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Statistically significant evidence is findings of studies found to have relationships or associations that are not caused by chances alone (Kenton & Westfall, 2021). According to Ranganathan et al. (2015), statistical significance can be heavily influenced by the sample size. Even minor treatment effects that are not clinically meaningful can be statistically significant with a large sample population determined by the p-value. On the other hand, clinical significance depends on its implications on current practice treatment. The effect size is considered to have the most important factors that drive decision-making (Ranganathan et al., 2015). For example, there is a significant difference between the control group and the experiment group in an interventional study in which the intervention decreases the BP by 1-2 mmHg. Although the findings show a statistically significant result, the findings may not be clinically significant because according to De Los Rios (2017), for a study to be clinically significant, it should have positive and noticeable improvement to patients. Further clinically relevant or clinically significant findings from studies should be able to express insights on the applicability of the findings that are medically crucial in various stakeholders in the health care system such as the patient, clinicians, administrators (Armijo-Olivo, 2018).

Statistically significant evidence can also be valid evidence to support an EBP project because it indicates that the research findings are correct and do not occur by any chance and that the study design is quite rigorous. However, in clinical research, EBP projects should not heavily rely on the statistical significance but also scrutinize the study’s clinical importance by determining the findings’ relevant improvements in patient outcomes. Thus, according to Nordahl-Hansen et al. (2018), studies selected in the conceptualization and support for EBP projects should be statistically significant and consider which best inform the clinical practice.

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