p1,p2 and p3

   Hello i need a Good and Positive Comment related with this argument .A paragraph  with no more  100 words   .   

 

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Wendy Santos 

1 posts

Re:Topic 8 DQ 2

Clinical significance is defined as a conclusion that an intervention has an effect of practical meaning, and can be graphically represented by showing pretreatment or post treatment means (Busch, Wagener, Gregor, Ring, Borrelli, 2011). Clinical significance is subjective interpretations of research results, which could affect behaviors, when statistical significance is more about proving research is true (Shelly, 2011). Clinical significance could have meaning from the results, to the nurse and the patient. Clinical significance that would support positive outcomes in my project could be a change in lifestyle habits, after receiving culturally appropriate prevention strategies (Skelly, 2011). A change in behavior, that helps with lifestyle choices,, is viewed as important which is then classified as clinically significant, and could be great enough to alter the way you do practice (Busch et al, 2011). Confidence intervals can be used to help determine clinical significance by intervals in range of percentages (Busch et al, 2011).

Statistically significant is defined as the probability that the research results are true (UCCS, 1999). In order to know if your data is statistically significant one must test the hypothesis to provide a p-value with 5% or lower considered to be statistically significant (UCCS, 1999). Statistical significance is a function of the sample size, reliability of the effect and measurement instrument, along with magnitude of the effect (UCCS, 1999). When the sample size is very large almost anything can be found to be statistically significant, but when the sample size is small then random errors can occur (UCCS, 1999).  Even if an intervention is found to have a statistically significant effect, it does not mean the intervention will be clinically significant (Busch et al, 2011).

Clinical significance is important to healthcare workers, because the risk or benefit of an intervention would indicate how effective the results would be in real life, and help with your decision making process (Skelly, 2011). By conducting a base line assessment at the start of your EBP and comparing changes at an later assessment, and grouping participants who experienced an issue against those that do not, you can then get clinical significant results to support your project (Busch et al, 2011).

 

Busch, A. M., Wagener, T. L., Gregor, K. L., Ring, K. T., & Borrelli, B. (2011). Utilizing reliable and clinically significant change criteria to assess for the development of depression during smoking cessation treatment: The importance of tracking idiographic change. Addictive Behaviors, 36(12), 1228–1232. http://doi.org/10.1016/j.addbeh.2011.07.031

Skelly, A. C. (2011). Probability, proof, and clinical significance. Evidence-Based Spine-Care Journal, 2(4), 9–11.

http://doi.org/10.1055/s-0031-1274751

University of Colorado Colorado Springs [UCCS]. (1999). Statistical and Clinical Significance. Retrieved from

https://www.uccs.edu/lbecker/clinsig.html

 

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Erin Dieguez 

2 posts

Re:Topic 8 DQ 2

Significance is noted to be the importance of something or possessing the important quality. The statistical significance of something means that it did not happen just by chance, but because it was true. “Significant, in terms of statistics, is defined as “probably caused by something other than mere chance.” Researchers proclaim a study finding to be “statistically significant” or not, depending on whether their research result is less than the a priori alpha level set before the study commenced.” (Thompson, 2017)

“ Clinical significance
, or clinical importance
: Is the difference between new and old therapy found in the study large enough for you to alter your practice? Because there is always a leap of faith in applying the results of a study to your patients (who, after all, were not in the study), perhaps a small improvement in the new therapy is not sufficient to cause you to alter your clinical approach. Note that you would almost certainly not alter your approach if the study results were not statistically significant (i.e. could well have been due to chance).” (Significance vs. Importance, n.d.)

This is such a hard concept for me to understand honestly. What does make sense to me is that statistics and statistical evidence are actual facts and what makes sense to me is that the significance is based on actual factors and not just a random result. The clinical significance is necessarily just by chance but you are taking a little more of a “leap of faith”, as they stated, in applying their results to the actual practice. They are not sure if this result is for sure the answer to treatments and if it will work on every single person  but there is a strong possibility based on research that this will work for most of the population.

