The p-value is a measure of statistical significance that is often abused by researchers. The p-value is used to determine whether a null hypothesis can be rejected. A p-value of less than 0.05 is often considered to be statistically significant, meaning that the null hypothesis can be rejected. However, the p-value does not give any information about the magnitude of the effect and it does not indicate whether the results are clinically significant. The p-value is also affected by the sample size, so results with a small sample size are more likely to be statistically significant than results with a large sample size.
There are several problems with using the p-value as a measure of statistical significance. First, the p-value does not give any information about the magnitude of the effect. Second, the p-value is affected by the sample size, so results with a small sample size are more likely to be statistically significant than results with a large sample size. Third, the p-value does not indicate whether the results are clinically significant. Finally, the p-value is often abused by researchers who cherry-pick results that are statistically significant and ignore results that are not statistically significant.