This advice is insane. Except in specific settings (where a sensor may be misbehaving, where a survey respondent clearly just picked random choices) outliers are really just outlying values and should be kept in the analysis, or at most clipped / winsorized. When submitting to a scientific journal, admitting that outliers were removed without first inspecting why they are there can be enough for an instant rejection, and rightly so.
It's one reason median is preferred over mean, at the outset, as well as throwing out outliers just to see what things look like.