Clinical significance as a component of the research process is the value that makes it possible to determine the differences in specific effects and, thereby, implement appropriate interventions. In some cases, the application of this practice does not require additional statistical correlations, for instance, when certain determinants of health and their effects are compared in individual population groups (Page, 2014).
If this principle is applied to identify the manifestations of a particular factor on the condition of patients with similar symptoms, the clinical significance is an appropriate methodology to consider a research project successful. According to Ranganathan, Pramesh, and Buyse (2015), this approach may be more relevant than statistical in cases when the degree of exposure to specific factors or symptoms needs to be determined rather than their predominance in numerical correlation. Such an analysis allows understanding the unique implications of specific conditions and, thereby, eliminating them competently.
The results of a specific project may be determined by using this criterion. Polit (2017) notes that the result of research work implies the absence of changes throughout all stages of screening tests and other procedures can be considered clinically significant. In other words, an opportunity to prove stable patient resistance to specific effects is the aspect that does not depend on statistical correlations and does not require calculations.
For the field of healthcare research, this practice is of high importance since it is not always possible to summarize numerical outcomes competently. Moreover, the suitability of clinical significance in the aforementioned cases is higher. Therefore, this approach to the field of evidence-based research is relevant, provided that specific effects and symptoms are analyzed but not their ratio.
References
Page, P. (2014). Beyond statistical significance: Clinical interpretation of rehabilitation research literature. International Journal of Sports Physical Therapy, 9(5), 726-736.
Polit, D. F. (2017). Clinical significance in nursing research: A discussion and descriptive analysis. International Journal of Nursing Studies, 73, 17-23.
Ranganathan, P., Pramesh, C. S., & Buyse, M. (2015). Common pitfalls in statistical analysis: Clinical versus statistical significance. Perspectives in Clinical Research, 6(3), 169-170.