Friday, April 15, 2011

Four-part series on pain research and its problems

This is by News/Research UPDATES, a blog by Stewart B Leavitt.
I've read several posts at this blog. This 4-part series is particularly insightful, I think. Excerpts provided:
1. How to Make Practical Sense of Pain Research
"Most presentations of research today are overflowing with data and statistics that often seem to defy sensible interpretation. The old saying, "There are three kinds of lies: lies, damned lies, and statistics," has never seemed more pertinent than in this era dominated by computerized data analysis programs. These can crank out sophisticated statistics to make even misguided or ill-conceived research appear to be the latest and greatest discovery in pain management. So, learning to interpret the often mysterious and complex language of research is a challenging but vital task."
2.  Pain Research: All That Glitters is Not Gold
"Just because a pain research study is published does not mean it is accurate, unbiased, valid, or useful for any clinical or decision making purpose. The truth is that much pain-related research literature is simply not worth reading, and sifting out the golden nuggets of worthwhile research from fool’s gold can be a challenging task for any healthcare provider or patient."
3.  Validity, Reliability, & Bias in Pain Research
"Critics of medical research have proposed that many wrong, or at least unreliable and invalid, therapeutic answers are being generated due to biased studies that are poorly designed and use inappropriate analyses. The pain field is no exception, even though the underlying research may seek answers to important clinical questions that are of value. Understanding potential sources of bias in pain research is vital for assessing reliability and validity of the outcomes."
4.  Pain Research: Insignificance of “Significance”
"As described in preceding articles in this series [here] many experts have warned through the years that medical researchers’ love of statistics has spawned countless faulty findings. And, as Albert Einstein pointed out long ago, “Not everything that counts can be counted, and not everything that can be counted counts.” Along those same lines we would add, “Not all that is statistically significant is significant.” Understanding this is key to becoming a more critical consumer of pain research."

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