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Solution Manual for Statistics for Nursing Research A Workbook for Evidence-Based Practice 4th Edition Susan Grove Daisha 17,29 €   In den Einkaufswagen

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Solution Manual for Statistics for Nursing Research A Workbook for Evidence-Based Practice 4th Edition Susan Grove Daisha

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Solution Manual for Statistics for Nursing Research A Workbook for Evidence-Based Practice 4th Edition Susan Grove Daisha

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  • 13. september 2024
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  • Solution Manual For Statistics For Nursing, 4e
  • Solution Manual For Statistics For Nursing, 4e
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,Solution Manual for
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Statistics for Nursing
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Research A Workbook
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for Evidence-Based
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Practice 4th Edition
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SusanGrove Daisha
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,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
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rationale for your answer.
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Answer: The current therapy variable was measured at the nominal level. These drug categories
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were probably developed to be exhaustive for this study and included the categories of drugs the
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subjects were receiving. However, the categories are not exclusive, since patients are usually on
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more than one category of these drugs to manage their health problems. The current
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rtherapies are not measured at the ordinal level because they cannot be rank ordered, since no drug
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category can be considered more or less beneficial than another drug category (see Figure 1 -1; Grove
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r& Gray, 2019).
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2. What is the mode for the current therapy variable in this study? Provide a rationale for
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your answer.
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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 this
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sample.
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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
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resulted in ratio-level data with continuous values and an absolute zero (Stone & Frazier, 2017).
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rRatio - level data should be analyzed with parametric statistics such as the mean and SD (Grove &
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Gray, 2017; Knapp, 2017).
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4. Researchers used the following item to measure registered nurses’ (RNs) income in a study:
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What 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
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rules 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-
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ended

AG 1-1 r

, AG r1-2 Answer r Guidelines r for r Questions r to r Be r Graded


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
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either (d) or (e) or both categories, resulting in erroneous data. Category (e) could be
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rchanged to greater than $80,000, making the categories exclusive. The categories can be rank
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rordered from the lowest salary to the highest salary, which is consistent with ordinal data (Grove &
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Gray, 2019; Waltz 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-item Likert
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scale developed to measure depression in cardiac patients. Study participants rated their symp-
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toms on a scale of 1 to 7, with higher numbers indicating increased severity in the depression
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symptoms. The total scores for each subject obtained from this multi-item scale are
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rconsidered to be at the interval level of measurement (Gray et al., 2017; Waltz et al., 2017).
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6. Were nonparametric or parametric analysis techniques used to analyze the CDS scores for
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the 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
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study participants (see Table 1). CDS scores are interval-level data as indicated in Questions 5, so
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parametric statistics are appropriate for this level of data (Gray et al., 2017; Kim & Mallory, 2017).
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7. Is the prevalence of depression linked to the NYHA class? Discuss the clinical
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importance of this result.
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Answer: The study narrative indicated that the prevalence of depression increased with the
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greater NYHA class. In NYHA class III, 64% of the subjects were depressed, whereas 11% of the
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subjects were depressed in NYHA class I. Thus, as the NYHA class increased, the number of sub-
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jects with depression increased. This is an expected finding because as the NYHA class increases,
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cardiac patients have more severe physical symptoms, which usually result in emotional distress,
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such as depression. Nurses need to actively assess cardiac patients for depression, especially
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rthosein higher 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
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with an antidepressant? Show your calculations and round your answer to the nearest whole
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percent (%).
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Answer: A total of 106 cardiac patients participated in this study. The sample included 15
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patients who were receiving an antidepressant (see Table 1). The number of cardiac patients
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not treated for depression was 91 (106 – 15 = 91). The group percent is calculatedby the
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following formula: (group frequency ÷ total sample size) × 100%. For this study,(91
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patients ÷ 106 sample size) × 100% = 0.858 × 100% = 85.8% = 86%. The finalanswer is
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rounded to the nearest whole percent as directed in the question. You could havealso
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subtracted the 14% of patients treated with antidepressants from 100% and obtained the 86%
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who were not treated with an antidepressant.
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9. What was the purpose of the 6-minute walk test (6MWT)? Would the 6MWT be useful in
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clinical practice?
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Answer: Ha et al. (2018) stated, “The 6-min walk test (6MWT) is a measure of the submaximal,
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steady-state functional capacity” of cardiac patients. This test would be a quick, easy way to
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determine a cardiac patient’s functional status in a clinical setting. This functional statusscore
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could be used to determine the treatment plan to promote or maintain functional statusof
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cardiac patients.
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