NUR 590 Discuss the difference between statistically significant evidence and clinically significant evidence

NUR 590 Discuss the difference between statistically significant evidence and clinically significant evidence

NUR 590 Discuss the difference between statistically significant evidence and clinically significant evidence

The successful implementation of an evidence-based practice (EBP) proposal depends on the ability of an investigator to synthesize and interpret data collected from research. Therefore, the findings of a study must be differentiated based on their relevance in improving the reliability of research and on their reliance on being applicable within the clinical context. Statistically, significant evidence is a finding that suggests a positive relationship between variables that happened by chance (Schober, Bossers, & Schwarte, 2018). This aspect is evaluated as a probability value (p-value), which suggests that a finding is statistically significant if its p-value is above 0.005. The discovery of a statistically significant finding allows an investigator to evaluate the parameters of using the study results to justify or confirm the parameters of the EBP proposal. The likelihood that a study finding is true provides confidence in using the information to evaluate an EBP.

On the other hand, clinical significance refers to an evaluation of evidence-based subjective interpretation in terms of its application within a clinical setting. It directly relates to the relevance of information from a study and its impact on patient care; therefore, it influences the healthcare provider’s decision-making process within a practice context (Schober, Bossers, & Schwarte, 2018). Clinically significant evidence can alter and change the existing practice principles and procedures due to its ability to integrate with the practical concerns of care. Therefore, this finding can be used as a supportive element to promote positive outcomes of an EBP project that is already established to be statistically significant.


Schober, P., Bossers, S. M., & Schwarte, L. A. (2018). Statistical significance versus clinical importance of observed effect sizes: what do P values and confidence intervals really represent? Anesthesia and analgesia126(3), 1068

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 A substantive discussion post of clinical and statistical significance. Is the statement below true or false and what is the importance of the understanding?

“Statistical significance results do not necessarily mean that the results are clinically relevant and lead to improvement in the quality of life of the individuals.” 

Thank you so much for your clear and concise description of statistically significant evidence versus clinically significant evidence. Honestly, I was having some trouble differentiating between the two, and your explanation clarified it for me. I feel that, since clinically significant evidence is somewhat subjective, it offers nurses an opportunity to implement change based upon what is best for the patients under our care. This makes me excited to become a leader and implement change.

Good post! Clinical significant research can be used in areas where clinical results are used to assess the effectiveness of certain treatments. These findings are those in which makes the patients quality of life is improved. There is usually an improvement in physical function, mental status and the involvement in a social life.

The main difference between statistical and clinical significance is that clinical significance observes dissimilarity between two groups or two treatment modalities. In contrast, statistical significance indicates whether or not there is any mathematical significance to the analysis results (Sharma,2021). In quantitative research, researchers use statistical tests to determine whether there is a significant difference or association between variables. Clinical significance, on the other hand, refers to the practical importance or relevance of the observed effect in a study. It focuses on whether the effect size is large enough to have meaningful implications for patients or the population under consideration.

Statistically significant evidence is crucial in determining whether a relationship or intervention effect exists in a study (Melnyk & Fineout-Overholt, 2019). It provides a strong foundation for evidence-based practice projects by establishing a measurable effect size beyond what would be expected by chance alone. A statistically significant finding may prompt further investigation and exploration, while a clinically considerable result may influence clinical guidelines, treatment protocols, or healthcare policies.

Melnyk, B. M., & Fineout-Overholt, E. (2019). Evidence-based practice in nursing and healthcare: A guide to best practice (4th ed.). Wolters Kluwer. ISBN-13: 9781496384539

Sharma H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi journal of anaesthesia15(4), 431–434.

Statistical significance is a measure that indicates whether the results observed in a study are likely due to a natural effect or if they could be attributed to chance. Statistical significance does not necessarily imply practical or clinical significance. Clinical relevance concerns whether the observed product or difference is meaningful in real-world applications, patient outcomes, or improving quality of life. Researchers and healthcare professionals must consider statistical significance and effect size to assess the practical importance of a study’s findings. (Sharma,2021) They must also consider factors such as the magnitude of the observed effect, the relevance to the target population, potential side effects or risks, and the overall context in which the findings will be applied.

Sharma H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi journal of anesthesia15(4), 431–434.

In research, statistically significant and clinically significant evidence are two different concepts, each important in advancing evidence-based practice programs. According to Polit and Beck (2020), statistical significance refers to the likelihood that the observed results in a study are not related to chance but are a true reflection of the relationship between variables. Statistical tests are used in quantitative research to examine if the findings are likely to have occurred by chance. When a result is statistically significant, it indicates that there is a true effect or correlation between the variables under consideration.

Clinical significance, on the other hand, focuses on the practical or real-world importance of the research findings, the authors added. It assesses whether the observed effect or difference between groups greatly impacts patient outcomes or clinical practice. For instance, a treatment may be statistically significant in reducing the severity of symptoms in a particular condition, but if the effect size is small, the clinical significance may be questionable. In such cases, the treatment may be statistically effective, but its practical impact on the patient’s quality of life might be minimal.

Each of these findings can be used to advance an evidenced-based practice project in such a way. Statistically significant findings are essential for determining whether there is a genuine effect in the study. When conducting an evidence-based practice project, researchers use statistical analyses to determine whether the intervention being studied produces meaningful outcomes compared to the control intervention. If the findings are statistically significant, it suggests that the intervention has a measurable impact and that the results are unlikely to be due to chance alone. This information can guide healthcare practitioners in deciding whether to adopt the intervention in their practice.

Clinically significant evidence is equally vital in evidence-based practice. While statistical significance helps establish the existence of an effect, clinical significance evaluates the practical value of the intervention in real-life settings. Clinicians and researchers must consider whether the observed effects are meaningful and relevant to patients’ well-being. Even if an intervention is statistically significant, it might not be clinically significant if the observed differences are too small to make a tangible difference in patient outcomes.

Polit, D. F., & Beck, C. T. (2020). Nursing Research: Generating and Assessing Evidence for Nursing Practice. LWW.