NUR 590 Discuss The Difference Between SSE And CSE

NUR 590 Discuss The Difference Between SSE And CSE
NUR 590 Discuss The Difference Between SSE And CSE
 
Discuss 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?
Statistically, significant evidence is defined as a result when it is determined that an occurrence is different from the theoretical by coincidence. Statistical significance focuses on the null hypothesis (no association or change), p-value (probability), and the significance level (data collected previous to study). Statistics help researchers, businesses, and other entities to comprehend the extent of the findings of an experiment, survey, or poll (Ranganathan et al., 2017). Statistical importance is intended to ensure that an impact occurs. Decision-makers can use the results of specific research as a helpful tool. Nevertheless, truth, effectiveness, or relevance should not be the prime determinant.
NUR 590 Discuss The Difference Between SSE And CSE
Clinically significant evidence is defined as a result is granted where actual and measurable results have been achieved through intervention. Clinical significance depends on the affected size (correlating multiple variables), the number needed to treat (the affected sample size), and the Jacobson-Truax (calculates reliability change index). In practice, significant clinical results may be reproduced to a considerably higher degree than just significant statistical findings and can thus be utilized in the circumstances with more significant stakes when even a slim margin of mistake is too high (MHA, 2021). The clinical relevance aims at understanding the extent and extent of an impact. This is a vital tool for policymakers working on the pharmacological, psychological, and medical fields of high interest.
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In evidence-based research practice, statistical importance must always be considered prior to clinical significance. The evidence-based clinical importance of the research project will be utilized to promote good projects findings that correspond with statistically significant results.
 
MHA. (2021). Clinical Significance vs. Statistical Significance – Side-by-Side Comparison. Mhaonline. https://www.mhaonline.com/faq/clinical-vs-statistical-significance
Ranganathan, P., Pramesh, C., & Buyse, M. (2017). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in Clinical Research, 6(3), 169. https://doi.org/10.4103/2229-3485.159943
 
The difference between statistical versus clinical significance is the former reflects reliability of the study results while the latter is the reflection of how a study has an impact with one’s clinical practice (Ranganathan et al., 2015). Statistical significance can be measured and quantified. It can measure the probability of a null hypothesis being correct when comparing it to the acceptable level of uncertainty (Tenny & Abdelgawad, 2021). This basically is able to determine if the results yielded are true and not just a mere chance. On the other hand, clinical significance refers to the magnitude of the actual treatment effect (Ranganathan et al., 2015).
These findings can be used to advance an evidence based-practice project . It is important to note that statistical significance is not the same as clinical significance. Statistical significance can assist a researcher to whether reject or accept the null hypothesis or use the alternative hypothesis (Tenny & Abdelgawad, 2021). Clinical significance can have implications to the current trends in practice because it may or may not create a positive impact in patient care delivery.
 
 
References
 
Ranganathan, P., Pramesh, C. S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in Clinical Research, 6(3), 169–170. https://doi.org/10.4103/2229-3485.159943
 