 

References

Significance vs. Importance. (n.d.). Retrieved from https://www.med.uottawa.ca/sim/data/Statistical_significance_importance_e.htm

Thompson, C. (2017, April 11). What’s the Difference Between Statistical Significance and Clinical Significance? Retrieved from https://nursingeducationexpert.com/difference-statistical-significance-clinical-significance/

 

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Ryan Mcclure 

2 posts

Re:Topic 8 DQ 2

“Significance is defined as the quality of being important. In medicine, we distinguish between statistical significance and clinical importance.

Statistical Significance
. Medical studies are carried out on selected samples of people, but the goal is to apply the findings to another population (e.g., your patients).  Naturally, a concern is that the sample used in the study could provide misleading results. Perhaps it was a very small sample; perhaps it was a biased sample that is not equivalent to the people you are treating; perhaps the sample was large enough, but by chance or bad luck it contained people who gave wacky results. Statistical significance considers the first and third of these concerns. The middle one, bias, cannot be detected by mathematical deductive logic: it needs detailed information on the way the sample was chosen.” (Significance VS. Importance, n.d.).

“Statistical significance in hypothesis testing is expressed in terms of a probability (hence that little letter “p”). By convention this is set at 5%, or p < 0.05: there is only a 5% chance that a difference of the size found in your study, or a greater difference, would occur by chance, if there was actually no difference in the whole population. (In other words, you have drawn a false positive conclusion over the new therapy). The 5% value is arbitrary and is not chosen in terms of the actual magnitude of the effect seen in the study. Results are said to be "statistically significant" if the probability that the result is compatible with the null hypothesis is very small. Crucial Point: testing statistical significance is all about the likelihood of a chance finding that will not hold up in future replications. Significance does not tell us directly how big the difference was." (Significance VS. Importance, n.d.).

We learned about this concept in our Statistics class and I must say this was a hard concept for me to understand and truthfully I am not sure that I truly understand this completely. We used a program that made these calculations for us so I was depending on the data I was inputing for the results to be accurate so there is definetly room for human error here. 

” Clinical significance, or clinical importance
: Is the difference between new and old therapy found in the study large enough for you to alter your practice? Because there is always a leap of faith in applying the results of a study to your patients (who, after all, were not in the study), perhaps a small improvement in the new therapy is not sufficient to cause you to alter your clinical approach. Note that you would almost certainly not alter your approach if the study results were not statistically significant (i.e. could well have been due to chance). But when is the difference between two therapies large enough for you to alter your practice? Statistics cannot fully answer this question. It is one of clinical judgment, considering the magnitude of benefit of each treatment, the respective profiles of side effects of the two treatments, their relative costs, your comfort with prescribing a new therapy, the patient’s preferences, and so on. But we can provide different ways of illustrating the benefit of treatments, in terms of the Number Needed to Treat. Yet another example of science offering only partial guidance to the art of medicine. A partial way out of this uncertainty is to express study results using confidence intervals instead of significance levels. Confidence intervals show the likely range of results within which the true value is likely to lie. An example: a study showed a statistically significant impact (p < 0.03) of Transcendental Meditation on reducing systolic BP compared to controls. The mean reduction was 7 mm Hg (95% CI 4, 10). Instead of significance testing telling us that this study result could have occurred 3% of the time by chance alone, confidence intervals tell us what our best guess is for the size of the population effect, 95% of the time. This seems more informative for the clinician." (Significance VS. Importance, n.d.).

In the end there is always a chance that your research can produce null results or be considered clinically and or statistically insignificant. This is why we do these tests to show the public that the research has been tested and is valid or possibly invalid. 

I know I would be very discouraged if after researching something and working on a project for many many hours/days/weeks etc. and it was shown to be insigificant. That would be a hard blow but neccessary to prove or disprove a practice change and this is what makes EBP so important and credible in the healthcare industry. It is backed by facts and tested for validity.

References

University of Ottawa. (n.d.). Significance vs. Importance. Retrieved from https://www.med.uottawa.ca/sim/data/Statistical_significance_importance_e.htm