NRS 493 Define clinical significance, and explain the difference between clinical and statistical significance
NRS 493 Define clinical significance, and explain the difference between clinical and statistical significance
NRS 493 Define clinical significance, and explain the difference between clinical and statistical significance
Statistical significance indicates the reliability of a study’s results, while clinical significance reflects its impact on clinical practice. To expound, measures of statistical significance quantify the probability of a study’s results being due to chance. Statistical significance is a mathematical measure that is used to determine variances between groups based on certain mathematical criteria. Clinical significance, on the other hand, refers to the magnitude of the actual treatment effect, which will determine whether the results of the trial are likely to impact current medical/clinical practice (Ranganathan, Pramesh & Buyse, 2015). For example, a study may have true findings and a truly effective outcomes (statistically significant), however, the effect may be very small compared to the financial cost, or resources it may utilize to implement, deeming the study non-clinically significant. The measure of clinical significance is the determining factor whether an evidence-based practice will be implemented in the healthcare system (Schober, Bossers & Schwarte, 2018). Based on the positive outcomes of my change project, if true clinical significance is proven there is a greater potential for continued implementation into standard practice at the facility.
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
Schober, Patrick MD, PhD, MMedStat; Bossers, Sebastiaan M. MD, MSc; Schwarte, Lothar A. MD, PhD, MBA Statistical Significance Versus Clinical Importance of Observed Effect Sizes: What Do P Values and Confidence Intervals Really Represent?, Anesthesia & Analgesia: March 2018 – Volume 126 – Issue 3 – p 1068-1072 http://doi:10.1213/ANE.0000000000002798
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A project hopes to have results that mean something. However, this is not always the case, sometimes the results do not show a change. The resulted question is why a change wasn’t there. The primary cause of insignificance is not having enough samples. Statistical significance is at the heart of this discussion. If a study is done on one person, the value of the resultant data has no relation to other people. There just isn’t enough data and results to comfortably assume there is a pattern or connection (Dybvik, et al., 2018).
Clinical significance relates to the clinical setting. Statistical significance merely relates to mathematical importance. It may have no bearing on the clinical area, be in a hospital or a lab. The way Mellis (2018) described it, there are those that produce and those that consume research. Clinical significance is more important for those that consume research. Statistical significance is more for those that produce the research. The importance of accepting clinical significance is the hopes there was a conclusion that was viable and true. Clinical significance will have different values than that of statistical significance. These two can be combined in a conclusion or evaluation as well (Mellis, 2018). There may not necessarily be numbers related to clinical significance, but results may support it regardless of the statistical values. There can be a positive outcome will low changes in expected results.
For instance, the author’s practicum does look to have some statistical data that supports a positive conclusion due to valuation of blood glucose levels. Even with results not supporting lower blood glucose levels, perhaps in the case of the authors proposal, overall patient health can be related as a positive finding if indicated by the patient. Things such as a reduction in hospital visits are one way of analyzing the clinical value.
Dybvik, J. B., Sundsford, S., Wang, C. E. A., & Nivison, M. (2018). Significance of nature in a clinical setting and its perceived therapeutic value from patients’ perspective. European Journal of Psychotherapy & Counselling, 20(4), 429–449. https://doi-org.lopes.idm.oclc.org/10.1080/13642537.2018.1529690
Mellis, C. (2018). Lies, damned lies and statistics: Clinical importance versus statistical significance in research. Paediatric Respiratory Reviews, 25, 88–93. https://doi-org.lopes.idm.oclc.org/10.1016/j.prrv.2017.02.002
Clinical significance is the significance that is linked to the significance of a course of treatments. When a project has clinical significance, it means that the intervention that was implemented had both genuine and quantifiable effects (Polit, 2017). Clinical significance has various key applications and it is mostly in major applications such as pharmaceutical testing and medical research or even in non-medical research, but it is also used in the critique of data sets.
On the other hand, statistical significance on the other hand is significance that emanates from the finding that an event is unlikely to have been caused by something else, or to have occurred by chance (Andrade, 2019).
During the implementation of EBP, I would use clinical significance to show the superiority of the interest, as compared to competing interventions. I would first design my intention in such a manner that it is extensively supported by evidence that has achieved both clinical and statistical significance, and also ensure that there are no outliers that ultimately affect the intervention. My intervention which is Nicotine Replacement Therapy and Education and in this case, I would use clinical significance to prove that both of these intentions would have a more positive impact than no intervention at all.
