Solution Manual for
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Statistics for Nursing Rp p p
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EXERCISE
Identifying Levels of p p p
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Measurement: Nominal, Or
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1
The questions are in bold followed by answers.
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1. In Table 1, identify the level of measurement for the current therapy variable. Provide a rat
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ionale for your answer. p p p
Answer: The current therapy variable was measured at the nominal level. These drug categoriesw
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ere probably developed to be exhaustive for this study and included the categories of drugs thesubj
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ects were receiving. However, the categories are not exclusive, since patients are usually on more t
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han one category of these drugs to manage their health problems. The current therapies are not me
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asured at the ordinal level because they cannot be rank ordered, since no drug category can be consi
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dered more or less beneficial than another drug category (see Figure 1-1; Grove & Gray, 2019).
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2. What is the mode for the current therapy variable in this study? Provide a rationale fory
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our answer. p
Answer: The mode for current therapy was β blocker. A total of 100 (94%) of the cardiac patients
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were receiving this category of drug, which was the most common prescribed drug for thissa
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mple.
3. What statistics were conducted to describe the BMI of the cardiac patients in this sample?
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Discuss whether these analysis techniques were appropriate or inappropriate.
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Answer: BMI was described with a mean and standard deviation (SD). BMI measurement resulted in
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ratio-level data with continuous values and an absolute zero (Stone & Frazier, 2017). Ratio-
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plevel data should be analyzed with parametric statistics such as the mean and SD (Grove & Gray,20
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17; Knapp, 2017).
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4. Researchers used the following item to measure registered nurses’ (RNs) income in a study:W
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hat category identifies your current income as an RN?
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a. Less than $50,000
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b. $50,000 to 59,999
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c. $60,000 to 69,999
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d. $70,000 to 80,000
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e. $80,000 or greater
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What level of measurement is this income variable? Does the income variable follow the r
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ules outlined in Figure 1-1? Provide a rationale for your answer.
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Answer: In this example, the income variable is measured at the ordinal level. The income catego-
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ries are exhaustive, ranging from less than $50,000 to greater than $80,000. The two open-ended
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categories ensure that all salary levels are covered. The categories are not exclusive, since catego-
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ries (d) and (e) include an $80,000 salary, so study participants making $80,000 might mark either
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p(d) or (e) or both categories, resulting in erroneous data. Category (e) could be changedto great
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er than $80,000, making the categories exclusive. The categories can be rank ordered from the lo
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west salary to the highest salary, which is consistent with ordinal data (Grove & Gray, 2019; Walt
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z et al., 2017).
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5. What level of measurement is the CDS score? Provide a rationale for your answer.
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Answer: The CDS score is at the interval level of measurement. The CDS is a 26-
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item Likert scale developed to measure depression in cardiac patients. Study participants rated the
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ir symp-p
ptoms on a scale of 1 to 7, with higher numbers indicating increased severity in the depression sym
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ptoms. The total scores for each subject obtained from this multi-
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item scale are considered to be at the interval level of measurement (Gray et al., 2017; Waltz et al.,
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2017).
6. Were nonparametric or parametric analysis techniques used to analyze the CDS scores fort
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he cardiac patients in this study? Provide a rationale for your answer.
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Answer: Parametric statistics, such as mean and SD, were conducted to describe CDS scoresfor s
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tudy participants (see Table 1). CDS scores are interval-
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level data as indicated in Questions 5, so parametric statistics are appropriate for this level of data (Gra
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y et al., 2017; Kim & Mallory, 2017).
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7. Is the prevalence of depression linked to the NYHA class? Discuss the clinical importance o
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f this result.
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Answer: The study narrative indicated that the prevalence of depression increased with the greate
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r NYHA class. In NYHA class III, 64% of the subjects were depressed, whereas 11% of thesubjects
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were depressed in NYHA class I. Thus, as the NYHA class increased, the number of sub-
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pjects with depression increased. This is an expected finding because as the NYHA class increases, car
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diac patients have more severe physical symptoms, which usually result in emotional distress, such
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as depression. Nurses need to actively assess cardiac patients for depression, especially thosein high
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er NYHA classes, so they might be diagnosed and treated as needed.
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8. What frequency and percent of cardiac patients in this study were not being treated with a
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n antidepressant? Show your calculations and round your answer to the nearest whole perc
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ent (%). p
Answer: A total of 106 cardiac patients participated in this study. The sample included 15 pat
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ients who were receiving an antidepressant (see Table 1). The number of cardiac patients not tre
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ated for depression was 91 (106 –
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p15 = 91). The group percent is calculatedby the following formula: (group frequency ÷ tota
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l sample size) × 100%. For this study,(91 patients ÷ 106 sample size) × 100% = 0.858 × 100
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% = 85.8% = 86%. The finalanswer is rounded to the nearest whole percent as directed in the
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pquestion. You could havealso subtracted the 14% of patients treated with antidepressants from 1
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00% and obtained the 86% who were not treated with an antidepressant.
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9. What was the purpose of the 6- p p p p p p
minute walk test (6MWT)? Would the 6MWT be useful in clinical practice?
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Answer: Ha et al. (2018) stated, ―The 6- p p p p p p p
min walk test (6MWT) is a measure of the submaximal,steady-
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state functional capacity‖ of cardiac patients. This test would be a quick, easy way to determine a
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cardiac patient’s functional status in a clinical setting. This functional statusscore could be use
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d to determine the treatment plan to promote or maintain functional statusof cardiac patients.
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10. How was exercise confidence measured in this study? What was the level of measurementf
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or the exercise confidence variable in this study? Provide a rationale for your answer. Ans
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wer: Exercise confidence of the patients with heart failure (HF) in this study was measuredwith t
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he Exercise Confidence Scale that included four subscales focused on walking, climbing,lifting
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objects of graded weight, and running (see the study narrative). This was a rating scalewith valu
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es ranging from 0 to 100. The patients’ scores for the Total Exercise Confidence scaleand the sub
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scales were considered interval-
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level data and analyzed with parametric statistics,such as means and SDs (see the study narrative
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; Waltz et al., 2017).
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