y -axis. The x -axis is used to document time, and the y -axis is used to document the mean scores or values for a variable ( Grove, Burns, & Gray, 2013 ; Plichta & Kelvin, 2013 ). Researchers might include a line graph to compare the values for three or four variables in a study or to identify the changes in groups for a selected variable over time. For example, Figure 7-1 presents a line graph that documents time in weeks on the x -axis and mean weight loss in pounds on the y -axis for an experimental group consuming a low carbohydrate diet and a control group consuming a standard diet. This line graph illustrates the trend of a strong, steady increase in the mean weight lost by the experimental or intervention group and minimal mean weight loss by the control group. EXERCISE 7 FIGURE 7-1 ■ LINE GRAPH COMPARING EXPERIMENTAL AND CONTROL GROUPS FOR WEIGHT LOSS OVER FOUR WEEKS. Weight loss (lbs)Weeksy-axisx-axisControlExperimental10864201234 70EXERCISE 7 • Interpreting Line GraphsCopyright © 2017, Elsevier Inc. All rights reserved. RESEARCH ARTICLE Source Azzolin, K., Mussi, C. M., Ruschel, K. B., de Souza, E. N., Lucena, A. D., & Rabelo-Silva, E. R. (2013). Effectiveness of nursing interventions in heart failure patients in home care using NANDA-I, NIC, and NOC. Applied Nursing Research, 26 (4), 239–244. Introduction Azzolin and colleagues (2013) analyzed data from a larger randomized clinical trial to determine the effectiveness of 11 nursing interventions (NIC) on selected nursing out-comes (NOC) in a sample of patients with heart failure (HF) receiving home care. A total of 23 patients with HF were followed for 6 months after hospital discharge and provided four home visits and four telephone calls. The home visits and phone calls were organized using the nursing diagnoses from the North American Nursing Diagnosis Association International (NANDA-I) classifi cation list. The researchers found that eight nursing interven tions signifi cantly improved the nursing outcomes for these HF patients. Those interventions included “health education, self-modifi cation assistance, behavior modifi -cation, telephone consultation, nutritional counselling, teaching: prescribed medications, teaching: disease process, and energy management” ( Azzolin et al., 2013 , p. 243). The researchers concluded that the NANDA-I, NIC, and NOC linkages were useful in manag-ing patients with HF in their home. Relevant Study Results Azzolin and colleagues (2013) presented their results in a line graph format to display the nursing outcome changes over the 6 months of the home visits and phone calls. The nursing outcomes were measured with a fi ve-point Likert scale with 1 = worst and 5 = best. “Of the eight outcomes selected and measured during the visits, four belonged to the health & knowledge behavior domain (50%), as follows: knowledge: treatment regimen; compliance behavior; knowledge: medication; and symptom control. Signifi cant increases were observed in this domain for all outcomes when comparing mean scores obtained at visits no. 1 and 4 ( Figure 1 ; p < 0.001 for all comparisons). The other four outcomes assessed belong to three different NOC domains, namely, functional health (activity tolerance and energy conservation), physiologic health (fl uid balance), and family health (family participation in professional care). The scores obtained for activity tolerance and energy conservation increased signifi cantly from visit no. 1 to visit no. 4 ( p = 0.004 and p < 0.001, respectively). Fluid balance and family participation in professional care did not show statistically signifi cant differences ( p = 0.848 and p = 0.101, respectively) ( Figure 2 )” ( Azzolin et al., 2013 , p. 241). The signifi cance level or alpha ( α ) was set at 0.05 for this study. Interpreting Line Graphs • EXERCISE 7Copyright © 2017, Elsevier Inc. All rights reserved. FIGURE 2 ■ NURSING OUTCOMES MEASURED OVER 6 MONTHS (OTHER DOMAINS): Activity tolerance (95% CI − 1.38 to − 0.18, p = 0.004); energy conservation (95% CI − 0.62 to − 0.19, p < 0.001); fl uid balance (95% CI − 0.25 to 0.07, p = .848); family participation in professional care (95% CI − 2.31 to − 0.11, p = 0.101). HV = home visit. CI = confi dence interval. Azzolin, K., Mussi, C. M., Ruschel, K. B., de Souza, E. N., Lucena, A. D., & Rabelo-Silva, E. R. (2013). Effectiveness of nursing interventions in heart failure patients in home care using NANDA-I, NIC, and NOC. Applied Nursing Research, 26 (4), p. 242. 5.04.54.03.53.02.52.01.51.00.50MeanHV1HV2HV3HV4Fluid balanceFamily participationin professional careActivity toleranceEnergy conservation FIGURE 1 ■ NURSING OUTCOMES MEASURED OVER 6 MONTHS (HEALTH & KNOWLEDGE BEHAVIOR DOMAIN): Knowledge: medication (95% CI − 1.66 to − 0.87, p < 0.001); knowledge: treatment regimen (95% CI − 1.53 to − 0.98, p < 0.001); symptom control (95% CI − 1.93 to − 0.95, p < 0.001); and compliance behavior (95% CI − 1.24 to − 0.56, p < 0.001). HV = home visit. CI = confi dence interval. 5.04.54.03.53.02.52.01.51.00.50MeanHV1HV2HV3HV4Compliance behaviorSymptom controlKnowledge: medicationKnowledge: treatment reg 72EXERCISE 7 • Interpreting Line GraphsCopyright © 2017, Elsevier Inc. All rights reserved. STUDY QUESTIONS 1. What is the purpose of a line graph? What elements are included in a line graph? 2. Review Figure 1 and identify the focus of the x -axis and the y -axis. What is the time frame for the x -axis? What variables are presented on this line graph? 3. In Figure 1 , did the nursing outcome compliance behavior change over the 6 months of home visits? Provide a rationale for your answer. 4. State the null hypothesis for the nursing outcome compliance behavior. 5. Was there a signifi cant difference in compliance behavior from the fi rst home visit (HV1) to the fourth home visit (HV4)? Was the null hypothesis accepted or rejected? Provide a rationale for your answer. 6. In Figure 1 , what outcome had the lowest mean at HV1? Did this outcome improve over the four home visits? Provide a rationale for your answer.

