DNP 810 Explain the difference between statistical significance and clinical significance

DNP 810 Explain the difference between statistical significance and clinical significance

DNP 810 Explain the difference between statistical significance and clinical significance

Evidence-based practices and research in the medical field have provided enormous information that can be applied in clinical practice. However, it is important to understand the differences between statistical and clinical significance since they are important aspects in the clinical field, application of evidence-based research, as well as clinical projects. Therefore, Sharma, (2021) explains that the main difference between clinical and statistical significance is that clinical significance observes dissimilarity between two groups or two treatment modalities while statistical significance on the other hand shows whether there is any mathematical significance to the carried analysis of the results or not.

Additionally, Alsoufi, (2018) adds that statistically significant results do not necessarily mean that the results are clinically relevant because many outcomes can be statistically significant but not clinically relevant. An example of clinical significance can be explained using two different chemotherapy agents for cancer whereby drug A is less expensive as compared to the usual chemotherapy agents and it increases the survival of treated patients by five years while drug B is more expensive than the usual chemotherapy drugs and increases the survival of the treated patient five months. Drug A is considered to be clinically significant because it increases the patients’ survival by five years and it is inexpensive while the statistical significance is the difference in values recorded in analysis when differentiating the years and months of patient survival.

Statistical and clinical significance is very important and can be applied in clinical practice to improve service quality. Clinically significant research outcomes are considered to be clinically viable and can be implemented in healthcare facilities to improve the quality of healthcare services thus improving patient outcomes (Polit, 2017). From the example provided earlier in comparing the effectiveness of drugs A and B, drug A can be used in healthcare facilities in the treatment cancer patients undergoing chemotherapy thus improving their survival by five years.


Alsoufi, B. (2018). Statistical versus clinical significance. The Journal of Thoracic and Cardiovascular Surgery, 155(1), 344-345.DOI:

Polit, D. F. (2017). Clinical significance in nursing research: A discussion and descriptive analysis. International Journal of Nursing Studies, 73, 17-23.

Sharma H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi journal of anaesthesia, 15(4), 431–434.

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Clinical significance is the importance of the research findings. How will it affect the clinical care being provided or how will it affect the clinical decision that needs to be made for care? While statistical significance is the knowledge that the results were based on facts and the interventions performed and not by chance or an accident that happened (Melnyk, & Fineout-Overholt, 2018).  The extent to which random errors in a study will affect it, is reported by using the statistical significance which is represented by p values (Melnyk, & Fineout-Overholt, 2018). When the clinical and statistical significance of a study is not understood, it can lead to misleading reports of the study results and the effects of the study. For instance, with clinical significance, if a study does not randomly assign participants to a particular group, there is a possibility that a lot of sick people could be on one group by chance and that will affect the results of the study (Melnyk, & Fineout-Overholt, 2018).

On the other hand, the statistical significance which is used to determine fact or chance, accepts or rejects the hypothesis, that is, what the author believes will happen. For instance, when an author compares two groups stating that the administration of pain medication to the intervention group and a placebo to the control group, stating that the medication will make a difference. The null hypothesis will be that it will not make a difference. Hence, the p value is used to determine the statistical significance. When the p value is small with large samples, it can lead to the study being reported as statistically significant but clinically insignificant while large p values with small sample sizes can be clinically significant and reported as statistically insignificant (Melnyk, & Fineout-Overholt, 2018).

When a study is clinically significant, it helps to improve the medical, physical, emotional and social aspects of care

DNP 810 Explain the difference between statistical significance and clinical significance
DNP 810 Explain the difference between statistical significance and clinical significance

for a patient. It includes both the objective effects such as function, the duration of the illness and how long life is prolonged and the subjective effects refers to the improvement in their attitude, mood, and wellbeing, decrease in pain and increased comfort. Even though statistical significance does not mean clinical significance but it leads to the improvement in the care of the patient, therefore, in a DPI project, researchers and clinicians should not discount either but should pay attention to both to improve the outcome for the patient to decrease the chances of reporting a biased study (Sharma, 2021).


Melnyk, B. M., & Fineout-Overholt, E. (2018). Evidence-based practice in nursing & healthcare: A guide to best practice. LWW.

Sharma, H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi Journal of Anaesthesia15(4), 431.

Statistical significance as seen in an investigator-initiated trial is used to determine whether the results of a treatment group are different than that of a control group. This is done by selecting the appropriate statistical tests based on a sample and then calculating the corresponding P-values. Another way of looking at statistical significance is that the difference seen in the sample also exists in the population. It is simply the relationship between two variables.  For example, a researcher would want to know whether changing the sound of a car horn will result in more people buying it. Clinical significance on the other hand, measures the extent that a change can create a significant impact for a patient. Clinical significance, unlike in statistical significance has no set guidelines to determine clinical importance of a response. Subjective judgment is relied upon in identifying the clinical relevance of results. It also means that the difference between effectiveness of treatments is clinically relevant (Sedgwick, 2015).

It is important to note that statistical significance is very valuable in research because it is used to depict the reliability of the study results, while clinical significance shows its relevance to clinical practice. Clinical significance should be able to tell how much change it has impacted, whether the change makes an actual difference on the lives of the subjects, sustainability of the change, its cost-effectiveness, and how easy it is to implement (Ranganathan, 2015). Both statistical and clinical significance play an essential role in a DPI project, in the sense that the validity and viability, and reliability will give credibility to the project which will positively impact the practice improvement in all aspects.

Ranganathan, P., Pramesh, C. S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in clinical research, 6(3), 169.

Sedgwick, P. (2014). Statistical Significance vs Clinical Significance

One purpose of statistical significance is to accept or reject the null hypothesis, not focus on research hypotheses. The primary focus is to measure the strength of evidence. It may be altered by sample size, the magnitude of the relationship and error, this can cause distortion of findings.

Clinical studies are valuable and importance to clinical practice when results are appropriately interpreted. Clinically significant findings support medical care that results in improved individual physical function, mental health, and ability improve engagement in society.

The clinical point of view, the statistically significant difference among groups is not of prime importance. If a well‑conducted study shows a difference in treatment options within two groups, it is of prime importance to know whether that difference is of clinically importance or not. Sample size and measurement variability easily influences the statistical results, a nonsignificant outcome does not imply that the new therapy or treatment protocol is not beneficial (Sharma, 2021)

When reviewing articles, researchers should not only consider statistical significance and clinical significance, but take into consideration sample size, effect size of study, potential biases, the ability to reproduce the study results. (Sharma, 2021).

When researching what type of quality improvement initiative to implement., statistical and clinical significance of studies should be reviewed. Ensuring more balanced and less chance of biases. Answering questions re: journal articles it should be understood that variables are observed results, should be clearly identified. The study for article review of statistical and clinical significance wa a review of six databases researching literature on how the affects of transportation barriers affect those with chronic conditions. (Starbird, DiMaina, et al, 2019). The research was supportive of the need for more research in relation to transportation barriers. The article is interesting but doesn’t do a good job with statistical significance.

Sharma, H. (2021). Statistical significance or clinical significance? A researcher’s dilemma for appropriate interpretation of research results. Saudi Journal of Anesthesia, 15(4), 431–434.


Starbird, L. E., DiMaina, C., Sun, C.-A., & Han, H.-R. (2019). A systematic review of interventions to minimize transportation barriers among people with chronic diseases. Journal of Community Health, 44(2), 400–411.