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Evidence-based research implies retrieving and analyzing objective data that is not based on researchers opinions or subjective vision but on numerical and impact-based findings. For that matter, the statistical and clinical significance of studies is essential to demonstrate the validity of results and their relevance to the clinical setting or academic world in general. Since both measures are important in research, they are not equally valuable to the clinical setting and treatment improvement options (Fleischmann & Vaughan, 2019).
Indeed, a study finding might have a high level of statistical significance, demonstrating that two variables are interdependent. Although such a relationship is statistically significant and true, it does not imply that the proved dependence will apply to the treatment of patients effectively. For example, if a study involving 200 individuals showed statistically significant results of medication intake, which shifted the recovery by only one day, it would not be clinically relevant (Lira & Rocha, 2019). Such clinical irrelevance is validated by the lack of specific treatment- and evidence-based ground for better patient outcomes (Fleischmann & Vaughan, 2019). Therefore, such a study might apply to the academic world to further research in the area but would not significantly change the currently used treatment and practice-based interventions.
Given the essential role of clinical significance in evidence-based practice research, researchers should properly analyze the goals of their studies to use relevant designs, variables, sample sizes, and other factors. One of the important elements is the properly asked research question that implies clinical relevance. For example, when conducting a clinical trial, which is considered one of the most effective study designs in the medical field, using a PICOT (Population, Intervention, Control, Outcome, and Time) model is recommended (Lira & Rocha, 2019). In such a manner, at the very stage of study planning, a researcher is capable of foreseeing the clinical significance of potential findings, which helps increase the viability of research results.
References
Fleischmann, M., & Vaughan, B. (2019). Commentary: Statistical significance and clinical significance-a call to consider patient reported outcome measures, effect size, confidence interval and minimal clinically important difference (MCID). Journal of Bodywork and Movement Therapies, 23(4), 690-694.
Lira, R. P. C., & Rocha, E. M. (2019). PICOT: Imprescriptible items in a clinical research question. Arquivos Brasileiros de Oftalmologia, 82(2), 1-1.
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