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1. The raw scores in the population are normally distributed.

2. The dependent variable(s) is(are) measured at the interval or ratio levels.

3. The two groups examined for differences have equal variance, which is best achieved by a random sample and random assignment to groups.

4. All scores or observations collected within each group are independent or not related to other study scores or observations.

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).

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?

6. 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?

7. 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.

8. 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.

9. 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?

10. 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.

1. An independent samples t-test was conducted to examine group differences in the dependent variables in this study. The two groups analyzed for differences were the Buzzy experimental or intervention group and the control group.

2. The level of significance or alpha (α) was set at 0.05.

3. The result was t = −6.065, p = 0.000 for procedural self-reported pain with the VAS (see Table 2). The t value is statistically significant as indicated by the p = 0.000, which is less than α = 0.05 set for this study. The t result means there is a significant difference between the Buzzy intervention group and the control group in terms of the procedural self-reported pain measured with the VAS. As a point of clarification, p values are never zero in a study. There is always some chance of error.

4. The null hypothesis is: There is no difference in observer-reported procedural anxiety levels between the Buzzy intervention and the control groups for school-age children. The t = −6.745 for observer-reported procedural anxiety levels, p = 0.000, which is less than α = 0.05 set for this study. Since this study result was statistically significant, the null hypothesis was rejected.

5. The t = −1.309 for BMI. The nonsignificant p = .192 for BMI is greater than α = 0.05 set for this study. The nonsignificant result means there is no statistically significant difference between the Buzzy intervention and control groups for BMI. The two groups need to be similar for demographic variables to decrease the potential for error and increase the likelihood that the results are an accurate reflection of reality.

6. The conduct of multiple t-tests causes an increased risk for Type I errors. If only one t-test is conducted on study data, the risk of Type I error does not increase. The Bonferroni procedure and the more stringent Tukey’s honestly significant difference (HSD), Student Newman-Keuls, or Scheffé test can be calculated to reduce the risk of a Type I error (Plichta & Kelvin, 2013; Zar, 2010).

7. The Bonferroni procedure is calculated by alpha ÷ number of t-tests conducted on study variables’ data. Note that researchers do not always report all t-tests conducted, especially if they were not statistically significant. The t-tests conducted on demographic data are not of concern. Canbulat et al. reported the results of four t-tests conducted to examine differences between the intervention and control groups for the dependent variables procedural self-reported pain with WBFS, procedural self-reported pain with VAS, parent-reported anxiety levels, and observer-reported anxiety levels. The Bonferroni calculation for this study: 0.05 (alpha) ÷ number of t-tests conducted = 0.05 ÷ 4 = 0.0125. The new α set for the study is 0.0125.

8. Based on the Bonferroni result = 0.0125 obtained in Question 7, the t = −6.745, p = 0.000, is still significant since it is less than 0.0125.