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Statistical significance and clinical significance are used to interpret research studies. Evidenceâ€based practice requires clinicians to stay current with the scientific literature. Clinical research data is often analyzed with traditional statistical probability (pâ€values), which may not give rehabilitation professionals enough information to make clinical decisions. Statistically significant differences or outcomes simply address whether to accept or reject a null or directional hypothesis, without providing information on the magnitude or direction of the difference (treatment effect). To improve the interpretation of clinical significance in the rehabilitation literature, researchers commonly include more clinicallyâ€relevant information.
Statistical significance addresses a hypothesis about whether or not differences exist, statistically, between groups. Statistical significance is based on several assumptions. The sample tested should be representative of the entire clinical population. Statistically significant differences alone should not be the primary influence for clinical interpretation of a study’s outcome for application to patient care. Statistically significant differences do not provide clinical insight intoimportant variables such as treatment effect size, magnitude of change, or direction of the outcome (Brignardello-Petersen, Carrasco-Labra, Shah & Azarpazhooh, 2013). A study outcome can be statistically significant, but not be clinically significant, and viceâ€versa but, clinical significance is not well defined or understood. Many research consumers mistakenly relate statistically significant outcomes with clinical relevance.
Clinicians and researchers sometimes have different values for clinically important changes, and minimal changes may be specific to the individual patient. My research yielded that there are no standards for calculating clinically important changes in outcomes. There is some subjectivity in determining clinical significance because of the paucity of research determining clinically significant values, and variations in patient status and goals and clinician experience (Chan, 2018). In my evidence-based project, the clinical significance can be measured by patient outcomes on days with an understaffed and adequately staffed emergency department.
Brignardello-Petersen, R., Carrasco-Labra, A., Shah, P., & Azarpazhooh, A. (2013). Clinical and Statistical Significance: A practitionerâ€™s guide to developing critical appraisal skills. What is the difference between clinical and statistical significance? The Journal of the American Dental Association, 144, 780â€“786.
https://doi.org/10.14219/jada.archive.2013.0187 Chan, Z. Y. (2018). Clinical Research Issues in Nursing. New York, NY: Nova Science Publishers, Inc.
Clinical significance is how effective a treatment is and if there is an obvious effect in the patient due to the treatment. A treatment can be thought to have clinical significance if it helps the patient and has changed the expected outcome. Clinical significance often measures the magnitude of the relationship between the independent variable and the outcome variable (El-Masri, M PhD, RN, 2016). Whereas, statistical significance refers to a decision to reject the null hypothesis based on a predetermined norm. It means that a statistically significant result simply shows that the observed effect is not likely due to chance.
After all of the data is reviewed from hospital acquired pressure injuries, and the results show that with implementation of early assessments and interventions for HAPIs has decreased the incidence, I will be able to present this statistical data to the organization to support practice and policy change that is needed.
El-Masri, Maher, PhD, RN. (2016). Statistical versus clinical significance in nursing research. Canadian Journal of Nursing. https://doi.org/10.1177/0844562116677895
Clinical significance is the practical importance of the treatment effect, whether it has a real, palpable, noticeable effect on daily life. Statistical significance is oberved by the p-value and confidence intervals. If the results show a difference where p<0.05, this is considered statistically significant and unlikely to have randomly occured or by chance. However, it doesn’t inform others about the importance of this difference or its impact on the patient. With enough study particpants, the smallest differences between goups can be become statistically significant. Generally speaking, the larger the effect size, the more likely it is that difference will be meaningful to patients. Whether or not treatment effects wll be clinically relevant will be for patients and their healthcare providers to decide. With my proposed EBP project of implementing early SSC to promote breastfeeding and newborn/parental bonding, I anticipate that this intervention will be clinically and statisically significant and practical and observable improvements will be observed in both of these areas. The sample size is large and the treatment effect should positively impact patient outcomes on a long-term and hopefully, permanent basis.
De Los Rios, Cindy. (2017). Statistical significance vs. clinical significance. Retrieved from www.students4bestevidence.net/statistical-significance-vs-clinical-significance.