Bad information is far more common than good on the Internet, especially in complex and often ambiguous fields such as medicine. This should not be a surprise to anyone -- while it takes a great deal of effort to assemble good information, bad information is far easier to put together.
As such, finding the good information -- via free services, anyway -- is often a matter of combing for a metaphorical needle in a haystack, and the information you find is often highly skewed in a variety of ways even when it is of decent quality.
I regularly read blogs maintained by doctors and researchers, for instance. While they provide news and often-educational commentary, their commentary on basic issues is usually provided on an ad hoc and incomplete manner as parts of explanations on other matters. This is fine if you already understand the basic issues involved, but if you're trying to educate yourself on issues surrounding the use of the P value in hypothesis testing, for instance, comments on what Study X did wrong will only take you so far.
This is particularly vexing when running a blog and attempting to provide references for the concepts in question. I try to write my articles in such a way that a naive reader can educate himself on the relevant issues with a minimum of fuss; as such, I often need a bit more than I can easily find in other blogs.
Because of this, it was an extremely pleasant surprise for me to find out that one of my favorite basic introductions to P values and the general nature of statistical hypothesis testing is available for free. I'd originally gotten access to it through my university, so I didn't realize at first, but this really has renewed my awareness of the free articles available on the Internet -- and the value of the available literature on how to interpret the literature.
In other words -- I'm happy about this, even if I'm far less so about the way my left knee's acting up. Joint instability is not fun.