Copyright © 2017, Elsevier Inc. All rights reserved. 77

Questions to Be Graded EXERCISE 7 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 is the focus of the example Figure 7-1 in the section introducing the statistical technique of this exercise?

2. In Figure 2 of the Azzolin et al. (2013 , p. 242) study, did the nursing outcome activity tolerance change over the 6 months of home visits (HVs) and telephone calls? Provide a rationale for your answer.

3. State the null hypothesis for the nursing outcome activity tolerance.

4. Was there a signifi cant difference in activity tolerance from the fi rst home visit (HV1) to the fourth home visit (HV4)? Was the null hypothesis accepted or rejected? Provide a rationale for your answer.

5. In Figure 2 , what nursing outcome had the lowest mean at HV1? Did this outcome improve over the four HVs? Provide a rationale for your answer.

6. What nursing outcome had the highest mean at HV1 and at HV4? Was this outcome signifi -cantly different from HV1 to HV4? Provide a rationale for your answer.

7. State the null hypothesis for the nursing outcome family participation in professional care.

 8. Was there a statistically signifi cant difference in family participation in professional care from HV1 to HV4? Was the null hypothesis accepted or rejected? Provide a rationale for your answer.

9. Was Figure 2 helpful in understanding the nursing outcomes for patients with heart failure (HF) who received four HVs and telephone calls? Provide a rationale for your answer. 10. What nursing interventions signifi cantly improved the nursing outcomes for these patients with HF? What implications for practice do you note from these study results? Copyright © 2017, Elsevier Inc. All rights reserved. 79 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 sub-jected to mathematical operations. If a distribution has two scores that occur more fre-quently 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 distribu-tion 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 ten-dency for ordinal-level data and for nonnormally distributed or skewed interval- or ratio-level data. The following formula can be used to calculate a median in a distribution of scores. Median()()MDN=+÷12 N is the number of scores ExampleMedianscoreth_N==+=÷=31311232216 ExampleMedianscoreth:.N==+=÷=404012412205 Thus in the second example, the median is halfway between the 20 th and the 21 st scores. The mean ( X ) 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

