Case Study 1:
Patient AO has a history of obesity and has recently gained 9 pounds. The patient has been diagnosed with hypertension and hyperlipidemia. Drugs currently prescribed include the following:

Atenolol 12.5 mg daily
Doxazosin 8 mg daily
Hydralazine 10 mg qid
Sertraline 25 mg daily
Simvastatin 80 mg daily
Case Study 2:
Patient HM has a history of atrial fibrillation and a transient ischemic attack (TIA). The patient has been diagnosed with type 2 diabetes, hypertension, hyperlipidemia and ischemic heart disease. Drugs currently prescribed include the following:

Warfarin 5 mg daily MWF and 2.5 mg daily T, TH, Sat, Sun
Aspirin 81 mg daily
Metformin 1000 mg po bid
Glyburide 10 mg bid
Atenolol 100 mg po daily
Motrin 200 mg 1–3 tablets every 6 hours as needed for pain
Case Study 3:
Patient CB has a history of strokes. The patient has been diagnosed with type 2 diabetes, hypertension, and hyperlipidemia. Drugs currently prescribed include the following:

Glipizide 10 mg po daily
HCTZ 25 mg daily
Atenolol 25 mg po daily
Hydralazine 25 mg qid
Simvastatin 80 mg daily
Verapamil 180 mg CD daily
To prepare:
Review this week’s media presentation on hypertension and hyperlipidemia, as well as Chapters 19 and 20 of the Arcangelo and Peterson text.
Select one of the three case studies, as well as one the following factors: genetics, gender, ethnicity, age, or behavior factors.
Reflect on how the factor you selected might influence the patient’s pharmacokinetic and pharmacodynamic processes.
Consider how changes in the pharmacokinetic and pharmacodynamic processes might impact the patient’s recommended drug therapy.
Think about how you might improve the patient’s drug therapy plan based on the pharmacokinetic and pharmacodynamic changes. Reflect on whether you would modify the current drug treatment or provide an alternative treatment option for the patient.
With these thoughts in mind:

By Day 3

Post an explanation of how the factor you selected might influence the pharmacokinetic and pharmacodynamic processes in the patient from the case study you selected. Then, describe how changes in the processes might impact the patient’s recommended drug therapy. Finally, explain how you might improve the patient’s drug therapy plan.

As the country focuses on the restructuring of the U.S. health care delivery system, nurses will continue to play an important role. It is expected that more and more nursing jobs will become available out in the community, and fewer will be available in acute care hospitals.

Write an informal presentation (500-700 words) to educate nurses about how the practice of nursing is expected to grow and change. Include the concepts of continuity or continuum of care, accountable care organizations (ACO), medical homes, and nurse-managed health clinics.

Share your presentation with nurse colleagues on your unit or department and ask them to offer their impressions of the anticipated changes to health care delivery and the new role of nurses in hospital settings, communities, clinics, and medical homes.

In 800-1,000 words summarize the feedback shared by three nurse colleagues and discuss whether their impressions are consistent with what you have researched about health reform.

A minimum of three scholarly references are required for this assignment.

rubrics

Clearly States How the Practice of Nursing and Patient Delivery Will Evolve, While Addressing Relevant Concepts That Include Continuity or Continuum of Care, Accountable Care Organizations, Medical Homes, and Nurse-Managed Health Clinics

Evidence of Feedback and Forecasting of Nursing Role From Colleagues

The independent samples t-test is a parametric statistical technique used to determine significant differences between the scores obtained from two samples or groups. Since the t-test is considered fairly easy to calculate, researchers often use it in determining differences between two groups. The t-test examines the differences between the means of the two groups in a study and adjusts that difference for the variability (computed by the standard error) among the data. When interpreting the results of t-tests, the larger the calculated t ratio, in absolute value, the greater the difference between the two groups. The significance of a t ratio can be determined by comparison with the critical values in a statistical table for the t distribution using the degrees of freedom (df) for the study (see Appendix A Critical Values for Student’s t Distribution at the back of this text). The formula for df for an independent t-test is as follows:

df=(numberofsubjectsinsample1+numberofsubjectsinsample2)−2

image
Exampledf=(65insample1+67insample2)−2=132−2=130

image
The t-test should be conducted only once to examine differences between two groups in a study, because conducting multiple t-tests on study data can result in an inflated Type 1 error rate. A Type I error occurs when the researcher rejects the null hypothesis when it is in actuality true. Researchers need to consider other statistical analysis options for their study data rather than conducting multiple t-tests. However, if multiple t-tests are conducted, researchers can perform a Bonferroni procedure or more conservative post hoc tests like Tukey’s honestly significant difference (HSD), Student-Newman-Keuls, or Scheffé test to reduce the risk of a Type I error. Only the Bonferroni procedure is covered in this text; details about the other, more stringent post hoc tests can be found in Plichta and Kelvin (2013) and Zar (2010).

