Science

Avoid “pre-publication” studies- these are reports of data implying conclusions, but have not been peer reviewed or screened for publication. These are often just thinly veiled press releases to generate headlines and stimulate investor interest.

Avoid meta-analyses- meta analyses have a high risk for bias, as they are a collection of studies, often cherry picked by someone with an agenda. The flaws of each individual study are masked when the aggregator states something like “in a review of 20 studies, x results was found x% of the time”.

Avoid “preliminary studies” or “preliminary data”- preliminary studies are often very small data sets that cannot be generalized to the larger population. Always look for the “n” of number of subjects. If the n= dozens, rather than hundreds, or preferably thousands of subjects, beware. If there no human subjects, be especially careful about drawing any conclusions from the study.