Copyright © 2017, Elsevier Inc. All rights reserved. 77 Questions to Be Graded EXERCISE 7 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 is the focus of the example Figure 7-1 in the section introducing the statistical technique of this exercise? 2. In Figure 2 of the Azzolin et al. (2013 , p. 242) study, did the nursing outcome activity tolerance change over the 6 months of home visits (HVs) and telephone calls? Provide a rationale for your answer. 3. State the null hypothesis for the nursing outcome activity tolerance. 4. Was there a signifi cant difference in activity tolerance from the fi rst home visit (HV1) to the fourth home visit (HV4)? Was the null hypothesis accepted or rejected? Provide a rationale for your answer. Name: _______________________________________________________ Class: _____________________ Date: ___________________________________________________________________________________ 78EXERCISE 7 • Interpreting Line GraphsCopyright © 2017, Elsevier Inc. All rights reserved. 5. In Figure 2 , what nursing outcome had the lowest mean at HV1? Did this outcome improve over the four HVs? Provide a rationale for your answer. 6. What nursing outcome had the highest mean at HV1 and at HV4? Was this outcome signifi -cantly different from HV1 to HV4? Provide a rationale for your answer. 7. State the null hypothesis for the nursing outcome family participation in professional care. 8. Was there a statistically signifi cant difference in family participation in professional care from HV1 to HV4? Was the null hypothesis accepted or rejected? Provide a rationale for your answer. 9. Was Figure 2 helpful in understanding the nursing outcomes for patients with heart failure (HF) who received four HVs and telephone calls? Provide a rationale for your answer. 10. What nursing interventions signifi cantly improved the nursing outcomes for these patients with HF? What implications for practice do you note from these study results? Copyright © 2017, Elsevier Inc. All rights reserved. 79 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 sub-jected to mathematical operations. If a distribution has two scores that occur more fre-quently 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 distribu-tion 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 ten-dency for ordinal-level data and for nonnormally distributed or skewed interval- or ratio-level data. The following formula can be used to calculate a median in a distribution of scores. Median()()MDN=+÷12 N is the number of scores ExampleMedianscoreth_N==+=÷=31311232216 ExampleMedianscoreth:.N==+=÷=404012412205 Thus in the second example, the median is halfway between the 20 th and the 21 st scores. The mean ( X ) 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

Copyright © 2017, Elsevier Inc. All rights reserved. 77 Questions to Be Graded EXERCISE 7 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 is the focus of the example Figure 7-1 in the section introducing the statistical technique of this exercise?

2. In Figure 2 of the Azzolin et al. (2013 , p. 242) study, did the nursing outcome activity tolerance change over the 6 months of home visits (HVs) and telephone calls? Provide a rationale for your answer.

3. State the null hypothesis for the nursing outcome activity tolerance.

 4. Was there a signifi cant difference in activity tolerance from the fi rst home visit (HV1) to the fourth home visit (HV4)? Was the null hypothesis accepted or rejected? Provide a rationale for your answer.

 5. In Figure 2 , what nursing outcome had the lowest mean at HV1? Did this outcome improve over the four HVs? Provide a rationale for your answer.

6. What nursing outcome had the highest mean at HV1 and at HV4? Was this outcome signifi -cantly different from HV1 to HV4? Provide a rationale for your answer.

7. State the null hypothesis for the nursing outcome family participation in professional care.

8. Was there a statistically signifi cant difference in family participation in professional care from HV1 to HV4? Was the null hypothesis accepted or rejected? Provide a rationale for your answer.

9. Was Figure 2 helpful in understanding the nursing outcomes for patients with heart failure (HF) who received four HVs and telephone calls? Provide a rationale for your answer.

 10. What nursing interventions signifi cantly improved the nursing outcomes for these patients with HF? What implications for practice do you note from these study results?

