NR 439 Week 6: Data Results and Analysis

NR 439 Week 6: Data Results and Analysis

NR 439 Week 6: Data Results and Analysis

After the data are collected, it is time to analyze the results!

1. Discuss one of the four basic rules for understanding results in a research study.
1. Compare clinical significance and statistical significance. Which one is more meaningful when considering applying evidence to your practice?
1. Compare descriptive statistics and inferential statistics in research. Please give an example of each type that could be collected in a study that would be done on your nursing clinical issue you identified in previous weeks.

Class this week we are going to review the data collected. Our discussion will review the following course outcomes.

CO2: Apply research principles to the interpretation of the content of published research studies. (PO: 4, 8)

CO4: Evaluate published nursing research for credibility and clinical significance related to evidence-based practice. (PO: 4, 8)

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After the data are collected, it is time to analyze the results!

Discuss one of the four basic rules for understanding results in a research study.
Compare clinical significance and statistical significance. Which one is more meaningful when considering applying evidence to your practice?
Compare descriptive statistics and inferential statistics in research. Please give an example of each type that could be collected in a study that would be done on your nursing clinical issue you identified in previous weeks.

According to this week’s lesson, the four basic rules for understanding results in a research study are understand the purpose of the study, identify the variables—dependent and independent, identify how the variables are measured, and look at the measures of central tendency and the measures of variability for the study variables. I chose to explore the rule: identify the variables-dependent and independent. A dependent variable is something that depends on other factors.

An independent variable is a variable that stands alone and isn’t changed by the other variables you are trying to measure. A dependent factor can be changed by what happens with the independent factor but a dependent factor can never change an independent factor. A simple example would be: Insulin causes a drop in blood sugar. Insulin is the independent factor and blood sugar is the dependent factor. There is no way for blood sugar to cause a drop in insulin.

“Statistical significance tells us the findings are real; clinical significance tells us if the results are important for practice” (Houser, 2018, p. 356). Both statistical significance and clinical significance relate to quantitative data. Statistical significance could mean that in 0.5% of the population x, y, and z occurred. The probability of it happening could be chance because it is such a small percentage of the population. Clinical significance shows to what degree the new intervention is needed to make a difference in a client’s life. Clinical significance is thought to be much more meaningful but without the initial statistical significance, further studies would not have been done to prove a clinical significance. In reference to practice, clinical significance is more important when applying evidence to my practice. When utilizing clinical significance, there is evidence-based support of your actions.

“The goal of statistical inference is to estimate likely true or large-sample effects based on random samples from the collective(s) of interest” (Wilkinson & Winter, 2014, p. 492). In a study, the variances between groups are measured quantitatively and examined using inferential statistics. Inferential statistics utilize numbers to determine the probability that random error plays a role in the outcome. It also suggests that independent variables have an effect on the results.

Descriptive statistics are usually related to the mean, minimum, maximum, standard deviation, and median of results. These studies are not usually utilized for change in evidence-based practice but are more likely to be used to measure current practice. An example of inferential statistics would be if I questioned all of the Emergency Department nurses at my facility about the effects of education on compassion fatigue. The results would infer that the results would be the same in another location but I only used a small population. For the descriptive statistics, I would use a table, graph, or chart in addition to the statistical data to summarize my study.

References:

Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.

Wilkinson, M., & Winter, E.M. (2014). Clinical and practical importance vs statistical significance: Limitations of conventional statistical inference. International Journal of Therapy & Rehabilitation, 21(10), 488-495.

What are the variables in your clinical issue study? Many sources are now calling clinical significance, practical significance. I think that change in terminology makes it easier to understand. Descriptive statistics were found in the RRL assignments when they asked for demographics.
Chamberlain College of Nursing (CCN). (2017). NR-439- Week 6 Lecture: Reading Research Literature –
The Research Process [Online lesson]. Downers Grove, IL: DeVry Education Group

Dependent variables “are expected to change as a result of an experimental manipulation of the independent variable or variables. It is the presumed effect” (Research Guides, n.d). The dependent variable for my clinical issue is compassion fatigue education perception. Half of my population will be given education. The other half will be my control group. An independent variable is a variable that doesn’t change during the study. Independent variables for my study will be age, gender, and ethnicity.

Reference:

Research Guides: Organizing Your Social Sciences Research Paper: Independent and Dependent Variables. (n.d.). Retrieved August 09, 2017, from http://libguides. usc.edu/writingguide/variablesLinks to an external site..

I liked the insight into the variables with the independent and dependent examples you gave. You also gave me a new understanding to statistical and clinical significance. I am still a little fuzz on them both but your input made it a little clearer for me. Also you insight into descriptive, and inferential statistics was very good. Thank you for helping a fellow student have clearer understanding of the topic this week.

For one independent variable, there may be more than one dependent variable. On the contrary, for more than one dependent variable, there is always one independent variable. The value of independent variable is changeable, while we cannot change the value of dependent variable. The independent variable is controllable, while we cannot control the value of dependent variable (Petter, DeLone, & McLean, 2013). Dependent variable depends upon independent variable, as when independent variable will change, there must be a change in the value of dependent variable. On the other hand, there is no impact of dependent variable upon independent variable. The value of independent variable is that which is manipulated in an experiment, while dependent variable is that value, which is observed by the researcher in an experiment

Petter, S., DeLone, W., & McLean, E. R. (2013). Information systems success: The quest for the independent variables. Journal of Management Information Systems, 29(4), 7-62.