DQ: 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:https://doi.org/10.1016/j.jtcvs.2017.08.108
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. https://doi.org/10.4103/sja.sja_158_21
Clinical significance is the importance of the research findings. How will it affect the clinical care being provided or how will it affect
DQ Explain the difference between statistical significance and clinical significance
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 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 Anaesthesia, 15(4), 431.
Thank you for your post. I agree with you it is important as a researcher that we identify statistical and clinical significance. It is essential in the outcome of the findings so it will not be misinterpreted. Researchers must understand the clinical study and value to the clinical practice. According to Ron Wasserstein, ASA’s executive director, the P value was never meant to substitute the scientific reasoning, which is of greater interest. Clinically significant findings are those that can improve quality patient care.
Examining both the clinical significance and statistical significance can assist in improving patient care as you mentioned. Statistical analysis focuses on the P-value in order to test all hypothesis. This value can be change due to various alterations in the sample size, “the magnitude of the relationship and error” (Sharma, 2021).
An example that comes to mind that relays both clinical and statistical significance is the implementation of the ABCDEF bundle in the critical care setting. This bundle demonstrates clinical improvement of ICU patients. These improvements include decrease in mortality, use of mechanical ventilation, delirium, restrain requirements, and readmissions (Pun et al., 2020). This bundle was started in the institution I work for a few years ago however it was not fully implemented house wide. The education from the pilot unit has recently begun in order to ensure all ICU’s utilize this evidence-based tool.