Copyright © 2017, Elsevier Inc. All rights reserved. 79 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 sub-jected to mathematical operations. If a distribution has two scores that occur more fre-quently 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 distribu-tion 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 ten-dency for ordinal-level data and for nonnormally distributed or skewed interval- or ratio-level data. The following formula can be used to calculate a median in a distribution of scores. Median()()MDN=+÷12 N is the number of scores ExampleMedianscoreth_N==+=÷=31311232216 ExampleMedianscoreth:.N==+=÷=404012412205 Thus in the second example, the median is halfway between the 20 th and the 21 st scores. The mean ( X ) 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

Copyright © 2017, Elsevier Inc. All rights reserved. 291

Calculating Descriptive Statistics

There are two major classes of statistics: descriptive statistics and inferential statistics. Descriptive statistics are computed to reveal characteristics of the sample data set and to describe study variables. Inferential statistics are computed to gain information about effects and associations in the population being studied. For some types of studies, descriptive statistics will be the only approach to analysis of the data. For other studies, descriptive statistics are the fi rst step in the data analysis process, to be followed by infer-ential statistics. For all studies that involve numerical data, descriptive statistics are crucial in understanding the fundamental properties of the variables being studied. Exer-cise 27 focuses only on descriptive statistics and will illustrate the most common descrip-tive statistics computed in nursing research and provide examples using actual clinical data from empirical publications. MEASURES OF CENTRAL TENDENCY A measure of central tendency is a statistic that represents the center or middle of a frequency distribution. The three measures of central tendency commonly used in nursing research are the mode, median ( MD ), and mean ( X ). The mean is the arithmetic average of all of a variable ’ s values. The median is the exact middle value (or the average of the middle two values if there is an even number of observations). The mode is the most commonly occurring value or values (see Exercise 8 ). The following data have been collected from veterans with rheumatoid arthritis ( Tran, Hooker, Cipher, & Reimold, 2009 ). The values in Table 27-1 were extracted from a larger sample of veterans who had a history of biologic medication use (e.g., infl iximab [Remi-cade], etanercept [Enbrel]). Table 27-1 contains data collected from 10 veterans who had stopped taking biologic medications, and the variable represents the number of years that each veteran had taken the medication before stopping. Because the number of study subjects represented below is 10, the correct statistical notation to refl ect that number is: n=10 Note that the n is lowercase, because we are referring to a sample of veterans. If the data being presented represented the entire population of veterans, the correct notation is the uppercase N. Because most nursing research is conducted using samples, not popu-lations, all formulas in the subsequent exercises will incorporate the sample notation, n. Mode The mode is the numerical value or score that occurs with the greatest frequency; it does not necessarily indicate the center of the data set. The data in Table 27-1 contain two EXERCISE 27 292EXERCISE 27 • Calculating Descriptive StatisticsCopyright © 2017, Elsevier Inc. All rights reserved. modes: 1.5 and 3.0. Each of these numbers occurred twice in the data set. When two modes exist, the data set is referred to as bimodal ; a data set that contains more than two modes would be multimodal . Median The median ( MD ) is the score at the exact center of the ungrouped frequency distribution. It is the 50th percentile. To obtain the MD , sort the values from lowest to highest. If the number of values is an uneven number, exactly 50% of the values are above the MD and 50% are below it. If the number of values is an even number, the MD is the average of the two middle values. Thus the MD may not be an actual value in the data set. For example, the data in Table 27-1 consist of 10 observations, and therefore the MD is calculated as the average of the two middle values. MD=+()=15202175… Mean The most commonly reported measure of central tendency is the mean. The mean is the sum of the scores divided by the number of scores being summed. Thus like the MD, the mean may not be a member of the data set. The formula for calculating the mean is as follows: XXn=∑ where X = mean ∑ = sigma, the statistical symbol for summation X = a single value in the sample n = total number of values in the sample The mean number of years that the veterans used a biologic medication is calculated as follows: X=+++++++++()=010313151520223030401019………..years TABLE 27-1 DURATION OF BIOLOGIC USE AMONG VETERANS WITH