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Both statistical significance and clinical importance are essential in healthcare research, but they have different meanings and applications. As such, scholars have to know how they are similar or different when conducting investigations on the usefulness of a specific treatment. According to Abbott (2017), any hypothesis test result that has a p below 0.05 should be considered statistically significant. The value can be lowered if necessary, with 0.01 being a popular choice in medicine due to its stringent requirements. However, statistical significance alone is not sufficient to confirm the efficacy of a treatment, though it is required.
Clinical importance is also necessary to mark the results of the study as definitive on whether the new treatment warrants implementation. According to Newman, Takei, Klokkevold, and Carranza (2019), it is classified depending on the tangibility and size of the effect. Tangible results and significant effects are more clinically important than their opposites. As such, according to Mackridge and Rowe (2018), it is possible for a result to be statistically but not clinically significant and vice versa. Researchers should pay attention to both criteria when determining whether the results are relevant.
Statistical significance and clinical importance are essential statistics for clinical research, but they share no other similarities. The former concerns the results of the test and whether the information obtained is likely to represent the objective reality. The latter indicates whether the treatment produces sufficient positive results it warrants implementation in clinical settings if its reliability is confirmed. One characteristic does not indicate the presence of the other, and the two are not mutually exclusive. As such, researchers have to consider both independently when conducting clinical studies.
Abbott, M.L. (2017). Using statistics in the social and health sciences with SPSS and Excel. Hoboken, NJ: John Wiley & Sons.
Mackridge, A., & Rowe, P. (2018). A practical approach to using statistics in health research: From planning to reporting. Hoboken, NJ: John Wiley & Sons.
Newman, M.G., Takei, H., Klokkevold, P.R., & Carranza, F.A. (2019). Newman and Carranza’s clinical periodontology (13th ed.). Philadelphia, PA: Elsevier.