Statistical significance and clinical significance are two distinct concepts used to interpret research findings, particularly in the context of medical and clinical research. Here’s the difference between the two:

1. Statistical Significance:
   • Statistical significance refers to the likelihood that an observed result is not due to random chance but rather reflects a true effect or relationship in the population. In statistical terms, it indicates whether the results obtained in a study are unlikely to have occurred by random variability alone.
   • Statistical significance is typically assessed using hypothesis testing and is often represented by a p-value. A p-value below a predetermined threshold (e.g., 0.05) suggests that the observed result is statistically significant, meaning there is evidence to reject the null hypothesis in favor of the alternative hypothesis.
   • However, statistical significance does not necessarily imply practical importance or relevance to clinical practice. It only indicates the presence of an effect that is unlikely to have occurred by chance. For example, an intervention study that shows a statistically significant change in range of motion at the hip, may have actual changes that do not translate to improved performance and have minimal clinical importance.
2. Clinical Significance:
   • Clinical significance, on the other hand, relates to the practical importance or relevance of the observed effect or result in clinical practice or real-world settings. It focuses on whether the observed effect size is meaningful in terms of its impact on patient outcomes, treatment decisions, or healthcare practices.
   • Unlike statistical significance, which is primarily determined by statistical tests and p-values, clinical significance considers factors such as the magnitude of the effect, its clinical relevance, the potential benefits and harms, and the context of the study.
   • A result may be statistically significant but not clinically significant if the effect size is very small and unlikely to have a meaningful impact on patient care or health outcomes. Conversely, a result may be clinically significant even if it is not statistically significant, particularly if the sample size is small or the study lacks statistical power to detect the effect.

In summary, while statistical significance indicates the likelihood of an observed result being due to true effects rather than chance, clinical significance assesses whether these effects are meaningful and relevant in clinical practice. Both concepts are important in the interpretation of research findings, and it’s essential to consider both statistical and clinical significance when drawing conclusions from studies.