What is the difference between statistically significant evidence and clinically significant evidence? How would each of these findings be used to advance an evidenced-based practice project?
POST 1
To implement evidence-based practice, nurses must be able to comprehend and interpret research. This means understanding the distinction between statistical significance and clinical significance. According to Heavey (2015), a statistically significant difference means an association or difference exists between the variables that wasn’t caused solely by normal variation or chance. A clinically significant difference means the researchers found a statistically significant difference that experts in the field believe is substantial enough to be clinically important and thus should direct the course of patient care.
In clinical research, study results, which are statistically significant are often interpreted as being clinically important. While statistical significance indicates the reliability of the study results, clinical significance reflects its impact on clinical practice (Ranganathan, Pramesh, and Buyse, 2015). This article describes statistical significance is heavily dependent on the studys sample size and clinical significance reflects the extent of change.
Statistical significance is established by an analysis conducted by researchers, which makes this more valid in moving into an evidence based project. You know its been studied and and the findings are substantial. Statistical significance should be established before clinical significance can be determined. To me it seems like clinical significance is very subjective and would need to be determined by healthcare workers or clinical experts to evaluate.
POST 2
ifferent pieces of data are related. When given evidence is said to be statistically significant, it means that the variables involved could be related in different ways. When there is a true null hypothesis, it implies that there is a limited probability to have a similar or larger result in another population. The outcome of research is taken to be statistically significant when there is no valid prove given to show that a causal relationship exists in the variables under consideration in a study (Skelly, 2011). Clinically significant evidence refers to evidence that has been discovered to have a great potential in being justified to be adopted into standard practice. Proper interpretation of clinically significant evidence is always backed up by experiences in the clinical practice as well as research outcomes that are free of bias and errors and with a positive treatment effect (Mariani & Fernandes, 2014). Further approval is necessary from an association to see if statistically significant evidence is also clinically significant (Skelly, 2011). Clinically significant and statistically significant evidence could help advance EBP by helping identify gaps in previous studies that should be addressed (Rios, 2017). It is possible to establish the reason why statistically significant evidence may not be clinically significant especially if a large sample size was the reason for such a difference.