RHEUMATOID ARTHRITIS ( n = 10) Duration of Biologic Use (years) 0.10.31.31.51.52.02.23.03.04.0 293Calculating Descriptive Statistics • EXERCISE 27Copyright © 2017, Elsevier Inc. All rights reserved. The mean is an appropriate measure of central tendency for approximately normally distributed populations with variables measured at the interval or ratio level. It is also appropriate for ordinal level data such as Likert scale values, where higher numbers rep-resent more of the construct being measured and lower numbers represent less of the construct (such as pain levels, patient satisfaction, depression, and health status). The mean is sensitive to extreme 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. An example of an outlier in the data presented in Table 27-1 might be a value such as 11. The existing values range from 0.1 to 4.0, meaning that no veteran used a biologic beyond 4 years. If an additional veteran were added to the sample and that person used a biologic for 11 years, the mean would be much larger: 2.7 years. Simply adding this outlier to the sample nearly doubled the mean value. The outlier would also change the frequency distribution. Without the outlier, the frequency distribution is approximately normal, as shown in Figure 27-1 . Including the outlier changes the shape of the distribution to appear positively skewed. Although the use of summary statistics has been the traditional approach to describing data or describing the characteristics of the sample before inferential statistical analysis, its ability to clarify the nature of data is limited. For example, using measures of central tendency, particularly the mean, to describe the nature of the data obscures the impact of extreme values or deviations in the data. Thus, signifi cant features in the data may be concealed or misrepresented. Often, anomalous, unexpected, or problematic data and discrepant patterns are evident, but are not regarded as meaningful. Measures of disper-sion, such as the range, difference scores, variance, and standard deviation ( SD ), provide important insight into the nature of the data. MEASURES OF DISPERSION Measures of dispersion , or variability, are measures of individual differences of the members of the population and sample. They indicate how values in a sample are dis-persed around the mean. These measures provide information about the data that is not available from measures of central tendency. They indicate how different the scores are—the extent to which individual values deviate from one another. If the individual values are similar, measures of variability are small and the sample is relatively homogeneous in terms of those values. Heterogeneity (wide variation in scores) is important in some statistical procedures, such as correlation. Heterogeneity is determined by measures of variability. The measures most commonly used are range, difference scores, variance, and SD (see Exercise 9 ). FIGURE 27-1 ■ FREQUENCY DISTRIBUTION OF YEARS OF BIOLOGIC USE, WITHOUT OUTLIER AND WITH OUTLIER. 0FrequencyFrequency3-3.90-0.92-2.91-1.94-4.93-3.90-.91-1.92-2.94-4.95-5.96-6.97-7.98-8.99-9.910-10.911-11.9Years of biologic useYears of biologic use3.02.52.01.51.00.503.02.52.01.51.00.5 294EXERCISE 27 • Calculating Descriptive StatisticsCopyright © 2017, Elsevier Inc. All rights reserved. Range The simplest measure of dispersion is the range . In published studies, range is presented in two ways: (1) the range is the lowest and highest scores, or (2) the range is calculated by subtracting the lowest score from the highest score. The range for the scores in Table 27-1 is 0.3 and 4.0, or it can be calculated as follows: 4.0 − 0.3 = 3.7. In this form, the range is a difference score that uses only the two extreme scores for the comparison. The range is generally reported but is not used in further analyses. Difference Scores Difference scores are obtained by subtracting the mean from each score. Sometimes a difference score is referred to as a deviation score because it indicates the extent to which a score deviates from the mean. Of course, most variables in nursing research are not “scores,” yet the term difference score is used to represent a value ’ s deviation from the mean. The difference score is positive when the score is above the mean, and it is negative when the score is below the mean (see Table 27-2 ). Difference scores are the basis for many statistical analyses and can be found within many statistical equations. The formula for difference scores is: XX− Σof absolute values95:. TABLE 27-2 DIFFERENCE SCORES OF DURATION OF BIOLOGIC USE X –X XX– 0.1 − 1.9 − 1.80.3 − 1.9 − 1.61.3 − 1.9 − 0.61.5 − 1.9 − 0.41.5 − 1.9 − 0.42.0 − 1.90.12.2 − 1.90.33.0 − 1.91.13.0 − 1.91.14.0 − 1.92.1 The mean deviation is the average difference score, using the absolute values. The formula for the mean deviation is: XXXndeviation=−∑ In this example, the mean deviation is 0.95. This value was calculated by taking the sum of the absolute value of each difference score (1.8, 1.6, 0.6, 0.4, 