Tenny, S. & Abdelgawad, I. (2021). Statistical significance. StatPearls Publishing; Available from: https://www.ncbi.nlm.nih.gov/books/NBK459346/
Statistically significant evidence is when an event occurs and the result is thought to be not random in occurrence (Zbrog, n.d.). It is utilized when the researcher is attempting to see if something is not happening by chance, and Zbrog (n.d.) states that it would be well utilized in the initial stages of pharmaceutical trials. Clinically significant evidence is when the results are after a treatment has have results that are quantifiable (Zbrog, n.d.). Zbrog (n.d.) states that this type of significance is mostly utilized in the medical field and among pharmaceutical researchers, really wherever there is an intervention that the researcher needs to be able to measure and quantify. In our EBP projects there is room for both types of evidence. Obviously for most of us we are producing new interventions/ways to do things and therefore are looking at clinically significant evidence, because if our new way of thinking and doing things makes a difference that is significant to practitioners everywhere. With statistically significant evidence, we might not all find this within our own projects but it does have its place in EBP. In my EBP project in the phase where the facility will be utilizing a survey for all patients, it could be found statistically that most of the people agreeing to take the STD test are men who sleep with men. Furthermore, this could reflect that it is MSM who are more likely to have an STD, as most of the other research I have done have found this. It would be interesting to see if this infact happens, or if the other researchers were in areas with higher rates of homosexual STD spread, on purpose or otherwise. There are many reasons one might want this statistical data, it is not significant to my study and would only be statistically significant, whereas the outcome of my intervention is most important to me, and is clinically significant evidence.
Zbrog, M. (n.d.). Clinical Significance vs. Statistical Significance – Side-by-Side Comparison. Mhaonline. Retrieved September 21, 2021, from https://www.mhaonline.com/faq/clinical-vs-statistical-significance
The successful implementation of an evidence-based practice (EBP) proposal depends on the ability of an investigator to synthesize and interpret data collected from research. Therefore, the findings of a study must be differentiated based on their relevance in improving the reliability of research and on their reliance on being applicable within the clinical context. Statistically, significant evidence is a finding that suggests a positive relationship between variables that happened by chance (Schober, Bossers, & Schwarte, 2018). This aspect is evaluated a probability value (p-value) which suggests that a finding is statistically significant if its p-value is above 0.005. The discovery of a finding that is statistically significant allows an investigator to evaluate the parameters of using the study results to justify or confirm the parameters of the EBP proposal. The likelihood that a study finding is true provides the confidence of using the information on evaluating an EBP.
On the other hand, clinical significance refers to an evaluation of evidence-based subjective interpretation in terms of its application within a clinical setting. It directly relates to the relevance of information from a study and its impact on patient care; therefore, it influences the healthcare provider’s decision-making process within a practice context (Schober, Bossers, & Schwarte, 2018). Clinically significant evidence can alter and change the existing practice principles and procedures due to its ability to integrate with the practical concerns of care. Therefore, this finding can be used as a supportive element to promoting positive outcomes of an EBP project that is already established to be statistically significant.
References
Schober, P., Bossers, S. M., & Schwarte, L. A. (2018). Statistical significance versus clinical importance of observed effect sizes: what do P values and confidence intervals really represent?. Anesthesia and analgesia, 126(3), 1068
According to Ranganthan et. al., clinical research and study results provide information concerning reliability and validity of study results, whereas clinical significance is regarding whether or not the results and information is truly useful and significant in relation to its impact on clinical practice and patient outcomes (2015). Significance does not always mean importance, and importance does not always equate to significance.
 
Now, it is still important to understand the significance of both clinical research and clinical significance, and their parts in evidence-based practice projects. Looking at statistical significance, or results reliability and validity, is essential to reviewing the literature and understanding whether or not the results have occurred via happenstance, or if there is a true correlation between variables based on sample size(Ranganathan et. al., 2015). This allows researchers and clinicians alike to know whether or not they should move forward in their pursuit of evidence-based practice changes, based upon reliable and valid evidence that means something. Moving forward in the process, clinical significance is the next step that examines the extent to which the correlated variables and practice outcomes are meaningful to the patient at the bedside, so to speak. Both are significant in the evidence-based project process, and must be continually reexamined to ensure effective and meaningful outcomes are prioritized for the patient.
 
References
 
Ranganathan, P., Pramesh, C.S. and Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in Clinical Research, 6(3), 169-170. https://doi.org/10.4103/2229-3485.159943
Clinically significant evidence and statistically significant evidence are related, but do not mean the same thing. Statistical significance utilizes the probability value (p-value), and it tells a researcher the probability or chance that the results from the study are a random occurrence versus an actual difference between the variables (Heavey, 2015). Statistical significance also uses the alpha value and when the analysis of the results of the study are done and the p-value is less than the alpha value, it means that the data shows the results was real and did not occur by chance which makes the results statistically significant. When it comes to clinical significance, the researchers determine if the statistical significance is substantial enough to be clinically important and should be used to help direct the course of patient care (Heavey, 2015). Sometimes the results may be statistically significant, although may not clinically significant meaning that the results does not show that it is helpful and should not be used to help guide clinical practice. With this though, statistical significance has to be established before clinical significance can be determined (Heavey, 2015).
Each of these findings can be used to advance an evidence-based practice (EBP) project. Statistical significance helps to determine if something occurred by chance or not. If it did not occur by chance, that means it is statistically significant and can help determine the strength of the evidence against the null hypothesis (Armijo-Olivo, 2018). Clinical significance can be used to advance EBP by determining whether the results of the study are meaningful to clinical practice in a way that the intervention that was tested, its effects are big enough to make the costs, any inconveniences, and harms worthwhile to improve clinical practice and patient care (Armijo-Olivo, 2018).
References:
Armijo-Olivo, S. (2018). The importance of determining the clinical significance of research results in physical therapy clinical research. Brazilian Journal of Physical Therapy, 22(3), 175-176. https://doi.org/10.1016/j.bjpt.2018.02.001
Heavey, E. (2015). Differentiating between statistical significance and clinical significance. American Nurse today, 10(5), 26-28. https://www.myamericannurse.com/wp-content/uploads/2015/05/ant5-Research-421.pdf
 
 
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