Evidence-based practice is expected to affect the clinical decision-making of healthcare providers, but interpreting research is often difficult for some clinicians. Interpretation of clinical research is important in that it affects the clinical decision-making affecting patient safety, quality of care, and efficacy among other areas. Narrowing down, one of the common challenges faced by clinicians or readers is interpreting the word “significance.” According to Ranganathan, Pramesh, and Buyse (2015), the term clinically significant is often confused and misinterpreted with the word clinically important. The confusion emanates from the fact that people usually interpret significance in this case to literally mean important. However, when applied statistically, the word has a more restrictive connotation. In clinical practice, the word statistical significance implies the reliability of the study results, which is measured using the “P0″ values versus confidence intervals. Virtually, statistical significance quantifies the probability of a study results based on chance. On the other hand, clinical significance encompasses the magnitude of the actual treatment effect. It involves the ability f the study results to impact the current clinical practice.
Beyond the traditional testing of statistical significance, statistical significance is used to answer questions of probability to determine if a hypothesis can be accepted or rejected. Statistical significance provides important insights into levels of probability and to ensure that the null hypothesis is not rejected incorrectly. However, as Page (2014) elaborate, statistical significance cannot be used to provide clinical insight in important variables. Instead, it is clinical significance that provides important insight into variables such as treatment effect size, magnitude of change, or direction of the outcome.
Page, P. (2014). Beyond statistical significance: clinical interpretation of rehabilitation research literature. International Journal of Sports Physical Therapy, 9(5), 726-36.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.
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