0.4, 0.1, 0.3, 1.1, 1.1, 2.1) and dividing by 10. The result indicates that, on average, subjects ’ duration of biologic use deviated from the mean by 0.95 years. Variance Variance is another measure commonly used in statistical analysis. The equation for a sample variance ( s 2 ) is below. sXXn221=−()−∑ 295Calculating Descriptive Statistics • EXERCISE 27Copyright © 2017, Elsevier Inc. All rights reserved. Note that the lowercase letter s 2 is used to represent a sample variance. The lowercase Greek sigma ( σ 2 ) is used to represent a population variance, in which the denominator is N instead of n − 1. Because most nursing research is conducted using samples, not popu-lations, formulas in the subsequent exercises that contain a variance or standard deviation will incorporate the sample notation, using n − 1 as the denominator. Moreover, statistical software packages compute the variance and standard deviation using the sample formu-las, not the population formulas. The variance is always a positive value and has no upper limit. In general, the larger the variance, the larger the dispersion of scores. The variance is most often computed to derive the standard deviation because, unlike the variance, the standard deviation refl ects impor-tant properties about the frequency distribution of the variable it represents. Table 27-3 displays how we would compute a variance by hand, using the biologic duration data. s213419=. s²=1.49 TABLE 27-3 VARIANCE COMPUTATION OF BIOLOGIC USE X X XX– XX–(())2 0.1 − 1.9 − 1.83.240.3 − 1.9 − 1.62.561.3 − 1.9 − 0.60.361.5 − 1.9 − 0.40.161.5 − 1.9 − 0.40.162.0 − 1.90.10.012.2 − 1.90.30.093.0 − 1.91.11.213.0 − 1.91.11.214.0 − 1.92.14.41 Σ 13.41 Standard Deviation Standard deviation is a measure of dispersion that is the square root of the variance. The standard deviation is represented by the notation s or SD . The equation for obtaining a standard deviation is SDX=−()−∑Xn21 Table 27-3 displays the computations for the variance. To compute the SD , simply take the square root of the variance. We know that the variance of biologic duration is s 2 = 1.49. Therefore, the s of biologic duration is SD = 1.22. The SD is an important sta-tistic, both for understanding dispersion within a distribution and for interpreting the relationship of a particular value to the distribution. SAMPLING ERROR A standard error describes the extent of sampling error. For example, a standard error of the mean is calculated to determine the magnitude of the variability associated with the mean. A small standard error is an indication that the sample mean is close to 296EXERCISE 27 • Calculating Descriptive StatisticsCopyright © 2017, Elsevier Inc. All rights reserved. the population mean, while a large standard error yields less certainty that the sample mean approximates the population mean. The formula for the standard error of the mean ( sX ) is: ssnX= Using the biologic medication duration data, we know that the standard deviation of biologic duration is s = 1.22. Therefore, the standard error of the mean for biologic dura-tion is computed as follows: sX=12210. sX=039. The standard error of the mean for biologic duration is 0.39. Confi dence Intervals To determine how closely the sample mean approximates the population mean, the stan-dard error of the mean is used to build a confi dence interval. For that matter, a confi dence interval can be created for many statistics, such as a mean, proportion, and odds ratio. To build a confi dence interval around a statistic, you must have the standard error value and the t value to adjust the standard error. The degrees of freedom ( df ) to use to compute a confi dence interval is df = n − 1. To compute the confi dence interval for a mean, the lower and upper limits of that interval are created by multiplying the sX by the t statistic, where df = n − 1. For a 95% confi dence interval, the t value should be selected at α = 0.05. For a 99% confi dence inter-val, the t value should be selected at α = 0.01. Using the biologic medication duration data, we know that the standard error of the mean duration of biologic medication use is sX=039. . The mean duration of biologic medication use is 1.89. Therefore, the 95% confi dence interval for the mean duration of biologic medication use is computed as follows: XstX± 189039226…±()() 189088..± As referenced in Appendix A , the t value required for the 95% confi dence interval with df = 9 is 2.26. The computation above results in a lower limit of 1.01 and an upper limit of 2.77. This means that our confi dence interval of 1.01 to 2.77 estimates the population mean duration of biologic use with 95% confi dence ( Kline, 2004 ). Technically and math-ematically, it means that if we computed the mean duration of biologic medication use on an infi nite number of veterans, exactly 95% of the intervals would contain the true population mean, and 5% would not contain the population mean ( Gliner, Morgan, & Leech, 2009 ). If we were to compute a 99% confi dence interval, we would require the t value that is referenced at α = 0.01. Therefore, the 99% confi dence interval for the mean duration of biologic medication use is computed as follows: 189039325…±()() 189127..