The Bonferroni procedure is a simple calculation in which the alpha is divided by the number of t-tests conducted on different aspects of the study data. The resulting number is used as the alpha or level of significance for each of the t-tests conducted. The Bonferroni procedure formula is as follows: alpha (α) ÷ number of t-tests performed on study data = more stringent study α to determine the significance of study results. For example, if a study’s α was set at 0.05 and the researcher planned on conducting five t-tests on the study data, the α would be divided by the five t-tests (0.05 ÷ 5 = 0.01), with a resulting α of 0.01 to be used to determine significant differences in the study.

The t-test for independent samples or groups includes the following assumptions:

1. The raw scores in the population are normally distributed.
2. The dependent variable(s) is(are) measured at the interval or ratio levels.

162

1. The two groups examined for differences have equal variance, which is best achieved by a random sample and random assignment to groups.
2. All scores or observations collected within each group are independent or not related to other study scores or observations.

The t-test is robust, meaning the results are reliable even if one of the assumptions has been violated. However, the t-test is not robust regarding between-samples or within-samples independence assumptions or with respect to extreme violation of the assumption of normality. Groups do not need to be of equal sizes but rather of equal variance. Groups are independent if the two sets of data were not taken from the same subjects and if the scores are not related (Grove, Burns, & Gray, 2013; Plichta & Kelvin, 2013). This exercise focuses on interpreting and critically appraising the t-tests results presented in research reports. Exercise 31 provides a step-by-step process for calculating the independent samples t-test.

Research Article
Source
Canbulat, N., Ayhan, F., & Inal, S. (2015). Effectiveness of external cold and vibration for procedural pain relief during peripheral intravenous cannulation in pediatric patients. Pain Management Nursing, 16(1), 33–39.

Introduction
Canbulat and colleagues (2015, p. 33) conducted an experimental study to determine the “effects of external cold and vibration stimulation via Buzzy on the pain and anxiety levels of children during peripheral intravenous (IV) cannulation.” Buzzy is an 8 × 5 × 2.5 cm battery-operated device for delivering external cold and vibration, which resembles a bee in shape and coloring and has a smiling face. A total of 176 children between the ages of 7 and 12 years who had never had an IV insertion before were recruited and randomly assigned into the equally sized intervention and control groups. During IV insertion, “the control group received no treatment. The intervention group received external cold and vibration stimulation via Buzzy . . . Buzzy was administered about 5 cm above the application area just before the procedure, and the vibration continued until the end of the procedure” (Canbulat et al., 2015, p. 36). Canbulat et al. (2015, pp. 37–38) concluded that “the application of external cold and vibration stimulation were effective in relieving pain and anxiety in children during peripheral IV” insertion and were “quick-acting and effective nonpharmacological measures for pain reduction.” The researchers concluded that the Buzzy intervention is inexpensive and can be easily implemented in clinical practice with a pediatric population.

Relevant Study Results
The level of significance for this study was set at α = 0.05. “There were no differences between the two groups in terms of age, sex [gender], BMI, and preprocedural anxiety according to the self, the parents’, and the observer’s reports (p > 0.05) (Table 1). When the pain and anxiety levels were compared with an independent samples t test, . . . the children in the external cold and vibration stimulation [intervention] group had significantly lower pain levels than the control group according to their self-reports (both WBFC [Wong Baker Faces Scale] and VAS [visual analog scale] scores; p < 0.001) (Table 2). The external cold and vibration stimulation group had significantly lower fear and anxiety 163levels than the control group, according to parents’ and the observer’s reports (p < 0.001) (Table 3)” (Canbulat et al., 2015, p. 36).

TABLE 1

COMPARISON OF GROUPS IN TERMS OF VARIABLES THAT MAY AFFECT PROCEDURAL PAIN AND ANXIETY LEVELS

Characteristic Buzzy (n = 88) Control (n = 88) χ2
p
Sex
Female (%), n 11 (12.5) 13 (14.8) .82
Male (%), n 77 (87.5) 75 (85.2) .41
Characteristic Buzzy (n = 88) Control (n = 88) t
p
Age (mean ± SD) 8.25 ± 1.51 8.61 ± 1.69 −1.498
.136
BMI (mean ± SD) 25.41 ± 6.74 26.94 ± 8.68 −1.309
.192
Preprocedural anxiety
Self-report (mean ± SD) 2.03 ± 1.29 2.11 ± 1.58 −0.364
.716
Parent report (mean ± SD) 2.11 ± 1.20 2.17 ± 1.42 −0.285
.776
Observer report (mean ± SD) 2.18 ± 1.17 2.24 ± 1.37 −0.295
.768
image

BMI, body mass index.

