It has been proven that a study outcome might be statistically significant, yet it is not clinically relevant. As explained by Harris et al. (2017), clinical significance means that the difference in the effectiveness of the treatments being tested is clinically relevant, and there is a possibility of changing clinical practice in case the difference is observed. According to Armijo-Olivo (2018), statistical significance is determined by a test of the null hypothesis versus the alternative hypothesis. This means that the choice to reject or accept the null hypothesis depends on fixed probability levels (p-value less than 0.01 or 0.05), which tests the power of evidence to reject the null hypothesis. Therefore, accepting or rejecting the null hypothesis does not give insights into whether the study outcomes are clinically significant for various stakeholders such as clinicians, patients, and decision-makers.
Sharma (2021) states that the key difference between clinical significance and statistical significance is that while clinical significance investigates the differences between two treatment methods or two groups, statistical significance observes whether or not there exists any mathematical relevance in the accepted analysis of outcomes. Secondly, another difference between clinical significance and statistical significance is that clinical significance is based on the effect size, while statistical significance is based on the null hypothesis (Zbrog, 2022). The effect size measures the magnitude of the observed occurrence, which may consist of correlation between the two variables being tested, their mean difference, or the risk of occurrence of a specific event. On the other hand, the null hypothesis is used in statistical significance as the default supposition of lack of statistical significance, which means that no change was observed or the observed variables have no relationship or association.
The third difference between clinical and statistical significance, as explained by Zbrog (2022), is that while clinical significance uses the number needed to treat (NNT), statistical significance uses a p-value. NNT is an effect size type that estimates the average patients who require treatment to prevent an extra negative outcome or the total patients who require treatment for someone to benefit above the control (Zbrog, 2022). On the other hand, the p-value represents the likelihood of achieving study outcomes assuming that the null hypothesis is true. For instance, if P=0.045, it means there is a 4.5% probability that any difference observed was due to a random chance.
A clinical research study is important and valuable for clinical practice only if the researchers interpret the results appropriately. To establish whether a study’s conclusion has genuine clinical significance, the patient must perceive the extent of improvement and statistical analysis as being relevant and realize a satisfaction threshold (Sharma, 2021). An example of how clinical significance may be used in supporting positive patient outcomes includes testing vaccines to be sure that they work to achieve the desired results of preventing patients from contracting and spreading particular diseases such as COVID-19. A second example of how clinical significance can be used is in pharmaceutical testing, which entails measuring a treatment’s strengths, accuracy, and weaknesses and evaluating its efficacy, potency, and the appropriate dosage or use. Lastly, clinical significance can be used to support positive patient outcomes by providing reliable and accurate information to aid healthcare providers in improving their therapeutic and diagnostic decision-making. When providers have access to accurate information, they are able to reduce errors, improve the safety of patients, and support improved patient outcomes.
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.
Harris, J. D., Brand, J. C., Cote, M. P., Faucett, S. C., & Dhawan, A. (2017). Research pearls: The significance of statistics and perils of pooling. Part 1: Clinical versus statistical significance. Arthroscopy: The Journal of Arthroscopic & Related Surgery, 33(6), 1102-1112.
Sharma, H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi Journal of Anaesthesia, 15(4), 431.
Zbrog, M. (2022). Comparing Clinical Significance & Statistical Significance – Similarities & Differences. Retrieved from https://www.mhaonline.com/faq/clinical-vs-statistical-significance
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- Define clinical significance, and list at least three differences between clinical and statistical significance.
- Give three examples of how can you use clinical significance to support positive patient outcomes.
Note: Sources must be published within the last five years and appropriate for the assignment criteria.