± 297Calculating Descriptive Statistics • EXERCISE 27Copyright © 2017, Elsevier Inc. All rights reserved. As referenced in Appendix A , the t value required for the 99% confi dence interval with df = 9 is 3.25. The computation above results in a lower limit of 0.62 and an upper limit of 3.16. This means that our confi dence interval of 0.62 to 3.16 estimates the population mean duration of biologic use with 99% confi dence. Degrees of Freedom The concept of degrees of freedom ( df ) was used in reference to computing a confi dence interval. For any statistical computation, degrees of freedom are the number of inde-pendent pieces of information that are free to vary in order to estimate another piece of information ( Zar, 2010 ). In the case of the confi dence interval, the degrees of freedom are n − 1. This means that there are n − 1 independent observations in the sample that are free to vary (to be any value) to estimate the lower and upper limits of the confi dence interval. SPSS COMPUTATIONS A retrospective descriptive study examined the duration of biologic use from veterans with rheumatoid arthritis ( Tran et al., 2009 ). The values in Table 27-4 were extracted from a larger sample of veterans who had a history of biologic medication use (e.g., infl iximab [Remicade], etanercept [Enbrel]). Table 27-4 contains simulated demographic data col-lected from 10 veterans who had stopped taking biologic medications. Age at study enroll-ment, duration of biologic use, race/ethnicity, gender (F = female), tobacco use (F = former use, C = current use, N = never used), primary diagnosis (3 = irritable bowel syndrome, 4 = psoriatic arthritis, 5 = rheumatoid arthritis, 6 = reactive arthritis), and type of biologic medication used were among the study variables examined. TABLE 27-4 DEMOGRAPHIC VARIABLES OF VETERANS WITH RHEUMATOID ARTHRITIS Patient ID Duration (yrs) Age Race/Ethnicity Gender Tobacco Diagnosis Biologic 10.142CaucasianFF5Infl iximab20.341Black, not of Hispanic OriginFF5Etanercept31.356CaucasianFN5Infl iximab41.578CaucasianFF3Infl iximab51.586Black, not of Hispanic OriginFF4Etanercept62.049CaucasianFF6Etanercept72.282CaucasianFF5Infl iximab83.035CaucasianFN3Infl iximab93.059Black, not of Hispanic OriginFC3Infl iximab104.037CaucasianFF5Etanercept 298EXERCISE 27 • Calculating Descriptive StatisticsCopyright © 2017, Elsevier Inc. All rights reserved. This is how our data set looks in SPSS. Step 1: For a nominal variable, the appropriate descriptive statistics are frequencies and percentages. From the “Analyze” menu, choose “Descriptive Statistics” and “Frequen-cies.” Move “Race/Ethnicity and Gender” over to the right. Click “OK.” 299Calculating Descriptive Statistics • EXERCISE 27Copyright © 2017, Elsevier Inc. All rights reserved. Step 2: For a continuous variable, the appropriate descriptive statistics are means and standard deviations. From the “Analyze” menu, choose “Descriptive Statistics” and “Explore.” Move “Duration” over to the right. Click “OK.” INTERPRETATION OF SPSS OUTPUT The following tables are generated from SPSS. The fi rst set of tables (from the fi rst set of SPSS commands in Step 1) contains the frequencies of race/ethnicity and gender. Most (70%) were Caucasian, and 100% were female. Frequencies Frequency Table RaceEthnicityFrequencyPercentValid PercentCumulative PercentValidBlack, not of Hispanic Origin330.030.030.0Caucasian770.070.0100.0Total10100.0100.0GenderFrequencyPercentValid PercentCumulative PercentValidF10100.0100.0100.0 300EXERCISE 27 • Calculating Descriptive StatisticsCopyright © 2017, Elsevier Inc. All rights reserved. DescriptivesStatisticStd. ErrorDuration of Biologic Use1.890.3860Lower Bound1.017Upper Bound2.7631.8721.7501.4901.2206.14.03.92.0.159.687-.4371.334Mean95% Confidence Interval for Mean 5% Trimmed MeanMedianVarianceStd. DeviationMinimumMaximumRangeInterquartile RangeSkewnessKurtosis The second set of output (from the second set of SPSS commands in Step 2) contains the descriptive statistics for “Duration,” including the mean, s (standard deviation), SE , 95% confi dence interval for the mean, median, variance, minimum value, maximum value, range, and skewness and kurtosis statistics. As shown in the output, mean number of years for duration is 1.89, and the SD is 1.22. The 95% CI is 1.02–2.76. Explore 301Calculating Descriptive Statistics • EXERCISE 27Copyright © 2017, Elsevier Inc. All rights reserved. STUDY QUESTIONS 1. Defi ne mean. 2. What does this symbol, s 2 , represent? 3. Defi ne outlier. 4. Are there any outliers among the values representing duration of biologic use? 5. How would you interpret the 95% confi dence interval for the mean of duration of biologic use? 6. What percentage of patients were Black, not of Hispanic origin? 7. Can you compute the variance for duration of biologic use by using the information presented in the SPSS output above?