Canbulat, N., Ayban, F., & Inal, S. (2015). Effectiveness of external cold and vibration for procedural pain relief during peripheral intravenous cannulation in pediatric patients. Pain Management Nursing, 16(1), p. 36.

TABLE 2

COMPARISON OF GROUPS’ PROCEDURAL PAIN LEVELS DURING PERIPHERAL IV CANNULATION

 Buzzy (n = 88)  Control (n = 88)    t

p
Procedural self-reported pain with WBFS (mean ± SD) 2.75 ± 2.68 5.70 ± 3.31 −6.498
0.000
Procedural self-reported pain with VAS (mean ± SD) 1.66 ± 1.95 4.09 ± 3.21 −6.065
0.000
image

IV, intravenous; WBFS, Wong-Baker Faces Scale; SD, standard deviation; VAS, visual analog scale.

Canbulat, N., Ayban, F., & Inal, S. (2015). Effectiveness of external cold and vibration for procedural pain relief during peripheral intravenous cannulation in pediatric patients. Pain Management Nursing, 16(1), p. 37.

TABLE 3

COMPARISON OF GROUPS’ PROCEDURAL ANXIETY LEVELS DURING PERIPHERAL IV CANNULATION

Procedural Child Anxiety Buzzy (n = 88) Control (n = 88) t
p
Parent reported (mean ± SD) 0.94 ± 1.06 2.09 ± 1.39 −6.135
0.000
Observer reported (mean ± SD) 0.92 ± 1.03 2.14 ± 1.34 −6.745
0.000
image

SD, standard deviation; IV, intravenous.

Canbulat, N., Ayban, F., & Inal, S. (2015). Effectiveness of external cold and vibration for procedural pain relief during peripheral intravenous cannulation in pediatric patients. Pain Management Nursing, 16(1), p. 37.

164
Study Questions

1. What type of statistical test was conducted by Canbulat et al. (2015) to examine group differences in the dependent variables of procedural pain and anxiety levels in this study? What two groups were analyzed for differences?
2. What did Canbulat et al. (2015) set the level of significance, or alpha (α), at for this study?
3. What are the t and p (probability) values for procedural self-reported pain measured with a visual analog scale (VAS)? What do these results mean?
4. What is the null hypothesis for observer-reported procedural anxiety for the two groups? Was this null hypothesis accepted or rejected in this study? Provide a rationale for your answer.
5. What is the t-test result for BMI? Is this result statistically significant? Provide a rationale for your answer. What does this result mean for the study?

165

1. What causes an increased risk for Type I errors when t-tests are conducted in a study? How might researchers reduce the increased risk for a Type I error in a study?
2. Assuming that the t-tests presented in Table 2 and Table 3 are all the t-tests performed by Canbulat et al. (2015) to analyze the dependent variables’ data, calculate a Bonferroni procedure for this study.
3. Would the t-test for observer-reported procedural anxiety be significant based on the more stringent α calculated using the Bonferroni procedure in question 7? Provide a rationale for your answer.
4. The results in Table 1 indicate that the Buzzy intervention group and the control group were not significantly different for gender, age, body mass index (BMI), or preprocedural anxiety (as measured by self-report, parent report, or observer report). What do these results indicate about the equivalence of the intervention and control groups at the beginning of the study? Why are these results important?
5. Canbulat et al. (2015) conducted the χ2 test to analyze the difference in sex or gender between the Buzzy intervention group and the control group. Would an independent samples t-test be appropriate to analyze the gender data in this study (review algorithm in Exercise 12)? Provide a rationale for your answer.

The paired or dependent samples t-test is a parametric statistical procedure calculated to determine differences between two sets of repeated measures data from one group of people. The scores used in the analysis might be obtained from the same subjects under different conditions, such as the one group pretest–posttest design. With this type of design, a single group of subjects experiences the pretest, treatment, and posttest. Subjects are referred to as serving as their own control during the pretest, which is then compared with the posttest scores following the treatment. Paired scores also result from a one-group repeated measures design, where one group of participants is exposed to different levels of an intervention. For example, one group of participants might be exposed to two different doses of a medication and the outcomes for each participant for each dose of medication are measured, resulting in paired scores. The one group design is considered a weak quasi-experimental design because it is difficult to determine the effects of a treatment without a comparison to a separate control group (Shadish, Cook, & Campbell, 2002).

A less common type of paired groups is when the groups are matched as part of the design to ensure similarities between the two groups and thus reduce the effect of extraneous variables (Grove, Burns, & Gray, 2013; Shadish et al., 2002). For example, two groups might be matched on demographic variables such as gender, age, and severity of illness to reduce the extraneous effects of these variables on the study results. The assumptions for the paired samples t-test are as follows:

1. The distribution of scores is normal or approximately normal.
2. The dependent variable(s) is(are) measured at interval or ratio levels.
3. Repeated measures data are collected from one group of subjects, resulting in paired scores.
4. The differences between the paired scores are independent.

