The sample size is crucial as it impacts the power of the study—the ability to detect an effect if one exists. A small sample size may lead to false negatives, while an excessively large sample size may be unnecessary and resource-intensive. Calculating the appropriate sample size involves statistical techniques that consider the expected prevalence of the condition, the desired confidence level, and the margin of error.