In this TD we will discuss why confidence intervals are important and differentiate between statistical and clinical significance. If you recall in the research study a sample is a representation of the whole population. For example if we conduct a study involving patients with hypertension, it would be impossible for all patients with hypertension to be in the study, therefore we hope that our sample (N=1000) is representative of all hypertensive patients, and our sample statistics approximate to the population. Confidence intervals are a range of values (mean blood pressures) that a researcher believes with a certain level of confidence, contains the actual population mean blood pressure. Why are confidence intervals useful in helping to determine clinical significance?

Pure statisticians will say that only statistical significance has value. How is clinical significance different and what are your thoughts to its value in nursing? Why is the issue of statistical significance versus clinical significance controversial? Can something be clinically significant even if it is not statistically significant? Can something be statistically significant but not clinically significant? How does this relate to implementation of EBP?

As you reflect on these questions I came across two articles on this topic that you may consider helpful.

Bruner, S., Corbett, C., Gates, B., & Dupler, A. (2012). Clinical significance as it relates to evidence based practice. International Journal of Nursing Knowledge, 23(2), 62-74

Fethney, J. (2010). Statistical and clinical significance and how to use confidence intervals to help interpret both. Australian Critical Care, 23, 93-97. doi: 1.116/J.aucc.2010.03.001

Question to be answered:

Discuss why confidence intervals are useful in helping determine clinical significance? There are many controversies surrounding the issue of clinical significance vs. statistical significance. Identify one of them and summarize it. Finish with your opinion about the controversy.