References
Andrade C. (2019). The P Value and Statistical Significance: Misunderstandings, Explanations, Challenges, and Alternatives. Indian journal of psychological medicine, 41(3), 210–215. https://doi.org/10.4103/IJPSYM.IJPSYM_193_19
Polit D. F. (2017). Clinical significance in nursing research: A discussion and descriptive analysis. International journal of nursing studies, 73, 17–23. https://doi.org/10.1016/j.ijnurstu.2017.05.002
In a successful evidence-based project implementation, it is essential to understand and interpret the research findings. Therefore, it becomes critical to recognize and appreciate the difference between clinical significance and statistical significance. Statistical significance in research is phenomenon that is used to indicate the reliability of the study results by highlighting that a certain claim from data generated from experiment is attributed to a specific cause (Fleischmann & Vaughan, 2019). When the degree of statistical significance is high, the implication is that the observed relationship is unlikely coincidental but rather it has a direct association with a certain cause.
Clinical significance is essential in highlighting its implication in clinical practice. Clinically significant results or outcomes are subjective interpretations that are based on research findings as having healthcare implications for the specified patient. Clinically significant results indicate that the research findings can influence the healthcare practices and interventions hence shaping the behavior of healthcare practitioners. For results to be labeled clinically significant, the data must convince medical experts that the findings can inform the provision of care for a particular patient.
In the case of evidence-based research practice, it is essential to determine statistical significance of the research results before ascertaining whether the results are clinically significant. The main reason for establishing statistical significance before determining clinical significance is that clinical significance is determined after evaluating several research or experimental findings and confirming that they are statistically significant (Polit, 2017). I can make use of clinical significance to inform positive outcomes in my project outcome by ensuring that the results are statistically significant because clinical significance is informed by statistically significant results.
References
Fleischmann, M., & Vaughan, B. (2019). Commentary: statistical significance and clinical significance-a call to consider patient reported outcome measures, effect size, confidence interval and minimal clinically important difference (MCID). Journal of bodywork and movement therapies, 23(4), 690-694.
Polit, D. F. (2017). Clinical significance in nursing research: A discussion and descriptive analysis. International Journal of Nursing Studies, 73, 17-23.
Evidence-based practices (EBP) often have statistical information to assess or base project results and the clinical significance is key as it points to “patient safety or efficacy” and the true value of assessing via clinical research statistical results (Page, 2014). Page also informs us of the importance to incorporate information including effect sizes and confidence intervals for “clinically-relevant information” and ultimately the results are “only of value if it is properly interpreted” (2014). However, this is not the only venue to assess the outcome of a project.
Betterham and Watkins point out the statistical significance of there being or lacking differences is of limited value and stressing that a non-significant outcome does not necessarily (italics are Kitty’s) mean that a treatment or project was of no or minuscule value as many factors including sample size are key factors in the results (2006). Page continues with insight that a project or research not have an outcome that is clinically significant, yet is statistically significant “and vice-versa) (2014).
The site I am doing my preceptorship at has maintained records on each patient who has tested for Covid-19. The word has gotten out locally and beyond and in an interview, Dr. Tyson shared, their sites were seeing 200-400 persons a day (2021). The patients they saw were provided interventions from the beginning; which we now know as Covid-19, which addressed patients symptoms including possible headache, body aches, nausea, vomiting, shortness of breath or difficulty breathing and/or temp. their test results, symptoms or asymptomatic, what interventions needed or prescribed, if additional indications led to chest x-ray and/or breathing treatment and ultimately regarding the follow-up call or return to office visit for assessment, further medications or the need to go to the hospital. In most of the cases, there has been clinical significance to optimal outcome and less need of admittance to the hospital.
Resources
Batterham, A.M. and Hopkins, W. G. (2006). Making meaningful inferences about magnitudes. International Journal of Sports Physiology Performance. (1), 50‐57.
Page, P. (2014). beyond statistical significance: clinical interpretation of rehabilitation research literature. International Journal of Sports Physical Therapy, 9(5): 726–736. Beyond statistical significance: clinical interpretation of rehabilitation research literature – PMC (nih.gov)
Tyson, B. (2021). The miracle of the Imperial Valley: Dr. Tyson’s first-person account of COVID-19. The Desert Review. https://www.thedesertreview.com/news/the-miracle-of-the-imperial-valley-dr-tyson-s-first-person-account-of-covid-19/article_a8707136-196b-11eb-bc7b-87d7730460bb.html