Copyright © 2017, Elsevier Inc. All rights reserved. 305 Questions to Be Graded

 EXERCISE 27 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 “

Name: _______________________________________________________

Class: _____________________

 Date:_____________________

Questions to Be Graded.”

 1. What is the mean age of the sample data?

2. What percentage of patients never used tobacco?

3. What is the standard deviation for age?

4. Are there outliers among the values of age? Provide a rationale for your answer.

 5. What is the range of age values?

6. What percentage of patients were taking infl iximab?

7. What percentage of patients had rheumatoid arthritis as their primary diagnosis?

 8. What percentage of patients had irritable bowel syndrome as their primary diagnosis?

9. What is the 95% CI for age?

10. What percentage of patients had psoriatic arthritis as their primary diagnosis?

Copyright © 2017, Elsevier Inc. All rights reserved. 307 Calculating Pearson Product-Moment Correlation Coeffi cient Correlational analyses identify associations between two variables. There are many differ-ent kinds of statistics that yield a measure of correlation. All of these statistics address a research question or hypothesis that involves an association or relationship. Examples of research questions that are answered with correlation statistics are, “Is there an associa-tion between weight loss and depression?” and “Is there a relationship between patient satisfaction and health status?” A hypothesis is developed to identify the nature (positive or negative) of the relationship between the variables being studied. The Pearson product-moment correlation was the fi rst of the correlation measures developed and is the most commonly used. As is explained in Exercise 13 , this coeffi cient (statistic) is represented by the letter r , and the value of r is always between − 1.00 and + 1.00. A value of zero indicates no relationship between the two variables. A positive cor-relation indicates that higher values of x are associated with higher values of y . A negative or inverse correlation indicates that higher values of x are associated with lower values of y . The r value is indicative of the slope of the line (called a regression line) that can be drawn through a standard scatterplot of the two variables (see Exercise 11 ). The strengths of different relationships are identifi ed in Table 28-1 ( Cohen, 1988 ). EXERCISE 28 TABLE 28-1 STRENGTH OF ASSOCIATION FOR PEARSON r Strength of Association Positive Association Negative Association Weak association0.00 to < 0.300.00 to < − 0.30Moderate association0.30 to 0.49 − 0.49 to − 0.30Strong association0.50 or greater − 1.00 to − 0.50 RESEARCH DESIGNS APPROPRIATE FOR THE PEARSON r Research designs that may utilize the Pearson r include any associational design ( Gliner, Morgan, & Leech, 2009 ). The variables involved in the design are attributional, meaning the variables are characteristics of the participant, such as health status, blood pressure, gender, diagnosis, or ethnicity. Regardless of the nature of variables, the variables submit-ted to a Pearson correlation must be measured as continuous or at the interval or ratio level. STATISTICAL FORMULA AND ASSUMPTIONS Use of the Pearson correlation involves the following assumptions: 1. Interval or ratio measurement of both variables (e.g., age, income, blood pressure, cholesterol levels). However, if the variables are measured with a Likert scale, and the frequency distribution is approximately normally distributed, these data are