Research Article
Source
Lindseth, G. N., Coolahan, S. E., Petros, T. V., & Lindseth, P. D. (2014). Neurobehavioral effects of aspartame consumption. Research in Nursing & Health, 37(3), 185–193.

Introduction
Despite the widespread use of the artificial sweetener aspartame in drinks and food, there are concern and controversy about the mixed research evidence on its neurobehavioral 172effects. Thus Lindseth and colleagues (2014) conducted a one-group repeated measures design to determine the neurobehavioral effects of consuming both low- and high-aspartame diets in a sample of 28 college students. “The participants served as their own controls. . . . A random assignment of the diets was used to avoid an error of variance for possible systematic effects of order” (Lindseth et al., 2014, p. 187). “Healthy adults who consumed a study-prepared high-aspartame diet (25 mg/kg body weight/day) for 8 days and a low-aspartame diet (10 mg/kg body weight/day) for 8 days, with a 2-week washout between the diets, were examined for within-subject differences in cognition, depression, mood, and headache. Measures included weight of foods consumed containing aspartame, mood and depression scales, and cognitive tests for working memory and spatial orientation. When consuming high-aspartame diets, participants had more irritable mood, exhibited more depression, and performed worse on spatial orientation tests. Aspartame consumption did not influence working memory. Given that the higher intake level tested here was well below the maximum acceptable daily intake level of 40–50 mg/kg body weight/day, careful consideration is warranted when consuming food products that may affect neurobehavioral health” (Lindseth et al., 2014, p. 185).

Relevant Study Results
“The mean age of the study participants was 20.8 years (SD = 2.5). The average number of years of education was 13.4 (SD = 1.0), and the mean body mass index was 24.1 (SD = 3.5). . . . Based on Vandenberg MRT scores, spatial orientation scores were significantly better for participants after their low-aspartame intake period than after their high intake period (Table 2). Two participants had clinically significant cognitive impairment after consuming high-aspartame diets. . . . Participants were significantly more depressed after they consumed the high-aspartame diet compared to when they consumed the low-aspartame diet (Table 2). . . . Only one participant reported a headache; no difference in headache incidence between high- and low-aspartame intake periods could be established” (Lindseth et al., 2014, p. 190).

TABLE 2

WITHIN-SUBJECT DIFFERENCES IN NEUROBEHAVIOR SCORES AFTER HIGH AND LOW ASPARTAME INTAKE (N = 28)

Variable M SD Paired t-Test p
Spatial orientation
High-aspartame 14.1 4.2 2.4 .03*
Low-aspartame 16.6 4.3
Working memory
High-aspartame 730.0 152.7 1.5 N.S.
Low-aspartame 761.1 201.6
Mood (irritability)
High-aspartame 33.4 9.0 3.4 .002**
Low-aspartame 30.5 7.3
Depression
High-aspartame 36.8 7.0 3.8 .001**
Low-aspartame 34.4 6.2
image

*p < .05.

**p < .01.

M = Mean; SD = Standard deviation; N.S. = Nonsignificant.

Lindseth, G. N., Coolahan, S. E., Petros, T. V., & Lindseth, P. D. (2014). Neurobehavioral effects of aspartame consumption. Research in Nursing & Health, 37(3), p. 190

173
Study Questions

1. Are independent or dependent (paired) scores examined in this study? Provide a rationale for your answer.
2. What independent (intervention) and dependent (outcome) variables were included in this study?
3. What inferential statistical technique was calculated to examine differences in the participants when they received the high-aspartame diet intervention versus the low-aspartame diet? Is this technique appropriate? Provide a rationale for your answer.
4. What statistical techniques were calculated to describe spatial orientation for the participants consuming low- and high-aspartame diets? Were these techniques appropriate? Provide a rationale for your answer.
5. What was the dispersion of the scores for spatial orientation for the high- and low-aspartame diets? Is the dispersion of these scores similar or different? Provide a rationale for your answer.
6. What is the paired t-test value for spatial orientation between the participants’ consumption of high- and low-aspartame diets? Are these results significant? Provide a rationale for your answer.

174

1. State the null hypothesis for spatial orientation for this study. Was this hypothesis accepted or rejected? Provide a rationale for your answer.
2. Discuss the meaning of the results regarding spatial orientation for this study. What is the clinical importance of this result? Document your answer.
3. Was there a significant difference in the participants’ reported headaches between the high- and low-aspartame intake periods? What does the result indicate?
4. What additional research is needed to determine the neurobehavioral effects of aspartame consumption?