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Solution Manual for Statistics for Nursing Research A Workbook for Evidence-Based Practice, 3rd Edition, Susan Grove, Daisha Cipher $24.49   Add to cart

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Solution Manual for Statistics for Nursing Research A
Workbook for Evidence-Based Practice, 3rd Edition,
Susan Grove, Daisha Cipher

,Solution Manual for
Statistics for Nursing
Research A Workbook
for Evidence-Based
Practice 3rd Edition
Susan Grove Daisha

,Answer Guidelines for Questions to Be Graded
Identifying Levels of Measurement: Nominal,
Ordinal, Interval, EXERCISE
and Ratio

1

The questions are in bold followed by answers.

1. In Table 1, identify the level of measurement for the current therapy variable. Provide a
rationale for your answer.
Answer: The current therapy variable was measured at the nominal level. These drug categories
were probably developed to be exhaustive for this study and included the categories of drugs
the subjects were receiving. However, the categories are not exclusive, since patients are
usually on more than one category of these drugs to manage their health problems. The current
therapies are not measured at the ordinal level because they cannot be rank ordered, since no
drug category can be considered more or less beneficial than another drug category (see Figure
1-1; Grove & Gray, 2019).

2. What is the mode for the current therapy variable in this study? Provide a rationale for
your answer.
Answer: The mode for current therapy was β blocker. A total of 100 (94%) of the cardiac patients
were receiving this category of drug, which was the most common prescribed drug for this
sample.

3. What statistics were conducted to describe the BMI of the cardiac patients in this
sample? Discuss whether these analysis techniques were appropriate or inappropriate.
Answer: BMI was described with a mean and standard deviation (SD). BMI measurement resulted
in ratio-level data with continuous values and an absolute zero (Stone & Frazier, 2017). Ratio-
level data should be analyzed with parametric statistics such as the mean and SD (Grove &
Gray, 2017; Knapp, 2017).

4. Researchers used the following item to measure registered nurses’ (RNs) income in a
study: What category identifies your current income as an RN?
a. Less than $50,000
b. $50,000 to 59,999
c. $60,000 to 69,999
d. $70,000 to 80,000
e. $80,000 or greater

What level of measurement is this income variable? Does the income variable follow the
rules outlined in Figure 1-1? Provide a rationale for your answer.
Answer: In this example, the income variable is measured at the ordinal level. The income catego-
ries are exhaustive, ranging from less than $50,000 to greater than $80,000. The two open-
ended

AG 1-1

, AG 1-2 Answer Guidelines for Questions to Be Graded


categories ensure that all salary levels are covered. The categories are not exclusive, since
catego- ries (d) and (e) include an $80,000 salary, so study participants making $80,000 might
mark either (d) or (e) or both categories, resulting in erroneous data. Category (e) could be
changed to greater than $80,000, making the categories exclusive. The categories can be rank
ordered from the lowest salary to the highest salary, which is consistent with ordinal data
(Grove & Gray, 2019; Waltz et al., 2017).

5. What level of measurement is the CDS score? Provide a rationale for your answer.
Answer: The CDS score is at the interval level of measurement. The CDS is a 26-item Likert
scale developed to measure depression in cardiac patients. Study participants rated their symp-
toms on a scale of 1 to 7, with higher numbers indicating increased severity in the depression
symptoms. The total scores for each subject obtained from this multi-item scale are considered
to be at the interval level of measurement (Gray et al., 2017; Waltz et al., 2017).

6. Were nonparametric or parametric analysis techniques used to analyze the CDS scores
for the cardiac patients in this study? Provide a rationale for your answer.
Answer: Parametric statistics, such as mean and SD, were conducted to describe CDS scores
for study participants (see Table 1). CDS scores are interval-level data as indicated in Questions 5,
so parametric statistics are appropriate for this level of data (Gray et al., 2017; Kim & Mallory,
2017).

7. Is the prevalence of depression linked to the NYHA class? Discuss the clinical importance
of this result.
Answer: The study narrative indicated that the prevalence of depression increased with the
greater NYHA class. In NYHA class III, 64% of the subjects were depressed, whereas 11% of
the subjects were depressed in NYHA class I. Thus, as the NYHA class increased, the number of
sub- jects with depression increased. This is an expected finding because as the NYHA class
increases, cardiac patients have more severe physical symptoms, which usually result in
emotional distress, such as depression. Nurses need to actively assess cardiac patients for
depression, especially those in higher NYHA classes, so they might be diagnosed and treated as
needed.

8. What frequency and percent of cardiac patients in this study were not being treated with
an antidepressant? Show your calculations and round your answer to the nearest whole
percent (%).
Answer: A total of 106 cardiac patients participated in this study. The sample included
15 patients who were receiving an antidepressant (see Table 1). The number of cardiac
patients not treated for depression was 91 (106 – 15 = 91). The group percent is calculated
by the following formula: (group frequency ÷ total sample size) × 100%. For this study,
(91 patients ÷ 106 sample size) × 100% = 0.858 × 100% = 85.8% = 86%. The final
answer is rounded to the nearest whole percent as directed in the question. You could have
also subtracted the 14% of patients treated with antidepressants from 100% and obtained the
86% who were not treated with an antidepressant.

9. What was the purpose of the 6-minute walk test (6MWT)? Would the 6MWT be useful in
clinical practice?
Answer: Ha et al. (2018) stated, “The 6-min walk test (6MWT) is a measure of the
submaximal, steady-state functional capacity” of cardiac patients. This test would be a quick,
easy way to determine a cardiac patient’s functional status in a clinical setting. This
functional status score could be used to determine the treatment plan to promote or maintain
functional status of cardiac patients.

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