As a determined patient checking out conclusions of any medical research study, you will want to figure out whether the conclusions the study has drawn apply to you and your unique health situation. That’s why you should look at something called “P” values.
A “P” value, or probability value, is a term used by statisticians and in research to show whether the results of a study are due to an actual, significant difference in treatments or the difference is mostly likely due to some random factor. For example, let’s say a study showed that a group being treated with a particular drug had fewer symptoms compared to another group being treated with a different drug. In the summary of the results of a research study, it may be reported that drug A was better than drug B and give a P value for the results of less than (“<”) 0.05. This means that there is less than a 5 percent chance that you should dismiss the results showing that drug A was better than drug B and more than a 95 percent chance the results can be relied on. That's good news.
The lower the P value, the more unlikely that the results are due to a random factor that might not show up if the study were to be repeated. Thus, if the P value were <0.005, there would be less than 5/1000 (or 0.5 percent) chance that the results showing drug A was better than drug B are unreliable. That sounds even better, doesn't it?
The determined patient looks for a lower P value in studies because this means the conclusions are more likely to be correct. The controversy is how low the P value should be for a study to have value. By convention, it has been 0.05 but with the new call for a P value that is ten times lower, or 0.005, researchers are being pressured to make sure their studies are even more reliable than ever before.
