Reflection

The Understanding Risk and Ratio Reflection Session offers participants the chance to reflect on the key statistical concepts of risk, relative risk, and odds ratios introduced in the course.

We’ve explored key research concepts that help us interpret scientific findings in health studies. Measuring frequency (incidence and prevalence) tells us how common a disease is, while measuring association (relative risk and odds ratio) helps us understand the link between risk factors and health outcomes. These measures are essential for tracking disease trends and making informed public health decisions.

When evaluating research results, we must consider effect size, which measures the strength of a difference or relationship between groups. Standardising effect sizes allows fair comparisons across studies, ensuring that results are meaningful beyond just statistical calculations. A study’s power also plays a crucial role—it determines how likely the study is to detect a real effect. Larger sample sizes generally increase power, reducing the risk of errors and making conclusions more reliable.

However, statistical significance alone is not enough. A small difference, like a 2 mmHg reduction in blood pressure, may be statistically significant but not clinically significant if it doesn’t meaningfully improve health outcomes. This is why both statistical and clinical significance must be considered together when interpreting results. Large studies can detect tiny, statistically significant effects that may have little practical importance, leading to misleading conclusions if context is ignored.

Ultimately, research is about more than just numbers—it’s about understanding the bigger picture. By carefully analysing study results with these concepts in mind, we ensure that scientific evidence is applied effectively to improve patient care and public health.